Public Health Lessons Learned From Biases in Coronavirus Mortality Overestimation.
Level 5 - mechanism / opinion, no new human data
Critical appraisal and narrative commentary analyzing public health definitions and public testimony without empirical human trial data.
PubMed 32782048 · doi:10.1017/dmp.2020.298
What was done
The author performed a critical appraisal comparing informational materials from the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) with mortality calculations presented during US Congressional testimony on March 11, 2020.
What was found
The abstract reports no empirical numerical datasets. It notes that Congressional testimony cited novel coronavirus mortality as 10-times higher than seasonal influenza. The appraisal concluded that this calculation contained information and selection biases, most likely caused by comparing an influenza infection fatality rate (IFR) directly to a coronavirus case fatality rate (CFR).
Why it matters
Conflating case fatality rates with infection fatality rates can distort epidemiological risk assessments and misinform public health mitigation strategies during emerging infectious disease outbreaks.
Limits
This is a narrative critique and qualitative appraisal rather than an empirical epidemiological study, systematic review, or meta-analysis. It does not present new epidemiological data.
Cited by
- context The common seasonal flu has a mortality rate of approximately 0.1%.