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:
-
[1];
[7];
[8];
[9];
[10];
- Univ. de Rennes (France)
- Texas Tech Univ., Lubbock, TX (United States)
- Oregon State Univ., Corvallis, OR (United States)
- Univ. of Tennessee, Knoxville, TN (United States)
- Osnabruck Univ. (Germany)
- Imperial College London, Ascot (United Kingdom)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Cornell Univ., Ithaca, NY (United States)
- Wright State Univ., Dayton, OH (United States)
- Univ. of Cambridge (United Kingdom)
- London School of Hygiene & Tropical Medicine (United Kingdom)
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (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. doi: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 = {Tue Dec 03 00:00:00 EST 2019},
month = {Tue Dec 03 00:00:00 EST 2019}
}
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Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California
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Dynamics of Multiple Infection and Within‐Host Competition in Genetically Diverse Malaria Infections
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Diversity and Composition of Viral Communities: Coinfection of Barley and Cereal Yellow Dwarf Viruses in California Grasslands
journal, March 2009
- Seabloom, Eric W.; Hosseini, Parviez R.; Power, Alison G.
- The American Naturalist, Vol. 173, Issue 3
Multiple-Strain Infections of Borrelia afzelii : A Role for Within-Host Interactions in the Maintenance of Antigenic Diversity?
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Bias Due to Correlation Between Times-at-Risk for Infection in Epidemiologic Studies Measuring Biological Interactions Between Sexually Transmitted Infections: A Case Study Using Human Papillomavirus Type Interactions
journal, December 2016
- Malagón, Talía; Lemieux-Mellouki, Philippe; Laprise, Jean-François
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Multiple parasite infections and their relationship to self-reported morbidity in a community of rural Cote d'Ivoire
journal, May 2004
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Multiple Human Papillomavirus Infections and Type Competition in Men
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journal, April 1999
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The community ecology of pathogens: coinfection, coexistence and community composition
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Detecting interspecific macroparasite interactions from ecological data: patterns and process: Detecting interspecific parasite interactions
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Species Interactions in a Parasite Community Drive Infection Risk in a Wildlife Population
journal, October 2010
- Telfer, Sandra; Lambin, Xavier; Birtles, Richard
- Science, Vol. 330, Issue 6001
Identifying the Interaction Between Influenza and Pneumococcal Pneumonia Using Incidence Data
journal, June 2013
- Shrestha, S.; Foxman, B.; Weinberger, D. M.
- Science Translational Medicine, Vol. 5, Issue 191
Malaria and related outcomes in patients with intestinal helminths: a cross-sectional study
journal, November 2012
- Degarege, Abraham; Legesse, Mengistu; Medhin, Girmay
- BMC Infectious Diseases, Vol. 12, Issue 1
Tuberculosis-Human Immunodeficiency Virus (HIV) co-infection in Ethiopia: a systematic review and meta-analysis
journal, December 2018
- Teweldemedhin, Mebrahtu; Asres, Negasi; Gebreyesus, Hailay
- BMC Infectious Diseases, Vol. 18, Issue 1
The importance of multiparasitism: examining the consequences of co-infections for human and animal health
journal, October 2015
- Vaumourin, Elise; Vourc’h, Gwenaël; Gasqui, Patrick
- Parasites & Vectors, Vol. 8, Issue 1
Statistical Inference for Multi-Pathogen Systems
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