No evidence of systematic proximity ascertainment bias in early COVID-19 cases in Wuhan Reply to Weissman (2024)

TL;DR

This paper refutes Weissman's claim of proximity ascertainment bias in early COVID-19 cases, demonstrating that observed patterns can be explained without assuming bias, based on flawed premises and stochastic factors.

Contribution

The study challenges prior claims of bias by providing an alternative explanation rooted in stochasticity and infection locations, without evidence of systematic ascertainment bias.

Findings

No evidence of systematic proximity ascertainment bias

Patterns explained by stochasticity and infection locations

Refutes Weissman's flawed premise

Abstract

In a short text published as Letter to the Editor of the Journal of the Royal Statistical Society Series A, Weissman (2024) argues that the finding that early COVID-19 cases without an ascertained link to Wuhan's Huanan Seafood Wholesale market resided on average closer to the market than cases epidemiologically linked to it, reveals "major proximity ascertainment bias". Here we show that Weissman's conclusion is based on a flawed premise, and that there is no such "internal evidence" of major bias. The pattern can indeed be explained by places of infection not being limited to residential neighbourhoods, and by stochasticity -- i.e., without requiring any ascertainment bias.