Coinfections by noninteracting pathogens are not independent and require new tests of interaction

Frédéric M Hamelin, Linda J S Allen, Vrushali A Bokil, Louis J Gross, Frank M Hilker, Michael J Jeger, Carrie A Manore, Alison G Power, Megan A Rúa and Nik J Cunniffe

PLOS Biology, 2019, vol. 17, issue 12, 1-25

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.If pathogen species, strains, or clones do not interact, intuition suggests the proportion of coinfected hosts can be obtained by simply multiplying the individual prevalences. However, even simple epidemiological models show this to be untrue. This study develops new tests for interaction between pathogens that account for this surprising lack of statistical independence.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pbio00:3000551

DOI: 10.1371/journal.pbio.3000551

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