Routing algorithms as tools for integrating social distancing with emergency evacuation.

One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation. To explore the implications of integrating social distancing with evacuation operations, we describe this evacuation process as a Capacitated Vehicle Routing Problem (CVRP) and solve it using a DNN (Deep Neural Network)-based solution (Deep Reinforcement Learning) and a non-DNN solution (Sweep Algorithm). A central question is whether Deep Reinforcement Learning provides sufficient extra routing efficiency to accommodate increased social distancing in a time-constrained evacuation operation. We found that, in comparison to the Sweep Algorithm, Deep Reinforcement Learning can provide decision-makers with more efficient routing. However, the evacuation time saved by Deep Reinforcement Learning does not come close to compensating for the extra time required for social distancing, and its advantage disappears as the emergency vehicle capacity approaches the number of people per household.

Who benefits from urban green spaces during times of crisis? Perception and use of urban green spaces in New York City during the COVID-19 pandemic.

Urban green spaces (UGS) provide health benefits to city dwellers, which may be even more important during times of crisis such as the COVID-19 pandemic. However, lack of access to UGS or important features of UGS, in addition to concerns about UGS safety or maintenance, could prevent people from receiving these benefits. We designed an online survey to understand how people were using and perceiving UGS during the COVID-19 pandemic in New York City during the spring of 2020. The survey included questions about how people's visits to UGS and perceptions of the importance of UGS for their health had changed since the start of the pandemic, as well as the concerns people had and features of UGS they considered important. Of the 1372 people who took the survey, most respondents were concerned about a lack of social distancing and crowded UGS, and respondents with these concerns were less likely to visit UGS and had visited UGS less often during than before the pandemic. In addition, generalized linear models showed differences in some concerns and important features of UGS across gender, race and ethnicity, demonstrating the importance of considering specific community needs in UGS design and management. Although concerns about lack of access were not common in our study population, these also appeared to prevent people from using UGS, and were more common in certain areas of the city that were also hard-hit by COVID-19 in the beginning of the pandemic. To ensure that people can get health benefits from UGS during times of crisis, cities must eliminate barriers by providing equitable access to UGS, considering what amenities communities need from UGS, and provide consistent communication about public health policies.

Using internet search data to understand information seeking behavior for health and conservation topics during the COVID-19 pandemic.

Emerging zoonotic diseases, such as COVID-19, exist at the intersection of human health and the environment. Public interest and support are required to maximize the effectiveness of policies to combat the current pandemic and prevent future outbreaks of zoonoses. Here, we use internet search data from the United States to investigate changes in public information seeking about topics at the intersection of health and the environment during the COVID-19 pandemic. Using breakpoint detection methods, we identify sharp increases in interest for 'wildlife trade', 'bats', and 'pangolins' in the early stages of the pandemic (on Jan. 12, Jan. 19, and Jan. 26, 2020, respectively). Network analyses also revealed increasing connectivity between terms related to human health and the environment, as well as the emergence of novel search terms pointing to a greater interest in wildlife trade and consumption. During the pandemic, the network connectivity between coronavirus keywords and conservation keywords increased, which we measured using the number of unique connections (edge connectivity, k' (G)) and the number of simple paths (Sp) between keywords. Both measures of network connectivity increased between 'coronavirus' and 'bats' or 'pangolins' (Δk' (G) = 1, ΔSp = 37), and between 'coronavirus' and 'conservation' (Δk' (G) = 1, ΔSp = 160). These findings suggest that policy and outreach efforts aimed at engaging public interest in intersectional approaches to pandemic prevention (eg: One Health, Planetary Health), may be able to take advantage of increases in public information seeking following catalyzing events during the pandemic. Further monitoring is needed to determine if these changes persist over time.