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Limitations of COVID-19 testing and case data for evidence-informed health policy and practice

Elizabeth Alvarez1, Iwona A Bielska2, Stephanie Hopkins2

  • 1Department of Health Research Methods, Evidence and Impact, McMaster University, CRL 2nd Floor, 1280 Main Street West, Hamilton, ON, L8S4K1, Canada. alvare@mcmaster.ca.

Health Research Policy and Systems
|January 26, 2023
PubMed

Insights

International COVID-19 case data is unreliable due to testing and reporting barriers, leading to an undercount. Understanding these limitations is crucial for accurate pandemic response and future preparedness.

Area of Science:

  • Epidemiology
  • Public Health Surveillance

Background:

  • The rapid spread of Coronavirus Disease 2019 (COVID-19) highlighted significant data and surveillance gaps globally.
  • Policy decisions and public trust are often based on metrics like case and death numbers, which have inherent limitations.

Purpose of the Study:

  • To analyze the testing and reporting processes for COVID-19 cases.
  • To identify barriers within these processes that contribute to an undercount of infections.
  • To provide recommendations for improving data accuracy during the current pandemic and future public health crises.

Main Methods:

  • Review of testing and reporting procedures for COVID-19 across multiple countries.
  • Identification and documentation of encountered barriers at each stage of data collection.
  • Analysis of the impact of these barriers on case ascertainment.

Main Results:

  • Significant undercounting of COVID-19 cases is evident due to various barriers in testing and reporting.
  • Cross-country comparisons of raw COVID-19 data are challenging due to these inconsistencies.
  • The study details specific examples of these barriers from different national contexts.

Conclusions:

  • The limitations in COVID-19 data collection necessitate a cautious approach to interpreting case numbers.
  • Addressing identified barriers can improve the accuracy of surveillance data.
  • Recommendations are provided to enhance current COVID-19 data practices and prepare for future pandemics.
Abstract

Keywords:
COVID-19Case countEpidemiologyPhysical distancing policyTesting

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