Estimating risk factors for farm-level transmission of disease: Foot and mouth disease during the 2001 epidemic in Great Britain

Foot-and-Mouth Disease

Foot-and-mouth disease (FMD) is a viral infection of livestock that is an important determinant of global trade in animal products. The disease causes a highly contagious vesicular syndrome of cloven-hoofed animals. Successful control of FMD is dependent upon early detection and recognition of the clinical signs, followed by appropriate notification and response of responsible government entities. Awareness of the clinical signs of FMD amongst producers and veterinary practitioners is therefore the key in protecting US agriculture from the catastrophic impacts of an FMD outbreak. This review summarizes key clinical and epidemiologic features of FMD from a US perspective.

Spatiotemporal analysis of foot and mouth disease outbreaks in cattle and small ruminants in Türkiye between 2010 and 2019

Determining the dynamics associated with foot-and-mouth disease (FMD) outbreaks is important for being able to develop effective strategic plans against the disease. In this direction, spatiotemporal analysis of FMD virus (FMDV) epidemic data that occurred in Türkiye between 2010 and 2019 was carried out. Spatiotemporal analysis was performed by the space-time scan statistic using data from a total of 7,796 FMD outbreaks. Standard deviational ellipse analysis (SDE) was performed to analyse the directional trend of FMD. Five, six, and three significant and high-risk clusters were identified by the space-time cluster analysis for serotypes A, O, and Asia-1, respectively. The SDE analysis indicated that direction of FMD transmission was northeast to southwest. A significant decrease in the number of outbreaks and cases were observed between 2014 and 2019 compared to 2010-2013 (p = 0.010). Most of the serotype A, serotype O, and serotype Asia-1 associated FMD outbreaks were observed during the dry season (April to September). Among FMD cases, cattle and small ruminants accounted for 80.75% (180,932 cases) and 19.25% (43,116 cases), respectively. Among the serotypes detected in the cases, the most frequently detected serotype was serotype O (50.84%), followed by serotypes A (35.67%) and Asia-1 (13.49%). The results obtained in this study may contribute to when and where control programs could be implemented more efficiently for the prevention and control of FMD. Developing risk-defined regional control plans by taking into account the current livestock production including uncontrolled animal movements in border regions, rural livestock, livestock trade between provinces are recommended.

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.

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.

Challenges and opportunities for using national animal datasets to support foot-and-mouth disease control

National level databases of animal numbers, locations and movements provide the essential foundations for disease preparedness, outbreak investigations and control activities. These activities are particularly important for managing and mitigating the risks of high-impact transboundary animal disease outbreaks such as foot-and-mouth disease (FMD), which can significantly affect international trade access and domestic food security. In countries where livestock production systems are heavily subsidized by the government, producers are often required to provide detailed animal movement and demographic data as a condition of business. In the remaining countries, it can be difficult to maintain these types of databases and impossible to estimate the extent of missing or inaccurate information due to the absence of gold standard datasets for comparison. Consequently, competent authorities are often required to make decisions about disease preparedness and control based on available data, which may result in suboptimal outcomes for their livestock industries. It is important to understand the limitations of poor data quality as well as the range of methods that have been developed to compensate in both disease-free and endemic situations. Using FMD as a case example, this review first discusses the different activities that competent authorities use farm-level animal population data for to support (1) preparedness activities in disease-free countries, (2) response activities during an acute outbreak in a disease-free country, and (3) eradication and control activities in an endemic country. We then discuss (4) data requirements needed to support epidemiological investigations, surveillance, and disease spread modelling both in disease-free and endemic countries.

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.

Review of epidemiological risk models for foot-and-mouth disease: Implications for prevention strategies with a focus on Africa

Foot-and-mouth disease (FMD) is a highly infectious transboundary disease that affects domestic and wild cloven-hoofed animal species. The aim of this review was to identify and critically assess some modelling techniques for FMD that are well supported by scientific evidence from the literature with a focus on their use in African countries where the disease remains enzootic. In particular, this study attempted to provide a synopsis of the relative strengths and weaknesses of these models and their relevance to FMD prevention policies. A literature search was conducted to identify quantitative and qualitative risk assessments for FMD, including studies that describe FMD risk factor modelling and spatiotemporal analysis. A description of retrieved papers and a critical assessment of the modelling methods, main findings and their limitations were performed. Different types of models have been used depending on the purpose of the study and the nature of available data. The most frequently identified factors associated with the risk of FMD occurrence were the movement (especially uncontrolled animal movement) and the mixing of animals around water and grazing points. Based on the qualitative and quantitative risk assessment studies, the critical pathway analysis showed that the overall risk of FMDV entering a given country is low. However, in some cases, this risk can be elevated, especially when illegal importation of meat and the movement of terrestrial livestock are involved. Depending on the approach used, these studies highlight shortcomings associated with the application of models and the lack of reliable data from endemic settings. Therefore, the development and application of specific models for use in FMD endemic countries including Africa is encouraged.

Quantifying Transmission

Transmissibility is the defining characteristic of infectious diseases. Quantifying transmission matters for understanding infectious disease epidemiology and designing evidence-based disease control programs. Tracing individual transmission events can be achieved by epidemiological investigation coupled with pathogen typing or genome sequencing. Individual infectiousness can be estimated by measuring pathogen loads, but few studies have directly estimated the ability of infected hosts to transmit to uninfected hosts. Individuals' opportunities to transmit infection are dependent on behavioral and other risk factors relevant given the transmission route of the pathogen concerned. Transmission at the population level can be quantified through knowledge of risk factors in the population or phylogeographic analysis of pathogen sequence data. Mathematical model-based approaches require estimation of the per capita transmission rate and basic reproduction number, obtained by fitting models to case data and/or analysis of pathogen sequence data. Heterogeneities in infectiousness, contact behavior, and susceptibility can have substantial effects on the epidemiology of an infectious disease, so estimates of only mean values may be insufficient. For some pathogens, super-shedders (infected individuals who are highly infectious) and super-spreaders (individuals with more opportunities to transmit infection) may be important. Future work on quantifying transmission should involve integrated analyses of multiple data sources.

Epidemiology of Foot and Mouth Disease in Ethiopia: a Retrospective Analysis of District Level Outbreaks, 2007-2012

This study aimed at determining the incidence, distribution, risk factors, and causal serotypes of foot and mouth disease (FMD) outbreaks in Ethiopia based on 5 years of retrospective outbreak data (September 2007 until August 2012). District level outbreak data were collected from 115 randomly selected districts using a questionnaire administered to district animal health officers. The national incidence of FMD outbreaks during the study period was 1.45 outbreaks per five district years. Outbreaks were geographically widespread affecting all major regional states in the country and were more frequent in the central, southern, and southeastern parts of the country. Neither long-term nor seasonal trends were observed in the incidence of outbreaks. A mixed effects logistic regression analysis revealed that the type of production system (market oriented system versus subsistence systems), presence of a major livestock market and/or route, and adjacency to a national parks or wildlife sanctuary were found to be associated with increased risk of outbreaks in the districts. FMD virus serotypes O, A, SAT 2, and SAT 1 were identified as the causal serotypes of the outbreaks during the study period. Whereas O was the dominant serotype, SAT 2 was the serotype that showed increase in relative frequency of occurrence. The estimated incidence of outbreaks is useful in assessing the economic impacts of the disease, and the identified risk factors provide important knowledge to target a progressive FMD control policy for Ethiopia.

Distribution of cow-calf producers' beliefs regarding gathering and holding their cattle and observing animal movement restrictions during an outbreak of foot-and-mouth disease

The voluntary cooperation of producers with disease control measures such as movement restrictions and gathering cattle for testing, vaccination, or depopulation is critical to the success of many disease control programs. A cross-sectional survey was conducted in Texas in order to determine the distribution of key beliefs about obeying movement restrictions and gathering and holding cattle for disease control purposes. Two questionnaires were developed and distributed to separate representative samples of Texas cow-calf producers, respectively. The context for each behavior was provided through the use of scenarios in the questionnaire. Belief strength was measured using a 7-point Likert-like scale. Producers surveyed were unsure about the possible negative consequences of gathering and holding their cattle when requested by authorities, suggesting a key need for communication in this area during an outbreak. Respondents identified a lack of manpower and/or financial resources to gather and hold cattle as barriers to their cooperation with orders to gather and hold cattle. Producers also expressed uncertainty about the efficacy of movement restrictions to prevent the spread of foot-and-mouth disease and concern about possible feed shortages or animal suffering. However, there are emotional benefits to complying with movement restrictions and strong social expectations of cooperation with any movement bans put in place.

Vaccination against foot-and-mouth disease: do initial conditions affect its benefit?

When facing incursion of a major livestock infectious disease, the decision to implement a vaccination programme is made at the national level. To make this decision, governments must consider whether the benefits of vaccination are sufficient to outweigh potential additional costs, including further trade restrictions that may be imposed due to the implementation of vaccination. However, little consensus exists on the factors triggering its implementation on the field. This work explores the effect of several triggers in the implementation of a reactive vaccination-to-live policy when facing epidemics of foot-and-mouth disease. In particular, we tested whether changes in the location of the incursion and the delay of implementation would affect the epidemiological benefit of such a policy in the context of Scotland. To reach this goal, we used a spatial, premises-based model that has been extensively used to investigate the effectiveness of mitigation procedures in Great Britain. The results show that the decision to vaccinate, or not, is not straightforward and strongly depends on the underlying local structure of the population-at-risk. With regards to disease incursion preparedness, simply identifying areas of highest population density may not capture all complexities that may influence the spread of disease as well as the benefit of implementing vaccination. However, if a decision to vaccinate is made, we show that delaying its implementation in the field may markedly reduce its benefit. This work provides guidelines to support policy makers in their decision to implement, or not, a vaccination-to-live policy when facing epidemics of infectious livestock disease.

Estimation of the Infection Window for the 2010/2011 Korean Foot-and-Mouth Disease Outbreak

Objectives

This study aims to develop a method for calculating infection time lines for disease outbreaks on farms was developed using the 2010/2011 foot-and-mouth disease (FMD) epidemic in the Republic of Korea.

Methods

Data on farm demography, the detection date of FMD, the clinical history for the manifestation of lesions, the presence of antibodies against FMD virus (including antibodies against the structural and nonstructural proteins of serotype O), vaccination status (O1 Manisa strain), the number of reactors and information on the slaughter of infected animals were utilized in this method.

Results

Based on estimates of the most likely infection date, a cumulative detection probability that an infected farm would be identified on a specific day was determined. Peak infection was observed between late December and early January, but peak detection occurred in mid-January. The early detection probability was highest for pigs, followed by cattle (dairy, then beef) and small ruminants. Nearly 90% of the infected pig farms were detected by Day 11 post-infection while 13 days were required for detection for both dairy and beef cattle farms, and 21 days were necessary for small ruminant (goat and deer) farms. On average, 8.1 ± 3.1 days passed prior to detecting the presence of FMD virus on a farm. The interval between infection and detection of FMD was inversely associated with the intensity of farming.

Conclusion

The results of our study emphasize the importance of intensive clinical inspection, which is the quickest method of detecting FMD infection and minimizing the damage caused by an epidemic.

How to make predictions about future infectious disease risks

Formal, quantitative approaches are now widely used to make predictions about the likelihood of an infectious disease outbreak, how the disease will spread, and how to control it. Several well-established methodologies are available, including risk factor analysis, risk modelling and dynamic modelling. Even so, predictive modelling is very much the ‘art of the possible’, which tends to drive research effort towards some areas and away from others which may be at least as important. Building on the undoubted success of quantitative modelling of the epidemiology and control of human and animal diseases such as AIDS, influenza, foot-and-mouth disease and BSE, attention needs to be paid to developing a more holistic framework that captures the role of the underlying drivers of disease risks, from demography and behaviour to land use and climate change. At the same time, there is still considerable room for improvement in how quantitative analyses and their outputs are communicated to policy makers and other stakeholders. A starting point would be generally accepted guidelines for ‘good practice’ for the development and the use of predictive models.

Unravelling transmission trees of infectious diseases by combining genetic and epidemiological data

Knowledge on the transmission tree of an epidemic can provide valuable insights into disease dynamics. The transmission tree can be reconstructed by analysing either detailed epidemiological data (e.g. contact tracing) or, if sufficient genetic diversity accumulates over the course of the epidemic, genetic data of the pathogen. We present a likelihood-based framework to integrate these two data types, estimating probabilities of infection by taking weighted averages over the set of possible transmission trees. We test the approach by applying it to temporal, geographical and genetic data on the 241 poultry farms infected in an epidemic of avian influenza A (H7N7) in The Netherlands in 2003. We show that the combined approach estimates the transmission tree with higher correctness and resolution than analyses based on genetic or epidemiological data alone. Furthermore, the estimated tree reveals the relative infectiousness of farms of different types and sizes.