Identification of risk areas for foot and mouth disease in Thailand using a geographic information system-based multi-criteria decision analysis

Sangrat, Waratida; Thanapongtharm, Weerapong; Poolkhet, Chaithep

doi:10.1016/j.prevetmed.2020.105183

Cited by 20 publications

(33 citation statements)

References 27 publications

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“…Where R k is the adjusted-weight risk map; R 0 is the initial risk map; N is the number of pixels [15].…”

Section: Sensitivity Analysis and Uncertaintymentioning

confidence: 99%

“…In this study, ve types of relationships were proposed (linear, increasing sigmoidal, decreasing sigmoidal, symmetrical, and bi-directional). Based on previous literature for the relationship between these risk factors and FMD, sigmoidal was nally determined [15]. Standardized spatial layer maps of all risk factors were calculated by fuzzy membership functions at a scale of 0-1 (unsuitable to perfectly suitable, Supplement 2).…”

Section: Study Frameworkmentioning

confidence: 99%

“…The majority of this work has likely resulted from OIE requirements to conduct risk and economic consequence assessments, resulting in most available assessments being narrowly focused on speci c geographic regions and often addressing OIE guidelines [14]. To avoid inaccuracy of assessment, countries have conducted FMD risk assessments based on local prevalence and risk factors, including Thailand and Brazil [15,16].…”

Section: Introductionmentioning

confidence: 99%

“…In health geography, this approach can re ect the complexity of spatial risk factors that affect the disease occurrence and consider multiple criteria for better understanding of disease characteristics [18]. For example, Sangrat et al modeled FMD risk areas in Thailand based on MCDA and showed that some regions in western, central, upper northern, northeastern, and southern Thailand were identi ed as risk areas for FMD, which were associated with a large number of previous FMD epidemics, distribution of livestock markets, and high density of cattle [15]. Weerapong et al identi ed three types of spatial risk factors for Nipah virus transmission in pig farms through expert assessment, which included natural host factors, intermediate host factors, and environmental factors, and the results indicated that risk areas were mainly concentrated around bat colonies [21].…”

Section: Introductionmentioning

confidence: 99%

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Assessment of foot-and-mouth disease risk areas in mainland China based spatial multi-criteria decision analysis

Wang

Jian-hua

Ouyang

et al. 2021

Preprint

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Background Foot-and-mouth disease (FMD) is a highly contagious viral disease of cloven-hoofed animals. As a transboundary animal disease, the prevention and control of FMD are important. This study was based on spatial multi-criteria decision analysis (MCDA) to assess FMD risk areas in mainland China. Ten risk factors were identified for constructing risk maps by scoring, and the analytic hierarchy process (AHP) was used to calculate the criteria weights of all factors. Different risk factors had different units and attributes, and fuzzy membership was used to standardize the risk factors. The weighted linear combination (WLC) and one-at-a-time (OAT) were used to obtain risk and uncertainty maps as well as to perform sensitivity analysis. Results Four major risk areas were identified in mainland China, including western (Xinjiang and Tibet), southern (Yunnan, Guizhou, Guangxi and Guangdong), northern (Gansu, Ningxia and Inner Mongolia), and eastern (Hebei, Henan, Anhui, Jiangsu and Shandong). We found spring as the main season for FMD outbreaks. Risk areas were associated with the distance to previous outbreak points, grazing areas and cattle density. Receiver operating characteristic (ROC) analysis indicated that the risk map had good predictive power (AUC = 0.8532). Conclusions These results can be used to delineate FMD risk areas in mainland China, and provinces can adopt the targeted preventive measures and control strategies.

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“…Where R k is the adjusted-weight risk map; R 0 is the initial risk map; N is the number of pixels [15].…”

Section: Sensitivity Analysis and Uncertaintymentioning

confidence: 99%

Section: Study Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessment of foot-and-mouth disease risk areas in mainland China based spatial multi-criteria decision analysis

Wang

Jian-hua

Ouyang

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…The majority of this work has likely resulted from OIE requirements to conduct risk and economic consequence assessments, resulting in most available assessments being narrowly focused on specific geographic regions and often addressing OIE guidelines [ 14 ]. To avoid inaccuracy of assessment, countries have conducted FMD risk assessments based on local prevalence and risk factors, including Thailand and Brazil [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Assessment of foot-and-mouth disease risk areas in mainland China based spatial multi-criteria decision analysis

et al. 2021

View full text Add to dashboard Cite

Background Foot-and-mouth disease (FMD) is a highly contagious viral disease of cloven-hoofed animals. As a transboundary animal disease, the prevention and control of FMD are important. This study was based on spatial multi-criteria decision analysis (MCDA) to assess FMD risk areas in mainland China. Ten risk factors were identified for constructing risk maps by scoring, and the analytic hierarchy process (AHP) was used to calculate the criteria weights of all factors. Different risk factors had different units and attributes, and fuzzy membership was used to standardize the risk factors. The weighted linear combination (WLC) and one-at-a-time (OAT) were used to obtain risk and uncertainty maps as well as to perform sensitivity analysis. Results Four major risk areas were identified in mainland China, including western (parts of Xinjiang and Tibet), southern (parts of Yunnan, Guizhou, Guangxi, Sichuan and Guangdong), northern (parts of Gansu, Ningxia and Inner Mongolia), and eastern (parts of Hebei, Henan, Anhui, Jiangsu and Shandong). Spring is the main season for FMD outbreaks. Risk areas were associated with the distance to previous outbreak points, grazing areas and cattle density. Receiver operating characteristic (ROC) analysis indicated that the risk map had good predictive power (AUC=0.8634). Conclusions These results can be used to delineate FMD risk areas in mainland China, and veterinary services can adopt the targeted preventive measures and control strategies.

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Assessment of groundwater sustainable development considering geo-environment stability and ecological environment: a case study in the Pearl River Delta, China

Huang

Zhou

2021

Environ Sci Pollut Res

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Identification of risk areas for foot and mouth disease in Thailand using a geographic information system-based multi-criteria decision analysis

Cited by 20 publications

References 27 publications

Assessment of foot-and-mouth disease risk areas in mainland China based spatial multi-criteria decision analysis

Assessment of foot-and-mouth disease risk areas in mainland China based spatial multi-criteria decision analysis

Assessment of foot-and-mouth disease risk areas in mainland China based spatial multi-criteria decision analysis

Assessment of groundwater sustainable development considering geo-environment stability and ecological environment: a case study in the Pearl River Delta, China

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