AUTHOR=Montano Valle Damarys de las Nieves , Berezowski John , Delgado-Hernández Beatriz , Hernández Adrian Quintana , Percedo-Abreu María Irian , Alfonso Pastor , Carmo Luis Pedro TITLE=Modeling transmission of avian influenza viruses at the human-animal-environment interface in Cuba JOURNAL=Frontiers in Veterinary Science VOLUME=11 YEAR=2024 URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2024.1415559 DOI=10.3389/fvets.2024.1415559 ISSN=2297-1769 ABSTRACT=Introduction

The 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.

Materials and methods

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).

Results

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.

Discussion

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.