Risk maps for the spread of highly pathogenic avian influenza in poultry

Devastating epidemics of highly contagious animal diseases such as avian influenza, classical swine fever, and foot-and-mouth disease underline the need for improved understanding of the factors promoting the spread of these pathogens. Here the authors present a spatial analysis of the between-farm transmission of a highly pathogenic H7N7 avian influenza virus that caused a large epidemic in The Netherlands in 2003. The authors developed a method to estimate key parameters determining the spread of highly transmissible animal diseases between farms based on outbreak data. The method allows for the identification of high-risk areas for propagating spread in an epidemiologically underpinned manner. A central concept is the transmission kernel, which determines the probability of pathogen transmission from infected to uninfected farms as a function of interfarm distance. The authors show how an estimate of the transmission kernel naturally provides estimates of the critical farm density and local reproduction numbers, which allows one to evaluate the effectiveness of control strategies. For avian influenza, the analyses show that there are two poultry-dense areas in The Netherlands where epidemic spread is possible, and in which local control measures are unlikely to be able to halt an unfolding epidemic. In these regions an epidemic can only be brought to an end by the depletion of susceptible farms by infection or massive culling. The analyses provide an estimate of the spatial range over which highly pathogenic avian influenza viruses spread between farms, and emphasize that control measures aimed at controlling such outbreaks need to take into account the local density of farms.     

Estimating the per-contact probability of infection by highly pathogenic avian influenza (H7N7) virus during the 2003 epidemic in The Netherlands

Estimates of the per-contact probability of transmission between farms of Highly Pathogenic Avian Influenza virus of H7N7 subtype during the 2003 epidemic in the Netherlands are important for the design of better control and biosecurity strategies. We used standardized data collected during the epidemic and a model to extract data for untraced contacts based on the daily number of infectious farms within a given distance of a susceptible farm. With these data, we used a maximum likelihood estimation approach to estimate the transmission probabilities by the individual contact types, both traced and untraced. The estimated conditional probabilities, conditional on the contact originating from an infectious farm, of virus transmission were: 0.000057 per infectious farm within 1 km per day, 0.000413 per infectious farm between 1 and 3 km per day, 0.0000895 per infectious farm between 3 and 10 km per day, 0.0011 per crisis organisation contact, 0.0414 per feed delivery contact, 0.308 per egg transport contact, 0.133 per other-professional contact and, 0.246 per rendering contact. We validate these outcomes against literature data on virus genetic sequences for outbreak farms. These estimates can be used to inform further studies on the role that improved biosecurity between contacts and/or contact frequency reduction can play in eliminating between-farm spread of the virus during future epidemics. The findings also highlight the need to; 1) understand the routes underlying the infections without traced contacts and, 2) to review whether the contact-tracing protocol is exhaustive in relation to all the farm's day-to-day activities and practices.     

Evolutionary analysis of inter-farm transmission dynamics in a highly pathogenic avian influenza epidemic

Phylogenetic studies have largely contributed to better understand the emergence, spread and evolution of highly pathogenic avian influenza during epidemics, but sampling of genetic data has never been detailed enough to allow mapping of the spatiotemporal spread of avian influenza viruses during a single epidemic. Here, we present genetic data of H7N7 viruses produced from 72% of the poultry farms infected during the 2003 epidemic in the Netherlands. We use phylogenetic analyses to unravel the pathways of virus transmission between farms and between infected areas. In addition, we investigated the evolutionary processes shaping viral genetic diversity, and assess how they could have affected our phylogenetic analyses. Our results show that the H7N7 virus was characterized by a high level of genetic diversity driven mainly by a high neutral substitution rate, purifying selection and limited positive selection. We also identified potential reassortment in the three genes that we have tested, but they had only a limited effect on the resolution of the inter-farm transmission network. Clonal sequencing analyses performed on six farm samples showed that at least one farm sample presented very complex virus diversity and was probably at the origin of chronological anomalies in the transmission network. However, most virus sequences could be grouped within clearly defined and chronologically sound clusters of infection and some likely transmission events between farms located 0.8-13 Km apart were identified. In addition, three farms were found as most likely source of virus introduction in distantly located new areas. These long distance transmission events were likely facilitated by human-mediated transport, underlining the need for strict enforcement of biosafety measures during outbreaks. This study shows that in-depth genetic analysis of virus outbreaks at multiple scales can provide critical information on virus transmission dynamics and can be used to increase our capacity to efficiently control epidemics.     

The flock-to-flock force of infection for scrapie in Britain

A postal survey of British sheep farmers provided information on the proportion of farms that experienced their first case of scrapie in each year between 1962 and 1998. We found no evidence of a large increase in the proportion of scrapie-affected farms prior to, during or following the epidemic of BSE in British cattle. After correcting for between-farm heterogeneity in the probability of acquiring scrapie, we estimated the yearly between-flock force of infection since 1962. The current force of infection is estimated at approximately 0.0045 per farm per year and combined with a simple model of scrapie spread provides an estimate of the average duration of a scrapie outbreak on an individual farm. Considering all farms, the average outbreak lasts for five years, but if only those farms that have cases in animals born on the farm are considered, it lasts 15 years. We use these parameter estimates to compare the proportion of farms with scrapie in time periods of different lengths. In the survey, 2.7% of farms had a case in 1998. The 5.3% of farms reporting having a case between 1993 and 1997 is consistent with the hypothesis that the scrapie force of infection remained constant over this period.     

A Dynamic Spatio-Temporal Model to Investigate the Effect of Cattle Movements on the Spread of Bluetongue BTV-8 in Belgium

When Bluetongue Virus Serotype 8 (BTV-8) was first detected in Northern Europe in 2006, several guidelines were immediately put into place with the goal to protect farms and stop the spreading of the disease. This however did not prevent further rapid spread of BTV-8 across Northern Europe. Using information on the 2006 Bluetongue outbreak in cattle farms in Belgium, a spatio-temporal transmission model was formulated. The model quantifies the local transmission of the disease between farms within a municipality, the short-distance transmission between farms across neighbouring municipalities and the transmission as a result of cattle movement. Different municipality-level covariates such as farm density, land composition variables, temperature and precipitation, were assessed as possibly influencing each component of the transmission process. Results showed a significant influence of the different covariates in each model component, particularly the significant effect of temperature and precipitation values in the number of infected farms. The model which allowed us to predict the dynamic spreading of BTV for different movement restriction scenarios, also affirmed the significant impact of cattle movement in the 2006 BTV outbreak pattern. Simulation results further showed the importance of considering the size of restriction zones in the formulation of guidelines for animal infectious diseases.     

Accuracy of models for the 2001 foot-and-mouth epidemic

Since 2001 models of the spread of foot-and-mouth disease, supported by the data from the UK epidemic, have been expounded as some of the best examples of problem-driven epidemic models. These claims are generally based on a comparison between model results and epidemic data at fairly coarse spatio-temporal resolution. Here, we focus on a comparison between model and data at the individual farm level, assessing the potential of the model to predict the infectious status of farms in both the short and long terms. Although the accuracy with which the model predicts farms reporting infection is between 5 and 15%, these low levels are attributable to the expected level of variation between epidemics, and are comparable to the agreement between two independent model simulations. By contrast, while the accuracy of predicting culls is higher (20-30%), this is lower than expected from the comparison between model epidemics. These results generally support the contention that the type of the model used in 2001 was a reliable representation of the epidemic process, but highlight the difficulties of predicting the complex human response, in terms of control strategies to the perceived epidemic risk.     

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.     

Sheep Movement Networks and the Transmission of Infectious Diseases

Background and Methodology

Various approaches have been used to investigate how properties of farm contact networks impact on the transmission of infectious diseases. The potential for transmission of an infection through a contact network can be evaluated in terms of the basic reproduction number, R ₀. The magnitude of R ₀ is related to the mean contact rate of a host, in this case a farm, and is further influenced by heterogeneities in contact rates of individual hosts. The latter can be evaluated as the second order moments of the contact matrix (variances in contact rates, and co-variance between contacts to and from individual hosts). Here we calculate these quantities for the farms in a country-wide livestock network: >15,000 Scottish sheep farms in each of 4 years from July 2003 to June 2007. The analysis is relevant to endemic and chronic infections with prolonged periods of infectivity of affected animals, and uses different weightings of contacts to address disease scenarios of low, intermediate and high animal-level prevalence.

Principal Findings and Conclusions

Analysis of networks of Scottish farms via sheep movements from July 2003 to June 2007 suggests that heterogeneities in movement patterns (variances and covariances of rates of movement on and off the farms) make a substantial contribution to the potential for the transmission of infectious diseases, quantified as R ₀, within the farm population. A small percentage of farms (<20%) contribute the bulk of the transmission potential (>80%) and these farms could be efficiently targeted by interventions aimed at reducing spread of diseases via animal movement.     

An Epidemic of Salmonella Infantis Infection in Finnish Broiler Chickens in 1975–76

A large S. infantis infection epidemic in broiler chickens was studied during a period of one year. The outbreak affected three broiler producing companies in Finland. The infection spread to breeding farms according to available data during the summer of 1975. The epidemic still prevailed at the end of the studies on the farms of certain companies. The origin of the infection and the means of its spreading could not be ascertained. Some epidemiological evidence suggesting that a hatchery might have spread the infection was found. Contaminated feed may also have been involved, although the findings do not support feed as the principal vehicle in the epidemic. A complex pattern of transmission is most probable. A microbiological preventive method based on the feeding of a culture of intestinal flora of adult chickens to newly hatched broiler chickens was used on many farms in the study. The feeding of the culture lowered the proportion of infected flocks on the farms and significantly lowered the number of infected birds in those flocks, where the prevention was not complete. kw|Keywords|k]Salmonella infantis; k]infection; k]epidemic; k]broiler chicken     

The Influence of Between-Farm Distance and Farm Size on the Spread of Classical Swine Fever during the 1997–1998 Epidemic in The Netherlands

As the size of livestock farms in The Netherlands is on the increase for economic reasons, an important question is how disease introduction risks and risks of onward transmission scale with farm size (i.e. with the number of animals on the farm). Here we use the epidemic data of the 1997–1998 epidemic of Classical Swine Fever (CSF) Virus in The Netherlands to address this question for CSF risks. This dataset is one of the most powerful ones statistically as in this epidemic a total of 428 pig farms where infected, with the majority of farm sizes ranging between 27 and 1750 pigs, including piglets. We have extended the earlier models for the transmission risk as a function of between-farm distance, by adding two factors. These factors describe the effect of farm size on the susceptibility of a ‘receiving’ farm and on the infectivity of a ‘sending’ farm (or ‘source’ farm), respectively. Using the best-fitting model, we show that the size of a farm has a significant influence on both farm-level susceptibility and infectivity for CSF. Although larger farms are both more susceptible to CSF and, when infected, more infectious to other farms than smaller farms, the increase is less than linear. The higher the farm size, the smaller the effect of increments of farm size on the susceptibility and infectivity of a farm. Because of changes in the Dutch pig farming characteristics, a straightforward extrapolation of the observed farm size dependencies from 1997/1998 to present times would not be justified. However, based on our results one may expect that also for the current pig farming characteristics in The Netherlands, farm susceptibility and infectivity depend non-linearly on farm size, with some saturation effect for relatively large farm sizes.     

Epithelial expression of mRNA and protein for IL-6, IL-10 and TNF-α in endobronchial biopsies in horses with recurrent airway obstruction

Background  

Models of Foot and Mouth Disease (FMD) transmission have assumed a homogeneous landscape across which Euclidean distance is a suitable measure of the spatial dependency of transmission. This paper investigated features of the landscape and their impact on transmission during the period of predominantly local spread which followed the implementation of the national movement ban during the 2001 UK FMD epidemic. In this study 113 farms diagnosed with FMD which had a known source of infection within 3 km (cases) were matched to 188 control farms which were either uninfected or infected at a later timepoint. Cases were matched to controls by Euclidean distance to the source of infection and farm size. Intervening geographical features and connectivity between the source of infection and case and controls were compared.     

Molecular epidemiological analysis of the spread of human immunodeficiency virus (HIV) infection in the Novosibirsk region

The dynamics of the spread of individual subtypes of type 1 HIV (HIV-1), circulating in the Novosibirsk region during the epidemic rise of HIV infection was under study. The epidemic of HIV-1 in Novosibirsk has a pattern similar to that in Russia as a whole. At the initial stage of epidemics multiple sources of virus determine the heterogeneity of the isolated subtypes of HIV-1. Then the parenteral route of HIV transmission, connected with the intravenous use of narcotic drugs, becomes dominant. Recently the spread of HIV-1 from the group of intravenous drug users to other groups of the population has been observed. In the circulation of HIV-1 among drug users the leading role was shown to belong to subtype A, which ensures its rapid spread and dominating role in the epidemic process. Further spread of the HIV-1 epidemic is expected to proceed in parallel to the spread of viral hepatitis, sexually transmitted diseases and drug addiction. Thus, HIV-1, subtype A, may be assumed to be dominant in the Novosibirsk region in the nearest future.     

A Modeling Framework to Describe the Transmission of Bluetongue Virus within and between Farms in Great Britain

Background

Recently much attention has been given to developing national-scale micro-simulation models for livestock diseases that can be used to predict spread and assess the impact of control measures. The focus of these models has been on directly transmitted infections with little attention given to vector-borne diseases such as bluetongue, a viral disease of ruminants transmitted by Culicoides biting midges. Yet BT has emerged over the past decade as one of the most important diseases of livestock.

Methodology/Principal Findings

We developed a stochastic, spatially-explicit, farm-level model to describe the spread of bluetongue virus (BTV) within and between farms. Transmission between farms was modeled by a generic kernel, which includes both animal and vector movements. Once a farm acquired infection, the within-farm dynamics were simulated based on the number of cattle and sheep kept on the farm and on local temperatures. Parameter estimates were derived from the published literature and using data from the outbreak of bluetongue in northern Europe in 2006. The model was validated using data on the spread of BTV in Great Britain during 2007. The sensitivity of model predictions to the shape of the transmission kernel was assessed.

Conclusions/Significance

The model is able to replicate the dynamics of BTV in Great Britain. Although uncertainty remains over the precise shape of the transmission kernel and certain aspects of the vector, the modeling approach we develop constitutes an ideal framework in which to incorporate these aspects as more and better data become available. Moreover, the model provides a tool with which to examine scenarios for the spread and control of BTV in Great Britain.     

Molecular investigations of cytochrome c oxidase subunit I (COI) and the internal transcribed spacer (ITS) in the poultry red mite, Dermanyssus gallinae, in northern Europe and implications for its transmission between laying poultry farms

Samples of Dermanyssus gallinae (DeGeer) (Acari: Dermanyssidae) from more than 49 Norwegian and Swedish laying poultry farms, and additional samples collected from Scottish, Finnish, Danish and Dutch layer farms, were compared genetically. Analysis of partial mitochondrial gene cytochrome c oxidase subunit I (COI) sequences of mites from Norway and Sweden revealed 32 haplotypes. Only single haplotypes were found on most farms, which suggests that infections are recycled within farms and that transmission routes are few. Both Norwegian and Swedish isolates were found in the two major haplogroups, but no haplotypes were shared between Norway and Sweden, indicating little or no recent exchange of mites between these countries. There appears to be no link between haplotypes and geographical location as identical haplotypes were found in both the northern and southern Swedish locations, and haplotypes were scattered in locations between these extremes. The current data suggest that wild birds in Sweden are not a reservoir for D. gallinae infection of layer farms as their mites were genetically distinct from D. gallinae of farm layer birds. Transmission of the poultry red mite in Scandinavia is thus likely to depend on synantropic factors such as the exchange of contaminated material or infested birds between farms or facilities.     

Persistence of a Salmonella enterica serotype typhimurium clone in Danish pig production units and farmhouse environment studied by pulsed field gel electrophoresis (PFGE)

The clonal relationship among Salmonella enterica serotype Typhimurium isolates from selected pig production units in Denmark was investigated by the pulsed field gel electrophoresis (PFGE) typing method to determine environmental survival and spread of Salmonella in different herds. Thirty-four Typhimurium isolated during 1996-1998 from porcine faeces and environmental samples from three pig farms designated 1, 3 and 5 were characterised by PFGE using two restriction enzymes. Farm 5 supplied piglets to farm 1 and the herds were located close to each other. Results of PFGE analysis showed both intra- and inter-relationships, i.e. identical PFGE patterns among the faecal and environmental isolates from farm 1 and farm 5. All the isolates from farm 3 irrespective of the source showed identical PFGE patterns, but were different from samples from farms 1 and 5. This study indicates spread between farms and survival of a farm-specific clone. Furthermore, identical PFGE patterns of isolates from piglet supplier and finisher herds indicate that the farrow-to-grower herd of farm 5 was sub-clinically infected prior to delivery to farm 1 and thereby caused the transmission of Salmonella.     

High relative abundance of the stable fly Stomoxys calcitrans is associated with lumpy skin disease outbreaks in Israeli dairy farms

The vector of lumpy skin disease (LSD), a viral disease affecting Bovidae, is currently unknown. To evaluate the possible vector of LSD virus (LSDV) under field conditions, a yearlong trapping of dipterans was conducted in dairy farms that had been affected by LSD, 1‐2 years previously. This was done in order to calculate monthly relative abundances of each dipteran in each farm throughout the year. The relative abundances of Stomoxys calcitrans (Diptera: Muscidae) in the months parallel to the outbreaks (December and April) were significantly higher than those of other dipterans. A stable fly population model based on weather parameters for the affected area was used to validate these findings. Its results were significantly correlated with S. calcitrans abundance. This model, based on weather parameters during the epidemic years showed that S. calcitrans populations peaked in the months of LSD onset in the studied farms. These observations and model predictions revealed a lower abundance of stable flies during October and November, when LSD affected adjacent grazing beef herds. These findings therefore suggest that S. calcitrans is a potential vector of LSD in dairy farms and that another vector is probably involved in LSDV transmission in grazing herds. These findings should be followed up with vector competence studies.     

Fluctuations in the occurrence of Escherichia coli O157:H7 on a Norwegian farm*

AIM: To describe the distribution of Escherichia coli O157:H7 on a sporadically positive dairy farm and on possible contact farms over a one-year period. METHODS AND RESULTS: Environmental and faecal samples from all animals at the farm, and faecal samples from animals at contact farms were analysed for E. coli O157:H7 by immunomagnetic separation methods or VIDAS.Confirmed isolates were tested for cytotoxicity in the Vero cell assay and typed by PFGE. Escherichia coli O157:H7 (stx2 and eae) of the same PFGE type were isolated from cattle, sheep, hens and environmental samples at variable levels during summer and fall 2002, but were not detected in 2003. CONCLUSIONS: Escherichia coli O157:H7 had a widespread distribution on the farm investigated, but the original source of contamination could not be identified. The occurrence of this bacterium on the farm did not result in any detectable increase in gastrointestinal disease in the associated population. SIGNIFICANCE AND IMPACT OF THE STUDY: Despite a low endemic level of E. coli O157:H7 in the Norwegian cattle population, the growth and spread of this potentially important bacterium may occur.     

Seasonality and heterogeneity of live fish movements in Scottish fish farms

Movement of live animals is a key contributor to disease spread. Farmed Atlantic salmon Salmo salar, rainbow trout Onchorynchus mykiss and brown/sea trout Salmo trutta are initially raised in freshwater (FW) farms; all the salmon and some of the trout are subsequently moved to seawater (SW) farms. Frequently, fish are moved between farms during their FW stage and sometimes during their SW stage. Seasonality and differences in contact patterns across production phases have been shown to influence the course of an epidemic in livestock; however, these parameters have not been included in previous network models studying disease transmission in salmonids. In Scotland, farmers are required to register fish movements onto and off their farms; these records were used in the present study to investigate seasonality and heterogeneity of movements for each production phase separately for farmed salmon, rainbow trout and brown/sea trout. Salmon FW-FW and FW-SW movements showed a higher degree of heterogeneity in number of contacts and different seasonal patterns compared with SW-SW movements. FW-FW movements peaked from May to July and FW-SW movements peaked from March to April and from October to November. Salmon SW-SW movements occurred more consistently over the year and showed fewer connections and number of repeated connections between farms. Therefore, the salmon SW-SW network might be treated as homogeneous regarding the number of connections between farms and without seasonality. However, seasonality and production phase should be included in simulation models concerning FW-FW and FW-SW movements specifically. The number of rainbow trout FW-FW and brown/sea trout FW-FW movements were different from random. However, movements from other production phases were too low to discern a seasonal pattern or differences in contact pattern.     

Pair approximations and the inclusion of indirect transmission: theory and application to between farm transmission of Salmonella

The spatial-temporal dynamics of farm animal diseases depend both on disease specific processes and the underlying contact network between farms. Indirect transmission via free-living bacteria in the environment is an important transmission route and contributes significantly to the dynamics. The pair-wise model has been developed to include both direct transmission and indirect transmission via free stages. The model is compared with stochastic simulations of epidemics on contact networks. The network framework is applied to the investigation of the epidemiological dynamics of between-herd transmission of Salmonella spp. The main results help to explain differences in observed epidemiological patterns and to identify possible causes for different strains of Salmonella developing so much variation in their infection dynamics in UK dairy herds. Numerical results show that shorter infectious period, more persistent immune response and more rapid removal of faeces result in a lower prevalence of infection and a greater tendency for (damped) oscillation. A possible control strategy is consequently suggested. Furthermore, the effect of network structure on long-term dynamics is examined.     

Arcobacter population dynamics in pigs on farrow-to-finish farms

Healthy pigs are an important reservoir for the emerging human pathogen Arcobacter which can result in contamination of porcine carcasses and pork and the spread of arcobacters into the environment. Up to now, the excretion of arcobacters by pigs has been studied, but information about the transmission routes in fattening pigs is lacking. The present study aimed to elucidate the Arcobacter population dynamics in pigs during the fattening period on four farrow-to-finish farms. On each farm, 30 clinically healthy, 12-week-old piglets were selected. Fecal samples were collected on 10 sampling occasions until a slaughter age of 30 weeks was reached. Arcobacter spp. were isolated by a selective method and identified by multiplex PCR. The genetic diversity was examined by amplified fragment length polymorphism and enterobacterial repetitive intergenic consensus PCR. The Arcobacter presence in the fecal samples on the four farms ranged from 11.3 to 50.0%, with excretion levels of up to 10(4) CFU/g feces. The ratio in which Arcobacter species were isolated varied between the farms and over time. Characterization revealed a high degree of genotypic diversity among the isolates. Arcobacter strains persisted and spread within the finishing unit during the fattening period. The occurrence of both unique and shared genotypes in pigs in adjacent and nonadjacent pens demonstrates that transmission routes other than fecal-oral transmission occur.