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Updating estimates of Plasmodium knowlesi malaria risk in response to changing land use patterns across Southeast Asia

Abstract:
INTRODUCTION: Malaria transmission is highly spatially heterogeneous. Within Southeast Asia, forested landscapes are associated both with increased malaria transmission and reduced healthcare access. Identifying environments with malaria foci is a priority for control and elimination programmes. METHODS: Here, we integrate health facility and environmental data to identify optimal surveillance approaches across a forested district in the Philippines. We conducted convenience surveys of health facility attendees utilising tablet-based applications to geolocate participant residences. Malaria infection was assessed using both routine (microscopy and rapid diagnostic test) and molecular methods. Integrating remote-sensing derived data, we assessed how fine-scale environmental factors influence the spatial distributions of malaria infections, diagnostic sensitivity and health-seeking behavior. We evaluated costs and probability of detecting malaria foci for multiple surveillance approaches using different diagnostic methods and target populations defined by landscape data. RESULTS: We demonstrate that health facility-based surveys increase the probability of detecting malaria infections by increasing numbers of individuals screened and spatial coverage of surveillance systems. We additionally show sensitivity of routine malaria diagnostics varies spatially, with the decreased sensitivity in forests. By targeting diagnostic methods to high-risk environments, we developed a model approach for how to use landscape data within disease surveillance systems. Risk-based surveillance incorporating forest data is highly cost-effective and increases the probability of detecting malaria foci over three-fold compared to routine surveillance. DISCUSSION: Together, this illustrates the essential role of environmental data in designing risk-based surveillance to provide an operationally feasible and cost-effective method to characterise malaria transmission
Publication status:
Published
Peer review status:
Peer reviewed

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Role:
Author
ORCID:
0000-0002-5202-240X
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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-0590-1444
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Role:
Author
ORCID:
0000-0001-7075-9491
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Role:
Author
ORCID:
0000-0003-1383-3274


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Funder identifier:
10.13039/501100013885
Grant:
BP00500/117/1002
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Funder identifier:
10.13039/100000002
Grant:
R01 AI160457-01
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Funder identifier:
10.13039/501100001782
Grant:
Melbourne Research Scholarship
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Funder identifier:
10.13039/501100000923
Grant:
FT210100034 and DP200100747
More from this funder
Funder identifier:
10.13039/501100000925
Grant:
GNT1134989


Publisher:
Public Library of Science
Journal:
PLoS Neglected Tropical Diseases More from this journal
Volume:
18
Issue:
1
Pages:
e0011570-e0011570
Publication date:
2024-01-22
DOI:
EISSN:
1935-2735
ISSN:
1935-2727


Language:
English
Keywords:
Pubs id:
1927322
Local pid:
pubs:1927322
Source identifiers:
W4391094223
Deposit date:
2026-06-10
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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