ArticleProceedings of the National Academy of Sciences of the United States of America2021
Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 36 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
36 citing papers in PubMed, 68 citations in OpenAlex.
- Epidemiology of SARS-CoV-2 Infection in Italy Using Real-World Data: Methodology and Cohort Description of the Second Phase of Web-Based EPICOVID19 Study.International journal of environmental research and public health · 2022Trial
- Global Mind Project data in the United States: A comparison with national statistics.International journal of population data science · 2026Article
- When Omicron knocks at door: An inverted U-shape relationship between virus proximity and prosocial behavior.Fundamental research · 2025Article
- Association Between Trust in Health Care Professionals and Health Care Access: Insights From an Online Survey Across 21 Countries.International journal of public health · 2025Article
- The role of financial stress, food insecurity, and COVID-19-related illness concerns shaping mental health in five South Asian countries during the pandemic (2020-2022): A secondary analysis of the online COVID-19 Trends and Impact Survey (CTIS) data.PLOS global public health · 2025Article
- Insights on Late-Stage COVID-19 Pandemic Recovery From a 21-Country Online Survey.International journal of public health · 2025Article
- Impact of pandemic-related worries on mental health in India from 2020 to 2022.Npj mental health research · 2024Article
- Community-engaged artificial intelligence research: A scoping review.PLOS digital health · 2024Article
- Exploring the Big Data Paradox for various estimands using vaccination data from the global COVID-19 Trends and Impact Survey (CTIS).Science advances · 2024Article
- Vaccine effectiveness against emerging COVID-19 variants using digital health data.Communications medicine · 2024Article
- Innovations in public health surveillance: An overview of novel use of data and analytic methods.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2024Article
- Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- Performance and explainability of feature selection-boosted tree-based classifiers for COVID-19 detection.Heliyon · 2024Article
- Determinants of Unmet Healthcare Needs During the Final Stage of the COVID-19 Pandemic: Insights From a 21-Country Online Survey.International journal of public health · 2024Article
- Attractor landscapes: a unifying conceptual model for understanding behaviour change across scales of observation.Health psychology review · 2023Article
- Engaging a national-scale cohort of smart thermometer users in participatory surveillance.NPJ digital medicine · 2023Article
- COVID-19 activity risk calculator as a gamified public health intervention tool.Scientific reports · 2023Article
- Trends and symptoms of SARS-CoV-2 infection: a longitudinal study on an Alpine population representative sample.BMJ open · 2023Article
- Smart Thermometer-Based Participatory Surveillance to Discern the Role of Children in Household Viral Transmission During the COVID-19 Pandemic.JAMA network open · 2023Article
- COVID-19 Vaccine Acceptance and Uptake in Bangkok, Thailand: Cross-sectional Online Survey.JMIR public health and surveillance · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
15 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Simultaneously tracking the global impact of COVID-19 is challenging because of regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network has the potential to provide standardized data streams to support monitoring and decision-making worldwide, in real time, and with limited local resources. The University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, has invited daily cross-sectional samples from the social media platform's active users to participate in the survey since its launch on April 23, 2020. We analyzed UMD-CTIS survey data through December 20, 2020, from 31,142,582 responses representing 114 countries/territories weighted for nonresponse and adjusted to basic demographics. We show consistent respondent demographics over time for many countries/territories. Machine Learning models trained on national and pooled global data verified known symptom indicators. COVID-like illness (CLI) signals were correlated with government benchmark data. Importantly, the best benchmarked UMD-CTIS signal uses a single survey item whereby respondents report on CLI in their local community. In regions with strained health infrastructure but active social media users, we show it is possible to define COVID-19 impact trajectories using a remote platform independent of local government resources. This syndromic surveillance public health tool is the largest global health survey to date and, with brief participant engagement, can provide meaningful, timely insights into the global COVID-19 pandemic at a local scale.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.