Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Ecological characterization of 175 low-pathogenicity avian influenza viruses isolated from wild birds in Mongolia, 2009-2013 and 2016-2018.

BACKGROUND: Since 2005, highly pathogenic avian influenza A H5N1 viruses have spread from Asia worldwide, infecting poultry, humans and wild birds. Subsequently, global interest in avian influenza (AI) surveillance increased. OBJECTIVES: Mongolia presents an opportunity to study viruses in wild birds because the country has very low densities of domestic poultry and supports large concentrations of migratory water birds. METHODS: We conducted AI surveillance in Mongolia over two time periods, 2009-2013 and 2016-2018, utilizing environmental fecal sampling. Fresh fecal samples were collected from water bird congregation sites. Hemagglutinin (HA) and neuraminidase (NA) subtypes of positive samples were identified through viral isolation or molecular assays, with pathogenicity determined by HA subtype or sequencing the HA cleavage site. RESULTS: A total of 10,222 samples were collected. Of these, 7,025 fecal samples were collected from 2009 to 2013, and 3,197 fecal samples were collected from 2016 to 2018. Testing revealed 175 (1.7%) positive samples for low-pathogenicity influenza A, including 118 samples from 2009 to 2013 (1.7%) and 57 samples from 2016 to 2018 (1.8%). HA and NA subtyping of all positives identified 11 subtypes of HA and nine subtypes of NA in 29 different combinations. Within periods, viruses were detected more frequently during the fall season than in the early summer. CONCLUSION: Mongolias critical wild bird habitat is positioned as a crossroad of multiple migratory flyways. Our work demonstrates the feasibility of using an affordable environmental fecal sampling approach for AI surveillance and contributes to understanding the prevalence and ecology of low-pathogenicity avian influenza viruses in this important location, where birds from multiple flyways mix