Time-varying, serotype-specific force of infection of dengue virus

• Type of Material: Article
• Authors: Robert C. Reiner, National Institutes of Health; Steven T. Stoddard, National Institutes of Health; Brett M. Forshey, US Naval Medical Research Unit No. 6 Lima and Iquitos; Aaron A. King, National Institutes of Health; Alicia M. Ellis, National Institutes of Health; Alun L. Lloyd, National Institutes of Health; Kanya C. Long, National Institutes of Health; Claudio Rocha, US Naval Medical Research Unit No. 6 Lima and Iquitos; Stalin Vilcarromero, US Naval Medical Research Unit No. 6 Lima and Iquitos; Helvio Astete, US Naval Medical Research Unit No. 6 Lima and Iquitos; Isabel Bazan, US Naval Medical Research Unit No. 6 Lima and Iquitos; Audrey Lenhart, Emory University; Gonzalo Vazquez Prokopec, Emory University; Valerie A. Paz-Soldan, Tulane University School of Public Health and Tropical Medicine; Philip J. McCall, Liverpool School of Tropical Medicine; Uriel Kitron, Emory University; John P. Elder, San Diego State University; Eric S. Halsey, US Naval Medical Research Unit No. 6 Lima and Iquitos; Amy C. Morrison, University of California Davis; Tadeusz J. Kochel, US Naval Medical Research Unit No. 6 Lima and Iquitos; Thomas W. Scott, National Institutes of Health
• Language: English
• Date: 2014-07-01
• Publisher: National Academy of Sciences
• Publication Version: Final Published Version
• Copyright Statement: Freely available online through the PNAS open access option.
• Final Published Version (URL): http://dx.doi.org/10.1073/pnas.1314933111
• Title of Journal or Parent Work: Proceedings of the National Academy of Sciences
• ISSN: 0027-8424
• Volume: 111
• Issue: 26
• Start Page: E2694
• End Page: E2702
• Grant/Funding Information: This work was supported by the Research and Policy for Infectious Disease Dynamics program of the Science and Technology Directory, Department of Homeland Security, and Fogarty International Center, National Institutes of Health (NIH); NIH Grants RO1 AI-42332 and RO1 AI069341; Innovative Vector Control Consortium; US Department of Defense Global Emerging Infections Systems Research Program Work Unit 847705.82000.25GB.B0016; Military Infectious Disease Research Program Work Units 6000 RAD1.S.B0302, S0002 04 LI, DOD S0017 03LI, DOD 32519, and S0088 06 NM; Deployed Warfighter Protection Program DOD S0002 04; and Wellcome Trust Grant 08571.; A.L.L. acknowledges support from NIH Grant R01AI091980 and National Science Foundation Grant DMS 1246991.
• Keywords: disease ecology; Models, Biological; Dengue Virus; Time Factors; arthropod-borne virus; emerging infections; Public Health Surveillance; Peru; Humans; Dengue; Longitudinal Studies
• Research Categories: Environmental Sciences; Biology, Entomology

Abstract

Infectious disease models play a key role in public health planning. These models rely on accurate estimates of key transmission parameters such as the force of infection (FoI), which is the percapita risk of a susceptible person being infected. The FoI captures the fundamental dynamics of transmission and is crucial for gauging control efforts, such as identifying vaccination targets. Dengue virus (DENV) is a mosquito-borne, multiserotype pathogen that currently infects ≤390 million people a year. Existing estimates of the DENV FoI are inaccurate because they rely on the unrealistic assumption that risk is constant over time. Dengue models are thus unreliable for designing vaccine deployment strategies. Here, we present to our knowledge the first time-varying (daily), serotype-specific estimates of DENV FoIs using a spline-based fitting procedure designed to examine a 12-y, longitudinal DENV serological dataset from Iquitos, Peru (11,703 individuals, 38,416 samples, and 22,301 serotypespecific DENV infections from 1999 to 2010). The yearly DENV FoI varied markedly across time and serotypes (0-0.33), as did daily basic reproductive numbers (0.49-4.72). During specific time periods, the FoI fluctuations correlated across serotypes, indicating that different DENV serotypes shared common transmission drivers. The marked variation in transmission intensity that we detected indicates that intervention targets based on one-time estimates of the FoI could underestimate the level of effort needed to prevent disease. Our description of dengue virus transmission dynamics is u nprecedented in detail, providing a basis for understanding the persistence of this rapidly emerging pathogen and improving disease prevention programs.