Blogs

Testing Site Metrics: Potential Community Demand

This analysis and metric were inspired by the work of Kim et al.1 in their FiveThirtyEight’s article on distribution of testing sites. The purpose of this blog is to describe how we adapted their ‘Potential Community Need’ metric to calculate ‘Potential Community Demand (PCD)’ (a summary of how high the demand for testing could be for each neighborhood when accounting for resident population) in order to describe inequities in testing access on our Dashboard.

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Testing Site Metrics: Spatial Accessibility

Spatial accessibility to COVID-19 testing is an indicator of whether residents of a particular neighborhood have access to nearby COVID-19 testing. We used data provided by Castlight Health Inc. containing the location of testing sites in the 30 BCHC cities to construct two spatial accessibility measures: A walkshed-based measure: a neighborhood is defined as having high access if at least 25% of its area is within a 15 minute walk of a testing site.

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Demystifying Big Cities as COVID-19 Hotspots

Cities play an important role in connecting people by proximity while offering several benefits to its inhabitants. However, city living is accompanied by potential health risks and challenges unique to modern cities. City living, in close proximity, brings together businesses and individuals that drive innovation, productivity, and socioeconomic growth in cities. However, under some conditions, city living is also accompanied by increased crowding. Overcrowded conditions are associated with decreased quality of life, unsafe living conditions, substandard housing, and poor sanitation; all of which can potentially exacerbate the transmission of infectious diseases in vulnerable populations.

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Does Closing Indoor Dining Help Mitigate the Spread of COVID-19?

Since March, state and local governments have had to make challenging decisions to determine which services are essential, when to reopen certain sectors of the community, and to ensure that precautions are taken for the safety of their residents. These decisions have had to balance several aspects, including protecting public health and maintaining economy activity. With many food establishments forced to shutter or transition to takeout only service, the pandemic has led to widespread job loss and economic hardship in the restaurant industry.

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Age-Adjusting—why does it matter for disparities?

Un-adjusted Death Rates Un-adjusted Age Rates Age Distribution Key Insight Un-adjusted Death Rates I recently received an email from my microbiologist uncle, asking me to help him interpret Washington state’s COVID-19 data. The data didn’t seem to match articles he’d read on racial and ethnic inequities in coronovirus deaths. His question seemed a relevant one for many people, inundated with constant COVID-19 data, and who might want further information about how to interpret some of the data they’re seeing.

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Dynata Mask-Wearing Survey Analysis for BCHC Cities

Introduction Compare Estimated Mask Usage across BCHC cities (July 2 - 14) Effect of Mask Mandates on COVID-19 Methodology Dynata Dataset Mandatory Mask Policies Introduction The World Health Organization and the U.S. Centers for Disease Control and Prevention recommend using face masks to slow the spread of the COVID-19 virus. However, face coverings have not been as widely adopted in the US during this current epidemic as it has in previous epidemic epidemics (1918 Influenza Pandemic) or as in other countries internationally.

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