Global Avian Influenza Infections among Humans and Animals during 2013–2022 (Preprint)

BACKGROUND Avian influenza (AI) outbreaks occurred frequently in 2022 and continue to pose a health, economic, and food security risk. A comprehensive review of current global AI surveillance information is key to assessing the pandemic risk of AI viruses. OBJECTIVE We provide an analysis of global AI surveillance information from the last decade and identify risk factors of interest and surveillance gaps. METHODS We compared AI reports submitted to animal and public health authorities from January 2013 – June 2022 to January 2005 – December 2012. A multivariable regression analysis was used to evaluate associations between risk factors of interest and reported animal AI outbreaks. RESULTS From 2013–2022, 52% (95/182) of World Organization for Animal Health (WOAH) member-states identified 34 AI virus subtypes during 21,249 outbreaks. The most frequently reported subtypes were high pathogenic AI H5N1 (10,079, 47.4%) and H5N8 (6,722, 31.6%). Ten high pathogenic AI and six low pathogenic AI virus subtypes were reported to WOAH for the first time during 2013–2022. One in four member-states (26/95) did not report an outbreak prior to 2013. AI outbreaks in animals occurred in 26 more countries than reported in the previous eight years. Decreasing World Bank income classification was significantly associated with decreases in reported AI outbreaks. Seventeen (8.8%, 17/194) World Health Organization (WHO) member-states reported 2,000 human AI virus infections of 10 virus subtypes. H7N9 (1,568, 78.4%) and H5N1 (254, 12.7%) viruses accounted for the most human infections. Eight member-states did not report a human case prior to 2013. Of 1,953 human cases with available information, 75% (1,461/1,953) had a known animal exposure. The median time from illness onset to the notification posted on the WHO event information site was 15 days (IQR=21, Average= 23). Seasonality patterns of bird outbreaks and human infections with AI viruses were very similar, occurred year-round, and peaked during November through May. CONCLUSIONS Our analysis suggests that AI outbreaks are more frequent and geographically widespread than in the past. Global surveillance gaps include reporting delays and inconsistent reporting from all regions. Continued monitoring for AI outbreaks in animals and human infections with AI viruses is crucial for pandemic preparedness.