武汉早期COVID-19病例不存在系统性邻近确认偏倚的证据——对Weissman（2024）的回复
No evidence of systematic proximity ascertainment bias in early COVID-19 cases in Wuhan Reply to Weissman (2024)
AI总结：
本研究回应Weissman（2024）的观点，指出其关于武汉早期新冠病例存在严重邻近确认偏倚的结论基于错误前提，该病例分布模式可由感染地点不限于社区及随机性解释，无相关偏倚的内部证据。
摘要：
在以《皇家统计学会期刊A辑》致编辑信形式发表的短文中，Weissman（2024）提出，未确认与武汉华南海鲜批发市场存在关联的早期COVID-19病例，平均居住位置比经流行病学确认与该市场有关联的病例更近，这一发现揭示了“严重的邻近确认偏倚”。本文我们表明，Weissman的结论基于错误前提，并不存在能证明存在严重偏倚的此类“内部证据”。上述模式实际上可通过感染地点不限于居住社区以及随机性来解释，即无需假设存在任何确认偏倚。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
