Insights from the data about at risk parts of the US
Ultimately the maps represent ratios of risk adjustment “demand” by measures of Low, Medium, High and Sever risk (or combinations thereof), relative to “supply” by measures of Total Beds, ICU Beds and Physician Intensivists. Those ratios indicate areas of the U.S. with severe limitations of capacity relative to the abundance of populations with underlying complications and comorbid conditions for each ZIP3 region.
High/Severe Risk to Medium High Severe Risk. In addition, further experiment by changing the drop down selections of: Hospital Beds to ICU Beds to Physician Intensivists. The maps and underlying data are responsive to your selections.
1. Total Hospital Beds:
Counts of Total Hospital Beds within each 3-digit ZIP3 region (limited to hospital classes: General Medical/Surgical Adult and Children’s Hospitals, Critical Access Hospitals and Military and Veterans Affairs Hospitals)
2. ICU Beds:
Both measured and where null we estimated within each 3-digit ZIP3 region (where estimated is the mean percentage of ICU Beds / Total Beds within the same class of hospital)(Subject to the same limited set of hospital classes: General Medical/Surgical Adult and Children’s Hospitals, Critical Access Hospitals and Military and Veterans Affairs Hospitals as above)
3. Physician Intensivists:
Ajao et al.  and Gershengorn et al.  suggest limited Physicians to those specialties experienced in caring for ARDS and ventilator dependent patients (limited to: Critical Care Medicine, Pulmonary Medicine, Emergency Medicine, Anesthesiology and Thoracic Surgery specialties)
Unlike Ajao et al. , PurpleLab decided to risk adjust the population to understand the distribution of underlying chronic conditions and comorbidities that are likely to adversely affect outcomes in the COVID-19 population. Patients with underlying chronic conditions and comorbidities that COVID-19 is selective for are unevenly distributed throughout populations in various geographies across the U.S.