Extreme heat is the deadliest weather and climate-related hazard in the United States, and the threat it poses to urban residents is rising. City planners increasingly recognize these risks and are taking action to mitigate them. However, the COVID-19 pandemic has disrupted many plans. Building on a previous survey which queried city planners from across the United States about how concerned they were about extreme heat, and their heat management efforts. This thesis examines how these perceptions and efforts have changed in the face of the COVID-19 pandemic. In general, it was found that public spaces which would typically have been used to shelter individuals from extreme heat conditions were closed to mitigate close-contact and to encourage social distancing. Furthermore, priorities were changed as the presence of the virus became commonplace, with plans being altered, delayed, or shelved to diverge more time and effort towards the crisis at hand. Working environments and conditions also changed, which in several cases led to technological shortcomings, resulting in further delays. Finally, most planners had attained a surface-level understanding of which socio-economic groups were most impacted by both COVID-19 and extreme heat, in congruence with the current literature written on the topic. Generally, it appears that planners feel that the impact of COVID-19 on heat planning efforts has been limited.

For our project, we explored the growth of the ASU BioDesign Clinical Testing Laboratory (ABCTL) from a standard university research lab to a COVID-19 testing facility through a business lens. The lab has pioneered the saliva-test in the Western United States. This thesis analyzes the laboratory from various business concepts and aspects. The business agility of the lab and it’s quickness to innovation has allowed the lab to enjoy great success. Looking into the future, the laboratory has a promising future and will need to answer many questions to remain the premier COVID-19 testing institution in Arizona.

In the past year, considerable misinformation about the COVID-19 pandemic has circulated on social media platforms. Faced with this pervasive issue, it is important to identify the extent to which people are able to spot misinformation on social media and ways to improve people’s accuracy in spotting misinformation. Therefore, the current study aims to investigate people’s accuracy in spotting misinformation, the effectiveness of a game-based intervention, and the role of political affiliation in spotting misinformation. In this study, 235 participants played a misinformation game in which they evaluated COVID-19-related tweets and indicated whether or not they thought each of the tweets contained misinformation. Misinformation accuracy was measured using game scores, which were based on the correct identification of misinformation. Findings revealed that participants’ beliefs about how accurate they are at spotting misinformation about COVID-19 did not predict their actual accuracy. Participants’ accuracy improved after playing the game, but democrats were more likely to improve than republicans.

As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).