COVID-19 Community Impact Survey Data Dashboard

Explore the data from the COVID-19 Community Impact Survey using our interactive data dashboard.

Table of Contents


Welcome to the Massachusetts Department of Public Health's COVID-19 Community Impact Survey Data Dashboard. This dashboard allows users to explore data and findings from the CCIS. Before diving into the data, be sure to watch the CCIS Introduction Webinar and view the Introduction Slide Deck for guidance on how to view the findings using a racial justice lens and how to turn the data into action. More information about the CCIS and recommendations on how to use the data can also be found in the sections below.

To provide feedback related to the COVID Community Impact Survey (CCIS) Dashboard, please complete this feedback form.

COVID-19 Community Impact Survey Data Dashboard

About the data

About the CCIS Survey

This data is from the COVID-19 Community Impact Survey (CCIS), conducted online from September through November 2020 by the Massachusetts Department of Public Health.  The purpose of the survey was to understand the specific needs of populations that have been disproportionately impacted by the pandemic, including its social and economic impacts. The survey was open to all people over the age of 14 living in Massachusetts. Data included here are only from respondents aged 25 years old and older.

Please visit the CCIS webpage for more information and resources, including:

  • Preliminary analysis reports
  • Data tables
  • Recorded webinars, including an Introduction Webinar to understand how to interpret and use the data from the CCIS

Who responded to the survey

The CCIS captured the experiences and needs brought on by the COVID-19 pandemic of more than 33,000 adult residents across race, ethnicity, class, geography, and other population groups in Massachusetts. This allows us to share out data specific to many different population groups, including but not limited to:

  • Race and Hispanic Ethnicity
  • Ethnicity groups
  • Socioeconomic status (SES) such as education attainment and annual income
  • Gender identity, sexual orientation, and transgender status
  • Disability status such as those who are blind, deaf, or have mental or physical disabilities
  • Individuals who speak languages other than English

In addition to population groups, we can also share out data for various geographies where data is available to share, including by:

  • Counties
  • Rural clusters
  • Cities/Towns

Interpreting the data

While the CCIS was offered to everyone in Massachusetts, not everyone in your community took the survey. The experiences captured from respondents who answered the survey may represent others with similar circumstances, experiences, and identities, but may NOT fully represent the experience of everyone living within those geographies or with those identities. When interpreting the data for your community, it is very important to think about whether the characteristics of the residents who answered the survey are similar or different from all residents living in the community. Whose experiences may have been underrepresented in the survey? Whose experiences may have been overrepresented?

This is especially important since the survey found that overall, communities of color, in particular those from the Black, Hispanic/Latinx, American Indian/Alaska Native, and select Asian/Pacific Islander ethnicities, had disproportionately worse outcomes compared to Whites. Residents with lower income also consistently experienced worse outcomes than higher income residents. Older residents, however, tended to have better outcomes compared to younger residents.

What this may mean is that if for your community, respondents who answered the survey tend to be whiter, higher income, and/or older than all residents in your community, then the results may suggest that the outcomes are better than what is actually happening in the community.

Before looking at the responses for the geographies (by county, rural cluster, or city/town) you are interested in, it is important to look at some demographic characteristics of who responded to the survey and how they compare to the demographic characteristics of all residents living in that geography. Census data provides us with a more complete representation of the demographic characteristics of all residents living in a particular geography.

Using the data

There are many ways to take the CCIS results and use it to make an impact. Below are just some ideas to get you started:

  1. Use it in your organization or local government's resource prioritization decisions
  2. Use it to start or continue conversations with people most impacted or disproportionately impacted to hear firsthand about how this plays out for people with lived experience of inequities?  What are their concerns and ideas?​
  3. Use it to inform messaging, outreach, and PSAs to better reach target populations
  4. Use it as a conversation starter with current or new partners to support existing or start new initiatives
  5. Share it with decision makers to raise awareness or advocate for a specific cause
  6. Use it in community or regional health needs assessments
  7. Use it in a grant application to apply for additional funding
  8. Address underlying systemic issues that created the problem in the first place

Below are some guiding questions to think about as you explore the data and consider the problems it raises and identify appropriate solutions

  1. What do the data tell you about specific issues in your community?
  2. Who are the populations within your community who are most impacted?
    1. Although the spreadsheet does NOT show inequities by race, ethnicity, and other identity groups that are specific to your community, you can compare what you know about your community to statewide survey results for these groups.  Comparing the statewide survey results with what you know about your community's demographics, are there groups living in your community that are most impacted or disproportionately impacted?
  3. Does the data tell you something new about the issues in your community?
  4. What are some possible causes for the issues you’re seeing?
  5. What do you know from other data and experiences that help you understand this issue?
  6. Which voices have you heard from? Who has been left out of the conversation so far?
  7. What are possible solutions/goals?
  8. Are there things that can be done right away to address this issue?
  9. Are there things that you can work on long-term to address this issue?
  10. What action is needed?
  11. Who are partners that can help you take action? Think about partners that are already engaged, as well as those who have been left out of the conversation. What are possible barriers to taking action? How can you overcome them?
  12. What else do you need to know to take action?

About data suppression

Any group where less than 30 respondents answered the question (denominator < 30) or less than 5 respondents reported that outcome (numerator or "count" < 5) was suppressed.

For example, Town A had 25 respondents answer the question "How worried are you about getting infected with COVID-19", then all results related to that question will be suppressed for Town A.

If Town B had 60 respondents answer the question, but only 4 respondents who said they were "very worried", then when reporting out the outcome as % very worried about getting COVID-19, we also need to suppress Town B, since its numerator for that outcome was less than 5.

About ethnicity data

Respondents were able to select as their ethnicities from a pre-defined list as well as write-in their ethnicity if available options did not fully capture their ethnic identity. Write-in responses were then coded to be included analysis. Respondents were able to select as many ethnicities as needed, and in some cases, categories may not be mutually exclusive.

About rural data

The State Office of Rural Health has worked with its advisory council, the Massachusetts Rural Council on Health to develop the state definition for Rural.

A municipality in Massachusetts is considered rural if it meets one of the following criteria:

  • Meets at least one of three federal rural definitions at the sub-county level (Census Bureau, OMB, or RUCAs), and/or
  • Has a population less than 10,000 people and a population density below 500 people per square mile, and/or
  • Has an acute care hospital in the town that meets the state hospital licensure definition of a small rural hospital (SRH), or is a certified Critical Access Hospital (CAH).
  • Has a federally licensed Rural Health Clinic (RHC) in the town.

Two levels of rurality

Rural towns are also classified into two categories of rurality. Towns classified as rural level one meet fewer rural criteria than towns considered rural at level two.

  • Towns in Rural Level 2 are less densely populated and more remote and isolated from urban core area as compared to Rural Level 1.
  • Towns in Rural Level 1 and Rural Level 2 are both rural.
  • Towns not in level one or two are considered urban.

About weighting

Percentages presented here for all populations (except county, rural data, and municipality) are weighted to the statewide age and educational distribution of those 25 years old or older in Massachusetts. While the respondents were predominately female, data were not weighted to gender identity because the survey allowed respondents to select from a more inclusive list of gender identities than other sources of statewide data.

Data presented at sub-state geographies (county, rural cluster, municipality priority communities) were NOT weighted to the statewide age and educational distribution of those 25 years or older in MA since the age and educational distributions within those geographies may be different than the statewide distribution. The unweighted percentages in those tabs represent rates of response of individuals that completed the survey in those geographies and may not be representative of those geographies as a whole. Comparisons between geographies also should be made with caution as the populations that completed the survey in one geography may look very different than those that completed the survey in others.

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