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A global assessment of surveillance methods for dominant malaria vectors

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
Publication status:
Published
Peer review status:
Peer reviewed

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Role:
Author
ORCID:
0000-0002-1987-9655
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Role:
Author
ORCID:
0000-0002-0920-6844
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Role:
Author
ORCID:
0000-0001-6812-3320
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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0001-7145-3179
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Role:
Author
ORCID:
0000-0002-8994-6729


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Funder identifier:
10.13039/100000865
Grant:
18931
More from this funder
Funder identifier:
10.13039/501100000974
Grant:
#LS-2019-116


Publisher:
Nature Research
Journal:
Scientific Reports More from this journal
Volume:
11
Issue:
1
Pages:
15337-15337
Article number:
15337
Publication date:
2021-07-28
DOI:
EISSN:
2045-2322
ISSN:
2045-2322


Language:
English
Keywords:
Pubs id:
1191016
Local pid:
pubs:1191016
Source identifiers:
W3185230387
Deposit date:
2026-03-25
ARK identifier:
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