Determinants of follow-up participation in the Internet-based European influenza surveillance platform Influenzanet

Healthcare-seeking behaviours of patients with acute respiratory infection: a cross-sectional survey in a rural area of southwest China

OBJECTIVES

This study aimed to assess the healthcare-seeking behaviour and related factors of people with acute respiratory symptoms in the rural areas of central and western China to estimate the disease burden of influenza more accurately.

DESIGN

Cross-sectional survey.

SETTINGS

Fifty-two communities/villages in the Wanzhou District, Chongqing, China, a rural area in southwest China, from May 2022 to July 2022.

PARTICIPANTS

The participants were those who had been living in Wanzhou District continuously for more than 6 months and consented to participate.

OUTCOME MEASURES

A semistructured questionnaire was used to determine the healthcare-seeking behaviour of participants, and the dichotomous response of 'yes' or 'no' was used to assess whether participants had acute respiratory symptoms and their healthcare-seeking behaviour.

RESULTS

Only 50.92% (360 of 707) of the patients with acute respiratory infection visited medical and health institutions for treatment, whereas 49.08% (347 of 707) avoided treatment or opted for self-medication. The primary reason for not seeing a doctor was that patients felt their condition was not serious and visiting a medical facility for treatment was unnecessary. Short distance (87.54%) and reasonable charges (49.48%) were ranked as the most important reasons for choosing treatment at primary medical and health facilities (80.27%). The primary reasons for which patients visited secondary and tertiary hospitals (7.78% and 8.61%, respectively) were that doctors in such facilities were better at diagnosis (57.14%) and at treatment (87.10%).

CONCLUSION

The findings provided in this study indicated that regular healthcare-seeking behaviour investigations should be conducted. The disease burden of influenza can be calculated more accurately when healthcare-seeking behaviour investigations are combined with surveillance in the hospitals.

Participatory surveillance for COVID-19 trends detection in Brazil: Cross-section study

BACKGROUND

The ongoing COVID-19 pandemic has emphasized the necessity of a well-functioning surveillance system to detect and mitigate disease outbreaks. Traditional surveillance (TS) usually relies on healthcare providers and generally suffers from reporting lags that prevent immediate response plans. Participatory surveillance (PS), an innovative digital approach whereby individuals voluntarily monitor and report on their own health status via Web-based surveys, has emerged in the past decade to complement traditional data collections approaches.

OBJECTIVE

This study compares novel PS data on COVID-19 infection rates across nine Brazilian cities with official TS data to examine the opportunities and challenges of using the former, and the potential advantages of combining the two approaches.

METHODS

The traditional surveillance data for Brazil, prospectively called the TS data, is publicly accessible on GitHub. The participatory surveillance data was collected through the Brazil Sem Corona - a Colab platform. To gather information on an individual's health status, each participant was asked to fill out a daily questionnaire into the Colab app on symptoms as well as exposure.

RESULTS

We find that high participation rates are key for PS data to adequately mirror TS infection rates. Where participation was high, we document a significant trend correlation between lagged PS data and TS infection rates, suggesting that the former could be used for early detection. In our data, forecasting models integrating both approaches increased accuracy up to 3% relative to a 14-day forecast horizon model based exclusively on TS data. Furthermore, we show that the PS data captures a population that significantly differs from the traditional observation.

CONCLUSIONS

In the traditional system, the new recorded COVID-19 cases per day are aggregated based on positive lab-confirmed tests. In contrast, the PS data shows a significant share of reports categorized as potential COVID-19 case that are not lab-confirmed. Quantifying the economic value of a PS system implementation remains hard. But scarce public funds as well as persisting constraints to the TS system motivate for a PS system, making it an important avenue for future research. The decision to set up a PS system requires careful evaluation of its expected benefits, relative to the costs of setting up platforms and incentivizing engagement to increase both coverage and consistent reporting over time. The ability to compute such economic trade-offs might be key to have PS become a more integral part of policy toolkits moving forward. These results corroborate previous studies when it comes to the benefits of an integrated and comprehensive surveillance system, but also shed lights on its limitations, and on the need for additional research to improve future implementations of PS platforms.

CLINICALTRIAL

A mixed methods analysis of participation in a social contact survey

BACKGROUND

Social contact survey data forms a core component of modern epidemic models: however, there has been little assessment of the potential biases in such data.

METHODS

We conducted focus groups with university students who had (n = 13) and had never (n = 14) completed a social contact survey during the COVID-19 pandemic. Qualitative findings were explored quantitatively by analysing participation data.

RESULTS

The opportunity to contribute to COVID-19 research, to be heard and feel useful were frequently reported motivators for participating in the contact survey. Reductions in survey engagement following lifting of COVID-19 restrictions may have occurred because the research was perceived to be less critical and/or because the participants were busier and had more contacts. Having a high number of contacts to report, uncertainty around how to report each contact, and concerns around confidentiality were identified as factors leading to inaccurate reporting. Focus groups participants thought that financial incentives or provision of study results would encourage participation.

CONCLUSIONS

Incentives could improve engagement with social contact surveys. Qualitative research can inform the format, timing, and wording of surveys to optimise completion and accuracy.

Representativeness of the FluWatchers Participatory Disease Surveillance Program 2015-2016 to 2018-2019: How do participants compare with the Canadian population?

BACKGROUND

FluWatch is Canada's national surveillance system that monitors the spread of influenza. Its syndromic surveillance component monitors the spread of influenza-like illness (ILI) in near-real time for signals of unusual or increased activity. Syndromic surveillance data are collected from two main sources: the Sentinel Practitioner ILI Reporting System and FluWatchers.We evaluated the representativeness of the most recent participant population to understand changes in representativeness since 2015, to identify demographic and geographic gaps and correlates/determinants of participation to characterize a typical participant.

METHODS

In this serial cross-sectional study, characteristics of participants during four consecutive influenza seasons (2015-2016, 2016-2017, 2017-2018 and 2018-2019) were compared with the 2016 Canadian Census and the 2015-2016, 2016-2017, 2017-2018 and 2018-2019 National Seasonal Influenza Vaccination Coverage Surveys. Associations between demographic factors and the level of user participation were also analyzed among the 2018-2019 FluWatchers population.

RESULTS

Infants (0-4 years) and older adults (65 years and older) were under-represented in FluWatchers across all four influenza seasons. Female and urban participants were significantly over-represented. Vaccination coverage remained significantly higher among the FluWatchers populations from the past four influenza seasons across all age groups. Level of participation among FluWatchers was associated with age and vaccination status, but not with sex or geography. Over its four years of implementation, the FluWatchers participant population became more representative of the Canadian population with respect to age and geography (urban/rural and provincial/territorial).

CONCLUSION

FluWatchers participants under-represent the tails of Canada's age distribution and over-represent those who engage in health promoting behaviours as indicated by high influenza vaccine coverage, consistent with typical volunteer-based survey response biases. Representativeness would likely improve with targeted recruitment of under-represented groups, such as males, older adults and Canadians living in rural areas.

Analysis of a Vaping-Associated Lung Injury Outbreak through Participatory Surveillance and Archival Internet Data

The US Centers for Disease Control and Prevention alerted of a suspected outbreak of lung illness associated with using E-cigarette products in September 2019. At the time that the CDC published its alert little was known about the causes of the outbreak or who was at risk for it. Here we provide insights into the outbreak through analysis of passive reporting and participatory surveillance. We collected data about vaping habits and associated adverse reactions from four data sources pertaining to people in the USA: A participatory surveillance platform (YouVape), Reddit, Google Trends, and Bing. Data were analyzed to identify vaping behaviors and reported adverse events. These were correlated among sources and with prior reports. Data was obtained from 720 YouVape users, 4331 Reddit users, and over 1 million Bing users. Large geographic variation was observed across vaping products. Significant correlation was found among the data sources in reported adverse reactions. Models of participatory surveillance data found specific product and adverse reaction associations. Specifically, cannabidiol was found to be associated with fever, while tetrahydrocannabinol was found to be correlated with diarrhea. Our results demonstrate that utilization of different, complementary, online data sources provide a holistic view of vaping associated lung injury while augmenting traditional data sources.

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

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.

Challenges for Nontechnical Implementation of Digital Proximity Tracing During the COVID-19 Pandemic: Media Analysis of the SwissCovid App

BACKGROUND

Several countries have released digital proximity tracing (DPT) apps to complement manual contact tracing for combatting the SARS-CoV-2 pandemic. DPT aims to notify app users about proximity exposures to persons infected with SARS-CoV-2 so that they can self-quarantine. The success of DPT apps depends on user acceptance and the embedding of DPT into the pandemic mitigation strategy.

OBJECTIVE

By searching for media articles published during the first 3 months after DPT launch, the implementation of DPT in Switzerland was evaluated to inform similar undertakings in other countries. The second aim of the study was to create a link between reported DPT implementation challenges and normalization process theory for planning and optimizing complex digital health interventions, which can provide useful guidance for decision-making in DPT design and implementation.

METHODS

A Swiss media database was searched for articles on the Swiss DPT app (SwissCovid) published in German or French between July 4 and October 3, 2020. In a structured process, topics were extracted and clustered manually from articles that were deemed pertinent. Extracted topics were mapped to four NPT constructs, which reflected the flow of intervention development from planning, stakeholder onboarding, and execution to critical appraisal. Coherence constructs describe sense-making by stakeholders, cognitive participation constructs reflect participants' efforts to create engagement with the intervention, collective actions refer to intervention execution and joint stakeholder efforts to make the intervention work, and reflexive monitoring refers to collective risk-benefit appraisals to create improvements.

RESULTS

Out of 94 articles deemed pertinent and selected for closer inspection, 38 provided unique information on implementation challenges. Five challenge areas were identified: communication challenges, challenges for DPT to interface with other processes, fear of resource competition with established pandemic mitigation measures, unclear DPT effectiveness, and obstacles to greater user coverage and compliance. Specifically, several articles mentioned unclear DPT benefits to affect commitment and to raise fears among different health system actors regarding resource competition. Moreover, media reports indicated process interface challenges such as delays or unclear responsibilities in the notification cascade, as well as misunderstandings and unmet communication needs from health system actors. Finally, reports suggested misaligned incentives, not only for app usage by the public but also for process engagement by other actors in the app notification cascade. NPT provided a well-fitting framework to contextualize the different DPT implementation challenges and to highlight improvement strategies, namely a better alignment of stakeholder incentives, or stakeholder-specific communication to address their concerns about DPT.

CONCLUSIONS

Early experiences from one of the first adopters of DPT indicate that nontechnical implementation challenges may affect the effectiveness of DPT. The NPT analysis provides a novel perspective on DPT implementation and stresses the need for stakeholder inclusion in development and operationalization.

Effectiveness of a Mobile-Based Influenza-Like Illness Surveillance System (FluMob) Among Health Care Workers: Longitudinal Study

BACKGROUND

Existing studies have suggested that internet-based participatory surveillance systems are a valid sentinel for influenza-like illness (ILI) surveillance. However, there is limited scientific knowledge on the effectiveness of mobile-based ILI surveillance systems. Previous studies also adopted a passive surveillance approach and have not fully investigated the effectiveness of the systems and their determinants.

OBJECTIVE

The aim of this study was to assess the efficiency of a mobile-based surveillance system of ILI, termed FluMob, among health care workers using a targeted surveillance approach. Specifically, this study evaluated the effectiveness of the system for ILI surveillance pertaining to its participation engagement and surveillance power. In addition, we aimed to identify the factors that can moderate the effectiveness of the system.

METHODS

The FluMob system was launched in two large hospitals in Singapore from April 2016 to March 2018. A total of 690 clinical and nonclinical hospital staff participated in the study for 18 months and were prompted via app notifications to submit a survey listing 18 acute respiratory symptoms (eg, fever, cough, sore throat) on a weekly basis. There was a period of study disruption due to maintenance of the system and the end of the participation incentive between May and July of 2017.

RESULTS

On average, the individual submission rate was 41.4% (SD 24.3%), with a rate of 51.8% (SD 26.4%) before the study disruption and of 21.5% (SD 30.6%) after the disruption. Multivariable regression analysis showed that the adjusted individual submission rates were higher for participants who were older (<30 years, 31.4% vs 31-40 years, 40.2% [P<.001]; 41-50 years, 46.0% [P<.001]; >50 years, 39.9% [P=.01]), ethnic Chinese (Chinese, 44.4% vs non-Chinese, 34.7%; P<.001), and vaccinated against flu in the past year (vaccinated, 44.6% vs nonvaccinated, 34.4%; P<.001). In addition, the weekly ILI incidence was 1.07% on average. The Pearson correlation coefficient between ILI incidence estimated by FluMob and that reported by Singapore Ministry of Health was 0.04 (P=.75) with all data and was 0.38 (P=.006) including only data collected before the study disruption. Health care workers with higher risks of ILI and influenza such as women, non-Chinese, allied health staff, those who had children in their households, not vaccinated against influenza, and reported allergy demonstrated higher surveillance correlations.

CONCLUSIONS

Mobile-based ILI surveillance systems among health care workers can be effective. However, proper operation of the mobile system without major disruptions is vital for the engagement of participants and the persistence of surveillance power. Moreover, the effectiveness of the mobile surveillance system can be moderated by participants' characteristics, which highlights the importance of targeted disease surveillance that can reduce the cost of recruitment and engagement.

Elucidating user behaviours in a digital health surveillance system to correct prevalence estimates

Estimating seasonal influenza prevalence is of undeniable public health importance, but remains challenging with traditional datasets due to cost and timeliness. Digital epidemiology has the potential to address this challenge, but can introduce sampling biases that are distinct to traditional systems. In online participatory health surveillance systems, the voluntary nature of the data generating process must be considered to address potential biases in estimates. Here we examine user behaviours in one such platform, FluTracking, from 2011 to 2017. We build a Bayesian model to estimate probabilities of an individual reporting in each week, given their past reporting behaviour, and to infer the weekly prevalence of influenza-like-illness (ILI) in Australia. We show that a model that corrects for user behaviour can substantially affect ILI estimates. The model examined here elucidates several factors, such as the status of having ILI and consistency of prior reporting, that are strongly associated with the likelihood of participating in online health surveillance systems. This framework could be applied to other digital participatory health systems where participation is inconsistent and sampling bias may be of concern.

Community-based surveillance: A scoping review

Background

Involving community members in identifying and reporting health events for public health surveillance purposes, an approach commonly described as community-based surveillance (CBS), is increasingly gaining interest. We conducted a scoping review to list terms and definitions used to characterize CBS, to identify and summarize available guidance and recommendations, and to map information on past and existing in-country CBS systems.

Methods

We searched eight bibliographic databases and screened the worldwide web for any document mentioning an approach in which community members both collected and reported information on health events from their community for public health surveillance. Two independent reviewers performed double blind screening and data collection, any discrepancy was solved through discussion and consensus.

Findings

From the 134 included documents, several terms and definitions for CBS were retrieved. Guidance and recommendations for CBS were scattered through seven major guides and sixteen additional documents. Seventy-nine unique CBS systems implemented since 1958 in 42 countries were identified, mostly implemented in low and lower-middle income countries (79%). The systems appeared as fragmented (81% covering a limited geographical area and 70% solely implemented in a rural setting), vertical (67% with a single scope of interest), and of limited duration (median of 6 years for ongoing systems and 2 years for ended systems). Collection of information was mostly performed by recruited community members (80%).

Interpretation

While CBS has already been implemented in many countries, standardization is still required on the term and processes to be used. Further research is needed to ensure CBS integrates effectively into the overall public health surveillance system.

Unsupervised extraction of epidemic syndromes from participatory influenza surveillance self-reported symptoms

Seasonal influenza surveillance is usually carried out by sentinel general practitioners (GPs) who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This traditional practice for surveillance generally presents several issues, such as a delay of one week or more in releasing reports, population biases in the health-seeking behaviour, and the lack of a common definition of ILI case. On the other hand, the availability of novel data streams has recently led to the emergence of non-traditional approaches for disease surveillance that can alleviate these issues. In Europe, a participatory web-based surveillance system called Influenzanet represents a powerful tool for monitoring seasonal influenza epidemics thanks to aid of self-selected volunteers from the general population who monitor and report their health status through Internet-based surveys, thus allowing a real-time estimate of the level of influenza circulating in the population. In this work, we propose an unsupervised probabilistic framework that combines time series analysis of self-reported symptoms collected by the Influenzanet platforms and performs an algorithmic detection of groups of symptoms, called syndromes. The aim of this study is to show that participatory web-based surveillance systems are capable of detecting the temporal trends of influenza-like illness even without relying on a specific case definition. The methodology was applied to data collected by Influenzanet platforms over the course of six influenza seasons, from 2011-2012 to 2016-2017, with an average of 34,000 participants per season. Results show that our framework is capable of selecting temporal trends of syndromes that closely follow the ILI incidence rates reported by the traditional surveillance systems in the various countries (Pearson correlations ranging from 0.69 for Italy to 0.88 for the Netherlands, with the sole exception of Ireland with a correlation of 0.38). The proposed framework was able to forecast quite accurately the ILI trend of the forthcoming influenza season (2016-2017) based only on the available information of the previous years (2011-2016). Furthermore, to broaden the scope of our approach, we applied it both in a forecasting fashion to predict the ILI trend of the 2016-2017 influenza season (Pearson correlations ranging from 0.60 for Ireland and UK, and 0.85 for the Netherlands) and also to detect gastrointestinal syndrome in France (Pearson correlation of 0.66). The final result is a near-real-time flexible surveillance framework not constrained by any specific case definition and capable of capturing the heterogeneity in symptoms circulation during influenza epidemics in the various European countries.

Research Ethics in the European Influenzanet Consortium: Scoping Review

Background

Influenzanet was launched in several European countries to monitor influenza-like illness during flu seasons with the help of volunteering participants and Web-based technologies. As in the case of developing fields, ethical approaches are not well developed in the collection, processing, and analysis of participants’ information. Existing controversies and varying national ethical regulations can, thus, hamper efficient cross-border research collaboration to the detriment of quality disease surveillance.

Objective

This scoping review characterizes current practices on how ethical, legal, and social issues (ELSIs) pertinent to research ethics are handled by different Influenzanet country groups to analyze similarities and identify the need for further harmonization of ethical approaches.

Methods

A literature search was carried out on PubMed, Web of Science, Global Digital Library on Ethics, and Bioethics Literature Database to identify ELSIs for Influenzanet country platforms. Only English-language papers were included with publication dates from 2003 to 2017. Publications were screened for the application of bioethics principles in the implementation of country platforms. Additional publications gathered from the Influenzanet Consortium website, reference screening, and conference proceeding were screened for ELSIs.

Results

We gathered 96 papers from our search methodology. In total, 28 papers that mentioned ELSIs were identified and included in this study. The Research Ethics Committee (REC) approvals were sought for recruiting participants and collecting their data in 8 of 11 country platforms and informed e-consent was sought from participants in 9 of 11 country platforms. Furthermore, personal data protection was ensured throughout the Consortium using data anonymization before processing and analysis and using aggregated data.

Conclusions

Epidemics forecasting activities, such as Influenzanet, are beneficial; however, its benefits could be further increased through the harmonization of data gathering and ethical requirements. This objective is achievable by the Consortium. More transparency should be promoted concerning REC-approved research for Influenzanet-like systems. The validity of informed e-consent could also be increased through the provision of a user friendly and standard information sheet across the Consortium where participants agree to its terms, conditions, and privacy policies before being able to fill in the questionnaire. This will help to build trust in the general public while preventing any decline in participation.

Effect of Internet-based follow-up on antiviral treatment compliance and quality of life in discharged patients with chronic hepatitis B

AIM

To investigate the effect of Internet-based follow-up on antiviral treatment compliance and quality of life in discharged patients with chronic hepatitis B (CHB).

METHODS

Eighty-five discharged CHB patients who received antiviral therapy at Yuhang District Second People's Hospital of Hangzhou City from February 2016 to May 2017 were randomly divided into either an experimental group (n = 44) or a control group (n = 41). The patients in the control group were given routine telephone follow-up for 6 mo, and the patients in the experimental group were given Internet-based follow-up by using Internet service platforms (WeChat, QQ, or E-mail) for 6 mo. The antiviral treatment compliance and quality of life were evaluated using questionnaires at 1 d before follow-up and 1, 3, and 6 mo after follow-up. The compliance and quality of life were then compared between the two groups at four time points.

RESULTS

Seventy-five patients completed the study (38 cases in the experimental group and 37 cases in the control group). The compliance and life quality did not differ significantly between the two groups at 1 d before follow-up and 1 mo after follow-up in the two groups. With the extension of follow-up, the degree of compliance and the score of quality life showed an ascending trend from 1 mo after follow-up. At 6 mo after follow-up, the degree of compliance and the score of life quality in the experimental group were significantly high than those at 1 d before follow-up, and those in the control group at the same time point.

CONCLUSION

Internet-based follow-up performs better than traditional telephone follow-up with regard to improving the antiviral treatment compliance and quality of life in discharged CHB patients.

Participatory Disease Surveillance: Engaging Communities Directly in Reporting, Monitoring, and Responding to Health Threats

BACKGROUND

Since 2012, the International Workshop on Participatory Surveillance (IWOPS) has served as an informal network to share best practices, consult on analytic methods, and catalyze innovation to advance the burgeoning method of direct engagement of populations in voluntary monitoring of disease.

OBJECTIVE

This landscape provides an overview of participatory disease surveillance systems in the IWOPS network and orients readers to this growing field of practice.

METHODS

Authors reviewed participatory approaches that include human and animal health surveillance, both syndromic (self- reported symptoms) and event-based, and how these tools have been leveraged for disease modeling and forecasting. The authors also discuss benefits, challenges, and future directions for participatory disease surveillance.

RESULTS

There are at least 23 distinct participatory surveillance tools or programs represented in the IWOPS network across 18 countries. Organizations supporting these tools are diverse in nature.

CONCLUSIONS

Participatory disease surveillance is a promising method to complement both traditional, facility-based surveillance and newer digital epidemiology systems.

Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe

Background

The wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries.

Objective

In this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system.

Methods

Influenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone.

Results

In summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time.

Conclusions

Results from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases.

Factors associated with attrition in a longitudinal online study: results from the HaBIDS panel

Background

Knowing about predictors of attrition in a panel is important to initiate early measures against loss of participants. We investigated attrition in both early and late phase of an online panel with special focus on preferences regarding mode of participation.

Methods

We used data from the HaBIDS panel that was designed to investigate knowledge, attitudes, and practice regarding infections in the German general population. HaBIDS was divided into two phases: an initial phase when some participants could choose their preferred mode of participation (paper-and-pencil or online) and an extended phase when participants were asked to become members of an online panel that was not limited regarding its duration (i.e. participants initially preferring paper questionnaires switched to online participation). Using competing risks regression, we investigated two types of attrition (formal withdrawal and discontinuation without withdrawal) among online participants, separately for both phases. As potential predictors of attrition, we considered sociodemographic characteristics, physical and mental health as well as auxiliary information describing the survey process, and, in the extended phase, initial mode preference.

Results

In the initial phase, higher age and less frequent Internet usage predicted withdrawal, while younger age, higher stress levels, delay in returning the consent form, and need for receiving reminder emails predicted discontinuation. In the extended phase, only need for receiving reminder emails predicted discontinuation. Numbers of withdrawal in the extended phase were too small for analysis. Initial mode preference did not predict attrition in the extended phase. Besides age, there was no evidence of differential attrition by sociodemographic factors in any phase.

Conclusions

Predictors of attrition were similar in both phases of the panel, but they differed by type of attrition (withdrawal vs. discontinuation). Sociodemographic characteristics only played a minor role for both types of attrition. Need for receiving a reminder was the strongest predictor of discontinuation in any phase, but no predictor of withdrawal. We found predictors of attrition, which can be identified already in the early phase of a panel so that countermeasures (e.g. special incentives) can be taken.

Electronic supplementary material

The online version of this article (10.1186/s12874-017-0408-3) contains supplementary material, which is available to authorized users.

Evaluating a Web-Based Coaching Program Using Electronic Health Records for Patients With Chronic Obstructive Pulmonary Disease in China: Randomized Controlled Trial

Background

Chronic obstructive pulmonary disease (COPD) is now the fourth leading cause of death in the world, and it continues to increase in developing countries. The World Health Organization expects COPD to be the third most common cause of death in the world by 2020. Effective and continuous postdischarge care can help patients to maintain good health. The use of electronic health records (EHRs) as an element of community health care is new technology in China.

Objective

The aim of this study was to develop and evaluate a Web-based coaching program using EHRs for physical function and health-related quality of life for patients with COPD in China.

Methods

A randomized controlled trial was conducted from 2008 to 2015 at two hospitals. The control group received routine care and the intervention group received routine care with the addition of the Web-based coaching program using EHRs. These were used to manage patients’ demographic and clinical variables, publish relevant information, and have communication between patients and health care providers. Participants were not blinded to group assignment. The effects of the intervention were evaluated by lung function, including percent of forced expiratory volume in 1 second (FEV1%), percent of forced vital capacity (FVC%), peak expiratory flow (PEF), maximum midexpiratory flow; St George’s Respiratory Questionnaire (SGRQ); Modified Medical Research Council Dyspnea Scale (MMRC); and 6-Minute Walk Test (6MWT). Data were collected before the program, and at 1, 3, 6, and 12 months after the program.

Results

Of the 130 participants, 120 (92.3%) completed the 12-month follow-up program. There were statistically significant differences in lung function (FEV1%: F1,4=5.47, P=.002; FVC%: F1,4=3.06, P=.02; PEF: F1,4=12.49, P<.001), the total score of SGRQ (F1,4=23.30, P<.001), symptoms of SGRQ (F1,4=12.38, P<.001), the activity of SGRQ (F1,4=8.35, P<.001), the impact of SGRQ (F1,4=12.26, P<.001), MMRC (F1,4=47.94, P<.001), and 6MWT (F1,4=35.54, P<.001) between the two groups with the variation of time tendency.

Conclusions

The Web-based coaching program using EHRs in China appears to be useful for patients with COPD when they are discharged from hospital into the community. It promotes the sharing of patients’ medical information by hospital and community nurses, and achieves dynamic management and follow-up analysis for patients’ disease. In addition, this program can postpone the decreasing rate of lung function, improve quality of life, decrease dyspnea, and increase physical capacity.

Determinants of Participants' Follow-Up and Characterization of Representativeness in Flu Near You, A Participatory Disease Surveillance System

Background

Flu Near You (FNY) is an Internet-based participatory surveillance system in the United States and Canada that allows volunteers to report influenza-like symptoms using a brief weekly symptom report.

Objective

Our objective was to evaluate the representativeness of the FNY population compared with the general population of the United States, explore the demographic and behavioral characteristics associated with FNY’s high-participation users, and summarize results from a user survey of a cohort of FNY participants.

Methods

We compared (1) the representativeness of sex and age groups of FNY participants during the 2014-2015 flu season versus the general US population and (2) the distribution of Human Development Index (HDI) scores of FNY participants versus that of the general US population. We analyzed associations between demographic and behavioral factors and the level of participant follow-up (ie, high vs low). Finally, descriptive statistics of responses from FNY’s 2015 and 2016 end-of-season user surveys were calculated.

Results

During the 2014-2015 influenza season, 47,234 unique participants had at least one FNY symptom report that was either self-reported (users) or submitted on their behalf (household members). The proportion of female FNY participants was significantly higher than that of the general US population (n=28,906, 61.2% vs 51.1%, P<.001). Although each age group was represented in the FNY population, the age distribution was significantly different from that of the US population (P<.001). Compared with the US population, FNY had a greater proportion of individuals with HDI >5.0, signaling that the FNY user distribution was more affluent and educated than the US population baseline. We found that high-participation use (ie, higher participation in follow-up symptom reports) was associated with sex (females were 25% less likely than men to be high-participation users), higher HDI, not reporting an influenza-like illness at the first symptom report, older age, and reporting for household members (all differences between high- and low-participation users P<.001). Approximately 10% of FNY users completed an additional survey at the end of the flu season that assessed detailed user characteristics (3217/33,324 in 2015; 4850/44,313 in 2016). Of these users, most identified as being either retired or employed in the health, education, and social services sectors and indicated that they achieved a bachelor’s degree or higher.

Conclusions

The representativeness of the FNY population and characteristics of its high-participation users are consistent with what has been observed in other Internet-based influenza surveillance systems. With targeted recruitment of underrepresented populations, FNY may improve as a complementary system to timely tracking of flu activity, especially in populations that do not seek medical attention and in areas with poor official surveillance data.

Public Health Surveillance Systems: Recent Advances in Their Use and Evaluation

Surveillance is critical for improving population health. Public health surveillance systems generate information that drives action, and the data must be of sufficient quality and with a resolution and timeliness that matches objectives. In the context of scientific advances in public health surveillance, changing health care and public health environments, and rapidly evolving technologies, the aim of this article is to review public health surveillance systems. We consider their current use to increase the efficiency and effectiveness of the public health system, the role of system stakeholders, the analysis and interpretation of surveillance data, approaches to system monitoring and evaluation, and opportunities for future advances in terms of increased scientific rigor, outcomes-focused research, and health informatics.

Participatory Online Surveillance as a Supplementary Tool to Sentinel Doctors for Influenza-Like Illness Surveillance in Italy

The monitoring of seasonal influenza yearly epidemics remains one of the main activity of national syndromic surveillance systems. The development of internet-based surveillance tools has brought an innovative approach to seasonal influenza surveillance by directly involving self-selected volunteers among the general population reporting their health status on a weekly basis throughout the flu season. In this paper, we explore how Influweb, an internet-based monitoring system for influenza surveillance, deployed in Italy since 2008 has performed during three years from 2012 to 2015 in comparison with data collected during the same period by the Italian sentinel doctors surveillance system.

Web-based infectious disease surveillance systems and public health perspectives: a systematic review

BACKGROUND

Emerging and re-emerging infectious diseases are a significant public health concern, and early detection and immediate response is crucial for disease control. These challenges have led to the need for new approaches and technologies to reinforce the capacity of traditional surveillance systems for detecting emerging infectious diseases. In the last few years, the availability of novel web-based data sources has contributed substantially to infectious disease surveillance. This study explores the burgeoning field of web-based infectious disease surveillance systems by examining their current status, importance, and potential challenges.

METHODS

A systematic review framework was applied to the search, screening, and analysis of web-based infectious disease surveillance systems. We searched PubMed, Web of Science, and Embase databases to extensively review the English literature published between 2000 and 2015. Eleven surveillance systems were chosen for evaluation according to their high frequency of application. Relevant terms, including newly coined terms, development and classification of the surveillance systems, and various characteristics associated with the systems were studied.

RESULTS

Based on a detailed and informative review of the 11 web-based infectious disease surveillance systems, it was evident that these systems exhibited clear strengths, as compared to traditional surveillance systems, but with some limitations yet to be overcome. The major strengths of the newly emerging surveillance systems are that they are intuitive, adaptable, low-cost, and operated in real-time, all of which are necessary features of an effective public health tool. The most apparent potential challenges of the web-based systems are those of inaccurate interpretation and prediction of health status, and privacy issues, based on an individual's internet activity.

CONCLUSION

Despite being in a nascent stage with further modification needed, web-based surveillance systems have evolved to complement traditional national surveillance systems. This review highlights ways in which the strengths of existing systems can be maintained and weaknesses alleviated to implement optimal web surveillance systems.

Mediators of Atherosclerosis in South Asians Living in America: Use of Web-Based Methods for Follow-Up and Collection of Patient-Reported Outcome Measures

Background

A key challenge for longitudinal cohort studies is follow-up and retention of study participants. Participant follow-up in longitudinal cohort studies is costly and time-consuming for research staff and participants.

Objective

This study determined the feasibility and costs of using Web-based technologies for follow-up and collection of patient-reported outcomes in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study.

Methods

The MASALA study is a community-based cohort of 906 South Asians in the United States. Since the baseline in-person visits (2010-2013), a yearly telephone follow-up survey was used to assess participants’ health status and incidence of cardiovascular disease. A Web-based version of the follow-up survey was developed using the REDCap (Research Electronic Data Capture) Web app. Participants from the Chicago field center who were due for their annual follow-up and who had a valid email address were sent an email link to a secure online portal where they could complete the survey. Telephone follow-up was used with nonresponders.

Results

A link to the Web survey was emailed to 285 participants (February to October 2014) and the overall completion rate was 47.7% (136/285). One-third of participants who were unresponsive (n=36) to annual telephone follow-up completed the Web survey. Web responders were younger, more likely to be married, and to have higher education and income compared (P<.05) to telephone-only responders. Web survey development involved 240 hours of research staff time. Since launching, the Web-based survey has required 3 hours per week of staff time.

Conclusions

Although electronic follow-up will not be a panacea for cohort operations, it will serve as an adjunctive strategy to telephonic follow-up for maximizing cohort retention with lower costs.

First nationwide web-based surveillance system for influenza-like illness in pregnant women: participation and representativeness of the French G-GrippeNet cohort

Background

Pregnancy is a risk factor for severe influenza resulting in increased risks of hospitalisation and death in mothers and their new-borns. Our objective was to assess the representativeness and participation of French women to a new web-based collaborative tool for data collection and monitoring of Influenza Like Illness (ILI) during pregnancy.

Methods

During the 2014/2015 influenza season, pregnant women living in metropolitan France were enrolled through a web platform (https://www.grippenet.fr/). Then throughout the season, participants were asked to report, on a weekly basis, if they had experienced symptoms of ILI. Representativeness was assessed by comparing the characteristics of participants to those of the French National Perinatal Survey. For each participant, the participation rate was the number of weekly questionnaires completed, divided by the length of follow-up (in weeks). Predictors of active participation (participation rate >15 %) were assessed by multivariate logistic regression.

Results

A total of 153 women were enrolled. Participants were older (mean age 34 years vs. 29 years) and more highly educated (high school level 89 % versus 52 %) than the general population of pregnant women in France, but the sample did not differ on pregnancy-related characteristics (parity, history of hospitalisation during a previous pregnancy). The median rate of participation was high (78 %, interquartile range: 34–96). Higher educational level and participation to a previous GrippeNet.fr season were associated with active participation.

Conclusion

Despite small sample size and lack of representativeness, the retention rate was high, suggesting that pregnant women are prone to adhere to a longitudinal follow-up of their health status via the Internet.

Flu Near You: Crowdsourced Symptom Reporting Spanning 2 Influenza Seasons

OBJECTIVES

We summarized Flu Near You (FNY) data from the 2012-2013 and 2013-2014 influenza seasons in the United States.

METHODS

FNY collects limited demographic characteristic information upon registration, and prompts users each Monday to report symptoms of influenza-like illness (ILI) experienced during the previous week. We calculated the descriptive statistics and rates of ILI for the 2012-2013 and 2013-2014 seasons. We compared raw and noise-filtered ILI rates with ILI rates from the Centers for Disease Control and Prevention ILINet surveillance system.

RESULTS

More than 61 000 participants submitted at least 1 report during the 2012-2013 season, totaling 327 773 reports. Nearly 40 000 participants submitted at least 1 report during the 2013-2014 season, totaling 336 933 reports. Rates of ILI as reported by FNY tracked closely with ILINet in both timing and magnitude.

CONCLUSIONS

With increased participation, FNY has the potential to serve as a viable complement to existing outpatient, hospital-based, and laboratory surveillance systems. Although many established systems have the benefits of specificity and credibility, participatory systems offer advantages in the areas of speed, sensitivity, and scalability.

How computer literacy and socioeconomic status affect attitudes toward a Web-based cohort: results from the NutriNet-Santé study

BACKGROUND

In spite of the growing literature in the field of e-epidemiology, clear evidence about computer literacy or attitudes toward respondent burden among e-cohort participants is largely lacking.

OBJECTIVE

We assessed the computer and Internet skills of participants in the NutriNet-Santé Web-based cohort. We then explored attitudes toward the study demands/respondent burden according to levels of computer literacy and sociodemographic status.

METHODS

Self-reported data from 43,028 e-cohort participants were collected in 2013 via a Web-based questionnaire. We employed unconditional logistic and linear regression analyses.

RESULTS

Approximately one-quarter of participants (23.79%, 10,235/43,028) reported being inexperienced in terms of computer use. Regarding attitudes toward participant burden, women tended to be more favorable (eg, "The overall website use is easy") than were men (OR 0.65, 95% CI 0.59-0.71, P<.001), whereas better educated participants (>12 years of schooling) were less likely to accept the demands associated with participation (eg, "I receive questionnaires too often") compared to their less educated counterparts (OR 1.62, 95% CI 1.48-1.76, P<.001).

CONCLUSIONS

A substantial proportion of participants had low computer/Internet skills, suggesting that this does not represent a barrier to participation in Web-based cohorts. Our study also suggests that several subgroups of participants with lower computer skills (eg, women or those with lower educational level) might more readily accept the demands associated with participation in the Web cohort. These findings can help guide future Web-based research strategies.

Association between recruitment methods and attrition in Internet-based studies

Internet-based systems for epidemiological studies have advantages over traditional approaches as they can potentially recruit and monitor a wider range of individuals in a relatively inexpensive fashion. We studied the association between communication strategies used for recruitment (offline, online, face-to-face) and follow-up participation in nine Internet-based cohorts: the Influenzanet network of platforms for influenza surveillance which includes seven cohorts in seven different European countries, the Italian birth cohort Ninfea and the New Zealand birth cohort ELF. Follow-up participation varied from 43% to 89% depending on the cohort. Although there were heterogeneities among studies, participants who became aware of the study through an online communication campaign compared with those through traditional offline media seemed to have a lower follow-up participation in 8 out of 9 cohorts. There were no clear differences in participation between participants enrolled face-to-face and those enrolled through other offline strategies. An Internet-based campaign for Internet-based epidemiological studies seems to be less effective than an offline one in enrolling volunteers who keep participating in follow-up questionnaires. This suggests that even for Internet-based epidemiological studies an offline enrollment campaign would be helpful in order to achieve a higher participation proportion and limit the cohort attrition.

Evaluation of an Internet-based monitoring system for influenza-like illness in Sweden

To complement traditional influenza surveillance with data on disease occurrence not only among care-seeking individuals, the Swedish Institute for Communicable Disease Control (SMI) has tested an Internet-based monitoring system (IMS) with self-recruited volunteers submitting weekly on-line reports about their health in the preceding week, upon weekly reminders. We evaluated IMS acceptability and to which extent participants represented the Swedish population. We also studied the agreement of data on influenza-like illness (ILI) occurrence from IMS with data from a previously evaluated population-based system (PBS) with an actively recruited random sample of the population who spontaneously report disease onsets in real-time via telephone/Internet, and with traditional general practitioner based sentinel and virological influenza surveillance, in the 2011-2012 and 2012-2013 influenza seasons. We assessed acceptability by calculating the participation proportion in an invited IMS-sample and the weekly reporting proportion of enrolled self-recruited IMS participants. We compared distributions of socio-demographic indicators of self-recruited IMS participants to the general Swedish population using chi-square tests. Finally, we assessed the agreement of weekly incidence proportions (%) of ILI in IMS and PBS with cross-correlation analyses. Among 2,511 invited persons, 166 (6.6%) agreed to participate in the IMS. In each season, 2,552 and 2,486 self-recruited persons participated in the IMS respectively. The weekly reporting proportion among self-recruited participants decreased from 87% to 23% (2011-2012) and 82% to 45% (2012-2013). Women, highly educated, and middle-aged persons were overrepresented among self-recruited IMS participants (p<0.01). IMS (invited and self-recruited) and PBS weekly incidence proportions correlated strongest when no lags were applied (r = 0.71 and r = 0.69, p<0.05). This evaluation revealed socio-demographic misrepresentation and limited compliance among the self-recruited IMS participants. Yet, IMS offered a reasonable representation of the temporal ILI pattern in the community overall during the 2011-2012 and 2012-2013 influenza seasons and could be a simple tool for collecting community-based ILI data.