An investigation of geographical clusters of leptospirosis during the outbreak in Pangandaran, West Java, Indonesia.

Leptospirosis is neglected in many tropical developing countries, including Indonesia. Our research on this zoonotic disease aimed to investigate epidemiological features and spatial clustering of recent leptospirosis outbreaks in Pangandaran, West Java. The study analysed data on leptospirosis notifications between September 2022 and May 2023. Global Moran I and local indicator for spatial association (LISA) were applied. Comparative analysis was performed to characterise the identified hotspots of leptospirosis relative to its neighbourhoods. A total of 172 reported leptospirosis in 40 villages from 9 sub-districts in Pangandaran District were analysed. Of these, 132 cases (76.7%) were male. The median age was 49 years (interquartile range [IQR]: 34-59 years). Severe outcomes including renal failure, lung failure, and hepatic necrosis were reported in up to 5% of the cases. A total of 30 patients died, resulting in the case fatality rate (CFR) of 17.4%. Moran's I analysis showed significant spatial autocorrelation (I=0.293; p=0.002) and LISA results identified 7 High-High clusters (hotspots) in the Southwest, with the total population at risk at 26,184 people. The hotspots had more cases among older individuals (median age: 51, IQR: 36-61 years; p<0.001), more farmers (79%, p=0.001) and more evidence of the presence of rats (p=0.02). A comprehensive One Health intervention should be targeted towards these high-risk areas to control the transmission of leptospirosis. More empirical evidence is needed to understand the role of climate, animals and sociodemographic characteristics on the transmission of leptospirosis in the area studied.

Variation of preventive practices and its association with malaria infection in eastern Indonesia: Findings from community-based survey.

BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSION: Our study concluded that the protective effects of preventive practices were varied among localities, suggesting the need for specific intervention programs.

Individual and contextual factors predicting self-reported malaria among adults in eastern Indonesia: findings from Indonesian community-based survey.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Space-time scan statistics of 2007-2013 dengue incidence in Cimahi City, Indonesia.

Four dengue serotypes threatened more than 200 million people and has spread to over 400 districts in Indonesia. Furthermore, 26 districts in most densely populated province, West Java, have been declared as hyperendemic areas. Cimahi is an endemic city with the highest population (14,969 people per square kilometer). Evidence on distribution pattern of dengue cases is required to discover the spread of dengue cases in Cimahi. A study has been conducted to detect clusters of dengue incidence during 2007-2013. A temporal spatial analysis was performed using SaTScan™ software incorporated confirmed dengue monthly data from the Municipality Health Office and population data from a local Bureau of Statistics. A retrospective space-time analysis with a Poisson distribution model and monthly precision was performed. Our results revealed a significant most likely cluster (p<0.001) throughout period of study. The most likely cluster was detected in the centre of the city and moved to the northern region of Cimahi. Cimahi, Karangmekar, and Cibabat village were most likely cluster in 2007-2010 (p <0.001; RR = 2.16-2.98; pop at risk 12% total population); Citeureup were detected as the most likely cluster in 2011-2013 (p <0.001; RR 5.77), respectively. Temporaly, clusters were detected in the first quarter of each year each. In conclusion, a dynamic spread of dengue initiated from the centre to its surrounding areas during the period 2007-2013. Our study suggests the use of GIS to strengthen case detection and surveillance. An in-depth investigation to relevant risk factors in high-risk areas in Cimahi city is encouraged.