Paul Gale

Q fever through consumption of unpasteurised milk and milk products – a risk profile and exposure assessment

Q fever is a zoonotic disease caused by the bacterium Coxiella burnetii which is endemic in cattle, sheep and goats in much of the world, including the United Kingdom (UK). There is some epidemiological evidence that a small proportion of cases in the developed world may arise from consumption of unpasteurised milk with less evidence for milk products such as cheese. Long maturation at low pH may give some inactivation in hard cheese, and viable C. burnetii are rarely detected in unpasteurised cheese compared to unpasteurised milk. Simulations presented here predict that the probability of exposure per person to one or more C. burnetii through the daily cumulative consumption of raw milk in the UK is 0·4203. For those positive exposures, the average level of exposure predicted is high at 1266 guinea pig intraperitoneal infectious dose 50% units (GP_IP_ID50) per person per day. However, in the absence of human dose–response data, the case is made that the GP_IP_ID50 unit represents a very low risk through the oral route. The available evidence suggests that the risks from C. burnetii through consumption of unpasteurised milk and milk products (including cheese) are not negligible but they are lower in comparison to transmission via inhalation of aerosols from parturient products and livestock contact.

Potential for introduction of bat-borne zoonotic viruses into the EU: a review.

Bat-borne viruses can pose a serious threat to human health, with examples including Nipah virus (NiV) in Bangladesh and Malaysia, and Marburg virus (MARV) in Africa. To date, significant human outbreaks of such viruses have not been reported in the European Union (EU). However, EU countries have strong historical links with many of the countries where NiV and MARV are present and a corresponding high volume of commercial trade and human travel, which poses a potential risk of introduction of these viruses into the EU. In assessing the risks of introduction of these bat-borne zoonotic viruses to the EU, it is important to consider the location and range of bat species known to be susceptible to infection, together with the virus prevalence, seasonality of viral pulses, duration of infection and titre of virus in different bat tissues. In this paper, we review the current scientific knowledge of all these factors, in relation to the introduction of NiV and MARV into the EU.

Hyalomma Ticks on Northward Migrating Birds in Southern Spain: Implications for the Risk of Entry of Crimean-Congo Haemorrhagic Fever Virus to Great Britain

ABSTRACT: Crimean-Congo haemorrhagic fever virus (CCHFV) is a zoonotic virus transmitted by Hyalomma ticks, the immature stages of which may be carried by migratory birds. In this study, a total of 12 Hyalomma ticks were recovered from five of 228 migratory birds trapped in Spring, 2012 in southern Spain along the East Atlantic flyway. All collected ticks tested negative for CCHFV. While most birds had zero Hyalomma ticks, two individuals had four and five ticks each and the statistical distribution of Hyalomma tick counts per bird is over-dispersed compared to the Poisson distribution, demonstrating the need for intensive sampling studies to avoid underestimating the total number of ticks. Rates of tick exchange on migratory birds during their northwards migration will affect the probability that a Hyalomma tick entering Great Britain is positive for CCHFV. Drawing on published data, evidence is presented that the latitude of a European country affects the probability of entry of Hyalomma ticks on wild birds. Further data on Hyalomma infestation rates and tick exchange rates are required along the East Atlantic flyway to further our understanding of the origin of Hyalomma ticks (i.e., Africa or southern Europe) and hence the probability of entry of CCHFV into GB.

Drivers for emerging issues in animal and plant health

Abstract The history of agriculture includes many animal and plant disease events that have had major consequences for the sector, as well as for humans. At the same time, human activities beyond agriculture have often driven the emergence of diseases. The more that humans expand the footprint of the global population, encroach into natural habitats, alter these habitats to extract resources and intensify food production, as well as move animals, people and commodities along with the pathogens they carry, the greater the potential for pathogens and pests to spread and for infection to emerge or re‐emerge. While essential to human well‐being, producing food also plays a major role in disease dynamics. The risk of emergence of pests and pathogens has increased as a consequence of global changes in the way food is produced, moved and consumed. Climate change is likely to increase pressure on the availability of food and provide newly suitable conditions for invasive pests and pathogens. Human population displacements due to economic, political and humanitarian crises represent another set of potential drivers for emerging issues. The overlapping drivers of plant, animal and human disease emergence and environmental changes point towards the concept of ‘One Health’. This paradigm underlines the urgent need to understand the influence of human behaviour and incorporate this understanding into our approach to emerging risks. For this, we face two major challenges. One is cultural; the second is methodological. We have to look at systems not under the narrow view of specific hazards but with a wider approach to system dynamics, and consider a broad spectrum of potential outcomes in terms of risk. In addition, we have to make sense of the vast amounts of data that are available in the modern age. This paper aims to help in preparing for the cultural and methodological shifts needed in our approach to emerging risks.

A Generic Quantitative Risk Assessment Framework for the Entry of Bat-Borne Zoonotic Viruses into the European Union.

Bat-borne viruses have been linked to a number of zoonotic diseases; in 2014 there have been human cases of Nipah virus (NiV) in Bangladesh and Ebola virus in West and Central Africa. Here we describe a model designed to provide initial quantitative predictions of the risk of entry of such viruses to European Union (EU) Member States (MSs) through four routes: human travel, legal trade (e.g. fruit and animal products), live animal movements and illegal importation of bushmeat. The model utilises available datasets to assess the movement via these routes between individual countries of the world and EU MSs. These data are combined with virus specific data to assess the relative risk of entry between EU MSs. As a case study, the model was parameterised for NiV. Scenario analyses showed that the selection of exporting countries with NiV and potentially contaminated trade products were essential to the accuracy of all model outputs. Uncertainty analyses of other model parameters identified that the model expected number of years to an introduction event within the EU was highly susceptible to the prevalence of NiV in bats. The relative rankings of the MSs and routes, however, were more robust. The UK, the Netherlands and Germany were consistently the most likely points of entry and the ranking of most MSs varied by no more than three places (maximum variation five places). Legal trade was consistently the most likely route of entry, only falling below human travel when the estimate of the prevalence of NiV in bats was particularly low. Any model-based calculation is dependent on the data available to feed into the model and there are distinct gaps in our knowledge, particularly in regard to various pathogen/virus as well as host/bat characteristics. However, the strengths of this model lie in the provision of relative comparisons of risk among routes and MSs. The potential for expansion of the model to include other routes and viruses and the possibility of rapid parameterisation demonstrates its potential for use in an outbreak situation.

A generic framework for spatial quantitative risk assessments of infectious diseases: lumpy skin disease case study

The increase in availability of spatial data and the technological advances to handle such data allow for subsequent improvements in our ability to assess risk in a spatial setting. We provide a generic framework for quantitative risk assessments of disease introduction that capitalizes on these new data. It can be adopted across multiple spatial scales, for any pathogen, method of transmission or location. The framework incorporates the risk of initial infection in a previously uninfected location due to registered movement (e.g., trade) and unregistered movement (e.g., daily movements of wild animals). We discuss the steps of the framework and the data required to compute it. We then outline how this framework is applied for a single pathway using lumpy skin disease as a case study, a disease which had an outbreak in the Balkans in 2016. We calculate the risk of initial infection for the rest of Europe in 2016 due to trade. We perform the risk assessment on 3 spatial scales-countries, regions within countries and individual farms. We find that Croatia (assuming no vaccination occurred) has the highest mean probability of infection, with Italy, Hungary and Spain following. Including import detection of infected trade does reduce risk but this reduction is proportionally lower for countries with highest risk. The risk assessment results are consistent across the spatial scales, while in addition, at the finer spatial scales, it highlights specific areas or individual locations of countries on which to focus surveillance.

Using thermodynamic parameters to calibrate a mechanistic dose-response for infection of a host by a virus

Abstract Assessing the risk of infection from emerging viruses or of existing viruses jumping the species barrier into novel hosts is limited by the lack of dose response data. The initial stages of the infection of a host by a virus involve a series of specific contact interactions between molecules in the host and on the virus surface. The strength of the interaction is quantified in the literature by the dissociation constant (Kd) which is determined experimentally and is specific for a given virus molecule/host molecule combination. Here, two stages of the initial infection process of host intestinal cells are modelled, namely escape of the virus in the oral challenge dose from the innate host defenses (e.g. mucin proteins in mucus) and the subsequent binding of any surviving virus to receptor molecules on the surface of the host epithelial cells. The strength of virus binding to host cells and to mucins may be quantified by the association constants, Ka and Kmucin, respectively. Here, a mechanistic dose-response model for the probability of infection of a host by a given virus dose is constructed using Ka and Kmucin which may be derived from published Kd values taking into account the number of specific molecular interactions. It is shown that the effectiveness of the mucus barrier is determined not only by the amount of mucin but also by the magnitude of Kmucin. At very high Kmucin values, slight excesses of mucin over virus are sufficient to remove all the virus according to the model. At lower Kmucin values, high numbers of virus may escape even with large excesses of mucin. The output from the mechanistic model is the probability (p1) of infection by a single virion which is the parameter used in conventional dose-response models to predict the risk of infection of the host from the ingested dose. It is shown here how differences in Ka (due to molecular differences in an emerging virus strain or new host) affect p1, and how these differences in Ka may be quantified in terms of two thermodynamic parameters, namely enthalpy and entropy. This provides the theoretical link between sequencing data and risk of infection. Lack of data on entropy is a limitation at present and may also affect our interpretation of Kd in terms of infectivity. It is concluded that thermodynamic approaches have a major contribution to make in developing dose-response models for emerging viruses.

Application of a quantitative entry assessment model to compare the relative risk of incursion of zoonotic bat-borne viruses into European Union Member States

Abstract This paper presents a quantitative assessment model for the risk of entry of zoonotic bat-borne viruses into the European Union (EU). The model considers four routes of introduction: human travel, legal trade of products, live animal imports and illegal import of bushmeat and was applied to five virus outbreak scenarios. Two scenarios were considered for Zaire ebolavirus (wEBOV, cEBOV) and other scenarios for Hendra virus, Marburg virus (MARV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The use of the same framework and generic data sources for all EU Member States (MS) allows for a relative comparison of the probability of virus introduction and of the importance of the routes of introduction among MSs. According to the model wEBOV posed the highest risk of an introduction event within the EU, followed by MARV and MERS-CoV. However, the main route of introduction differed, with wEBOV and MERS-CoV most likely through human travel and MARV through legal trade of foodstuffs. The relative risks to EU MSs as entry points also varied between outbreak scenarios, highlighting the heterogeneity in global trade and travel to the EU MSs. The model has the capability to allow for a continual updating of the risk estimate using new data as, and when, it becomes available. The model provides an horizon scanning tool for use when available data are limited and, therefore, the absolute risk estimates often have high uncertainty. Sensitivity analysis suggested virus prevalence in bats has a large influence on the results; a 90% reduction in prevalence reduced the risk of introduction considerably and resulted in the relative ranking of MARV falling below that for MERS-CoV, due to this parameter disproportionately affecting the risk of introduction from the trade route over human travel.