FAKTOR-FAKTOR RISIKO KEJADIAN DEMAM BERDARAH DENGUE (DBD) DAN PEMETAAN RESISTENSI NYAMUK AEDES AEGYPTI DI KECAMATAN WONOGIRI KABUPATEN WONOGIRI TAHUN 2010

HF Background: Dengue hemorrhagic fever is a problem in tropical and sub tropical countries. In Wonogiri District, the IR of DHF cases in 2009 was 3.64 per 10,000 population with CFR of 0.52%, distributing in 13 sub districts and 48 villages having DHF endemics. Wonogiri sub district is a D endemic with IR of the cases in 2009 was 14.86 per 10,000 population with CFR of 1.43%. The factors of DHF incidences, the resistance of Aedes aegypti on insecticide used for DHF controlling and case dispersion pattern which is not yet known. ces Objective: To obtain a description on dispersion pattern of DHF patients and to find out risk factors that were related to DHF inciden in Wonogiri sub district in 2010 that included educational level, occupation status, Maya index, and mosquito resistance. ir - Method: This was an observational-analytical study with pa matched case-control study design. Quantitative data analyses used univariable analysis with frequency distribution, bivariable analysis with chi-square (� 2 ) test according to McNemar, multivariable analysis with conditional logistic regression, insecticide resistance with standard deviation of Absorbance Value (AV) and cluster with nearest neighbour analysis. T here was not a signi Result: ficant relationship between educational level and DHF incidences (p value > 0.05). Unemployed (p value = 0,0017, OR = 4,

Assessing the impact of booster vaccination on diphtheria transmission: Mathematical modeling and risk zone mapping

The COVID-19 pandemic caused significant disruptions in the healthcare system, affecting vaccinations and the management of diphtheria cases. As a consequence of these disruptions, numerous countries have experienced a resurgence or an increase in diphtheria cases. West Java province in Indonesia is identified as one of the high-risk areas for diphtheria, experiencing an upward trend in cases from 2021 to 2023. To analyze the situation, we developed an SIR model, which integrated DPT and booster vaccinations to determine the basic reproduction number, an essential parameter for infectious diseases. Through spatial analysis of geo-referenced data, we identified hotspots and explained diffusion in diphtheria case clusters. The calculation of R0 resulted in an R0 = 1.17, indicating the potential for a diphtheria outbreak in West Java. To control the increasing cases, one possible approach is to raise the booster vaccination coverage from the current 64.84% to 75.15%, as suggested by simulation results. Furthermore, the spatial analysis revealed that hot spot clusters were present in the western, central, and southern regions, posing a high risk not only in densely populated areas but also in rural regions. The diffusion pattern of diphtheria clusters displayed an expansion-contagious pattern. Understanding the rising trend of diphtheria cases and their geographic distribution can offer crucial insights for government and health authorities to manage the number of diphtheria cases and make informed decisions regarding the best prevention and intervention strategies