Anopheline Diversity in Indonesia: An Evaluation of Animal-Baited Sampling Techniques.

Indonesia has rich Anopheline (Diptera: Culicidae) mosquito species living in various types of ecosystems. The study was conducted to profile and compare Anopheles diversity, equitability, and dominance in various ecosystems using different animal-based sampling techniques. The present study analyzed a subset of data collected from a nation-wide vector and animal reservoirs survey in 2016. Analyses were restricted to three ecosystem types (forest, nonforest, and coastal areas) in Java and Sumatera Islands. A total of 5,477 Anopheles were collected by using animal-baited (n = 1,909) and animal-baited trap nets (n = 1,978), consisting of 23 Anopheline species. Overall, Anopheles vagus was the most abundant species, followed by An. subpictus and An. barbirostris. Among the three ecosystems, the forest had a higher diversity index (H' = 1.98), but each ecosystem has its specific predominant species. Compared with the animal-baited method, the Anopheles abundance collected by animal-baited trap nets was two-fold higher. Ecosystem, elevation, and sampling methods were associated with the abundance of female Anopheles (P-value < 0.001). Our findings revealed that Anopheles were found in a different ecosystem, indicating the potential of malaria transmission. This suggests that improved malaria vector surveillance is essential in all types of ecosystem. Furthermore, the study suggested that animal-baited trap nets could be used as the standard method of outdoor resting sampling in Indonesia in addition to the traditional human landing collection approach.

Sub-national disparities in accessing anti-malarial drug treatment in eastern Indonesia.

BACKGROUND: Poor access to health care providers was among the contributing factors to less prompt and ineffective malaria treatment. This limitation could cause severe diseases in remote areas. This study examined the sub-national disparities and predictors in accessing anti-malarial drug treatment among adults in Eastern Indonesia. METHODS: The study analyzed a subset of the 2018 National Basic Health Survey conducted in all 34 provinces in Indonesia. We extracted socio-demographic data of 4655 adult respondents diagnosed with malaria in the past 12 months in five provinces in Eastern Indonesia. The association between socio-demographic factors and the access to anti-malarial drug treatment was assessed using logistic regression. RESULTS: Over 20% of respondents diagnosed with malaria within last 12 months admitted that they did not receive anti-malarial drug treatment (range 12-29.9%). The proportion of untreated cases was 12.0% in East Nusa Tenggara, 29.9% in Maluku, 23.1% in North Maluku, 12.7% in West Papua, and 15.6% in Papua. The likelihood of receiving anti-malarial drug treatment was statistically lower in Maluku (adjusted OR = 0.258; 95% CI 0.161-0.143) and North Maluku (adjusted OR = 0.473; 95% CI 0.266-0.840) than those in Eastern Nusa Tenggara (reference). Urban respondents were less likely to receive malaria treatment than rural (adjusted OR = 0.545; 95% CI 0.431-0.689). CONCLUSIONS: This study found that there were sub-national disparities in accessing anti-malarial drug treatment in Eastern Indonesia, with a high proportion of untreated malaria cases across the areas. Findings from this study could be used as baseline information to improve access to anti-malarial drug treatment and better target malaria intervention in Eastern Indonesia.

Geographical heterogeneity and socio-ecological risk profiles of dengue in Jakarta, Indonesia.

The aim of this study was to assess the role of climate variability on the incidence of dengue fever (DF), an endemic arboviral infection existing in Jakarta, Indonesia. The work carried out included analysis of the spatial distribution of confirmed DF cases from January 2007 to December 2018 characterising the sociodemographical and ecological factors in DF high-risk areas. Spearman's rank correlation was used to examine the relationship between DF incidence and climatic factors. Spatial clustering and hotspots of DF were examined using global Moran's I statistic and the local indicator for spatial association analysis. Classification and regression tree (CART) analysis was performed to compare and identify demographical and socio-ecological characteristics of the identified hotspots and low-risk clusters. The seasonality of DF incidence was correlated with precipitation (r=0.254, P<0.01), humidity (r=0.340, P<0.01), dipole mode index (r= -0.459, P<0.01) and Tmin (r= -0.181, P<0.05). DF incidence was spatially clustered at the village level (I=0.294, P<0.001) and 22 hotspots were identified with a concentration in the central and eastern parts of Jakarta. CART analysis showed that age and occupation were the most important factors explaining DF clustering. Areaspecific and population-targeted interventions are needed to improve the situation among those living in the identified DF high-risk areas in Jakarta.