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

Abstract

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.

Toward a quantification of risks at the nexus of conservation and health: The case of bushmeat markets in Lao PDR

“…QRA models have been used in diverse disciplines (Vose, 2008), but are particularly popular for food safety (Notermans and Teunis, 1996) and foreign animal disease risk assessments (Miller et al, 2017;Peeler et al, 2015). Although their application to the risk of disease transmission from bushmeat consumption and wildlife trade has been recommended (OIE -World Organisation for Animal Health and International Union for Conservation of Nature and Natural Resources, 2014), only a few instances exist to date (Franssen et al, 2017;Simons et al, 2016;Wooldridge et al, 2006). Given the flexibility of QRA methods such as Monte Carlo simulations, we further recommend their use as a tool for multi-disciplinary data integration for the evaluation of the multiple trade-offs of the bushmeat system.…”

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

“…The entry assessment model parameterised for NiV (Simons et al, 2016), was re-parameterised for five outbreak scenarios (MARV, EBOV, HeV and MERS-CoV), to compare and assess the relative risk of introduction to the 28 EU MSs for these 5 viruses of concern. For EBOV two different outbreak scenarios were considered: 1) Disease geographically distributed in Western Africa, where the human cases are on a similar scale to that observed in the 2014 West Africa outbreak (wEBOV) (i.e.…”

“…The model has been discussed in detail by Simons et al (2016). Briefly, the main outputs of the model were a relative estimate of the annual probability of at least one introduction event into each EU MS, j, P V (j), and an overall estimate of the probability of at least one introduction event for the EU as a whole.…”

“…This estimate took into account factors such as the probability an individual unit is infected (or contaminated) in the exporting country, the survival of the virus over the duration of the journey, whether or not the animal/human displays clinical signs and the annual volume of products being imported. The model equations for the various routes are described by Simons et al (2016). The model was coded in the R software package and is deterministic; as such no stochastic variability of specific parameters was considered in the baseline model.…”

“…To address this need, a generic quantitative risk assessment framework for the entry of bat-borne zoonotic viruses to the EU was developed (Simons et al, 2016), considering the pathways: human travel, live animal movement, legal trade of food products and illegal trade of bushmeat. Using current knowledge of virus characteristics such as environmental survival and host incubation periods, the framework was parameterised for NiV, to provide an assessment of the relative risks of transmission through the known pathways of introduction into the EU.…”