Zoonotic cutaneous leishmaniasis in northeastern Iran: a GIS-based spatio-temporal multi-criteria decision-making approach

2016 ◽  
Vol 144 (10) ◽  
pp. 2217-2229 ◽  
Author(s):  
A. MOLLALO ◽  
E. KHODABANDEHLOO
Keyword(s):  
Decision Making ◽  
High Risk ◽  
Cutaneous Leishmaniasis ◽  
Vegetation Index ◽  
Fuzzy Ahp ◽  
Public Health Problem ◽  
Study Region ◽  
Zoonotic Cutaneous Leishmaniasis ◽  
Risk Areas ◽  
Risk Maps

SUMMARYZoonotic cutaneous leishmaniasis (ZCL) constitutes a serious public health problem in many parts of the world including Iran. This study was carried out to assess the risk of the disease in an endemic province by developing spatial environmentally based models in yearly intervals. To fill the gap of underestimated true burden of ZCL and short study period, analytical hierarchy process (AHP) and fuzzy AHP decision-making methods were used to determine the ZCL risk zones in a Geographic Information System platform. Generated risk maps showed that high-risk areas were predominantly located at the northern and northeastern parts in each of the three study years. Comparison of the generated risk maps with geocoded ZCL cases at the village level demonstrated that in both methods more than 90%, 70% and 80% of the cases occurred in high and very high risk areas for the years 2010, 2011, and 2012, respectively. Moreover, comparison of the risk categories with spatially averaged normalized difference vegetation index (NDVI) images and a digital elevation model of the study region indicated persistent strong negative relationships between these environmental variables and ZCL risk degrees. These findings identified more susceptible areas of ZCL and will help the monitoring of this zoonosis to be more targeted.

scholarly journals Identification of Risk Areas for Intestinal Schistosomiasis, Based on Malacological and Environmental Data and on Reported Human Cases

2021 ◽  
Vol 8 ◽  
Author(s):  
Paulo R. S. Coelho ◽  
Fabrício T. O. Ker ◽  
Amanda D. Araújo ◽  
Ricardo. J. P. S. Guimarães ◽  
Deborah A. Negrão-Corrêa ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Ecological Model ◽  
Integrated Approach ◽  
Google Earth ◽  
Environmental Data ◽  
Transmission Risk ◽  
Local Health ◽  
Temperature And Precipitation ◽  
Risk Areas ◽  
Risk Maps

The aim of the present study was to use an integrated approach for the identification of risk areas for Schistosoma mansoni transmission in an area of low endemicity in Minas Gerais, Brazil. For that, areas of distribution of Biomphalaria glabrata were identified and were related to environmental variables and communities with reported schistosomiasis cases, in order to determine the risk of infection by spatial analyses with predictive models. The research was carried out in the municipality of Alvorada de Minas, with data obtained between the years 2017 and 2019 inclusive. The Google Earth Engine was used to obtain geo-climatic variables (temperature, precipitation, vegetation index and digital elevation model), R software to determine Pearson's correlation and MaxEnt software to obtain an ecological model. ArcGis Software was used to create maps with data spatialization and risk maps, using buffer models (diameters: 500, 1,000 and 1,500 m) and CoKriging. Throughout the municipality, 46 collection points were evaluated. Of these, 14 presented snails of the genus Biomphalaria. Molecular analyses identified the presence of different species of Biomphalaria, including B. glabrata. None of the snails eliminated S. mansoni cercariae. The distribution of B. glabrata was more abundant in areas of natural vegetation (forest and cerrado) and, for spatial analysis (Buffer), the main risk areas were identified especially in the main urban area and toward the northern and eastern extensions of the municipality. The distribution of snails correlated with temperature and precipitation, with the latter being the main variable for the ecological model. In addition, the integration of data from malacological surveys, environmental characterization, fecal contamination, and data from communities with confirmed human cases, revealed areas of potential risk for infection in the northern and eastern regions of the municipality. In the present study, information was integrated on epidemiological aspects, transmission and risk areas for schistosomiasis in a small, rural municipality with low endemicity. Such integrated methods have been proposed as important tools for the creation of schistosomiasis transmission risk maps, serve as an example for other communities and can be used for control actions by local health authorities, e.g., indicate priority sectors for sanitation measures.

scholarly journals Epidemiological and geographical characterization of leprosy in a Brazilian hyperendemic municipality

2018 ◽  
Vol 34 (8) ◽  
Author(s):  
Lucia Helena Soares Camargo Marciano ◽  
Andréa de Faria Fernandes Belone ◽  
Patrícia Sammarco Rosa ◽  
Neusa Maria Broch Coelho ◽  
Cássio César Ghidella ◽  
...  
Keyword(s):  
High Risk ◽  
Public Health Problem ◽  
Control Measures ◽  
Scan Statistics ◽  
Mapping Technique ◽  
Socioeconomic Indicators ◽  
Mato Grosso ◽  
Choropleth Mapping ◽  
Risk Areas

Abstract: This study aimed to identify the distribution pattern of leprosy in a hyperendemic municipality in Brazil and determine its relationship with the clinico-epidemiological situation over 11 years. The geographic information system, MapInfo, spatial scan statistics and the Moran I index were used to analyze new cases. The digital cartographic base was used to map clusters of new paucibacillary and multibacillary cases and cases in minors under 15 years old. Socioeconomic indicators are shown using the choropleth mapping technique. A reduction in the detection coefficient, increases in high-risk spatial clusters, marked changes in the distribution of high-risk and low-risk clusters, and high-risk clusters of minors under 15 years old were observed from 2006 to 2010, showing recent illness, the presence of active foci, and overlapping of high-risk clusters of multibacillary infection in minors under 15 years old. Leprosy remains a public health problem in Rondonópolis, Mato Grosso State; the high-risk areas require an intensification of control measures and active search strategies to detect new cases.

scholarly journals Analysis of Malaria Incidence in Banyumas Using Spacial-Temporal Approach

2017 ◽  
Vol 13 (1) ◽  
pp. 1-6
Author(s):  
Supriyanto Supriyanto ◽  
Nunung Nurhayati ◽  
Dwi Sarwani Sri Rejeki
Keyword(s):  
Public Health ◽  
Spatial Distribution ◽  
High Risk ◽  
Malaria Incidence ◽  
Temporal Distribution ◽  
Public Health Problem ◽  
Spatial And Temporal Distribution ◽  
Spatial Clusters ◽  
Risk Areas ◽  
Unstable Transmission

Malaria still becomes a public health problem in Indonesia although has declined the last decades. The incidences of malaria in Banyumas shows unstable transmission and still risk of epidemic . Thus, the spatial and temporal distribution is required as part of efforts towards the elimination of malaria in Banyumas. Temporal spatial statistical methods is used to identify a group of malaria incidence at the district level. Purely spatial clusters of malaria incidence from 2004 to 2015 shows that the disease is not distributed randomly in the study area. A total of nine districts of high risk is determined by analysis of Morans I. The analysis showed that by the Morans I test, there is spatial autocorrelation found in the percentage malaria incidence from 2004 to 2015 in Banyumas. The use of the model can provide a means to detect the spatial distribution, temporal, and spatiotemporal malaria, as well as to identify areas of high risk of malaria. This research may help in prioritizing resources on high-risk areas for malaria control in the future and towards the elimination of malaria in Banyumas.

scholarly journals Government-led Resettlement after Natural Disasters as a Durable Solution? The Case of Cyclone Idai

2020 ◽  
Author(s):  
Carolien Jacobs ◽  
Bernardo Almeida
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
High Risk ◽  
Citizen Participation ◽  
Disaster Response ◽  
Decision Making Process ◽  
Short Term ◽  
Risk Areas ◽  
The Government ◽  
Term Response

Abstract Thousands of people had to flee their homes when Cyclone Idai hit Mozambique in 2019. In its aftermath, the government resettled more than 80,000 people from high-risk areas to safer ground. This article analyses resettlement as a durable solution to disaster response. The question of durable resettlement due to climate-related displacement is especially pertinent in the light of ongoing climate change. Based on empirical research, we show that, although the government succeeded in providing a short-term response to the disaster, there are two major impediments to using resettlement as a durable solution: the lack of citizen participation in the decision-making process leading to resettlement; and the gap between the short-term humanitarian perspective and a longer-term development viewpoint. Resettlement can hardly be seen as a durable solution to climate-related displacement as long as key principles are not respected.

scholarly journals The Effect of Geographical and Climatic Factors on the Distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Golestan Province, an Endemic Focus of Zoonotic Cutaneous Leishmaniasis in Iran, 2014

2021 ◽  
Author(s):  
Seyed Hamid Hosseini ◽  
Ehsan Allah-Kalteh ◽  
Aiuob Sofizadeh
Keyword(s):  
Cutaneous Leishmaniasis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Global Climate ◽  
Phlebotomus Papatasi ◽  
Temperature And Precipitation ◽  
Zoonotic Cutaneous Leishmaniasis ◽  
Diurnal Range ◽  
Annual Range

Background: Phlebotomus papatasi is known as the main vector of zoonotic cutaneous leishmaniasis. This study aimed to investigate the effect of geographical and bioclimatic factors on the Ph. papatasi distribution. Methods: A total of 34 villages were selected, and sampling was performed three times using 120 sticky traps in each selected village. All the collected species were mounted and identified their species. The densities of Ph. papatasi were measured in all the villages and entered into ArcMap as a point layer. The required bioclimatic and environmental vari- ables were extracted from the global climate database and The normalized difference vegetation index was obtained from the MODIS satellite imagery, also, all variables entered into ArcMap as raster layers, so The numerical value of each independent variable in the cell where the selected village is located in this, was extracted using spatial analyst tools and the value to point submenu. All the data were finally entered into IBM SPSS, and the relationship was exam- ined between the number of collected Ph. papatasi and the independent variables using Spearman's correlation test. Results: A total of 1773 specimens of Ph. papatasi were collected. The findings of this study showed that max tem­perature of warmest month, temperature annual range, temperature seasonality, mean diurnal range, precipitation sea­sonality, mean temperature of driest and warmest quarter were positively associated with the density of Ph. papatasi. Conclusion: Air temperature and precipitation were shown as the most significant factors in the distribution of Ph. pa­patasi.

scholarly journals Penilaian Risiko Bencana Longsor di Wilayah Kabupaten Serang

2020 ◽  
Vol 34 (1) ◽  
pp. 1
Author(s):  
Heru Sri Naryanto ◽  
Qoriatu Zahro
Keyword(s):  
High Risk ◽  
Age Groups ◽  
Landslide Hazard ◽  
Landslide Risk ◽  
Hazard Maps ◽  
Geological Conditions ◽  
Medium Risk ◽  
Risk Areas ◽  
Vulnerability Maps ◽  
Risk Maps

Kabupaten Serang membutuhkan peta bahaya, peta kerentanan dan peta risiko bencana tanah longsor sebagai dasar dalam pengurangan risiko. Parameter dan bobot untuk pembuatan peta bahaya longsor adalah: kelerengan (50%), kondisi geologi (20%), curah hujan (15%) dan penggunaan lahan (15%). Zona bahaya tanah longsor tinggi di Kabupaten Serang terdapat di kecamatan-kecamatan Padarincang, Ciomas, Mancak, Anyar, Cinangka, Pulo Ampel dan Bojonegara. Pembuatan peta kerentanan digunakan kerentanan sosial dengan indikatornya adalah: kepadatan penduduk, rasio jenis kelamin, rasio kemiskinan, rasio orang cacat dan rasio kelompok umur. Peta risiko tanah longsor dibuat dengan mengoverlaykan dari peta bahaya tanah longsor dan peta kerentanan. Pembuatan peta bahaya, peta kerentanan dan peta risiko mengunakan teknik overlay atau tumpang tindih dengan software ArcGIS. Daerah berisiko rendah di Kabupaten Serang seluas 92.416 ha (63,6% dari seluruh luas Kabupaten Serang), berisiko sedang seluas 46.971 ha. (32,3%) dan yang berisiko tinggi 5.907 ha. (4,1%). Bila dilihat dari tingkatan kecamatan, 5 urutan teratas kecamatan yang memiliki luasan daerah berisiko tinggi terbesar adalah Kecamatan Anyar (1.498 ha), Pulo Ampel (1,082 ha), Bojonegara (1.019 ha), Baros (828,5 ha) dan Padarincang (561 ha). Peta bahaya, peta kerentanan dan peta risiko sangat dibutuhkan oleh Pemerintah Kabupaten Serang, selain sebagai acuan kegiatan pengurangan risiko bencana juga untuk penataan kawasan yang aman berkelanjutan. Serang District requires hazard maps, vulnerability maps and risk maps as a basis for reducing the risk of landslides. Parameters and weights for making landslide hazard maps are: slope (50%), geological conditions (20%), rainfall (15%) and land use (15%). High landslide hazard zones in Serang District are found in the sub-districts of Padarincang, Ciomas, Mancak, Anyar, Cinangka, Pulo Ampel and Bojonegara. Making a vulnerability map used social vulnerability with indicators: population density, sex ratio, poverty ratio, ratio of disabled people and ratio of age groups. Landslide risk maps are made by overlaying landslide hazard maps and vulnerability maps. Making hazard maps, vulnerability maps and risk maps using overlay techniques with ArcGIS software. Low-risk areas in Serang District covering 92,416 ha (63.6% of the total area of Serang Regency), medium risk of 46,971 ha. (32.3%) and high risk 5,907 ha. (4.1%). When viewed from the sub-district level, the top 5 sub-districts that have the largest high-risk areas are Anyar District (1,498 ha), Pulo Ampel (1,082 ha), Bojonegara (1,019 ha), Baros (828.5 ha) and Padarincang (561 ha ) Hazard maps, vulnerability maps and risk maps are urgently needed by the Serang District Government, in addition to being a reference for disaster risk reduction activities as well as for the sustainable arrangement of areas. 

scholarly journals Prone Regions of Zoonotic Cutaneous Leishmaniasis in Southwest of Iran: Combination of Hierarchical Decision Model (AHP) and GIS

2019 ◽  
Author(s):  
Elham Jahanifard ◽  
Ahmad Ali Hanafi-Bojd ◽  
Hossein Nasiri ◽  
Hamid Reza Matinfar ◽  
Zabihollah Charrahy ◽  
...  
Keyword(s):  
Cutaneous Leishmaniasis ◽  
Leishmania Major ◽  
Public Health Problem ◽  
Underground Water ◽  
Important Public Health Problem ◽  
Khuzestan Province ◽  
Plain Area ◽  
Zoonotic Cutaneous Leishmaniasis ◽  
Hierarchical Decision Model ◽  
Southwest Of Iran

Background: Cutaneous leishmaniasis due to Leishmania major is an important public health problem in the world. Khuzestan Province is one of the main foci of zoonotic cutaneous leishmaniasis (ZCL) in the southwest of Iran. We aimed to predict the spatial distribution of the vector and reservoir(s) of ZCL using decision-making tool and to pre­pare risk map of the disease using integrative GIS, RS and AHP methods in endemic foci in Shush (plain area) and Khorramshahr (coastal area) counties of Khuzestan Province, southern Iran from Mar 2012 to Jan 2013. Methods: Thirteen criteria including temperature, relative humidity, rainfall, soil texture, soil organic matter, soil pH, soil moisture, altitude, land cover, land use, underground water depth, distance from river, slope and distance from human dwelling with the highest chance of the presence of the main vector and reservoir of the disease were chosen for this study. Weights of the criteria classes were determined using the Expert choice 11 software. The pres­ence proba­bility maps of the vector and reservoir of the disease were prepared with the combination of AHP method and Arc GIS 9.3. Results: Based on the maps derived from the AHP model, in Khorramshahr study area, the highest probability of ZCL is predicted in Gharb Karoon rural district. The presence probability of ZCL was high in Hossein Abad and Benmoala rural districts in the northeast of Shush. Conclusion: Prediction maps of ZCL distribution pattern provide valuable information which can guide policy mak­ers and health authorities to be precise in making appropriate decisions before occurrence of a possible disease out­break.

scholarly journals IDENTIFYING HIGH-RISK POPULATIONS OF TUBERCULOSIS USING ENVIRONMENTAL FACTORS AND GIS BASED MULTI-CRITERIA DECISION MAKING METHOD

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 9-13 ◽  
Author(s):  
A. R. Abdul Rasam ◽  
N. M. Shariff ◽  
J. F. Dony
Keyword(s):  
Decision Making ◽  
High Risk ◽  
Uncertainty Assessment ◽  
Assessment Method ◽  
Geographical Information ◽  
Risk Level ◽  
Multi Criteria Decision Making ◽  
Index Model ◽  
Risk Areas ◽  
Mcdm Method

Development of an innovative method to enhance the detection of tuberculosis (TB) in Malaysia is the latest agenda of the Ministry of Health. Therefore, a geographical information system (GIS) based index model is proposed as an alternative method for defining potential high-risk areas of local TB cases at Section U19, Shah Alam. It is adopted a spatial multi-criteria decision making (MCDM) method for ranking environmental risk factors of the disease in a standardised five-score scale. Scale 1 and 5 illustrate the lowest and the highest risk of the TB spread respectively, while scale from 3 to 5 is included as a potential risk level. These standardised scale values are then combined with expert normalised weights (0 to 1) to calculate the overall index values and produce a TB ranked map using a GIS overlay analysis and weighted linear combination. It is discovered that 71.43% of the Section is potential as TB high risk areas particularly at urban and densely populated settings. This predictive result is also reliable with the current real cases in 2015 by 76.00% accuracy. A GIS based MCDM method has demonstrated analytical capabilities in targeting high-risk spots and TB surveillance monitoring system of the country, but the result could be strengthened by applying other uncertainty assessment method.

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