NIH funding of COVID-19 research in 2020: a cross-sectional study

  1. Logesvar Balaguru
  2. Chen Dun
  3. Andrea Meyer
  4. Sanuri Hennayake
  5. Christi Walsh
  6. Christopher Kung
  7. Brittany Cary
  8. Frank Migliarese
  9. Tinglong Dai
  10. Ge Bai
  11. Kathleen Sutcliffe
  12. Martin Makary

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Abstract

This study aims to characterise and evaluate the National Institutes of Health’s (NIH’s) grant allocation speed and pattern of COVID-19 research.

Design

Cross-sectional study.

Setting

COVID-19 NIH RePORTER Dataset was used to identify COVID-19 relevant grants.

Participants

1108 grants allocated to COVID-19 research.

Main outcomes and measures

The primary outcome was to determine the number of grants and funding amount the NIH allocated for COVID-19 by research type and clinical/scientific area. The secondary outcome was to calculate the time from the funding opportunity announcement to the award notice date.

Results

The NIH awarded a total of 56 169 grants in 2020, of which 2.0% (n=1108) wwas allocated for COVID-19 research. The NIH had a US$45.3 billion budget that year, of which 4.9% (US$2.2 billion) was allocated to COVID-19 research. The most common clinical/scientific areas were social determinants of health (n=278, 8.5% of COVID-19 funding), immunology (n=211, 25.8%) and pharmaceutical interventions research (n=208, 47.6%). There were 104 grants studying COVID-19 non-pharmaceutical interventions, of which 2 grants studied the efficacy of face masks and 6 studied the efficacy of social distancing. Of the 83 COVID-19 funded grants on transmission, 5 were awarded to study airborne transmission of COVID-19 and 2 grants on transmission of COVID-19 in schools. The average time from the funding opportunity announcement to the award notice date was 151 days (SD: ±57.9).

Conclusion

In the first year of the pandemic, the NIH diverted a small fraction of its budget to COVID-19 research. Future health emergencies will require research funding to pivot in a timely fashion and funding levels to be proportional to the anticipated burden of disease in the population.

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  1. Version published to 10.1136/bmjopen-2021-059041
  2. ScreenIT

    SciScore for 10.1101/2021.12.08.21267482: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has several limitations. The type of research and the clinical/scientific areas studied were based on definitions that may not be collectively exhaustive and mutually exclusive. In addition, we only reviewed abstracts and did not review the entire funded proposals. There were other barriers to clinical research that were not captured here, including slow institutional review boards and long journal peer-review times. A rapid research protocol that protects research subjects with standard ethical principles for research could be developed for the next health emergency.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.12.08.21267482v1 on medRxiv