Evidence map›Paper›PMID 42316253›Full record

ArticleBMC medicine2026

Non-linear age dynamics of malaria infection and fine-scale environmental exposure in rural Uganda.

Max M Lang, Violet Tuhaise, Phionah Kafuko, Aisha Nakato, Asmin Mohamed, Betty Nabatte, Narcis B Kabatereine, Christl A Donnelly, Goylette F Chami

Abstract read
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Article in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Max M LangBig Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Violet TuhaiseMakerere University, College of Natural Sciences, Kampala, Uganda.
Phionah KafukoDivision of Vector-Borne and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda.
Aisha NakatoDivision of Vector-Borne and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda.
Asmin MohamedDivision of Vector-Borne and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda.
Betty NabatteDivision of Vector-Borne and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda.
Narcis B KabatereineDivision of Vector-Borne and Neglected Tropical Diseases, Uganda Ministry of Health, Kampala, Uganda.
Christl A DonnellyDepartment of Statistics, University of Oxford, Oxford, United Kingdom.
Goylette F ChamiBig Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom. goylette.chami@ndph.ox.ac.uk.

Funding

Engineering and Physical Sciences Research Council EP/X021793/1Nuffield Department of Population Health, University of Oxford N/ARobertson Foundation N/AWellcome TrustWellcome Trust 204826/Z/16/Z
6 · The paper itself

Abstract

backgroundAge-specific patterns of malaria are well-established for children aged  < 5 years. Less understood is the epidemiology of malaria in older children and adults, and the influence of granular environmental risk.

methodsWe analyzed data from SchistoTrack, a community-based cohort in rural Uganda. We studied 4308 participants aged 5 to 90 years from 52 villages across three lakeside districts of Mayuge, Buliisa, and Pakwach, with enrollment between January 2022 to February 2024. The primary outcome was malaria infection status by rapid diagnostic test (RDT). Secondary outcomes included microscopy-confirmed infection with parasite density quantification and self-reported fever within the past month. We fitted a generalized additive mixed model (GAMM) with adaptive age smoothing, adjusting for sociodemographic factors, household characteristics, healthcare access, and environmental exposures. Environmental exposure was quantified using the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 satellite imagery (10 m resolution), processed through hexagonal aggregation with Gaussian neighborhood smoothing and validated against field malacology surveys and participatory community mapping.

resultsOverall RDT prevalence was 41.2% (1776/4308), with microscopy prevalence at 32.3% (1363/4219), which was predominantly Plasmodium falciparum (83.1%; 1133/1363). Most infections were low-density ( < 999 parasites/μL; 71.6%; 976/1363). Malaria prevalence showed non-linear age patterns, peaking at 10 to 11 years then declining through adolescence before stabilizing in adulthood. Among RDT-positive individuals, fever prevalence decreased with age from 30.8% in children (aged 5 to 10 years) to 11.2% in adults (aged ≥20 years). Dense vegetation (per unit NDVI increase: Odds Ratio (OR) 3.25, 95% Confidence Interval (CI) 1.33-7.96) and greater distance from government health centers (per log-km: OR 1.87, 95% CI 1.34-2.59) increased the odds of infection. Proximity to vegetated water bodies increased the odds of infection compared to beaches: ponds/swamps (OR 1.65, 95% CI 1.19-2.28), river/river marsh (OR 1.63, 95% CI 1.16-2.31), lake marsh (OR 1.40, 95% CI 1.07-1.83).

conclusionsMalaria prevalence remains high in older children and adults, though with fewer febrile cases, and is influenced by the local environment. Our findings support age-specific interventions targeting school-aged children while maintaining adult surveillance, and using validated environmental indices to guide sub-district resource allocation in high-risk areas.

Indexed as

Environmental ExposureMalariaRural PopulationAdolescentAdultAgedAged, 80 and overAge FactorsChildChild, PreschoolFemaleHumansMaleMiddle AgedNonlinear DynamicsPrevalenceagecommunityenvironmentimmunitymalariapeak shiftrural Africasatellite remote sensing

Identifiers

PMID42316253
PMCPMC13617724

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