@cgreene since we don't have AppVeyor notifications linking directly to artifacts and GitHub Actions comments are still being explored (manubot/rootstock#322), we should stick your screenshots and instructions above somewhere permanent. They'll be very helpful for pull request reviewers.

Do we have / want a Wiki for this?

Originally posted by @agitter and @mprobson in #23 (comment)

Title: A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing

Please paste a link to the paper or a citation here:

Link: https://www.biorxiv.org/content/10.1101/2020.03.22.002386v2

What is the paper's DOI?

DOI: https://doi.org/10.1101/2020.03.22.002386

Is this paper primarily relevant to Background, Diagnostics, or Therapeutics? (OK if more than one)

Therapeutics

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• protein-protein interaction
• drug targets
• drug repurposing
• interactome

Which areas of expertise are particularly relevant to the paper (put an x in the brackets [x])?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Suggested questions to answer about each paper:

• What did they analyze?

  • 26 out of 29 known SARS-CoV-2 viral proteins were cloned, tagged, and expressed in human cells (HEK293T)
  • Protein-protein interactions between viral and human proteins were studied

• What methods did they use?

  • human proteins physically associated with SARS-CoV-2 viral proteins were identified using affinity-
    purification mass spectrometry (AP-MS)

• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?

  • SARS-CoV-2

• What is the main finding (or a few main takeaways)?

  • 332 total protein-protein interactions (PPIs) identified
  • 67 druggable human proteins identified, which are currently targeted by 69 FDA approved drugs
  • Pathways implicated: innate immune (interferon, NF-κB), Cullin 2 ubiquitin ligase complex
  • Many other interesting interactions to be analyzed

• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?

  • The SARS-CoV-2-human interactome contains wealth of information about both basic biology of the virus and possible drug targets

• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?
  N/A

Any comments or notes?

Twitter thread with other info: https://twitter.com/fraser_lab/status/1241929245812592641

Title(s):

1. Coronaviruses post-SARS: update on replication and pathogenesis (May 2009)
2. Coronavirus Pathogenesis (Nov 2011)
3. Origin and evolution of pathogenic coronaviruses (Dec 2018)

Please paste a link to the paper or a citation here:

https://www.nature.com/articles/nrmicro2147
https://www.sciencedirect.com/science/article/pii/B9780123858856000092?via%3Dihub
https://www.nature.com/articles/s41579-018-0118-9

What is the paper's DOI?

https://doi.org/10.1038/nrmicro2147
https://doi.org/10.1016/B978-0-12-385885-6.00009-2
https://doi.org/10.1038/s41579-018-0118-9

Is this paper primarily relevant to Background, Diagnostics, or Therapeutics? (OK if more than one)

Background

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

history, pathogenesis of related viruses

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?

Coronaviruses generally - SARS-CoV, MERS-CoV, SADS-CoV, etc.

• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?

• Advances (as of 2009) in our understanding of the mechanisms of coronavirus replication, interactions with the host immune response and disease pathogenesis.
• Identification of numerous novel coronaviruses and the propensity of this virus family to cross species barriers.

• Pathogenesis of murine coronavirus mouse hepatitis virus (MHV) and severe acute respiratory coronavirus (SARS-CoV) and the several reverse genetics systems that made much of these studies possible.
• Functions of coronavirus proteins, structural, enzymatic, and accessory, with an emphasis on roles in pathogenesis.

• Current knowledge (Dec 2018) on the origin and evolution of SARS-CoV and MERS-CoV and their receptor usage.

• The diversity and potential of spillover of bat-borne coronaviruses, as evidenced by the recent spillover of swine acute diarrhoea syndrome coronavirus (SADS-CoV) to pigs.

• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

In filing #56 I noticed a few issues with the templates that made things a bit more confusing. I'll attempt to take those on now.

Suggested by @vagarwal87

Title: The landscape of lung bronchoalveolar immune cells in COVID-19 revealed by single-cell RNA sequencing

General Information

Please paste a link to the paper or a citation here:

Link: https://www.medrxiv.org/content/10.1101/2020.02.23.20026690v1

What is the paper's Manubot-style citation?

Citation: @doi:10.1101/2020.02.23.20026690

Is this paper primarily relevant to Background or Pathogesis?

• Background
• Pathogenesis
• Methods

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• COVID-19
• immune microenvironment
• lung
• single-cell RNA sequence
• acute respiratory distress syndrome
• monocyte-derived FCN1+ macrophages
• cytokine storm
• CD8+ T cells

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other: omics

Summary

If you would like to submit a summary of the paper, please copy and paste the following into a comment.

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

Title: COVID-19 Treatment and Vaccine Tracker

Please paste a link to the paper or a citation here:

Link: https://milkeninstitute.org/sites/default/files/2020-03/Covid19%20Tracker%20NEW3-24-20-REVISED.pdf

What is the paper's DOI?

DOI: N/A

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• clinical trials
• treatments
• vaccines
• FDA approval status

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

This is not a full paper but rather a spreadsheet from the Milken Institute listing COVID-19 treatments and vaccines in development. It provides links to original sources.

Study question(s) being investigated:

How many/what drugs/combinations are being considered?

What are the main hypotheses being tested?

Study population:

What is the model system (e.g., human study, animal model, cell line study)?

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

• number treated with treatment A
• number treated with treatment B

For human studies:

What countries/regions are considered?

What is the age range, gender, other relevant characteristics?

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

What other specific inclusion-exclusion criteria are considered?

For example, do the investigators exclude patients with diagnosed neoplasms or patients over/under a certain age?

Treatment assignment:

How are treatments assigned?

For example, is it an interventional or an observational study?

Is the study randomized?

A study can be interventional but not randomized (e.g., a phase I or II clinical trial is interventional but often not randomized).

Provide other relevant details about the design.

This includes possible treatment stratification (e.g., within litters for animal studies, within hospitals for human studies), possible confounding variables (e.g., having a large age range of individuals), possible risks of bias and how they are addressed (e.g., is there masking in a clinical trial? how are individuals chosen in an observational study?).

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

For example: Is the outcome assessed by a clinician or is it self-reported?
Is the outcome based on viral load or a functional measurement (e.g., respiratory function, discharge from hospital)?
What method is used to measure the outcome?
How long after a treatment is the outcome measured?

Are outcome measurements complete?

For example, are there individuals lost to follow up?

Are outcome measurements subject to various kinds of bias?

For example, a lack of masking in randomized clinical trials.

Statistical Methods Assessment:

What methods are used for inference?

For example, logistic regression, nonparametric methods.

Are the methods appropriate for the study?

For example, are clustered data treated independently or are clusters adjusted for, such as different hospitals or litters?

Are adjustments made for possible confounders?

For example, adjustment for age, sex, or comorbidities.

Results Summary:

What is the estimated association?

For example, is it an estimated odds ratio, a median difference in detected cases, etc?

What measures of confidence or statistical significance are provided?

For example, confidence intervals, p-values, and/or Bayes factors.

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

For example, with a well-performed animal study or randomized trial it is often possible to infer causality.
If is an observational study, does it match up with some of the Bradford Hill criteria? https://www.edwardtufte.com/tufte/hill https://en.wikipedia.org/wiki/Bradford_Hill_criteria

Are there identified side effects or interactions with other drugs?

For example, is the treatment known to cause liver damage or to not be prescribed for individuals with certain comorbities?

Are there specific subgroups with different findings?

For example, do individuals with a specific baseline seem to do particularly well? Be particularly cautious with respect to multiple testing here.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

Is the model system appropriate? Is there evidence from past use that it's highly-relevant to therapeutic design in this context?

If it is a human study, what characteristics of the study population may support/limit extrapolation?

• Can results extrapolate easily to other similar groups? (e.g., same country, similar age groups)
• What would happen if conditions are extended in terms of dose or duration?
• Can results be extrapolated to other populations or in very different settings? (e.g., different age group, primary care setting vs emergency department etc)

Summary of reliability

1-2 sentences on concluding remarks, including summary of strengths, weaknesses, limitations.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe How many/what drugs/combinations are being considered
• Describe the model system
• What is the sample size?
• What countries/regions are considered
• What is the age range, gender, other relevant characteristics
• Describe study setting
• Describe other specific inclusion-exclusion criteria
• Describe how treatments are assigned
• Describe randomization (or not) and other relavent details about the design
• Describe the outcome that is assessed and whether it is appropriate.
• Describe whether the outcome measurements are complete
• Are outcome measurements subject to various kinds of bias?
• Describe methods used for inference
• Describe whether the methods are appropriate for the study
• Are adjustments made for possible confounders?
• Describe the estimated association
• What measures of confidence or statistical significance are provided?
• Describe whether a causal interpretation can be made
• Are there identified side effects or interactions with other drugs?
• Are there specific subgroups with different findings?
• If the study is an animal study, which animal and how relevant is that model?
• If it is a human study, what characteristics of the study population may support/limit extrapolation?
• Summary of reliability

Title: Research and Development on Therapeutic Agents and Vaccines for COVID-19 and Related Human Coronavirus Diseases

Please paste a link to the paper or a citation here:

Link: https://pubs.acs.org/doi/10.1021/acscentsci.0c00272

What is the paper's Manubot-style citation?

Citation: doi:10.1021/acscentsci.0c00272

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• review
• patents
• therapeutic classification and overview

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

This review uses the CAS content collection to systematically search for treatments for related viruses, many of which are being investigated for repurposing against SARS-CoV-2. One benefit for our review could be statistics about the abundance of different classes of treatments.

Study question(s) being investigated:

How many/what drugs/combinations are being considered?

Many types of treatments and vaccines are reviewed

What are the main hypotheses being tested?

Review article

Study population:

What is the model system (e.g., human study, animal model, cell line study)?

N/A

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

• number treated with treatment A
• number treated with treatment B

For human studies:

What countries/regions are considered?

What is the age range, gender, other relevant characteristics?

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

What other specific inclusion-exclusion criteria are considered?

For example, do the investigators exclude patients with diagnosed neoplasms or patients over/under a certain age?

Treatment assignment:

How are treatments assigned?

For example, is it an interventional or an observational study?

Is the study randomized?

A study can be interventional but not randomized (e.g., a phase I or II clinical trial is interventional but often not randomized).

Provide other relevant details about the design.

This includes possible treatment stratification (e.g., within litters for animal studies, within hospitals for human studies), possible confounding variables (e.g., having a large age range of individuals), possible risks of bias and how they are addressed (e.g., is there masking in a clinical trial? how are individuals chosen in an observational study?).

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

For example: Is the outcome assessed by a clinician or is it self-reported?
Is the outcome based on viral load or a functional measurement (e.g., respiratory function, discharge from hospital)?
What method is used to measure the outcome?
How long after a treatment is the outcome measured?

Are outcome measurements complete?

For example, are there individuals lost to follow up?

Are outcome measurements subject to various kinds of bias?

For example, a lack of masking in randomized clinical trials.

Statistical Methods Assessment:

What methods are used for inference?

For example, logistic regression, nonparametric methods.

Are the methods appropriate for the study?

For example, are clustered data treated independently or are clusters adjusted for, such as different hospitals or litters?

Are adjustments made for possible confounders?

For example, adjustment for age, sex, or comorbidities.

Results Summary:

What is the estimated association?

For example, is it an estimated odds ratio, a median difference in detected cases, etc?

What measures of confidence or statistical significance are provided?

For example, confidence intervals, p-values, and/or Bayes factors.

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

For example, with a well-performed animal study or randomized trial it is often possible to infer causality.
If is an observational study, does it match up with some of the Bradford Hill criteria? https://www.edwardtufte.com/tufte/hill https://en.wikipedia.org/wiki/Bradford_Hill_criteria

Are there identified side effects or interactions with other drugs?

For example, is the treatment known to cause liver damage or to not be prescribed for individuals with certain comorbities?

Are there specific subgroups with different findings?

For example, do individuals with a specific baseline seem to do particularly well? Be particularly cautious with respect to multiple testing here.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

Is the model system appropriate? Is there evidence from past use that it's highly-relevant to therapeutic design in this context?

If it is a human study, what characteristics of the study population may support/limit extrapolation?

• Can results extrapolate easily to other similar groups? (e.g., same country, similar age groups)
• What would happen if conditions are extended in terms of dose or duration?
• Can results be extrapolated to other populations or in very different settings? (e.g., different age group, primary care setting vs emergency department etc)

Summary of reliability

1-2 sentences on concluding remarks, including summary of strengths, weaknesses, limitations.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe How many/what drugs/combinations are being considered
• Describe the model system
• What is the sample size?
• What countries/regions are considered
• What is the age range, gender, other relevant characteristics
• Describe study setting
• Describe other specific inclusion-exclusion criteria
• Describe how treatments are assigned
• Describe randomization (or not) and other relavent details about the design
• Describe the outcome that is assessed and whether it is appropriate.
• Describe whether the outcome measurements are complete
• Are outcome measurements subject to various kinds of bias?
• Describe methods used for inference
• Describe whether the methods are appropriate for the study
• Are adjustments made for possible confounders?
• Describe the estimated association
• What measures of confidence or statistical significance are provided?
• Describe whether a causal interpretation can be made
• Are there identified side effects or interactions with other drugs?
• Are there specific subgroups with different findings?
• If the study is an animal study, which animal and how relevant is that model?
• If it is a human study, what characteristics of the study population may support/limit extrapolation?
• Summary of reliability

For people interested in joining the UPenn COVID-19 journal club via bluejeans. Hosted by the Wherry lab. https://bluejeans.com/2359300514?src=join_info
This Thursday (March 26 at 12pm EST)

Title: Please edit the title to add the name of the paper after the colon
A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing

Please paste a link to the paper or a citation here:

Link: https://www.biorxiv.org/content/10.1101/2020.03.22.002386v1

What is the paper's Manubot-style citation?

Citation: doi:10.1101/2020.03.22.002386

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• keyword 1 (replace me, copy and paste more than three if needed)
• keyword 2 (replace me, copy and paste more than three if needed)
• keyword 3 (replace me, copy and paste more than three if needed)

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

The authors cloned, tagged and expressed 26 of the 29 viral proteins in human cells
Using affinity-purification mass spectrometry the authors have identified the 332 high confidence SARS-CoV-2-human protein-protein interactions between the pathogen and human proteins
66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs are identified
SARS-CoV-2 interacts with multiple innate immune pathways
Cellular proteins implicated in innate immune signaling that are targeted by several SARS-CoV-2 viral proteins

Study question(s) being investigated:

How many/what drugs/combinations are being considered?

Large scale interactome analysis

What are the main hypotheses being tested?

Whether there are high confidence interactions between the SARS-CoV-2 and human proteins, if yes, are those potential drug targets?

Study population:

What is the model system (e.g., human study, animal model, cell line study)?

HEK293T cells

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

• number treated with treatment A
• number treated with treatment B

For human studies:

What countries/regions are considered?

What is the age range, gender, other relevant characteristics?

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

What other specific inclusion-exclusion criteria are considered?

For example, do the investigators exclude patients with diagnosed neoplasms or patients over/under a certain age?

Treatment assignment:

How are treatments assigned?

For example, is it an interventional or an observational study?

Is the study randomized?

A study can be interventional but not randomized (e.g., a phase I or II clinical trial is interventional but often not randomized).

Provide other relevant details about the design.

This includes possible treatment stratification (e.g., within litters for animal studies, within hospitals for human studies), possible confounding variables (e.g., having a large age range of individuals), possible risks of bias and how they are addressed (e.g., is there masking in a clinical trial? how are individuals chosen in an observational study?).

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

For example: Is the outcome assessed by a clinician or is it self-reported?
Is the outcome based on viral load or a functional measurement (e.g., respiratory function, discharge from hospital)?
What method is used to measure the outcome?
How long after a treatment is the outcome measured?

Are outcome measurements complete?

For example, are there individuals lost to follow up?

Are outcome measurements subject to various kinds of bias?

For example, a lack of masking in randomized clinical trials.

Statistical Methods Assessment:

What methods are used for inference?

For example, logistic regression, nonparametric methods.

Are the methods appropriate for the study?

For example, are clustered data treated independently or are clusters adjusted for, such as different hospitals or litters?

Are adjustments made for possible confounders?

For example, adjustment for age, sex, or comorbidities.

Results Summary:

What is the estimated association?

For example, is it an estimated odds ratio, a median difference in detected cases, etc?

What measures of confidence or statistical significance are provided?

For example, confidence intervals, p-values, and/or Bayes factors.

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

For example, with a well-performed animal study or randomized trial it is often possible to infer causality.
If is an observational study, does it match up with some of the Bradford Hill criteria? https://www.edwardtufte.com/tufte/hill https://en.wikipedia.org/wiki/Bradford_Hill_criteria

Are there identified side effects or interactions with other drugs?

For example, is the treatment known to cause liver damage or to not be prescribed for individuals with certain comorbities?

Are there specific subgroups with different findings?

For example, do individuals with a specific baseline seem to do particularly well? Be particularly cautious with respect to multiple testing here.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

Is the model system appropriate? Is there evidence from past use that it's highly-relevant to therapeutic design in this context?

If it is a human study, what characteristics of the study population may support/limit extrapolation?

• Can results extrapolate easily to other similar groups? (e.g., same country, similar age groups)
• What would happen if conditions are extended in terms of dose or duration?
• Can results be extrapolated to other populations or in very different settings? (e.g., different age group, primary care setting vs emergency department etc)

Summary of reliability

1-2 sentences on concluding remarks, including summary of strengths, weaknesses, limitations.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe How many/what drugs/combinations are being considered
• Describe the model system
• What is the sample size?
• What countries/regions are considered
• What is the age range, gender, other relevant characteristics
• Describe study setting
• Describe other specific inclusion-exclusion criteria
• Describe how treatments are assigned
• Describe randomization (or not) and other relavent details about the design
• Describe the outcome that is assessed and whether it is appropriate.
• Describe whether the outcome measurements are complete
• Are outcome measurements subject to various kinds of bias?
• Describe methods used for inference
• Describe whether the methods are appropriate for the study
• Are adjustments made for possible confounders?
• Describe the estimated association
• What measures of confidence or statistical significance are provided?
• Describe whether a causal interpretation can be made
• Are there identified side effects or interactions with other drugs?
• Are there specific subgroups with different findings?
• If the study is an animal study, which animal and how relevant is that model?
• If it is a human study, what characteristics of the study population may support/limit extrapolation?
• Summary of reliability

A few groups are discussing and reviewing published manuscripts and preprints in various forums. These could be candidate contributors to contact:

• SinaiImmunol Twitter thread
• DeepChem Twitter thread and forum

Feel free to edit this post if you want to make one list.

@mprobson suggested offline that feature branching has worked well on some of his large-scale collaborations.

Would you be OK with adopting feature branching as our standardized workflow? (When possible, obviously!)

I usually only get to work on my PRs piecemeal during the day, and end up having to deal with merge issues by the time I try to push. It sounds like rebasing each merge might help make this go a little more smoothly.

Currently only the four of us have write access so it shouldn't affect many people if we switch.

Title: Potential roles of social distancing in mitigating the spread of coronavirus disease 2019 (COVID-19) in South Korea

General Information

Link: https://github.com/parksw3/Korea-analysis/blob/master/v1/korea.pdf
Data & code link: https://github.com/parksw3/Korea-analysis

What is the paper's Manubot-style citation?

Citation: tag:Park2020_distancing

Is this paper primarily relevant to Background or Pathogenesis?

• Background
• Pathogenesis
• Methods

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• population dynamics
• transmission
• social distancing
• contact tracing
• reproductive number
• time-dependent reproductive number

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other:

Summary

If you would like to submit a summary of the paper, please copy and paste the following into a comment.

Suggested questions to answer about each paper:

• What did they analyze?

  • Analyzed epidemiological data (daily cases) from January 20 - March 16, 2020, and transport data (Metro travel) in South Korea between 2017 - 2020.
  • Studied the differences in epidemiological dynamics between Daegu (central to the SK outbreak) and Seoul.
  • Inferred the time-dependent reproductive number (R_t) in each location.

• What methods did they use?

  • Inferred time-dependent backward onset-to-confirmation delay distributions from daily case data using negative binomial regression.
  • Used weakly informative priors for fixed effects ~ Normal(0,2)
  • Incubation period modeled by a Gamma dist, generation time by Negative Binomial

• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?

  • Epidemiology of COVID-19

• What is the main finding (or a few main takeaways)?

  • social distancing and contact tracing in Daegu were effective (at least in part) at reducing the number of new cases
  • Suggests that the COVID-19 epidemic can be suppressed with less extreme measures than those taken by China
  • R_t in Daegu is now well below 1, however in Seoul is still above 1, this could lead to secondary outbreaks
  • Region-specific analysis is important: "recent decrease in the number of reported cases in South Korea is driven by the sharp decrease in Daegu. Our analysis reveals that the epidemic may still persist in other regions, including Seoul and Gyeonggi-do"

• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?

  • Tells us what the epidemiological dynamics of the disease are early, and lllater during an outbreak when social distancing measures are in place
  • Highlights the importance of focusing on region specific dynamics

• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

  • Choice of priors on the incubation period and generation time, is there support for these?

Any comments or notes?

Good supplemental data to #69 on dynamics of infection.

Title: A new coronavirus associated with human respiratory disease in China

General Information

Please paste a link to the paper or a citation here:

Link: https://www.nature.com/articles/s41586-020-2008-3

What is the paper's Manubot-style citation?

Citation: [@doi:10.1038/s41586-020-2008-3]

Is this paper primarily relevant to Background or Pathogesis?

• Background
• Pathogenesis
• Methods

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• metagenomics
• phylogenetics
• zoonotic disease
• SARS-CoV-2

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other: omics

Summary

If you would like to submit a summary of the paper, please copy and paste the following into a comment.

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

Title: JUST A TEST virology IN VITRO

Please paste a link to the paper or a citation here:

JUST A TEST

What is the paper's DOI?

Is this paper primarily relevant to Background, Diagnostics, or Therapeutics? (OK if more than one)

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

Edited to help testing. Another edit to test. Yet another test

Title: Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1

General Information

Please paste a link to the paper or a citation here:

Link: https://www.nejm.org/doi/full/10.1056/NEJMc2004973

What is the paper's Manubot-style citation?

Citation: @doi:10.1056/NEJMc2004973

Is this paper primarily relevant to Background or Pathogesis?

• Background
• Pathogenesis
• Methods

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• aerosol and surface stability
• viability

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other:

Summary

The authors tested the stability of SARS-CoV-1 and SARS-CoV-2 on different surfaces.

Suggested questions to answer about each paper:

• What did they analyze?

Viral stability in aerosol and on different environmental surfaces.

• What methods did they use?

Virus surface deposition, and re-hydration/recovery using DMEM
Bayesean regression

• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?

SARS-CoV-2 and SARS-CoV-1

• What is the main finding (or a few main takeaways)?

Virus stability on different surfaces is similar between SARS-CoV-2 and SARS-CoV-1 in the experimental conditions.

SARS-CoV-2 remains viable in aerosols for at least 3 hours with a median half-life between 1.1 and 1.2 hours

SARS-CoV-2 is more stable on plastic and stainless steel than on copper and cardboard.

• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?

The paper provides background information potentially relevant to transmission, epidemiology and prevention.

• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

These results were obtained in experimental conditions; it is unclear how they translate to real-world environmental conditions, particularly in relation to viral load necessary for infection.

Any comments or notes?

Title: Please edit the title to add the name of the paper after the colon

Please paste a link to the paper or a citation here: Recombination and lineage-specific mutations led to the emergence of SARS-CoV-2

Link: https://www.biorxiv.org/content/10.1101/2020.02.10.942748v2.full.pdf+html

What is the paper's Manubot-style citation?

Citation: @doi:10.1101/2020.02.10.942748

Is this paper primarily relevant to Background, Diagnostics, or Therapeutics? (OK if more than one)

Background

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• Genomic evolution
• Recombination
• Zoonotic virus

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Suggested questions to answer about each paper:

• What did they analyze?
  Genome sequences from SARS-CoV-2, its closest animal-infecting relative (RaTG13, accession number MN996532), genome sequences from human SARS-CoV and bat SARS-like CoV.
• What methods did they use?
  Phylogenetic and recombination analysis methods
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
  Yes.
• What is the main finding (or a few main takeaways)?
  The authors show that recombination in betacoronaviruses, including human-infecting viruses like SARS-CoV and MERS-CoV, impact the Receptor Binding Domain (RBD) in the Spike gene. A recombination event >11 years ago resulted in SARS-CoV and SARS-CoV-2 sharing a similar genotype in RBD, including two polymorphisms followed by more mutations in the gene.
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
  SARS-CoV-2 ancestors in bats first acquired genetic characteristics of SARS-CoV by incorporation of a SARS-like RBD through recombination before 2009, with subsequent acquisition of unique amino acid changing mutations.
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?
  The methodology used is quite straightforward, but put together with a commentary published today in Cell (https://www.cell.com/cell/fulltext/S0092-8674(20)30328-7), it can add to our understanding the origins of this virus.

Any comments or notes?

Is your feature request related to a problem? Please describe.
Given how rapidly information is being disseminated on general public-facing platforms and this pandemic being a global community concern, I think this review should have some aspects of general public-facing information. Reading through the albeit limited discussion thus far, I do not think such public-facing elements are in the plan.

Describe the solution you'd like
The review certainly cannot be pulled out of academic and toward losing the nuance of the issues at hand so I propose a "checkpointing" solution for any public or media-crew readers. I foresee this being sort of "bottom line" elements in highlighted boxes (supported in Manubot?), as well as asides for addressing any public misinformation. We cannot allow this review to be pulled so far toward obscure academic hair splitting that such a publicly accessible resource which will evolve as we learn more is impenetrable to a non-academic reader.

Describe alternatives you've considered
Mentioned above I see the solution as highlighted boxes in the manuscript, but could also foresee a section of public questions with brief answers starting the review. For example:

• Is hydroxychloroquine a miracle cure for coronavirus (1)? No (2), there have been some preliminary studies (3), but...(4)

This is intentionally structured as a clear question (1), clear answer (2), why the question is on peoples' minds (3), then what the literature tells us as academics (4).

I would not consider a separate document as there is not way to ensure the two are consistent and current. One document with public and academic elements is the solution, in my opinion. How these elements are presented and laid out on the page is the concern.

Additional context
My motivation for this feature request is that this review will be easily accessible to all and can be leveraged to combat misinformation if only we allow room for doing so.

Title: A human monoclonal antibody blocking SARS-CoV-2 infection

Please paste a link to the paper or a citation here: https://www.biorxiv.org/content/10.1101/2020.03.11.987958v1.full.pdf

https://doi.org/10.1101/2020.03.11.987958

Is this paper primarily relevant to Background, Diagnostics, or Therapeutics? (OK if more than one) Relevant to Therapeutics and Diagnostics

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

Neutralizing antibodies,
SARS-CoV-2 glycoproteins,
Receptor-binding-interference,

Suggested questions to answer about each paper:

• What did they analyze?

Antibody binding to SARS-CoV-2 surface glycoprotein

Inhibition of infection by SARS-CoV-2 using the neutralizing antibody

Binding affinities for various spike protein domains

• What methods did they use?
  Immunofluorescence,
  Flow-cytometry,
  Neutralization assays,
  ELIZA,
  Hybridoma antibody generation,

• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
  Yes

• What is the main finding (or a few main takeaways)?

Generation of a humanized monoclonal antibody against SARS-CoV-2

Mechanism of action unknown but distinct from ACE2 receptor binding interference

The antibody may be useful for diagnostics (antigen detection) and therapeutics

• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
  No approved targeted therapy available to date,
  Background about the emergence of the disease,
  Structural biology of the spike proteins,

• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Only in vitro, no in vivo validation

Any comments or notes?

Neutralizing concentration in vitro is relatively high

Title: Please edit the title to add the name of the paper after the colon

Please paste a link to the paper or a citation here:

Link:
https://doi.org/10.1016/S0140-6736(20)30251-8

What is the paper's Manubot-style citation?

Citation: [@doi:10/ggjr43]

Is this paper primarily relevant to Background or Pathogenesis?

• Background
• Pathogenesis

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• viral genome
• 2019-nCov
• SARS-CoV-2
• sequencing

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other: genomics

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

Recommended by @vagarwal87

Title: Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)

General Information

Please paste a link to the paper or a citation here:

Link: https://science.sciencemag.org/content/early/2020/03/24/science.abb3221

What is the paper's Manubot-style citation?

Citation: [@doi:10.1126/science.abb3221]

Is this paper primarily relevant to Background or Pathogenesis?

• Background
• Pathogenesis
• Methods

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• epidemiological modeling
• undocumented infections
• contagiousness
• SARS-CoV-2
• mobility data
• geographic spread

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other:

Summary

If you would like to submit a summary of the paper, please copy and paste the following into a comment.

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

Currently, clicking on the gear next to "Reviewers" or "Assignees" on a PR only allows for the selection of users from within certain groups (my guess is manubot and GreeneLab, possibly AlexsLemonadeStand as well).

This is also the case for tagging users within comments on PRs or in issues they didn't initiate. Users also can't add reviewers etc. to their own PRs. They can comment on issues. (Thanks to @mprobson for testing).

Looking at the settings, it seems like read permissions should be public, which to me implies that anyone can comment, but that doesn't seem to be the case. I explicitly gave @mprobson read permissions and then I could tag him here and assign him to the issue.

Is there a way to open this up so that contributors in general can comment on/be tagged in PRs? Or do we just need to add them individually?

Title: A serological assay to detect SARS-CoV-2 seroconversion in humans

Please paste a link to the paper or a citation here:

Link: https://www.medrxiv.org/content/10.1101/2020.03.17.20037713v1

What is the paper's DOI?

DOI: https://doi.org/10.1101/2020.03.17.20037713

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• Rapid Testing
• Serological Assay
• ELISA

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

The study describes a method for the detection of seroconversion upon SARS-CoV-2 infection based on the reactivity of the immunogenic spike protein (S protein) of the virus. The ELISA based assay is both sensitive and specific and capable for detecting COVID19 seroconverters, through plasma/serum samples, as early as 3 days post symptom onset.

Study question(s) being investigated:

What type of testing scenario is being considered?

It is a serological assay capable of detecting the generation of SARS-CoV-2 antibodies after initial viral infection. Detection of seroconversion is important for three main reasons: it allows for the study of the immune response to SARS-CoV-2 in a dynamic fashion, it allows to determine which individuals have already been exposed to the virus and have mounted an immune response (and therefore are non-contagious or they could serve as donors for the generation of convalescent serum therapeutics), and it allows to determine the precise rate of infection in a given region, providing better estimates of the true infection fatality rate.

Study population:

Human subjects

What is the model system (e.g., human study, animal model, cell line study)?

Human serum samples

What is the sample size?

• 59 banked human serum samples with previous exposure to viral infection (to generate an immune background as a control for the assay)

• 4 plasma/serum samples from three COVID-19 patients

What is the "pre-test" probability of disease in the study population (i.e., what is the anticipated prevalence of the disease?)

For human studies, the following are related to the pre-test probability:

What countries/regions are considered?

Control serum samples were acquired from individuals living in the US prior to the dissemination of COVID-19 within the US

COVID-19 samples were provided by the University of Melbourne and the University of Helsinki (no further information is provided from these subjects)

What is the age range, gender, other relevant characteristics?

For the control subjects: Ages ranged from 20-60+. Self-reported ethnicities include: Caucasian, Asian, African American, and Hispanic.

Previous viral exposure of the control subjects include: hantavirus, dengue virus, coronavirus NL63, and others.

COVID-19 Samples: Samples were obtained 2 and 6 days post symptom onset (for subject 3), 4 days post symptom onset (for subject 2), and 20 days post symptom onset (for subject 1)

What is the setting of the study (e.g., random sample of school children, retirement communities, etc.)?

What other specific inclusion-exclusion criteria are considered?

Reference test:

What reference test is considered as a "gold standard" comparator for the test under investigation?

Test assignment:

How are the new and reference tests assigned?

Examples of assignment could include: Recruited individuals have initially undergone neither the new nor the reference test; individuals tested as positive or negative by the reference test undergo the new test; individuals who have undertaken the new test are assessed by the standard test.

Are there any other relevant details about the study design?

Depending on how individuals are chosen, the test may be biasing towards more sick or less sick individuals or very clear-cut positive/negative cases.
Any factors that would influence this bias should be included here.

Test conduct:

How were tests performed?

Describe technical details of assays used, when measurements were taken and by whom, etc. for both the new and standard tests.

Test Assessment

Describe how individuals are classified as positive or negative, e.g. if a threshold is used.

Is there evidence that the test is precise/reproducible when repeated more than once?

Are measurements complete?

For example: Do some participants undergo just one test (the new or the reference test)?
Are there individuals with inconclusive results?

Results summary:

What are the estimated sensitivity, specificity, positive predictive value (PPV), and negative predicted value (NPV)?

Note that the PPV and NPV represent "post-test" probabilities of disease and are generally more meaningful than sensitivity and specificity.
Sometimes the post-test odds will be given instead.

What are the confidence bounds around these intervals?

Interpretation of results for study population:

How good is the test at ruling in or ruling out a disease based on the post-test probabilities?

Are there identified side affects of the test?

Is patient adherence to the test likely to be an issue?

Extrapolation of conclusions to other groups of individuals

How well is the test likely to work in populations with different pretest odds?

For example, if the prevalence is lower, then the PPV will also be lower, but the NPV will be higher.

How costly is the test?

How difficult is it to perform the test in different settings?

Could the test be combined with other existing tests?

Summary of reliability

1-2 sentences on concluding remarks, including summary of strengths, weaknesses, limitations.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe testing scenario
• Describe model system
• Sample size
• Describe prevalence of disease
• Describe countries/regions are considered
• Describe age range, gender, other relevant characteristics
• Describe setting of the study
• Describe other specific inclusion-exclusion criteria
• Describe "gold standard"
• Describe how the new and reference tests assigned
• Describe other relevant details about the study design
• Describe how the tests were performed
• Describe how individuals are classified as positive or negative
• Describe if test is precise/reproducible
• Describe whether measurements are complete
• What are the estimated sensitivity, specificity, positive predictive value (PPV), and negative predicted value (NPV)?
• What are the confidence bounds around these intervals?
• Describe post-test probabilities
• Describe side affects of the test
• Describe patient adherence
• Describe how it will extrapolate
• How costly is the test?
• How difficult is it to perform the test in different settings?
• Could the test be combined with other existing tests?
• Summary of reliability

Title: The proximal origin of SARS-CoV-2

Please paste a link to the paper or a citation here:

https://www.nature.com/articles/s41591-020-0820-9

What is the paper's DOI?

10.1038/s41591-020-0820-9

Is this paper primarily relevant to Background, Diagnostics, or Therapeutics? (OK if more than one)

Background

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

origin, evolution, genomic features

Suggested questions to answer about each paper:

• What did they analyze?

The authors describe the genomic features of SARS-CoV-2, in particular the receptor binding domain and the polybasic cleavage site. They relate these to other known coronaviruses such as SARS-CoV, and using these comparisons provide evidence for and against several putative origins of SARS-CoV-2.

• What methods did they use?

Comparative genomics

• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?

SARS-CoV-2 in relation to other coronaviruses

• What is the main finding (or a few main takeaways)?

It's highly likely that SARS-CoV-2 evolved naturally.

• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?

SARS-CoV-2 is unlikely to have a laboratory origin (either designed, genetically altered, or escaped). Instead it's highly likely to have evolved naturally in an animal host, however current evidence cannot discriminate an origin of the current form before or after zoonotic transfer to humans. It's genomic features highly resemble known coronaviruses present in bats (overall sequence similarity) and pangolins (receptor binding site).

• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

No

Any comments or notes?

Many open source software projects have a dedicated chatroom to discuss their project, welcome newcomers, and provide rapid feedback. Might be something to consider in this context as well as a place for people to quickly ask questions, get help, and contribute without directly engaging with GitHub.

Some Examples:

• Gitter
• Slack
• MS Teams
• IRC
• Discord

Pros:

• Real time feedback
• Helpful space for novices intimidated by GitHub and worried about making mistakes
• Rapid discussion between all interested parties in a centralized hub as opposed to email, issues, PRs, SMS, Slacks, etc.

Some potential downsides:

• Fractures discussion between several spaces (as opposed to concentrating discussion here)
• Potentially adds yet another service novices must sign up for (Gitter uses Twitter/Github so this wouldn't be a problem)
• Could obscure some conversations that happen in private channels (yet those might already be happening anyway and some projects, i.e. Gitter, are public be default)
• More management overhead for maintainers, e.g. moving messages into issues (I am happy to help with this)

I am happy to elaborate on the pros/cons of each and/or set up the service if that'd be helpful, just let me know!

Title: Early dynamics of transmission and control of COVID-19: a mathematical modelling study

Please paste a link to the paper or a citation here:

Link: https://www.sciencedirect.com/science/article/pii/S1473309920301444?via%3Dihub
Link to code: https://github.com/adamkucharski/2020-ncov/

What is the paper's DOI?

DOI: 10.1016/S1473-3099(20)30144-4

Is this paper primarily relevant to Background, Diagnostics, or Therapeutics? (OK if more than one)

Background

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• mathematical modeling
• population dynamics
• reproductive number
• R0
• transmission
• uncertainty quantification
• outbreak risk

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Suggested questions to answer about each paper:

• What did they analyze?

  • Analyzed four datasets (two within China, two international), using an SEIR model to predict R0, and variability of transmission in these regions between Dec 2019 - Feb 2020.

• What methods did they use?

  • Stochastic dynamical SEIR model (doi:10.1093/biostatistics/kxs052)
  • Sequential Monte Carlo for parameter inference

• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?

  • SARS-CoV-2, transmission, with reference to SARS-CoV, MERS-CoV

• What is the main finding (or a few main takeaways)?

  • In Wuhan, R0 in early-mid Jan ranged from 1.6 - 2.3, in late Jan, after restrictions had been in place for approx 2 weeks, R0 dropped to around 1.05
  • Based on median R0 in Jan, probability of a single individual exporting virus causing a large outbreak is 17-25% assuming MERS-like or SARS-like transmission; probability of a large outbreak occurring after ≥4 infections at a new location is greater than 50%

• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?

  • Provides info on the dynamics and speed of tranmission
  • Estimates of R0
  • Provides model & inference framework that can be used with new data

• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

  • As authors note, several parameters (e.g. latent period = incubation period) have been chosen despite uncertainty, needs further sensitivity analysis

Any comments or notes?

Hi all,

So excited that you are starting this initiative and very grateful to be involved! I was involved in a systematic review a couple years ago. Based on that experience, I have some thoughts/questions outlined below.

1. Centralized database. In order to synthesize the data we garner from the literature, wouldn't it be helpful to have information on each paper stored in a data format that is able to be searched and sorted? Is it possible to make a collaborative excel sheet on GitHub? That way we could list the paper information, name of the individual reviewing, whether it contains information relevant to diagnosis/therapeutics/other, the area of study (virology vs. epidemiology etc.), the summary of findings, and whatever other information we deem important. We would then have a centralized database that can be sorted and searched for relevant information when writing up the paper.

2. Inclusion and Exclusion Criteria. The typical systematic review process (from my experience) starts with an initial scan of titles and abstracts based on pre-specified inclusion and exclusion criteria. Those deemed relevant in that first pass are then subjected to a full-text scan based on another set of pre-specified inclusion and exclusion criteria. The resulting set of relevant papers are then subjected to data extraction. I think it might be important to get area experts involved in designing these inclusion and exclusion criteria. The literature at hand encompasses so many different topics that we would need help identifying those relevant to therapeutics and diagnostics (for example, do we want to include papers that estimate the reproduction number? or model the global spread of the pandemic? or are these questions beyond the scope of therapeutics/diagnostics?) Once we have these inclusion/exclusion criteria in place, we could crowd-source for help in the first and second pass scans of the literature.

In my experience, these scans of the literature are always done by hand, usually by two independent reviewers who talk through any discrepancies. When I was involved in this process, we used a software called EROS (but the link no longer seems to work...so it may not exist anymore?). Perhaps it would be possible to do this with machine learning? The main roadblock I can foresee is that abstracts and full-texts will include references to previous literature, so it would be difficult for a non-human to identify what the primary data from each paper is.

3. Risk of Bias. Typical systematic reviews also include a Risk of Bias assessment, in which each paper included in the review is assessed based on a pre-specified set of criteria (ex. Is there a control group? Were researchers blinded to experimental conditions?). Performing such a review informs how well we can trust the results of each study. The relevant criteria for performing a Risk of Bias assessment will vary depending on the type of study, however. For example, I can imagine that the sources of bias for a study coming from a virology lab performing a randomized control trial with cell lines will be vastly different from an epidemiological study attempting to estimate the reproduction number. Could we recruit experts in each area to design risk of bias assessment tools so we can understand the quality of data we collect?

4. New Articles How would we ensure we are including all new publications? In systematic reviews, you develop a search strategy using a combination of keywords and synonyms, and then input that search strategy into several different databases (such a PubMed, Web of Science, etc.). For most databases you can sign up to receive alerts when new articles are published that meet your search criteria. Would we set something like this up?

Thinking about all of this, I wonder if getting a reference librarian involved would be a good idea. I have heard of a terrific librarian from the Biomedical library at UPenn who is the go-to expert on systematic reviews. Perhaps she would be willing to be involved!

@rando2 @cgreene

Title: Potent human neutralizing antibodies elicited by SARS-CoV-2 infection

General Information

Please paste a link to the paper or a citation here:

Link: https://www.biorxiv.org/content/10.1101/2020.03.21.990770v2

What is the paper's Manubot-style citation?

Citation: @doi:10.1101/2020.03.21.990770v2

Is this paper primarily relevant to Background or Pathogesis?

• Background
• Pathogenesis
• Methods

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• Monoclonal specific antibodies
• Cross-reactive antibodies

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other:

Summary

If you would like to submit a summary of the paper, please copy and paste the following into a comment.

Suggested questions to answer about each paper:

• What did they analyze?
  Isolation and characterization of 206 monoclonal antibodies (mAbs) specific to receptor-binding domain (RBD) derived from single B cells of eight SARS-CoV-2 infected individuals.
• What methods did they use?
  ELISA, etc.
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
  Yes.
• What is the main finding (or a few main takeaways)?
  Patient-derived antibodies bind and neutralize activity against SARS-CoV-2 and some are specific to its RBD.
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
  This paper suggests that antibody response to RBDs could be viral species-specific with important therapeutic potential.
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?
  Experts need to review the methodology.

Any comments or notes?

Title: A pneumonia outbreak associated with a new coronavirus of probable bat origin

General Information

Please paste a link to the paper or a citation here:

Link: https://www.nature.com/articles/s41586-020-2012-7

What is the paper's Manubot-style citation?

Citation: [@doi:10.1038/s41586-020-2012-7]

Is this paper primarily relevant to Background or Pathogesis?

• Background
• Pathogenesis
• Methods

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• SARS-CoV-2
• zoonotic disease
• bats
• phylogenetics
• genome
• protein domains

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other: omics

Summary

If you would like to submit a summary of the paper, please copy and paste the following into a comment.

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

Should this review paper also explicitly address public health policy / epidemiology? Is there a critical mass of folks who can help manage contributions in this area?

Some specific subtopics that a section like this could address are listed in the comment below.

Title: Anti–spike IgG causes severe acute lung injury by skewing macrophage responses during acute SARS-CoV infection

Please paste a link to the paper or a citation here:

Link: https://doi.org/10.1172/jci.insight.123158

What is the paper's Manubot-style citation?

Citation: doi:10.1172/jci.insight.123158

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• keyword 1
• keyword 2
• keyword 3

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

Adding this paper that @nilswellhausen mentioned in #97 (comment) See also:

• https://twitter.com/VirusesImmunity/status/1243997325804142593
• https://twitter.com/jbloom_lab/status/1244017270294118406?s=09

Study question(s) being investigated:

How many/what drugs/combinations are being considered?

What are the main hypotheses being tested?

Study population:

What is the model system (e.g., human study, animal model, cell line study)?

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

• number treated with treatment A
• number treated with treatment B

For human studies:

What countries/regions are considered?

What is the age range, gender, other relevant characteristics?

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

What other specific inclusion-exclusion criteria are considered?

For example, do the investigators exclude patients with diagnosed neoplasms or patients over/under a certain age?

Treatment assignment:

How are treatments assigned?

For example, is it an interventional or an observational study?

Is the study randomized?

A study can be interventional but not randomized (e.g., a phase I or II clinical trial is interventional but often not randomized).

Provide other relevant details about the design.

This includes possible treatment stratification (e.g., within litters for animal studies, within hospitals for human studies), possible confounding variables (e.g., having a large age range of individuals), possible risks of bias and how they are addressed (e.g., is there masking in a clinical trial? how are individuals chosen in an observational study?).

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

For example: Is the outcome assessed by a clinician or is it self-reported?
Is the outcome based on viral load or a functional measurement (e.g., respiratory function, discharge from hospital)?
What method is used to measure the outcome?
How long after a treatment is the outcome measured?

Are outcome measurements complete?

For example, are there individuals lost to follow up?

Are outcome measurements subject to various kinds of bias?

For example, a lack of masking in randomized clinical trials.

Statistical Methods Assessment:

What methods are used for inference?

For example, logistic regression, nonparametric methods.

Are the methods appropriate for the study?

For example, are clustered data treated independently or are clusters adjusted for, such as different hospitals or litters?

Are adjustments made for possible confounders?

For example, adjustment for age, sex, or comorbidities.

Results Summary:

What is the estimated association?

For example, is it an estimated odds ratio, a median difference in detected cases, etc?

What measures of confidence or statistical significance are provided?

For example, confidence intervals, p-values, and/or Bayes factors.

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

For example, with a well-performed animal study or randomized trial it is often possible to infer causality.
If is an observational study, does it match up with some of the Bradford Hill criteria? https://www.edwardtufte.com/tufte/hill https://en.wikipedia.org/wiki/Bradford_Hill_criteria

Are there identified side effects or interactions with other drugs?

For example, is the treatment known to cause liver damage or to not be prescribed for individuals with certain comorbities?

Are there specific subgroups with different findings?

For example, do individuals with a specific baseline seem to do particularly well? Be particularly cautious with respect to multiple testing here.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

Is the model system appropriate? Is there evidence from past use that it's highly-relevant to therapeutic design in this context?

If it is a human study, what characteristics of the study population may support/limit extrapolation?

• Can results extrapolate easily to other similar groups? (e.g., same country, similar age groups)
• What would happen if conditions are extended in terms of dose or duration?
• Can results be extrapolated to other populations or in very different settings? (e.g., different age group, primary care setting vs emergency department etc)

Summary of reliability

1-2 sentences on concluding remarks, including summary of strengths, weaknesses, limitations.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe How many/what drugs/combinations are being considered
• Describe the model system
• What is the sample size?
• What countries/regions are considered
• What is the age range, gender, other relevant characteristics
• Describe study setting
• Describe other specific inclusion-exclusion criteria
• Describe how treatments are assigned
• Describe randomization (or not) and other relavent details about the design
• Describe the outcome that is assessed and whether it is appropriate.
• Describe whether the outcome measurements are complete
• Are outcome measurements subject to various kinds of bias?
• Describe methods used for inference
• Describe whether the methods are appropriate for the study
• Are adjustments made for possible confounders?
• Describe the estimated association
• What measures of confidence or statistical significance are provided?
• Describe whether a causal interpretation can be made
• Are there identified side effects or interactions with other drugs?
• Are there specific subgroups with different findings?
• If the study is an animal study, which animal and how relevant is that model?
• If it is a human study, what characteristics of the study population may support/limit extrapolation?
• Summary of reliability

Paper Background

Please paste a link to the paper or a citation here:

https://doi.org/f8v5cv

What is the paper's DOI?

DOI: 10.1038/nrmicro.2016.81

Is this paper primarily relevant to Background or Pathogenesis? (If it is primarily relevant to diagnostics or therapeutics, please go back and use the correct template)

• Background
• Pathogenesis
• Other:

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• transmission
• pathogenesis
• SARS
• MERS
• coronavirus
• review

Which areas of expertise are particularly relevant to the paper (put an x in the brackets [x])?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Suggested Reviewers (feel free to suggest yourself)

@rmrussell (who initially added this citation in #27 )

Questions for Reviewers to Address

Reviewers, please copy and paste the section below into a comment and fill it in.

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

Are you looking for a way to contribute? Great, we're happy to have you!

We'll comment below with the most up-to-date information about where help is needed.

As a note, here is some information about how to get started using GitHub

There have been some exciting new suggestions for avenues we can explore in the section on therapeutics! (Thanks, @RLordan and @nilswellhausen !)

Initially we had just thought about:

1. Symptom management, probably largely via pharmaceuticals
2. Antivirals
3. Vaccines

But now we have content about nutraceuticals and clonal antibodies as well.

Does anyone have ideas about how to most effectively group these into categories? Is there a hierarchical structure at all, where some of them are more or less similar to others, or do we have 5 distinct categories as the text reflects now?

This repo requires conflict of interest disclosure (COI) to be added to the metadata file for a new author entry but the template format is not specified in the linked file.

Additionally, the contribution section does not make note of the fact that it should be one of the fourteen CredIT taxonomy roles found here: https://casrai.org/credit/

Possible solutions include pointing the template format at something other than the rootstock default since this is repo specific or including extra directions and links in the main README.md file. Alternatively, a CONTRIBUTING.md file could describe this process in greater detail (and be linked to from the main page). More info on CONTRIBUTING files and there use in software projects on GitHub can be found here: https://help.github.com/en/github/building-a-strong-community/setting-guidelines-for-repository-contributors . I would be happy to help author any/all of these documents or changes.

Thanks again for putting this all together and welcoming so many people!

Title: Is There a Role for Tissue Plasminogen Activator (tPA) as a Novel Treatment for Refractory COVID-19 Associated Acute Respiratory Distress Syndrome (ARDS)?

Please paste a link to the paper or a citation here:

Link: https://journals.lww.com/jtrauma/Citation/publishahead/Is_There_a_Role_for_Tissue_Plasminogen_Activator.97967.aspx

What is the paper's Manubot-style citation?

Citation: doi:10.1097/TA.0000000000002694

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• therapeutic
• ARDS
• tPA

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

A big cause of the deaths from the coronavirus is due to ARDS (acute respiratory distress syndrome). Past work has noted that ARDS causes deposition of fibrin (protein involved in blood clotting along with platelets) in airspaces and lung parenchyma along with fibrin platelet microthrombi deposited in the pulmonary vasculature. In other words, blood clots are deposited into the lungs, causing damage.

tPA is a protein involved in breaking down blood clots. The protein can be manufactured using recombinant techniques and is widely used as a treatment for strokes (where blood clots obstruct blood flow to the brain). Given the current drastic shortage of ventilators with the ongoing coronavirus crisis, the authors posit that using tPA as a stopgap treatment for ARDS may have useful effect. The use of agents such as tPA is typically considered higher risk, but may be necessary given the current crisis.

The paper suggests that using experience from strokes, intravenous administration of tPA may be useful. They suggest that unlike strokes, where a brief dose is used, for coronanavirus, a better treatment may be to have a first dose of 25 mg tPA administered over 2 hours, followed by another 25 mg tPA dose over the subsequent 22 hours. They suggest patients with severe ARDS where ventilators are not available may be good candidates.

Study question(s) being investigated:

Can tPA be used as an emergency stopgap treatment for severe cases where ventilators aren't available

How many/what drugs/combinations are being considered?

tPA, administered intravenously

What are the main hypotheses being tested?

Can tPA be used as a stopgap treatment for ARDS in the absence of a ventilator?

Study population:

N/A. This is a proposal paper, no data yet.

What is the model system (e.g., human study, animal model, cell line study)?

N/A. Human studies would be needed to validate

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

N/A

For human studies:

N/A

What countries/regions are considered?

N/A

What is the age range, gender, other relevant characteristics?

N/A

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

N/A

What other specific inclusion-exclusion criteria are considered?

Given the risks of tPA, the authors recommend using this potential treatment only for patients with severe ARDS where P/F < 50.

Treatment assignment:

N/A

How are treatments assigned?

N/A. This is a position paper

Is the study randomized?

N/A

Provide other relevant details about the design.

This is a position paper, no results yet.

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

N/A

Are outcome measurements complete?

N/A

Are outcome measurements subject to various kinds of bias?

N/A

Statistical Methods Assessment:

What methods are used for inference?

For example, logistic regression, nonparametric methods.

Are the methods appropriate for the study?

For example, are clustered data treated independently or are clusters adjusted for, such as different hospitals or litters?

Are adjustments made for possible confounders?

For example, adjustment for age, sex, or comorbidities.

Results Summary:

What is the estimated association?

For example, is it an estimated odds ratio, a median difference in detected cases, etc?

What measures of confidence or statistical significance are provided?

For example, confidence intervals, p-values, and/or Bayes factors.

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

For example, with a well-performed animal study or randomized trial it is often possible to infer causality.
If is an observational study, does it match up with some of the Bradford Hill criteria? https://www.edwardtufte.com/tufte/hill https://en.wikipedia.org/wiki/Bradford_Hill_criteria

Are there identified side effects or interactions with other drugs?

For example, is the treatment known to cause liver damage or to not be prescribed for individuals with certain comorbities?

Are there specific subgroups with different findings?

For example, do individuals with a specific baseline seem to do particularly well? Be particularly cautious with respect to multiple testing here.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

Is the model system appropriate? Is there evidence from past use that it's highly-relevant to therapeutic design in this context?

If it is a human study, what characteristics of the study population may support/limit extrapolation?

• Can results extrapolate easily to other similar groups? (e.g., same country, similar age groups)
• What would happen if conditions are extended in terms of dose or duration?
• Can results be extrapolated to other populations or in very different settings? (e.g., different age group, primary care setting vs emergency department etc)

Summary of reliability

1-2 sentences on concluding remarks, including summary of strengths, weaknesses, limitations.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe How many/what drugs/combinations are being considered
• Describe the model system
• What is the sample size?
• What countries/regions are considered
• What is the age range, gender, other relevant characteristics
• Describe study setting
• Describe other specific inclusion-exclusion criteria
• Describe how treatments are assigned
• Describe randomization (or not) and other relavent details about the design
• Describe the outcome that is assessed and whether it is appropriate.
• Describe whether the outcome measurements are complete
• Are outcome measurements subject to various kinds of bias?
• Describe methods used for inference
• Describe whether the methods are appropriate for the study
• Are adjustments made for possible confounders?
• Describe the estimated association
• What measures of confidence or statistical significance are provided?
• Describe whether a causal interpretation can be made
• Are there identified side effects or interactions with other drugs?
• Are there specific subgroups with different findings?
• If the study is an animal study, which animal and how relevant is that model?
• If it is a human study, what characteristics of the study population may support/limit extrapolation?
• Summary of reliability

Title: Nutraceuticals have potential for boosting the type 1 interferon response
to RNA viruses including influenza and coronavirus

Please paste a link to the paper or a citation here:

Link: https://www.sciencedirect.com/science/article/pii/S0033062020300372?via%3Dihub

What is the paper's DOI?

DOI: https://doi.org/10.1016/j.pcad.2020.02.007

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• keyword 1 (Nutraceuticals)
• keyword 2 (RNA viruses)
• keyword 3 (Interferon Response)

Which areas of expertise are particularly relevant to the paper?

• virology
• therapeutics
• nutraceuticals
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

This review paper discusses the potential use of nutraceuticals to prevent and lessen the response to infection by RNA viruses such as influenza and coronavirus. In particular, they highlight the utility of nutraceuticals capable of amplifying TLR7 and mitochondrial antiviral-signaling protein (MAVs) to induce type 1 interferon production.

Study question(s) being investigated:

How many/what drugs/combinations are being considered?

Several types of nutraceuticals are considered, including lipoic acid, ferulic acid, and vitamin supplements among others. However, the most promising seem to be phycocyanobilin (PCB - spirulina), N-acetylcysteine, and glucosamine.

Summary and comments on the paper

This review highlights potential nutraceuticals and supplements already on the market and makes the case that some nutraceuticals, namely spirulina (PCB), phase 2 inducers, high-dose glucosamine, and N-acetylcysteine might aid in the prevention or modulation of RNA virus infections via evoking type 1 interferon production. Overall there is the suggestion that these supplements may benefit the consumer. However, it is a review and there was little clinical evidence to support the claims.

Hello interested contributors! Welcome to the covid19-review project. Our goal here is to provide an up-to-date perspective on the current peer reviewed and preprinted literature around diagnostics and therapeutics relevant to COVID-19. There's more in our README, which you may have already seen: https://github.com/greenelab/covid19-review#sars-cov-2-and-covid-19-an-evolving-review-of-diagnostics-and-therapeutics

As a first step, let's get to know each other. Please answer these questions!

• Your name
• Your job other than this review
• What you hope to get out of participating
• How you feel best prepared to contribute
• What you have the most trepidation about

Here I upload a document with several points of discussion, including the most recent literature on the most hopeful experimental drugs (I have found 4 of them), as well as diagnostic tests, based on antibody detection, recently developed. I also added some thoughts concerning the Italian Covid-19 situation.

Please let me know your feedback.

Best,

Ada
20200326_Corona virus review.pdf

Originally posted by @aadattoli in #17 (comment)

Context
As we begin the review, we need a place for contributors to track which papers have been read as well as a place to record summaries of the articles. This will help us to:

• Keep a list of older papers that may be relevant of new papers as they appear,
• Maintain an easy-to-access record of contributors' interpretation of the original lit
• Protect against authors' meaning from becoming distorted through the rapid editing of the main text by many contributors
• Provide a forum for discussion among contributors of the significance and interpretation of articles

Problem
We need to make some sort of template to encourage the submission of papers as issues in a standardized format that will allow for filtering, searching, maintenance, etc. It would also be good to recommend contributors include certain pieces of information in their summaries.

Ideas

1. We likely want to use labels to differentiate new papers from other types of issues (e.g., people asking for help). Do we want separate labels for unclaimed vs claimed papers, or does the "assignees" function work to filter these out?
2. For searching, are user-provided keywords sufficient? Would we want to set up subject area labels, for example?
3. We could list questions to address in the summary as part of the template, but what if the person creating the new paper issue isn't the one who ends up reading/summarizing? How difficult would it be to set up a bot to comment on each New Paper issue, for example?
4. Below is my first pass at what information we might want users to provide. Feedback would be much appreciated!

Request thoughts from
@cgreene

Please paste a link to the paper (preferably DOI) or citation information here:

Is this paper primarily relevant to Background, Diagnostics, or Therapeutics? (OK if more than one)

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

Please leave a comment with your summary below.
Suggested questions to address in summary:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Title: Pangolin homology associated with 2019-nCoV

General Information

Please paste a link to the paper or a citation here:

Link: https://www.biorxiv.org/content/10.1101/2020.02.19.950253v1

What is the paper's Manubot-style citation?

Citation: [@doi:10.1101/2020.02.19.950253]

Is this paper primarily relevant to Background or Pathogesis?

• Background
• Pathogenesis
• Methods

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• zoonotic disease
• pangolin
• bat
• genome
• genomics
• protein
• S1 protein
• ACE2

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology
• other: omics

Summary

If you would like to submit a summary of the paper, please copy and paste the following into a comment.

Suggested questions to answer about each paper:

• What did they analyze?
• What methods did they use?
• Does this paper study COVID-19, SARS-CoV-2, or a related disease and/or virus?
• What is the main finding (or a few main takeaways)?
• What does this paper tell us about the background and/or diagnostics/therapeutics for COVID-19 / SARS-CoV-2?
• Do you have any concerns about methodology or the interpretation of these results beyond this analysis?

Any comments or notes?

Title: A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe Covid-19

Please paste a link to the paper or a citation here:

Link: https://www.nejm.org/doi/full/10.1056/NEJMoa2001282

What is the paper's DOI?

Citation: doi:10.1056/NEJMoa2001282

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• keyword 1 drug-repurposing
• keyword 2 antiviral
• keyword 3 randomized-controlled-trial

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

The study is trial of a combination therapy for COVID-19. The intervention did not succeed.

Study question(s) being investigated:

Efficacy of a combination of antiviral drugs in COVID-19.

How many/what drugs/combinations are being considered?

A combination of Ritonavir-Lopinavir.

What are the main hypotheses being tested?

The efficacy of Ritonavir-Lopinavir in COVID-19 over placebo.

Study population:

What is the model system (e.g., human study, animal model, cell line study)?

Human study.

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

199 patients in total.

• number treated with Ritonavir-Lopinavir: 99
• number in standard care: 100

For human studies:

What countries/regions are considered?

Wuhan, China.

What is the age range, gender, other relevant characteristics?

median age: 58 years

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

Patients admitted for COVID-19 symptoms.

What other specific inclusion-exclusion criteria are considered?

• Inclusion:
• Male and nonpregnant female patients 18 years of age or older,
• had a diagnostic specimen that was positive
  on RT-PCR,
• had pneumonia confirmed by chest
  imaging,
• had an oxygen saturation (Sao2) of
  94% or less while they were breathing ambient
  air or a ratio of the partial pressure of oxygen
  (Pao2) to the fraction of inspired oxygen (Fio2)
  (Pao2:Fio2) at or below 300 mg Hg.
• Exclusion:
• physician decision that involvement in the trial was not in the patient’s best interest,
• presence of any condition that would not
  allow the protocol to be followed safely,
• known allergy or hypersensitivity to lopinavir–ritonavir,
• known severe liver disease (e.g., cirrhosis, with
  an alanine aminotransferase level >5× the upper
  limit of the normal range or an aspartate aminotransferase level >5× the upper limit of the normal range),
• use of medications that are contraindicated with lopinavir–ritonavir and that could
  not be replaced or stopped during the trial period,
• pregnancy or breast-feeding,
• or known HIV infection, because of concerns about the development
  of resistance to lopinavir–ritonavir if used without
  combining with other antiretrovirals.
• Patients who were unable to swallow received lopinavir–ritonavir through a nasogastric tube.

Treatment assignment:

How are treatments assigned?

For example, is it an interventional or an observational study?
Interventional.

Is the study randomized?

yes.

Provide other relevant details about the design.

Of the 357 patients, 158 were excluded and 199 were included. Among the 99 assigned to treatment group, three died after admission and two could not take the treatment.

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

The outcome is determined by a clinician.

• The outcome was mainly the viral load, respiratory assistance (supplemental oxygen), and clinical improvement score, days of invasive intubation
• The outcome is measured after 7, 14, and 28 days

Are outcome measurements complete?

Five patients were dropped during the study.

Are outcome measurements subject to various kinds of bias?

I think that accounting for a placebo arm (standard-care) corrects for several bias.

Statistical Methods Assessment:

What methods are used for inference?

Kaplan-Meier plot, hazard ratio.

Are the methods appropriate for the study?

Yes.

Are adjustments made for possible confounders?

No adjustment was considered because no important between-group
differences in demographic characteristics, baseline laboratory test results, distribution of ordinal
scale scores, or NEWS2 scores at enrollment

Results Summary:

What is the estimated association?

odds ratio.

What measures of confidence or statistical significance are provided?

Treatment with lopinavir–ritonavir was not associated with a
difference from standard care in the time to clinical improvement (hazard ratio for
clinical improvement, 1.24; 95% confidence interval [CI], 0.90 to 1.72). Mortality
at 28 days was similar in the lopinavir–ritonavir group and the standard-care group
(19.2% vs. 25.0%; difference, −5.8 percentage points; 95% CI, −17.3 to 5.7).

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

Yes.

Are there identified side effects or interactions with other drugs?

Patients with such characteristics were excluded from the study.

Are there specific subgroups with different findings?

No.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

No.

If it is a human study, what characteristics of the study population may support/limit extrapolation?

-I think it is hard to tell if the study extrapolates to other countries with n=199, with all the patients from Wuhan, China.

Summary of reliability

I think it is a remarkable study, with sound design and flawless execution and design. It helps narrow down the search for therapy.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe How many/what drugs/combinations are being considered
• Describe the model system
• What is the sample size?
• What countries/regions are considered
• What is the age range, gender, other relevant characteristics
• Describe study setting
• Describe other specific inclusion-exclusion criteria
• Describe how treatments are assigned
• Describe randomization (or not) and other relavent details about the design
• Describe the outcome that is assessed and whether it is appropriate.
• Describe whether the outcome measurements are complete
• Are outcome measurements subject to various kinds of bias?
• Describe methods used for inference
• Describe whether the methods are appropriate for the study
• Are adjustments made for possible confounders?
• Describe the estimated association
• What measures of confidence or statistical significance are provided?
• Describe whether a causal interpretation can be made
• Are there identified side effects or interactions with other drugs?
• Are there specific subgroups with different findings?
• If the study is an animal study, which animal and how relevant is that model?
• If it is a human study, what characteristics of the study population may support/limit extrapolation?
• Summary of reliability

Title: Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial

Please paste a link to the paper or a citation here: : https://doi.org/10.1016/j.ijantimicag.2020.105949

Link: https://www.sciencedirect.com/science/article/pii/S0924857920300996

What is the paper's Manubot-style citation?

Citation: doi:10.1016/j.ijantimicag.2020.105949

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• hydroxychloroquine
• azithomycin
• clinical trial

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

The study investigated the impact of hydroxychloroquine combined with azithromycin on viral loads in SARS-CoV-2-infected patients.

Study question(s) being investigated:

Does hydroxychloroquine and azithromycin effect SARS-CoV-2-infected patients?

How many/what drugs/combinations are being considered?

2 drugs (hydroxychloroquine and azithromycin) were being considered

What are the main hypotheses being tested?

In vitro and in vivo positive effects of Chloroquine have been reported.
Hydroxychloroquine has been demonstrated to have an anti-SARS-CoV activity in vitro and is safer than chloroquine.

Study population:

Hospitalized patients with confirmed COVID-19 that were older than 12 years and PCR documented SARS-CoV-2 carriage in nasopharyngeal sample at admission whatever their clinical status.

What is the model system (e.g., human study, animal model, cell line study)?

Human

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

20 treated
16 controls

For human studies:

What countries/regions are considered?

Marseille, France

What is the age range, gender, other relevant characteristics?

12 years old
Mean age of patients was 45.1
15 patients were male
hydroxychloroquine patients were older than controls

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

in patient (hospitalized)

What other specific inclusion-exclusion criteria are considered?

12 years old
PCR documented SARS-CoV-2 carriage in nasopharyngeal sample at admission
Patients were excluded if they had a known allergy to hydroxychloroquine or chloroquine or had another known contraindication to treatment with the study drug, including retinopathy, G6PD deficiency and QT prolongation. Breastfeeding and pregnant patients were excluded based on their declaration and pregnancy test results when required.

Treatment assignment:

oral hydroxychloroquine sulfate 200 mg, three times per day during ten days

Six patients received azithromycin (500mg on day1
followed by 250mg per day, the next four days) to prevent bacterial super-infection under daily electrocardiogram control

How are treatments assigned?

Interventional
Patients had to consent to receive hydroxychloroquine, those that did not were included in the control group.

Is the study randomized?

No

A study can be interventional but not randomized (e.g., a phase I or II clinical trial is interventional but often not randomized).

non-randomized clinical trial

This includes possible treatment stratification (e.g., within litters for animal studies, within hospitals for human studies), possible confounding variables (e.g., having a large age range of individuals), possible risks of bias and how they are addressed (e.g., is there masking in a clinical trial? how are individuals chosen in an observational study?).

Outcome Assessment:

PCR positive nasopharyngeal samples

At day 3,4,5, and 6 post-inclusion treated patients had increased virological clearance between patients and controls.

At day 6 post-inclusion, 70% hydroxychloroquine treated patients had increased virological clearance, compared to 12.5% in the control group.

At day 6 post-inclusion, 100% of patients treated with hydroxychloroquine and azithromycin increased virological clearance.

Describe the outcome that is assessed and whether it is appropriate.

The outcome measurement was PCR positive nasopharyngeal samples. The authors said that clinical follow-up and occurrence of side-effects will be
described in a further paper at the end of the trial.

For example: Is the outcome assessed by a clinician or is it self-reported?
Is the outcome based on viral load or a functional measurement (e.g., respiratory function, discharge from hospital)?
What method is used to measure the outcome?
How long after a treatment is the outcome measured?

Are outcome measurements complete?

For example, are there individuals lost to follow up?

Are outcome measurements subject to various kinds of bias?

Not a randomized clinical trial.

Statistical Methods Assessment:

What methods are used for inference?

For example, logistic regression, nonparametric methods.

Are the methods appropriate for the study?

For example, are clustered data treated independently or are clusters adjusted for, such as different hospitals or litters?

Are adjustments made for possible confounders?

For example, adjustment for age, sex, or comorbidities.

Results Summary:

What is the estimated association?

For example, is it an estimated odds ratio, a median difference in detected cases, etc?

What measures of confidence or statistical significance are provided?

For example, confidence intervals, p-values, and/or Bayes factors.

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

For example, with a well-performed animal study or randomized trial it is often possible to infer causality.
If is an observational study, does it match up with some of the Bradford Hill criteria? https://www.edwardtufte.com/tufte/hill https://en.wikipedia.org/wiki/Bradford_Hill_criteria

Are there identified side effects or interactions with other drugs?

For example, is the treatment known to cause liver damage or to not be prescribed for individuals with certain comorbities?

Are there specific subgroups with different findings?

For example, do individuals with a specific baseline seem to do particularly well? Be particularly cautious with respect to multiple testing here.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

Is the model system appropriate? Is there evidence from past use that it's highly-relevant to therapeutic design in this context?

If it is a human study, what characteristics of the study population may support/limit extrapolation?

• Can results extrapolate easily to other similar groups? (e.g., same country, similar age groups)
• What would happen if conditions are extended in terms of dose or duration?
• Can results be extrapolated to other populations or in very different settings? (e.g., different age group, primary care setting vs emergency department etc)

Summary of reliability

1-2 sentences on concluding remarks, including summary of strengths, weaknesses, limitations.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe How many/what drugs/combinations are being considered
• [x ] Describe the model system
• What is the sample size?
• What countries/regions are considered
• What is the age range, gender, other relevant characteristics
• [ x] Describe study setting
• [ x] Describe other specific inclusion-exclusion criteria
• [x ] Describe how treatments are assigned
• Describe randomization (or not) and other relavent details about the design
• Describe the outcome that is assessed and whether it is appropriate.
• Describe whether the outcome measurements are complete
• Are outcome measurements subject to various kinds of bias?
• Describe methods used for inference
• Describe whether the methods are appropriate for the study
• Are adjustments made for possible confounders?
• Describe the estimated association
• What measures of confidence or statistical significance are provided?
• Describe whether a causal interpretation can be made
• Are there identified side effects or interactions with other drugs?
• Are there specific subgroups with different findings?
• If the study is an animal study, which animal and how relevant is that model?
• If it is a human study, what characteristics of the study population may support/limit extrapolation?
• Summary of reliability

I think people may be more overwhelmed than anything by the volume of papers that are available, but I wanted to start a record of collections of relevant papers in case anyone is looking for a place to start:

1. @rbharath commented in #17 that they are maintaining this list
2. @cgreene posted in gitter with these treatment guidelines from UPenn Med (with an excellent list of references at the bottom)
3. The COVID-19 Open Research Dataset, which is intended for machine learning, is actually quite a nice resource for human learning as well, if a huge file to download!
4. @dziakj1 suggested this nicely organized list of papers from UCSF

Please feel free to comment below with additional links for good ways to find papers, or to open a new discussion on any interesting paper you find using by starting a new Issue and filling in one of the new paper templates (either just the top part, or the whole thing!) (Just make sure you search first in case someone already opened one!)

Due to the complexity of manubot, right now there are a lot of files and folders in the repository, and many of these file extensions might be new for folks. I think we might be running into some confusion about which are up for grabs in terms of editing. I'm wondering if some sort of TOC could help direct people to which ones we want edits on!

Happy for comments, or else I will keep thinking about it and hopefully submit a PR later today.

Title: Treatment of 5 Critically Ill Patients With COVID-19 With Convalescent Plasma

Please paste a link to the paper or a citation here:

Link: https://jamanetwork.com/journals/jama/fullarticle/2763983

What is the paper's Manubot-style citation?

Citation: @doi:10.1001/jama.2020.4783

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• Convalescent Plasma Treatment
• Neutralizing antibodies
• Clinical paper

Which areas of expertise are particularly relevant to the paper?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

In this uncontrolled case series of 5 critically ill patients with COVID-19 and acute respiratory distress syndrome (ARDS), administration of convalescent plasma containing neutralizing antibody was followed by an improvement in clinical status.

Study question(s) being investigated:

Can plasma transfusion improve clinical status

How many/what drugs/combinations are being considered?

Antiviral treatment + Plasma transfusion

What are the main hypotheses being tested?

Can plasma containing neutralizing antibodies improve critically ill patients disease status

Study population:

What is the model system (e.g., human study, animal model, cell line study)?

Human study:5 Patients that are sick and did not responded to antivirals received plasma from 5 patients that have been confirmed sick but recovered

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

Only one treatment group:

• 5

For human studies:

What countries/regions are considered?

China

What is the age range, gender, other relevant characteristics?

36-65 years, 3 men, 2 woman,

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

5 critically ill patients, required ventilation, did not respond to antivirals

What other specific inclusion-exclusion criteria are considered?

Case series of 5 critically ill patients with laboratory-confirmed COVID-19 and acute respiratory distress syndrome (ARDS) who met the following criteria: severe pneumonia with rapid progression and continuously high viral load despite antiviral treatment; Pao2/Fio2 <300; and mechanical ventilation

For example, do the investigators exclude patients with diagnosed neoplasms or patients over/under a certain age?

Not stated

Treatment assignment:

How are treatments assigned?

All 5 people got treatment (uncontrolled)

For example, is it an interventional or an observational study?

Interventional

Is the study randomized?

No

A study can be interventional but not randomized (e.g., a phase I or II clinical trial is interventional but often not randomized).

Provide other relevant details about the design.

This includes possible treatment stratification (e.g., within litters for animal studies, within hospitals for human studies), possible confounding variables (e.g., having a large age range of individuals), possible risks of bias and how they are addressed (e.g., is there masking in a clinical trial? how are individuals chosen in an observational study?).

Age range and gender distribution is fair

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

Changes of body temperature, Sequential Organ Failure Assessment (SOFA) score (range 0-24, with higher scores indicating more severe illness), Pao2/Fio2, viral load, serum antibody titer, routine blood biochemical index, ARDS, and ventilatory and extracorporeal membrane oxygenation (ECMO) supports before and after convalescent plasma transfusion.

Are outcome measurements complete?

For example, are there individuals lost to follow up?

Are outcome measurements subject to various kinds of bias?

Since every patient got treatment there is of course bias towards before vs after plasma transfusion

Statistical Methods Assessment:

What methods are used for inference?

For example, logistic regression, nonparametric methods.

Are the methods appropriate for the study?

For example, are clustered data treated independently or are clusters adjusted for, such as different hospitals or litters?

Are adjustments made for possible confounders?

For example, adjustment for age, sex, or comorbidities.

Results Summary:

What is the estimated association?

Pre vs post infusion

For example, is it an estimated odds ratio, a median difference in detected cases, etc?

What measures of confidence or statistical significance are provided?

For example, confidence intervals, p-values, and/or Bayes factors.

No statistics

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

For example, with a well-performed animal study or randomized trial it is often possible to infer causality.
If is an observational study, does it match up with some of the Bradford Hill criteria? https://www.edwardtufte.com/tufte/hill https://en.wikipedia.org/wiki/Bradford_Hill_criteria

It is interventional but they do not have a control group therefore we can not conclude that the transfusion did anything or if it was just time.

Are there identified side effects or interactions with other drugs?

For example, is the treatment known to cause liver damage or to not be prescribed for individuals with certain comorbities?

Those patient also got steroids and antivirals

Are there specific subgroups with different findings?

For example, do individuals with a specific baseline seem to do particularly well? Be particularly cautious with respect to multiple testing here.

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If it is a human study, what characteristics of the study population may support/limit extrapolation?

• Can results extrapolate easily to other similar groups? (e.g., same country, similar age groups)
• What would happen if conditions are extended in terms of dose or duration?
• Can results be extrapolated to other populations or in very different settings? (e.g., different age group, primary care setting vs emergency department etc)

There is a lot of variability here: The donors for the plasma, recipients etc.

Summary of reliability

1-2 sentences on concluding remarks, including a summary of strengths, weaknesses, limitations.

While this is an interesting study, it is also the epitome of a poorly controlled study. It is impossible to say if the treatment caused the beneficial effects or if it was the other treatments or just time. But the results are pretty striking (for me not being a clinician). The reports concerning the benefit of using neutralizing antibodies remain controversial at this point. I just wish someone would conduct a proper clinical trial on this topic as there seems potential but we really do not understand what is going on.

Progress

Check off the components as they are completed. If the component is not applicable, check the box as well.

• 1-2 sentences introducing the study and its main findings
• Describe How many/what drugs/combinations are being considered
• Describe the model system
• What is the sample size?
• What countries/regions are considered
• What is the age range, gender, other relevant characteristics
• Describe study setting
• Describe other specific inclusion-exclusion criteria
• Describe how treatments are assigned
• Describe randomization (or not) and other relavent details about the design
• Describe the outcome that is assessed and whether it is appropriate.
• Describe whether the outcome measurements are complete
• Are outcome measurements subject to various kinds of bias?
• Describe methods used for inference
• Describe whether the methods are appropriate for the study
• Are adjustments made for possible confounders?
• Describe the estimated association
• What measures of confidence or statistical significance are provided?
• Describe whether a causal interpretation can be made
• Are there identified side effects or interactions with other drugs?
• Are there specific subgroups with different findings?
• If the study is an animal study, which animal and how relevant is that model?
• If it is a human study, what characteristics of the study population may support/limit extrapolation?
• Summary of reliability

Title: Repurposing host-based therapeutics to control coronavirus and influenza virus

Please paste a link to the paper or a citation here:

Link: https://www.sciencedirect.com/science/article/pii/S1359644618303805

What is the paper's DOI?

DOI: 10.1016/j.drudis.2019.01.018

Please list some keywords (3-10) that help identify the relevance of this paper to COVID-19

• review paper
• antivirals
• drug repurposing

Which areas of expertise are particularly relevant to the paper (put an x in the brackets [x])?

• virology
• epidemiology
• biostatistics
• immunology
• pharmacology

Questions to answer about each paper:

Please provide 1-2 sentences introducing the study and its main findings

This is more of a speculative piece that discusses a few potential avenues that one might consider. It is a review paper, so it's more of a "potential mechanisms" description than a specific drug, though they do mention some (I found it via a tweet from @mattmight about one of these).

Study question(s) being investigated:

How many/what drugs/combinations are being considered?

This is a review, not a research paper.

What are the main hypotheses being tested?

This is a review, not a research paper.

Study population:

What is the model system (e.g., human study, animal model, cell line study)?

N/A

What is the sample size? If multiple groups are considered, give sample size for each group (including controls).

N/A

For human studies:

What countries/regions are considered?

N/A

What is the age range, gender, other relevant characteristics?

N/A

What is the setting of the study (random sample of school children, inpatient, outpatient, etc)?

N/A

What other specific inclusion-exclusion criteria are considered?

N/A

Treatment assignment:

How are treatments assigned?

N/A

Is the study randomized?

N/A

Provide other relevant details about the design.

N/A

Outcome Assessment:

Describe the outcome that is assessed and whether it is appropriate.

N/A

Are outcome measurements complete?

N/A

Are outcome measurements subject to various kinds of bias?

N/A

Statistical Methods Assessment:

What methods are used for inference?

N/A

Are the methods appropriate for the study?

N/A

Are adjustments made for possible confounders?

N/A

Results Summary:

What is the estimated association?

N/A

What measures of confidence or statistical significance are provided?

N/A

Interpretation of results for study population:

Can we make a causal interpretation for the individuals in the study of drug -> outcome, such as "taking drug A improves likelihood of survival twofold over taking drug B."

N/A

Are there identified side effects or interactions with other drugs?

N/A

Are there specific subgroups with different findings?

N/A

Extrapolation of conclusions to other groups of individuals not specifically included in the study:

If the study is an animal study, which animal and how relevant is that model?

N/A

If it is a human study, what characteristics of the study population may support/limit extrapolation?

N/A

Summary of reliability

This is a review paper, so it is primarily speculation around potential mechanisms.

@LucyMcGowan and @SiminaB had been discussing the value of having a checklist where someone submitting a paper summary can confirm which sections they filled out vs skipped.

@LucyMcGowan implemented a prototype here

My only concern is related to implementation, specifically formatting the check boxes correct so that they will work when copy and pasted. I believe the issue templates open in plain text (so the check boxes look like - [ ]; however, once the issue is submitted, the check boxes will be visible as interactive boxes:

• test box 1
• test box 2

If I copy the "test box" lines above from Preview mode (translated markdown), here's how they look:
test box 1
test box 2

But if we use the code formatting like I did for the inline example ( `- [ ] `) then they won't work when copied from plain text!

This seems kind of trivial but I'm not sure how to work around it from a usability standpoint, since in many cases, the paper submitter is likely to copy the check boxes out of the plain text template (so they will work), but all subsequent commenters will copy them out of the issue and lose the formatting.

There seem to be several people in the introductions thread (#17 ) who are interested in zoonotic diseases, a topic that is currently missing from the introduction section outline.

I wanted to encourage a discussion of what you (and anyone else who is interested!) think are the most important elements of this topic to include in the introduction to help guide an understanding of the virus towards an understanding of possible diagnostics/therapeutics.

Please feel free either to discuss here or to propose modifications to the outline document -- here are some directions.

Also, feel more than welcome to start adding sentences/paragraphs if you feel inspired to write!

Finally, let me know if there are other fields to tag to help bring other relevant experts into this conversation (I'm putting virology for now)

People who stated interest in this topic:
@rmrussell @Huiyanangelchow

Would anyone be willing to do some research on the support / questions surrounding treatment with hydroxychloroquine? @rishirajgoel had mentioned that we don't seem to have anyone looking at it yet, and obviously it's a very popular topic right now.

If you find any interesting papers and can record them (with the DOI and some background info) as a New Paper (Therapeutic) in the Issues, that would be great! Even better if you want to start to fill out the questions in the Template describing what the studies do/find.

Additionally, it would be great to start putting together a rough draft or an outline for that section of the treatments analysis, if anyone is interested.

@cgreene found this resource that might be helpful: http://www.uphs.upenn.edu/antibiotics/COVID19.html

Please use this space to discuss and collaborate!

In #12 , @cgreene pointed out:

Reagents are going to become an even larger challenge than they are now. Advances that require fewer reagents (particularly those in short supply) might be good to talk about. In any case, the PPE situation might be the thing that eventually limits testing.

My take is also that at some point the spread is so much that testing for the sake of telling people they are infected and to stay isolated is no longer practical, so the focus shifts to testing healthcare workers or those for whom a diagnosis would change their course of treatment. In this setting faster tests may become even more important.

Some updates have been added in #20
We would love to hear more thoughts on this topic from people in fields like epidemiology and possibly public health. Comment below if you have opinions!

@juliettemarie0405