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.

Paediatric dengue infection in Cirebon, Indonesia: a temporal and spatial analysis of notified dengue incidence to inform surveillance.

BACKGROUND: The recent situation of dengue infection in Cirebon district is concerning due to an upsurge trend since the year 2010. The largest dengue outbreak was reported in 2016 which has affected more than 1600 children. A study was conducted to explore the temporal variability of dengue outbreak in Cirebon's child population in during 2011-2017, and to assess the short-term effects of climatic and environmental factor on dengue incidence. In addition, the spatial pattern of dengue incidence in children and high-risk villages were investigated. METHODS: A total of 4597 confirmed dengue cases in children notified from January 2011 to December 2017 were analysed. Seasonal decomposition analysis was carried out to examine the annual seasonality. A generalized linear model (GLM) was applied to assess the short-term effect of climate and normalized difference vegetation index (NDVI) on dengue incidence. The incidence rate ratio (IRR) of the final model was reported. Spatial analyses were conducted by using Moran's I and local indicator of spatial association (LISA) analyses to explore geographical clustering in incidence and to identify high-risk villages for dengue, respectively. RESULTS: An annual dengue epidemic period was observed with peaks occurring every January/February. Based on the GLM, temperature at a lag 4 months (IRR = 1.27; 95% confidence interval, 95% CI: 1.22-1.31, P < 0.001), rainfall at a lag 2 months (IRR = 0.99, 95% CI: 0.99-0.99, P < 0.001), humidity at lag 0 month (IRR = 1.05, 95% CI: 1.04-1.06, P < 0.001) and NDVI at a lag 1 month (IRR = 3.07, 95% CI: 1.94-4.86, P < 0.001) were associated with dengue incidence in children. The dengue incidence in children was spatially varied and clustered at the village level across Cirebon. During 2011-2017, a total of 38 high-risk villages for dengue were identified, which were mainly located in the northern part of Cirebon. CONCLUSIONS: Seasonal patterns of dengue incidence in children in Cirebon were strongly associated with rainfall, temperature, humidity and NDVI variability, suggesting that climatic and environmental data could be used to help predict dengue outbreaks. Our spatial analysis revealed a clustered pattern in dengue incidence and high-risk villages for dengue across Cirebon, suggesting that effective interventions such as vector surveillance and school-based campaigns should be prioritized around the identified high-risk villages. Temporal and spatial analytical tools could be utilized to support local health authorities to apply timely and targeted public health interventions and help better planning and decision-making in order to minimize the impact of dengue outbreaks.

Molecular surveillance of Dengue in Sukabumi, West Java province, Indonesia.

INTRODUCTION: Dengue is endemic and affects people in all Indonesian provinces. Increasing dengue cases have been observed every year in Sukabumi in West Java province. Despite the endemicity, limited data is available on the genetic of dengue viruses (DENV) circulating in the country. To understand the dynamics of dengue disease, we performed molecular and serological surveillance of dengue in Sukabumi. METHODOLOGY: A total of 113 patients were recruited for this study. Serological data were obtained using anti-dengue IgM and IgG tests plus dengue NS1 antigen detection. Dengue detection and serotyping were performed using real-time RT-PCR. Viruses were isolated and the envelope genes were sequenced. Phylogenetic and evolutionary analyses were performed to determine the genotype of the viruses and their evolutionary rates. RESULTS: Real-time RT-PCR detected DENV in 25 (22%) of 113 samples. Serotyping revealed the predominance of DENV-2 (16 isolates, 64%), followed by DENV-1 (5 isolates, 20%), and DENV-4 (4 isolates, 16%). No DENV-3 was detected in the samples. Co-circulation of genotype I and IV of DENV-1 was observed. The DENV-2 isolates all belonged to the Cosmopolitan genotype, while DENV-4 isolates were grouped into genotype II. Overall, their evolutionary rates were similar to DENV from other countries. CONCLUSIONS: We revealed the distribution of DENV serotypes and genotypes in Sukabumi. Compared to data obtained from other cities in Indonesia, we observed the differing predominance of DENV serotypes but similar genotype distribution, where the infecting viruses were closely related with Indonesian endemic viruses isolated previously.