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. 2021 Dec 6;17(1):374.
doi: 10.1186/s12917-021-03084-5.

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

Affiliations

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

Wang Haoran et al. BMC Vet Res. .

Abstract

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.

Keywords: Analytic hierarchy process; Foot-and-mouth disease; Multi-criteria decision analysis; Risk areas.

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Conflict of interest statement

All the authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
The prevalence of FMD in mainland China from 2010 to 2020. A Geographical distribution. B Annual outbreaks. C Monthly outbreaks. D The proportion of species affected. Uncertain: an outbreak of FMD at this location, but its serotype was not reported
Fig. 2
Fig. 2
Spatial distribution of FMD in mainland China from 2010 to 2020. A Number of FMD outbreaks. B Number of FMD cases. C Number of FMD destroyed. D Number of FMD deaths
Fig. 3
Fig. 3
Risk map of FMD in mainland China
Fig. 4
Fig. 4
Uncertainty map (The maximum standard deviation of 4000 adjusted-weight risk map)
Fig. 5
Fig. 5
Mean absolute values of the change rate (MACRs) for the risk maps under simulations. (Buffalo: buffalo density; Cattle: cattle density; Dis_Ls: distance to livestock market and slaughterhouse; Dis_Nb: distance to national boundaries; Dis_Ou: distance to previous outbreak points; Gazing: grazing area; Goat: goat density; Pig: pig density; Road: major road density; Sheep: sheep density.)
Fig. 6
Fig. 6
ROC of risk map
Fig. 7
Fig. 7
Study framework of FMD risk areas in mainland China based on spatial MCDA

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