# COVID-19 Trends and Impact Survey

• Source name: fb-survey
• Earliest issue available: April 29, 2020
• Number of data revisions since May 19, 2020: 1
• Date of last change: June 3, 2020
• Available for: county, hrr, msa, state, nation (see geography coding docs)
• Time type: day (see date format docs)

## Overview

This data source is based on the COVID-19 Trends and Impact Survey (CTIS) run by the Delphi group at Carnegie Mellon. Facebook directs a random sample of its users to these surveys, which are voluntary. Users age 18 or older are eligible to complete the surveys, and their survey responses are held by CMU and are sharable with other health researchers under a data use agreement. No individual survey responses are shared back to Facebook. See our surveys page for more detail about how the surveys work and how they are used outside the COVIDcast API.

As of November 2021, the average number of Facebook survey responses we receive each day is about 40,000, and the total number of survey responses we have received is over 25 million.

We produce several sets of signals based on the survey data, listed and described in the sections below:

1. Influenza-like and COVID-like illness indicators, based on reported symptoms
2. Behavior indicators, including mask-wearing, traveling, in-person schooling, and other activities outside the home
3. Testing indicators based on respondent reporting of their COVID test results
4. Vaccination indicators, based on respondent reporting of COVID vaccinations, whether they would accept a vaccine, and reasons for any hesitancy to accept a vaccine
5. Mental health indicators, based on self-reports of anxiety, depression, isolation, and worry about COVID
6. Belief, experience, and information indicators, about the respondent’s beliefs about COVID-19, their experiences of health care, their sources of information about COVID-19, and their degree of trust in different sources

Many of these signals can also be browsed on our survey dashboard at any selected location.

## Survey Text and Questions

The survey starts with the following 5 questions:

1. In the past 24 hours, have you or anyone in your household had any of the following (yes/no for each):
• (a) Fever (100 °F or higher)
• (b) Sore throat
• (c) Cough
• (d) Shortness of breath
• (e) Difficulty breathing
2. How many people in your household (including yourself) are sick (fever, along with at least one other symptom from the above list)?
3. How many people are there in your household in total (including yourself)? [Beginning in wave 4, this question asks respondents to break the number down into three age categories.]
4. What is your current ZIP code?
5. How many additional people in your local community that you know personally are sick (fever, along with at least one other symptom from the above list)?

Beyond these 5 questions, there are also many other questions that follow in the survey, which go into more detail on symptoms, contacts, risk factors, and demographics. These are used for many of our behavior and testing indicators below. The full text of the survey (including all deployed versions) can be found on our questions and coding page.

## ILI and CLI Indicators

We define COVID-like illness (fever, along with cough, or shortness of breath, or difficulty breathing) or influenza-like illness (fever, along with cough or sore throat) for use in forecasting and modeling. Using this survey data, we estimate the percentage of people (age 18 or older) who have a COVID-like illness, or influenza-like illness, in a given location, on a given day.

Signals beginning raw_w or smoothed_w are adjusted using survey weights to be demographically representative as described below. Weighted signals have 1-2 days of lag, so if low latency is paramount, unweighted signals are also available. These begin smoothed_ or raw_, such as raw_cli instead of raw_wcli.

Signals Description
raw_wcli and smoothed_wcli Estimated percentage of people with COVID-like illness
Earliest date available: 2020-04-06
raw_wili and smoothed_wili Estimated percentage of people with influenza-like illness
Earliest date available: 2020-04-06
raw_whh_cmnty_cli and smoothed_whh_cmnty_cli Estimated percentage of people reporting illness in their local community, as described below, including their household
Earliest date available: 2020-04-15
raw_wnohh_cmnty_cli and smoothed_wnohh_cmnty_cli Estimated percentage of people reporting illness in their local community, as described below, not including their household
Earliest date available: 2020-04-15

Note that for raw_whh_cmnty_cli and raw_wnohh_cmnty_cli, the illnesses included are broader: a respondent is included if they know someone in their household (for raw_whh_cmnty_cli) or community with fever, along with sore throat, cough, shortness of breath, or difficulty breathing. This does not attempt to distinguish between COVID-like and influenza-like illness.

Influenza-like illness or ILI is a standard indicator, and is defined by the CDC as: fever along with sore throat or cough. From the list of symptoms from Q1 on our survey, this means a and (b or c).

COVID-like illness or CLI is not a standard indicator. Through our discussions with the CDC, we chose to define it as: fever along with cough or shortness of breath or difficulty breathing.

Symptoms alone are not sufficient to diagnose influenza or coronavirus infections, and so these ILI and CLI indicators are not expected to be unbiased estimates of the true rate of influenza or coronavirus infections. These symptoms can be caused by many other conditions, and many true infections can be asymptomatic. Instead, we expect these indicators to be useful for comparison across the United States and across time, to determine where symptoms appear to be increasing.

Smoothing. The signals beginning with smoothed estimate the same quantities as their raw partners, but are smoothed in time to reduce day-to-day sampling noise; see details below. Crucially, because the smoothed signals combine information across multiple days, they have larger sample sizes and hence are available for more counties and MSAs than the raw signals.

### Defining Household ILI and CLI

For a single survey, we are interested in the quantities:

• $$X =$$ the number of people in the household with ILI;
• $$Y =$$ the number of people in the household with CLI;
• $$N =$$ the number of people in the household.

Note that $$N$$ comes directly from the answer to Q3, but neither $$X$$ nor $$Y$$ can be computed directly (because Q2 does not give an answer to the precise symptomatic profile of all individuals in the household, it only asks how many individuals have fever and at least one other symptom from the list).

We hence estimate $$X$$ and $$Y$$ with the following simple strategy. Consider ILI, without a loss of generality (we apply the same strategy to CLI). Let $$Z$$ be the answer to Q2.

• If the answer to Q1 does not meet the ILI definition, then we report $$X=0$$.
• If the answer to Q1 does meet the ILI definition, then we report $$X = Z$$.

This can only “over count” (result in too large estimates of) the true $$X$$ and $$Y$$. For example, this happens when some members of the household experience ILI that does not also qualify as CLI, while others experience CLI that does not also qualify as ILI. In this case, for both $$X$$ and $$Y$$, our simple strategy would return the sum of both types of cases. However, given the extreme degree of overlap between the definitions of ILI and CLI, it is reasonable to believe that, if symptoms across all household members qualified as both ILI and CLI, each individual would have both, or neither—with neither being more common. Therefore we do not consider this “over counting” phenomenon practically problematic.

### Estimating Percent ILI and CLI

Let $$x$$ and $$y$$ be the number of people with ILI and CLI, respectively, over a given time period, and in a given location (for example, the time period being a particular day, and a location being a particular county). Let $$n$$ be the total number of people in this location. We are interested in estimating the true ILI and CLI percentages, which we denote by $$p$$ and $$q$$, respectively:

$p = 100 \cdot \frac{x}{n} \quad\text{and}\quad q = 100 \cdot \frac{y}{n}.$

In a given aggregation unit (for example, daily-county), let $$X_i$$ and $$Y_i$$ denote number of ILI and CLI cases in the household, respectively (computed according to the simple strategy described above), and let $$N_i$$ denote the total number of people in the household, in survey $$i$$, out of $$m$$ surveys we collected. Then our unweighted estimates of $$p$$ and $$q$$ are:

$\hat{p} = 100 \cdot \frac{1}{m}\sum_{i=1}^m \frac{X_i}{N_i} \quad\text{and}\quad \hat{q} = 100 \cdot \frac{1}{m}\sum_{i=1}^m \frac{Y_i}{N_i}.$

See below for details on weighting and standard errors for these estimates.

### Estimating “Community CLI”

Over a given time period, and in a given location, let $$u$$ be the number of people who know someone in their community with CLI, and let $$v$$ be the number of people who know someone in their community, outside of their household, with CLI. With $$n$$ denoting the number of people total in this location, we are interested in the percentages:

$a = 100 \cdot \frac{u}{n} \quad\text{and}\quad b = 100 \cdot \frac{y}{n}.$

For a single survey, let:

• $$U = 1$$ if and only if a positive number is reported for Q2 or Q5;
• $$V = 1$$ if and only if a positive number is reported for Q2.

Let $$U_i$$ and $$V_i$$ denote these quantities for survey $$i$$, and $$m$$ denote the number of surveys total. We report the percentage of surveys where $$U_i = 1$$ as in the hh_cmnty_cli signals and the percentage where $$V_i = 1$$ in the nohh_cmnty_cli signals. The exact estimators are described below.

Note that $$\sum_{i=1}^m U_i$$ is the number of survey respondents who know someone in their community with either ILI or CLI, and not CLI alone; and similarly for $$V$$. Hence $$\hat{a}$$ and $$\hat{b}$$ will generally overestimate $$a$$ and $$b$$. However, given the extremely high overlap between the definitions of ILI and CLI, we do not consider this to be practically very problematic.

### Smoothing

The smoothed versions of all fb-survey signals (with smoothed prefix) are calculated using seven day pooling. For example, the estimate reported for June 7 in a specific geographical area (such as county or MSA) is formed by collecting all surveys completed between June 1 and 7 (inclusive) and using that data in the estimation procedures described above.

## Behavior Indicators

Signals beginning smoothed_w are adjusted using survey weights to be demographically representative as described below. Weighted signals have 1-2 days of lag, so if low latency is paramount, unweighted signals are also available. These begin smoothed_, such as smoothed_wearing_mask instead of smoothed_wwearing_mask.

Signal Description Survey Item Introduced
smoothed_wwearing_mask_7d Estimated percentage of people who wore a mask for most or all of the time while in public in the past 7 days; those not in public in the past 7 days are not counted.
Earliest date available: 2021-02-08
C14a Wave 8, Feb 8, 2021
smoothed_wwearing_mask Discontinued as of Wave 8, Feb 8, 2021 Estimated percentage of people who wore a mask for most or all of the time while in public in the past 5 days; those not in public in the past 5 days are not counted.
Earliest date available: 2020-09-08
C14 Wave 4, Sept 8, 2020
smoothed_wothers_masked_public Estimated percentage of respondents who say that most or all other people wear masks, when they are in public.
Earliest date available: 2021-05-19
H2 Wave 11, May 19, 2021
smoothed_wothers_masked Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who say that most or all other people wear masks, when they are in public and social distancing is not possible.
Earliest date available: 2020-11-24
C16 Wave 5, Nov 24, 2020

### Social Distancing and Travel

Signal Description Survey Item Introduced
smoothed_wothers_distanced_public Estimated percentage of respondents who reported that all or most people they enountered in public in the past 7 days maintained a distance of at least 6 feet. Respondents who said that they have not been in public for the past 7 days are excluded.
Earliest date available: 2021-06-10
H1 Wave 11, May 19, 2021
smoothed_wpublic_transit_1d Estimated percentage of respondents who “used public transit” in the past 24 hours
Earliest date available: 2020-09-08
C13 or C13b Wave 4, Sept 8, 2020
smoothed_wtravel_outside_state_7d Estimated percentage of respondents who report traveling outside their state in the past 7 days. This item was asked of respondents starting in Wave 10.
Earliest date available: 2021-03-02
C6a Wave 10
smoothed_wwork_outside_home_indoors_1d Estimated percentage of respondents who worked or went to school indoors and outside their home in the past 24 hours
Earliest date available: 2021-03-02
C13b Wave 10, Mar 2, 2021
smoothed_wshop_indoors_1d Estimated percentage of respondents who went to an “indoor market, grocery store, or pharmacy” in the past 24 hours
Earliest date available: 2021-03-02
C13b Wave 10, Mar 2, 2021
smoothed_wrestaurant_indoors_1d Estimated percentage of respondents who went to an indoor “bar, restaurant, or cafe” in the past 24 hours
Earliest date available: 2021-03-02
C13b Wave 10, Mar 2, 2021
smoothed_wspent_time_indoors_1d Estimated percentage of respondents who “spent time indoors with someone who isn’t currently staying with you” in the past 24 hours
Earliest date available: 2021-03-02
C13b Wave 10, Mar 2, 2021
smoothed_wlarge_event_indoors_1d Estimated percentage of respondents who “attended an indoor event with more than 10 people” in the past 24 hours
Earliest date available: 2021-03-02
C13b Wave 10, Mar 2, 2021
smoothed_wtravel_outside_state_5d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who report traveling outside their state in the past 5 days
Earliest date available: 2020-04-06
C6 Wave 1
smoothed_wwork_outside_home_1d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who worked or went to school outside their home in the past 24 hours
Earliest date available: 2020-09-08
C13 Wave 4, Sept 8, 2020
smoothed_wshop_1d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who went to a “market, grocery store, or pharmacy” in the past 24 hours
Earliest date available: 2020-09-08
C13 Wave 4, Sept 8, 2020
smoothed_wrestaurant_1d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who went to a “bar, restaurant, or cafe” in the past 24 hours
Earliest date available: 2020-09-08
C13 Wave 4, Sept 8, 2020
smoothed_wspent_time_1d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who “spent time with someone who isn’t currently staying with you” in the past 24 hours
Earliest date available: 2020-09-08
C13 Wave 4, Sept 8, 2020
smoothed_wlarge_event_1d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who “attended an event with more than 10 people” in the past 24 hours
Earliest date available: 2020-09-08
C13 Wave 4, Sept 8, 2020

### Schooling Indicators

Signal Description Survey Item
smoothed_winperson_school_fulltime Estimated percentage of people who had any children attending in-person school on a full-time basis, among people reporting any pre-K-grade 12 children in their household.
Earliest date available: 2020-11-24
E2
smoothed_winperson_school_parttime Estimated percentage of people who had any children attending in-person school on a part-time basis, among people reporting any pre-K-grade 12 children in their household.
Earliest date available: 2020-11-24
E2

## Testing Indicators

Signals beginning smoothed_w are adjusted using survey weights to be demographically representative as described below. Weighted signals have 1-2 days of lag, so if low latency is paramount, unweighted signals are also available. These begin smoothed_, such as smoothed_tested_14d instead of smoothed_wtested_14d.

Signal Description Survey Item
smoothed_wtested_14d Estimated percentage of people who were tested for COVID-19 in the past 14 days, regardless of their test result
Earliest date available: 2020-09-08
B8, B10
smoothed_wtested_positive_14d Estimated test positivity rate (percent) among people tested for COVID-19 in the past 14 days
Earliest date available: 2020-09-08
B10a or B10c
smoothed_wscreening_tested_positive_14d Estimated test positivity rate (percent) among people tested for COVID-19 in the past 14 days who were being screened with no symptoms or known exposure. Note: Until Wave 11 (May 19, 2021), this included people who said they were tested while receiving other medical care, because their employer or school required it, after attending a large outdoor gathering, or prior to visiting friends or family. After that date, this includes people who said they were tested while receiving other medical care, because their employer or school required it, prior to visiting friends or family, or prior to domestic or international travel.
Earliest date available: 2021-03-20
B10a or B10c, B10b
smoothed_whad_covid_ever Estimated percentage of people who report having ever had COVID-19.
Earliest date available: 2021-05-20
B13
smoothed_wwanted_test_14d Discontinued as of Wave 11, May 19, 2021 Estimated percentage of people who wanted to be tested for COVID-19 in the past 14 days, out of people who were not tested in that time
Earliest date available: 2020-09-08
B12

These indicators are based on questions in Wave 4 of the survey, introduced on September 8, 2020.

## Vaccination Indicators

Signals beginning smoothed_w are adjusted using survey weights to be demographically representative as described below. Weighted signals have 1-2 days of lag, so if low latency is paramount, unweighted signals are also available. These begin smoothed_, such as smoothed_covid_vaccinated instead of smoothed_wcovid_vaccinated.

### Vaccine Uptake and Acceptance

Signal Description Survey Item
smoothed_wcovid_vaccinated_appointment_or_accept Estimated percentage of respondents who either have already received a COVID vaccine or have an appointment to get a COVID vaccine or would definitely or probably choose to get vaccinated, if a vaccine were offered to them today.
Earliest date available: 2021-05-19
V1, V11a, V3a
smoothed_wcovid_vaccinated_or_accept Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who either have already received a COVID vaccine or would definitely or probably choose to get vaccinated, if a vaccine were offered to them today.
Earliest date available: 2021-01-06
V1 and V3
smoothed_wappointment_or_accept_covid_vaccine Estimated percentage of respondents who either have an appointment to get a COVID-19 vaccine or would definitely or probably choose to get vaccinated, if a vaccine were offered to them today, among respondents who have not yet been vaccinated.
Earliest date available: 2021-05-19
V11a, V3a
smoothed_waccept_covid_vaccine_no_appointment Estimated percentage of respondents who would definitely or probably choose to get vaccinated, if a vaccine were offered to them today, among respondents who have not yet been vaccinated and do not have an appointment to do so.
Earliest date available: 2021-05-19
V3a
smoothed_wvaccinate_children Estimated percentage of respondents with children who report that they will definitely or probably get the vaccine for their children.
Earliest date available: 2021-06-10
E4
smoothed_waccept_covid_vaccine Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who would definitely or probably choose to get vaccinated, if a COVID-19 vaccine were offered to them today. Note: Until January 6, 2021, all respondents answered this question; beginning on that date, only respondents who said they have not received a COVID vaccine are asked this question.
Earliest date available: 2021-01-01
V3
smoothed_wcovid_vaccinated Estimated percentage of respondents who have already received a vaccine for COVID-19. Note: The Centers for Disease Control compiles data on vaccine administration across the United States. This signal may differ from CDC data because of survey biases and should not be treated as authoritative. However, the survey signal is not subject to the lags and reporting problems in official vaccination data.
Earliest date available: 2021-01-06
V1
smoothed_wappointment_not_vaccinated Estimated percentage of respondents who have an appointment to get a COVID-19 vaccine, among respondents who have not yet been vaccinated.
Earliest date available: 2021-05-19
V11a
smoothed_wreceived_2_vaccine_doses Estimated percentage of respondents who have received two doses of a COVID-19 vaccine, among respondents who have received either one or two doses of a COVID-19 vaccine. This item was shown to respondents starting in Wave 7.
Earliest date available: 2021-02-06
V2
smoothed_wcovid_vaccinated_friends Estimated percentage of respondents who report that most of their friends and family have received a COVID-19 vaccine.
Earliest date available: 2021-05-20
H3
smoothed_wtry_vaccinate_1m Estimated percentage of respondents who report that they will try to get the COVID-19 vaccine within a week to a month, among unvaccinated respondents who do not have a vaccination appointment and who are uncertain about getting vaccinated (i.e. did not say they definitely would get vaccinated, nor that they definitely would not).
Earliest date available: 2021-06-10
V16

### Barriers to Accessing Vaccination

Signal Description Survey Item
smoothed_wvaccine_barrier_eligible Estimated percentage of respondents who report eligibility requirements as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_no_appointments Estimated percentage of respondents who report lack of vaccine or vaccine appointments as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_appointment_time Estimated percentage of respondents who report available appointment times as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_technical_difficulties Estimated percentage of respondents who report technical difficulties with the website or phone line as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_document Estimated percentage of respondents who report inability to provide required documents as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_technology_access Estimated percentage of respondents who report limited access to internet or phone as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_travel Estimated percentage of respondents who report difficulty traveling to vaccination sites as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_language Estimated percentage of respondents who report information not being available in their native language as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_childcare Estimated percentage of respondents who report lack of childcare as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_time Estimated percentage of respondents who report difficulty getting time away from work or school as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_type Estimated percentage of respondents who report available vaccine type as a barrier to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_none Estimated percentage of respondents who report experiencing none of the listed barriers to getting the vaccine, among those who have already been vaccinated or have tried to get vaccinated.
Earliest date available: 2021-06-10
V15a and V15b
smoothed_wvaccine_barrier_eligible_has Estimated percentage of respondents who report eligibility requirements as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_no_appointments_has Estimated percentage of respondents who report lack of vaccine or vaccine appointments as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_appointment_time_has Estimated percentage of respondents who report available appointment times as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_technical_difficulties_has Estimated percentage of respondents who report technical difficulties with the website or phone line as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_document_has Estimated percentage of respondents who report inability to provide required documents as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_technology_access_has Estimated percentage of respondents who report limited access to internet or phone as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_travel_has Estimated percentage of respondents who report difficulty traveling to vaccination sites as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_language_has Estimated percentage of respondents who report information not being available in their native language as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_childcare_has Estimated percentage of respondents who report lack of childcare as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_time_has Estimated percentage of respondents who report difficulty getting time away from work or school as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_type_has Estimated percentage of respondents who report available vaccine type as a barrier to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_none_has Estimated percentage of respondents who report experiencing none of the listed barriers to getting the vaccine, among those who have already been vaccinated.
Earliest date available: 2021-05-20
V15a
smoothed_wvaccine_barrier_eligible_tried Estimated percentage of respondents who report eligibility requirements as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_no_appointments_tried Estimated percentage of respondents who report lack of vaccine or vaccine appointments as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_appointment_time_tried Estimated percentage of respondents who report available appointment times as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_technical_difficulties_tried Estimated percentage of respondents who report technical difficulties with the website or phone line as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_document_tried Estimated percentage of respondents who report inability to provide required documents as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_technology_access_tried Estimated percentage of respondents who report limited access to internet or phone as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_travel_tried Estimated percentage of respondents who report difficulty traveling to vaccination sites as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_language_tried Estimated percentage of respondents who report information not being available in their native language as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_childcare_tried Estimated percentage of respondents who report lack of childcare as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_time_tried Estimated percentage of respondents who report difficulty getting time away from work or school as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_type_tried Estimated percentage of respondents who report available vaccine type as a barrier to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b
smoothed_wvaccine_barrier_none_tried Estimated percentage of respondents who report experiencing none of the listed barriers to getting the vaccine, among those who have tried to get vaccinated.
Earliest date available: 2021-05-20
V15b

### Reasons for Vaccine Hesitancy

Signal Description Survey Item
smoothed_wworried_vaccine_side_effects Estimated percentage of respondents who are very or moderately concerned that they would “experience a side effect from a COVID-19 vaccination.” Note: Until March 2, 2021, all respondents answered this question, including those who had already received one or more doses of a COVID-19 vaccine; beginning on that date, only respondents who said they have not received a COVID vaccine are asked this question.
Earliest date available: 2021-01-12
V9
smoothed_whesitancy_reason_sideeffects Estimated percentage of respondents who say they are hesitant to get vaccinated because they are worried about side effects, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_allergic Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who say they are hesitant to get vaccinated because they are worried about having an allergic reaction, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_ineffective Estimated percentage of respondents who say they are hesitant to get vaccinated because they don’t know if a COVID-19 vaccine will work, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_unnecessary Estimated percentage of respondents who say they are hesitant to get vaccinated because they don’t believe they need a COVID-19 vaccine, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_dislike_vaccines Estimated percentage of respondents who say they are hesitant to get vaccinated because they dislike vaccines, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_not_recommended Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who say they are hesitant to get vaccinated because their doctor did not recommend it, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_wait_safety Estimated percentage of respondents who say they are hesitant to get vaccinated because they want to wait to see if the COVID-19 vaccines are safe, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_low_priority Estimated percentage of respondents who say they are hesitant to get vaccinated because they think other people need it more than they do, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_cost Estimated percentage of respondents who say they are hesitant to get vaccinated because they are worried about the cost, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_distrust_vaccines Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who say they are hesitant to get vaccinated because they don’t trust COVID-19 vaccines, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_distrust_gov Estimated percentage of respondents who say they are hesitant to get vaccinated because they don’t trust the government, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_health_condition Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who say they are hesitant to get vaccinated because they have a health condition that may impact the safety of a COVID-19 vaccine, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_pregnant Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who say they are hesitant to get vaccinated because they are pregnant or breastfeeding, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_religious Estimated percentage of respondents who say they are hesitant to get vaccinated because it is against their religious beliefs, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc
smoothed_whesitancy_reason_other Estimated percentage of respondents who say they are hesitant to get vaccinated for another reason, among respondents who answered “Yes, probably”, “No, probably not”, or “No, definitely not” when asked if they would get vaccinated if offered (item V3). This series of items was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-26
V5abc

### Reasons for Believing Vaccine is Unnecessary

Respondents who indicate that “I don’t believe I need a COVID-19 vaccine” (in items V5a, V5b, V5c, or, prior to Wave 11, V5d) are asked a follow-up item asking why they don’t believe they need the vaccine. These signals summarize the reasons selected. Respondents who do not select any reason (including “Other”) are treated as missing.

Note: Item V5d was removed in Wave 11, thus these indicators no longer include respondents who indicate in V5d that “I don’t believe I need a COVID-19 vaccine”. Item V5d was shown to those who received one dose of a COVID-19 vaccine, but are not planning to get all recommended doses.

Signal Description Survey Item
smoothed_wdontneed_reason_had_covid Estimated percentage of respondents who say they don’t need to get a COVID-19 vaccine because they already had the illness, among respondents who provided at least one reason for why they believe a COVID-19 vaccine is unnecessary.
Earliest date available: 2021-03-12
V6
smoothed_wdontneed_reason_dont_spend_time Estimated percentage of respondents who say they don’t need to get a COVID-19 vaccine because they don’t spend time with high-risk people, among respondents who provided at least one reason for why they believe a COVID-19 vaccine is unnecessary.
Earliest date available: 2021-03-12
V6
smoothed_wdontneed_reason_not_high_risk Estimated percentage of respondents who say they don’t need to get a COVID-19 vaccine because they are not in a high-risk group, among respondents who provided at least one reason for why they believe a COVID-19 vaccine is unnecessary.
Earliest date available: 2021-03-12
V6
smoothed_wdontneed_reason_precautions Estimated percentage of respondents who say they don’t need to get a COVID-19 vaccine because they will use other precautions, such as a mask, instead, among respondents who provided at least one reason for why they believe a COVID-19 vaccine is unnecessary.
Earliest date available: 2021-03-12
V6
smoothed_wdontneed_reason_not_serious Estimated percentage of respondents who say they don’t need to get a COVID-19 vaccine because they don’t believe COVID-19 is a serious illness, among respondents who provided at least one reason for why they believe a COVID-19 vaccine is unnecessary.
Earliest date available: 2021-03-12
V6
smoothed_wdontneed_reason_not_beneficial Estimated percentage of respondents who say they don’t need to get a COVID-19 vaccine because they don’t think vaccines are beneficial, among respondents who provided at least one reason for why they believe a COVID-19 vaccine is unnecessary.
Earliest date available: 2021-03-12
V6
smoothed_wdontneed_reason_other Estimated percentage of respondents who say they don’t need to get a COVID-19 vaccine for another reason, among respondents who provided at least one reason for why they believe a COVID-19 vaccine is unnecessary.
Earliest date available: 2021-03-12
V6

### Outreach and Image

Signal Description Survey Item
smoothed_wvaccine_likely_friends Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who would be more likely to get a COVID-19 vaccine if it were recommended to them by friends and family, among respondents who have not yet been vaccinated.
Earliest date available: 2021-01-20
V4
smoothed_wvaccine_likely_local_health Discontinued as of Wave 8, Feb 8, 2021 Estimated percentage of respondents who would be more likely to get a COVID-19 vaccine if it were recommended to them by local health workers, among respondents who have not yet been vaccinated.
Earliest date available: 2021-01-20
V4
smoothed_wvaccine_likely_who Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who would be more likely to get a COVID-19 vaccine if it were recommended to them by the World Health Organization, among respondents who have not yet been vaccinated.
Earliest date available: 2021-01-20
V4
smoothed_wvaccine_likely_govt_health Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who would be more likely to get a COVID-19 vaccine if it were recommended to them by government health officials, among respondents who have not yet been vaccinated.
Earliest date available: 2021-01-20
V4
smoothed_wvaccine_likely_politicians Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who would be more likely to get a COVID-19 vaccine if it were recommended to them by politicians, among respondents who have not yet been vaccinated.
Earliest date available: 2021-01-20
V4
smoothed_wvaccine_likely_doctors Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who would be more likely to get a COVID-19 vaccine if it were recommended to them by doctors and other health professionals they go to for medical care, among respondents who have not yet been vaccinated. This item was shown to respondents starting in Wave 8.
Earliest date available: 2021-02-08
V4

The “vaccine_likely_*” indicators are based on questions added in Wave 6 of the survey, introduced on December 19, 2020; however, Delphi only enabled item V1 beginning January 6, 2021.

## Mental Health Indicators

Signals beginning smoothed_w are adjusted using survey weights to be demographically representative as described below. Weighted signals have 1-2 days of lag, so if low latency is paramount, unweighted signals are also available. These begin smoothed_, such as smoothed_anxious_5d instead of smoothed_wanxious_5d.

Signal Description Survey Item
smoothed_wworried_finances Estimated percentage of respondents who report being very or somewhat worried about their “household’s finances for the next month”
Earliest date available: 2020-09-08
C15
smoothed_wanxious_7d Estimated percentage of respondents who reported feeling “nervous, anxious, or on edge” for most or all of the past 7 days. This item was shown to respondents starting in Wave 10.
Earliest date available: 2021-03-02
C8a or C18a
smoothed_wdepressed_7d Estimated percentage of respondents who reported feeling depressed for most or all of the past 7 days. This item was shown to respondents starting in Wave 10.
Earliest date available: 2021-03-02
C8a or C18b
smoothed_wworried_catch_covid Estimated percentage of respondents worrying either a great deal or a moderate amount about catching COVID-19.
Earliest date available: 2021-05-20
G1
smoothed_wfelt_isolated_7d Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who reported feeling “isolated from others” for most or all of the past 7 days. This item was shown to respondents starting in Wave 10.
Earliest date available: 2021-03-02
C8a
smoothed_wanxious_5d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who reported feeling “nervous, anxious, or on edge” for most or all of the past 5 days
Earliest date available: 2020-09-08
C8
smoothed_wdepressed_5d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who reported feeling depressed for most or all of the past 5 days
Earliest date available: 2020-09-08
C8
smoothed_wfelt_isolated_5d Discontinued as of Wave 10, Mar 2, 2021 Estimated percentage of respondents who reported feeling “isolated from others” for most or all of the past 5 days
Earliest date available: 2020-09-08
C8
smoothed_wworried_become_ill Discontinued as of Wave 11, May 19, 2021 Estimated percentage of respondents who reported feeling very or somewhat worried that “you or someone in your immediate family might become seriously ill from COVID-19”
Earliest date available: 2020-09-08
C9

Some of these questions were present in the earliest waves of the survey, but only in Wave 4 did respondents consent to our use of aggregate data to study other impacts of COVID, such as mental health. Hence, these aggregates only include respondents to Wave 4 and later waves, beginning September 8, 2020.

## Belief, Experience, and Information Indicators

Signals beginning smoothed_w are adjusted using survey weights to be demographically representative as described below. Weighted signals have 1-2 days of lag, so if low latency is paramount, unweighted signals are also available. These begin smoothed_, such as smoothed_belief_children_immune instead of smoothed_wbelief_children_immune.

Signal Description Survey Item Introduced
smoothed_wbelief_masking_effective Estimated percentage of respondents who believe that wearing a face mask is either very or moderately effective for preventing the spread of COVID-19.
Earliest date available: 2021-06-10
G3 Wave 11, May 19, 2021
smoothed_wbelief_distancing_effective Estimated percentage of respondents who believe that social distancing is either very or moderately effective for preventing the spread of COVID-19.
Earliest date available: 2021-05-20
G2 Wave 11, May 19, 2021
smoothed_wbelief_vaccinated_mask_unnecessary Estimated percentage of people who believe that the statement “Getting the COVID-19 vaccine means that you can stop wearing a mask around people outside your household” is definitely or probably true.
Earliest date available: 2021-05-20
I1 Wave 11, May 19, 2021
smoothed_wbelief_children_immune Estimated pPercentage of people who believe that the statement “Children cannot get COVID-19” is definitely or probably true.
Earliest date available: 2021-05-20
I2 Wave 11, May 19, 2021
smoothed_wbelief_created_small_group Estimated percentage of people who believe that the statement “COVID-19 was deliberately created by a small group of people who secretly manipulate world events” is definitely or probably true.
Earliest date available: 2021-05-20
I3 Wave 11, May 19, 2021
smoothed_wbelief_govt_exploitation Estimated percentage of people who indicate that the statement “The COVID-19 pandemic is being exploited by the government to control people” is definitely or probably true.
Earliest date available: 2021-05-20
I4 Wave 11, May 19, 2021

### Medical Care Experiences

Signal Description Survey Item Introduced
smoothed_wdelayed_care_cost Estimated percentage of respondents who have ever delayed or not sought medical care in the past year because of cost.
Earliest date available: 2021-05-20
K1 Wave 11, May 19, 2021
smoothed_wrace_treated_fairly_healthcare Estimated percentage of respondents who somewhat or strongly agree that people of their race are treated fairly in a healthcare setting.
Earliest date available: 2021-05-20
K2 Wave 11, May 19, 2021

### Sources of News

Signal Description Survey Item Introduced
smoothed_wreceived_news_local_health Estimated percentage of respondents who received news about COVID-19 from local health workers, clinics, and community organizations in the past 7 days.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021
smoothed_wreceived_news_experts Estimated percentage of respondents who received news about COVID-19 from scientists and other health experts in the past 7 days.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021
smoothed_wreceived_news_cdc Estimated percentage of respondents who received news about COVID-19 from the CDC in the past 7 days.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021
smoothed_wreceived_news_govt_health Estimated percentage of respondents who received news about COVID-19 from government health authorities or officials in the past 7 days.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021
smoothed_wreceived_news_politicians Estimated percentage of respondents who received news about COVID-19 from politicians in the past 7 days.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021
smoothed_wreceived_news_journalists Estimated percentage of respondents who received news about COVID-19 from journalists in the past 7 days.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021
smoothed_wreceived_news_friends Estimated percentage of respondents who received news about COVID-19 from friends and family in the past 7 days.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021
smoothed_wreceived_news_religious Estimated percentage of respondents who received news about COVID-19 from religious leaders in the past 7 days.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021
smoothed_wreceived_news_none Estimated percentage of respondents who in the past 7 days received news about COVID-19 from none of the listed sources.
Earliest date available: 2021-05-20
I5 Wave 11, May 19, 2021

### Trusted Sources of Information

Signal Description Survey Item
smoothed_wtrust_covid_info_doctors Estimated percentage of respondents who trust doctors and other health professionals they go to for medical care to provide accurate news and information about COVID-19.
Earliest date available: 2021-05-19
I6
smoothed_wtrust_covid_info_experts Estimated percentage of respondents who trust scientists and other health experts to provide accurate news and information about COVID-19.
Earliest date available: 2021-05-19
I6
smoothed_wtrust_covid_info_cdc Estimated percentage of respondents who trust the Centers for Disease Control (CDC) to provide accurate news and information about COVID-19.
Earliest date available: 2021-05-19
I6
smoothed_wtrust_covid_info_govt_health Estimated percentage of respondents who trust government health officials to provide accurate news and information about COVID-19.
Earliest date available: 2021-05-19
I6
smoothed_wtrust_covid_info_politicians Estimated percentage of respondents who trust politicians to provide accurate news and information about COVID-19.
Earliest date available: 2021-05-19
I6
smoothed_wtrust_covid_info_journalists Estimated percentage of respondents who trust journalists to provide accurate news and information about COVID-19.
Earliest date available: 2021-05-19
I6
smoothed_wtrust_covid_info_friends Estimated percentage of respondents who trust friends and family to provide accurate news and information about COVID-19.
Earliest date available: 2021-05-19
I6
smoothed_wtrust_covid_info_religious Estimated percentage of respondents who trust religious leaders to provide accurate news and information about COVID-19.
Earliest date available: 2021-05-19
I6

### Desired Information

Signal Description Survey Item Introduced
smoothed_wwant_info_covid_treatment Estimated percentage of people who want more information about the treatment of COVID-19.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021
smoothed_wwant_info_vaccine_access Estimated percentage of people who want more information about how to get a COVID-19 vaccine.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021
smoothed_wwant_info_vaccine_types Estimated percentage of people who want more information about different types of COVID-19 vaccines.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021
smoothed_wwant_info_covid_variants Estimated percentage of people who want more information about COVID-19 variants and mutations.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021
smoothed_wwant_info_children_education Estimated percentage of people who want more information about how to support their children’s education.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021
smoothed_wwant_info_mental_health Estimated percentage of people who want more information about how to maintain their mental health.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021
smoothed_wwant_info_relationships Estimated percentage of people who want more information about how to maintain their social relationships despite physical distancing.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021
smoothed_wwant_info_employment Estimated percentage of people who want more information about employment and other economic and financial issues.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021
smoothed_wwant_info_none Estimated percentage of people who want more information about none of the listed topics.
Earliest date available: 2021-05-20
I7 Wave 11, May 19, 2021

## Limitations

When interpreting the signals above, it is important to keep in mind several limitations of this survey data.

• Survey population. People are eligible to participate in the survey if they are age 18 or older, they are currently located in the USA, and they are an active user of Facebook. The survey data does not report on children under age 18, and the Facebook adult user population may differ from the United States population generally in important ways. We use our survey weighting to adjust the estimates to match age and gender demographics by state, but this process doesn’t adjust for other demographic biases we may not be aware of.
• Non-response bias. The survey is voluntary, and people who accept the invitation when it is presented to them on Facebook may be different from those who do not. The survey weights provided by Facebook attempt to model the probability of response for each user and hence adjust for this, but it is difficult to tell if these weights account for all possible non-response bias.
• Social desirability. Previous survey research has shown that people’s responses to surveys are often biased by what responses they believe are socially desirable or acceptable. For example, if it there is widespread pressure to wear masks, respondents who do not wear masks may feel pressured to answer that they do. This survey is anonymous and online, meaning we expect the social desirability effect to be smaller, but it may still be present.
• False responses. As with anything on the Internet, a small percentage of users give deliberately incorrect responses. We discard a small number of responses that are obviously false, but do not perform extensive filtering. However, the large size of the study, and our procedure for ensuring that each respondent can only be counted once when they are invited to take the survey, prevents individual respondents from having a large effect on results.
• Repeat invitations. Individual respondents can be invited by Facebook to take the survey several times. Usually Facebook only re-invites a respondent after one month. Hence estimates of values on a single day are calculated using independent survey responses from unique respondents (or, at least, unique Facebook accounts), whereas estimates from different months may involve the same respondents.

Whenever possible, you should compare this data to other independent sources. We believe that while these biases may affect point estimates – that is, they may bias estimates on a specific day up or down – the biases should not change strongly over time. This means that changes in signals, such as increases or decreases, are likely to represent true changes in the underlying population, even if point estimates are biased.

### Privacy Restrictions

To protect respondent privacy, we discard any estimate (whether at a county, MSA, HRR, or state level) that is based on fewer than 100 survey responses. For signals reported using a 7-day average (those beginning with smoothed_), this means a geographic area must have at least 100 responses in 7 days to be reported.

This affects some items more than others. For instance, items about vaccine hesitancy reasons are only asked of respondents who are unvaccinated and hesitant, not to all survey respondents. It also affects some geographic areas more than others, particularly rural areas with low population densities. When doing analysis of county-level data, one should be aware that missing counties are typically more rural and less populous than those present in the data, which may introduce bias into the analysis.

### Declining Response Rate

We have noted a steady decrease in the number of daily survey responses, beginning no later than January 2021. As the number of survey responses declines, some indicators will become unavailable once they no longer meet the privacy limit for sample size. This affects some signals, such as those based on a subset of responses, more than others, with finer geographic resolutions becoming unavailable first.

### Target Region

Facebook only invites users to take the survey if they appear, based on attributes in their Facebook profiles, to reside in the 50 states or Washington, DC. Puerto Rico is sampled separately as part of the international version of the survey. If Facebook believes a user qualifies for the survey, but the user then replies that they live in Puerto Rico or another US territory, we do not include their response in the aggregations.

## Survey Weighting and Estimation

When Facebook sends a user to our survey, it generates a random ID number and sends this to us as well. Once the user completes the survey, we pass this ID number back to Facebook to confirm completion, and in return receive a weight. (The random ID number is completely meaningless for any other purpose than receiving this weight, and does not allow us to access any information about the user’s Facebook profile. Nor does it provide Facebook any information about the survey responses.)

We can use these weights to adjust our estimates so that they are representative of the US population—adjusting both for the differences between the US population and US Facebook users (according to a state-by-age-gender stratification of the US population from the 2018 Census March Supplement) and for the propensity of a Facebook user to take our survey in the first place.

In more detail, we receive a participation weight

$w^{\text{part}}_i \propto \frac{1}{\pi_i},$

where $$\pi_i$$ is an estimated probability (produced by Facebook) that an individual with the same state-by-age-gender profile as user $$i$$ would be a Facebook user and take our survey. The adjustment we make follows a standard inverse probability weighting strategy.

Detailed documentation on how Facebook calculates these weights is available in our survey weight documentation.

For unweighted survey signals, we set $$w^\text{part}_i = 1$$ for all respondents.

### Geographic Weighting and Mixing

Besides the participation weight $$w^\text{part}_i$$, each survey response receives a geographical-division weight $$w^{\text{geodiv}}_i$$ describing how much a participant’s ZIP code “belongs” in the spatial unit of interest. For example, a ZIP code may overlap with multiple counties, so the weight describes what proportion of the ZIP code’s population is in each county.

Each survey’s weight is hence $$w^{\text{init}}_i = w^{\text{part}}_i w^{\text{geodiv}}_i$$. When a ZIP code spans multiple counties or states, a single survey may have different weights when used to calculate different geographic aggregates.

### Adjusting Household ILI and CLI

For a given aggregation unit (for example, daily-county), let $$X_i$$ and $$Y_i$$ denote the numbers of ILI and CLI cases in household $$i$$, respectively (computed according to the simple strategy above), and let $$N_i$$ denote the total number of people in the household. Let $$i = 1, \dots, m$$ denote the surveys started during the time period of interest and reported in a ZIP code intersecting the spatial unit of interest.

First, we adjust the initial weights $$w^\text{init}$$ to reduce sensitivity to any individual survey by “mixing” them with a uniform weighting across all relevant surveys. This prevents specific survey respondents with high survey weights having disproportionate influence on the weighted estimates.

Specifically, we select the smallest value of $$a \in [0.05, 1]$$ such that

$w_i = a\cdot\frac1m + (1-a)\cdot w^{\text{init}}_i \leq 0.01$

for all $$i$$. If such a selection is impossible, then we have insufficient survey responses (less than 100), and do not produce an estimate for the given aggregation unit.

Next, we rescale the weights $$w_i$$ over all $$i$$ so that $$\sum_{i=1}^m w_i=1$$. Then our adjusted estimates of $$p$$ and $$q$$ are:

\begin{aligned} \hat{p}_w &= 100 \cdot \sum_{i=1}^m w_i \frac{X_i}{N_i} \\ \hat{q}_w &= 100 \cdot \sum_{i=1}^m w_i \frac{Y_i}{N_i}, \end{aligned}

with estimated standard errors:

\begin{aligned} \widehat{\mathrm{se}}(\hat{p}_w) &= 100 \cdot \frac{1}{1 + n_e} \sqrt{ \left(\frac12 - \frac{\hat{p}_w}{100}\right)^2 + n_e^2 \hat{s}_p^2 }\\ \widehat{\mathrm{se}}(\hat{q}_w) &= 100 \cdot \frac{1}{1 + n_e} \sqrt{ \left(\frac12 - \frac{\hat{q}_w}{100}\right)^2 + n_e^2 \hat{s}_q^2 }, \end{aligned}

where

\begin{aligned} \hat{s}_p^2 &= \sum_{i=1}^m w_i^2 \left(\frac{X_i}{N_i} - \frac{\hat{p}_w}{100}\right)^2 \\ \hat{s}_q^2 &= \sum_{i=1}^m w_i^2 \left(\frac{Y_i}{N_i} - \frac{\hat{q}_w}{100}\right)^2 \\ n_e &= \frac1{\sum_{i=1}^m w_i^2}, \end{aligned}

which are the delta method estimates of variance associated with self-normalized importance sampling estimators above, after combining with a pseudo-observation of 1/2 with weight $$1/n_e$$, assigned to appear like a single effective observation. The use of the pseudo-observation prevents standard error estimates of zero, and in simulations improves the quality of the standard error estimates. See the Appendix for further motivation for these estimators.

The pseudo-observation is not used in $$\hat{p}$$ and $$\hat{q}$$ themselves, to avoid potentially large amounts of estimation bias, as $$p$$ and $$q$$ are expected to be small.

The sample size reported is calculated by rounding down $$\sum_{i=1}^{m} w^{\text{geodiv}}_i$$ before adding the pseudo-observations. When ZIP codes do not overlap multiple spatial units of interest, these weights are all one, and this expression simplifies to $$m$$. When estimates are available for all spatial units of a given type over some time period, the sum of the associated sample sizes under this definition is consistent with the number of surveys used to prepare the estimate. (This notion of sample size is distinct from “effective” sample sizes based on variance of the importance sampling estimators which were used above.)

The household ILI and CLI estimates are complex to weight, as shown in the previous subsection, because they use an estimator based on the survey respondent and their household. All other estimates reported in the API are simply based on percentages of respondents, such as the percentage who report knowing someone in their community who is sick. In this subsection we will describe how survey weights are used to construct weighted estimates for these indicators, using community CLI as an example.

In a given aggregation unit (for example, daily-county), let $$U_i$$ the indicator that the survey respondent knows someone in their community with CLI, including their household, for survey $$i$$, out of $$m$$ surveys collected. Also let $$w_i$$ be the weight that accompanies survey $$i$$, normalized to sum to 1 as above. Then our initial weighted estimate of the population proportion $$a$$ is:

$\hat{a}_{w, \text{init}} = 100 \cdot \sum_{i=1}^m w_i U_i$

To prevent observations and standard errors from being zero, we add a pseudo-observation of 1/2 with weight $$1/n_e$$. (This psuedo-observation can be thought of as equivalent to using a Bayesian estimate of the proportion, with a Jeffreys prior.) The estimate is hence:

$\hat{a}_w = 100 \cdot \frac{n_e \frac{\hat{a}_{w, \text{init}}}{100} + \frac12}{1 + n_e},$

with estimated standard error:

$\widehat{\mathrm{se}}(\hat{a}_w) = 100 \cdot \sqrt{\frac{\frac{\hat{a}_w}{100}(1-\frac{\hat{a}_w}{100})}{1 + n_e}}$

which is the plug-in estimate of the standard error of the binomial proportion.

## Appendix

Here are some details behind the choice of estimators for percent ILI and percent CLI.

Suppose there are $$h$$ households total in the underlying population, and for household $$i$$, denote $$\theta_i=N_i/n$$. Then note that the quantities of interest, $$p$$ and $$q$$, are

$p = \sum_{i=1}^h \frac{X_i}{N_i} \theta_i \quad\text{and}\quad q = \sum_{i=1}^h \frac{Y_i}{N_i} \theta_i.$

Let $$S \subseteq \{1,\dots,h\}$$ denote sampled households, with $$m=|S|$$, and suppose we sampled household $$i$$ with probability $$\theta_i=N_i/n$$ proportional to the household size. Then unbiased estimates of $$p$$ and $$q$$ are simply

$\hat{p} = \frac{1}{m} \sum_{i \in S} \frac{X_i}{N_i} \quad\text{and}\quad \hat{q} = \frac{1}{m} \sum_{i \in S} \frac{Y_i}{N_i},$

which are an equivalent way of writing our previously-defined estimates.

Note that we can again rewrite our quantities of interest as

$p = \frac{\mu_x}{\mu_n} \quad\text{and}\quad q = \frac{\mu_y}{\mu_n},$

where $$\mu_x=x/h$$, $$\mu_y=y/h$$, $$\mu_n=n/h$$ denote the expected number people with ILI per household, expected number of people with CLI per household, and expected number of people total per household, respectively, and $$h$$ denotes the total number of households in the population.

Suppose that instead of proportional sampling, we sampled households uniformly, resulting in $$S \subseteq \{1,\dots,h\}$$ denote sampled households, with $$m=|S|$$. Then the natural estimates of $$p$$ and $$q$$ are instead plug-in estimates of the numerators and denominators in the above,

$\tilde{p} = \frac{\bar{X}}{\bar{N}} \quad\text{and}\quad \tilde{q} = \frac{\bar{X}}{\bar{N}}$

where $$\bar{X}=\sum_{i \in S} X_i/m$$, $$\bar{Y}=\sum_{i \in S} Y_i/m$$, and $$\bar{N}=\sum_{i \in S} N_i/m$$ denote the sample means of $$\{X_i\}_{i \in S}$$, $$\{Y_i\}_{i \in S}$$, and $$\{N_i\}_{i \in S}$$, respectively.

Whether we consider $$\hat{p}$$ and $$\hat{q}$$, or $$\tilde{p}$$ and $$\tilde{q}$$, to be more natural—mean of fractions, or fraction of means, respectively—depends on the sampling model: if we are sampling households proportional to household size, then it is $$\hat{p}$$ and $$\hat{q}$$; if we are sampling households uniformly, then it is $$\tilde{p}$$ and $$\tilde{q}$$. We settled on the former, based on both conceptual and empirical supporting evidence:

• Conceptually, though we do not know the details, we have reason to believe that Facebook offers an essentially uniform random draw of eligible users—those 18 years or older—to take our survey. In this sense, the sampling is done proportional to the number of “Facebook adults” in a household: individuals 18 years or older, who have a Facebook account. Hence if we posit that the number of “Facebook adults” scales linearly with the household size, which seems to us like a reasonable assumption, then sampling would still be proportional to household size. (Notice that this would remain true no matter how small the linear coefficient is, that is, it would even be true if Facebook did not have good coverage over the US.)

• Empirically, we have computed the distribution of household sizes (proportion of households of size 1, size 2, size 3, etc.) in the Facebook survey data thus far, and compared it to the distribution of household sizes from the Census. These align quite closely, also suggesting that sampling is likely done proportional to household size.