Identification of foot and mouth disease risk areas using a multi-criteria analysis approach

Development and application of a WebGIS-based prediction system for multi-criteria decision analysis of porcine pasteurellosis

Porcine pasteurellosis is an infectious disease caused by Pasteurella multocida (P. multocida), which seriously endangers the healthy development of pig breeding industry. Early detection of disease transmission in animals is a crucial early warning for humans. Therefore, predicting risk areas for disease is essential for public health authorities to adopt preventive measures and control strategies against diseases. In this study, we developed a predictive model based on multi-criteria decision analysis (MCDA) and assessed risk areas for porcine pasteurellosis in the Chinese mainland. By using principal component analysis, the weights of seven spatial risk factors were determined. Fuzzy membership function was used to standardize all risk factors, and weight linear combination was used to create a risk map. The sensitivity of the risk map was analyzed by calculating the mean of absolute change rates of risk factors, as well as calculating an uncertainty map. The results showed that risk areas for porcine pasteurellosis were predicted to be locate in the south-central of the Chinese mainland, including Sichuan, Chongqing, Guangdong, and Guangxi. The maximum standard deviation of the uncertain map was less than 0.01and the ROC results showed that the prediction model has moderate predictive performance with the area under the curve (AUC) value of 0.80 (95% CI 0.75-0.84). Based on the above process, MCDA was combined with WebGIS technology to construct a system for predicting risk areas of porcine pasteurellosis. Risk factor data was directly linked to the developed model, providing decision support for disease prevention and control through monthly updates.

Unveiling the spatial distribution and transboundary pathways of FMD serotype O in Western China and its bordering countries

Foot-and-mouth disease (FMD) is a severe, highly contagious viral disease of livestock that has a significant economic impact on domestic animals and threatens wildlife survival in China and border countries. However, effective surveillance and prevention of this disease is often incomplete and unattainable due to the cost, the great diversity of wildlife hosts, the changing range and dynamics, and the diversity of FMDV. In this study, we used predictive models to reveal the spread and risk of FMD in anticipation of identifying key nodes to control its spread. For the first time, the spatial distribution of FMD serotype O was predicted in western China and border countries using a niche model, which is a combination of eco-geographic, human, topographic, and vegetation variables. The transboundary least-cost pathways (LCPs) model for ungulates in the study area were also calculated. Our study indicates that FMD serotype O survival is seasonal at low altitudes (March and June) and more sensitive to temperature differences at high altitudes. FMD serotype O risk was higher in Central Asian countries and both were highly correlated with the population variables. Ten LCPs were obtained representing Pakistan, Kazakhstan, Kyrgyzstan, and China.

A comparison of risk factor investigation and experts' opinion elicitation analysis for identifying foot-and-mouth disease (FMD) high-risk areas within the FMD protection zone of South Africa (2007-2016)

Foot-and-mouth disease is a controlled disease in accordance with the South African Animal Diseases Act (Act 35 of 1984). The country was classified by the World Organisation for Animal Health (WOAH) as having a FMD free zone without vaccination in 1996. However, this status was suspended in 2019 due to a FMD outbreak outside the controlled zones. FMD control in South Africa includes animal movement restrictions placed on cloven-hoofed species and products, prophylactic vaccination of cattle, clinical surveillance of susceptible species, and disease control fencing to separate livestock from wildlife reservoirs. The objectives of this study were to evaluate differences in identifying high-risk areas for FMD using risk factor and expert opinion elicitation analysis. Differences in risk between FMD introduction and FMD spread within the FMD protection zone with vaccination (PZV) of South Africa (2007-2016) were also investigated. The study was conducted in the communal farming area of the FMD PZV, which is adjacent to wildlife reserves and characterised by individual faming units. Eleven risk factors that were considered important for FMD occurrence and spread were used to build a weighted linear combination (WLC) score based on risk factor data and expert opinion elicitation. A multivariable conditional logistic regression model was also used to calculate predicted probabilities of a FMD outbreak for all dip-tanks within the study area. Smoothed Bayesian kriged maps were generated for 11 individual risk factors, overall WLC scores for FMD occurrence and spread and for predicted probabilities of a FMD outbreak based on the conditional logistic regression model. Descriptively, vaccine matching was believed to have a great influence on both FMD occurrence and spread. Expert opinion suggested that FMD occurrence was influenced predominantly by proximity to game reserves and cattle density. Cattle populations and vaccination practices were considered most important for FMD spread. Highly effective cattle inspections were observed within areas that previously reported FMD outbreaks, indicating the importance of cattle inspection (surveillance) as a necessary element of FMD outbreak detection. The multivariable conditional logistic regression analysis, which was consistent with expert opinion elicitation; identified three factors including cattle population density (OR 3.87, 95% CI 1.47-10.21) and proximities to game reserve fences (OR 0.82, 95% CI 0.73-0.92) and rivers (OR 1.04, 95% CI 1.01-1.07) as significant factors for reported FMD outbreaks. Regaining and maintaining an FMD-free status without vaccination requires frequent monitoring of high-risk areas and designing targeted surveillance.

A foot and mouth disease ranking of risk using cattle transportation

Foot-and-mouth disease (FMD) is a highly infectious condition that affects domestic and wild cloven-hoofed animals. This disease has substantial economic consequences. Livestock movement is one of the primary causes of disease dissemination. The centrality properties of the livestock mobilization transportation network provide valuable information for surveillance and control of FMD. However, the same transportation network can be described by different centrality descriptions, making it challenging to prioritize the most vulnerable nodes in the transportation network. This work considers the construction of a single network risk ranking, which helps prioritize disease control measurements. Results show that the proposed ranking constructed on 2016 livestock mobilization data may predict an actual outbreak reported in the Cesar (Colombia) region in 2018, with a performance measured by the area under the receiver operating characteristic curve of 0.91. This result constitutes the first quantitative evidence of the predictive capacity of livestock transportation to target FMD outbreaks. This approach may help decision-makers devise strategies to control and prevent FMD.

Compliance of biosecurity practices for compartmentalization to foot-mouth disease and classical swine fever viruses in commercial swine companies from southern Brazil

Classical swine fever (CSF) and foot-mouth disease (FMD) are both highly contagious disease and disruptive to commercial trades, but they are examples of foreign animal diseases that biosecurity-based compartmentalization could be used to support trade in free zones in response to an outbreak. This study aimed to evaluate biosecurity compliance to the Federal Normative Instruction #44 from December 4th, 2017 (BRAZIL, 2017) in commercial swine farms located in southern Brazil. A total of 604 swine farms from 10 commercial swine companies were sampled, from which 28.5% were breeding farms, 29.1% nursery, 32.8% finishing, 6.8% multipliers, and 2.8% farrow-to-finish. Cluster analyses revealed that farms with high compliance (n = 303, Cluster 1) performed 71% of the practices, moderate (n = 219, Cluster 2) 47%, and the low (n = 82, Cluster 3) 33%. A spatial logistic regression model estimated that biosecurity compliance was highest in only one of 10 commercial swine companies, and within a company, multipliers (when present) obtained the highest biosecurity compliance (p-value < 0.01). These results suggest that major improvements in biosecurity practices are needed in breeding herds, nursery, and grow-finish farms to be compliant to the Federal Instruction #44. Based on the combination of these analyses, only one commercial swine company was more suitable to establish compartments for CSF and FMD with minimal investments. Still, this study revealed that the majority of commercial swine companies needs to improve biosecurity practice protocols to then target compartmentalization.

Analysis of cattle movement networks in Paraguay: Implications for the spread and control of infectious diseases

Beef exports represent a substantial part of Paraguay's agricultural sector. Cattle movements involve a high risk due to the possible spread of bovine diseases that can have a significant impact on the country's economy. We analyzed cattle movements from 2014 to 2018 using the networks analysis methodology at the holding and district levels at different temporal scales. We built two types of networks to identify network characteristics that may contribute to the spread of two diseases with different epidemiological characteristics: i) a network including all cattle movements to consider the transmission of a disease of rapid spread like foot and mouth disease, and ii) a network including only cow movements to account for bovine brucellosis, a disease of slow spread that occurs mainly in adult females. Network indicators did not vary substantially among the cattle and cow only networks. The holdings/districts included in the largest strongly connected components were distributed throughout the country. Percolation analysis performed at the holding level showed that a large number of holdings should be removed to make the largest strongly connected component disappear. Higher values of the centrality indicators were found for markets than for farms, indicating that they may play an important role in the spread of an infectious disease. At the holding level (but not at the district level), the networks exhibited characteristics of small-world networks. This property may facilitate the spread of foot and mouth disease in case of re-emergence, or of bovine brucellosis in the country through cattle movements. They should be taken into account when implementing surveillance or control measures for these diseases.

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.

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

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-021-03084-5.

Development of an Index for the Inspection of Aedes aegypti Breeding Sites in Brazil: Multi-criteria Analysis

BACKGROUND

Aedes aegypti is a vector for the transmission of diseases such as dengue fever, chikungunya, Zika fever, and yellow fever. In 2016, over 1 million cases of these diseases were reported in Brazil, which is an alarming public health issue. One of the ways of controlling this disease is by inspecting and neutralizing the places where A. aegypti lays its eggs. The Ministry of Planning, Development, and Administration of Brazil maintains the inspection statistics.

OBJECTIVE

We propose a multi-criteria analysis to create an index for A. aegypti inspections reported through the Ministry of Planning, Development, and Administration system of Brazil.

METHODS

Based on the repository from urban cleaning services combined with data on inspections conducted by government agencies in several Brazilian cities and municipalities, we selected and combined metrics, which we further ranked using the analytic hierarchy process methodology. We also developed risk maps based on the analytic hierarchy process ranking of the A. aegypti breeding sites.

RESULTS

Based on our analysis and the available data, the priority for inspections should consider the number of sick people (weight 0.350), medical evaluations (weight 0.239), inspections (weight 0.201), mosquito breeding sites (weight 0.126), and days of absence from work (weight 0.096).

CONCLUSIONS

The proposed index could aid public health practitioners in preventing the appearance of new A. aegypti breeding sites. This information technology application can help solve such public health challenges.

Implementation of zoning to guide management of foot and mouth disease in Tunisia

The World Organisation for Animal Health advocates the zoning approach for the surveillance and monitoring of foot and mouth disease (FMD), a highly contagious animal disease. Our purpose is to implement the zoning approach in Tunisia by identifying existing natural and artificial barriers to the movement of live animals. A Geographic Information System (GIS)-based MultiCriteria Evaluation approach was developed. Eight national and international experts were asked to identify the barriers and prioritize them, characterized by a percentage weight between 0 and 100. These barriers were mapped and combined, taking into account their relative importance, to create a friction map that makes it possible to visualize areas where animal movements are restricted. Uncertainty analysis was performed to assess the robustness of the model. The results showed that the selected barriers were in order of decreasing importance: maritime borders with a weight of 33.5%, rivers (13.8%), slopes equal to or greater than 10% (13.8%), wetlands (13.3%), forests (7.7%), land borders (7.7%), railway networks (5%) and main roads (4.9%). The Cap Bon zone is the only favourable zoning area for the control of FMD in Tunisia. A regional approach resulting from this work could be a major asset in identifying regions suitable for zoning in North Africa.

Use of Network Analysis and Spread Models to Target Control Actions for Bovine Tuberculosis in a State from Brazil

Livestock movements create complex dynamic interactions among premises that can be represented, interpreted, and used for epidemiological purposes. These movements are a very important part of the production chain but may also contribute to the spread of infectious diseases through the transfer of infected animals over large distances. Social network analysis (SNA) can be used to characterize cattle trade patterns and to identify highly connected premises that may act as hubs in the movement network, which could be subjected to targeted control measures in order to reduce the transmission of communicable diseases such as bovine tuberculosis (TB). Here, we analyzed data on cattle movement and slaughterhouse surveillance for detection of TB-like lesions (TLL) over the 2016-2018 period in the state of Rio Grande do Sul (RS) in Brazil with the following aims: (i) to characterize cattle trade describing the static full, yearly, and monthly snapshots of the network contact trade, (ii) to identify clusters in the space and contact networks of premises from which animals with TLL originated, and (iii) to evaluate the potential of targeted control actions to decrease TB spread in the cattle population of RS using a stochastic metapopulation disease transmission model that simulated within-farm and between-farm disease spread. We found heterogeneous densities of premises and animals in the study area. The analysis of the contact network revealed a highly connected (~94%) trade network, with strong temporal trends, especially for May and November. The TLL cases were significantly clustered in space and in the contact network, suggesting the potential for both local (e.g., fence-to-fence) and movement-mediated TB transmission. According to the disease spread model, removing the top 7% connected farms based on degree and betweenness could reduce the total number of infected farms over three years by >50%. In conclusion, the characterization of the cattle network suggests that highly connected farms may play a role in TB dissemination, although being close to infected farms was also identified as a risk factor for having animals with TLL. Surveillance and control actions based on degree and betweenness could be useful to break the transmission cycle between premises in RS.

Network Analysis of Cattle Movement in Mato Grosso Do Sul (Brazil) and Implications for Foot-and-Mouth Disease

Foot-and mouth disease (FMD) is an animal disease that generates many economic impacts and sanctions on the international market. In 2018, Brazil, the world's largest beef exporter, had the recognition by World Organization for Animal Health (OIE) as a country free of FMD with vaccination and proposed to withdraw FMD vaccination throughout the country, based on a 10-year schedule, beginning in 2019. Therefore, Brazil needs studies to help the decision-making process, particularly regarding the availability of resources for strengthening of official animal health services. The state of Mato Grosso do Sul (MS) was chosen to be analyzed for three reasons: the size of its herd, the economic importance of its livestock and its location-which lies on the border with Paraguay and Bolivia. The current study adopted the Social Network Analysis and performed an exploratory analysis of cattle movement in MS. The most central municipalities in the networks were identified and they can be seen as crucial in strategies to monitor animal movement and to control outbreaks. The cattle movement networks demonstrated to be strongly connected, implying a high-speed potential FMD diffusion, in case of reintroduction. In a second stage, we performed an exploratory analysis of animal movement within the state, assuming distinct points in time for the identification of animal origin. The results of the analysis underlined the need and relevance of investing in animal control, sanitary education for producers and equipment and technologies to assist in the early detection, diagnosis, and eradication of outbreaks in a fast and efficient manner, preventing a possible outbreak from spreading to other regions.

Timeliness of vesicular disease notification system in Brazilian foot-and-mouth disease surveillance programme

Animal health surveillance programmes should be reliable and informative to ensure their effective implementation. As such, the regular assessment of those aiming to demonstrate the absence of disease, as well as the ability to detect outbreaks on time, is of vital importance. Several criteria make it possible to assess the performance of surveillance systems, including timeliness, which represents the speed between steps in a surveillance system. Therefore, the objective of this study was to evaluate the variability in the timeliness, within and between states, of the surveillance programme of the Brazilian Veterinary Services (BVS) for foot-and-mouth disease (FMD), for the notification of vesicular disease. A total of 14 years (2004-2017) of data relating to vesicular syndromes from the Brazilian Continental Information and Surveillance System (SivCont) were included. A categorical variable was created with four classes to group the notified vesicular processes in the SivCont, according to two criteria, the similarity of the symptoms of the diseases reported with FMD and aetiology (viral, bacterial, fungal and non-infectious). The three timeliness values (TL-1, TL-2 and TL-3) related to different portions of the FMD surveillance system were analysed as a response in a generalized linear model in which the states of Brazil were the explanatory variables. The analyses were performed separately for each notification class (FMD, vesicular stomatitis, similar symptoms and similar non-infectious symptoms) and included comparisons within and between states. The study results provide an understanding and evaluation of the timeliness of the Brazilian FMD surveillance system, thereby providing a base of knowledge from which involved agents and decision-makers can evaluate BVS and reinforce surveillance measures in the states with poorer timeliness than permitted.

Development and validation of a scoring system to assess the relative vulnerability of swine breeding herds to the introduction of PRRS virus

Biosecurity is defined as the set of practices carried out to prevent the introduction and spread of infectious agents in a herd. These practices are essential in swine production, especially for highly infectious agents such as porcine reproductive and respiratory syndrome virus (PRRSv). Even with years of research and experience over the last three decades, PRRSv is still causing productivity losses and is the major health problem affecting the global swine industry. Despite knowledge of the various ways in which the virus can be transmitted from one herd to another (e.g. animals, semen, truck, air, and people), determining the most frequent ways in which the virus is transmitted in the field is difficult. A systematic approach to assess vulnerabilities at a herd level related to PRRSv transmission could help producers prioritize biosecurity practices to reduce or avoid the occurrence of outbreaks. The aim of this study was to develop a biosecurity vulnerability score that represents the relative vulnerability of swine breeding herds to the introduction of PRRSv. To create the biosecurity vulnerability score (outcome), a multi-criteria decision analysis methodology was used to rank and quantify biosecurity practices based on expert opinion. To validate the biosecurity vulnerability score, a survey of biosecurity practices and PRRS outbreak histories in 125 breed-to-wean herds in the U.S. swine industry was used. Data on the frequency of PRRS outbreaks was used to test the hypothesis that biosecurity vulnerability scores were different between farms that have a low incidence of PRRS outbreaks, compared to farms that have a high incidence. In the two databases used, the scores consistently showed that farms with higher scores have a higher frequency of PRRS outbreaks. In the first validation, farms that had never had an outbreak investigation before had a significant (p < 0.02) lower score (0.29; 0.21-0.37) when compared to farms that had 2 or more outbreaks (0.43; 0.39-0.46). In the second, the farms of the control group also had significant (p < 0.004) lower scores (0.30; 0.27-0.33) compared to the case group (0.35; 0.33-0.38). Also, the results suggest that events related to swine movements, transmission by air and water, and people movements should be prioritized. The biosecurity vulnerability scores may be useful to assess vulnerabilities on biosecurity protocols in order to reduce the frequency of PRRS outbreaks and may help producers and veterinarians prioritize investments in improving biosecurity practices over time.

The Global Threats from Naturally Occurring Infectious Diseases

Biological risk relates to a broad spectrum of possible scenarios, that can be classified in three categories: natural occurring, unintended and deliberate. The prevention and management of such events require dedicated measures at national and international level, in terms of biosafety and biosecurity: an optimized intervention can minimize the probability of occurrence, but also adverse short-term (i.e.: number of casualties, population reaction…) and long-term (i.e.: chronic illnesses, ecological changes, trades drop…) consequences. Natural scenarios include common, emerging/re-emerging and chronic infectious diseases: they are caused by biological agents, which can be normally present in the communities, as acute or chronic pathologies, or suddenly appear, causing new or uncommon syndromes. In particular, a lot of environmental and human factors can influence emerging and re-emerging diseases: for example, urbanization and people mobility facilitate microorganisms spread, while climate changes are likely to induce a relocation of pathogens vectors. Unintended events are usually due to research and diagnostic activities: laboratories are the places where biological agents are handled and a lack in Biosafety measures or negligence can result in accidental release; the so called Laboratory Acquired Infections represent the main consequence, since they cause pathologies in the laboratory workers, but could be also transmitted in the population. Deliberate use of biological agents is strictly related to terroristic activities: microorganisms are very suitable for this purpose, since they are hidden and can easily spread. The present chapter summarizes the main characteristics of biological agents related events, taking in account their origin and the principal consequences on the community.