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

A comparative life cycle assessment (LCA) of alternative material for Australian building construction

The use of wood is seen as a sustainable alternative to reduce environmental impacts in building and construction sector. The low quality hardwood logs from plantation thinning are enhanced by producing engineered wood such as laminated veneer lumber (LVL). Nevertheless, engineered wood requires the use of chemicals and energy that may reduce its environmental benefits. A life cycle assessment (LCA) was conducted to compare the environmental performance of LVL produced from forestry thinning and final harvest to steel and concrete. The functional unit used in this study was a 1-m-long structural beam in a continuous beam system of 6-m-span designed according to the Australian standards. The Global Warming Potential (GWP) and embedded energy were assessed. The results indicated that LVL beam from thinned logs presented the lowest GWP impact (5.22kg-CO2-Eq). However, due to significant energy requirements for wood drying, the embedded energy in LVL was 186.78MJ which is only marginally less than steel (216.86MJ) but significantly less than concrete (352.82MJ). LVL from mature hardwood logs had slightly higher GWP than that produced from thinning; mainly due to extra energy and materials consumption in the plantation stage. Furthermore, LVL produced from mature trees had higher embedded energy than steel. © The Authors, published by EDP Sciences, 2017