scholarly journals Studi Epidemiologi Dengan Pendekatan Analisis Spasial Terhadap Faktor-Faktor Risiko Penyakit Infeksi Saluran Pernapasan Akut (ISPA) Pada Anak Di Kecamatan Sragen

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Wiwik Setyaningsih ◽  
Dodiet Aditya Setyawan ◽  
Ari Sarwanto
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Health Problem ◽  
Skin Diseases ◽  
Respiratory Infections ◽  
Public Health Problem ◽  
Developed Countries ◽  
Geographic Information ◽  
Acute Respiratory Infections ◽  
A Value

Abstract : Geographic Information System (GIS), acute respiratory infection in children. Manifestation quality healthy environment is an essential part that can not be abandoned in the field of health. Air as an important environmental component in the life of mankind, should be maintained and enhanced so as to provide carrying capacity for a higher quality of human life. Today the disease based on environment is still a health problem that is dominant in the middle - the middle of the Indonesian people. This is reflected in the high number of events and visits patients with several diseases to the center - the center of health care such as diarrhea, malaria, dengue hemorrhagic fever (DHF), tuberculosis, acute respiratory infections, skin diseases, worm infection as well as health problems or poisoning from chemicals and pesticides (Depkes RI, 2002). From these diseases, Acute Respiratory Infections still contributed the most to the morbidity, and until now the disease is still a public health problem that is the main, both in developed countries and countries emerging (Wahyudi, 2004). This study design is modeling Case Control using Geographic Information System (GIS). Purposive sample taken with the number of 80 respondents. Data were analyzed using Chi Square, Multiple Logistic Regression and spatial analysis using overlay function and Buffering. Results show risk factors are shown to be significantly associated with the incidence of respiratory disease in children in the district of Sragen is the density of the household (OR = 0.075, 95% CI = 0019-0293, with a value of p = 0.000); distance of residence to the highway within a radius of ≤ 250 meters (OR = 0334, 95% CI = 0118 to 0949, with a value of p = 0.040).

scholarly journals Epidemiological Study and Spatial Modeling of Cutaneous Leishmaniasis in Bushehr Province Using the Geographic Information System (GIS) from 2011 to 2015

2019 ◽  
Author(s):  
Ali Dehghani ◽  
Mohamad Hasan Lotfi ◽  
Hossein Falahzadeh ◽  
Katayon Vahdat ◽  
Zahra Shabani
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Cutaneous Leishmaniasis ◽  
Health Problem ◽  
Rural Areas ◽  
Urban Areas ◽  
Geographic Information ◽  
Cross Sectional ◽  
Important Health ◽  
Epidemiological Characteristics

Introduction: It is generally accepted that cutaneous leishmaniasis is considered as an important health problem all over the world which is caused by leishmaniasis protozoan. This disease is also known as a health problem in some regions of Iran including Bushehr province. The present study investigated the geographical dispersion and the epidemiological characteristics of subjects with the cutaneous leishmaniasis in this province from 2011 to 2015. Method: In this cross-sectional and analytical study, the epidemiologic data including the age, gender, residential area, and counties with this disease was analyzed and collected from 663 patients who were followed up and treated from 2011 to 2015. Results: 422 (63.7%) of studied people were residents of urban areas and 241 (36.3%) lived in rural areas. 59.4% (394 people) were male and 40.6% (269) were female. The mean age of the subjects was 21.91± 17.01 (ranging from 1 to 80). Kangan County with an average 5-year incidence of 17.72 per a hundred thousand people had the highest incidence, but Tangestan County with the incidence of 8.47 per a hundred thousand people had the lowest average incidence. Based on GIS results, Jam County, which was not recognized as the focus of this disease in the past, has been considered as a new focus of disease in recent years. Conclusion: The geographic information system (GIS) is regarded as an effective tool for the organization of diseases and health data. The crisis can be identified and controlled by taking proper measures with the discovery of spatial accumulation of diseases.

scholarly journals PENGARUH HOUSE INDEX DAN MAYA INDEX TERHADAP KEJADIAN DEMAM BERDARAH DENGUE DI KECAMATAN GROGOL KABUPATEN SUKOHARJO MENGGUNAKAN GEOGRAPHIC INFORMATION SYSTEM (GIS)

IKESMA ◽  
2018 ◽  
Vol 14 (2) ◽  
pp. 135
Author(s):  
Nine Elissa Maharani ◽  
Pranichayudha Rohsulina
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Dengue Fever ◽  
Public Health Problem ◽  
Geographic Information ◽  
P Value ◽  
Important Public Health Problem ◽  
Cross Sectional ◽  
Central Java ◽  
Index Effect

Dengue fever is an important public health problem in indonesia, in the year 2014 the number of death due to dengue fever in Indonesia 903 people from 99499 cases. Sukoharjo district is one of the bloody endemic distrric in central java. In eradicating dengue fever, the larva survey used is a visual method using the entomology indicator, the house index and maya index. This study aims to determine the effect of house index and maya index on the incidence of dengue fever in  Grogol district of Sukoharjo using geographic information system (GIS). The research method used is an analytical survey wuth cross sectional approach. The result of the study showed a maya index effect on the incidence of dengue fever in  Grogol district of Sukoharjo (p value 0,00), there is no effect of house index on the incidence of dengue fever in Grogol District of Sukoharjo (p value 0,87).

Use of Geographic Information System Mapping in the Examination of Specialized Low Vision Resources and Areas of Need in Michigan

2021 ◽  
Vol 115 (1) ◽  
pp. 5-16
Author(s):  
Elyse Connors ◽  
Amber E. Willard ◽  
Kathleen M. Baker ◽  
Katie Debiak ◽  
Renee Beranek ◽  
...  
Keyword(s):  
Public Health ◽  
Risk Factors ◽  
Information System ◽  
Geographic Information System ◽  
Vision Loss ◽  
Low Vision ◽  
Public Health Problem ◽  
Geographic Information ◽  
Gis Mapping ◽  
Lower Peninsula

Introduction: The number of adults with visual impairments (i.e., blindness or low vision) is increasing, especially with the aging of the population. Although awareness of vision loss as a public health problem is growing, public health budgets are decreasing. This study exemplifies the use of publicly available secondary data and geographic information system (GIS) mapping to spatially map areas of potential higher risk for vision loss and identify where specialized, low vision resources are located, by county, in Michigan. Methods: County-level, publicly available data on risk factors for low vision (health and demographic) and specialized low vision resources (medical, rehabilitation, and community) are extracted from existing public health data sets and information published on the Internet. GIS mapping is applied to visually examine potential areas of disparity between need and resources. Results: Broadly speaking, counties in Michigan with the highest number of risk factors for low vision are clustered in the center of the Lower Peninsula and on the eastern and western ends of the Upper Peninsula. Areas that have fewer resources for low vision are clustered in the thumb area and the middle to upper part of the Lower Peninsula. Resources are concentrated near the state’s metropolitan areas (i.e., Detroit and suburbs, Kalamazoo, and Grand Rapids). Discussion: Maps can be helpful in locating areas of health disparities, but they need to be interpreted carefully such as by considering the county’s population size. Understanding the eligibility criteria of available services can help to uncover groups of persons not being served. Implications for practitioners: With increasing need for services and shrinking budgets, strategic planning may help alleviate anticipated shortfalls in available services. Use of publicly available data and GIS mapping may be an affordable and efficient method to identify areas of need and resources, for targeted public health efforts in vision.

scholarly journals The Implementation of Spatial Weighted Regression on Detecting the Risk Factors of Malaria Incidences In Kulonprogo District

2019 ◽  
Author(s):  
Nur Rokhman ◽  
Nuryati . ◽  
Marko Ferdian Salim ◽  
M. Syairaji ◽  
Ismil Khairi Lubis
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
System Approach ◽  
Public Health Problem ◽  
Geographic Information ◽  
Weighted Regression ◽  
Cross Sectional ◽  
Anopheles Mosquitoes ◽  
Partial Analysis ◽  
Cross Sectional Design

Malaria is still a public health problem caused by Plasmodium parasites. This disease is naturally transmitted through the bite of female Anopheles mosquitoes. Kulonprogo Regency is one of the malaria endemic areas that needs to be developed to combat malaria. This research aims to describe the distribution of malaria cases to determine vulnerable areas in Kulonprogo Regency. This research was an observational analytic with cross sectional design conducted in April - October 2018. This research used the total sampling of 62 malaria cases. Data analysis was performed by using a Geographic Information System approach with overlay, buffer, cluster techniques, and spatial weighted regression. Based on the results of the partial analysis, it was found that 62 cases of malaria spread in 6 sub-districts namely: Kokap, Pengasih, Samigaluh, Kalibawang, Wates and Sentolo. The distribution of malaria cases clustered in Kokap Sub District, namely in Kalirejo Village (29 cases) and Hargorejo Village (9 cases). The overlay and buffer techniques found that the distribution of cases spread in Menoreh hills which have forest vegetation. Malaria-prone areas in Kulonprogo Regency were found in Kalirejo Village and Hargorejo Village through the results of spatial analysis using a Geographic Information System approach. Thus, malaria control efforts were focused on these vulnerable areas.

PEMANFAATAN WEBGIS DALAM MENDUKUNG PROGRAM DESA BERSAUDARA DI KABUPATEN MAGELANG

2018 ◽  
Vol 2 ◽  
pp. 223
Author(s):  
Humam Zarodi
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Geographic Information

<p>Erupsi Gunungapi Merapi tahun 2010 mengakibatkan banyak korban jiwa, kerusakan aset dan kerugian di berbagai bidang. Untuk meminimalkan korban jiwa, kerusakan dan kerugian, diperlukan upaya pengurangan risiko bencana (PRB). Salah satu upaya yang dilakukan adalah program desa bersaudara (<em>sister village</em>) yang digagas oleh Pemerintah Kabupaten Magelang melalui Badan Penanggulangan Bencana Daerah (BPBD). Program desa bersaudara ini bertujuan agar ada kepastian tempat pengungsian, mengurangi kesemrawutan proses pengungsian serta memudahkan pelayanan pengungsi. Program ini dapat memanfaatan Sistem Informasi Geografis/<em>Geographic Information System</em> (GIS) yang berbasis web (<em>WebGIS</em>). <em>WebGIS</em> mampu mendiseminasikan peta yang dihasilkan dalam program desa bersaudara, misalnya peta jalur evakuasi. Makalah ini bertujuan untuk mendiskripsikan pemanfataan <em>WebGIS</em> dalam mendukung program desa bersaudara, dengan mengambil kasus di Desa Ngargomulyo (desa rawan bencana) dan Desa Tamanagung (desa penyangga/ penerima pengungsi). Metodenya adalah memaparkan proses pemetaan jalur evakuasi. Proses penyusunan peta tersebut terbagi empat tahap:   survei lapangan, penyiapan data spasial, coding dan publikasi. Hasilnya adalah tampilan peta jalur evakuasi yang bisa diakses oleh siapapun tanpa menggunakan aplikasi GIS yang memudahkan masyarakat pengungsi, penerima pengungsi, pemerintah maupun parapihak, mengetahui asal pengungsi, jalur evakuasi dan titik pengungsian. Penelitian ini menyimpulkan bahwa pemetaan <em>WebGIS</em> dapat mendukung upaya PRB dengan keunggulan bisa dijangkau pengguna secara sangat luas.<strong></strong></p><p><strong>Kata kunci</strong>: desa bersaudara, <em>sister village</em>, pemetaan jalur evakuasi, <em>gis</em>, <em>webgis</em></p>

Implementation of A-Star Algorithm for Searching Routes Near the Tsunami Evacuation Shelter Point

2020 ◽  
Vol 4 (2) ◽  
pp. 254-259
Author(s):  
Renita Astri ◽  
Sularno
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Distance Estimation ◽  
Geographic Information ◽  
High Population

District of West Padang which is the area closest to the coast and has a high population. Therefore a geographic information system was created using the A-Star Algorithm method. The A-Star algorithm uses the closest distance estimation to reach a goal and has a heuristic value that is used as a basis for consideration. In this system there are alternative paths and show the amount of capacity and distance from the shelter to be addressed.

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