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The complexity of transmission of COVID-19 in the human population cannot be overstated. Although major transmission routes of COVID-19 remain as human-to-human interactions, understanding the possible role of climatic and weather processes in accelerating such interactions is still a challenge. The majority of studies on the transmission of this disease have suggested a positive association between a decrease in ambient air temperature and an increase in human cases. Using data from 19 early epicenters, we show that the relationship between the incidence of COVID-19 and temperature is a complex function of prevailing climatic conditions influencing human behavior that govern virus transmission dynamics. We note that under a dry (low-moisture) environment, notably at dew point temperatures below 0°C, the incidence of the disease was highest. Prevalence of the virus in the human population, when ambient air temperatures were higher than 24°C or lower than 17°C, was hypothesized to be a function of the interaction between humans and the built or ambient environment. An ambient air temperature range of 17 to 24°C was identified, within which virus transmission appears to decrease, leading to a reduction in COVID-19 human cases. 

Our career-forward approach to general chemistry laboratory for engineers involves the use of design challenges (DCs), an innovation that employs authentic professional context and practice to transform traditional tasks into developmentally appropriate career experiences. These challenges are scaled-down engineering problems related to the US National Academy of Engineering’s Grand Challenges that engage students in collaborative problem solving via the modeling process. With task features aligned with professional engineering practice, DCs are hypothesized to support student motivation for the task as well as for the profession. As an evaluation of our curriculum design process, we use expectancy–value theory to test our hypotheses by investigating the association between students’ task value beliefs and self-confidence with their user experience, gender and URM status. Using stepwise multiple regression analysis, the results reveal that students find value in completing a DC (F(5,2430) = 534.96,p < .001) and are self-confident (F(8,2427) = 154.86,p < .001) when they feel like an engineer, are satisfied, perceive collaboration, are provided help from a teaching assistant, and the tasks are not too difficult. We highlight that although female and URM students felt less self-confidence in completing a DC, these feelings were moderated by their perceptions of feeling like an engineer and collaboration in the learning process (F(10,2425) = 127.06,p < .001). When female students felt like they were engineers (gender x feel like an engineer), their self-confidence increased (β = .288) and when URM students perceived tasks as collaborative (URM status x collaboration), their self-confidence increased (β = .302). Given the lack of representation for certain groups in engineering, this study suggests that providing an opportunity for collaboration and promoting a sense of professional identity afford a more inclusive learning experience.