Developing stochastic epidemiological models to quantify the dynamics of infectious diseases in domestic livestock

A stochastic model describing disease transmission dynamics for a microparasitic infection in a structured domestic animal population is developed and applied to hypothetical epidemics on a pig farm. Rational decision making regarding appropriate control strategies for infectious diseases in domestic livestock requires an understanding of the disease dynamics and risk profiles for different groups of animals. This is best achieved by means of stochastic epidemic models. Methodologies are presented for 1) estimating the probability of an epidemic, given the presence of an infected animal, whether this epidemic is major (requires intervention) or minor (dies out without intervention), and how the location of the infected animal on the farm influences the epidemic probabilities; 2) estimating the basic reproductive ratio, R0 (i.e., the expected number of secondary cases on the introduction of a single infected animal) and the variability of the estimate of this parameter; and 3) estimating the total proportion of animals infected during an epidemic and the total proportion infected at any point in time. The model can be used for assessing impact of altering farm structure on disease dynamics, as well as disease control strategies, including altering farm structure, vaccination, culling, and genetic selection.     

A novel method to identify herds with an increased probability of disease introduction due to animal trade

In the design of surveillance, there is often a desire to target high risk herds. Such risk-based approaches result in better allocation of resources and improve the performance of surveillance activities. For many contagious animal diseases, movement of live animals is a main route of transmission, and because of this, herds that purchase many live animals or have a large contact network due to trade can be seen as a high risk stratum of the population. This paper presents a new method to assess herd disease risk in animal movement networks. It is an improvement to current network measures that takes direction, temporal order, and also movement size and probability of disease into account. In the study, the method was used to calculate a probability of disease ratio (PDR) of herds in simulated datasets, and of real herds based on animal movement data from dairy herds included in a bulk milk survey for Coxiella burnetii. Known differences in probability of disease are easily incorporated in the calculations and the PDR was calculated while accounting for regional differences in probability of disease, and also by applying equal probability of disease throughout the population. Each herd's increased probability of disease due to purchase of animals was compared to both the average herd and herds within the same risk stratum. The results show that the PDR is able to capture the different circumstances related to disease prevalence and animal trade contact patterns. Comparison of results based on inclusion or exclusion of differences in risk also highlights how ignoring such differences can influence the ability to correctly identify high risk herds. The method shows a potential to be useful for risk-based surveillance, in the classification of herds in control programmes or to represent influential contacts in risk factor studies.     

Direct and indirect contacts between cattle farms in north-west England

Little is known regarding the types and frequencies of contact that exist between farms and which of these may act as pathogen transmission routes; however it is likely that farms demonstrate considerable heterogeneity in such contacts. In this cross-sectional study, we explored the direct and indirect contact types and frequencies that exist between cattle farms within a region, focusing on potential routes of pathogen transmission. The owners/managers of 56 farms located in a 10 km by 10 km study area in north-west England were administered an interview-based questionnaire between June and September 2005. Information was obtained relating to contact types and frequencies, including those involving animal movements, equipment sharing between farms and any contractors or companies visiting the farms.

The data was explored using hierarchical cluster analysis and network analysis. There was considerable variation between farms arising from different contact types. Some networks exhibited great connectivity, incorporating approximately 90% of the farms interviewed in a single component, whilst other networks were more fragmented, with multiple small components (sets of connected farms not linked with other farms). A range of factors influencing contact between farms were identified. For example, contiguous farms were more likely to be linked via other contacts, such as sharing of equipment and direct farm-to-farm animal movements (p < 0.001 and p = 0.02, respectively).

The frequency of contacts was also investigated; it is likely that the amount of contact a farm receives from a company or contractor and whether or not biosecurity is performed after contact would impact on disease transmission potential. We found considerable heterogeneity in contact frequency and that many company and contractor personnel undertook little biosecurity.

These findings lead to greater understanding of inter-farm contact and may aid development of appropriate biosecurity practices and control procedures, and inform mathematical modelling of infectious diseases.     

Relationship of trade patterns of the Danish swine industry animal movements network to potential disease spread

The movements of animals were analysed under the conceptual framework of graph theory in mathematics. The swine production related premises of Denmark were considered to constitute the nodes of a network and the links were the animal movements. In this framework, each farm will have a network of other premises to which it will be linked. A premise was a farm (breeding, rearing or slaughter pig), an abattoir or a trade market. The overall network was divided in premise specific subnets that linked the other premises from and to which animals were moved. This approach allowed us to visualise and analyse the three levels of organization related to animal movements that existed in the Danish swine production registers: the movement of animals between two premises, the premise specific networks, and the industry network. The analyses of animal movements were done using these three levels of organisation. The movements of swine were studied for the period September 30, 2002 to May 22, 2003. For daily movements of swine between two slaughter pig premises, the median number of pigs moved was 130 pigs with a maximum of 3306. For movements between a slaughter pig premise and an abattoir, the median number of pigs was 24. The largest percentage of movements was from farm to abattoir (82.5%); the median number of pigs per movement was 24 and the maximum number was 2018. For the whole period the median and maximum Euclidean distances observed in farm-to-farm movements were 22 km and 289 km respectively, while in the farm-to-abattoir movements, they were 36.2 km and 285 km. The network related to one specific premise showed that the median number of premises was mainly away from slaughter pig farms (3) or breeder farms (26) and mainly to an abattoir (1535). The assumption that animal movements can be randomly generated on the basis of farm density of the surrounding area of any farm is not correct since the patterns of animal movements have the topology of a scale-free network with a large degree of heterogeneity. This supported the opinion that the disease spread software assuming homogeneity in farm-to-farm relationship should only be used for large-scale interpretation and for epidemic preparedness. The network approach, based on graph theory, can be used efficiently to express more precisely, on a local scale (premise), the heterogeneity of animal movements. This approach, by providing network knowledge to the local veterinarian in charge of controlling disease spread, should also be evaluated as a potential tool to manage epidemics during the crisis. Geographic information systems could also be linked in the approach to produce knowledge about local transmission of disease.     

Exploring the role of auction markets in cattle movements within Great Britain

Within Great Britain cattle are often traded at regional markets, of which there are approximately 200 located throughout England, Scotland and Wales. The movement of animals through markets was important in the spread of foot-and-mouth disease (FMD) virus during the 2001 GB outbreak. Here, we describe the movements of cattle to and from markets for 2002-2004 and, using social network analysis, we construct networks based on these movements. In 2002, 56,227 animal holdings (AH) sent cattle to 222 cattle auction markets, compared to 58,476 AH and 187 auction markets in 2004. Auction markets vary considerably in their trading with AH. The majority of markets received animals from less than 50 AH, but one received animals from as many as 6155 AH during a year. The distances travelled between origin AH and destination AH when cattle move "directly" were found to be significantly shorter compared to distances between origin and destination AH where the movement occurred via a market. However, the vast majority of distances moved, for both types of movements, were less than 50 km. Some auction markets appear as highly connected premises within the contact network and are associated with high betweenness scores. However AH also occupy positions central to the contact network. The variation in the characteristics and role of individual markets within the contact network suggests important differences in risk of disease transmission associated with each market. Inclusion of network parameters, when considering the risk associated with moving cattle through auction markets may enhance the development of effective targeted disease control strategies.     

Network modeling of BVD transmission

ABSTRACT: Endemic diseases of cattle, such as bovine viral diarrhea, have significant impact on production efficiency of food of animal origin with consequences for animal welfare and climate change reduction targets. Many modeling studies focus on the local scale, examining the on-farm dynamics of this infectious disease. However, insight into prevalence and control across a network of farms ultimately requires a network level approach. Here, we implement understanding of infection dynamics, gained through these detailed on-farm modeling studies, to produce a national scale model of bovine viral diarrhea virus transmission. The complex disease epidemiology and on-farm dynamics are approximated using SIS dynamics with each farm treated as a single unit. Using a top down approach, we estimate on-farm parameters associated with contraction and subsequent clearance from infection at herd level. We examine possible control strategies associated with animal movements between farms and find measures targeted at a small number of high-movement farms efficient for rapid and sustained prevalence reduction.     

A survey of zoonotic diseases contracted by South African veterinarians

A survey of 88 veterinarians employed at the Faculty of Veterinary Science, University of Pretoria, South Africa, was carried out to investigate the occurrence of zoonotic diseases among South African veterinarians. The survey found that 63.6% of veterinarians interviewed had suffered from a zoonotic disease. Veterinarians predominantly involved in farm animal practice were 3 times more likely to have contracted a zoonotic disease than those working in other veterinary fields. Fifty-six percent of disease incidents were initially diagnosed by the veterinarians themselves. Fifty-three percent of incidents required treatment by a medical practitioner, but the majority (61%) of incidents did not require absence from work. The incidence density rate for contracting a zoonotic disease was 0.06 per person year of exposure. Kaplan-Meier survival analysis estimated that the probability of having contracted a zoonotic disease was 50% after 11 years in practice. The risk of contracting a zoonotic disease appeared to be higher early in practice. The most common mode of transmission was by direct contact. Approximately 46% of South Africans still live in rural areas and regularly come into close contact with farm animals. The implications of this in the light of this survey's results are discussed.     

Modelling the dynamics of the health-production complex in livestock herds: a review

This paper reviews how the dynamics of the health-production complex in livestock herds is mimicked by livestock herd simulation models. Twelve models simulating the dynamics of dairy, beef, sheep and sow herds were examined. All models basically included options to alter input and output of reproductive animals in a manner which could be related to health problems. Direct effects of diseases on growth or milk production were, however, addressed in only a few models and were confined to a few basic relations if modelled.

The lack of effects on individual animal production in the models may relate to difficulties in obtaining valid parameters for these effects. We recommend: (1) that disease-production relations be based on mechanistic, reasonable hypotheses at the animal level; or (2) that groups of animals be specified that have different disease-production relations. These relations and their interactions could be studied by applying the same standards of analysis to simulated data as to real herd data.     

Estimation of distance related probability of animal movements between holdings and implications for disease spread modeling

Between holding contacts are more common over short distances and this may have implications for the dynamics of disease spread through these contacts. A reliable estimation of how contacts depend on distance is therefore important when modeling livestock diseases. In this study, we have developed a method for analyzing distant dependent contacts and applied it to animal movement data from Sweden. The data were analyzed with two competing models. The first model assumes that contacts arise from a purely distance dependent process. The second is a mixture model and assumes that, in addition, some contacts arise independent of distance. Parameters were estimated with a Bayesian Markov Chain Monte Carlo (MCMC) approach and the model probabilities were compared. We also investigated possible between model differences in predicted contact structures, using a collection of network measures.We found that the mixture model was a much better model for the data analyzed. Also, the network measures showed that the models differed considerably in predictions of contact structures, which is expected to be important for disease spread dynamics. We conclude that a model with contacts being both dependent on, and independent of, distance was preferred for modeling the example animal movement contact data.     

Oxidants and antioxidants in disease: oxidative stress in farm animals

Important infectious diseases in farm animals, such as pneumonia and enteritis, are thought to be associated with the so-called oxidative stress, i.e. a chemical phenomenon involving an imbalance in the redox status of the individual animal. The specifics of oxidative stress and how it may result in disease or be prevented are complex questions with no simple answers. However, the considerable literature on the subject suggests that many researchers consider oxidative stress-related mechanisms to be important early events in disease development. A particularly intriguing aspect is that, at least theoretically, oxidative stress should be easily prevented with antioxidants yet the use of antioxidants as therapy remains controversial. The present knowledge on oxidative stress in farm animals is the topic of this review.     

猪日本乙型脑炎检测技术研究进展

猪日本乙型脑炎是由黄病毒科乙型脑炎病毒引起的一种人畜共患的病毒性传染病。人与多种动物均能感染,其中猪是主要的储存宿主和扩散宿主,猪感染该病毒后引发猪的繁殖障碍,使养猪业遭受重大经济损失,因此学者们一直在致力于寻找可以快速检测和诊断日本乙型脑炎的方法,为预防和治疗该病提供基础条件。文章对猪日本乙型脑炎检测技术,包括病毒分离鉴定方法、血清学方法、分子生物学方法等方面的研究进展进行了较为全面的综述。     

Network analysis of cattle and pig movements in Sweden: measures relevant for disease control and risk based surveillance

Registration of cattle and pig movements is mandatory in Sweden and all registered movements between farms in the years 2006-2008 were investigated using network analysis. The networks were analysed as monthly and yearly networks, separately per species and with the two species together. Measures that have been previously discussed in relation to outbreaks and disease control were calculated; moreover a measure of the ingoing infection chain was constructed. The ingoing infection chain captures ingoing contacts through other holdings, taking the temporal aspect and sequence of the movements into account. The distribution of the contacts among the holdings was skewed. Many farms had few or no contacts, while others had many, a pattern which has also been described from other countries. The cattle network and the combined network showed a recurring seasonal pattern, while this was not seen in the pig network. The in-degree was not equivalent to the ingoing infection chain; there were holdings with limited direct contacts, but a large number of indirect contacts. The ingoing infection chain could be a useful measure when setting up strategies for disease control and for risk based surveillance as it identifies holdings with many contacts through live animal movements and thus at potentially higher risk for introduction of contagious diseases.     

Presence of Escherichia coli carrying the EAST1 toxin gene in farm animals

Enteroaggregative Escherichia coli (EAEC) heat-stable toxin 1 (EAST1) is a small toxin of proteic nature. The reference strain producing this toxin was originally detected in the stools of a diarrheic Chilean child. Today, we know that EAST1 is not solely associated with EAEC but also with many other diarrheic E. coli families. Some studies have established the role of EAST1 in human outbreaks of diarrhea. In addition, isolates from farm animals were shown, more recently, to carry the astA gene coding for EAST1. However, the relation between the presence of EAST1 and disease is not conclusive. In this article, the current state of the knowledge on the presence and probable role of EAST1 in farm animal diseases is reviewed and discussed.     

Characterizing the Role of Animal Exposures in Cryptosporidiosis and Shiga Toxin‐producing Escherichia coli Infections: South Dakota, 2012

Cryptosporidium spp. and Shiga toxin‐producing Escherichia coli strains (STEC) are important causes of human illness. Incidence rates of these illnesses are high in South Dakota compared to the USA as a whole. Direct animal contact has been identified as a possible route of exposure for these illnesses. Ruminant animals may carry STEC subclinically, while young ruminants are common sources of zoonotic strains of Cryptosporidium. South Dakota patients with either STEC or cryptosporidiosis during 2012 were interviewed regarding seven categories of animal exposure: (i) petting zoo/fair attendance, (ii) animal event/rodeo attendance, (iii) feed/pet store visits, (iv) farm visits, (v) employment or residence at a farm, (vi) residence with pets and (vii) visiting other households with pets. Of the 50 STEC cases, 78.0% reported animal exposure prior to illness onset, with 23.3% having lived or worked on a farm. Farm visitors in particular had high degrees of animal contact and infrequently practiced personal protective measures. Of the 115 cryptosporidiosis cases, 87.8% reported animal exposures, with 45.6% having lived or worked on a farm and 29.0% having visited a farm prior to illness. Cases with farm exposures reported a high degree of direct animal contact and inconsistent use of personal protective measures. Cryptosporidiosis patients were significantly more likely than STEC patients to have lived or worked on a farm prior to their illness and were older on average. Patients with these illnesses had high rates of animal contact prior to illness. Animal contact on farms emerged as an important exposure route. Educational messages about personal protective measures should be directed at these individuals.     

Network analysis of Danish cattle industry trade patterns as an evaluation of risk potential for disease spread

Trade patterns of animal movements in a specific industry are complex and difficult to study because there are many stakeholders, premises that are heterogeneously spread over the country, and a highly dynamic flow of animals exists among them. The Danish cattle industry was defined as a network of animal movements and graph theory was used to analyse the movements of cattle within this network. A premise was defined as a farm, an abattoir or a market. These premises constituted the network nodes in the graph and the animal movements between them were the links. In this framework, each premise had a sub-network of other premises to which it was linked by these animal movements. If no movement of animals were registered for a specific farm, then the sub-network for that premise consisted of only that premise. Otherwise, the sub-network linked the premise of interest to all premises from which and to which animals were moved, as long as there was a path linking animal movements to that specific premise. This approach allowed visualization and analyses of four levels of organization that existed in Denmark animal registers: (1) the animal that was moved, (2) the movements of all animals between two premises, (3) the specific premise network, and (4) the overall industry network. When contagious animals are moved from one premise to another, then to a third and so forth, these movements create a path for potential transfer of pathogens. The paths within which pathogens are present identify the transmission risks. A network of animal movements should provide information about pathogen transmission and disease spread. The network of the Danish cattle industry network was a directed scale-free graph (the direction of a movement was known), with an in-degree power of 2 an out-degree power of 1.46, consisted of 29,999 nodes, and 130,265 movements during a 6-month period. The in clustering coefficient was calculated to be 0.52 for the inward direction (movement to), while it was 0.02 for the outward direction (movement from). In Denmark, the cattle movements between premises demonstrated a large degree of heterogeneity. This heterogeneity in movements between farms should be used to evaluate the risk potential of disease transmission for each premise and must be considered when modelling disease spread between premises. The objective of this research was to describe the network of animal movements and not just the animal movements per se.     

Notifiable animal diseases diagnosed at the Institute of Veterinary Pathology of the University of Zurich between 1988 and 2004

One of the essential tasks of veterinary pathology is the gross and microscopic examination of animals post mortem. Frequently requests are made for the cause of disease or death in the absence of a precise history or an otherwise specific assignment e.g. whether a notifiable disease is involved. The general examination is supplemented by a spectrum of additional examinations depending on the case whereas attempts are made to keep the costs within limits and to answer the client's request with justifiable effort. 36,365 necropsy cases and 9192 organs submitted between 1988 and 2004 were analysed to give indications on the number and type of notifiable diseases that were diagnosed in the course of routine diagnostic procedures. Notifiable animal diseases were discovered in 2918 cases (6.4% of all investigated cases) namely 2426 farm animals (9.1% of all farm animals) and 492 animals of other species (2.6% of all other animal species).These data illustrate the considerable value of pathological-anatomical examinations and compliment the figures from other databases.     

Associations of veterinary services and farmer characteristics with the prevalences of brucellosis and border disease in small ruminants in Spain

We investigated the farm factors associated with the prevalences of brucellosis and border disease (BD) in small-ruminant herds in the Madrid region of Spain. These infections were used as models of diseases of well-known and totally unknown distribution, respectively, to assess the association between the perception of the importance of a given disease on the relative contributions of veterinary services and the farmer's attitudes to its prevention. Sera, farming-management information and data concerning veterinary assistance and farmer characteristics were collected from 60 sheep or goat herds. The overall sero-prevalence of brucellosis was 5.7% (complement fixation) and for BD was 17.9% (ELISA test). The relationship between sero-positivity and the variables in the questionnaire was assessed by multivariable analysis using random-effects logistic-normal regression. ‘Availability of veterinary services' was a major protective factor for brucellosis. In contrast, no association with veterinary services was observed for BD, whereas ‘membership in a farmers' organization' (a variable associated with good farming practice and animal care) was a protective factor. ‘Membership of a farmers' organisation' and two other farmer variables indicative of good husbandry (‘youth' and ‘schooling') were associated with a lower sero-prevalence of brucellosis in univariable analysis but they did not remain significant in the multivariable model. Our observations suggest that veterinary-activity variables predominate over non-specific protective farm factors related to good husbandry in the case the disease is subject to disease surveillance. This underscores the importance of organized control programs for veterinary services to be effective in terms of animal disease prevention.     

A multi-analysis approach for space–time and economic evaluation of risks related with livestock diseases: The example of FMD in Peru

This study presents a multi-disciplinary decision-support tool, which integrates geo-statistics, social network analysis (SNA), spatial-stochastic spread model, economic analysis and mapping/visualization capabilities for the evaluation of the sanitary and socio-economic impact of livestock diseases under diverse epidemiologic scenarios. We illustrate the applicability of this tool using foot-and-mouth disease (FMD) in Peru as an example. The approach consisted on a flexible, multistep process that may be easily adapted based on data availability. The first module (mI) uses a geo-statistical approach for the estimation (if needed) of the distribution and abundance of susceptible population (in the example here, cattle, swine, sheep, goats, and camelids) at farm-level in the region or country of interest (Peru). The second module (mII) applies SNA for evaluating the farm-to-farm contact patterns and for exploring the structure and frequency of between-farm animal movements as a proxy for potential disease introduction or spread. The third module (mIII) integrates mI–II outputs into a spatial-stochastic model that simulates within- and between-farm FMD-transmission. The economic module (mIV) connects outputs from mI–III to provide an estimate of associated direct and indirect costs. A visualization module (mV) is also implemented to graph and map the outputs of module I–IV. After 1000 simulated epidemics, the mean (95% probability interval) number of outbreaks, infected animals, epidemic duration, and direct costs were 37 (1, 1164), 2152 (1, 13, 250), 63 days (0, 442), and US$ 1.2 million (1072, 9.5 million), respectively. Spread of disease was primarily local (<4.5 km), but geolocation and type of index farm strongly influenced the extent and spatial patterns of an epidemic. The approach is intended to support decisions in the last phase of the FMD eradication program in Peru, in particular to inform and support the implementation of risk-based surveillance and livestock insurance systems that may help to prevent and control potential FMD virus incursions into Peru.     

Epidemiological observations of Zimbabwean theileriosis: disease incidence and pathogenicity in susceptible cattle during Rhipicephalus appendiculatus nymphal and adult seasonal activity.

Fifty-nine Hereford cattle susceptible to tick-borne diseases were used as tracer animals to assess the tick challenge and pathogenicity of Theileria parva under field conditions in Zimbabwe. They were moved periodically in groups of five to three commercial farms (one group consisted of four) during seasons of Rhipicephalus appendiculatus nymphal and adult activity. All tracer cattle were herded together with the farm cattle but were not dipped. The nymphal tick counts were high on two of the farms (up to 2000 per animal) but were very low on the third farm (less than ten per animal). On the three farms, 19 out of 24 (76%) tracers had patent Theileria schizonts. There was a range of clinical manifestations of theileriosis with acute and fatal infections occurring on one farm. The adult R. appendiculatus infestations during the wet season numbered 120-800 per animal on the three farms. The disease transmitted by the adults was very pathogenic on the three farms; 30 out of 35 (86%) had severe theileriosis infections. Cattle, which survived the nymphal diseases challenge, showed various degrees of immunity to subsequent T. parva challenge transmitted by adult ticks. Therefore, 13 out of 18 (72%) of these cattle had a second disease episode and the case fatality rate on the three farms was 46%. The factors which determined the epidemiological status of Theileria challenge on the farms, such as the farming systems and presence of wild animals, are discussed.