ArticlemedRxiv : the preprint server for health sciences2025
Inferring pathogen superspreading potential using early spatial spread patterns.
Article in medRxiv : the preprint server for health sciences, 2025. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
Funding
Abstract
Superspreading driven by individual variation in transmissibility shapes novel pathogen emergence and the effectiveness of control measures. Current approaches to estimating superspreading typically rely on cluster size distributions informed by contact tracing or genomic data, limited by data availability and potential sampling bias. Here, we examined the impact of superspreading on the early spatial spread of novel pathogens using a branching process model incorporating inter-county mobility in the United States (US). To represent individual transmission heterogeneity, we modeled the number of secondary infections using a negative binomial distribution with a mean reproduction number
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Registered trials
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