Using the Newcomb-Benford law to study the association between a country's COVID-19 reporting accuracy and its development.
Sci Rep
; 11(1): 22914, 2021 11 25.
Article
in English
| MEDLINE | ID: covidwho-1537336
ABSTRACT
The COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb-Benford law (NBL) to gauge data accuracy. We run an OLS regression of an index constructed from developmental indicators (democracy level, gross domestic product per capita, healthcare expenditures, and universal healthcare coverage) on goodness-of-fit measures to the NBL. We find that countries with higher values of the developmental index are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests and for a sub-sample of countries with regional data. The NBL provides a first screening for potential data manipulation during pandemics. Our study indicates that data from autocratic regimes and less developed countries should be treated with more caution. The paper further highlights the importance of independent surveillance data verification projects.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Disease Notification
/
COVID-19
Type of study:
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Sci Rep
Year:
2021
Document Type:
Article
Affiliation country:
S41598-021-02367-z
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