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Research Article

Recurring infection with ecologically distinct HPV types can explain high prevalence and diversity

Sylvia L. Ranjeva, View ORCID ProfileEdward B. Baskerville, Vanja Dukic, Luisa L. Villa, Eduardo Lazcano-Ponce, Anna R. Giuliano, Greg Dwyer, and Sarah Cobey
PNAS December 19, 2017 114 (51) 13573-13578; first published December 5, 2017; https://doi.org/10.1073/pnas.1714712114
Sylvia L. Ranjeva
aDepartment of Ecology and Evolution, University of Chicago, Chicago, IL 60637;
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  • For correspondence: slr@uchicago.edu
Edward B. Baskerville
aDepartment of Ecology and Evolution, University of Chicago, Chicago, IL 60637;
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  • ORCID record for Edward B. Baskerville
Vanja Dukic
bDepartment of Applied Mathematics, University of Colorado, Boulder, CO 80309;
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Luisa L. Villa
cFaculdade de Medicina, Universidade de São Paulo Department of Radiology and Oncology, Centro de Investigação Translacional em Oncologia, Universidade de São Paulo, 01246-000, São Paulo, Brazil;
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Eduardo Lazcano-Ponce
dCentro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública, Cuernavaca, 62100, Mexico;
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Anna R. Giuliano
eCenter for Infection Research in Cancer, Moffitt Cancer Center & Research Institute, Tampa, FL 33612
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Greg Dwyer
aDepartment of Ecology and Evolution, University of Chicago, Chicago, IL 60637;
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Sarah Cobey
aDepartment of Ecology and Evolution, University of Chicago, Chicago, IL 60637;
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  1. Edited by Burton H. Singer, University of Florida, Gainesville, FL, and approved November 10, 2017 (received for review August 23, 2017)

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    Fig. 1.

    (A) Average prevalence of HPV types in the study population, with SEs calculated across visits. (B) Prevalence over time of the six types analyzed.

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    Fig. 2.

    Dynamics for one individual host i and one HPV type j under the additional risk model (Eq. 4). S and I denote susceptible and infected, respectively. The duration of each infection is drawn from a gamma distribution with mean 1/γj.

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    Fig. 3.

    (A) Log estimate of the additional risk d by sexual subclass for each HPV type [maximum likelihood estimate (MLE) and 95% confidence interval]. (B) Predicted number of unique individuals infected with HPV16 during follow-up across 1,000 simulations under the additional risk model compared with the memoryless model and the data.

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    Fig. 4.

    Inferred effect of host-specific covariates (maximum likelihood parameter estimate and the 95% confidence interval). Colored cells denote statistically significant positive (blue) and negative (red) effects.

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High HPV prevalence arises by recurring infection
Sylvia L. Ranjeva, Edward B. Baskerville, Vanja Dukic, Luisa L. Villa, Eduardo Lazcano-Ponce, Anna R. Giuliano, Greg Dwyer, Sarah Cobey
Proceedings of the National Academy of Sciences Dec 2017, 114 (51) 13573-13578; DOI: 10.1073/pnas.1714712114

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High HPV prevalence arises by recurring infection
Sylvia L. Ranjeva, Edward B. Baskerville, Vanja Dukic, Luisa L. Villa, Eduardo Lazcano-Ponce, Anna R. Giuliano, Greg Dwyer, Sarah Cobey
Proceedings of the National Academy of Sciences Dec 2017, 114 (51) 13573-13578; DOI: 10.1073/pnas.1714712114
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Proceedings of the National Academy of Sciences: 114 (51)
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