ArticlebioRxiv : the preprint server for biology2026
Data aggregation and mechanistic modeling enable dose-response analysis of SARS-CoV-1 in non-human primates.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Dose-response modeling provides estimates of infectious and lethal doses, which can be used to inform control and prevention measures. Unfortunately, data from experimental challenge studies, which are needed to perform dose-response modeling, are often sparse. For example, non-human primate (NHP) challenge studies tend to have small samples sizes and little dose variation, often with only one or two dose levels per study. Thus, it is infeasible to apply traditional dose-response modeling approaches to data from single NHP studies. To address this challenge, we developed a mechanistic Bayesian model that aggregates and analyzes NHP pathogen load data across multiple studies. Our model links dose-infectivity to pathogen kinetics, which allows us to estimate the infectious dose and evaluate dose effects on within-host viral kinetics simultaneously. With this model, we obtained the first-ever ID
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