多版本治疗理论下的病原体菌株特异性效应的潜在变异
Latent variation in pathogen strain-specific effects under multiple-versions-of-treatment theory
AI总结：
研究探讨了在多版本治疗理论下，病原体菌株特异性效应的异质性对流行病学研究解释的影响，指出菌株组成信息缺失时，因果推断需考虑菌株流行率。
摘要：
基于证据的政策制定需要估计感染对健康的影响。然而，病原体变异可能导致不良后果依赖于感染菌株，这可能使许多传染病研究复杂化。本文利用潜在结果和因果推断理论，探讨在存在菌株特异性异质性和菌株组成信息缺失时，流行病学研究中常用量的因果解释依赖于感染菌株的流行率。此外，如在其他治疗-变异-无关假设可能被违反的情况下，可移植性需要额外考虑，而不仅仅是非复合暴露所需的考虑。本文讨论了菌株特异性效应的潜在异质性，将有助于解释这些研究，并基于上述原因，也突显了病原体亚型数据的价值。
英文摘要：
Evidence-informed policy on infections requires estimates of their effects on health. However, pathogenic variation, whereby occurrence of adverse outcomes depends on the infecting strain, might complicate the study of many infectious agents. Here, we consider the interpretation of epidemiologic studies on effects of infections on health when there is heterogeneity in strain-specific effects and information on strain composition is unavailable. We use potential outcomes and causal inference theory for analyses in the presence of multiple versions of treatment to argue that oft-reported quantities in these studies have a causal interpretation that depends on population frequencies of infecting strains. Moreover, as in other contexts where the treatment-variation-irrelevance assumption might be violated, transportability requires additional considerations, beyond those needed for non-compound exposures. This discussion, that considers potential heterogeneity in strain-specific effects, will facilitate interpretation of these studies, and for the reasons mentioned above, also highlights the value of pathogen subtype data.
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