Coinfections by noninteracting pathogens are not independent and require new tests of interaction.
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. Howe...
Main Authors: | , , , , , , , , , |
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Format: | Article |
Language: | English |
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Public Library of Science (PLoS)
2019-12-01
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Series: | PLoS Biology |
Online Access: | https://doi.org/10.1371/journal.pbio.3000551 |
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author | 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 Nik J Cunniffe |
author_facet | 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 Nik J Cunniffe |
author_sort | Frédéric M Hamelin |
collection | DOAJ |
description | 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. |
first_indexed | 2024-12-24T03:13:33Z |
format | Article |
id | doaj.art-fe57a5415fc743ea9aac7e26fd1e38be |
institution | Directory Open Access Journal |
issn | 1544-9173 1545-7885 |
language | English |
last_indexed | 2024-12-24T03:13:33Z |
publishDate | 2019-12-01 |
publisher | Public Library of Science (PLoS) |
record_format | Article |
series | PLoS Biology |
spelling | doaj.art-fe57a5415fc743ea9aac7e26fd1e38be2022-12-21T17:17:44ZengPublic Library of Science (PLoS)PLoS Biology1544-91731545-78852019-12-011712e300055110.1371/journal.pbio.3000551Coinfections by noninteracting pathogens are not independent and require new tests of interaction.Frédéric M HamelinLinda J S AllenVrushali A BokilLouis J GrossFrank M HilkerMichael J JegerCarrie A ManoreAlison G PowerMegan A RúaNik J CunniffeIf 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.https://doi.org/10.1371/journal.pbio.3000551 |
spellingShingle | 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 Nik J Cunniffe Coinfections by noninteracting pathogens are not independent and require new tests of interaction. PLoS Biology |
title | Coinfections by noninteracting pathogens are not independent and require new tests of interaction. |
title_full | Coinfections by noninteracting pathogens are not independent and require new tests of interaction. |
title_fullStr | Coinfections by noninteracting pathogens are not independent and require new tests of interaction. |
title_full_unstemmed | Coinfections by noninteracting pathogens are not independent and require new tests of interaction. |
title_short | Coinfections by noninteracting pathogens are not independent and require new tests of interaction. |
title_sort | coinfections by noninteracting pathogens are not independent and require new tests of interaction |
url | https://doi.org/10.1371/journal.pbio.3000551 |
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