Visual Analytics Dashboard for COVID-19 Risk Management Tracking
| RISK FACTORS | ||||||
|---|---|---|---|---|---|---|
| Primary Measure | Additional Measurements | Model | Granularity | What questions did the data help answer? | Stratification Factors (By category, time, etc.) | |
| 1 | Vulnerable populations | Epidemiological, healthcare system, transportation | Surgo foundation / PrecisionforCovid | Census tract | Which regions are the most vulnerable (in terms of socio-demographic-economic & health factors)? | CDC SVI factors (socioeconomic, household composition, disability, minority status, housing type & transportation) & COVID-19 vulnerability factor (Epidemiologic factor & healthcare system factors) |
| 2 | Worker Vulnerability Information | Physical proximity required and the probability of contraction of a disease | O-Net OnLine | Occupation | What is the vulnerability of an occupation to contract COVID based on their proximity to their clients and job requirement? | |
| 3 | Demographic Information | Vulnerable population | Identify factors contributing to hospitalization risk | Census block | What is the socio-demographic characteristics of the regions vulnerable to COVID | Census block level and aggregated to higher levels of granularity |
| 4 | General epidemiological data | Daily cases, deaths, hospitalization, ventilation and testing | The Atlantic/The COVID Tracking Project | State level | Disease trends across states | Country, State |
| SPREAD DYNAMICS | ||||||
| Primary Measure | Additional Measurements | Model | Granularity | What questions did the data help answer? | Stratification Factors (By category, time, etc.) | |
| 5 | COVID Infections & Fatalities | Number of infected, recovered | Forecast infections Forecast Hospitalizations | Census tract | Which geographical areas are likely to have high infection and hospitalizations (short term and long term)? | Parish level or census tract level |
| 6 | Testing Facilities | Locations of facilities | Forecast infections | Address lat-long | Locations where testing is available (temporary and hospitals) | Facility type, size |
| 7 | Hospitals and number of beds | Number of beds, staffed beds, staff, and ICUs | Forecast hospitalizations | Address lat-long | Which hospitals have additional capacity available for new COVID cases | Facility type, size |
| 8 | Thermometer Data | Temperature of individuals | Kinsa | County level | What are the expected and observed temperatures of individuals in a given region? | County level |
| 9 | General epidemiological data | Daily cases, deaths. | Johns Hopkins Coronavirus Resource Center | Country, State and some City level | Disease trends across countries and states | Country, State, some Cities |
| ECONOMIC FACTORS | ||||||
| Primary Measure | Additional Measurements | Model | Granularity | What questions did the data help answer? | Stratification Factors (By category, time, etc.) | |
| 10 | Economic Drivers (Revenue, Employees) | Sales, Revenue | Show economic indicators | Address | Which businesses have the highest employment and/or revenue, essential (DHS defined), and shutdown (partial or full)? | Number of employees and sales volume |
| 11 | Economic Drivers (Tax Revenue) | Tax Revenue | Show actual variables | Address | Which businesses contribute to the highest tax revenue? | |
| 12 | Employee and Sales Information | Info USA/ArcGIS Business Analyst | Address Lat-long | How many employees are reported for a business along with the economic output of the business? | NAICS code of the business for aggregation and filtering | |
| 13 | Longitudinal Employer-Household Dynamics | Origin-Destination of workforce, Residence and worker area characteristics | Bureau of Labor Statistics | Census Block | Employees from different vulnerable regions | Stratified by types of jobs (based on NAICS codes) and age of workers. |
| MOBILITY PATTERNS | ||||||
| Primary Measure | Additional Measurements | Model | Granularity | What questions did the data help answer? | Stratification Factors (By category, time, etc.) | |
| 14 | Mobility Index (by day) | Type of business, Number of visits | Cubiq | Parish level | What is the social mobility within a given parish? | Time |
| 15 | Commuting Patterns, stay at home index | employees/customer origin for business | Safegraph | Census tract | Which regions/businesses have people coming from high-risk regions? | Number of visitors between business and origin |
| 16 | Community Mobility | Community Mobility | County level | What is the change in mobility in a county | Essential, non-essential, economic mobility | |
| 17 | Longitudinal Employer-Household Dynamics | Origin-Destination of workforce, Residence and worker area characteristics | Bureau of Labor Statistics | Census Block | How many workers living and working in a pair of census blocks? | Stratified by different types of jobs (based on NAICS codes) and age of workers. |