A global assessment of surveillance methods for dominant malaria vectors

van de Straat, Bram, Russell, Tanya L., Staunton, Kyran M., Sinka, Marianne E., and Burkot, Thomas R. (2021) A global assessment of surveillance methods for dominant malaria vectors. Scientific Reports, 11. 15337.

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Abstract

The epidemiology of human malaria differs considerably between and within geographic regions due, in part, to variability in mosquito species behaviours. Recently, the WHO emphasised stratifying interventions using local surveillance data to reduce malaria. The usefulness of vector surveillance is entirely dependent on the biases inherent in the sampling methods deployed to monitor mosquito populations. To understand and interpret mosquito surveillance data, the frequency of use of malaria vector collection methods was analysed from a georeferenced vector dataset (> 10,000 data records), extracted from 875 manuscripts across Africa, the Americas and the Asia-Pacific region. Commonly deployed mosquito collection methods tend to target anticipated vector behaviours in a region to maximise sample size (and by default, ignoring other behaviours). Mosquito collection methods targeting both host-seeking and resting behaviours were seldomly deployed concurrently at the same site. A balanced sampling design using multiple methods would improve the understanding of the range of vector behaviours, leading to improved surveillance and more effective vector control.

Item ID: 68950
Item Type: Article (Research - C1)
ISSN: 2045-2322
Copyright Information: Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Funders: Bill and Melinda Gates Foundation (BMGF), ZOOMAL, Australian Centre for International Agricultural Research (ACIAR)
Projects and Grants: BMGF Contract No. 18931, ZOOMAL #LS-2019-116
Date Deposited: 17 Aug 2021 01:25
FoR Codes: 42 HEALTH SCIENCES > 4206 Public health > 420699 Public health not elsewhere classified @ 100%
SEO Codes: 20 HEALTH > 2004 Public health (excl. specific population health) > 200406 Health protection and disaster response @ 100%
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