ArticleEpidemics2023
Malaria temporal dynamic clustering for surveillance and intervention planning.
Article in Epidemics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Household malaria risk perception in Ethiopia: multilevel and spatial analysis using the 2022-2023 National Health Equity Survey.BMC public health · 2026Article
- Spatiotemporal trends in P. falciparum malaria and identification of high-risk villages in Eastern Myanmar: an 8-year observational study.Scientific reports · 2025Observational
- Monitoring individual rice field flooding dynamics over a large scale to improve mosquito surveillance and control.Malaria journal · 2025Article
- Imported malaria in Cabo Verde (2010-2024): Risks to post-elimination stability.PLOS global public health · 2025Article
- 'Forest malaria' in Myanmar? Tracking transmission landscapes in a diversity of environments.Parasites & vectors · 2023Article
- Geo-epidemiology of malaria incidence in the Vhembe District to guide targeted elimination strategies, South-Africa, 2015-2018: a local resurgence.Scientific reports · 2023Article
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Authors and funding
12 authors.
Funding
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Abstract
backgroundTargeting interventions where most needed and effective is crucial for public health. Malaria control and elimination strategies increasingly rely on stratification to guide surveillance, to allocate vector control campaigns, and to prioritize access to community-based early diagnosis and treatment (EDT). We developed an original approach of dynamic clustering to improve local discrimination between heterogeneous malaria transmission settings.
methodsWe analysed weekly malaria incidence records obtained from community-based EDT (malaria posts) in Karen/Kayin state, Myanmar. We smoothed longitudinal incidence series over multiple seasons using functional transformation. We regrouped village incidence series into clusters using a dynamic time warping clustering and compared them to the standard, 5-category annual incidence standard stratification.
resultsWe included 1115 villages from 2016 to 2020. We identified eleven P. falciparum and P. vivax incidence clusters which differed by amplitude, trends and seasonality. Specifically the 124 villages classified as "high transmission area" in the standard P. falciparum stratification belonged to the 11 distinct groups when accounting to inter-annual trends and intra-annual variations. Likewise for P. vivax, 399 "high transmission" villages actually corresponded to the 11 distinct dynamics.
conclusionOur temporal dynamic clustering methodology is easy to implement and extracts more information than standard malaria stratification. Our method exploits longitudinal surveillance data to distinguish local dynamics, such as increasing inter-annual trends or seasonal differences, providing key information for decision-making. It is relevant to malaria strategies in other settings and to other diseases, especially when many countries deploy health information systems and collect increasing amounts of health outcome data.
fundingThe Bill & Melinda Gates Foundation, The Global Fund against AIDS, Tuberculosis and Malaria (the Regional Artemisinin Initiative) and the Wellcome Trust funded the METF program.
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