Large events and gatherings, particularly those taking place indoors, have been linked to multi-transmission events that have accelerated the pandemic spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To provide real-time, geo-localized risk information, we developed an interactive online dashboard that estimates the risk that at least one individual with SARS-CoV-2 is present in gatherings of different sizes in the United States. The website combines documented case reports at the county level with ascertainment bias information obtained via population-wide serological surveys to estimate real time circulating, per-capita infection rates. These rates are updated daily as a means to visualize the risk associated with gatherings, including county maps and state-level plots. The website provides data-driven information to help individuals and policy-makers make prudent decisions (e.g., increasing mask wearing compliance and avoiding larger gatherings) that could help control the spread of SARS-CoV-2, particularly in hard-hit regions.
Epidemiological forecasts of COVID-19 spread at the country and/or state level have helped shape public health interventions. However, such models leave a scale-gap between the spatial resolution of actionable information (i.e. the county or city level) and that of modeled viral spread. States and nations are not spatially homogeneous and different areas may vary in disease risk and severity. For example, COVID-19 has age-stratified risk. Similarly, ICU units, PPE and other vital equipment are not equally distributed within states. Here, we implement a county-level epidemiological framework to assess and forecast COVID-19 spread through Georgia, where 1,933 people have died from COVID-19 and 44,638 cases have been documented as of May 27, 2020. We find that county-level forecasts trained on heterogeneity due to clustered events can continue to predict epidemic spread over multi-week periods, potentially serving efforts to prepare medical resources, manage supply chains, and develop targeted public health interventions. We find that the premature removal of physical (social) distancing could lead to rapid increases in cases or the emergence of sustained plateaus of elevated fatalities.
Individuals connect to sets of places through travel, migration, telecommunications, and social interactions. This set of multiplex network connections comprises an individual’s “extensibility,” a human geography term that qualifies one’s geographic reach as locally‐focused or globally extensible. Here we ask: Are there clear signals of global vs. local extensibility? If so, what demographic and social life factors correlate with each type of pattern? To answer these questions, we use data from the Neighborhood Connectivity Survey conducted in Akron, Ohio, State College, Pennsylvania, and Philadelphia, Pennsylvania (global sample N = 950; in model n = 903). Based on the location of a variety of connections (travel, phone call patterns, locations of family, migration, etc.), we found that individuals fell into one of four different typologies: (a) hyperlocal, (b) metropolitan, (c) mixed‐many, and (d) regional‐few. We tested whether individuals in each typology had different levels of local social support and different sociodemographic characteristics. We found that respondents who are white, married, and have higher educational attainment are significantly associated with more connections to a wider variety of places (more global connections), while respondents who are Black/African American, single, and with a high school level educational attainment (or lower) have more local social and spatial ties. Accordingly, the “urban poor” may be limited in their ability to interact with a variety of places (yielding a wide set of geographic experiences and influences), suggesting that wide extensibility may be a mark of privileged circumstances and heightened agency.
We analyze the consumer-age-specific patterns of restaurant preferences in commercial areas of Seoul, through the mining of place recommendation results from the Naver Place online service. We calculate indices for 188 distinct areas of Seoul measuring the heterogeneity of taste across age groups, and the dominance of any one age group over the general options presented to the public. Our results suggest that both high-traffic and rapidly changing commercial areas present diverse options appealing to all age groups, and that this diversity is primarily driven by the tastes of younger age groups. Recognizing these patterns may help stakeholders predict gentrification and proactively shape neighborhood transformation from business turnover. This study contributes to the broader literature on applying online behavioral data to study urban economic activity.
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