GIS Database and Google Map of the Population at Risk of Cholangiocarcinoma in Mueang Yang District, Nakhon Ratchasima Province of Thailand.

Cholangiocarcinoma (CCA) is a serious problem in Thailand, particularly in the northeastern and northern regions. Database of population at risk are need required for monitoring, surveillance, home health care, and home visit. Therefore, this study aimed to develop a geographic information system (GIS) database and Google map of the population at risk of CCA in Mueang Yang district, Nakhon Ratchasima province, northeastern Thailand during June to October 2015. Populations at risk were screened using the Korat CCA verbal screening test (KCVST). Software included Microsoft Excel, ArcGIS, and Google Maps. The secondary data included the point of villages, sub-district boundaries, district boundaries, point of hospital in Mueang Yang district, used for created the spatial databese. The populations at risk for CCA and opisthorchiasis were used to create an arttribute database. Data were tranfered to WGS84 UTM ZONE 48. After the conversion, all of the data were imported into Google Earth using online web pages www.earthpoint.us. Some 222 from a 4,800 population at risk for CCA constituted a high risk group. Geo-visual display available at following www.google.com/maps/d/u/0/ edit?mid=zPxtcHv_iDLo.kvPpxl5mAs90 and hl=th. Geo-visual display 5 layers including: layer 1, village location and number of the population at risk for CCA; layer 2, sub-district health promotion hospital in Mueang Yang district and number of opisthorchiasis; layer 3, sub-district district and the number of population at risk for CCA; layer 4, district hospital and the number of population at risk for CCA and number of opisthorchiasis; and layer 5, district and the number of population at risk for CCA and number of opisthorchiasis. This GIS database and Google map production process is suitable for further monitoring, surveillance, and home health care for CCA sufferers.

Distribution of the Population at Risk of Cholangiocarcinoma in Bua Yai District, Nakhon Ratchasima of Thailand Using Google Map.

BACKGROUND: Cholangiocarcinoma (CCA), a major problem of health in Thailand, particularly in Northeastern and Northern regions, is generally incurable and rapidly lethal because of presentation in stage 3 or 4. Early diagnosis of stage 1 and 2 could allow better survival. Therefore, this study aimed to provide a distribution map of populations at risk for CCA in BuaYai district of Nakhon Ratchasima province, Northeast Thailand. MATERIALS AND METHODS: A cross-sectional survey was carried out in 10 sub-districts and 122 villages, during June and November 2015. The populations at risk for CCA were screened using the Korat CCA verbal screening test (KCVST) and then risk areas were displayed by using Google map (GM). RESULTS: A total of 11,435 individuals from a 26,198 population completed the KCVST. The majority had a low score of risk for CCA (1-4 points; 93.3%). High scores with 6, 7 and 8 points accounted for 1.20%, 0.13% and 0.02%. The population at risk was found frequently in sub-district municipalities, followed by sub-district administrative organization and town municipalities, (F=396.220, P-value=0.000). Distribution mapping comprised 11 layers: 1, district; 2, local administrative organization; 3, hospital; 4, KCVST opisthorchiasis; 5, KCVST praziquantel used; 6, KCVST cholelithiasis; 7, KCVST raw fish consumption; 8, KCVST alcohol consumption; 9, KCVST pesticide used; 10, KCVST relative family with CCA; and 11, KCVST naive northeastern people. Geovisual display is now available online. CONCLUSIONS: This study indicated that the population at high risk of CCA in Bua Yai district is low, therefore setting a zero model project is possible. Key success factors for disease prevention and control need further study. GM production is suitable for further CCA surveillance and monitoring of the population with a high risk score in this area.

Spatial Distribution of the Population at Risk of Cholangiocarcinoma in Chum Phaung District, Nakhon Ratchasima Province of Thailand.

BACKGROUND: Cholangiocarcinoma (CCA) is a serious health problem in Thailand, particularly in northeastern and northern regions, but epidemiological studies are scarce and the spatial distribution of CCA remains to be determined. A database for the population at risk is required for monitoring, surveillance and organization of home health care. This study aim was to geo-visually display the distribution of CCA in northeast Thailand, using a geographic information system and Google Earth. MATERIALS AND METHODS: A cross-sectional survey was carried out in 9 sub-districts and 133 villages in Chum Phuang district, Nakhon Ratchasima province during June and October 2015. Data on demography, and the population at risk for CCA were combined with the points of villages, sub-district boundaries, district boundaries, and points of hospitals in districts, then fed into a geographical information system. After the conversion, all of the data were imported into Google Earth for geo-visualization. RESULTS: A total of 11,960 from 83,096 population were included in this study. Females and male were 52.5%, and 47.8%, the age group 41-50 years old 33.3%. Individual risk for CCA was identifed and classified by using the Korat CCA verbal screening test as low (92.8%), followed by high risk (6.74%), and no (0.49%), respectively. Gender (X2-test=1143.63, p-value= 0.001), age group (X2-test==211.36, p-value=0.0001), and sub-district (X2-test=1471.858, p-value=0.0001) were significantly associated with CCA risk. Spatial distribution of the population at risk for CCA in Chum Phuang district was viewed with Google Earth. Geo-visual display followed Layer 1: District, Layer 2: Sub-district, Layer 3: Number of low risk in village, Layer 4: Number of high risk in village, and Layer 5: Hospital in Chum Phuang District and their related catchment areas. CONCLUSIONS: We present the first risk geo-visual display of CCA in this rural community, which is important for spatial targeting of control efforts. Risk appears to be strongly associated with gender, age group, and sub-district. Therefor, spatial distribution is suitable for the use in the further monitoring, surveillance, and home health care for CCA.

Risk Areas of Liver Flukes in Surin Province of Thailand using Geographic Information System.

BACKGROUND: Opisthorchiasis, caused by Opisthorchis viverrini, is of considerable public health importance in Southeast Asia, particularly in Lao PDR and Thailand. OBJECTIVE: This study aims to analyze the risk areas for liver flukes in Surin province, Thailand using Geographic Information Systems (GIS). MATERIAL AND METHOD: The 5 main factors (131 variables) were: (1) personal data (2) knowledge, attitude and practice, (3) health service unit, (4) environmental data, and (5) climate data. The relationship between these mainfactors and liver fluke infection was analyzed using multiple regression analysis. Potential surface analysis (PSA) with geographic information systems (GIS) was performed to create maps displaying areas at risk for liver fluke infection in Surin province. RESULTS: The population density (148-169 pop/km2; X73), human attitude (< 50%; X111), and land use (wetland; X64), were statistically significant with liver fluke infection by a percentage of 88.60% (Adjusted R2 = 0.886). The heavy risk areas covered 221.39 km2 and including 8 districts; Si Narong, Sangkha, Phnom Dong Rak, Mueang Surin, Non Narai, Samrong Thap, Chumphon Buri and Rattanaburi. CONCLUSION: Present study identifies the increased risk areas for liver flukes in Surin Province and may be useful for future planning of prevention and control.

GIS-based spatial statistical analysis of risk areas for liver flukes in Surin Province of Thailand.

It is urgently necessary to be aware of the distribution and risk areas of liver fluke, Opisthorchis viverrini, for proper allocation of prevention and control measures. This study aimed to investigate the human behavior, and environmental factors influencing the distribution in Surin Province of Thailand, and to build a model using stepwise multiple regression analysis with a geographic information system (GIS) on environment and climate data. The relationship between the human behavior, attitudes (<50%; X111), environmental factors like population density (148-169 pop/km2; X73), and land use as wetland (X64), were correlated with the liver fluke disease distribution at 0.000, 0.034, and 0.006 levels, respectively. Multiple regression analysis, by equations OV=-0.599+0.005(population density (148-169 pop/km2); X73)+0.040 (human attitude (<50%); X111)+0.022 (land used (wetland; X64), was used to predict the distribution of liver fluke. OV is the patients of liver fluke infection, R Square=0.878, and, Adjust R Square=0.849. By GIS analysis, we found Si Narong, Sangkha, Phanom Dong Rak, Mueang Surin, Non Narai, Samrong Thap, Chumphon Buri, and Rattanaburi to have the highest distributions in Surin province. In conclusion, the combination of GIS and statistical analysis can help simulate the spatial distribution and risk areas of liver fluke, and thus may be an important tool for future planning of prevention and control measures.