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Updated: Mar 15, 2026
A Multi-detection Assay for Malaria Transmitting Mosquitoes
Published on: February 28, 2015
Malaria risk factor assessment using active and passive surveillance data from Aceh Besar, Indonesia, a low endemic,
Herdiana Herdiana1,2, Chris Cotter3, Farah N Coutrier4
1School of Public Health, University of Queensland, Brisbane, QLD, Australia.
Background:
As malaria transmission declines, it becomes more geographically focused and more likely due to asymptomatic and non-falciparum infections. To inform malaria elimination planning in the context of this changing epidemiology, local assessments on the risk factors for malaria infection are necessary, yet challenging due to the low number of malaria cases.
Methods:
A population-based, cross-sectional study was performed using passive and active surveillance data collected in Aceh Besar District, Indonesia from 2014 to 2015. Malaria infection was defined as symptomatic polymerase chain reaction (PCR)-confirmed infection in index cases reported from health facilities, and asymptomatic or symptomatic PCR-confirmed infection identified in reactive case detection (RACD). Potential risk factors for any infection, species-specific infection, or secondary-case detection in RACD were assessed through questionnaires and evaluated for associations.
Results:
Nineteen Plasmodium knowlesi, 12 Plasmodium vivax and six Plasmodium falciparum cases were identified passively, and 1495 community members screened in RACD, of which six secondary cases were detected (one P. knowlesi, three P. vivax, and two P. falciparum, with four being asymptomatic). Compared to non-infected subjects screened in RACD, cases identified through passive or active surveillance were more likely to be male (AOR 12.5, 95 % CI 3.0-52.1), adult (AOR 14.0, 95 % CI 2.2-89.6 for age 16-45 years compared to <15 years), have visited the forest in the previous month for any reason (AOR 5.6, 95 % CI 1.3-24.2), and have a workplace near or in the forest and requiring overnight stays (AOR 7.9, 95 % CI 1.6-39.7 compared to workplace not near or in the forest). Comparing subjects with infections of different species, differences were observed in sub-district of residence and other demographic and behavioural factors. Among subjects screened in RACD, cases compared to non-cases were more likely to be febrile and reside within 100 m of the index case.
Conclusion:
In this setting, risk of malaria infection in index and RACD identified cases was associated with forest exposure, particularly overnights in the forest for work. In low-transmission settings, utilization of data available through routine passive and active surveillance can support efforts to target individuals at high risk.
