Prevalence and risk factors for foot and mouth disease infection in cattle in Israel

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

In our study, we used geographic information system (GIS)-based multi-criteria decision analysis (MCDA) to predict suitable areas for foot and mouth disease (FMD) occurrence in Thailand. Eleven experts evaluated 10 spatial risk factors associated with the occurrence and spread of FMD in Thailand during 2014-2015. The analytic hierarchy process was used to conduct problem structuring and prioritising of pairwise comparisons with criterion weighting. Important spatial risk factors were converted to geographical layers using standardised fuzzy membership. Thus, weight linear combination was used to combine and create suitability and uncertainty maps as well as to perform sensitivity analysis. We identified areas in northern, north-eastern, western, and central Thailand as hotspots of FMD occurrence. In the predictive map, the suitable areas presented a moderate degree of agreement with those after FMD outbreaks in the year 2016 (AUC = 0.71, 95 %CI: 0.68-0.75). In conclusion, GIS-based MCDA mapping well supported veterinary services in identifying hotspot areas of FMD occurrence in Thailand. This tool was very useful for disease surveillance.

Seroepidemiology of foot and mouth disease (FMD) virus non-structural protein (NSP) antibodies in the livestock of Oman

Foot and mouth disease (FMD) is a highly contagious acute viral disease that causes severe economic losses to the affected countries. To estimate the serological prevalence of the local livestock to the natural infection with FMD virus, a cross-sectional study was conducted from 2015 to 2017 in Oman. Sera from 5807 randomly selected animals (1792 cattle, 2119 goats and 1896 sheep) belonging to 884 herds were tested for the presence of antibodies against 3ABC non-structural protein (NSP) of the FMD virus by a Competition ELISA. Prevalence along with confidence intervals (CI) and odds ratio (OR) was calculated, and the data were further analysed through univariable and multivariable techniques. The herd-level seroprevalence of NSP (41.4%) varied significantly among 11 governorates of Oman. At herd-level seroprevalence varied significantly among cattle (55.2%), goats (38.2%) and sheep (37.7%). At animal-level, the significantly higher prevalence was recorded in cattle (26.8%) followed by sheep (17.9%) and goats (17.3%). Binary logistic regression analysis at the individual level indicated that cattle (OR: 1.88), livestock above one year of age (OR: 3.47), imported breeds (OR: 1.82) and females (OR: 1.27) were the risk factors associated with higher prevalence. Whereas, sedentary (OR: 2.63) farming system, vaccination against FMD (OR: 5.98) and previous history of FMD (OR: 5.55) were the variables found associated with higher seroprevalence at the herd-level. We conclude that natural infection of FMDV is widespread in Oman and in future molecular typing of FMD virus outbreaks strains and vaccine matching studies should be employed to develop an effective control program in Oman.

Social network analysis for the assessment of pig, cattle and buffalo movement in Xayabouli, Lao PDR

The aim of this study is to understand the role that the movement patterns of pigs, cattle and buffalo play in the spread of foot-and-mouth disease (FMD). A cross-sectional survey consisting of a questionnaire was used in a hotspot area for FMD: Xayabouli Province, Lao People’s Democratic Republic. A total of 189 respondents were interviewed. We found that the key players in this network were people who were involved with more than one species of animal or occupation (multipurpose occupational node), which represents the highest number of activities of animals moved off the holding (shown with the highest out-degree centrality) and a high likelihood of being an intermediary between others (shown with the highest betweenness centrality). Moreover, the results show that the animals moved to and away from each node had few connections. Some nodes (such as traders) always received animals from the same group of cattle owners at different times. The subgroup connection within this network has many weak components, which means a connection in this network shows that some people can be reached by others, but most people were not. In this way, the number of connections present in the network was low when we defined the proportion of observed connections with all possible connections (density). These findings indicate that the network might not be busy; only one type of node is dominant which enables increased control of disease spread. We recommend that the relevant authorities implement control measures regarding the key players, which is the best way to effectively control the spread of infectious diseases.