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African swine fever (ASF) is a notifiable, virulent swine disease, and is a major threat to animal health and trade for many European Union (EU) countries. Early detection of the introduction of ASF virus is of paramount importance to be able to limit the potential extent of outbreaks. However, the timely and accurate reporting of ASF primary cases strongly depends on how familiar pig farmers are with the clinical signs, and their motivation to report the disease. Here, an online questionnaire survey was conducted between December 2014 and April 2015 to investigate English pig farmers' knowledge and behaviour towards ASF in terms of clinical suspicion and reporting. Multivariable logistic regression analysis was used to identify factors influencing the two variables of interest: 1) farmers who "would immediately suspect ASF" if they observed clinical signs of fever, lethargy, reduced eating and high mortality on their farm and 2) farmers who "would immediately report ASF" if they suspected ASF on their farm. The questionnaire was completed by 109 pig farmers. Results indicate that pig farmers having poor knowledge about ASF clinical signs and limited concern about ASF compared with other pig diseases are less likely to consider the possibility of an outbreak of ASF on their farm. In addition, pig farmers lacking awareness of outbreaks in other countries, having a perception of the negative impact on them resulting from false positive reporting and the perceived complexity of reporting procedures are less likely to report an ASF suspicion. These findings indicate important areas for educational campaigns targeted at English pig farmers to focus on in an attempt to increase the likelihood of a rapid response in the event of an ASF outbreak. ; ISSN:1932-6203

African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS that would most likely contribute to ASF spread ("super-spreaders") or MS that would most likely receive cases from other MS ("super-receivers"). A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10–60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature. Model outputs showed that virus circulation was generally limited to 1–2 infected premises per outbreak (95% IQR: 1–4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified as "super-spreaders"; Germany and Poland as "super-receivers". In the sensitivity analysis, the total number of premises per country involved in intra-Community trade was found to be a key determinant for the between-MS spread dynamic and needs to be further investigated. It was concluded that spread during the HRP is likely to be limited, especially if the HRP is short. This emphasises the importance of having good disease awareness in all MS for early disease detection.

In this paper, we identify behaviours in live bird commodity chains in Chattogram, Bangladesh, which may influence the risk of pathogen emergence and transmission: the nature of poultry trade, value appropriation and selling sick or infected birds. Examining the reasons why actors engage in these behaviours, we emphasise the politics of constraints within a context of real-world decisions, governed by existential and pragmatic agency. Focusing on contact zones and entanglement, analysing patron-client relationships and precarious circumstances, we argue that agency and structure specific to the Bangladeshi context produce a risk environment. Structural constraints may reinforce risky occupational practises and limit individual agency. Structural constraints need to be addressed in order to tackle animal and zoonotic disease risk along live animal commodity chains.

In this paper, we identify behaviours in live bird commodity chains in Chattogram, Bangladesh, which may influence the risk of pathogen emergence and transmission: the nature of poultry trade, value appropriation and selling sick or infected birds. Examining the reasons why actors engage in these behaviours, we emphasise the politics of constraints within a context of real-world decisions, governed by existential and pragmatic agency. Focusing on contact zones and entanglement, analysing patron-client relationships and precarious circumstances, we argue that agency and structure specific to the Bangladeshi context produce a risk environment. Structural constraints may reinforce risky occupational practises and limit individual agency. Structural constraints need to be addressed in order to tackle animal and zoonotic disease risk along live animal commodity chains.

Decades of warnings by conservationists, epidemiologists, and virologists that the trade and consumption of wildlife could result in serious zoonotic pandemics have gone largely unheeded. Now the world is ravaged by COVID-19 that has caused tremendous loss of life and economic and societal disruption, with dire predictions of more destructive and frequent pandemics. There are now calls to tightly regulate and even enact complete wildlife trade bans, while others call for more nuanced approaches since many rural people rely on wildlife for sustenance. Given forces of political and societal expediency and limitations to enforcing bans, a response closer to the latter is more likely to unfold. But this will require monitoring and assessing trade situations for zoonotic risks. We present a framework for government authorities in the public health and wildlife sectors to assess wildlife trade situations for risks of serious zoonoses in order to inform policies to curtail or control the trade, much of which is illegal in most countries. The framework is based on available knowledge of different wildlife taxa traded in the Asia-Pacific Region, taxa known to carry highly virulent and transmissible viruses, and broad categories of market types and trade chains.

© 2020 Salvador et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The Philippines confirmed its first epidemic of Highly Pathogenic Avian Influenza (HPAI) on August 11, 2017. It ended in November of 2017. Despite the successful management of the epidemic, reemergence is a continuous threat. The aim of this study was to conduct a mathematical model to assess the spatial transmission of HPAI among poultry farms in Central Luzon. Different control strategies and the current government protocol of 1 km radius preemptive culling (PEC) from infected farms were evaluated. The alternative strategies include 0.5km PEC, 1.5km PEC, 2 km PEC, 2.5 km PEC, and 3 km PEC, no pre-emptive culling (NPEC). The NPEC scenario was further modeled with a time of government notification set at 24hours, 48 hours, and 72 hours after the detection. Disease spread scenarios under each strategy were generated using an SEIR (susceptible-exposed-infectious-removed) stochastic model. A spatial transmission kernel was calculated and used to represent all potential routes of infection between farms. We assumed that the latent period occurs between 1–2 days, disease detection at 5–7 days post-infection, notification of authorities at 5–7 days post-detection and start of culling at 1–3 days post notification. The epidemic scenarios were compared based on the number of infected farms, the total number of culled farms, and the duration of the epidemic. Our results revealed that the current protocol is the most appropriate option compared with the other alternative interventions considered among farms with reproductive ratio (Ri) > 1. Shortening the culling radius to 0.5 km increased the duration of the epidemic. Further increase in the PEC zone decreased the duration of the epidemic but may not justify the increased number of farms to be culled. Nonetheless, the no-pre-emptive culling (NPEC) strategy can be an effective alternative to the current protocol if farm managers inform the government immediately within 24 hours of observation of the presence of HPAI in their farms. Moreover, if notification is made on days 1–3 after the detection, the scale and length of the outbreak have been significantly reduced. In conclusion, this study provided a comparison of various control measures for confronting the spread of HPAI infection using the simulation model. Policy makers can use this information to enhance the effectiveness of the current control strategy.

Decades of warnings by conservationists, epidemiologists, and virologists that the trade and consumption of wildlife could result in serious zoonotic pandemics have gone largely unheeded. Now the world is ravaged by COVID-19 that has caused tremendous loss of life and economic and societal disruption, with dire predictions of more destructive and frequent pandemics. There are now calls to tightly regulate and even enact complete wildlife trade bans, while others call for more nuanced approaches since many rural people rely on wildlife for sustenance. Given forces of political and societal expediency and limitations to enforcing bans, a response closer to the latter is more likely to unfold. But this will require monitoring and assessing trade situations for zoonotic risks. We present a framework for government authorities in the public health and wildlife sectors to assess wildlife trade situations for risks of serious zoonoses in order to inform policies to curtail or control the trade, much of which is illegal in most countries. The framework is based on available knowledge of different wildlife taxa traded in the Asia-Pacific Region, taxa known to carry highly virulent and transmissible viruses, and broad categories of market types and trade chains.

Decades of warnings that the trade and consumption of wildlife could result in serious zoonotic pandemics have gone largely unheeded. Now the world is ravaged by COVID-19, with tremendous loss of life, economic and societal disruption, and dire predictions of more destructive and frequent pandemics. There are now calls to tightly regulate and even enact complete wildlife trade bans, while others call for more nuanced approaches since many rural communities rely on wildlife for sustenance. Given pressures from political and societal drivers and resource limitations to enforcing bans, increased regulation is a more likely outcome rather than broad bans. But imposition of tight regulations will require monitoring and assessing trade situations for zoonotic risks. We present a tool for relevant stakeholders, including government authorities in the public health and wildlife sectors, to assess wildlife trade situations for risks of potentially serious zoonoses in order to inform policies to tightly regulate and control the trade, much of which is illegal in most countries. The tool is based on available knowledge of different wildlife taxa traded in the Asia-Pacific Region and known to carry highly virulent and transmissible viruses combined with relative risks associated with different broad categories of market types and trade chains.

Around 60% of all human pathogens are zoonoses and domestic animals and wildlife are of equal importance as reservoir hosts. Moreover, most emerging infectious diseases are zoonoses and most emerge from wildlife. There have been several recent initiatives to categorize zoonoses and their reservoirs but their socio-economic impact remains poorly defined and previous reviews lacked both poverty and gender perspectives. We present the initial findings of a multi-disciplinary, systematic review commissioned by the Department for International Development (UK) to synthesize best available scientific knowledge about zoonotic disease transmission through direct or indirect domestic livestock/wildlife interaction, with emphasis on risk factors, drivers and trajectories of transmission, and promising interventions for controlling important zoonoses based on managing domestic livestock/wildlife interaction. The review covers: zoonoses transmission and relative importance of the wildlife/livestock route; wildlife pathogens capable of recombining with analogous organisms in domestic livestock; risk factors and drivers for zoonoses transmission at the human/livestock/wildlife interface; historical changes in transmission and trends; livestock production systems as primary drivers of zoonotic disease load in the environment and role of wildlife as amplifiers, spill-over/indicator hosts and reservoirs; socio-economic, institutional and political factors influencing risk of transmission between wildlife and domestic livestock and from wildlife/livestock to people; risk management and control interventions and their success or failure with emphasis on interventions based on managing interaction between hosts (wildlife/livestock/humans). This review summarizes best evidence on livestock/wildlife interactions and zoonoses transmission.

The island of Mayotte is a department of France, an outermost region of the European Union located in the Indian Ocean between Madagascar and the coast of Eastern Africa. Due to its close connection to the African mainland and neighbouring islands, the island is under constant threat of introduction of infectious diseases of both human and animal origin. Here, using social network analysis and mathematical modelling, we assessed potential implications of livestock movements between communes in Mayotte for risk-based surveillance. Our analyses showed that communes in the central region of Mayotte acted as a hub in the livestock movement network. The majority of livestock movements occurred between communes in the central region and from communes in the central region to those in the outer region. Also, communes in the central region were more likely to be infected earlier than those in the outer region when the spread of an exotic infectious disease was simulated on the livestock movement network. The findings of this study, therefore, suggest that communes in the central region would play a major role in the spread of infectious diseases via livestock movements, which needs to be considered in the design of risk-based surveillance systems in Mayotte.

The recent incursion and spread of African swine fever virus (ASFV) in the Russian Federation and Caucasus region, close to European Union (EU) borders, have increased the concerns regarding the probability of ASFV introduction into the EU. There are many potential routes of ASFV entry into EU, but here we specifically aimed to assess the probability of ASFV introduction by legal trade of pigs, which historically has been one of the most important ways of exotic diseases introduction into the EU. A stochastic model was used to estimate the monthly probability of ASFV introduction for each country of the EU. Results of this model suggest an annual probability for ASFV introduction in the whole EU by this way of 5.22*10−3, which approximately corresponds with one outbreak in 192 years. The risk of ASFV introduction via live pigs was highest in Poland (69%), particularly during the months of November and December. As expected, Russian Federation is the country that most contributes to this risk, representing 68% of the overall annual risk. Methods and results presented here may be useful for informing risk-based surveillance and control programmes and, ultimately, for prevention and control of potential ASFV incursions into the EU.