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

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.

A scoping review of foot‐and‐mouth disease risk, based on spatial and spatio‐temporal analysis of outbreaks in endemic settings

“…Two of these studies also addressed factors connected to disease notification (Chhetri et al., 2010 ; Jafarzadeh et al., 2014 ). Four studies focused only on forecasting FMD outbreaks using epidemiological factors as co‐variates to predict areal FMDv suitability, estimate spatial risk (number of outbreaks) or to detect spatial abnormalities in FMD passive surveillance data (Haoran et al., 2021 ; Perez et al., 2006 ; Richards et al., 2014 ; Sangrat et al., 2020 ).…”

“…Six models implemented a Bayesian framework to model the spatial or spatial‐temporal distribution of FMD (Allepuz et al., 2015 ; Branscum et al., 2008 ; Chhetri et al., 2010 ; Choi et al., 2012 ; Gunasekera et al., 2022 ; Richards et al., 2014 ). Other spatial analysis included the use of co‐kriging method to assess the probability of FMD incidence (Perez et al., 2006 ); Maximum Entropy Ecological Niche (MaxEnt) modelling to detect suitable areas for FMDV serotypes (Gao & Ma, 2021 ); GIS‐based multi‐criterion decision analysis to predict suitability for FMD occurrence (Haoran et al., 2021 ; Sangrat et al., 2020 ); point process model to explain outbreak intensity (Hamoonga et al., 2014 ) and regression tree analysis to identify predictors and interactions that influence FMD occurrence (Souley Kouato et al., 2018 ).…”

“…Complex or 'simple' causal pathways, influenced by data availability, contextual knowledge and previously reported risk factors, were assessed to undercover atrisk areas. Many risk factors for FMDv have been documented on knowledge-driven initiatives aimed to identify risk areas, predict FMDv suitable territories or develop participatory qualitative or quantitative risk assessments to estimate the risk of incursion and spread in endemic and at-risk countries (Haoran et al, 2021;Sangrat et al, 2020). For instance, Dos Santos et al (2017) (Bessell et al, 2008;Rivas et al, 2004Rivas et al, , 2006).…”

Characterization of T-cell subsets in response to foot-and-mouth disease bivalent inactivated vaccine in Chinese Holstein cows

“…In China, FMD has caused substantial economic losses to dairy farms, with serotypes O and A being endemic in many provinces of northwest and southeast China since 2010 ( 10 ). The bivalent FMD vaccine has effectively controlled the spread of FMDV in China.…”

Foot and mouth disease: risk factors and control measures (review)

“…Незаконный ввоз продуктов животного происхождения из стран, неблагополучных по ящуру, остается одним из основных рисков его заноса. Такие продукты могут попасть животным, восприимчивых к ящуру [25,26,27,28] Используя эпизоотологические подходы, можно определить основные факторы риска, важные для возникновения ящура в отдельных регионах. Инструменты исследования должны включать интервью с владельцами животных и структурированные опросники.…”