Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 111, Issue 26, Pages E2694-E2702Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1314933111
Keywords
disease ecology; emerging infections; arthropod-borne virus
Categories
Funding
- Research and Policy for Infectious Disease Dynamics program of the Science and Technology Directory, Department of Homeland Security
- Fogarty International Center, National Institutes of Health (NIH)
- NIH [RO1 AI-42332, RO1 AI069341, R01AI091980]
- Innovative Vector Control Consortium
- US Department of Defense Global Emerging Infections Systems Research Program [847705.82000.25GB.B0016]
- Military Infectious Disease Research Program [6000 RAD1.S.B0302, S0002 04 LI, DOD S0017 03LI, DOD 32519, S0088 06 NM]
- Deployed Warfighter Protection Program [DOD S0002 04]
- Wellcome Trust [08571]
- National Science Foundation [DMS 1246991]
- Direct For Mathematical & Physical Scien
- Division Of Mathematical Sciences [1246991] Funding Source: National Science Foundation
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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 similar to 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 serotype-specific 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 unprecedented in detail, providing a basis for understanding the persistence of this rapidly emerging pathogen and improving disease prevention programs.
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