Many serious emerging zoonotic infections have recently arisen from bats, including Ebola, Marburg, SARS-coronavirus, Hendra, Nipah, and a number of rabies and rabies-related viruses, consistent with the overall observation that wildlife are an important source of emerging zoonoses for the human population. Mechanisms underlying the recognized association between ecosystem health and human health remain poorly understood and responding appropriately to the ecological, social and economic conditions that facilitate disease emergence and transmission represents a substantial societal challenge. In the context of disease emergence from wildlife, wildlife and habitat should be conserved, which in turn will preserve vital ecosystem structure and function, which has broader implications for human wellbeing and environmental sustainability, while simultaneously minimizing the spillover of pathogens from wild animals into human beings. In this review, we propose a novel framework for the holistic and interdisciplinary investigation of zoonotic disease emergence and its drivers, using the spillover of bat pathogens as a case study. This study has been developed to gain a detailed interdisciplinary understanding, and it combines cutting-edge perspectives from both natural and social sciences, linked to policy impacts on public health, land use and conservation.
bat; zoonosis; emergence; collaborative framework
viruses; Ebola virus; Ebolavirus sp.; Reston Ebola virus; REBOV; Zaire Ebola virus; ZEBOV; African fruit bats; Africa; Epomops franqueti; Epomophorus gambianus; Hypsignathus monstrosus; Nanonycteris veldkampii; Eidolon helvum; viruses; Ghana
Salmonella enterica causes a range of diseases. Salmonellae are intracellular parasites of macrophages, and the control of bacteria within these cells is critical to surviving an infection. The dynamics of the bacteria invading, surviving, proliferating in and killing macrophages are central to disease pathogenesis. Fundamentally important parameters, however, such as the cellular infection rate, have not previously been calculated. We used two independent approaches to calculate the macrophage infection rate: mathematical modelling of Salmonella infection experiments, and analysis of real-time video microscopy of infection events. Cells repeatedly encounter salmonellae, with the bacteria often remain associated with the macrophage for more than ten seconds. Once Salmonella encounters a macrophage, the probability of that bacterium infecting the cell is remarkably low: less than 5%. The macrophage population is heterogeneous in terms of its susceptibility to the first infection event. Once infected, a macrophage can undergo further infection events, but these reinfection events occur at a lower rate than that of the primary infection.
Salmonella; macrophage; dynamic; infection rate; Holling's type II
A case-control investigation was undertaken to determine management and health related factors associated with pleurisy in slaughter pigs in England and Wales.
The British Pig Executive Pig Health Scheme database of abattoir pathology was used to identify 121 case (>10% prevalence of pleurisy on 3 or more assessment dates in the preceding 24 months) and 121 control units (≤5% prevalence of pleurisy on 3 or more assessment dates in the preceding 24 months). Farm data were collected by postal questionnaire. Data from respondents (70 cases and 51 controls) were analysed using simple logistic regression models with Bonferroni corrections. Limited multivariate analyses were also performed to check the robustness of the overall conclusions.
Results and Conclusions
Management factors associated with increased odds of pleurisy included no all-in all-out pig flow (OR 9.3, 95% confidence interval [CI]: 3.3–29), rearing of pigs with an age difference of >1 month in the same airspace (OR 6.5 [2.8–17]) and repeated mixing (OR 2.2 [1.4–3.8]) or moving (OR 2.2 [1.5–3.4]) of pigs during the rearing phase. Those associated with decreased odds of pleurisy included filling wean-to-finish or grower-to-finish systems with piglets from ≤3 sources (OR 0.18 [0.07–0.41]) compared to farrow-to-finish systems, cleaning and disinfecting of grower (ORs 0.28 [0.13–0.61] and 0.29 [0.13–0.61]) and finisher (ORs 0.24 [0.11–0.51] and 0.2 [0.09–0.44]) accommodation between groups, and extended down time of grower and finisher accommodation (OR 0.84 [0.75–0.93] and 0.86 [0.77–0.94] respectively for each additional day of downtime). This study demonstrated the value of national-level abattoir pathology data collection systems for case control analyses and generated guidance for on-farm interventions to help reduce the prevalence of pleurisy in slaughter pigs.
Equine influenza viruses (EIVs) of the H3N8 and H7N7 subtypes are the causative agents of an important disease of horses. While EIV H7N7 apparently is extinct, H3N8 viruses have circulated for more than 50 years. Like human influenza viruses, EIV H3N8 caused a transcontinental pandemic followed by further outbreaks and epidemics, even in populations with high vaccination coverage. Recently, EIV H3N8 jumped the species barrier to infect dogs. Despite its importance as an agent of infectious disease, the mechanisms that underpin the evolutionary and epidemiological dynamics of EIV are poorly understood, particularly at a genomic scale. To determine the evolutionary history and phylodynamics of EIV H3N8, we conducted an extensive analysis of 82 complete viral genomes sampled during a 45-year span. We show that both intra- and intersubtype reassortment have played a major role in the evolution of EIV, and we suggest that intrasubtype reassortment resulted in enhanced virulence while heterosubtypic reassortment contributed to the extinction of EIV H7N7. We also show that EIV evolves at a slower rate than other influenza viruses, even though it seems to be subject to similar immune selection pressures. However, a relatively high rate of amino acid replacement is observed in the polymerase acidic (PA) segment, with some evidence for adaptive evolution. Most notably, an analysis of viral population dynamics provided evidence for a major population bottleneck of EIV H3N8 during the 1980s, which we suggest resulted from changes in herd immunity due to an increase in vaccination coverage.
► Universal real-time PCR primer pair demonstrated to hybridize to and detect each of the known Lyssaviruses (including Rabies virus) with greater sensitivity than a standard pan-Lyssavirus hemi-nested RT-PCR typically used. ► Target sequences of bat derived virus species unavailable for analysis (Aravan-, Khujand-, Irkut-, West Caucasian bat- and Shimoni bat virus) were synthesized to produce oligonucleotides and the synthetic DNA was used as a target for primer hybridization.
Rabies virus (RABV) is enzootic throughout most of the world. It is now widely accepted that RABV had its origins in bats. Ten of the 11 Lyssavirus species recognised, including RABV, have been isolated from bats. There is, however, a lack of understanding regarding both the ecology and host reservoirs of Lyssaviruses. A real-time PCR assay for the detection of all Lyssaviruses using universal primers would be beneficial for Lyssavirus surveillance. It was shown that using SYBR® Green, a universal real-time PCR primer pair previously demonstrated to detect European bat Lyssaviruses 1 and 2, and RABV, was able to detect reverse transcribed RNA for each of the seven virus species available to us. Target sequences of bat derived virus species unavailable for analysis were synthesized to produce oligonucleotides. Lagos Bat-, Duvenhage- and Mokola virus full nucleoprotein gene clones enabled a limit of 5–50 plasmid copies to be detected. Five copies of each of the synthetic DNA oligonucleotides of Aravan-, Khujand-, Irkut-, West Caucasian bat- and Shimoni bat virus were detected. The single universal primer pair was therefore able to detect each of the most divergent known Lyssaviruses with great sensitivity.
Lyssavirus; Rabies; Bat; SYBR Green; Real-time PCR; Synthetic DNA
Henipaviruses, Hendra virus (HeV) and Nipah virus (NiV), have Pteropid bats as their known natural reservoirs. Antibodies against henipaviruses have been found in Eidolon helvum, an old world fruit bat species, and henipavirus-like nucleic acid has been detected in faecal samples from E. helvum in Ghana. The initial outbreak of NiV in Malaysia led to over 265 human encephalitis cases, including 105 deaths, with infected pigs acting as amplifier hosts for NiV during the outbreak. We detected non-neutralizing antibodies against viruses of the genus Henipavirus in approximately 5% of pig sera (N = 97) tested in Ghana, but not in a small sample of other domestic species sampled under a E. helvum roost. Although we did not detect neutralizing antibody, our results suggest prior exposure of the Ghana pig population to henipavirus(es). Because a wide diversity of henipavirus-like nucleic acid sequences have been found in Ghanaian E. helvum, we hypothesise that these pigs might have been infected by henipavirus(es) sufficiently divergent enough from HeVor NiV to produce cross-reactive, but not cross-neutralizing antibodies to HeV or NiV.
The development of modern and affordable sequencing technologies has allowed the
study of viral populations to an unprecedented depth. This is of particular
interest for the study of within-host RNA viral populations, where variation due
to error-prone polymerases can lead to immune escape, antiviral resistance and
adaptation to new host species. Methods to sequence RNA virus genomes include
reverse transcription (RT) and polymerase chain reaction (PCR). RT-PCR is a
molecular biology technique widely used to amplify DNA from an RNA template. The
method itself relies on the in vitro synthesis of copy DNA from
RNA followed by multiple cycles of DNA amplification. However, this method
introduces artefactual errors that can act as confounding factors when the
sequence data are analysed. Although there are a growing number of published
studies exploring the intra- and inter-host evolutionary dynamics of RNA
viruses, the complexity of the methods used to generate sequences makes it
difficult to produce probabilistic statements about the likely sources of
observed sequence variants. This complexity is further compounded as both the
depth of sequencing and the length of the genome segment of interest increase.
Here we develop a Bayesian method to characterise and differentiate between
likely structures for the background viral population. This approach can then be
used to identify nucleotide sites that show evidence of change in the
within-host viral population structure, either over time or relative to a
reference sequence (e.g. an inoculum or another source of infection), or both,
without having to build complex evolutionary models. Identification of these
sites can help to inform the design of more focussed experiments using molecular
biology tools, such as site-directed mutagenesis, to assess the function of
specific amino acids. We illustrate the method by applying to datasets from
experimental transmission of equine influenza, and a pre-clinical vaccine trial
Characterising genetic variation in viral populations can have important
implications in terms of understanding how viruses evolve within infected hosts.
Modern sequencing technologies allow genetic information to be obtained faster,
more affordably, and in much greater quantities than before. This allows new
experimental procedures to be designed to explore aspects of pathogenesis that
were previously unattainable, particularly with regard to mutations that occur
at particular nucleotide sites that may confer a fitness advantage to the
pathogen. This information can be used to study important issues such as the
development of antiviral resistance, virulence, and/or changes in host-range
specificity. Nonetheless, the experimental procedures used to generate the data
can incorporate artefactual errors, and in order to optimise the information
obtained from these studies techniques are required to characterise which sites
exhibit mutations that may alter viral fitness. As both the depth of sequencing
increases and the length of the region sequenced increases (e.g. moves to whole
genomes rather than smaller segments), large numbers of sites will exhibit some
form of variation, and hence development of a probabilistic method to define and
extract these sites-of-interest becomes more important. We tackle this problem
here using a Bayesian framework.
The patterns and dynamics of evolution in acutely infecting viruses within individual hosts are largely unknown. To this end, we investigated the intrahost variation of canine influenza virus (CIV) during the course of experimental infections in naïve and partially immune dogs and in naturally infected dogs. Tracing sequence diversity in the gene encoding domain 1 of the hemagglutinin (HA1) protein over the time course of infection provided information on the patterns and processes of intrahost viral evolution and revealed some of the effects of partial host immunity. Viral populations sampled on any given day were generally characterized by mean pairwise genetic diversities between 0.1 and 0.2% and by mutational spectra that changed considerably on different days. Some observed mutations may have affected antigenicity or host range, including reversions of CIV host-associated mutations. Patterns of sequence diversity differed between naïve and vaccinated dogs, with some presumably antigenic mutations transiently reaching high frequency in the latter. CIV populations are therefore characterized by the rapid generation and clearance of genetic diversity. Potentially advantageous mutations arise readily during the course of single infections and may give rise to antigenic escape or host range variants.
A key question in pandemic influenza is the relative roles of innate immunity and target cell depletion in limiting primary infection and modulating pathology. Here, we model these interactions using detailed data from equine influenza virus infection, combining viral and immune (type I interferon) kinetics with estimates of cell depletion. The resulting dynamics indicate a powerful role for innate immunity in controlling the rapid peak in virus shedding. As a corollary, cells are much less depleted than suggested by a model of human influenza based only on virus-shedding data. We then explore how differences in the influence of viral proteins on interferon kinetics can account for the observed spectrum of virus shedding, immune response, and influenza pathology. In particular, induction of high levels of interferon (“cytokine storms”), coupled with evasion of its effects, could lead to severe pathology, as hypothesized for some fatal cases of influenza.
Ebolaviruses (EBOV) (family Filoviridae) cause viral hemorrhagic fevers in humans and non-human primates when they spill over from their wildlife reservoir hosts with case fatality rates of up to 90%. Fruit bats may act as reservoirs of the Filoviridae. The migratory fruit bat, Eidolon helvum, is common across sub-Saharan Africa and lives in large colonies, often situated in cities. We screened sera from 262 E. helvum using indirect fluorescent tests for antibodies against EBOV subtype Zaire. We detected a seropositive bat from Accra, Ghana, and confirmed this using western blot analysis. The bat was also seropositive for Lagos bat virus, a Lyssavirus, by virus neutralization test. The bat was fitted with a radio transmitter and was last detected in Accra 13 months after release post-sampling, demonstrating long-term survival. Antibodies to filoviruses have not been previously demonstrated in E. helvum. Radio-telemetry data demonstrates long-term survival of an individual bat following exposure to viruses of families that can be highly pathogenic to other mammal species. Because E. helvum typically lives in large urban colonies and is a source of bushmeat in some regions, further studies should determine if this species forms a reservoir for EBOV from which spillover infections into the human population may occur.
Bluetongue (BT) is a viral disease of ruminants transmitted by Culicoides biting midges and has the ability to spread rapidly over large distances. In the summer of 2006, BTV serotype 8 (BTV-8) emerged for the first time in northern Europe, resulting in over 2000 infected farms by the end of the year. The virus subsequently overwintered and has since spread across much of Europe, causing tens of thousands of livestock deaths. In August 2007, BTV-8 reached Great Britain (GB), threatening the large and valuable livestock industry. A voluntary vaccination scheme was launched in GB in May 2008 and, in contrast with elsewhere in Europe, there were no reported cases in GB during 2008.
Here, we use carefully parameterised mathematical models to investigate the spread of BTV in GB and its control by vaccination. In the absence of vaccination, the model predicted severe outbreaks of BTV, particularly for warmer temperatures. Vaccination was predicted to reduce the severity of epidemics, with the greatest reduction achieved for high levels (95%) of vaccine uptake. However, even at this level of uptake the model predicted some spread of BTV. The sensitivity of the predictions to vaccination parameters (time to full protection in cattle, vaccine efficacy), the shape of the transmission kernel and temperature dependence in the transmission of BTV between farms was assessed.
A combination of lower temperatures and high levels of vaccine uptake (>80%) in the previously-affected areas are likely to be the major contributing factors in the control achieved in England in 2008. However, low levels of vaccination against BTV-8 or the introduction of other serotypes could result in further, potentially severe outbreaks in future.
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.
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.
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.
Henipaviruses are emerging RNA viruses of fruit bat origin that can cause fatal encephalitis in man. Ghanaian fruit bats (megachiroptera) were tested for antibodies to henipaviruses. Using a Luminex multiplexed microsphere assay, antibodies were detected in sera of Eidolon helvum to both Nipah (39%, 95% confidence interval: 27–51%) and Hendra (22%, 95% CI: 11–33%) viruses. Virus neutralization tests further confirmed seropositivity for 30% (7/23) of Luminex positive serum samples. Our results indicate that henipavirus is present within West Africa.
To investigate the presence of Lagos bat virus (LBV)–specific antibodies in megachiroptera from West Africa, we conducted fluorescent antibody virus neutralization tests. Neutralizing antibodies were detected in Eidolon helvum (37%), Epomophorus gambianus (3%), and Epomops buettikoferi (33%, 2/6) from Ghana. These findings confirm the presence of LBV in West Africa.
Lagos Bat Virus; rabies; megachiroptera; bat; Lyssavirus; dispatch
Since 1998 bluetongue virus (BTV), which causes bluetongue, a non-contagious, insect-borne infectious disease of ruminants, has expanded northwards in Europe in an unprecedented series of incursions, suggesting that there is a risk to the large and valuable British livestock industry. The basic reproduction number, R0, provides a powerful tool with which to assess the level of risk posed by a disease. In this paper, we compute R0 for BTV in a population comprising two host species, cattle and sheep. Estimates for each parameter which influences R0 were obtained from the published literature, using those applicable to the UK situation wherever possible. Moreover, explicit temperature dependence was included for those parameters for which it had been quantified. Uncertainty and sensitivity analyses based on Latin hypercube sampling and partial rank correlation coefficients identified temperature, the probability of transmission from host to vector and the vector to host ratio as being most important in determining the magnitude of R0. The importance of temperature reflects the fact that it influences many processes involved in the transmission of BTV and, in particular, the biting rate, the extrinsic incubation period and the vector mortality rate.
bluetongue; epidemiology; basic reproduction number; model; sensitivity analysis; uncertainty analysis
The control of outbreaks of calicivirus infection in high-density, high-throughput populations is a challenge to both human and veterinary medicine. In such populations, the prevalence of infection is, in part, dependent on the levels of biosecurity and how this affects virus transmission. Here we show how longitudinal analysis of feline calicivirus (FCV) infection in an animal rescue shelter can be used as a model to examine the dynamics of calicivirus transmission and evolution in such environments. FCV was isolated from 33 of 116 cats sampled over a 15-month period (overall prevalence, 28%). Sequence analysis of the immunodominant variable regions of the viral capsid gene identified 16 strains circulating in the shelter, with no single strain appearing to predominate. The majority of these strains were introduced into the shelter from the community and did not appear to be transmitted within the population. However, for three of these strains, putative transmission events within the shelter were identified. The rates of evolution within hypervariable regions of the FCV capsid gene in individual cats ranged from 0.05 to 1.4% per week, with the highest rates generally being found in animals that either acquired the virus while in the shelter or were undergoing acute infection. These data suggest that despite the high prevalence and presence of multiple strains of FCV within the shelter, the spread of such pathogens may be restricted by various control measures, including good hygiene and biosecurity.
Infectious disease ecology has recently raised its public profile beyond the scientific community due to the major threats that wildlife infections pose to biological conservation, animal welfare, human health and food security. As we start unravelling the full extent of emerging infectious diseases, there is an urgent need to facilitate multidisciplinary research in this area. Even though research in ecology has always had a strong theoretical component, cultural and technical hurdles often hamper direct collaboration between theoreticians and empiricists. Building upon our collective experience of multidisciplinary research and teaching in this area, we propose practical guidelines to help with effective integration among mathematical modelling, fieldwork and laboratory work. Modelling tools can be used at all steps of a field-based research programme, from the formulation of working hypotheses to field study design and data analysis. We illustrate our model-guided fieldwork framework with two case studies we have been conducting on wildlife infectious diseases: plague transmission in prairie dogs and lyssavirus dynamics in American and African bats. These demonstrate that mechanistic models, if properly integrated in research programmes, can provide a framework for holistic approaches to complex biological systems.
Field ecology; infectious diseases; mathematical models; statistical models; study design; wildlife epidemiology
Control measures for canine rabies include vaccination and reducing population density through culling or sterilization.Despite the evidence that culling fails to control canine rabies, efforts to reduce canine population density continue in many parts of the world.The rationale for reducing population density is that rabies transmission is density-dependent, with disease incidence increasing directly with host density. This may be based, in part, on an incomplete interpretation of historical field data for wildlife, with important implications for disease control in dog populations. Here, we examine historical and more recent field data, in the context of host ecology and epidemic theory, to understand better the role of density in rabies transmission and the reasons why culling fails to control rabies.We conclude that the relationship between host density, disease incidence and other factors is complex and may differ between species. This highlights the difficulties of interpreting field data and the constraints of extrapolations between species, particularly in terms of control policies.We also propose that the complex interactions between dogs and people may render culling of free-roaming dogs ineffective irrespective of the relationship between host density and disease incidence.We conclude that vaccination is the most effective means to control rabies in all species.
culling; density; dog; sterilisation; vaccination
Bats carry a variety of paramyxoviruses that impact human and domestic animal health when spillover occurs. Recent studies have shown a great diversity of paramyxoviruses in an urban-roosting population of straw-colored fruit bats in Ghana. Here, we investigate this further through virus isolation and describe two novel rubulaviruses: Achimota virus 1 (AchPV1) and Achimota virus 2 (AchPV2). The viruses form a phylogenetic cluster with each other and other bat-derived rubulaviruses, such as Tuhoko viruses, Menangle virus, and Tioman virus. We developed AchPV1- and AchPV2-specific serological assays and found evidence of infection with both viruses in Eidolon helvum across sub-Saharan Africa and on islands in the Gulf of Guinea. Longitudinal sampling of E. helvum indicates virus persistence within fruit bat populations and suggests spread of AchPVs via horizontal transmission. We also detected possible serological evidence of human infection with AchPV2 in Ghana and Tanzania. It is likely that clinically significant zoonotic spillover of chiropteran paramyxoviruses could be missed throughout much of Africa where health surveillance and diagnostics are poor and comorbidities, such as infection with HIV or Plasmodium sp., are common.
The ability of influenza A viruses (IAVs) to cross species barriers and evade host immunity is a major public health concern. Studies on the phylodynamics of IAVs across different scales – from the individual to the population – are essential for devising effective measures to predict, prevent or contain influenza emergence. Understanding how IAVs spread and evolve during outbreaks is critical for the management of epidemics. Reconstructing the transmission network during a single outbreak by sampling viral genetic data in time and space can generate insights about these processes. Here, we obtained intra-host viral sequence data from horses infected with equine influenza virus (EIV) to reconstruct the spread of EIV during a large outbreak. To this end, we analyzed within-host viral populations from sequences covering 90% of the infected yards. By combining gene sequence analyses with epidemiological data, we inferred a plausible transmission network, in turn enabling the comparison of transmission patterns during the course of the outbreak and revealing important epidemiological features that were not apparent using either approach alone. The EIV populations displayed high levels of genetic diversity, and in many cases we observed distinct viral populations containing a dominant variant and a number of related minor variants that were transmitted between infectious horses. In addition, we found evidence of frequent mixed infections and loose transmission bottlenecks in these naturally occurring populations. These frequent mixed infections likely influence the size of epidemics.
Influenza A viruses (IAVs) are major pathogens of humans and animals. Understanding how IAVs spread and evolve at different scales (individual, regional, global) in natural conditions is critical for preventing or managing influenza epidemics. A vast body of knowledge has been generated on the evolution of IAVs at the global scale. Additionally, recent experimental transmission studies have examined the diversity and transmission of influenza viruses within and between hosts. However, most studies on the spread of IAVs during epidemics have been based on consensus viral sequences, an approach that does not have enough discriminatory power to reveal exact transmission pathways. Here, we analyzed multiple within-host viral populations from different horses infected with equine influenza virus (EIV) during the course of an outbreak in a population within a confined area. This provided an opportunity to examine the genetic diversity of the viruses within single animals, the transmission of the viruses between each closely confined population within a yard, and the transmission between horses in different yards. We show that individual horses can be infected by viruses from more than one other horse, which has important implications for facilitating segment reassortment and the evolution of EIV. Additionally, by combining viral sequencing data and epidemiological data we show that the high levels of mixed infections can reveal the underlying epidemiological dynamics of the outbreak, and that epidemic size could be underestimated if only epidemiological data is considered. As sequencing technologies become cheaper and faster, these analyses could be undertaken almost in real-time and help control future outbreaks.
Bovine tuberculosis is endemic in cattle herds in Great Britain, with a substantial economic impact. A reservoir of Mycobacterium bovis within the Eurasian badger (Meles meles) population is thought to have hindered disease control. Cattle herd incidents, termed breakdowns, that are either ‘prolonged’ (lasting ≥240 days) or ‘recurrent’ (with another breakdown within a specified time period) may be important foci for onward spread of infection. They drain veterinary resources and can be demoralising for farmers. Randomised Badger Culling Trial (RBCT) data were re-analysed to examine the effects of two culling strategies on breakdown prolongation and recurrence, during and after culling, using a Bayesian hierarchical model. Separate effect estimates were obtained for the ‘core’ trial areas (where culling occurred) and the ‘buffer’ zones (up to 2 km outside of the core areas). For breakdowns that started during the culling period, ‘reactive’ (localised) culling was associated with marginally increased odds of prolongation, with an odds ratio (OR) of 1.7 (95% credible interval [CI] 1.1–2.4) within the core areas. This effect was not present after the culling ceased. There was no notable effect of ‘proactive’ culling on prolongation. In contrast, reactive culling had no effect on breakdown recurrence, though there was evidence of a reduced risk of recurrence in proactive core areas during the culling period (ORs and 95% CIs: 0.82 (0.64–1.0) and 0.69 (0.54–0.86) for 24- and 36-month recurrence respectively). Again these effects were not present after the culling ceased. There seemed to be no effect of culling on breakdown prolongation or recurrence in the buffer zones. These results suggest that the RBCT badger culling strategies are unlikely to reduce either the prolongation or recurrence of breakdowns in the long term, and that reactive strategies (such as employed during the RBCT) are, if anything, likely to impact detrimentally on breakdown persistence.
The number of cattle herds placed under movement restrictions in Great Britain (GB) due to the suspected presence of bovine tuberculosis (bTB) has progressively increased over the past 25 years despite an intensive and costly test-and-slaughter control program. Around 38% of herds that clear movement restrictions experience a recurrent incident (breakdown) within 24 months, suggesting that infection may be persisting within herds. Reactivity to tuberculin, the basis of diagnostic testing, is dependent on the time from infection. Thus, testing efficiency varies between outbreaks, depending on weight of transmission and cannot be directly estimated. In this paper, we use Approximate Bayesian Computation (ABC) to parameterize two within-herd transmission models within a rigorous inferential framework. Previous within-herd models of bTB have relied on ad-hoc methods of parameterization and used a single model structure (SORI) where animals are assumed to become detectable by testing before they become infectious. We study such a conventional within-herd model of bTB and an alternative model, motivated by recent animal challenge studies, where there is no period of epidemiological latency before animals become infectious (SOR). Under both models we estimate that cattle-to-cattle transmission rates are non-linearly density dependent. The basic reproductive ratio for our conventional within-herd model, estimated for scenarios with no statutory controls, increases from 1.5 (0.26–4.9; 95% CI) in a herd of 30 cattle up to 4.9 (0.99–14.0) in a herd of 400. Under this model we estimate that 50% (33–67) of recurrent breakdowns in Britain can be attributed to infection missed by tuberculin testing. However this figure falls to 24% (11–42) of recurrent breakdowns under our alternative model. Under both models the estimated extrinsic force of infection increases with the burden of missed infection. Hence, improved herd-level testing is unlikely to reduce recurrence unless this extrinsic infectious pressure is simultaneously addressed.
Epidemic models are commonly used to assess the impact of alternative management strategies. The efficacy of controls is typically assumed from “expert opinion” rather than estimated from data. Managed endemic diseases such as bovine tuberculosis offer the potential to estimate the efficiency of control directly from epidemiological data. Our methodology constitutes a shift in the level of statistical rigor applied to “policy” models and offers insights into the epidemiology of Bovine tuberculosis in Great Britain. bTB continues to persist and spread relentlessly in Britain, despite extensive testing and control programs. Cattle farmers question the efficacy of cattle controls, blaming the badger wildlife reservoir. Contrary to much public perception, we demonstrate the importance of cattle-to-cattle transmission, especially in larger herds. We estimate that in the worst case scenario up to 21% of herds may be harboring infection after they clear restrictions. However, we also estimate that there is a high rate of re-introduction of infection into herds, particularly in high incidence areas. Eliminating the hidden burden of infection alone is unlikely to be sufficient to prevent recurrent breakdowns. Rather, the high rate of external infection, both through cattle movements and environmental sources, must be addressed if recurrence is to be reduced.
Outbreaks of avian influenza in poultry can be devastating, yet many of the basic epidemiological parameters have not been accurately characterised. In 1999–2000 in Northern Italy, outbreaks of H7N1 low pathogenicity avian influenza virus (LPAI) were followed by the emergence of H7N1 highly pathogenic avian influenza virus (HPAI). This study investigates the transmission dynamics in turkeys of representative HPAI and LPAI H7N1 virus strains from this outbreak in an experimental setting, allowing direct comparison of the two strains. The fitted transmission rates for the two strains are similar: 2.04 (1.5–2.7) per day for HPAI, 2.01 (1.6–2.5) per day for LPAI. However, the mean infectious period is far shorter for HPAI (1.47 (1.3–1.7) days) than for LPAI (7.65 (7.0–8.3) days), due to the rapid death of infected turkeys. Hence the basic reproductive ratio, is significantly lower for HPAI (3.01 (2.2–4.0)) than for LPAI (15.3 (11.8–19.7)). The comparison of transmission rates and are critically important in relation to understanding how HPAI might emerge from LPAI. Two competing hypotheses for how transmission rates vary with population size are tested by fitting competing models to experiments with differing numbers of turkeys. A model with frequency-dependent transmission gives a significantly better fit to experimental data than density-dependent transmission. This has important implications for extrapolating experimental results from relatively small numbers of birds to the commercial poultry flock size, and for how control, including vaccination, might scale with flock size.
Bovine tuberculosis (bTB) is one of the most serious economic animal health problems affecting the cattle industry in Great Britain (GB), with incidence in cattle herds increasing since the mid-1980s. The single intradermal comparative cervical tuberculin (SICCT) test is the primary screening test in the bTB surveillance and control programme in GB and Ireland. The sensitivity (ability to detect infected cattle) of this test is central to the efficacy of the current testing regime, but most previous studies that have estimated test sensitivity (relative to the number of slaughtered cattle with visible lesions [VL] and/or positive culture results) lacked post-mortem data for SICCT test-negative cattle. The slaughter of entire herds (“whole herd slaughters” or “depopulations”) that are infected by bTB are occasionally conducted in GB as a last-resort control measure to resolve intractable bTB herd breakdowns. These provide additional post-mortem data for SICCT test-negative cattle, allowing a rare opportunity to calculate the animal-level sensitivity of the test relative to the total number of SICCT test-positive and negative VL animals identified post-mortem (rSe). In this study, data were analysed from 16 whole herd slaughters (748 SICCT test-positive and 1031 SICCT test-negative cattle) conducted in GB between 1988 and 2010, using a Bayesian hierarchical model. The overall rSe estimate of the SICCT test at the severe interpretation was 85% (95% credible interval [CI]: 78–91%), and at standard interpretation was 81% (95% CI: 70–89%). These estimates are more robust than those previously reported in GB due to inclusion of post-mortem data from SICCT test-negative cattle.