To support evidence-based decisions by our county and state leaders that impact our North Carolina citizens during this historic pandemic, the DHIT team has developed the Community Confidence dashboard. The metrics you see here are based on vetted data sources, statistical and disease dynamics models, and findings from key COVID-19 research groups published in many top scientific journals. In addition to relying on the scientific community’s rapidly changing understanding of COVID-19, the DHIT team has developed a novel modeling framework that addresses the key challenge of this pandemic: how do we balance the physical health and the economic health of our communities?

Our Approach

Behind our Community Confidence score are analytical models that incorporate disease dynamics and community preference. The Community Confidence score itself results from a Choice Experiment in which North Carolinians were systematically polled to understand how they prioritize various elements related to the pandemic. Analysis of the thousands of responses yields an understanding of the preferences, priorities and tolerances of our state residents.  Community members and leaders, therefore, look to the Community Confidence score as a measure of how acceptable the current scenario is (in the case of the County tab), or how preferable a potential scenario would be (in the case of changes under consideration in the Simulation tab).  

However, coupled with the Choice Experiment algorithm is a disease dynamics model that tracks the trajectory of spread in our North Carolina counties. To predict how changes in policy or behavior will impact COVID-19, we apply either a spread reduction factor or a spread increase factor, using findings from key research groups. For example, when an action is considered to mitigate COVID-19 spread such as closing all restaurants, our modeling takes this action into account and projects the impact on short-term future cases and deaths. The combination of projected cases, deaths, and economic and behavioral factors (the closure of restaurants, and other similar factors), is a scenario. This scenario is then rated by our Choice Experiment algorithm to gauge Community Confidence in that decision or policy along with the projected COVID-19 impacts.

Our Data Sources

Our data sources include the North Carolina Department of Health and Human Services, providing us with daily COVID-19 data for every county in North Carolina, the US Census Bureau, ClimaCell weather data, and SafeGraph data regarding mobility behavior.

Our Knowledge Sources

To effectively deliver valuable insights to North Carolinians, we leverage the findings and methods from the broader COVID-19 research community, including the following resources:

  • Institute for Health Metrics and Evaluation (IHME)
  • CovidActNow  
  • Numerous scientific journal articles
Wunderground Wunderground is a comprehensive historic weather data repository that reports on over 250,000 personal weather stations and commercial weather stations in the USA. We obtain the highest quality temperature, dew point, humidity, and wind gust data by the hour per county.
ClimaCell ClimaCell is one of the most reputable weather APIs, used by Google, Amazon, and Facebook. We collect daily temperature, dew point, humidity, and wind gust data via their reliable and tested API.
Johns Hopkins Johns Hopkins is the most cited, referenced, and utilized source for COVID case information. The JH API offers a reliable and accessible API to source COVID cases and death data.
NC-DHHS The Department of Health and Human Services is responsible for housing and providing capacity, COVID cases, comorbidities, and testing data for all health systems in the USA. DHHS currently is the only source which stores this data other than individual health systems.
Keystone Strategy Insufficient data has complicated the rollout of Coronavirus (COVID-19) “Non-Pharmaceutical Interventions” (NPIs) such as the closing of schools. Keystone has partnered with Susan Athey, Stanford Professor of Economics, and Marco Iansiti, Director of Harvard Business School’s Digital Initiative, to estimate the effectiveness of NPIs as a guide to policymakers, and to aid firms in developing strategic responses, respectively. We are building a comprehensive, highly localized and freely available data set of city, county and state rollout dates for NPIs. The most widely used source for calculating growth infection rates.
US Census Bureau The only source which supplies US County demographic data.
County Health Rankings Provides community health data and some socioeconomic data per county (sources from US Census Bureau).
Broadband Now Provides percentage of people who have access to internet per county.
NC State Board of Elections Voter registration data per county.
New York Times Data Provides COVID-19 case data and some survey data such as mask wearing in July per county.
NC Commerce Economic data per county in North Carolina.
MIT Supplies customer risk when entering establishments per industry. Based on study by MIT in collaboration with Cyprus University.
Visual Capitalist Sole provider of Employee risk per industry.
NCBI Repository of Scientific Journals about coronavirus. Used to replicate, validate our methods, and incorporate the rigorous work of other research groups.
ChoiceFlows Investigates community opinion on economic policies, NPIs and coronavirus using the accurate and tried/tested Discrete Choice Experiment approach. The DCE was tailored specifically to DHIT’s mission using ChoiceFlow’s resources along with our qualified staff of data scientists and statisticians.
National Center for Education Statistics Socioeconomic data per county (also sources some data points from US Census Bureau).
SafeGraph Provides the most granular (by county, by industry) and high quality mobility data available, making SafeGraph the most widely used and gold standard data source for social distancing/mobility in the field.