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Modeling host-seeking behavior of African malaria vector mosquitoes in the presence of long-lasting insecticidal nets.
- Source :
-
Mathematical biosciences [Math Biosci] 2018 Jan; Vol. 295, pp. 36-47. Date of Electronic Publication: 2017 Oct 12. - Publication Year :
- 2018
-
Abstract
- The efficiency of spatial repellents and long-lasting insecticide-treated nets (LLINs) is a key research topic in malaria control. Insecticidal nets reduce the mosquito-human contact rate and simultaneously decrease mosquito populations. However, LLINs demonstrate dissimilar efficiency against different species of malaria mosquitoes. Various factors have been proposed as an explanation, including differences in insecticide-induced mortality, flight characteristics, or persistence of attack. Here we present a discrete agent-based approach that enables the efficiency of LLINs, baited traps and Insecticide Residual Sprays (IRS) to be examined. The model is calibrated with hut-level experimental data to compare the efficiency of protection against two mosquito species: Anopheles gambiae and Anopheles arabiensis. We show that while such data does not allow an unambiguous identification of the details of how LLINs alter the vector behavior, the model calibrations quantify the overall impact of LLINs for the two different mosquito species. The simulations are generalized to community-scale scenarios that systematically demonstrate the lower efficiency of the LLINs in control of An. arabiensis compared to An. gambiae.<br /> (Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Animals
Anopheles parasitology
Anopheles pathogenicity
Computer Simulation
Humans
Malaria prevention & control
Malaria transmission
Markov Chains
Mathematical Concepts
Monte Carlo Method
Mosquito Vectors parasitology
Species Specificity
Host-Seeking Behavior physiology
Insecticide-Treated Bednets statistics & numerical data
Models, Biological
Mosquito Control statistics & numerical data
Mosquito Vectors pathogenicity
Subjects
Details
- Language :
- English
- ISSN :
- 1879-3134
- Volume :
- 295
- Database :
- MEDLINE
- Journal :
- Mathematical biosciences
- Publication Type :
- Academic Journal
- Accession number :
- 29031707
- Full Text :
- https://doi.org/10.1016/j.mbs.2017.10.005