Spatio-temporal dynamics and drivers of Highly Pathogenic Avian Influenza H5N1 in Chile.

Abstract

Highly pathogenic avian influenza A H5N1 clade 2.3.4.4b (hereafter H5N1) is causing vast impacts on biodiversity and poultry around the globe. In Chile it was first reported on December 7th, 2022, in a pelican (Pelecanus thagus) found dead in the northern city of Arica. In the following months, lethal H5N1 cases were reported in a wide range of wild bird species, marine mammals, backyard and industrial poultry, and in a human. Despite its high impact and spread, it is not well-known what environmental factors are associated with outbreaks. This study describes the spatio-temporal patterns of the current epizootic of H5N1 in Chile and test ecological and anthropogenic drivers that could be associated with outbreak occurrence. We used H5N1 cases reported by the Chilean national animal health authority to the World Animal Health Information System (WAHIS) from December 9th, 2022, to March 3rd, 2023. These included bird cases confirmed through avian influenza specific real-time PCR assay (qPCR), obtained from passive and active surveillance. Data was analyzed to detect the presence of H5N1 clusters under space-time permutation probability modelling, H5N1 association between distance and days since first outbreak through linear regression, and correlation between H5N1 presence with a range of ecological and anthropogenic variables by general linear modelling. From the 197 H5N1 identified outbreaks, involving 478 individual cases among wild and domestic birds, a wave-like steady spread of H5N1 from north to south was identified, that can help predict hotspots of outbreak risk and establish targeted preventive measures. For instance, 14 statistically significant clusters were identified, with the largest located in central Chile (18-29 km in radius) where poultry production is concentrated. Also, one of the clusters was identified in Tocopilla, location where the H5N1 human case occurred time later. In addition, the presence of H5N1 outbreaks was positively correlated with bird richness, human footprint, precipitation of the wettest month, minimum temperature of the coldest month, and mean diurnal temperature. In contrast, presence of H5N1 was negatively correlated to distance to the closest urban center, precipitation seasonality and isothermality. Preventive actions based on our modeling approach include developing wildlife surveillance diagnostic capabilities in Chilean regions concentrating outbreaks. It is urgent that scientists, the poultry sector, local communities and national health authorities co-design and implement science-based measures from a One Health perspective to avoid further H5N1 spillover from wildlife to domestic animals and humans, including rapid removal and proper disposal of wild dead animals, and the closure of public areas (i.e., beaches) reporting high wildlife mortalities.