Epidemiology of malaria and district-level factors associated with malaria elimination in Sumatra region, Indonesia: a retrospective analysis of surveillance data
Lestari, K. D. D.; Surendra, H.; Djaafara, B. A.; Fadilah, I.; Ekawati, L. L.; Susanto, H.; Prameswari, H. D.; Fajariyani, S. B.; Supriyanto, D.; Herdiana, H.; Conway, E.; Charoen, P.; Lawpoolsri, S.; Pan-ngum, W.; Elyazar, I.
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BackgroundAs transmission declines, malaria is likely to become more spatially and demographically concentrated. This study investigated individual-level malaria characteristics and district-level factors associated with elimination in Sumatra, Indonesia. MethodsWe analysed individual-level data of 13,386 reported malaria cases from 2019 to 2021. Logistic regression was used to examine individual-level factors associated with imported cases, and district-level socioeconomic and environmental factors associated with elimination. Spatial clustering of indigenous cases was assessed using Global Morans I and SaTScan. FindingsAmong reported cases, 71.8% (9,617) were P. vivax, 18.4% (2,467) P. falciparum, and 2.8% (369) probable P. knowlesi. Of 11,390 investigated cases, 8,748 (76.8%) were indigenous, 1,741 (15.3%) imported, and 901 (7.9%) unclassified. Imported cases were associated with working age, males (aOR 1.73; 95% CI 1.47-2.04), working in mobile and migrant population-related occupations (aOR 1.21; 95% CI 1.01-1.43), diagnosed at hospitals or clinics (aOR 1.31; 95% CI 1.06-1.61), infected with P. falciparum (aOR 1.39; 95% CI 1.16-1.67), and hospitalised (aOR 19.77; 95% CI 16.48-23.77). At district level, higher human development index (aOR 1.15; 95% CI 1.01-1.34), lower historical annual parasite incidence (aOR 0.46; 95% CI 0.29-0.69), and fewer endemic neighbours (aOR 0.78; 95% CI 0.67-0.89) were associated with a higher likelihood of elimination. Spatial analysis revealed clustering tendencies, with localised clusters for P. falciparum, P. vivax, and probable P. knowlesi. InterpretationImported malaria, local clusters, and socioeconomic and environmental factors affecting the elimination progress. This highlights the need for strengthened surveillance and targeted interventions. FundingAustralian DFAT under SPARK project and WHO Indonesia under TSA of MOTION project.
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