Assessment of the Risk of Foot and Mouth Disease among Beef Cattle at Slaughter from East African Production Systems.

Endemic foot and mouth disease (FMD) in East African cattle systems is one factor that limits access to export markets. The probability of FMD transmission associated with export from such systems have never been quantified and there is a need for data and analyses to guide strategies for livestock exports from regions where FMD remains endemic. The probability of infection among animals at slaughter is an important contributor to the risk of FMD transmission associated with the final beef product. In this study, we built a stochastic model to estimate the probability that beef cattle reach slaughter while infected with FMD virus for four production systems in two East African countries (Kenya and Uganda). Input values were derived from the primary literature and expert opinion. We found that the risk that FMD-infected animals reach slaughter under current conditions is high in both countries (median annual probability ranging from 0.05 among cattle from Kenyan feedlots to 0.62 from Ugandan semi-intensive systems). Cattle originating from feedlot and ranching systems in Kenya had the lowest overall probabilities of the eight systems evaluated. The final probabilities among cattle from all systems were sensitive to the likelihood of acquiring new infections en route to slaughter and especially the probability and extent of commingling with other cattle. These results give insight into factors that could be leveraged by potential interventions to lower the probability of FMD among beef cattle at slaughter. Such interventions should be evaluated considering the cost, logistics, and tradeoffs of each, ultimately guiding resource investment that is grounded in the values and capacity of each country.

Transmission network reconstruction for foot-and-mouth disease outbreaks incorporating farm-level covariates.

Transmission network modelling to infer 'who infected whom' in infectious disease outbreaks is a highly active area of research. Outbreaks of foot-and-mouth disease have been a key focus of transmission network models that integrate genomic and epidemiological data. The aim of this study was to extend Lau's systematic Bayesian inference framework to incorporate additional parameters representing predominant species and numbers of animals held on a farm. Lau's Bayesian Markov chain Monte Carlo algorithm was reformulated, verified and pseudo-validated on 100 simulated outbreaks populated with demographic data Japan and Australia. The modified model was then implemented on genomic and epidemiological data from the 2010 outbreak of foot-and-mouth disease in Japan, and outputs compared to those from the SCOTTI model implemented in BEAST2. The modified model achieved improvements in overall accuracy when tested on the simulated outbreaks. When implemented on the actual outbreak data from Japan, infected farms that held predominantly pigs were estimated to have five times the transmissibility of infected cattle farms and be 49% less susceptible. The farm-level incubation period was 1 day shorter than the latent period, the timing of the seeding of the outbreak in Japan was inferred, as were key linkages between clusters and features of farms involved in widespread dissemination of this outbreak. To improve accessibility the modified model has been implemented as the R package 'BORIS' for use in future outbreaks.

Incorporating Contact Network Uncertainty in Individual Level Models of Infectious Disease using Approximate Bayesian Computation.

Infectious disease transmission between individuals in a heterogeneous population is often best modelled through a contact network. However, such contact network data are often unobserved. Such missing data can be accounted for in a Bayesian data augmented framework using Markov chain Monte Carlo (MCMC). Unfortunately, fitting models in such a framework can be highly computationally intensive. We investigate the fitting of network-based infectious disease models with completely unknown contact networks using approximate Bayesian computation population Monte Carlo (ABC-PMC) methods. This is done in the context of both simulated data, and data from the UK 2001 foot-and-mouth disease epidemic. We show that ABC-PMC is able to obtain reasonable approximations of the underlying infectious disease model with huge savings in computation time when compared to a full Bayesian MCMC analysis.

Modeling the role of carrier and mobile herds on foot-and-mouth disease virus endemicity in the Far North Region of Cameroon.

Foot and mouth disease virus (FMDV) is an RNA virus that infects cloven-hoofed animals, often produces either epidemic or endemic conditions, and negatively affects agricultural economies worldwide. FMDV epidemic dynamics have been extensively studied, but understanding of drivers of disease persistence in areas in which FMDV is endemic, such as most of sub-Saharan Africa, is lacking. We present a spatial stochastic model of disease dynamics that incorporates a spatial transmission kernel in a modified Gillespie algorithm, and use it to evaluate two hypothesized drivers of endemicity: asymptomatic carriers and the movement of mobile herds. The model is parameterized using data from the pastoral systems in the Far North Region of Cameroon. Our computational study provides evidence in support of the hypothesis that asymptomatic carriers, but not mobile herds, are a driver of endemicity.

Phylogeographical and cross-species transmission dynamics of SAT1 and SAT2 foot-and-mouth disease virus in Eastern Africa.

Understanding the dynamics of foot-and-mouth disease virus (FMDV), an endemic and economically constraining disease, is critical in designing control programmes in Africa. This study investigates the evolutionary epidemiology of SAT1 and SAT2 FMDV in Eastern Africa, as well as between cattle and wild African buffalo. Bayesian phylodynamic models were used to analyse SAT1 and SAT2 VP1 gene segments collected between 1975 and 2016, focusing on the SAT1 and SAT2 viruses currently circulating in Eastern Africa. The root state posterior probabilities inferred from our analyses suggest Zimbabwe as the ancestral location for SAT1 currently circulating in Eastern Africa (p = 0.67). For the SAT2 clade, Kenya is inferred to be the ancestral location for introduction of the virus into other countries in Eastern Africa (p = 0.72). Salient (Bayes factor >10) viral dispersal routes were inferred from Tanzania to Kenya, and from Kenya to Uganda for SAT1 and SAT2, respectively. Results suggest that cattle are the source of the SAT1 and SAT2 clades currently circulating in Eastern Africa. In addition, our results suggest that the majority of SAT1 and SAT2 in livestock come from other livestock rather than wildlife, with limited evidence that buffalo serve as reservoirs for cattle. Insights from the present study highlight the role of cattle movements and anthropogenic activities in shaping the evolutionary history of SAT1 and SAT2 in Eastern Africa. While the results may be affected by inherent limitations of imperfect surveillance, our analysis elucidates the dynamics between host species in this region, which is key to guiding disease intervention activities.

Real-time decision-making during emergency disease outbreaks.

In the event of a new infectious disease outbreak, mathematical and simulation models are commonly used to inform policy by evaluating which control strategies will minimize the impact of the epidemic. In the early stages of such outbreaks, substantial parameter uncertainty may limit the ability of models to provide accurate predictions, and policymakers do not have the luxury of waiting for data to alleviate this state of uncertainty. For policymakers, however, it is the selection of the optimal control intervention in the face of uncertainty, rather than accuracy of model predictions, that is the measure of success that counts. We simulate the process of real-time decision-making by fitting an epidemic model to observed, spatially-explicit, infection data at weekly intervals throughout two historical outbreaks of foot-and-mouth disease, UK in 2001 and Miyazaki, Japan in 2010, and compare forward simulations of the impact of switching to an alternative control intervention at the time point in question. These are compared to policy recommendations generated in hindsight using data from the entire outbreak, thereby comparing the best we could have done at the time with the best we could have done in retrospect. Our results show that the control policy that would have been chosen using all the data is also identified from an early stage in an outbreak using only the available data, despite high variability in projections of epidemic size. Critically, we find that it is an improved understanding of the locations of infected farms, rather than improved estimates of transmission parameters, that drives improved prediction of the relative performance of control interventions. However, the ability to estimate undetected infectious premises is a function of uncertainty in the transmission parameters. Here, we demonstrate the need for both real-time model fitting and generating projections to evaluate alternative control interventions throughout an outbreak. Our results highlight the use of using models at outbreak onset to inform policy and the importance of state-dependent interventions that adapt in response to additional information throughout an outbreak.

Spatio-temporal patterns of foot-and-mouth disease transmission in cattle between 2007 and 2015 and quantitative assessment of the economic impact of the disease in Niger.

Foot-and-mouth disease (FMD) is endemic in Niger, with outbreaks occurring every year. Recently, there was an increasing interest from veterinary authorities to implement preventive and control measures against FMD. However, for an efficient control, improving the current knowledge on the disease dynamics and factors related to FMD occurrence is a prerequisite. The objective of this study was therefore to obtain insights into the incidence and the spatio-temporal patterns of transmission of FMD outbreaks in Niger based on the retrospective analysis of 9-year outbreak data. A regression tree analysis model was used to identify statistically significant predictors associated with FMD incidence, including the period (year and month), the location (region), the animal-contact density and the animal-contact frequency. This study provided also a first report on economic losses associated with FMD. From 2007 to 2015, 791 clinical FMD outbreaks were reported from the eight regions of Niger, with the number of outbreaks per region ranging from 5 to 309. The statistical analysis revealed that three regions (Dosso, Tillabery and Zinder), the months (September, corresponding to the end of rainy season, to December and January, i.e., during the dry and cold season), the years (2007 and 2015) and the density of contact were the main predictors of FMD occurrence. The quantitative assessment of the economic impacts showed that the average total cost of FMD at outbreak level was 499 euros, while the average price for FMD vaccination of one outbreak was estimated to be more than 314 euros. Despite some limitations of the clinical data used, this study will guide further research into the epidemiology of FMD in Niger and will promote a better understanding of the disease as well as an efficient control and prevention of FMD.

Bayesian inference of epidemiological parameters from transmission experiments.

Epidemiological parameters for livestock diseases are often inferred from transmission experiments. However, there are several limitations inherent to the design of such experiments that limits the precision of parameter estimates. In particular, infection times and latent periods cannot be directly observed and infectious periods may also be censored. We present a Bayesian framework accounting for these features directly and employ Markov chain Monte Carlo techniques to provide robust inferences and quantify the uncertainty in our estimates. We describe the transmission dynamics using a susceptible-exposed-infectious-removed compartmental model, with gamma-distributed transition times. We then fit the model to published data from transmission experiments for foot-and-mouth disease virus (FMDV) and African swine fever virus (ASFV). Where the previous analyses of these data made various assumptions on the unobserved processes in order to draw inferences, our Bayesian approach includes the unobserved infection times and latent periods and quantifies them along with all other model parameters. Drawing inferences about infection times helps identify who infected whom and can also provide insights into transmission mechanisms. Furthermore, we are able to use our models to measure the difference between the latent periods of inoculated and contact-challenged animals and to quantify the effect vaccination has on transmission.

Quantitative Assessment of the Risk of Release of Foot-and-Mouth Disease Virus via Export of Bull Semen from Israel.

Various foot-and-mouth disease (FMD) virus strains circulate in the Middle East, causing frequent episodes of FMD outbreaks among Israeli livestock. Since the virus is highly resistant in semen, artificial insemination with contaminated bull semen may lead to the infection of the receiver cow. As a non-FMD-free country with vaccination, Israel is currently engaged in trading bull semen only with countries of the same status. The purpose of this study was to assess the risk of release of FMD virus through export of bull semen in order to estimate the risk for FMD-free countries considering purchasing Israeli bull semen. A stochastic risk assessment model was used to estimate this risk, defined as the annual likelihood of exporting at least one ejaculate of bull semen contaminated with viable FMD virus. A total of 45 scenarios were assessed to account for uncertainty and variability around specific parameter estimates and to evaluate the effect of various mitigation measures, such as performing a preexport test on semen ejaculates. Under the most plausible scenario, the annual likelihood of exporting bull semen contaminated with FMD virus had a median of 1.3 * 10-7 for an export of 100 ejaculates per year. This corresponds to one infected ejaculate exported every 7 million years. Under the worst-case scenario, the median of the risk rose to 7.9 * 10-5 , which is equivalent to the export of one infected ejaculate every 12,000 years. Sensitivity analysis indicated that the most influential parameter is the probability of viral excretion in infected bulls.

U.K. Foot and Mouth Disease: A Systemic Risk Assessment of Existing Controls.

This article details a systemic analysis of the controls in place and possible interventions available to further reduce the risk of a foot and mouth disease (FMD) outbreak in the United Kingdom. Using a research-based network analysis tool, we identify vulnerabilities within the multibarrier control system and their corresponding critical control points (CCPs). CCPs represent opportunities for active intervention that produce the greatest improvement to United Kingdom's resilience to future FMD outbreaks. Using an adapted 'features, events, and processes' (FEPs) methodology and network analysis, our results suggest that movements of animals and goods associated with legal activities significantly influence the system's behavior due to their higher frequency and ability to combine and create scenarios of exposure similar in origin to the U.K. FMD outbreaks of 1967/8 and 2001. The systemic risk assessment highlights areas outside of disease control that are relevant to disease spread. Further, it proves to be a powerful tool for demonstrating the need for implementing disease controls that have not previously been part of the system.

Field application of a combined pig and poultry market chain and risk pathway analysis within the Pacific Islands region as a tool for targeted disease surveillance and biosecurity.

Limited resources are one of the major constraints in effective disease monitoring and control in developing countries. This paper examines the pig and poultry market chains of four targeted Pacific Island countries and territories (PICTs): Fiji, Papua New Guinea, Solomon Islands and Vanuatu and combines them with a risk pathway analysis to identify the highest risk areas (risk hotspots) and risky practices and behaviours (risk factors) of animal disease introduction and/or spread, using highly pathogenic avian influenza (HPAI) and foot-and-mouth disease (FMD) as model diseases because of their importance in the region. The results show that combining a market chain analysis with risk pathways is a practical way of communicating risk to animal health officials and improving biosecurity. It provides a participatory approach that helps officials to better understand the trading regulations in place in their country and to better evaluate their role as part of the control system. Common risk patterns were found to play a role in all four PICTs. Legal trade pathways rely essentially on preventive measures put in place in the exporting countries while no or only limited control measures are undertaken by the importing countries. Legal importations of animals and animal products are done mainly by commercial farms which then supply local smallholders. Targeting surveillance on these potential hotspots would limit the risk of introduction and spread of animal diseases within the pig and poultry industry and better rationalize use of skilled manpower. Swill feeding is identified as a common practice in the region that represents a recognized risk factor for dissemination of pathogens to susceptible species. Illegal introduction of animals and animal products is suspected, but appears restricted to small holder farms in remote areas, limiting the risk of spread of transboundary animal diseases along the market chain. Introduction of undeclared goods hidden within a legal trade activity was identified as a major risk pathway. Activities such as awareness campaigns for pig and poultry farmers regarding disease reporting, biosecurity measures or danger of swill feeding and training of biosecurity officers in basic animal health and import-associated risks are recommended to prevent and limit the spread of pathogens within the PICTs.

How do resources influence control measures during a simulated outbreak of foot and mouth disease in Australia?

An outbreak of foot and mouth disease (FMD) could seriously impact Australia's livestock sector and economy. As an FMD-free country, an outbreak would trigger a major disease control and eradication program that would include the culling of infected and at risk animals ('stamping out'), movement restrictions and zoo-sanitary measures. Additional control measures may also include pre-emptive culling or vaccination. However, it is unclear what disease strategy would be most effective under Australian conditions and different resource levels. Using a stochastic simulation model that describes FMD transmission between farms in a livestock dense region of Australia, our results suggest that using current estimates of human resource capacity for surveillance, infected premises operations and vaccination, outbreaks were effectively controlled under a stamping out strategy. However, under more constrained resource allocations, ring vaccination was more likely to achieve eradication faster than stamping out or pre-emptive culling strategies.

Impact of foot-and-mouth disease on pork and chicken prices in Central Luzon, Philippines.

Central Luzon is the number one pig-producing region in the Philippines and was affected by Foot-and-Mouth disease (FMD) in 1995. In this paper, the impact of FMD on the Central Luzon meat market from 1995 to 1999 was examined. Employing the error correction model (ECM) and historical decomposition, the impact of FMD on the Central Luzon pork and chicken meat market was quantified. The following findings were observed: (a) pig farm and pork wholesale prices dropped 11.8% and 15.7%, respectively, after the initial FMD outbreaks in January, 1995; (b) in February, 1995, chicken farm and wholesale prices declined by 21.1% and 14.2%, respectively (while chicken retail prices also went down by 10.5%); (c) the margins of pig and chicken traders were also adversely affected at some point; and (d) FMD caused changes of dynamic interdependence among prices by meat type at different levels of the meat supply chain. This study makes several contributions to the literature on the impact of FMD outbreaks. This study is the first that simultaneously investigates the impact of FMD outbreaks on meat prices, price margins along the supply chain, and price interdependence in the meat system in Central Luzon, Philippines. Also, the Philippine pork industry is dominated by backyard farmers rather than the predominantly large commercial pig farmers existing in developed countries. Secondly, it yielded the novel finding of price decline in both pig and chicken prices as a result of the FMD outbreaks. And lastly, the study showed that the profit margins of the pig traders, pork traders, chicken traders and chicken meat traders were also negatively affected by the FMD outbreaks in January 1995. However, over the long term, the price margins of pork traders were more severely affected in contrast to that of the other traders' profits.

Some challenges to progressive control of foot and mouth disease in Pakistan--findings of a pilot survey.

Pakistan is at an initial stage for progressive control of foot and mouth disease (FMD). Understanding the risk factors for introduction, spread and persistence of the infection is important to design an evidence-based disease control programme. A rapid appraisal method was adopted, and a convenient sample of twenty commercial dairy farmers was interviewed. The following were considered to contribute in secondary transmission of infection: (i) intermediaries and service providers [animal health workers, animal traders and transporters, raw milk collectors, persons who remove skin of dead animals], (ii) places where animals come in close contact [livestock markets, animal fairs, communal grazing pastures, routes in villages where livestock move, watering points, animal transport vehicles], (iii) use of bulls immediately after recovery from FMD infection, (iv) range land/desert livestock production, (v) small holder sheep and goat production, (vi) purchase of replacement stock and fodder from infected locations. This article reveals contacts within and between villages, some of which may act as routes of transmission of FMD. The study suggests the need for zoosanitary education of the livestock keepers.

Decisions on control of foot-and-mouth disease informed using model predictions.

The decision on whether or not to change the control strategy, such as introducing emergency vaccination, is perhaps one of the most difficult decisions faced by the veterinary authorities during a foot-and-mouth disease (FMD) epidemic. A simple tool that may predict the epidemic outcome and consequences would be useful to assist the veterinary authorities in the decision-making process. A previously proposed simple quantitative tool based on the first 14 days outbreaks (FFO) of FMD was used with results from an FMD simulation exercise. Epidemic outcomes included the number of affected herds, epidemic duration, geographical size and costs. The first 14 days spatial spread (FFS) was also included to further support the prediction. The epidemic data was obtained from a Danish version (DTU-DADS) of a pre-existing FMD simulation model (Davis Animal Disease Spread - DADS) adapted to model the spread of FMD in Denmark. The European Union (EU) and Danish regulations for FMD control were used in the simulation. The correlations between FFO and FFS and the additional number of affected herds after day 14 following detection of the first infected herd were 0.66 and 0.82, respectively. The variation explained by the FFO at day 14 following detection was high (P-value<0.001). This indicates that the FFO may take a part in the decision of whether or not to intensify FMD control, for instance by introducing emergency vaccination and/or pre-emptive depopulation, which might prevent a "catastrophic situation". A significant part of the variation was explained by supplementing the model with the FFS (P-value<0.001). Furthermore, the type of the index-herd was also a significant predictor of the epidemic outcomes (P-value<0.05). The results of the current study suggest that national veterinary authorities should consider to model their national situation and to use FFO and FFS to help planning and updating their contingency plans and FMD emergency control strategies.

Within-farm transmission dynamics of foot and mouth disease as revealed by the 2001 epidemic in Great Britain.

This paper uses statistical and mathematical models to examine the potential impact of within-farm transmission dynamics on the spread of the 2001 foot and mouth disease (FMD) outbreak in Great Britain. We partly parameterize a simple within farm transmission model using data from experimental studies of FMD pathogenesis, embed this model within an existing between-farm transmission model, and then estimate unknown parameters (such as the species-specific within-farm reproduction number) from the 2001 epidemic case data using Markov Chain Monte-Carlo (MCMC) methods. If the probability of detecting an infected premises depends on farm size and species mix then the within-farm species specific basic reproduction ratios for baseline models are estimated to be 21 (16, 25) and 14 (10, 19) for cattle and sheep, respectively. Alternatively, if detection is independent of farm size, then the corresponding estimates are 49 (41, 61) and 10 (1.4, 21). Both model variants predict that the average fraction of total farm infectiousness accumulated prior to detection of infection on an IP is about 30-50% in cattle or mixed farms. The corresponding estimate for sheep farms depended more on the detection model, being 65-80% if detection was linked to the farms' characteristics, but only 25% if not. We highlighted evidence which reinforces the role of within-farm dynamics in contributing to the long tail of the 2001 epidemic.

Modelling the within-host dynamics of the foot-and-mouth disease virus in cattle.

In this paper we investigate the within-host dynamics of the foot-and-mouth disease virus (FMDV) in cattle using previously published data for 8 experimentally infected cows. An 8-compartment, 14-parameter differential equation model was fitted to data collected from each cow every 24 h over the course of an infection on: (i) the concentration of FMDV genomes in the blood, (ii) the concentration of infectious virus in the blood, (iii) antibody levels, and (iv) interferon levels. Model parameters were estimated using maximum-likelihood methods. The likelihood surface was sampled using Markov chain Monte Carlo methods giving credible intervals for each of the model parameters. The model was able to capture the within-host dynamics well for 6 of the infections, with both the innate (type 1 interferon) and antibody responses playing key roles in determining the height and duration of peak levels of virus. There was considerable variation between virus dynamics in individual cattle which was only partly accounted for by inferred differences in the dose of virus received. A better understanding of the within-host dynamics also provides insights into the dynamics of infectiousness and the transmission of virus to new hosts.

Non-exponential tolerance to infection in epidemic systems--modeling, inference, and assessment.

The transmission dynamics of infectious diseases have been traditionally described through a time-inhomogeneous Poisson process, thus assuming exponentially distributed levels of disease tolerance following the Sellke construction. Here we focus on a generalization using Weibull individual tolerance thresholds under the susceptible-exposed-infectious-removed class of models which is widely employed in epidemics. Applications with experimental foot-and-mouth disease and historical smallpox data are discussed, and simulation results are presented. Inference is carried out using Markov chain Monte Carlo methods following a Bayesian approach. Model evaluation is performed, where the adequacy of the models is assessed using methodology based on the properties of Bayesian latent residuals, and comparison between 2 candidate models is also considered using a latent likelihood ratio-type test that avoids problems encountered with relevant methods based on Bayes factors.

A quantitative assessment of the risk of introducing foot and mouth disease virus into the United States via cloned bovine embryos.

The trade of livestock or their products between nations requires information on the risk of introducing infectious agents such as foot and mouth disease virus (FMDV). Although transmission pathways for FMDV vary, a recent concern in the United States (USA) is that it might enter via cloned embryos. A quantitative risk assessment model was developed to determine the scenarios (with mathematical probabilities) that could lead to the introduction and maintenance of FMDV via the importation of cloned bovine embryos. Using @RISK software with Monte Carlo simulation involving 50,000 iterations, the probability of introducing FMDV via cloned embryos was estimated to be 3.1 x 10(-7). Given the current cloning protocol, and assuming the annual importation of 250 to 1,700 (mean = 520) cloned embryos, the expected number of infected embryos ranges from 1.1 x 10(-7) to 4.4 x 10(-3) (mean = 1.6 x 10(-4)) per year. Critical pathway analysis showed that the risk of FMDV entering the USA by this route is extremely low.