Modeling Transmission of Avian Influenza Viruses at the Human-Animal-Environment Interface in Cuba

TThe increasing geographical spread of highly pathogenic avian influenza viruses (HPAIVs) is of global concern due to the underlying zoonotic and pandemic potential of the virus and its economic impact. An integrated One Health model was developed to estimate the likelihood of Avian Influenza (AI) introduction and transmission in Cuba, which will help inform and strengthen risk-based surveillance activities. The spatial resolution used for the model was the smallest administrative district (“Consejo Popular”). The model was parameterised for transmission from wild birds to poultry and pigs (commercial and backyard) and then to humans. The model includes parameters such as risk factors for the introduction and transmission of AI into Cuba, animal and human population densities; contact intensity and a transmission parameter (β). Areas with a higher risk of AI transmission were identified for each species and type of production system. Some variability was observed in the distribution of areas estimated to have a higher probability of AI introduction and transmission. In particular, the south-western and eastern regions of Cuba were highlighted as areas with the highest risk of transmission. These results are potentially useful for refining existing criteria for the selection of farms for active surveillance, which could improve the ability to detect positive cases. The model results could contribute to the design of an integrated One Health risk-based surveillance system for AI in Cuba. In addition, the model identified geographical regions of particular importance where resources could be targeted to strengthen biosecurity and early warning surveillance

Modeling Transmission of Avian Influenza Viruses at the Human-Animal-Environment Interface in Cuba

TThe increasing geographical spread of highly pathogenic avian influenza viruses (HPAIVs) is of global concern due to the underlying zoonotic and pandemic potential of the virus and its economic impact. An integrated One Health model was developed to estimate the likelihood of Avian Influenza (AI) introduction and transmission in Cuba, which will help inform and strengthen risk-based surveillance activities. The spatial resolution used for the model was the smallest administrative district (“Consejo Popular”). The model was parameterised for transmission from wild birds to poultry and pigs (commercial and backyard) and then to humans. The model includes parameters such as risk factors for the introduction and transmission of AI into Cuba, animal and human population densities; contact intensity and a transmission parameter (β). Areas with a higher risk of AI transmission were identified for each species and type of production system. Some variability was observed in the distribution of areas estimated to have a higher probability of AI introduction and transmission. In particular, the south-western and eastern regions of Cuba were highlighted as areas with the highest risk of transmission. These results are potentially useful for refining existing criteria for the selection of farms for active surveillance, which could improve the ability to detect positive cases. The model results could contribute to the design of an integrated One Health risk-based surveillance system for AI in Cuba. In addition, the model identified geographical regions of particular importance where resources could be targeted to strengthen biosecurity and early warning surveillance

The Implementation Gap in Emerging Disease Risk Management in the Wildlife Trade.

The wildlife trade has been characterized as one of the biggest risk factors in the emergence of new infectious diseases. In the shadow of COVID-19, there is growing political and scientific urgency to manage this risk. Existing studies and experiences make it clear that something must be done but are less clear on how to get it done. It is a quite different task to accumulate evidence on the presence of pathogens, their locations in the supply chain, and their spillover to new hosts than to identify effective ways to prevent and mitigate emerging disease under real-world conditions. This study sought peer-reviewed evidence on the effectiveness, acceptability, feasibility, and sustainability of risk reduction interventions for zoonotic and nonzoonotic disease emergence in the wildlife trade. An environmental scan triangulated information from a scoping review following a Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for scoping review protocol, two narrative literature reviews, and key informant interviews of 26 international wildlife health experts. Existing literature has been inattentive to program implementation or evaluation studies. There was insufficient evidence to identify effective and sustainable risk management actions. Studies on the effects of social, epidemiologic, and ecologic context on intervention success was lacking, as was research using a complex systems perspective. The lack of systematic program evaluations or implementation studies leaves decision makers with insufficient evidence to select interventions likely to be acceptable, effective, and sustainable within and across the disparate context of the wildlife trade. This necessitates adaptive risk management and innovations in program implementation and evaluation to ensure evidence-based risk management