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

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.

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [5];  [6]; ORCiD logo [7]; ORCiD logo [8]; ORCiD logo [9]; ORCiD logo [10];  [11]
  1. Univ. de Rennes (France)
  2. Texas Tech Univ., Lubbock, TX (United States)
  3. Oregon State Univ., Corvallis, OR (United States)
  4. Univ. of Tennessee, Knoxville, TN (United States)
  5. Osnabruck Univ. (Germany)
  6. Imperial College London, Ascot (United Kingdom)
  7. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  8. Cornell Univ., Ithaca, NY (United States)
  9. Wright State Univ., Dayton, OH (United States)
  10. Univ. of Cambridge (United Kingdom)
  11. London School of Hygiene & Tropical Medicine (United Kingdom)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program; National Science Foundation (NSF)
OSTI Identifier:
1603988
Report Number(s):
LA-UR-19-23586
Journal ID: ISSN 1545-7885
Grant/Contract Number:  
89233218CNA000001; DBI-1300426
Resource Type:
Accepted Manuscript
Journal Name:
PLoS biology (Online)
Additional Journal Information:
Journal Name: PLoS biology (Online); Journal Volume: 17; Journal Issue: 12; Journal ID: ISSN 1545-7885
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Biological Science; Mathematics

Citation Formats

Hamelin, Frédéric M., Allen, Linda J. S., Bokil, Vrushali A., Gross, Louis J., Hilker, Frank M., Jeger, Michael J., Manore, Carrie Anna, Power, Alison G., Rúa, Megan A., Cunniffe, Nik J., and Kucharski, Adam J. Coinfections by noninteracting pathogens are not independent and require new tests of interaction. United States: N. p., 2019. Web. https://doi.org/10.1371/journal.pbio.3000551.
Hamelin, Frédéric M., Allen, Linda J. S., Bokil, Vrushali A., Gross, Louis J., Hilker, Frank M., Jeger, Michael J., Manore, Carrie Anna, Power, Alison G., Rúa, Megan A., Cunniffe, Nik J., & Kucharski, Adam J. Coinfections by noninteracting pathogens are not independent and require new tests of interaction. United States. https://doi.org/10.1371/journal.pbio.3000551
Hamelin, Frédéric M., Allen, Linda J. S., Bokil, Vrushali A., Gross, Louis J., Hilker, Frank M., Jeger, Michael J., Manore, Carrie Anna, Power, Alison G., Rúa, Megan A., Cunniffe, Nik J., and Kucharski, Adam J. Tue . "Coinfections by noninteracting pathogens are not independent and require new tests of interaction". United States. https://doi.org/10.1371/journal.pbio.3000551. https://www.osti.gov/servlets/purl/1603988.
@article{osti_1603988,
title = {Coinfections by noninteracting pathogens are not independent and require new tests of interaction},
author = {Hamelin, Frédéric M. and Allen, Linda J. S. and Bokil, Vrushali A. and Gross, Louis J. and Hilker, Frank M. and Jeger, Michael J. and Manore, Carrie Anna and Power, Alison G. and Rúa, Megan A. and Cunniffe, Nik J. and Kucharski, Adam J.},
abstractNote = {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.},
doi = {10.1371/journal.pbio.3000551},
journal = {PLoS biology (Online)},
number = 12,
volume = 17,
place = {United States},
year = {2019},
month = {12}
}

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