After the 2011 declaration of rinderpest disease eradication, we surveyed 150 countries about rinderpest virus stocks. Forty-four laboratories in 35 countries held laboratory-attenuated strains, field strains, or diagnostic samples. Vaccine and reagent production and laboratory experiments continued. Rigorous standards are necessary to ensure that stocks are kept under safe conditions.

Background

Rift Valley fever (RVF) is a zoonotic arbovirosis for which the primary hosts are domestic livestock (cattle, sheep and goats). RVF was first described in South Africa in 1950–1951. Mechanisms for short and long distance transmission have been hypothesised, but there is little supporting evidence. Here we describe RVF occurrence and spatial distribution in South Africa in 2008–11, and investigate the presence of a contagious process in order to generate hypotheses on the different mechanisms of transmission.

Methodology/Principal Findings

A total of 658 cases were extracted from World Animal Health Information Database. Descriptive statistics, epidemic curves and maps were produced. The space-time K-function was used to test for evidence of space-time interaction. Five RVF outbreak waves (one in 2008, two in 2009, one in 2010 and one in 2011) of varying duration, location and size were reported. About 70% of cases (n = 471) occurred in 2010, when the epidemic was almost country-wide. No strong evidence of space-time interaction was found for 2008 or the second wave in 2009. In the first wave of 2009, a significant space-time interaction was detected for up to one month and over 40 km. In 2010 and 2011 a significant intense, short and localised space-time interaction (up to 3 days and 15 km) was detected, followed by one of lower intensity (up to 2 weeks and 35 to 90 km).

Conclusions/Significance

The description of the spatiotemporal patterns of RVF in South Africa between 2008 and 2011 supports the hypothesis that during an epidemic, disease spread may be supported by factors other than active vector dispersal. Limitations of under-reporting and space-time K-function properties are discussed. Further spatial analyses and data are required to explain factors and mechanisms driving RVF spread.

Author Summary

The factors explaining Rift Valley fever (RVF) spread in domestic livestock during an epidemic are attributed to short and long distance mechanisms, including active vector dispersal, passive vector dispersal and movements of infectious animals. However, because of data scarcity, quantifying and disentangling these mechanisms remains challenging. Here, we generate hypotheses on the possible mechanisms involved in RVF spread in South Africa between 2008 and 2011. We use descriptive statistics and estimate the space-time K-function to explore the presence of space-time interactions, being interpreted as an indicator of an underlying transmission process. Our results confirm the presence of an intense, short, initial transmission process that could be attributed to active vector dispersal; but also highlight the presence of another transmission mechanism of a lower intensity and over further distances that could be explained by the movements of infectious animals, passive vector dispersal or emergence of other foci. Further data collection and modelling tools are required to confirm these hypotheses.

Background

Respiratory diseases account for significant economic losses to the UK pig industry. Lesions indicative of respiratory disease in pig lungs at slaughter e.g. pneumonia and pleuritis are frequently recorded to assess herd health or provide data for epidemiological studies. The BPEX Pig Health Scheme (BPHS) is a monitoring system, which informs producers of gross lesions in their pigs' carcasses at slaughter, enabling farm-level decisions to be made. The aim of the study was to assess whether information provided by the BPHS regarding respiratory lesions was associated with respiratory pathogens in the farm, farm management practices and each other.

Results

BPHS reports were obtained from a subset of 70 pig farms involved in a cross-sectional study conducted in 2008-09 investigating the epidemiology of post-weaning multi-systemic wasting syndrome. The reports were combined with data regarding the presence/absence of several pathogens in the herd and potential farm-level risk factors for respiratory disease. Principal component analysis (PCA) performed on BPHS reports generated three principal components, explaining 71% of the total variance. Enzootic pneumonia score, severe pleurisy and acute pleuropneumonia had the highest loadings for the principal component which explained the largest percentage of the total variance (35%) (BPHS component 1), it was thought that this component identifies farms with acute disease. Using the factor loadings a score for each farm for BPHS component 1 was obtained. As farms' score for BPHS component 1 increased, average carcass weight at slaughter decreased. In addition, farms positive for H1N2 and porcine reproductive and respiratory disease virus (PRRSV) were more likely to have higher levels of severe and mild pleurisy reported by the BPHS, respectively.

Conclusions

The study found statistical associations between levels of pleurisy recorded by BPHS at slaughter and the presence H1N2 and PRRSV in the herd. There is also some evidence that farms which submit pigs with these lesions may have reduced productivity. However, more research is needed to fully validate the scheme.

Highly pathogenic avian influenza (HPAI) H5N1 was first encountered in 1996 in Guangdong province (China) and started spreading throughout Asia and the western Palearctic in 2004–2006. Compared to several other countries where the HPAI H5N1 distribution has been studied in some detail, little is known about the environmental correlates of the HPAI H5N1 distribution in China. HPAI H5N1 clinical disease outbreaks, and HPAI virus (HPAIV) H5N1 isolated from active risk-based surveillance sampling of domestic poultry (referred to as HPAIV H5N1 surveillance positives in this manuscript) were modeled separately using seven risk variables: chicken, domestic waterfowl population density, proportion of land covered by rice or surface water, cropping intensity, elevation, and human population density. We used bootstrapped logistic regression and boosted regression trees (BRT) with cross-validation to identify the weight of each variable, to assess the predictive power of the models, and to map the distribution of HPAI H5N1 risk. HPAI H5N1 clinical disease outbreak occurrence in domestic poultry was mainly associated with chicken density, human population density, and elevation. In contrast, HPAIV H5N1 infection identified by risk-based surveillance was associated with domestic waterfowl density, human population density, and the proportion of land covered by surface water. Both models had a high explanatory power (mean AUC ranging from 0.864 to 0.967). The map of HPAIV H5N1 risk distribution based on active surveillance data emphasized areas south of the Yangtze River, while the distribution of reported outbreak risk extended further North, where the density of poultry and humans is higher. We quantified the statistical association between HPAI H5N1 outbreak, HPAIV distribution and post-vaccination levels of seropositivity (percentage of effective post-vaccination seroconversion in vaccinated birds) and found that provinces with either outbreaks or HPAIV H5N1 surveillance positives in 2007–2009 appeared to have had lower antibody response to vaccination. The distribution of HPAI H5N1 risk in China appears more limited geographically than previously assessed, offering prospects for better targeted surveillance and control interventions.

Author Summary

The geographical distribution of highly pathogenic avian influenza (HPAI) H5N1 and agro-ecological risk factors have been studied in a number of countries in Southeast Asia. However, little is know of its distribution in China where HPAI H5N1 first emerged in 1996, evolved, and spread throughout Asia and the western Palearctic in 2004–2006. This study analyzes separately the distribution, in domestic poultry, of HPAI virus (HPAIV) H5N1 isolated from active risk-based surveillance sampling and HPAI H5N1 clinical disease outbreaks. These data are analyzed in relation to the distribution of chicken and domestic waterfowl population density, proportion of land covered by rice or surface water, cropping intensity, elevation, and human population density. HPAI H5N1 viruses identified by risk-based surveillance are found to be associated with domestic waterfowl density, human population density, and the proportion of land covered by surface water. In contrast, HPAI H5N1 clinical disease outbreak occurrences were mainly associated with chicken density, human population density, and low elevation. These results show that the distribution of HPAI H5N1 risk in China appears more limited geographically than previously assessed, offering prospects for better targeted surveillance and control interventions.

While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify ‘hidden’ aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.

African swine fever (ASF) is a devastating haemorrhagic fever of pigs with mortality rates approaching 100 per cent. It causes major economic losses, threatens food security and limits pig production in affected countries. ASF is caused by a large DNA virus, African swine fever virus (ASFV). There is no vaccine against ASFV and this limits the options for disease control. ASF has been confined mainly to sub-Saharan Africa, where it is maintained in a sylvatic cycle and/or among domestic pigs. Wildlife hosts include wild suids and arthropod vectors. The relatively small numbers of incursions to other continents have proven to be very difficult to eradicate. Thus, ASF remained endemic in the Iberian peninsula until the mid-1990s following its introductions in 1957 and 1960 and the disease has remained endemic in Sardinia since its introduction in 1982. ASF has continued to spread within Africa to previously uninfected countries, including recently the Indian Ocean islands of Madagascar and Mauritius. Given the continued occurrence of ASF in sub-Saharan Africa and increasing global movements of people and products, it is not surprising that further transcontinental transmission has occurred. The introduction of ASF to Georgia in the Caucasus in 2007 and dissemination to neighbouring countries emphasizes the global threat posed by ASF and further increases the risks to other countries.

We review the mechanisms by which ASFV is maintained within wildlife and domestic pig populations and how it can be transmitted. We then consider the risks for global spread of ASFV and discuss possibilities of how disease can be prevented.

Background

Currently, the highly pathogenic avian influenza virus (HPAIV) of the subtype H5N1 is believed to have reached an endemic cycle in Vietnam. We used routine surveillance data on HPAIV H5N1 poultry outbreaks in Vietnam to estimate and compare the within-flock reproductive number of infection (R0) for periods before (second epidemic wave, 2004-5; depopulation-based disease control) and during (fourth epidemic wave, beginning 2007; vaccination-based disease control) vaccination.

Results

Our results show that infected premises (IPs) in the initial (exponential) phases of outbreak periods have the highest R0 estimates. The IPs reported during the outbreak period when depopulation-based disease control was implemented had higher R0 estimates than IPs reported during the outbreak period when vaccination-based disease control was used. In the latter period, in some flocks of a defined size and species composition, within-flock transmission estimates were not significantly below the threshold for transmission (R0 < 1).

Conclusions

Our results indicate that the current control policy based on depopulation plus vaccination has protected the majority of poultry flocks against infection. However, in some flocks the determinants associated with suboptimal protection need to be further investigated as these may explain the current pattern of infection in animal and human populations.

Highly pathogenic avian influenza (HPAI) virus H5N1 is now endemic in South-East Asia but HPAI control methods differ between countries. A widespread HPAI vaccination campaign that started at the end of 2005 in Viet Nam resulted in the cessation of poultry and human cases, but in 2006/2007 severe HPAI outbreaks re-emerged. In this study we investigated the pattern of this first post-vaccination epidemic in southern Viet Nam identifying a spatio-temporal cluster of outbreak occurrence and estimating spatially smoothed incidence rates of HPAI. Spatial risk factors associated with HPAI occurrence were identified. Medium-level poultry density resulted in an increased outbreak risk (Odds ratio (OR) = 5.4, 95% confidence interval (CI): 1.6–18.9) but also climate-vegetation factors played an important role: medium-level normalised difference vegetation indices during the rainy season from May to October were associated with higher risk of HPAI outbreaks (OR = 3.7, 95% CI: 1.7–8.1), probably because temporal flooding might have provided suitable conditions for the re-emergence of HPAI by expanding the virus distribution in the environment and by enlarging areas of possible contacts between domestic waterfowl and wild birds. On the other hand, several agricultural production factors, such as sweet potatoes yield, increased buffalo density, as well as increased electricity supply were associated with decreased risk of HPAI outbreaks. This illustrates that preventive control measures for HPAI should include a promotion of low-risk agricultural management practices as well as improvement of the infrastructure in village households. Improved HPAI vaccination efforts and coverage should focus on medium poultry density areas and on the pre-monsoon time period.

Background

In contrast to most pastoral systems, the Somali livestock production system is oriented towards domestic trade and export with seasonal movement patterns of herds/flocks in search of water and pasture and towards export points. Data from a rinderpest survey and other data sources have been integrated to explore the topology of a contact network of cattle herds based on a spatial proximity criterion and other attributes related to cattle herd dynamics. The objective of the study is to integrate spatial mobility and other attributes with GIS and network approaches in order to develop a predictive spatial model of presence of rinderpest.

Results

A spatial logistic regression model was fitted using data for 562 point locations. It includes three statistically significant continuous-scale variables that increase the risk of rinderpest: home range radius, herd density and clustering coefficient of the node of the network whose link was established if the sum of the home ranges of every pair of nodes was equal or greater than the shortest distance between the points. The sensitivity of the model is 85.1% and the specificity 84.6%, correctly classifying 84.7% of the observations. The spatial autocorrelation not accounted for by the model is negligible and visual assessment of a semivariogram of the residuals indicated that there was no undue amount of spatial autocorrelation. The predictive model was applied to a set of 6176 point locations covering the study area. Areas at high risk of having serological evidence of rinderpest are located mainly in the coastal districts of Lower and Middle Juba, the coastal area of Lower Shabele and in the regions of Middle Shabele and Bay. There are also isolated spots of high risk along the border with Kenya and the southern area of the border with Ethiopia.

Conclusions

The identification of point locations and areas with high risk of presence of rinderpest and their spatial visualization as a risk map will be useful for informing the prioritization of disease surveillance and control activities for rinderpest in Somalia. The methodology applied here, involving spatial and network parameters, could also be applied to other diseases and/or species as part of a standardized approach for the design of risk-based surveillance activities in nomadic pastoral settings.

Background

The structure of contact between individuals plays an important role in the incursion and spread of contagious diseases in both human and animal populations. In the case of avian influenza, the movement of live birds is a well known risk factor for the geographic dissemination of the virus among poultry flocks. Live bird markets (LBM's) contribute to the epidemiology of avian influenza due to their demographic characteristics and the presence of HPAI H5N1 virus lineages. The relationship between poultry producers and live poultry traders (LPT's) that operate in LBM's has not been adequately documented in HPAI H5N1-affected SE Asian countries. The aims of this study were to document and study the flow of live poultry in a poultry trade network in northern Vietnam, and explore its potential role in the risk for HPAI H5N1 during 2003 to 2006.

Results

Our results indicate that LPT's trading for less than a year and operating at retail markets are more likely to source poultry from flocks located in communes with a past history of HPAI H5N1 outbreaks during 2003 to 2006 than LPT's trading longer than a year and operating at wholesale markets. The results of the network analysis indicate that LPT's tend to link communes of similar infection status.

Conclusions

Our study provides evidence which can be used for informing policies aimed at encouraging more biosecure practices of LPT's operating at authorised LBM's. The results suggest that LPT's play a role in HPAI H5N1 transmission and may contribute to perpetuating HPAI H5N1 virus circulation amongst certain groups of communes. The impact of current disease prevention and control interventions could be enhanced by disseminating information about outbreak risk and the implementation of a formal data recording scheme at LBM's for all incoming and outgoing LPT's.

SYNOPSIS

Understanding interactions between animals and humans is critical in preventing outbreaks of zoonotic disease. This is particularly important for avian influenza. Food animal production has been transformed since the 1918 influenza pandemic. Poultry and swine production have changed from small-scale methods to industrial-scale operations. There is substantial evidence of pathogen movement between and among these industrial facilities, release to the external environment, and exposure to farm workers, which challenges the assumption that modern poultry production is more biosecure and biocontained as compared with backyard or small holder operations in preventing introduction and release of pathogens. An analysis of data from the Thai government investigation in 2004 indicates that the odds of H5N1 outbreaks and infections were significantly higher in large-scale commercial poultry operations as compared with backyard flocks. These data suggest that successful strategies to prevent or mitigate the emergence of pandemic avian influenza must consider risk factors specific to modern industrialized food animal production.

Background

Peste des petits ruminants (PPR) is a contagious viral disease of small ruminants in Africa and Asia. In 1999, probably the largest survey on PPR ever conducted in Africa was initiated in Ethiopia where 13 651 serum samples from 7 out of the 11 regions were collected and analyzed by competitive enzyme-linked immunosorbent assay (cELISA). The objective of this paper is to present the results of this survey and discuss their practical implications for PPR-endemic regions.

Methods

We explored the spatial distribution of PPR in Ethiopia and we investigated risk factors for positive serological status. Intracluster correlation coefficients (ρ), were calculated for 43 wereda (administrative units).

Results

Seroprevalence was very heterogeneous across regions and even more across wereda, with prevalence estimates ranging from 0% to 52.5%. Two groups of weredas could be distinguished on the basis of the estimated ρ: a group with very low ρ (ρ < 0.12) and a group with very high ρ (ρ > 0.37).

Conclusion

The results indicate that PPRV circulation has been very heterogeneous, the values for the ρ may reflect the endemic or epidemic presence of the virus or the various degrees of mixing of animals in the different areas and production systems. Age appears as a risk factor for seropositive status, the linear effect seeming to confirm in the field that PPRV is highly immunogenic. Our estimates of intracluster correlation may prove useful in the design of serosurveys in other countries where PPR is of importance.

Background

Biosecurity is at the forefront of the fight against infectious diseases in animal populations. Few research studies have attempted to identify and quantify the effectiveness of biosecurity against disease introduction or presence in cattle farms and, when done, they have relied on the collection of on-farm data. Data on environmental, animal movement, demographic/husbandry systems and density disease determinants can be collated without requiring additional specific on-farm data collection activities, since they have already been collected for some other purposes. The aim of this study was to classify cattle herds according to their risk of disease presence as a proxy for compromised biosecurity in the cattle population of Wales in 2004 for risk-based surveillance purposes.

Results

Three data mining methods have been applied: logistic regression, classification trees and factor analysis. Using the cattle holding population in Wales, a holding was considered positive if at least bovine TB or one of the ten most frequently diagnosed infectious or transmissible non-notifiable diseases in England and Wales, according to the Veterinary Investigation Surveillance Report (VIDA) had been diagnosed in 2004. High-risk holdings can be described as open large cattle herds located in high-density cattle areas with frequent movements off to many locations within Wales. Additional risks are associated with the holding being a dairy enterprise and with a large farming area.

Conclusion

This work has demonstrated the potential of mining various livestock-relevant databases to obtain generic criteria for individual cattle herd biosecurity risk classification. Despite the data and analytical constraints the described risk profiles are highly specific and present variable sensitivity depending on the model specifications. Risk profiling of farms provides a tool for designing targeted surveillance activities for endemic or emerging diseases, regardless of the prior amount of information available on biosecurity at farm level. As the delivery of practical evidence-based information and advice is one of the priorities of Defra's new Animal Health and Welfare Strategy (AHWS), data-driven models, derived from existing databases, need to be developed that can then be used to inform activities during outbreaks of endemic diseases and to help design surveillance activities.

Background

There are few studies that have investigated uncertainties surrounding the scientific community's knowledge of the geographical distribution of major animal diseases. This is particularly relevant to Rift Valley fever (RVF), a zoonotic disease causing destructive outbreaks in livestock and man, as the geographical range of the disease is widening to involve previously unaffected regions. In the current study we investigate the application of methods developed in the decision sciences: multiple criteria decision making using weighted linear combination and ordered weighted averages, and Dempster-Shafer theory, implemented within the geographical information system IDRISI, to obtain a greater understanding of uncertainty related to the geographical distribution of RVF. The focus is on presenting alternate methods where extensive field data are not available and traditional, model-based approaches to disease mapping are impossible to conduct.

Results

Using a compensatory multiple criteria decision making model based on weighted linear combination, most of sub-Saharan Africa was suitable for endemic circulation of RVF. In contrast, areas where rivers and lakes traversed semi-arid regions, such as those bordering the Sahara, were highly suitable for RVF epidemics and wet, tropical areas of central Africa had low suitability. Using a moderately non-compensatory model based on ordered weighted averages, the areas considered suitable for endemic and epidemic RVF were more restricted. Varying the relative weights of the different factors in the models did not affect suitability estimates to a large degree, but variations in model structure had a large impact on our suitability estimates. Our Dempster-Shafer analysis supported the belief that a range of semi-arid areas were suitable for RVF epidemics and the plausibility that many other areas of the continent were suitable. Areas where high levels of uncertainty were highlighted included the Ethiopian Highlands, southwest Kenya and parts of West Africa.

Conclusion

We have demonstrated the potential of methods developed in the decision sciences to improve our understanding of uncertainties surrounding the geographical distribution of animal diseases, particularly where information is sparse, and encourage wider application of the decision science methodology in the field of animal health.

Background

The number of outbreaks of highly pathogenic avian influenza virus of the H5N1 subtype (HPAIV H5N1) over the past 5 years has been drastically reduced in China but sporadic infections in poultry and humans are still occurring. In this study, we aimed to investigate seasonal patterns in the association between the movement of live poultry originating from southern China and HPAIV H5N1 infection history in humans and poultry in China.

Methodology/Principal Findings

During January to April 2010, longitudinal questionnaire surveys were carried out monthly in four wholesale live bird markets (LBMs) in Hunan and Guangxi provinces of South China. Using social network analysis, we found an increase in the number of observed links and degree centrality between LBMs and poultry sources in February and March compared to the months of January and April. The association of some live poultry traders (LPT’s) with a limited set of counties (within the catchment area of LBMs) in the months of February and March may support HPAIV H5N1 transmission and contribute to perpetuating HPAIV H5N1 virus circulation among certain groups of counties. The connectivity among counties experiencing human infection was significantly higher compared to counties without human infection for the months of January, March and April. Conversely, counties with poultry infections were found to be significantly less connected than counties without poultry infection for the month of February.

Conclusions/Significance

Our results show that temporal variation in live poultry trade in Southern China around the Chinese New Year festivities is associated with higher HPAIV H5N1 infection risk in humans and poultry. This study has shown that capturing the dynamic nature of poultry trade networks in Southern China improves our ability to explain the spatiotemporal dissemination in avian influenza viruses in China.

Wet markets are common in many parts of the world and may promote the emergence, spread and maintenance of livestock pathogens, including zoonoses. A survey was conducted in order to assess the potential of Vietnamese and Cambodian live bird markets (LBMs) to sustain circulation of highly pathogenic avian influenza virus subtype H5N1 (HPAIV H5N1). Thirty Vietnamese and 8 Cambodian LBMs were visited, and structured interviews were conducted with the market managers and 561 Vietnamese and 84 Cambodian traders. Multivariate and cluster analysis were used to construct a typology of traders based on their poultry management practices. As a result of those practices and large poultry surplus (unsold poultry reoffered for sale the following day), some poultry traders were shown to promote conditions favorable for perpetuating HPAIV H5N1 in LBMs. More than 80% of these traders operated in LBMs located in the most densely populated areas, Ha Noi and Phnom Penh. The profiles of sellers operating at a given LBM could be reliably predicted using basic information about the location and type of market. Consequently, LBMs with the largest combination of risk factors for becoming virus reservoirs could be easily identified, potentially allowing control strategies to be appropriately targeted. These findings are of particular relevance to resource-scarce settings with extensively developed LBM systems, commonly found in South-East Asia.