Geographical variation may likely influence the effectiveness of prevention efforts for malaria across Indonesia, in addition to factors at the individual level, household level, and contextual factors. This study aimed to describe preventive practices at individual and a household levels applied by rural communities in five provinces in eastern Indonesia and its association with the incidence of malaria among adult (≥15 years) populations. This study analyzed a subset of data of nationally representative community-based survey 2018 Riset Kesehatan Dasar (Riskesdas). Data for socio-demographic (age, gender, education and occupation) and preventive behaviors (use of mosquito bed nets while slept, insecticide-treated mosquito nets (ITNs), mosquito repellent, mosquito electric rackets, mosquito coil/electric anti-mosquito mats, and mosquito window screen) were collected. Data were analyzed using bivariate and multivariable logistic regression model. Total of 56,159 respondents (n = 23,070 households) living in rural areas in Maluku (n = 8044), North Maluku (n = 7356), East Nusa Tenggara (n = 23,254), West Papua (n = 5759) and Papua (n = 11,746) were included in the study. In the multivariable models, using a bed net while slept likely reduced the odds of self-reported malaria among Maluku participants. Reduced odds ratios of self-reported malaria were identified in those participants who used ITNs (North Maluku, ENT, Papua), repellent (Maluku, West Papua, Papua), anti-mosquito racket (ENT), coil (Maluku, North Maluku, Papua) and window screen (West Papua, Papua). Our study concluded that the protective effects of preventive practices were varied among localities, suggesting the need for specific intervention programs.

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. 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. 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. 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.

Malaria is still an important parasitic infectious disease that affecting poor and vulnerable communities in many developing countries, including Indonesia. During the period of 2010–2017, there have been approximately 2.2 million confirmed malaria cases reported across Indonesia. This study aimed to identify individual, household and village-level factors associated with self-reported malaria among adults more than 15 years of age in Maluku, West Papua and Papua province. This study analysed a subset of the data from nationally representative population-based Indonesian National Basic Health Research (Riset Kesehatan Dasar) (N = 1,027,763 in 294,959 households in 33 provinces) in 2013. Total of 41,079 individuals (20,326 males and 20,753 females) aged ≥ 15 years in 19,269 households in Maluku, West Papua and Papua provinces were included. Participants were interviewed if they ever had been diagnosed and laboratory confirmed of having malaria by physician in the past 12 months. A mixed effects multilevel logistic regression models were developed to assess the associations between socio-demographical variables at individual, household and village level and self-reported malaria. Individuals aged ≥ 15 years in 701 villages in Maluku (n = 11,919), West Papua (n = 8003) and Papua (n = 21,157) were analysed. In all provinces, gender distribution was equally-represented. The prevalence of self-reported malaria was 4.1% (Maluku), 12.4% (West Papua) and 18.8% (Papua). At the individual level, primary industry workers (OR 1.29, 95% CI 1.15–1.46 [Maluku]; OR 1.17, 95% CI 1.09–1.25 [Papua]) and having higher education were associated with self-reporting malaria (OR 0.67, 95% CI 0.53–0.83 [Maluku]; OR 1.27, 95% CI 1.15–1.40 [Papua]). Household level factors include having bed net and better off wealth index were associated with increased self-reporting malaria among West Papua (OR 1.21; 95% CI 1.09–1.34 and OR 1.38; 95% CI 1.17–1.65, respectively) and Papuan (OR 1.12; 95% CI 1.02–1.23 and OR 1.33; 95% CI 1.11–1.57, respectively) adults. Increased odds of self-reporting malaria was associated with time required to reach healthcare facility (OR 1.30, 95% CI 1.01–1.67 [Maluku]). Contextual village-level characteristics such as living in rural (OR 1.31, 95% CI 1.12–1.54 [Maluku]; OR 1.56, 95% CI 1.17–2.07 [West Papua]), higher community education level (OR 1.28, 95% CI 1.02–1.63 [West Papua]; OR 1.45, 95% CI 1.23–1.72 [Papua]), higher community bed net ownerships (OR 0.59 95% CI 0.45–0.77 [West Papua]) were associated with self-reported malaria. Factors associated with self-reported malaria were varied between provinces suggesting locally-specific determinants were exist at individual, household and community-level. This study highlights the need for specific interventions by taking into consideration the contextual factors within the region and involving multi-sectoral collaboration between health authorities and related stakeholders (e.g., bureau of education, bureau of public works and infrastructure) to improve designs in planning and intervention strategies to succesfully eliminate malaria in Maluku and Papua.

Background: Maluku region is one of the vulnerable areas in Indonesia, and this region has extreme geographical conditions with thousands of islands. The study aims to analyze the role of travel time to a hospital in the Maluku region in Indonesia. Material and Methods: This cross-sectional study analyzed the 2018 Indonesian Basic Health Survey data. The research included 14,625 respondents by stratification and multistage random sampling. The study used hospital utilization as an outcome variable and the travel time to the hospital as an exposure variable. Moreover, the study employed nine control variables: province, residence, age, gender, marital status, education, employment, wealth, and health insurance. The study performed binary logistic regression to interpret the data in the final analysis. Results: The result shows a relationship between travel time and hospital utilization. Someone with a travel time of 30 min or less to the hospital has a 1.792 (95% CI 1.756–1.828) higher probability than those with a travel time of more than 30 min. The results of this analysis find that shorter travel time to the hospital has a better possibility of hospital utilization. In addition, the study also found eight control variables to have a significant relationship with hospital utilization. Conclusion: Shorter travel time to the hospital is more likely to be utilized in the Maluku region.

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.

The government targets malaria elimination in Java and Bali by 2023. But until 2020, Pangandaran and Pandeglang Regency haven’t received malaria-free certification. This qualitative study was conducted to provide an overview of Pangandaran and Pandeglang malaria control implementation by comparing it to Activity Indicators based on the Indonesian Minister of Health Decree on malaria elimination. In-depth interviews, using thematically interview guidelines, were conducted to 48 key informants such as policyholders and people in charge of health programs and cross-sectoral at the provincial, district, sub-district, and village levels. Thematic analysis was used in the theme of policy implementation, budget, facilities and infrastructures, human resources, and cross-sector cooperation. The result shows that malaria control is implemented according to the decree, but some activities haven’t been done. The analysis on policy implementation theme shows that both districts have carried out according to the guidelines, with innovation in the form of establishing Posmaldes (village malaria post) in Ujung Kulon National Park in Pandeglang. APBD, APBN, and Global Fund are used as budget sources. Both districts stated that facilities and infrastructures are sufficiently available, but there is a lack in human resources’ quantity and varying degrees of competencies. There is also a lack of cross-sector cooperation because malaria control hasn’t become a priority in those sectors and they are only acting as supports to the health sector. Efforts to control malaria are considered less optimal due to the absence of malaria elimination regulations, varied human resource capabilities, and the limitation in the duties and functions of cross-sectors.