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

  • Robert C. Reiner
  • , Steven T. Stoddard
  • , Brett M. Forshey
  • , Aaron A. King
  • , Alicia M. Ellis
  • , Alun L. Lloyd
  • , Kanya C. Long
  • , Claudio Rocha
  • , Stalin Vilcarromero
  • , Helvio Astete
  • , Isabel Bazan
  • , Audrey Lenhart
  • , Gonzalo M. Vazquez-Prokopec
  • , Valerie A. Paz-Soldan
  • , Philip McCall
  • , Uriel Kitron
  • , John P. Elder
  • , Eric S. Halsey
  • , Amy C. Morrison
  • , Tadeusz J. Kochel
  • Thomas W. Scott
  • National Institutes of Health
  • University of California at Davis
  • Iquitos Laboratory
  • University of Michigan, Ann Arbor
  • University of Vermont
  • North Carolina State University
  • Andrews University
  • Liverpool School of Tropical Medicine
  • Centers for Disease Control and Prevention
  • Emory University
  • Tulane University
  • San Diego State University

Research output: Contribution to journalArticlepeer-review

97 Citations (Scopus)

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 per-capita 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 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.

Original languageEnglish
Pages (from-to)E2694-E2702
JournalProceedings of the National Academy of Sciences of the United States of America
Volume111
Issue number26
DOIs
Publication statusPublished - 1 Jul 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Arthropod-borne virus
  • Disease ecology
  • Emerging infections

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