Risk factors for malaria infection and dihydroartemisinin+piperaquine resistance distribution between high and low endemic areas in Indonesia

Abstract

Globally, malaria case is decreasing over decades. This similar trend happens in Indonesia but it is still not even close to elimination. To control and eradicate malaria require a comprehensive and coincident strategy for the parasite and its vector. However, malaria elimination strategy of many countries, including Indonesia, is still considering only treatment which has led to resistance of Plasmodium species over various antimalarial drugs. Recently, resistance to the only and current available drug, artemisinin, has appeared and spread over continents in the world. However, it has not been extensively discovered in Indonesia. Additionally, it was widely known that a poor adherence in a population to antimalarial medication will lead to the development of treatment failure prior to the spread of parasite resistance genetically. Therefore, the objective of the current study is to discover extensively the factors contributing to the development of such resistance in Plasmodium parasite population in Indonesia. The assessment included identification of malaria risk factors and the vector and measurement of adherence level to artemisinin combination therapy in comparison between low and high endemicity areas in Indonesia. The assessment of malaria risk factors and dihydroartemisinin+piperaquine (DHP) population adherence were done by structured questionnaires. A three weeks longitudinal observation of vector biting dynamics was done using human landing catch method in each area. Efficacy study of DHP was done with 42-days follow up according to WHO guideline. Additionally, molecular marker for artemisinin (K13) and piperaquine (Plasmepsin II) were also included. In total, 2364 Anopheles mosquitoes were successfully collected and a difference in number of mosquitoes between low and high endemicity areas was also found. There was also an evidence that the biting time of each area differs significantly. We also found several risk factors of malaria between the two areas and discovered that there was a spatial effect of malaria risk factor between those two areas. Additionally, the population in those two areas had a low level of drug adherence. However, the efficacy of DHP in low and high endemiciy areas remained effective. Although several mutations occurred in K13 gene and multi-copy of Plasmepsin II gene were found, but no association was detected in accordance to treatment failure. The result of entomological assessment indicates that there is a difference in biting time of Anopheles mosquitoes between the studied locations and there is no effect of housing construction in preventing malaria. Malaria risk factor study suggested that the risk factor variable on malaria infection is influenced by area that may reflect the differences in annual parasite incidence (API). Since a low level of population adherence to antimalarial drug medication was found, it needs better monitoring and strategy to elevate adherence level to prevent the deployment of currently available antimalarial drug as seen in other South East Asian countries. Finally, although an efficacious DHP medication was found in study setting, but mutations and elevated number of multi copy of DHP marker was suggesting that the parasite may have developed the ability to resist the medication genetically. Therefore, a careful monitoring of DHP efficacy in Indonesia needs to be done continuously. In conclusion, it is imperative to public policy maker to control malaria case by controlling the risk factor and population adherence level in a population and continuous monitoring of DHP efficacy as well as the strategy needs to consider area-specific.