ArticleBMC infectious diseases2018
Comparison of crowd-sourced, electronic health records based, and traditional health-care based influenza-tracking systems at multiple spatial resolutions in the United States of America.
Article in BMC infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04663776 (Wide Scale Monitoring for Acute Respiratory Infection Using a Mobile-Based Study Platform), which is not on this map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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.
Wide Scale Monitoring for Acute Respiratory Infection Using a Mobile-Based Study Platform
Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of spatial decision support systems in public health informatics supporting the identification of high risk areas for zoonotic disease outbreaks.International journal of health geographics · 2018Pooled it
- Harnessing Participatory Surveillance Cohorts and Proxy Indicators to Dynamically Track Epidemic Trends and Undiagnosed COVID-19 Infections in Singapore: Longitudinal Observational Study.Journal of medical Internet research · 2026Observational
- Heterogeneity in seasonal influenza vaccination opportunity and disease risk during pregnancy and in infants <6 months.Vaccine · 2025Article
- Comparison of Influenza-Like Illness (ILI) incidence data from the novel LeCellPHIA participatory surveillance system with COVID-19 case count data, Lesotho, July 2020 - July 2021.BMC infectious diseases · 2023Article
- Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States.Science advances · 2023Article
- Influenza surveillance systems using traditional and alternative sources of data: A scoping review.Influenza and other respiratory viruses · 2022Article
- SARS-CoV-2 pandemic in New York metropolitan area: the view from a major urgent care provider.Annals of epidemiology · 2022Article
- Using GPS-enabled mobile phones to evaluate the associations between human mobility changes and the onset of influenza illness.Spatial and spatio-temporal epidemiology · 2022Article
- Concordance between the Clinical Diagnosis of Influenza in Primary Care and Epidemiological Surveillance Systems (PREVIGrip Study).International journal of environmental research and public health · 2022Article
- Comparison of longitudinal trends in self-reported symptoms and COVID-19 case activity in Ontario, Canada.PloS one · 2022Article
- Re-examining COVID-19 Self-Reported Symptom Tracking Programs in the United States: Updated Framework Synthesis.JMIR formative research · 2021Article
- Cross-sectional telephone surveys as a tool to study epidemiological factors and monitor seasonal influenza activity in Malta.BMC public health · 2021Article
- Crowdsourced disease surveillance success story: The FluWatchers program.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2021Article
- Using big data for evaluating development outcomes: A systematic map.Campbell systematic reviews · 2021Article
- Epidemiological observations on breaking COVID-19 transmission: from the experience of Taiwan.Journal of epidemiology and community health · 2021Article
- Front-Line Emergency Department Clinician Acceptability and Use of a Prototype Real-Time Cloud-Based Influenza Surveillance System.Frontiers in public health · 2021Article
- Influenza-like illness in Australia: A comparison of general practice surveillance system with electronic medical records.Influenza and other respiratory viruses · 2020Article
- COVID-19 Self-Reported Symptom Tracking Programs in the United States: Framework Synthesis.Journal of medical Internet research · 2020Article
- Surveilling Influenza Incidence With Centers for Disease Control and Prevention Web Traffic Data: Demonstration Using a Novel Dataset.Journal of medical Internet research · 2020Article
- Socioeconomic bias in influenza surveillance.PLoS computational biology · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundInfluenza causes an estimated 3000 to 50,000 deaths per year in the United States of America (US). Timely and representative data can help local, state, and national public health officials monitor and respond to outbreaks of seasonal influenza. Data from cloud-based electronic health records (EHR) and crowd-sourced influenza surveillance systems have the potential to provide complementary, near real-time estimates of influenza activity. The objectives of this paper are to compare two novel influenza-tracking systems with three traditional healthcare-based influenza surveillance systems at four spatial resolutions: national, regional, state, and city, and to determine the minimum number of participants in these systems required to produce influenza activity estimates that resemble the historical trends recorded by traditional surveillance systems.
methodsWe compared influenza activity estimates from five influenza surveillance systems: 1) patient visits for influenza-like illness (ILI) from the US Outpatient ILI Surveillance Network (ILINet), 2) virologic data from World Health Organization (WHO) Collaborating and National Respiratory and Enteric Virus Surveillance System (NREVSS) Laboratories, 3) Emergency Department (ED) syndromic surveillance from Boston, Massachusetts, 4) patient visits for ILI from EHR, and 5) reports of ILI from the crowd-sourced system, Flu Near You (FNY), by calculating correlations between these systems across four influenza seasons, 2012-16, at four different spatial resolutions in the US. For the crowd-sourced system, we also used a bootstrapping statistical approach to estimate the minimum number of reports necessary to produce a meaningful signal at a given spatial resolution.
resultsIn general, as the spatial resolution increased, correlation values between all influenza surveillance systems decreased. Influenza-like Illness rates in geographic areas with more than 250 crowd-sourced participants or with more than 20,000 visit counts for EHR tracked government-lead estimates of influenza activity.
conclusionsWith a sufficient number of reports, data from novel influenza surveillance systems can complement traditional healthcare-based systems at multiple spatial resolutions.
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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.