• Source name: google-symptoms
• Earliest issue available: November 30, 2020
• Number of data revisions since May 19, 2020: 1
• Date of last change: January 20, 2022
• Available for: county, MSA, HRR, state, HHS, nation (see geography coding docs)
• Time type: day (see date format docs)

Overview

This data source is based on the COVID-19 Search Trends symptoms dataset. Using this search data, we estimate the volume of searches mapped to symptom sets related to COVID-19. The resulting daily dataset for each region shows the average relative frequency of searches for each symptom set. The signals are measured in arbitrary units that are normalized for overall search users in the region and scaled by the maximum value of the normalized popularity within a geographic region across a specific time range. Values are comparable across signals in the same location but NOT across geographic regions. For example, within a state, we can compare s01_smoothed_search and s02_smoothed_search. However, we cannot compare s01_smoothed_search between states. Larger numbers represent increased relative popularity of symptom-related searches.

Symptom sets

• s01: Cough, Phlegm, Sputum, Upper respiratory tract infection
• s02: Nasal congestion, Post nasal drip, Rhinorrhea, Sinusitis, Rhinitis, Common cold
• s03: Fever, Hyperthermia, Chills, Shivering, Low grade fever
• s04: Shortness of breath, Wheeze, Croup, Pneumonia, Asthma, Crackles, Acute bronchitis, Bronchitis
• s05: Anosmia, Dysgeusia, Ageusia
• s06: Laryngitis, Sore throat, Throat irritation
• scontrol: Type 2 diabetes, Urinary tract infection, Hair loss, Candidiasis, Weight gain

The symptoms were combined in sets that showed positive correlation with cases, especially after Omicron was declared a variant of concern by the WHO. Note that symptoms in scontrol are not COVID-19 related, and this symptom set can be used as a negative control.

Until January 20, 2022, we had separate signals for symptoms Anosmia, Ageusia, and their sum.

Signal Description
s01_raw_search The average of Google search volume for related searches of symptom set s01, in an arbitrary units that are normalized for overall search users.
Earliest date available: 2020-01-01
s01_smoothed_search The average of Google search volume for related searches of symptom set s01, in an arbitrary units that are normalized for overall search users, smoothed by 7-day average.
Earliest date available: 2020-01-07
s02_raw_search The average of Google search volume for related searches of symptom set s02, in an arbitrary units that are normalized for overall search users.
Earliest date available: 2020-01-01
s02_smoothed_search The average of Google search volume for related searches of symptom set s02, in an arbitrary units that are normalized for overall search users, smoothed by 7-day average.
Earliest date available: 2020-01-07
s03_raw_search The average of Google search volume for related searches of symptom set s03, in an arbitrary units that are normalized for overall search users.
Earliest date available: 2020-01-01
s03_smoothed_search The average of Google search volume for related searches of symptom set s03, in an arbitrary units that are normalized for overall search users, smoothed by 7-day average.
Earliest date available: 2020-01-07
s04_raw_search The average of Google search volume for related searches of symptom set s04, in an arbitrary units that are normalized for overall search users.
Earliest date available: 2020-01-01
s04_smoothed_search The average of Google search volume for related searches of symptom set s04, in an arbitrary units that are normalized for overall search users, smoothed by 7-day average.
Earliest date available: 2020-01-07
s05_raw_search The average of Google search volume for related searches of symptom set s05, in an arbitrary units that are normalized for overall search users.
Earliest date available: 2020-01-01
s05_smoothed_search The average of Google search volume for related searches of symptom set s05, in an arbitrary units that are normalized for overall search users, smoothed by 7-day average.
Earliest date available: 2020-01-07
s06_raw_search The average of Google search volume for related searches of symptom set s06, in an arbitrary units that are normalized for overall search users.
Earliest date available: 2020-01-01
s06_smoothed_search The average of Google search volume for related searches of symptom set s06, in an arbitrary units that are normalized for overall search users, smoothed by 7-day average.
Earliest date available: 2020-01-07
scontrol_raw_search The average of Google search volume for related searches of symptom set scontrol, in an arbitrary units that are normalized for overall search users.
Earliest date available: 2020-01-01
scontrol_smoothed_search The average of Google search volume for related searches of symptom set scontrol, in an arbitrary units that are normalized for overall search users, smoothed by 7-day average.
Earliest date available: 2020-02-20
anosmia_raw_search Google search volume for anosmia-related searches, in arbitrary units that are normalized for overall search users. This signal is no longer updated as of 20 January, 2022.
Earliest date available: 2020-02-13
anosmia_smoothed_search Google search volume for anosmia-related searches, in arbitrary units that are normalized for overall search users, smoothed by 7-day average. This signal is no longer updated as of 20 January, 2022.
Earliest date available: 2020-02-20
ageusia_raw_search Google search volume for ageusia-related searches, in arbitrary units that are normalized for overall search users. This signal is no longer updated as of 20 January, 2022.
Earliest date available: 2020-02-13
ageusia_smoothed_search Google search volume for ageusia-related searches, in arbitrary units that are normalized for overall search users, smoothed by 7-day average. This signal is no longer updated as of 20 January, 2022.
Earliest date available: 2020-02-20
sum_anosmia_ageusia_raw_search The sum of Google search volume for anosmia and ageusia related searches, in an arbitrary units that are normalized for overall search users. This signal is no longer updated as of 20 January, 2022.
Earliest date available: 2020-02-13
sum_anosmia_ageusia_smoothed_search The sum of Google search volume for anosmia and ageusia related searches, in an arbitrary units that are normalized for overall search users, smoothed by 7-day average. This signal is no longer updated as of 20 January, 2022.
Earliest date available: 2020-02-20

Estimation

Each signal is the average of the values of search trends for each symptom in the symptom set. For example, s05_raw_search is the average of the search trend values of anosmia, ageusia, and dysgeusia. Note that this is different from the union of anosmia, ageusia, and dysgeusia related searches divided by 3, because the data volume for each symptom is calculated based on search queries. A single search query can be mapped to more than one symptom. Currently, Google does not provide intersection/union data. Users should be careful when considering such signals.

For each symptom set: when search trends for all symptoms are missing, the signal is reported as missing. When search trends are available for at least one of the symptoms, we fill the missing trends for other symptoms with 0 and compute the average. We use this approach because the missing observations in the Google Symptoms search trends dataset do not occur randomly; they represent low popularity and are censored for quality and/or privacy reasons. The same approach is used for smoothed signals. A 7 day moving average is used, and missing raw signals are filled with 0 as long as there is at least one day available within the 7 day window.

Geographical Aggregation

The state-level and county-level raw_search signals for each symptoms set are the average of its individual symptoms search trends, taken directly from the COVID-19 Search Trends symptoms dataset.

We aggregate county and state data to other geographic levels using population-weighted averaging.

Source level Aggregated level
county MSA, HRR
state HHS, nation

For aggregation purposes only, we assign a value of 0 to source regions that have no data provided due to quality or privacy issues for a certain day (see Limitations for details). We do not report aggregated regions if none of their source regions have data. Because of this censoring behavior, the resulting data for aggregated regions does not fully match the actual search volume for these regions (which is not provided to us).

Lag and Backfill

Google does not currently update the search data daily, but usually twice a week. Each update will usually extend the coverage to within three days of the day of the update. As a result the delay can range from 3 to 10 days or even more. We check for updates every day and provide the most up-to-date data.

Limitations

When daily volume in a region does not meet quality or privacy thresholds, set by Google, no daily value is reported. Weekly data may be available from Google in these cases, but we do not yet support importation using weekly data.

Google uses differential privacy, which adds artificial noise to the raw datasets to avoid identifying any individual persons without affecting the quality of results.

Google normalizes and scales time series values to determine the relative popularity of symptoms in searches within each geographical region individually. This means that the resulting values of symptom set popularity are NOT comparable across geographic regions, while the values of different symptom sets are comparable within the same location.

Standard errors and sample sizes are not available for this data source.

More details about the limitations of this dataset are available in Google’s Search Trends symptoms dataset documentation.