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Metode: Penelitian ini menggunakan desain kasus kontrol. Besar sampel dalam penelitian ini sebanyak 121 responden dengan jumlah kasus 31 responden dan kontrol 90 responden. Penelitian ini dilakukan oleh Tim dari mahasiswa FETP FKM UI dan Dinas Kesehatan Kabupaten Garut yang dilaksanakan tanggal 6 9 Februari 2018 di 13 Puskesmas yang dilaporkan adanya kasus. Analisis data dilakukan dengan uji resgresi logistic untuk melihat nilai odds ratio menggunakan stata versi 14,2 di Laboratorium Komputer FKM UI.
Hasil: Pola KLB merupakan propagated epidemic yang terjadi pada umur 1 Tahun 71 Tahun. Kasus Primer terjadi pada minggu 48 Tahun 2017. Analisis multivariat fit model menunjukan status imunisasi berhubungan dengan kejadian difteri (Pvalue = 0,036; OR=3,5; 95% CI = 1,08-11,10) dan riwayat perjalanan berhubungan dengan kejadian difteri (Pvalue = 0,000; OR = 5,4; 95% CI = 2,08-13,93). Efikasi vaksin DPT, DT, Td sebesar 71,4%.
Kesimpulan dan saran: Telah terjadi penularan penyakit dari orang ke orang. Indeks case dan sumber penularan tidak diketahui karena mobilitas penduduk yang tinggi. Ada hubungan bermakna antara status imunisasi dan riwayat perjalanan dengan kejadian difteri. Disarankan kepada Dinas Kesehatan Kabupaten Garut agar dapat Meningkatkan Kwalitas dan cakupan imunisasi DPT, DT, Td, Meningkatkan perbaikan pencatatan imunisasi dengan tertib, dan Meningkatkan koordinasi pelaporan dalam penemuan kasus baru dan karier
Global TB Report 2016 states only about 35,3% of people with TB who successfullyfound/has been reported in Indonesia of about 1.020.000 estimation of incident in theyear 2016. This is certainly making the risk of people with TB who still has not beenfound to transmit the disease will increase. From around the districts in Indonesia noteverything has a coverage of the discovery of TB cases. Many of the factors that lead toit, so the discrepancy in the discovery and reporting TB cases. The characteristics of thedistricts with TB households diagnosed it is important to note that when there are othercounties that have similar characteristics so it can be suspected the possibility ofdiagnosed TB households in the district Although no case of TB was found. This thesisexamines the characteristics of districts with TB households diagnosed in Indonesia.Research with secondary data analysis using Data Riskesdas 2013 and 2014 PODESData. The analysis conducted to see the difference in the proportion of each of thevariables and assess the influences between variables independent of the dependentvariable. Fractional regression test used to measure the value of risk variables areindependent of the dependent variable. The results showed the influence ofcharacteristics of household environment for the district comprising the counties withthe proportion of slum households (1%), with the proportion of the village have slums(0.3%), and district with the proportion the village does not exist health care facility(1%). Influence of the characteristics of district to household conditions physically seenfrom districts with solid household proportion (1%), with the proportion of householdsthere are no window (3%), and district with the proportion of the village that has a homethe staircase there are indoor pollution (1%), while the influence of the districts with theproportion of households with less lighting and a proportion of the village householdswithout electricity against the characteristics of districts with TB households is difficultto explained. Districts with low proportion of household economy (0.6%) influence onthe characteristics of districts with TB households diagnosed. This research suggestedthat the strengthening of programs related to TB prevention and control efforts on at-risk households and as a basis for the intervention priorities based on refinementsepidemic levels of TB at the district/city.Key words:TB, Influence, District.
ABSTRAK Tuberkulosis (TB) adalah penyakit menular yang disebabkan oleh infeksi Mycobacterium tuberculosis (MTb). Penyakit infeksi M.Tb ini menyerang semua negara di dunia. Selain menyebabkan kematian, penderita TB ini juga mengalami kerugian secara ekonomis dan menghadapi stigma negatif di masyarakat. Indonesia merupakan negara dengan jumlah penderita TB terbanyak ke-5 di dunia, dan meskipun program DOTS digalakkan, penurunan insidensinya masih belum berarti. Penelitian ini merupakan studi ekologi dengan desain cross sectional bertujuan mengelompokkan prevalensi TB dan faktor risikonya. Dilaksanakan pada bulan Maret sampai Juni 2013. Data yang dipergunakan merupakan hasil dari Riskesdas dan Survei kependudukan dari BPS tahun 2007. Penggugusan dilakukan dengan cluster analysis, sementara untuk melihat faktor penentu yang paling berperan terhadap prevalensi TB dilakukan dengan multiple regression analysis. Hasil akhir pembentukan klaster yang optimal sebanyak 5, dan didapatkan sebagian besar kabupaten/kota di wilayah Indonesia Bagian Barat dan Tengah berada dalam satu klaster. Empat kabupaten/kota di Provinsi Papua berada dalam satu klaster dan merupakan wilayah dengan prevalensi TB terbesar, dengan ratarata empat faktor risiko lebih tinggi dibandingkan klaster lainnya. Faktor penentu yang paling berpengaruh terhadap prevalensi TB adalah jumlah prevalensi Diabetes Mellitus (DM). Masing-masing klaster menunjukkan permasalahannya sendiri, sehingga dalam upaya untuk menurunkan prevalensi TB di masyarakat dan dengan keterbatasan sumber daya yang dimiliki pemerintah, perlu ditentukan prioritas program yang dilakukan untuk mengatasi faktor risiko TB sesuai dengan permasalahan di tiap-tiap daerah.
ABSTRACT Tuberculosis, a communicable disease transmitted by Mycobacterium tuberculosis, has become a global issue. With its high mortality and morbidity, this disease become a negative stigma in population Indonesia accounts for nearly one twentieth of the global burden of TB. Although it has a growing DOTS programme there has not been a discernible reduction in the incidence of TB in this country. A cross-sectional ecological study was conducted to determine TB prevalence and its risk factors between March and June 2013. Data was taken from Basic Health Research and Demographic Survey from Center of Statistical Bureau 2007, then clustered with cluster analysis, while to find the most affecting risk factor on TB data was analyzed with multiple regression analysis. Result showed the number of optimal cluster was 5, and most city/town in west and central Indonesian region were within one cluster. Four city/town in Papua Province were in one cluster with highestTB prevalence, with four average risk factor higher than other cluster. The determining factor which was the most affecting onTB prevalence was DM prevalence. Since each cluster has its specific problems, Indonesian government has to set priority on program dealing with TB risk factors based on regional problems, inspite of minimal sources.
Dengue Hemorrhagic Fever is an endemic disease in most parts of Indonesia, including in other tropical regions. Nutritional status is closely related to a person's immunological status related to immunopathogenesis of DHF. The purpose of this study was to determine the relationship of stunting with the incidence of DHF in toddlers in Sumbawa Regency. The study design that will be used in this study is an analytic study with a case control design. Case samples will be taken from all cases, and for control samples will be taken by using a random sample technique (Simple Random Sampling). So it can be concluded the number of cases 97 (total cases) of families who have toddlers with DHF diagnoses from 2018 to March 2020 (from 5 working areas of puskesmas with the highest number of DHFs in toddlers) while control of 194 families who have toddlers who are neighboring cases. From the bivariate results it can be concluded that there is a significant relationship between nutritional status and the incidence of DHF in children under five in Sumbawa Regency (p value = 0.0001) with OR = 3,269 (95% CI: 1,757-6,083). In multivariate analysis showed the same thing (p value = 0.0001) with OR = 3.22 (95% CI: 1,679-6,174). This shows that toddlers with short and very short nutritional status increase the risk of 3.22 times getting DHF.
Background. Indonesia is a country with a large number of disaster events and the number tends to increase. However, the current system has not responded to the needs of disaster victims, especially in post-disaster conditions where the network often does not function. Objective. Develop a prototype of a disaster information system that can be used to improve a fast and accurate response when a disaster occurs, starting from disaster victims prediction, data collection, problem mapping, and determining priority areas according to needs in disaster-affected locations. Method. Analysis of system requirements through literature review and in-depth interviews with nine informants, followed by the design of a disaster information system prototype, online-based facility data collection and the design of a disaster information system dashboard. Results. A prototype of a disaster information system has been created which includes data collection suitable for disaster events (can be used offline), integrated with demographic and health surveillance (DHS) and pre-disaster data, along with a userfriendly disaster information system dashboard by utilizing the geographic information system (GIS). Conclusion. Opportunities to develop a disaster information system are very possible with the integration of DHS data and pre-disaster data (including contacts and coordinates for health facilities, public ambulances, estimated places for evacuation, clean water facilities, toilets). This prototype is in accordance with disaster conditions, making the recording process faster, more effective and able to display a GIS-based interactive dashboard for prediction of victims based on vulnerable groups, logistical assistance needs, planning for evacuation places and available facilities, and for coordination with health facilities, and distribution resources and volunteers according to the results of regional priority mapping.
