A Global Building Occupant Behavior Database

This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting

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

Disparities in self-reported extreme weather impacts by race, ethnicity, and income in the United States

Dataset accompanying the article "Disparities in self-reported extreme weather impacts by race, ethnicity, and income in the United States" (Zanocco, Flora & Boudet, 2022)

Food Practice Lifestyles: Identification and Implications for Energy Sustainability

Food systems, including production, acquisition, preparation, and consumption, feature importantly in environmental sustainability, energy consumption and climate change. With predicted increases in food and water shortages associated with climate change, food-related lifestyle and behavioral changes are advocated as important mitigation and adaptation measures. Yet, reducing emissions from food systems is predicted to be one of our greatest challenges now and in the future. Traditional theories of environmental behavioral change often assume that individuals make “reasoned choices” that incorporate cost–benefit assessment, moral and normative concerns and affect/symbolic motives, yielding behavioral interventions that are often designed as informational or structural strategies. In contrast, some researchers recommend moving toward an approach that systematically examines the temporal organization of society with an eye toward understanding the patterns of social practices to better understand behaviors and develop more targeted and effective interventions. Our study follows on these recommendations with a study of food consumption “lifestyles” in the United States, using extant time use diary data from a nationally representative sample of Americans (n = 16,100) from 2014 to 2016. We use cluster analysis to identify unique groups based on temporal and locational eating patterns. We find evidence of six respondent clusters with distinct patterns of food consumption based on timing and location of eating, as well as individual and household characteristics. Factors associated with cluster membership include age, employment status, and marital status. We note the close connections between age and behaviors, suggesting that a life course scholarship approach may add valuable insight. Based on our findings, we identify opportunities for promoting sustainable energy use in the context of the transition to renewables, such as targeting energy-shifting and efficiency-improvement interventions based on group membership