Abstract Title
Modelling Avian Influenza Virus Transmission at the Human-Animal-Environment Interface in Cuba
Abstract
Introduction: The current panzootic caused by HPAI (H5N1) clade 2.3.4.4b demonstrates the need for collaborative surveillance and a paradigm shift towards risk detection, supporting the development of early warning systems to identify and mitigate risks before they become events. We have developed an integrated One Health model to estimate the probability of AI transmission at the human-animal-environment interface in Cuba.
Methods: Models were developed for AI virus transmission from wild birds to domestic birds or pigs and from the latter to farmers and the general population, with national scope and at the resolution of the of the smallest administrative structure. Parameters included were risk factors for AI introduction into Cuba (rice fields, wild bird abundance, permanent hydrography and migratory waterfowl stopover areas), animal and human population densities and contact intensity and a transmission parameter.
Results: Areas with higher risk of AI transmission were identified for each species showing some spatial heterogeneity in the distribution of these areas. In particular, the southwestern and eastern regions were at higher risk.
Discussion: These results are potentially useful for refining existing criteria for selecting farms for active surveillance, which could improve the ability to detect positive cases. Model results could contribute to the design of an integrated risk-based surveillance system for AI in Cuba.
Conclusions: Model results allow risk stratification of areas according to the country's smaller administrative structure, providing decision makers with a better opportunity to manage health risks by prioritizing resources for surveillance and risk reduction based on scientific evidence.
Methods: Models were developed for AI virus transmission from wild birds to domestic birds or pigs and from the latter to farmers and the general population, with national scope and at the resolution of the of the smallest administrative structure. Parameters included were risk factors for AI introduction into Cuba (rice fields, wild bird abundance, permanent hydrography and migratory waterfowl stopover areas), animal and human population densities and contact intensity and a transmission parameter.
Results: Areas with higher risk of AI transmission were identified for each species showing some spatial heterogeneity in the distribution of these areas. In particular, the southwestern and eastern regions were at higher risk.
Discussion: These results are potentially useful for refining existing criteria for selecting farms for active surveillance, which could improve the ability to detect positive cases. Model results could contribute to the design of an integrated risk-based surveillance system for AI in Cuba.
Conclusions: Model results allow risk stratification of areas according to the country's smaller administrative structure, providing decision makers with a better opportunity to manage health risks by prioritizing resources for surveillance and risk reduction based on scientific evidence.
Co-Author(s)
Damarys de las Nieves Montano Valle1, Luis Pedro Carmo2, Beatriz Delgado-Hernández1, Adrián Quintana Hernández3, María Irían Percedo-Abreu1, Pastor Alfonso Zamora1 and John Berezowski4
Affiliations:
1National Center for Animal and Plant Health, Cuba.
2Norwegian Veterinary Institute.
3National Center of the Protected Areas, Cuba.
4Scotland's Rural College (SRUC)
Abstract Category
Avian influenza in mammals, pandemic preparedness, and one health