ArticlePloS one2022
Reliability of COVID-19 data: An evaluation and reflection.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Balancing access, precision, and equity in adaptive test site allocation with an application to COVID-19 in Atlanta, Georgia.Scientific reports · 2025Article
- A data-driven approach to study temporal characteristics of COVID-19 infection and death Time Series for twelve countries across six continents.BMC medical research methodology · 2025Article
- Countries' progress towards Global Health Security (GHS) increased health systems resilience during the Coronavirus Disease-19 (COVID-19) pandemic: A difference-in-difference study of 191 countries.PLOS global public health · 2025Article
- Article
- Regional geographies and public health lessons of the COVID-19 pandemic in the Arctic.Frontiers in public health · 2023Article
- "Won't get fooled again": statistical fault detection in COVID-19 Latin American data.Globalization and health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
importanceThe rapid proliferation of COVID-19 has left governments scrambling, and several data aggregators are now assisting in the reporting of county cases and deaths. The different variables affecting reporting (e.g., time delays in reporting) necessitates a well-documented reliability study examining the data methods and discussion of possible causes of differences between aggregators.
objectiveTo statistically evaluate the reliability of COVID-19 data across aggregators using case fatality rate (CFR) estimates and reliability statistics. DESIGN, SETTING, AND
participantsCases and deaths were collected daily by volunteers via state and local health departments, as primary sources and newspaper reports, as secondary sources. In an effort to begin comparison for reliability statistical analysis, BroadStreet collected data from other COVID-19 aggregator sources, including USAFacts, Johns Hopkins University, New York Times, The COVID Tracking Project. MAIN OUTCOMES AND MEASURES: COVID-19 cases and death counts at the county and state levels.
resultsLower levels of inter-rater agreement were observed across aggregators associated with the number of deaths, which manifested itself in state level Bayesian estimates of COVID-19 fatality rates. CONCLUSIONS AND RELEVANCE: A national, publicly available data set is needed for current and future disease outbreaks and improved reliability in reporting.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.