Prediction of province-level outbreaks of foot-and-mouth disease in Iran using a zero-inflated negative binomial model

Socioeconomic and environmental determinants of foot and mouth disease incidence: an ecological, cross-sectional study across Iran using spatial modeling

Foot-and-mouth disease (FMD) is a highly contagious animal disease caused by a ribonucleic acid (RNA) virus, with significant economic costs and uneven distribution across Asia, Africa, and South America. While spatial analysis and modeling of FMD are still in their early stages, this research aimed to identify socio-environmental determinants of FMD incidence in Iran at the provincial level by studying 135 outbreaks reported between March 21, 2017, and March 21, 2018. We obtained 46 potential socio-environmental determinants and selected four variables, including percentage of population, precipitation in January, percentage of sheep, and percentage of goats, to be used in spatial regression models to estimate variation in spatial heterogeneity. In our analysis, we employed global models, namely ordinary least squares (OLS), spatial error model (SEM), and spatial lag model (SLM), as well as local models, including geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR). The MGWR model yielded the highest adjusted [Formula: see text] of 90%, outperforming the other local and global models. Using local models to map the effects of environmental determinants (such as the percentage of sheep and precipitation) on the spatial variability of FMD incidence provides decision-makers with helpful information for targeted interventions. Our findings advocate for multiscale and multidisciplinary policies to reduce FMD incidence.

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

Foot-and-mouth disease (FMD) is one of the most important transboundary animal diseases affecting livestock and wildlife species worldwide. Sustained viral circulation, as evidenced by serological surveys and the recurrence of outbreaks, suggests endemic transmission cycles in some parts of Africa, Asia and the Middle East. This is the result of a complex process in which multiple serotypes, multi-host interactions and numerous socio-epidemiological factors converge to facilitate disease introduction, survival and spread. Spatial and spatio-temporal analyses have been increasingly used to explore the burden of the disease by identifying high-risk areas, analysing temporal trends and exploring the factors that contribute to the outbreaks. We systematically retrieved spatial and spatial-temporal studies on FMD outbreaks to summarize variations on their methodological approaches and identify the epidemiological factors associated with the outbreaks in endemic contexts. Fifty-one studies were included in the final review. A high proportion of papers described and visualized the outbreaks (72.5%) and 49.0% used one or more approaches to study their spatial, temporal and spatio-temporal aggregation. The epidemiological aspects commonly linked to FMD risk are broadly categorizable into themes such as (a) animal demographics and interactions, (b) spatial accessibility, (c) trade, (d) socio-economic and (e) environmental factors. The consistency of these themes across studies underlines the different pathways in which the virus is sustained in endemic areas, with the potential to exploit them to design tailored evidence based-control programmes for the local needs. There was limited data linking the socio-economics of communities and modelled FMD outbreaks, leaving a gap in the current knowledge. A thorough analysis of FMD outbreaks requires a systemic view as multiple epidemiological factors contribute to viral circulation and may improve the accuracy of disease mapping. Future studies should explore the links between socio-economic and epidemiological factors as a foundation for translating the identified opportunities into interventions to improve the outcomes of FMD surveillance and control initiatives in endemic contexts.

The roles of machine learning methods in limiting the spread of deadly diseases: A systematic review

Machine learning (ML) methods can be leveraged to prevent the spread of deadly infectious disease outbreak (e.g., COVID-19). This can be done by applying machine learning methods in predicting and detecting the deadly infectious disease. Most reviews did not discuss about the machine learning algorithms, datasets and performance measurements used for various applications in predicting and detecting the deadly infectious disease. In contrast, this paper outlines the literature review based on two major ways (e.g., prediction, detection) to limit the spread of deadly disease outbreaks. Hence, this study aims to investigate the state of the art, challenges and future works of leveraging ML methods to detect and predict deadly disease outbreaks according to two categories mentioned earlier. Specifically, this study provides a review on various approaches (e.g., individual and ensemble models), types of datasets, parameters or variables and performance measures used in the previous works. The literature review included all articles from journals and conference proceedings published from 2010 through 2020 in Scopus indexed databases using the search terms Predicting Disease Outbreaks and/or Detecting Disease using Machine Learning. The findings from this review focus on commonly used machine learning approaches, challenges and future works to limit the spread of deadly disease outbreaks through preventions and detections.

Spatiotemporal analysis of foot-and-mouth disease outbreaks in the Republic of Kazakhstan, 1955 - 2013

Foot-and-mouth disease (FMD) poses a significant obstacle to international trade and economic development, and for that reason, FMD prevention, control and eradication are major goals guiding animal health policy in most countries. The purpose of this study was to conduct a retrospective spatiotemporal analysis of FMD outbreaks among livestock in the Republic of Kazakhstan (RK) from 1955 to 2013. During that time, several FMD control strategies were implemented in RK, which culminated with the World Organization for Animal Health (OIE) recognition of RK as a country that is FMD-free with partial vaccination (2015). Here, we describe and analyse the changes in spatial and temporal dynamics of FMD under different control strategies that were utilized as the country progressively moved towards eradication of the disease. A total number of 5,260 FMD outbreaks of serotype O and A (including the A₂₂ lineage) were recorded in the cattle, pig and small ruminant populations of RK during that period. We found that outbreaks occurred in spatiotemporal clusters only prior to 1970, which is before ring vaccination around outbreaks was first employed. This finding suggests that ring vaccination substantially reduced local spread and prevented large FMD epidemics in the country. Disease incidence steadily decreased after the implementation of ring vaccination and culling of infected animals, with spatiotemporal clusters only occurring as a result of an introduction of an antigenically distinct variant of serotype A. From 1955 to 1984, FMD outbreaks demonstrated two seasonal peaks of incidence in the spring and fall. In contrast, only the peak in spring was observed between 1984 and 2013. Quantitative knowledge on how different policy and alternative control strategies contributed to RK achieving FMD-free status could improve prospects for continued control in RK and inform control strategies in other FMD-endemic regions.

Molecular and Serological Survey of Selected Viruses in Free-Ranging Wild Ruminants in Iran

A molecular and serological survey of selected viruses in free-ranging wild ruminants was conducted in 13 different districts in Iran. Samples were collected from 64 small wild ruminants belonging to four different species including 25 Mouflon (Ovis orientalis), 22 wild goat (Capra aegagrus), nine Indian gazelle (Gazella bennettii) and eight Goitered gazelle (Gazella subgutturosa) during the national survey for wildlife diseases in Iran. Serum samples were evaluated using serologic antibody tests for Peste de petits ruminants virus (PPRV), Pestiviruses [Border Disease virus (BVD) and Bovine Viral Diarrhoea virus (BVDV)], Bluetongue virus (BTV), Bovine herpesvirus type 1 (BHV-1), and Parainfluenza type 3 (PI3). Sera were also ELISA tested for Pestivirus antigen. Tissue samples including spleen, liver, lung, tonsils, mesenteric and mediastinal lymph nodes and white blood cells (WBCs) were tested using polymerase chain reaction (PCR) for PPRV, Foot and Mouth Disease virus (FMDV), Pestivirus, BTV, Ovine herpesvirus type 2 (OvHV-2) and BHV-1. Serologic tests were positive for antibodies against PPRV (17%), Pestiviruses (2%) and BTV (2%). No antibodies were detected for BHV-1 or PI3, and no Pestivirus antigen was detected. PCR results were positive for PPRV (7.8%), FMDV (11%), BTV (3%), OvHV-2 (31%) and BHV-1 (1.5%). None of the samples were positive for Pestiviruses.

Dissatisfaction with Veterinary Services Is Associated with Leopard (Panthera pardus) Predation on Domestic Animals

Human-carnivore conflicts challenge biodiversity conservation and local livelihoods, but the role of diseases of domestic animals in their predation by carnivores is poorly understood. We conducted a human-leopard (Panthera pardus) conflict study throughout all 34 villages around Golestan National Park, Iran in order to find the most important conflict determinants and to use them in predicting the probabilities of conflict and killing of cattle, sheep and goats, and dogs. We found that the more villagers were dissatisfied with veterinary services, the more likely they were to lose livestock and dogs to leopard predation. Dissatisfaction occurred when vaccination crews failed to visit villages at all or, in most cases, arrived too late to prevent diseases from spreading. We suggest that increased morbidity of livestock makes them particularly vulnerable to leopard attacks. Moreover, conflicts and dog killing were higher in villages located closer to the boundaries of the protected area than in distant villages. Therefore, we appeal for improved enforcement and coordination of veterinary services in our study area, and propose several priority research topics such as veterinarian studies, role of wild prey in diseases of domestic animals, and further analysis of potential conflict predictors.