The information below pertains only to the 2020-21 school year and is being retained for archival purposes. It will no longer be updated. All schools are expected to operate fully in-person in 2021-22. For additional data on COVID-19, visit data.ct.gov/coronavirus.

This page provides access to data on the key metrics developed by the Connecticut Department of Health (DPH) and the Department of Education (CSDE) to support local district decision-making on the level of in-person, hybrid (blended), and remote learning model for Pre K-12 education. The information on this page is intended to supplement the comprehensive plan from CSDE, “Adapt, Advance, Achieve: Connecticut’s Plan to Learn and Grow Together”, which will serve as a roadmap for districts as they plan to reopen schools at the beginning of the 2020-21 academic year.

In Addendum 4 of this plan, CSDE and DPH recommend that decisions on in-person vs. remote learning should be based on indicators of the spread and prevalence of COVID-19 in the community; and on the physical and operational ability of schools to implement critical mitigation strategies.

For the national weekly surveillance summary of COVID-19 activity, see the CDC's COVID View.

The key leading indicator to support decision-making on the level of in-person education recommended by DPH and CSDE is:

Additionally, the guidance in Addendum 4 identifies three secondary indicators:

These indicators are summarized in the following dataset: CT School Learning Model Indicators by County (14-day metrics).

While these leading and secondary indicators can be loosely stratified into categories for low, moderate, and high risk, any use of those stratifications should be considered relative, and not an assumption of individual risk of COVID-19 infection in a school or other setting. 

These metrics were adapted from recommendations by the Harvard Global Institute and supplemented by existing DPH measures. 

These data are updated weekly and reflect the previous two full Sunday-Saturday (MMWR) weeks.

The key leading indicator  for community spread recommended by DPH and CSDE is the number of new cases of COVID-19 per 100,000 population per day. The chart below shows the 14-day average for new cases per 100,000 population for the most recent data available.

Percent test positivity is one of three secondary indicators in the guidance from CSDE and DPH. Percent test positivity is calculated by dividing the number of positive tests by the number of total tests for the previous two weeks. The chart below shows the weekly percent test positivity since March 2020.

The number of new COVID-19 hospital admissions per 100,000 population has been identified by CSDE and DPH as one of three secondary indicators. The hospitalization data used to create this metric comes from the Connecticut Hospital Association. Hospitalization data are based on hospital location, not county of patient residence. The chart below shows new COVID-19 hospital admissions per 100,000 population since June 2020.

COVID-like and Influenza-like Illness (CLI and ILI) Syndromic Surveillance has been identified as one of three secondary indicators in the CSDE and DPH guidance. COVID-19-like illness includes fever and cough or shortness of breath or difficulty breathing or the presence of coronavirus diagnosis code and excludes patients with influenza-like illness. The chart below shows the percent of emergency department hospital visits that are for COVID-like illness since March 2020.

The leading and secondary indicators are based on county-level data, but DPH is making town-level data available for the number of new cases per 100,000 population and for the percent test positivity in the following dataset: COVID-19 case rate per 100,000 population and percent test positivity in the last 14 days by town. 

Because the size of Connecticut’s population is relatively small in comparison to many other states, infection and disease rates for many conditions (including COVID-19) can become extremely unstable as statewide statistics are analyzed by smaller geographic areas. As such, analyzing any of the suggested leading or secondary indicators at the individual town or school district level in our state will result in rates that are too unstable to be of any use in continuous decision-making. In addition, daily reporting of metrics that may be somewhat unstable can cause unnecessary alarm and trigger changes where none may be needed. Therefore, DPH recommends analysis of leading and secondary indicators be performed on a weekly basis and be limited by geography to include statewide data and data for each county.

The learning model indicator metrics were originally calculated using a 7-day average. Starting on 10/15/2020, the metrics will be calculated using a 14-day average. We are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH made the decision to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

With respect to geography, DPH has also learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

For questions or suggestions about the data, please contact the individual dataset owner or post suggestions here. For questions regarding the learning model of your school, please contact the school or district office directly. Additional data on COVID-19 in Connecticut can be found at the COVID-19 Data Portal.