The US COVID-19 Trends and Impact Survey Continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination
The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental...
Saved in:
Published in | Proceedings of the National Academy of Sciences - PNAS Vol. 118; no. 51; pp. 1 - 9 |
---|---|
Main Authors | , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
National Academy of Sciences
21.12.2021
|
Series | Beyond Cases and Deaths: The Benefits of Auxiliary Data Streams In Tracking the COVID-19 Pandemic |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey—over 20 million responses in its first year of operation—allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems. |
---|---|
AbstractList | The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey-over 20 million responses in its first year of operation-allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems. The US COVID-19 Trends and Impact Survey (CTIS) has operated continuously since April 6, 2020, collecting over 20 million responses. As the largest public health survey conducted in the United States to date, CTIS was designed to facilitate detailed demographic and geographic analyses, track trends over time, and accommodate rapid revision to address emerging priorities. Using examples of CTIS results illuminating trends in symptoms, risks, mitigating behaviors, testing, and vaccination in relation to evolving high-priority policy questions over 12 mo of the pandemic, we illustrate the value of online surveys for tracking patterns and trends in COVID outcomes as an adjunct to official reporting, and showcase unique insights that would not be visible through traditional public health reporting. The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey—over 20 million responses in its first year of operation—allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems. The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey-over 20 million responses in its first year of operation-allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems.The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey-over 20 million responses in its first year of operation-allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems. |
Author | Bilinski, Alyssa LaRocca, Sarah Rönn, Minttu M. Salomon, Joshua A. Farag, Tamer H. Chua, Eu Jing Reitsma, Marissa B. Reinhart, Alex Tibshirani, Ryan J. La Motte-Kerr, Wichada Rosenfeld, Roni Kreuter, Frauke Morris, Katherine A. |
Author_xml | – sequence: 1 givenname: Joshua A. surname: Salomon fullname: Salomon, Joshua A. – sequence: 2 givenname: Alex surname: Reinhart fullname: Reinhart, Alex – sequence: 3 givenname: Alyssa surname: Bilinski fullname: Bilinski, Alyssa – sequence: 4 givenname: Eu Jing surname: Chua fullname: Chua, Eu Jing – sequence: 5 givenname: Wichada surname: La Motte-Kerr fullname: La Motte-Kerr, Wichada – sequence: 6 givenname: Minttu M. surname: Rönn fullname: Rönn, Minttu M. – sequence: 7 givenname: Marissa B. surname: Reitsma fullname: Reitsma, Marissa B. – sequence: 8 givenname: Katherine A. surname: Morris fullname: Morris, Katherine A. – sequence: 9 givenname: Sarah surname: LaRocca fullname: LaRocca, Sarah – sequence: 10 givenname: Tamer H. surname: Farag fullname: Farag, Tamer H. – sequence: 11 givenname: Frauke surname: Kreuter fullname: Kreuter, Frauke – sequence: 12 givenname: Roni surname: Rosenfeld fullname: Rosenfeld, Roni – sequence: 13 givenname: Ryan J. surname: Tibshirani fullname: Tibshirani, Ryan J. |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34903656$$D View this record in MEDLINE/PubMed |
BookMark | eNp1kc1v1DAQxS1URLcLZ06gSFx6STv2-CO-IKGlhZUq9dAtV8txHJpV1l7spFL_exJtW6ASpznM7z29mXdCjkIMnpD3FM4oKDzfB5vPGKWUC05p9YosKGhaSq7hiCwAmCorzvgxOcl5CwBaVPCGHOO0Rynkgpxu7nxxe1Osrn-sv5ZUF5vkQ5MLG5pivdtbNxQ3Y7r3D2_J69b22b97nEtye3mxWX0vr66_rVdfrkrHOQ6ldcJqVKLmDBWTldLoUHnVSicry7EGhtig5gI1a5vaVorzGurWI3ghPC7J54Pvfqx3vnE-DMn2Zp-6nU0PJtrO_LsJ3Z35Ge9NpSgqiZPB6aNBir9Gnwez67LzfW-Dj2M2TFIApTnO6KcX6DaOKUznzZQUWLEp_5J8_DvRc5SnJ06AOAAuxZyTb43rBjt0cQ7Y9YaCmcsyc1nmT1mT7vyF7sn6_4oPB8U2DzE940xRqgRI_A05vpy7 |
CitedBy_id | crossref_primary_10_1002_ajim_23370 crossref_primary_10_1038_s41467_024_48528_2 crossref_primary_10_1136_jech_2023_221672 crossref_primary_10_1377_hlthaff_2022_00727 crossref_primary_10_1002_ajim_23410 crossref_primary_10_1016_j_epidem_2023_100728 crossref_primary_10_1192_bjo_2023_550 crossref_primary_10_3389_fpubh_2024_1408193 crossref_primary_10_1016_j_jiph_2024_102615 crossref_primary_10_3390_healthcare10071242 crossref_primary_10_3390_vaccines12121338 crossref_primary_10_1016_j_jnma_2024_07_007 crossref_primary_10_2196_57309 crossref_primary_10_1016_j_ijmedinf_2023_105133 crossref_primary_10_1073_pnas_2111452118 crossref_primary_10_1038_s43856_022_00183_8 crossref_primary_10_4269_ajtmh_22_0349 crossref_primary_10_1093_aje_kwae275 crossref_primary_10_1177_0272989X231218024 crossref_primary_10_1016_j_epidem_2024_100761 crossref_primary_10_1080_10810730_2023_2230929 crossref_primary_10_3390_vaccines10050739 crossref_primary_10_1126_sciadv_adj0266 crossref_primary_10_1515_jci_2022_0070 crossref_primary_10_1073_pnas_2111456118 crossref_primary_10_2196_42128 crossref_primary_10_1016_S2468_2667_24_00279_2 crossref_primary_10_1016_j_eswa_2024_124930 crossref_primary_10_1016_S2589_7500_22_00167_4 crossref_primary_10_1111_puar_13652 crossref_primary_10_1186_s41687_022_00471_w crossref_primary_10_1056_NEJMra2106441 crossref_primary_10_1080_24694452_2023_2292807 crossref_primary_10_1371_journal_pgph_0002601 crossref_primary_10_1080_19345747_2022_2131660 crossref_primary_10_1371_journal_pcbi_1011610 crossref_primary_10_1186_s12889_024_20623_5 crossref_primary_10_2105_AJPH_2023_307274 crossref_primary_10_1002_adhm_202300850 crossref_primary_10_1002_ejsp_3095 crossref_primary_10_1016_j_epidem_2024_100799 crossref_primary_10_3390_vaccines12091011 crossref_primary_10_3390_bios12111003 crossref_primary_10_1136_bmjopen_2023_072650 crossref_primary_10_1016_j_focus_2023_100140 crossref_primary_10_1073_pnas_2111453118 crossref_primary_10_1038_s41562_023_01743_1 crossref_primary_10_1016_j_focus_2022_100004 crossref_primary_10_1371_journal_pone_0279968 crossref_primary_10_2196_49185 crossref_primary_10_2105_AJPH_2023_307317 crossref_primary_10_1016_j_socscimed_2024_116775 crossref_primary_10_1016_j_mbs_2024_109345 crossref_primary_10_1038_s41598_023_29239_y crossref_primary_10_1016_j_mbs_2024_109337 crossref_primary_10_1186_s12889_022_14286_3 crossref_primary_10_1371_journal_pone_0286857 crossref_primary_10_1080_10618600_2023_2285337 crossref_primary_10_3389_ijph_2024_1607639 crossref_primary_10_1073_pnas_2211144119 crossref_primary_10_1111_irv_13143 crossref_primary_10_1016_j_heliyon_2023_e23219 crossref_primary_10_1016_j_pmedr_2023_102251 crossref_primary_10_1136_bmjopen_2022_066897 crossref_primary_10_1016_j_lanepe_2022_100350 crossref_primary_10_1007_s12650_024_00994_y crossref_primary_10_1287_ijds_2022_9016 crossref_primary_10_1093_jrsssa_qnae005 crossref_primary_10_1016_j_ajic_2023_09_010 crossref_primary_10_1038_s41598_023_27951_3 crossref_primary_10_1287_ijds_2023_0013 crossref_primary_10_1080_24725854_2024_2301966 crossref_primary_10_1186_s44247_023_00026_z crossref_primary_10_1080_2330443X_2023_2190008 crossref_primary_10_2196_47563 crossref_primary_10_3390_bs14100890 crossref_primary_10_1007_s10669_024_09981_y crossref_primary_10_1016_j_amepre_2023_03_001 crossref_primary_10_1080_10888705_2023_2268540 crossref_primary_10_2196_49307 crossref_primary_10_1016_j_vaccine_2023_12_016 crossref_primary_10_1111_padr_12558 |
Cites_doi | 10.1093/cid/ciab101 10.1214/18-AOAS1161SF 10.1016/S1473-3099(20)30120-1 10.1007/s11606-021-06633-8 10.1126/science.abh2939 10.1056/NEJMp2016259 10.1038/s41591-020-0916-2 10.1073/pnas.2111453118 10.1038/s41562-020-00944-2 10.12688/gatesopenres.13202.1 10.1016/S2589-7500(20)30293-4 |
ContentType | Journal Article |
Copyright | Copyright © 2021 the Author(s). Published by PNAS. Copyright National Academy of Sciences Dec 21, 2021 Copyright © 2021 the Author(s). Published by PNAS. 2021 |
Copyright_xml | – notice: Copyright © 2021 the Author(s). Published by PNAS. – notice: Copyright National Academy of Sciences Dec 21, 2021 – notice: Copyright © 2021 the Author(s). Published by PNAS. 2021 |
DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QG 7QL 7QP 7QR 7SN 7SS 7T5 7TK 7TM 7TO 7U9 8FD C1K FR3 H94 M7N P64 RC3 7X8 5PM |
DOI | 10.1073/pnas.2111454118 |
DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Calcium & Calcified Tissue Abstracts Chemoreception Abstracts Ecology Abstracts Entomology Abstracts (Full archive) Immunology Abstracts Neurosciences Abstracts Nucleic Acids Abstracts Oncogenes and Growth Factors Abstracts Virology and AIDS Abstracts Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database AIDS and Cancer Research Abstracts Algology Mycology and Protozoology Abstracts (Microbiology C) Biotechnology and BioEngineering Abstracts Genetics Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) |
DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Virology and AIDS Abstracts Oncogenes and Growth Factors Abstracts Technology Research Database Nucleic Acids Abstracts Ecology Abstracts Neurosciences Abstracts Biotechnology and BioEngineering Abstracts Environmental Sciences and Pollution Management Entomology Abstracts Genetics Abstracts Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) AIDS and Cancer Research Abstracts Chemoreception Abstracts Immunology Abstracts Engineering Research Database Calcium & Calcified Tissue Abstracts MEDLINE - Academic |
DatabaseTitleList | Virology and AIDS Abstracts CrossRef MEDLINE - Academic MEDLINE |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Sciences (General) Public Health |
EISSN | 1091-6490 |
EndPage | 9 |
ExternalDocumentID | PMC8713763 34903656 10_1073_pnas_2111454118 27117506 |
Genre | Research Support, U.S. Gov't, P.H.S Journal Article Comparative Study |
GeographicLocations | United States United States--US |
GeographicLocations_xml | – name: United States – name: United States--US |
GrantInformation_xml | – fundername: NCIRD CDC HHS grantid: U01 IP001121 – fundername: ACL HHS grantid: U01IP001121 – fundername: NICHD NIH HHS grantid: P2C HD041041 – fundername: HHS | Centers for Disease Control and Prevention (CDC) grantid: U01IP001121 – fundername: HHS | Centers for Disease Control and Prevention (CDC) grantid: NU38OT000297-02 |
GroupedDBID | --- -DZ -~X .55 0R~ 123 29P 2AX 2FS 2WC 4.4 53G 5RE 5VS 85S AACGO AAFWJ AANCE ABBHK ABOCM ABPLY ABPPZ ABTLG ABXSQ ABZEH ACGOD ACIWK ACNCT ACPRK AENEX AEUPB AEXZC AFFNX AFOSN AFRAH ALMA_UNASSIGNED_HOLDINGS BKOMP CS3 D0L DCCCD DIK DU5 E3Z EBS F5P FRP GX1 H13 HH5 HYE IPSME JAAYA JBMMH JENOY JHFFW JKQEH JLS JLXEF JPM JSG JST KQ8 L7B LU7 N9A N~3 O9- OK1 PNE PQQKQ R.V RHI RNA RNS RPM RXW SA0 SJN TAE TN5 UKR W8F WH7 WOQ WOW X7M XSW Y6R YBH YKV YSK ZCA ~02 ~KM AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QG 7QL 7QP 7QR 7SN 7SS 7T5 7TK 7TM 7TO 7U9 8FD C1K FR3 H94 M7N P64 RC3 7X8 5PM |
ID | FETCH-LOGICAL-c443t-ac5a9375b4237268793c37e7f6c68a43b0233d3945392fdba8744b0bfe30e55e3 |
ISSN | 0027-8424 1091-6490 |
IngestDate | Thu Aug 21 18:32:59 EDT 2025 Fri Jul 11 06:51:44 EDT 2025 Mon Jun 30 08:08:16 EDT 2025 Sat May 31 02:12:02 EDT 2025 Tue Jul 01 01:03:07 EDT 2025 Thu Apr 24 23:04:52 EDT 2025 Thu May 29 08:51:42 EDT 2025 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 51 |
Keywords | COVID-19 SARS-CoV2 survey |
Language | English |
License | Copyright © 2021 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY). |
LinkModel | OpenURL |
MergedId | FETCHMERGED-LOGICAL-c443t-ac5a9375b4237268793c37e7f6c68a43b0233d3945392fdba8744b0bfe30e55e3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23 Edited by Larry Wasserman, Carnegie Mellon University, Pittsburgh, PA, and approved October 29, 2021 (received for review June 22, 2021) Author contributions: J.A.S., A.R., A.B., K.A.M., S.L., T.H.F., F.K., R.R., and R.J.T. designed research; J.A.S., A.R., A.B., E.J.C., W.L.M.-K., M.M.R., M.B.R., R.R., and R.J.T. performed research; J.A.S., A.R., A.B., E.J.C., M.M.R., and M.B.R. analyzed data; J.A.S. and A.R. wrote the paper; and A.B., E.J.C., W.L.M.-K., M.M.R., M.B.R., K.A.M., S.L., T.H.F., F.K., R.R., and R.J.T. revised the paper. |
ORCID | 0000-0002-6658-514X 0000-0003-3929-5515 0000-0002-9292-5670 0000-0002-3274-5862 0000-0003-1826-6600 0000-0002-2158-8304 |
OpenAccessLink | https://pubmed.ncbi.nlm.nih.gov/PMC8713763 |
PMID | 34903656 |
PQID | 2616538279 |
PQPubID | 42026 |
PageCount | 9 |
ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_8713763 proquest_miscellaneous_2610079433 proquest_journals_2616538279 pubmed_primary_34903656 crossref_citationtrail_10_1073_pnas_2111454118 crossref_primary_10_1073_pnas_2111454118 jstor_primary_27117506 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2021-12-21 |
PublicationDateYYYYMMDD | 2021-12-21 |
PublicationDate_xml | – month: 12 year: 2021 text: 2021-12-21 day: 21 |
PublicationDecade | 2020 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States – name: Washington |
PublicationSeriesTitle | Beyond Cases and Deaths: The Benefits of Auxiliary Data Streams In Tracking the COVID-19 Pandemic |
PublicationTitle | Proceedings of the National Academy of Sciences - PNAS |
PublicationTitleAlternate | Proc Natl Acad Sci U S A |
PublicationYear | 2021 |
Publisher | National Academy of Sciences |
Publisher_xml | – name: National Academy of Sciences |
References | e_1_3_4_3_2 e_1_3_4_2_2 e_1_3_4_1_2 Astley C. M. (e_1_3_4_6_2) Reinhart A. (e_1_3_4_12_2) e_1_3_4_9_2 e_1_3_4_8_2 e_1_3_4_5_2 e_1_3_4_4_2 e_1_3_4_11_2 e_1_3_4_20_2 e_1_3_4_10_2 e_1_3_4_15_2 e_1_3_4_16_2 e_1_3_4_13_2 Rodríguez A. (e_1_3_4_18_2) 2021; 35 e_1_3_4_14_2 e_1_3_4_19_2 e_1_3_4_17_2 Kreuter F. (e_1_3_4_7_2) 2020; 14 |
References_xml | – volume: 14 start-page: 159 year: 2020 ident: e_1_3_4_7_2 article-title: Partnering with a global platform to inform research and public policy making publication-title: Surv. Res. Methods – volume: 35 start-page: 15393 year: 2021 ident: e_1_3_4_18_2 article-title: DeepCOVID: An operational deep learning-driven framework for explainable real-time COVID-19 forecasting publication-title: Proc. Conf. AAAI Artif. Intell. – ident: e_1_3_4_13_2 doi: 10.1093/cid/ciab101 – ident: e_1_3_4_20_2 doi: 10.1214/18-AOAS1161SF – ident: e_1_3_4_10_2 doi: 10.1016/S1473-3099(20)30120-1 – ident: e_1_3_4_8_2 – ident: e_1_3_4_12_2 article-title: An open repository of real-time COVID-19 indicators publication-title: Proc. Natl. Acad. Sci. U.S.A. – ident: e_1_3_4_9_2 – ident: e_1_3_4_15_2 doi: 10.1007/s11606-021-06633-8 – ident: e_1_3_4_1_2 – ident: e_1_3_4_6_2 article-title: Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base publication-title: Proc. Natl. Acad. Sci. U.S.A. – ident: e_1_3_4_17_2 doi: 10.1126/science.abh2939 – ident: e_1_3_4_11_2 – ident: e_1_3_4_3_2 doi: 10.1056/NEJMp2016259 – ident: e_1_3_4_4_2 doi: 10.1038/s41591-020-0916-2 – ident: e_1_3_4_19_2 doi: 10.1073/pnas.2111453118 – ident: e_1_3_4_5_2 – ident: e_1_3_4_2_2 doi: 10.1038/s41562-020-00944-2 – ident: e_1_3_4_16_2 doi: 10.12688/gatesopenres.13202.1 – ident: e_1_3_4_14_2 doi: 10.1016/S2589-7500(20)30293-4 |
SSID | ssj0009580 |
Score | 2.6537747 |
Snippet | The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By... The US COVID-19 Trends and Impact Survey (CTIS) has operated continuously since April 6, 2020, collecting over 20 million responses. As the largest public... |
SourceID | pubmedcentral proquest pubmed crossref jstor |
SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 1 |
SubjectTerms | Adult Aged Biological Sciences Coronaviruses COVID-19 COVID-19 - diagnosis COVID-19 - epidemiology COVID-19 - prevention & control COVID-19 - transmission COVID-19 Testing - statistics & numerical data COVID-19 Vaccines Cross-Sectional Studies Economic impact Epidemiologic Methods Female Health Status Indicators Humans Immunization Male Mental health Middle Aged Patient Acceptance of Health Care - statistics & numerical data Polls & surveys Priorities Public health Real time Risk taking Social Media - statistics & numerical data Social Sciences Surveillance systems Time measurement Trends United States - epidemiology Vaccination Young Adult |
Subtitle | Continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination |
Title | The US COVID-19 Trends and Impact Survey |
URI | https://www.jstor.org/stable/27117506 https://www.ncbi.nlm.nih.gov/pubmed/34903656 https://www.proquest.com/docview/2616538279 https://www.proquest.com/docview/2610079433 https://pubmed.ncbi.nlm.nih.gov/PMC8713763 |
Volume | 118 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1db9MwFLXKkNBeEAMGhYGMxMNQm9LETpzwVg3QmESZ6Ir2Vjmpo1Zq02pJkMYP4dfw47j-ituyScBLFCX-eLgn18fOufci9DoWIiE8DT2W08yjAjhcGsShl0ShCPOcBTyTscOfh9HpmJ5dhpet1q8N1VJdpb3sx41xJf9jVXgGdpVRsv9g2WZQeAD3YF-4goXh-tc2Ho86J1--fXrv-UnHCFyVxFdHP47qK1nxmMjgc1kTopaKV-CJC08Wle8s3Qmh0mXYgcrr5bpa6VMYKT5XNyalg5K7m-B-9bySiTq0y5Azf-dZNi-cwQ3zPW9WytLqEob2IHLgwlqMryk7Xud86Iokj_hitdQCgbNVOau5O4P9KubFjOvIIxmu4479F01V7sHiuiydJgn66yCfzplduc3BR-BLEYmOpu4J7ayB63gR1eVGG2_u3Hltk9n-sUyAX5O1jQte9mAD7NOQmm4boFkvFWoIjE-icCddtyEA-tUddDeATUpgz4qalM9x3yaTYuTtzmz76J7tv0WJtCr2pv3Ormx3gwddPED3zQYGDzQaD1BLFA_RgTUbPjZ5zN88Qj8Bnng8whZVWMMTA0iwhifW8HyHHThxA068AU68yt0wFpxdrKDZxQ6YuAFmFxtYdtV8G6B8jMYfP1ycnHqmDIiXUUoqj2chBxIdplLBFUQxrCgZYYLlURbFnJIUaCeZkoSGwPXzacplRYe0n-aC9EUYCnKI9opVIZ4iHGT5lDM_oXTKaNznKSNcprhjeTCNcxa1Uc9aYpKZHPmyVMtiorQajEykFSfOim103HRY6_Qwtzc9VKZt2gVMpsntw6RH1tYT41ygX-RHwEUClrTRq-Y1uH75P48XAgwi2wDDTyghbfREQ6MZ3GKrjdgWaJoGMq389ptiPlPp5WPmS9bx7NYxn6N99z0eob3qqhYvgJpX6Uv1BfwGdPHkJQ |
linkProvider | National Library of Medicine |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=The+US+COVID-19+Trends+and+Impact+Survey%3A+Continuous+real-time+measurement+of+COVID-19+symptoms%2C+risks%2C+protective+behaviors%2C+testing%2C+and+vaccination&rft.jtitle=Proceedings+of+the+National+Academy+of+Sciences+-+PNAS&rft.au=Salomon%2C+Joshua+A&rft.au=Reinhart%2C+Alex&rft.au=Bilinski%2C+Alyssa&rft.au=Chua%2C+Eu+Jing&rft.date=2021-12-21&rft.eissn=1091-6490&rft.volume=118&rft.issue=51&rft_id=info:doi/10.1073%2Fpnas.2111454118&rft_id=info%3Apmid%2F34903656&rft.externalDocID=34903656 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0027-8424&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0027-8424&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0027-8424&client=summon |