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Author Notes:

Corresponding author: Tel: +202 731 4896; E-mail: dlsmith@jhsph.edu

See publication for full list of author contributions.

The findings and conclusions in this report are those of the author(s) and do not necessarily represent the views of the U.S. Department of Health and Human Services or its components, or the U.S. Department of Defense.

Competing interests: None declared.

Ethical approval: Not required.

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Research Funding:

This work was primarily supported by the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science and Technology Directory, Department of Homeland Security, and Fogarty International Center, National Institutes of Health.

DLS acknowledges funding from the Bloomberg Family Foundation.

ALL acknowledges funding from the NIH [R01-AI091980] and NSF [RTG/DMS -1246991].

DLS and AJT acknowledge funding from NIH/NIAID [U19AI089674] and the Bill and Melinda Gates Foundation [49446].

AJT is also supported by a grant from the Bill and Melinda Gates Foundation [1032350].

CMB acknowledges additional funding from the US Centers for Disease Control and Prevention [5 U01 EH000418].

LFC is funded by the Leading Program in Tropical and Emerging Communicable Diseases of Nagasaki University.

EM and BKS acknowledge funding from the NIH [R01 AI069387-01A1].

SIH is also funded by a Senior Research Fellowship from the Wellcome Trust [095066].

PWG is a Medical Research Council Career Development Fellow [K00669X] and receives support from the Bill and Melinda Gates Foundation [OPP1068048].

TWS acknowledges funding from the Bill & Melinda Gates Foundation [OPP52250], the Innovative Vector Control Consortium, and the NIH [R01-AI069341, R01-AI091980, and R01-GM08322].

EYK acknowledges funding from MIDAS [U01GM070708] and NIH [DP1OD003874].

AJG is partially supported by the National Science Foundation under Grant No. 0801544 in the Quantitative Spatial Ecology, Evolution and Environment Program at the University of Florida. HCJG is supported by the Foundation for the National Institutes of Health through the Vector-Based Control of Transmission: Discovery Research program of the Grand Challenges in Global Health Initiative.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Public, Environmental & Occupational Health
  • Tropical Medicine
  • PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH, SCI
  • TROPICAL MEDICINE
  • Dengue
  • Filariasis
  • Malaria
  • Mosquito-borne pathogen transmission
  • Vector control
  • West Nile virus
  • DENGUE VIRUS TRANSMISSION
  • ENTOMOLOGICAL INOCULATION RATE
  • PLASMODIUM-FALCIPARUM MALARIA
  • MATHEMATICAL-MODELS
  • HUMAN MOVEMENT
  • LYMPHATIC FILARIASIS
  • POPULATION-DYNAMICS
  • ANOPHELES-GAMBIAE
  • AEDES-AEGYPTI
  • VECTOR

Recasting the theory of mosquito-borne pathogen transmission dynamics and control

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Journal Title:

Transactions of The Royal Society of Tropical Medicine and Hygiene

Volume:

Volume 108, Number 4

Publisher:

, Pages 185-197

Type of Work:

Article | Final Publisher PDF

Abstract:

Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of theworld. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald's formula for R 0 and its entomological derivative, vectorial capacity, are nowused to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross-Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context formosquito blood feeding, themovement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control. © The Author 2014. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.

Copyright information:

© The Author 2014. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 3.0 Unported License (http://creativecommons.org/licenses/by/3.0/).

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