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• W2941554603 startingPage "e3000551" @default.
• W2941554603 abstract "If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts should be the product of the individual prevalences. Independence consequently underpins the wide range of methods for detecting pathogen interactions from cross-sectional survey data. However, the very simplest of epidemiological models challenge the underlying assumption of statistical independence. Even if pathogens do not interact, death of coinfected hosts causes net prevalences of individual pathogens to decrease simultaneously. The induced positive correlation between prevalences means the proportion of coinfected hosts is expected to be higher than multiplication would suggest. By modelling the dynamics of multiple noninteracting pathogens causing chronic infections, we develop a pair of novel tests of interaction that properly account for nonindependence between pathogens causing lifelong infection. Our tests allow us to reinterpret data from previous studies including pathogens of humans, plants, and animals. Our work demonstrates how methods to identify interactions between pathogens can be updated using simple epidemic models." @default.
• W2941554603 created "2019-05-03" @default.
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• W2941554603 date "2019-12-03" @default.
• W2941554603 modified "2023-10-12" @default.
• W2941554603 title "Coinfections by noninteracting pathogens are not independent and require new tests of interaction" @default.
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• W2941554603 doi "https://doi.org/10.1371/journal.pbio.3000551" @default.
• W2941554603 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6890165" @default.
• W2941554603 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31794547" @default.
• W2941554603 hasPublicationYear "2019" @default.
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