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Risk factors associated with the incidence of self-reported COVID-19-like illness: data from a web-based syndromic surveillance system in the Netherlands.

ABSTRACT: During the first wave of the severe acute respiratory syndrome-coronavirus-2 epidemic in the Netherlands, notifications consisted mostly of patients with relatively severe disease. To enable real-time monitoring of the incidence of mild coronavirus disease 2019 (COVID-19) - for which medical consultation might not be required - the Infectieradar web-based syndromic surveillance system was launched in mid-March 2020. Our aim was to quantify associations between Infectieradar participant characteristics and the incidence of self-reported COVID-19-like illness. Recruitment for this cohort study was via a web announcement. After registering, participants completed weekly questionnaires, reporting the occurrence of a set of symptoms. The incidence rate of COVID-19-like illness was estimated and multivariable Poisson regression used to estimate the relative risks associated with sociodemographic variables, lifestyle factors and pre-existing medical conditions. Between 17 March and 24 May 2020, 25 663 active participants were identified, who reported 7060 episodes of COVID-19-like illness over 131 404 person-weeks of follow-up. The incidence rate declined over the analysis period, consistent with the decline in notified cases. Male sex, age 65+ years and higher education were associated with a significantly lower COVID-19-like illness incidence rate (adjusted rate ratios (RRs) of 0.80 (95% CI 0.76-0.84), 0.77 (0.70-0.85), 0.84 (0.80-0.88), respectively) and the baseline characteristics ever-smoker, asthma, allergies, diabetes, chronic lung disease, cardiovascular disease and children in the household were associated with a higher incidence (RRs of 1.11 (1.04-1.19) to 1.69 (1.50-1.90)). Web-based syndromic surveillance has proven useful for monitoring the temporal trends in, and risk factors associated with, the incidence of mild disease. Increased relative risks observed for several patient factors could reflect a combination of exposure risk, susceptibility to infection and propensity to report symptoms.

SUBMITTER: McDonald SA

PROVIDER: S-EPMC8160488 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundInfluenza and Influenza-like-illness (ILI) represents a substantial public health problem, but it is difficult to measure the overall burden as many cases do not access health care. Community cohorts have the advantage of not requiring individuals to present at hospitals and surgeries and therefore can potentially monitor a wider variety of cases. This study reports on the incidence and risk factors for ILI in the UK as measured using Flusurvey, an internet-based open community cohort.MethodsUpon initial online registration participants were asked background characteristics, and every week were asked to complete a symptoms survey. We compared the representativeness of our sample to the overall population. We used two case definitions of ILI, which differed in whether fever/chills was essential. We calculated ILI incidence week by week throughout the season, and investigated risk factors associated with ever reporting ILI over the course of the season. Risk factor analysis was conducted using binomial regression.Results5943 participants joined the survey, and 4532 completed the symptoms survey at least twice. Participants who filled in symptoms surveys at least twice filled in a median of nine symptoms surveys over the course of the study. 46.1% of participants reported at least one episode of ILI, and 6.0% of all reports were positive for ILI. Females had slightly higher incidence, and individuals over 65 had the lowest incidence. Incidence peaked just before Christmas and declined dramatically during school holidays. Multivariate regression showed that, for both definitions of ILI considered, being female, unvaccinated, having underlying health issues, having contact with children, being aged between 35 and 64, and being a smoker were associated with the highest risk of reporting an ILI. The use of public transport was not associated with an increased risk of ILI.ConclusionsOur results show that internet based surveillance can be used to measure ILI and understand risk factors. Vaccination is shown to be linked to a reduced risk of reporting ILI. Taking public transport does not increase the risk of reporting ILI. Flusurvey and other participatory surveillance techniques can be used to provide reliable information to policy makers in nearly real-time.

Project description:BackgroundWith their increasing availability in resource-limited settings, mobile phones may provide an important tool for participatory syndromic surveillance, in which users provide symptom data directly into a centralized database.ObjectiveWe studied the performance of a mobile phone app-based participatory syndromic surveillance system for collecting syndromic data (acute febrile illness and acute gastroenteritis) to detect dengue virus and norovirus on a cohort of children living in a low-resource and rural area of Guatemala.MethodsRandomized households were provided with a mobile phone and asked to submit weekly reports using a symptom diary app (Vigilant-e). Participants reporting acute febrile illness or acute gastroenteritis answered additional questions using a decision-tree algorithm and were subsequently visited at home by a study nurse who performed a second interview and collected samples for dengue virus if confirmed acute febrile illness and norovirus if acute gastroenteritis. We analyzed risk factors associated with decreased self-reporting of syndromic data using the Vigilant-e app and evaluated strategies to improve self-reporting. We also assessed agreement between self-report and nurse-collected data obtained during home visits.ResultsFrom April 2015 to June 2016, 469 children in 207 households provided 471 person-years of observation. Mean weekly symptom reporting rate was 78% (range 58%-89%). Households with a poor (<70%) weekly reporting rate using the Vigilant-e app during the first 25 weeks of observation (n=57) had a greater number of children (mean 2.8, SD 1.5 vs mean 2.5, SD 1.3; risk ratio [RR] 1.2, 95% CI 1.1-1.4), were less likely to have used mobile phones for text messaging at study enrollment (61%, 35/57 vs 76.7%, 115/150; RR 0.6, 95% CI 0.4-0.9), and were less likely to access care at the local public clinic (35%, 20/57 vs 67.3%, 101/150; RR 0.4, 95% CI 0.2-0.6). Parents of female enrolled participants were more likely to have low response rate (57.1%, 84/147 vs 43.8%, 141/322; RR 1.4, 95% CI 1.1-1.9). Several external factors (cellular tower collapse, contentious elections) were associated with periods of decreased reporting. Poor response rate (<70%) was associated with lower case reporting of acute gastroenteritis, norovirus-associated acute gastroenteritis, acute febrile illness, and dengue virus-associated acute febrile illness (P<.001). Parent-reported syndromic data on the Vigilant-e app demonstrated agreement with nurse-collected data for fever (kappa=.57, P<.001), vomiting (kappa=.63, P<.001), and diarrhea (kappa=.61, P<.001), with decreased agreement as the time interval between parental report and nurse home visit increased (<1 day: kappa=.65-.70; ≥2 days: kappa=.08-.29).ConclusionsIn a resource-limited area of rural Guatemala, a mobile phone app-based participatory syndromic surveillance system demonstrated a high reporting rate and good agreement between parental reported data and nurse-reported data during home visits. Several household-level and external factors were associated with decreased syndromic reporting. Poor reporting rate was associated with decreased syndromic and pathogen-specific case ascertainment.

Project description:BackgroundDiabetes mellitus (DM) is a leading contributor to morbidity and mortality in the United States (US). Prior DM prevalence estimates in Asian Americans are predominantly from Asians aggregated into a single group, but the Asian American population is heterogenous.ObjectiveTo evaluate self-reported DM prevalence in disaggregated Asian American subgroups to inform targeted management and prevention.DesignSerial cross-sectional analysis.ParticipantsRespondents to the US Behavioral Risk Factor Surveillance System surveys who self-identify as non-Hispanic Asian American (NHA, N=57,001), comprising Asian Indian (N=11,089), Chinese (N=9458), Filipino (N=9339), Japanese (N=10,387), and Korean Americans (N=2843), compared to non-Hispanic White (NHW, N=2,143,729) and non-Hispanic Black (NHB, N=215,957) Americans.Main measuresPrevalence of self-reported DM. Univariate Satterthwaite-adjusted chi-square tests compared the differences in weighted DM prevalence by sociodemographic and health status.Key resultsSelf-reported fully adjusted DM prevalence was 8.7% (95% confidence interval 8.2-9.3) in NHA, compared to 14.3% (14.0-14.6) in NHB and 10.0% (10.0-10.1) in NHW (p<0.01 for difference). In NHA subgroups overall, DM prevalence was 14.4% (12.6-16.3) in Filipino, 13.4% (10.9-16.2) in Japanese, 10.7% (9.6-11.8) in Asian Indian, 5.1% (4.2-6.2) in Chinese, and 4.7% (3.4-6.3) in Korean Americans (p<0.01). Among those aged ≥65 years, DM prevalence was highest in Filipino (35.0% (29.4-41.2)) and Asian Indian (31.5% (25.9-37.8)) Americans. Adjusted for sex, education, and race/ethnicity-specific obesity category, NHA overall had a 21% higher DM prevalence compared to NHW (prevalence ratio 1.21 [1.14-1.27]), while prevalence ratios were 1.42 (1.24-1.63) in Filipinos and 1.29 (1.14-1.46) in Asian Indians.ConclusionsAdjusted self-reported DM prevalence is higher in NHA compared with NHW. Disaggregating NHA reveals heterogeneity in self-reported DM prevalence, highest in Filipino and Asian Indian Americans.

Project description:School children may transmit pathogens with cluster cases occurring on campuses and in families. In response to the 2009 influenza A (H1N1) pandemic, Taipei City Government officials developed a School-based Infectious Disease Syndromic Surveillance System (SID-SSS). Teachers and nurses from preschools to universities in all 12 districts within Taipei are required to daily report cases of symptomatic children or sick leave requests through the SID-SSS. The pre-diagnosis at schools is submitted firstly as common pediatric disease syndrome-groups and re-submitted after confirmation by physicians. We retrieved these data from January 2010 to August 2011 for spatio-temporal analysis and evaluated the temporal trends with cases obtained from both the Emergency Department-based Syndromic Surveillance System (ED-SSS) and the Longitudinal Health Insurance Database 2005 (LHID2005). Through the SID-SSS, enterovirus-like illness (EVI) and influenza-like illness (ILI) were the two most reported syndrome groups (77.6% and 15.8% among a total of 19,334 cases, respectively). The pre-diagnosis judgments made by school teachers and nurses showed high consistency with physicians' clinical diagnoses for EVI (97.8%) and ILI (98.9%). Most importantly, the SID-SSS had better timeliness with earlier peaks of EVI and ILI than those in the ED-SSS. Furthermore, both of the syndrome groups in these two surveillance systems had the best correlation reaching 0.98 and 0.95, respectively (p<0.01). Spatio-temporal analysis observed the patterns of EVI and ILI both diffuse from the northern suburban districts to central Taipei, with ILI spreading faster. This novel system can identify early suspected cases of two important pediatric infections occurring at schools, and clusters from schools/families. It was also cost-effective (95.5% of the operation cost reduced and 59.7% processing time saved). The timely surveillance of mild EVI and ILI cases integrated with spatial analysis may help public health decision-makers with where to target for enhancing surveillance and prevention measures to minimize severe cases.

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Risk factors associated with the incidence of self-reported COVID-19-like illness: data from a web-based syndromic surveillance system in the Netherlands.

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