Modeling of at risk areas of Zoonotic Cutaneous Leishmaniasis (ZCL) using Hierarchical Analysis Process (AHP) and Geographic Information System (GIS) in Southwest of Iran

2020 ◽  
Vol 44 (2) ◽  
pp. 315
Author(s):  
Elham Jahanifard ◽  
Ahmad Ali Hanafi-Bojd ◽  
Amir Ahmad Akhavan ◽  
Mona Sharififard ◽  
Atefeh Khazeni ◽  
...  
2019 ◽  
Author(s):  
Maereg Teklay A Amare ◽  
Gebrehiwot Gebretsadik kassa ◽  
Esie G/wahid Gebre ◽  
Abadi Abay ◽  
Mekonen yimer ◽  
...  

Abstract Background: Erer is one of the districts in Ethiopia where the first malaria transmission season occurs. Although the focus on malaria research has increasingly gained ground, little emphasis has been given to develop quantitative methods for assessing malaria hazard and risk in a temporal and spatial perspective. Objective: To characterize and examine the temporal and spatial malaria trend. The research also aims at producing a predictive model of malaria hazard and risk in Erer district. Methods: In this study a cross sectional research design was used. It was carried out through the collection of both quantitative and qualitative data about the nature of malaria and household’s response towards it. A multi-stage sampling method was used and 136 sample size was determined from the sampling frame of 6203 households. Simple descriptive analysis technique was used to determine the malaria trend of the district. Integration of Geographic information system and analytic hierarchy process was used to determine the weight of each factor pair wise comparison and weighted linear combination was used to aggregate and produce the hazard and malaria risk maps. Results: Results have shown that 19.92%, 27.96%, 32.35%, 18.93% and 0.82% of the district was very high, high, moderate, low and very low malaria risk areas respectively. The malaria trend of the area was found to be variable across time with 2014 the peak year while the minimum case observed was in 2016. Conclusion: It is possible to conclude that risk maps are important for estimating the scale of the risk, and enable detection of high risk areas, thus facilitating decision making and policy formulation for enhanced malaria control interventions. Key words: Analytic Hierarchy Process; Malaria risk; Malaria trend; Weighted overlay


2020 ◽  
Vol 5 (2) ◽  
pp. 107-121
Author(s):  
Listyo Yudha Irawan ◽  
Nabila Nabila ◽  
Damar Panoto ◽  
Agung Chandra Darmansyah ◽  
Annisa Nur Rasyidah ◽  
...  

Abstrak: Sub DAS Amprong secara administrasi masuk pada wilayah Kabupaten Malang dan Kota Malang. Meliputi lima Kecamatan yakni: Kedungkandang, Poncokusumo, Tumpang, Pakis dan Jabung. Risiko bencana longsor tergolong tinggi pada kawasan ini. Maka dari itu, penelitian ini bertujuan untuk melakukan pengurangan risiko bencana longsor mengunakan pendeketaan GIS (Geographic Information System). Menggunakan GIS distribusi tingkat risiko akan dapat diketahui dengan baik, sehingga mampu memberikan solusi yang lebih akurat. Penelitian ini meliputi empat tahapan: 1) pemetaan bahaya longsor, 2) pemetaan kerentanan bencana, 3) pemetaan kapasitas bencana, 4) pemetaan risiko bencana. Hasilnya diketahui bahwa kecamatan Jabung dan Poncokusumo merupakan wialayah dengan tingkat risiko longsor paling tinggi. Upaya yang dapat dilakukan untuk mengurangi tingkat risiko dapat dilakukan melalui mitigasi bencana secara struktural dan nonstruktural. Wilayah dengan risiko tinggi bukan merupakan kawasan pemukiman, namun memiliki aktivitas utama berupa pertanian. Oleh karena itu perlu adanya manajemen risiko bencana longsor dalam usaha longsor seperti: dengan cara: 1) pengaturan sistem irigasi dengan baik, 2) penerapan sistem terasering, dan 3) pemasangan bronjong pada kaki lereng. Abstract: Amprong watershed is administratively included in Malang Regency and Malang City. Includes five districts namely: Kedungkandang, Poncokusumo, Tumpang, Pakis and Jabung. The risk of landslides is classified high in this region. Therefore, this research aims to reduce the risk of landslides using GIS (Geographic Information System). Using GIS the distribution of risk levels will be well known, so as to provide a more accurate solution. This research includes four stages: 1) mapping of landslide hazards, 2) mapping of disaster vulnerability, 3) mapping of disaster capacity, 4) mapping of disaster risk. The results are known that the Jabung and Poncokusumo sub-districts are areas with the highest risk of landslides. Efforts that can be made to reduce the level of risk can be done through structural and nonstructural disaster mitigation. High risk areas are not residential areas, but have major activities in the form of agriculture. Therefore, it is necessary to have landslide risk management, such as: by: 1) regulating the irrigation system properly, 2) applying the terracing system, and 3) installing gabions at the foot of the slope.


2017 ◽  
Vol 11 (1) ◽  
pp. 9 ◽  
Author(s):  
James L. Wilson, PhD ◽  
Ruth Little, MPH ◽  
Lloyd Novick, MD, MPH

Objective: To develop a simple, cost-effective method for determining the size and geographic distribution of medically fragile (MF) individuals at risk from tropical storm surges for use by emergency management planners.Design: The study used Geographic Information System (GIS) spatially referenced layers based on secondary data sources from both state and federal levels. Setting: The study setting included the eastern North Carolina coastal counties that would be affected by tropical storm surges.Subjects: The initial MF population was extrapolated from national estimates for five conditions and then applied to US Census block population. These conditions included insulin dependent diabetes, chronic obstructive pulmonary disease, congestive heart failure, end stage renal disease, and patients receiving long-term oxygen treatment.Main outcomes: The main outcome of this study was a series of local and regional maps that portrayed the geographic distribution and estimated counts of potentially at-risk MF population from a tropical storm surge scenario.Conclusions: Maps depicting the geographic distribution and potential numbers of MF individuals are important information for planning and preparedness in emergency management and potentially engaging the public.


Author(s):  
Ali Dehghani ◽  
Mohamad Hasan Lotfi ◽  
Hossein Falahzadeh ◽  
Katayon Vahdat ◽  
Zahra Shabani

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gayan P. Withanage ◽  
Malika Gunawardana ◽  
Sameera D. Viswakula ◽  
Krishantha Samaraweera ◽  
Nilmini S. Gunawardena ◽  
...  

AbstractDengue is one of the most important vector-borne infection in Sri Lanka currently leading to vast economic and social burden. Neither a vaccine nor drug is still not being practiced, vector controlling is the best approach to control disease transmission in the country. Therefore, early warning systems are imminent requirement. The aim of the study was to develop Geographic Information System (GIS)-based multivariate analysis model to detect risk hotspots of dengue in the Gampaha District, Sri Lanka to control diseases transmission. A risk model and spatial Poisson point process model were developed using separate layers for patient incidence locations, positive breeding containers, roads, total buildings, public places, land use maps and elevation in four high risk areas in the district. Spatial correlations of each study layer with patient incidences was identified using Kernel density and Euclidean distance functions with minimum allowed distance parameter. Output files of risk model indicate that high risk localities are in close proximity to roads and coincide with vegetation coverage while the Poisson model highlighted the proximity of high intensity localities to public places and possibility of artificial reservoirs of dengue. The latter model further indicate that clustering of dengue cases in a radius of approximately 150 m in high risk areas indicating areas need intensive attention in future vector surveillances.


Author(s):  
Herwin Pisestyani ◽  
Nisa Nurul Fitria ◽  
Ardilasunu Wicaksono

Abstract There is still lack of bruselosis in beef cattle in Barru District, South Sulawesi. The aim of this study was to analyze data about the temporary distribution of disease by measuring spreading speed, and spatial distribution by mapping risk areas for bruselosis over the past three years. The data of this study was collected using the records from Dinas Peternakan and conducting interviews using structured questionnaires. This research was a descriptive study by measuring the incidence rate and describing the risk map using geographic information system (GIS). The results of this study indicate that, based on the incidence rate, the average of distribution rate of bruselosis in beef cattle in Barru is 5 cases per 10 000 heads/year. This incidence rate always decreases every year. There was no sub-district that classified as high risk. There was one area that classified as medium risk namely sub-district of Mallusetasi. Control measure that have been carried out by goverment were successful to reduce the spread of disease. Keywords: Beef cattle; Bruselosis; Incidence rate; Occurrence; Risk.   Abstrak Informasi mengenai penyebaran kejadian penyakit pada sapi potong di Kabupaten Barru Sulawesi selatan masih kurang. Penelitian ini bertujuan menganalisis data distribusi kejadian penyakit secara temporal dengan mengukur kecapatan penyebaran, dan secara spasial dengan memetakan wilayah berisiko bruselosis selama tiga tahun terakhir. Data dalam penelitian ini menggunakan rekapan dari Dinas Peternakan dan wawancara mendalam menggunakan kuesioner terstruktur. Penelitian ini mengunakan metode deskriptif dengan mengukur incidence rate dan menggambarkan peta risiko menggunakan geographic information system. Hasil penelitian ini menunjukkan bahwa berdasarkan incidence rate, kecepatan rata-rata penyebaran bruselosis pada sapi potong di Kabupaten Barru sebesar 5 kasus per 10 000 ekor/tahun. Nilai incidence rate tersebut selalu menurun setiap tahunnya. Kejadian penyakit paling tinggi terjadi di Kecamatan Mallusetasi dengan incidence rate sebesar 35 kasus per 10 000 ekor/tahun. Terdapat satu wilayah yang tergolong ke dalam risiko sedang, yaitu Kecamatan Mallusetasi. Tindakan pengendalian yang telah dilakukan oleh pemerintah setempat dikatakan berhasil dalam menekan tingkat kejadian penyakit. Kata kunci: Bruselosis; Incidence rate; Risiko; Sapi potong; Tingkat kejadian


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