Internet-based monitoring of influenza-like illness in the general population: experience of five influenza seasons in The Netherlands

Cost-effectiveness of high-dose influenza vaccination in the Netherlands: Incorporating the impact on both respiratory and cardiovascular hospitalizations

OBJECTIVES

We assess the cost-effectiveness of switching from standard-dose quadrivalent influenza vaccination (SD-QIV) to high-dose vaccination (HD-QIV) for Dutch adults aged 60 years and older.

METHODS

A health-economic model was used to compare the scenario where HD-QIV was implemented compared to the current standard, SD-QIV. This model used a lifetime horizon and assessed the cost-effectiveness from a societal perspective. A recently published meta-analysis was used to incorporate the benefits of HD-QIV, including cardiorespiratory hospitalizations, in analyses considering RCT only or combining RCT and RWE estimates in a scenario analysis.

RESULTS

Implementing HD-QIV is cost effective at its list price, with an ICER of €5,400 per QALY gained. The main driver of these results is the prevention of cardiorespiratory hospitalizations. Other public health benefits are the prevention of GP consults and deaths. HD-QIV is highly likely to be cost-effective, reaching a 100% probability of being cost effective at the Dutch willingness-to-pay threshold of €20,000 per QALY.

CONCLUSIONS

Implementing HD-QIV for adults aged 60 and over within the existing influenza vaccination campaign is highly cost effective. HD-QIV may support alleviating potential capacity issues in Dutch hospitals in the winter respiratory season.

Calculating incidence of Influenza-like and COVID-like symptoms from Flutracking participatory survey data

This article describes a new method for estimating weekly incidence (new onset) of symptoms consistent with Influenza and COVID-19, using data from the Flutracking survey. The method mitigates some of the known self-selection and symptom-reporting biases present in existing approaches to this type of participatory longitudinal survey data. The key novel steps in the analysis are: 1) Identifying new onset of symptoms for three different Symptom Groupings: COVID-like illness (CLI1+, CLI2+), and Influenza-like illness (ILI), for responses reported in the Flutracking survey. 2) Adjusting for symptom reporting bias by restricting the analysis to a sub-set of responses from those participants who have consistently responded for a number of weeks prior to the analysis week. 3) Weighting responses by age to adjust for self-selection bias in order to account for the under- and over-representation of different age groups amongst the survey participants. This uses the survey package [22] in R [30]. 4) Constructing 95% point-wise confidence bands for incidence estimates using weighted logistic regression from the survey package [21] in R [28]. In addition to describing these steps, the article demonstrates an application of this method to Flutracking data for the 12 months from 27th April 2020 until 25th April 2021.

Exploratory Analysis of the Economically Justifiable Price of a Hypothetical RSV Vaccine for Older Adults in the Netherlands and the United Kingdom

Background

In older adults, the burden of respiratory syncytial virus (RSV) resembles that of influenza and may even be considered worse due to the lack of preventive interventions. This study was performed to identify the available literature on RSV infection in older adults, and to provide updated exploratory results of the cost-effectiveness of a hypothetical RSV vaccine in the Netherlands and the United Kingdom.

Methods

A literature search was performed in Medline and EMBASE on 11 November 2019, which served as input for a static decision-tree model that was used to estimate the EJP, for an RSV vaccine applying different willingness-to-pay (WTP) thresholds. WTP thresholds applied were €20 000 and €50 000 per quality-adjusted life-year for the Netherlands, and £20 000 and £30 000 per quality-adjusted life-year for the United Kingdom. Analyses were—in line with country-specific guidelines—conducted from a societal perspective for the Netherlands and a third-party payer perspective for the United Kingdom. The robustness of the cost-effectiveness results was tested in sensitivity analysis.

Results

After screening the literature, 3 studies for the Netherlands and 6 for the United Kingdom remained to populate the country-specific models. In the base case analysis for the Netherlands (mean RSV incidence, 3.32%), justifiable vaccine prices of €16.38 and €50.03 were found, based on applying the lower and higher WTP thresholds, respectively. Similarly, for the United Kingdom (mean incidence, 7.13%), vaccine prices of £72.29 and £109.74 were found, respectively.

Conclusion

RSV vaccination may well be cost-effective in both the Netherlands and the United Kingdom, depending on the exact RSV incidence, vaccine effectiveness and price. However, sensitivity analysis showed that the results were robust based on varying the different parameter estimates and assumptions. With RSV vaccines reaching the final stages of development, a strong need exists for cost-effectiveness studies to understand economically justifiable pricing of the vaccine.

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.

Participatory COVID-19 Surveillance Tool in Rural Appalachia : Real-Time Disease Monitoring and Regional Response

INTRODUCTION

Few US studies have examined the usefulness of participatory surveillance during the coronavirus disease 2019 (COVID-19) pandemic for enhancing local health response efforts, particularly in rural settings. We report on the development and implementation of an internet-based COVID-19 participatory surveillance tool in rural Appalachia.

METHODS

A regional collaboration among public health partners culminated in the design and implementation of the COVID-19 Self-Checker, a local online symptom tracker. The tool collected data on participant demographic characteristics and health history. County residents were then invited to take part in an automated daily electronic follow-up to monitor symptom progression, assess barriers to care and testing, and collect data on COVID-19 test results and symptom resolution.

RESULTS

Nearly 6500 county residents visited and 1755 residents completed the COVID-19 Self-Checker from April 30 through June 9, 2020. Of the 579 residents who reported severe or mild COVID-19 symptoms, COVID-19 symptoms were primarily reported among women (n = 408, 70.5%), adults with preexisting health conditions (n = 246, 70.5%), adults aged 18-44 (n = 301, 52.0%), and users who reported not having a health care provider (n = 131, 22.6%). Initial findings showed underrepresentation of some racial/ethnic and non-English-speaking groups.

PRACTICAL IMPLICATIONS

This low-cost internet-based platform provided a flexible means to collect participatory surveillance data on local changes in COVID-19 symptoms and adapt to guidance. Data from this tool can be used to monitor the efficacy of public health response measures at the local level in rural Appalachia.

Cost-Effectiveness of Quadrivalent Versus Trivalent Influenza Vaccination in the Dutch National Influenza Prevention Program

OBJECTIVES

As of 2019, quadrivalent influenza vaccine (QIV) has replaced trivalent influenza vaccine (TIV) in the national immunization program in The Netherlands. Target groups are individuals of 60+ years of age and those with chronic diseases. The objective was to estimate the incremental break-even price of QIV over TIV at a threshold of €20 000 per quality-adjusted life-year (QALY).

METHODS

An age-structured compartmental dynamic model was adapted for The Netherlands to assess health outcomes and associated costs of vaccinating all individuals at higher risk for influenza with QIV instead of TIV over the seasons 2010 to 2018. Influenza incidence rates were derived from a global database. Other parameters (probabilities, QALYs and costs) were extracted from the literature and applied according to Dutch guidelines. A threshold of €20 000 per QALY was applied to estimate the incremental break-even prices of QIV versus TIV. Sensitivity analyses were performed to test the robustness of the model outcomes.

RESULTS

Retrospectively, vaccination with QIV instead of TIV could have prevented on average 9500 symptomatic influenza cases, 2130 outpatient visits, 84 hospitalizations, and 38 deaths per year over the seasons 2010 to 2018. This translates into 385 QALYs and 398 life-years potentially gained. On average, totals of €431 527 direct and €2 388 810 indirect costs could have been saved each year.

CONCLUSION

Using QIV over TIV during the influenza seasons 2010 to 2018 would have been cost-effective at an incremental price of maximally €3.81 (95% confidence interval, €3.26-4.31). Sensitivity analysis showed consistent findings on the incremental break-even price in the same range.

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.

Severe Salmonella spp. or Campylobacter spp. Infection and the Risk of Biliary Tract Cancer: A Population-Based Study

Simple Summary

Although it is known that bacterial infection may increase risk of cancer, the relationship between certain infections and cancer remains ill-quantified. To identify potential risk factors, this study compared the incidence of biliary tract cancer (BTC) in patients with Salmonella spp. or Campylobacter spp. infection to the general population in a large Western cohort of 16,252 salmonellosis and 27,668 campylobacteriosis patients. Standardized relative incidence ratio for BTC was 1.53 (95% CI 0.70–2.91) in salmonellosis patients and 0.97 (95% CI 0.39–2.00) in campylobacteriosis patients. Patients with Salmonella spp. infection and BTC were significantly younger than BTC patients without Salmonella spp. infection. Potentially, the study was underpowered to detect differences in cancer incidence, or cancer etiology in Western patients differs from those in non-Western countries and instead of bacterial infection, other factors contribute to cancer risk. Better understanding of cancer etiology is needed to identify risk factors and facilitate screening and early detection of cancer patients.

Abstract

Salmonella spp. infection has shown to have oncogenic transformative effects and thereby increases the risk of certain cancers. For Campylobacter spp., similar effects have been demonstrated. Risk factor identification may allow for timely diagnosis and preventive treatment. To substantiate the oncogenic potential of Salmonella and Campylobacter spp., this study compared the incidence of extrahepatic biliary tract cancer (BTC) in patients with diagnosed Salmonella or Campylobacter spp. infection with BTC incidence in the Netherlands. National infectious diseases surveillance records of patients diagnosed with a laboratory-confirmed Salmonella or Campylobacter spp. infection during 1999–2016 were linked to the Netherlands Cancer Registry. Incidence of BTC in Salmonella and Campylobacter spp. patients was compared to the incidence of BTC in the general population using Standardized Incidence Ratios (SIRs). In total, 16,252 patients were diagnosed with Salmonella spp. and 27,668 with Campylobacter spp. infection. Nine patients developed BTC at a median of 46 months (13–67) after Salmonella spp. infection and seven at a median of 60 months (18–138) after Campylobacter spp. infection. SIR of BTC in salmonellosis patients was 1.53 (95% CI 0.70–2.91). In patients aged <60 years, the SIR was 1.74 (95% CI 0.36–5.04). For campylobacteriosis patients, the SIR was 0.97 (95% CI 0.39–2.00). Even though Salmonella or Campylobacter spp. infection was not significantly associated with increased BTC risk in this cohort, it remains extremely important to study potential risk factors for cancer to facilitate screening and ultimately improve prognosis of cancer patients.

Substantial underestimation of SARS-CoV-2 infection in the United States

Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Here, we use a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy. We estimate 6,454,951 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) in the United States as of April 18, 2020. Accounting for uncertainty, the number of infections during this period was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference is due to incomplete testing, while 14% (0.3-36%) is due to imperfect test accuracy. The approach can readily be applied in future studies in other locations or at finer spatial scale to correct for biased testing and imperfect diagnostic accuracy to provide a more realistic assessment of COVID-19 burden.

Grippenet: A New Tool for the Monitoring, Risk-Factor and Vaccination Coverage Analysis of Influenza-Like Illness in Switzerland

Implemented in Switzerland in November 2016, Grippenet provides Internet-based participatory surveillance of influenza-like illness (ILI). The aim of this research is to test the feasibility of such a system and its ability to detect risk factors and to assess ILI-related behaviors. Participants filled in a web-based socio-demographic and behavioral questionnaire upon registration, and a weekly symptoms survey during the influenza season. ILI incidence was calculated weekly, and risk factors associated to ILI were analyzed at the end of each season. From November 2016 to May 2019, 1247 participants were included. The crossing of the Sentinel System (Sentinella) epidemic threshold was associated with an increase or decrease of Grippenet ILI incidence, within the same week or earlier. The number of active users varied according to ILI incidence. Factors associated with ILI were: ages 0–4 compared with 5–14 (adjusted odds ratio (AOR) 0.6, 95% confidence interval (CI) 0.19–0.99), 15–29 (AOR 0.29, 95% CI 0.15–0.60), and 65+ (AOR 0.38, 95% CI 0.16–0.93); female sex (male AOR 0.81, 95% CI 0.7–0.95); respiratory allergies (AOR 1.58, 95% CI 1.38–1.96), not being vaccinated (AOR 2.4, 95% CI 1.9–3.04); and self-employment (AOR 1.97, 95% CI 1.33–3.03). Vaccination rates were higher than those of the general population but not high enough to meet the Swiss recommendations. Approximately, 36.2% to 42.5% of users who reported one or more ILIs did not seek medical attention. These results illustrate the potential of Grippenet in complementing Sentinella for ILI monitoring in Switzerland.

Vaccinating children against influenza: overall cost-effective with potential for undesirable outcomes

BACKGROUND

The present study aims to assess the cost-effectiveness of an influenza vaccination program for children in the Netherlands. This requires an evaluation of the long-term impact of such a program on the burden of influenza across all age groups, using a transmission model that accounts for the seasonal variability in vaccine effectiveness and the shorter duration of protection following vaccination as compared to natural infection.

METHODS

We performed a cost-effectiveness analysis based on a stochastic dynamic transmission model that has been calibrated to reported GP visits with influenza-like illness in the Netherlands over 11 seasons (2003/2004 to 2014/2015). We analyzed the costs and effects of extending the current program with vaccination of children aged 2-16 years at 50% coverage over 20 consecutive seasons. We measured the effects in quality-adjusted life-years (QALYs) and we adopted a societal perspective.

RESULTS

The childhood vaccination program is estimated to have an average incremental cost-effectiveness ratio (ICER) of €3944 per QALY gained and is cost-effective in the general population (across 1000 simulations; conventional Dutch threshold of €20,000 per QALY gained). The childhood vaccination program is not estimated to be cost-effective for the target-group itself with an average ICER of €57,054 per QALY gained. Uncertainty analyses reveal that these ICERs hide a wide range of outcomes. Even though introduction of a childhood vaccination program decreases the number of infections, it tends to lead to larger epidemics: in 23.3% of 1000 simulations, the childhood vaccination program results in an increase in seasons with a symptomatic attack rate larger than 5%, which is expected to cause serious strain on the health care system. In 6.4% of 1000 simulations, the childhood vaccination program leads to a net loss of QALYs. These findings are robust across different targeted age groups and vaccination coverages.

CONCLUSIONS

Modeling indicates that childhood influenza vaccination is cost-effective in the Netherlands. However, childhood influenza vaccination is not cost-effective when only outcomes for the children themselves are considered. In approximately a quarter of the simulations, the introduction of a childhood vaccination program increases the frequency of seasons with a symptomatic attack rate larger than 5%. The possibility of an overall health loss cannot be excluded.

Syndromic surveillance using web data: a systematic review

During the recent years, a lot of debate is taken place about the evolution of Smart Healthcare systems. Particularly, how these systems can help people improve human conditions of health, by taking advantages of the new Information and Communication Technologies (ICT), regarding early prediction and efficient treatment. The purpose of this study is to provide a systematic review of the current literature available that focuses on information systems on syndromic surveillance using web data. All published items concern articles, books, reviews, reports, conference announcements, and dissertations. We used a variation of PRISMA Statements methodology to conduct a systematic review. The review identifies the relevant published papers from the year 2004 to 2018, systematically includes and explores them to extract similarities, gaps, and conclusions on the research that has been done so far. The results presented concern the year, the examined disease, the web data source, the geographic location/country, and the data analysis method used. The results show that influenza is the most examined infectious disease. The internet tools most used are Twitter and Google. Regarding the geographical areas explored in the published papers, the most examined country is the United States, since many scientists come from this country. There is a significant growth of articles since 2009. There are also various statistical methods used to correlate the data retrieved from the internet to the data from national authorities. The conclusion of all researches is that the Web can be a useful tool for the detection of serious epidemics and for a creation of a syndromic surveillance system using the Web, since we can predict epidemics from web data before they are officially detected in population. With the advance of ICT, Smart Healthcare can benefit from the monitoring of epidemics and the early prediction of such a system, improving national or international health strategies and policy decision. This can be achieved through the provision of new technology tools to enhance health monitoring systems toward the new innovations of Smart Health or eHealth, even with the emerging technologies of Internet of Things. The challenges and impacts of an electronic system based on internet data include the social, medical, and technological disciplines. These can be further extended to Smart Healthcare, as the data streaming can provide with real-time information, awareness on epidemics and alerts for both patients or medical scientists. Finally, these new systems can help improve the standards of human life.

Plasmacytoid dendritic cell and myeloid dendritic cell function in ageing: A comparison between elderly and young adult women

Ageing is associated with a changing immune system, leading to inflammageing (increased levels of inflammation markers in serum) and immunosenescence (reduced immune cells and reduced responses towards pathogens). This results in reduced vaccination responses and increased infections in elderly. Much is known about the adaptive immune system upon ageing, but less is known about the innate immune system. Therefore, the aim of this study was to compare innate immune function of Toll like receptor (TLR)-mediated responses between elderly and young adult women.

To this end, elderly and young adult women were compared to study the effect of ageing on the relative prevalence and reactivity to TLR-mediated responses of myeloid- and plasmacytoid dendritic cells (mDC, pDC). In addition, TLR expression and inflammatory markers in serum were investigated. Elderly women had reduced numbers of circulating pDCs. In addition, pDCs and mDCs of elderly women responded differently towards TLR stimulation, especially TLR7/8 mediated stimulation was reduced, compared to young adults. In serum, markers involved in inflammation were generally increased in elderly. In conclusion, this study confirms and extends the knowledge about immunosenescence and inflammageing on innate immunity in elderly women.

Participatory Disease Surveillance Systems: Ethical Framework

Advances in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging digital (eg, Web-based) communities of volunteer citizens to report symptoms and other pertinent information on public health threats and also by empowering individuals to promptly respond to them. However, this digital model raises ethical issues on top of those inherent in traditional forms of public health surveillance. Research ethics are undergoing significant changes in the digital era where not only participants' physical and psychological well-being but also the protection of their sensitive data have to be considered. In this paper, the digital platform of Influenzanet is used as a case study to illustrate those ethical challenges posed to participatory surveillance systems using digital platforms and mobile apps. These ethical challenges include the implementation of electronic consent, the protection of participants' privacy, the promotion of justice, and the need for interdisciplinary capacity building of research ethics committees. On the basis of our analysis, we propose a framework to regulate and strengthen ethical approaches in the field of digital public health surveillance.

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.

The incidence of symptomatic infection with influenza virus in the Netherlands 2011/2012 through 2016/2017, estimated using Bayesian evidence synthesis

Due to differences in the circulation of influenza viruses, distribution and antigenic drift of A subtypes and B lineages, and susceptibility to infection in the population, the incidence of symptomatic influenza infection can vary widely between seasons and age-groups. Our goal was to estimate the symptomatic infection incidence in the Netherlands for the six seasons 2011/2012 through 2016/2017, using Bayesian evidence synthesis methodology to combine season-specific sentinel surveillance data on influenza-like illness (ILI), virus detections in sampled ILI cases and data on healthcare-seeking behaviour. Estimated age-aggregated incidence was 6.5 per 1000 persons (95% uncertainty interval (UI): 4.7–9.0) for season 2011/2012, 36.7 (95% UI: 31.2–42.8) for 2012/2013, 9.1 (95% UI: 6.3–12.9) for 2013/2014, 41.1 (95% UI: 35.0–47.7) for 2014/2015, 39.4 (95% UI: 33.4–46.1) for 2015/2016 and 27.8 (95% UI: 22.7–33.7) for season 2016/2017. Incidence varied substantially between age-groups (highest for the age-group <5 years: 23 to 47/1000, but relatively low for 65+ years: 2 to 34/1000 over the six seasons). Integration of all relevant data sources within an evidence synthesis framework has allowed the estimation – with appropriately quantified uncertainty – of the incidence of symptomatic influenza virus infection. These estimates provide valuable insight into the variation in influenza epidemics across seasons, by virus subtype and lineage, and between age-groups.

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.

The potential value of crowdsourced surveillance systems in supplementing sentinel influenza networks: the case of France

IntroductionParticipatory surveillance systems provide rich crowdsourced data, profiling individuals and their health status at a given time. We explored the usefulness of data from GrippeNet.fr, a participatory surveillance system, to estimate influenza-related illness incidence in France. Methods: GrippeNet.fr is an online cohort since 2012 averaging ca. 5,000 weekly participants reporting signs/symptoms suggestive of influenza. GrippeNet.fr has flexible criteria to define influenza-related illness. Different case definitions based on reported signs/symptoms and inclusions of criteria accounting for individuals' reporting and participation were used to produce influenza-related illness incidence estimates, which were compared to those from sentinel networks. We focused on the 2012/13 and 2013/14 seasons when two sentinel networks, monitoring influenza-like-illness (ILI) and acute respiratory infections (ARI) existed in France. Results: GrippeNet.fr incidence estimates agreed well with official temporal trends, with a higher accuracy for ARI than ILI. The influenza epidemic peak was often anticipated by one week, despite irregular participation of individuals. The European Centre for Disease Prevention and Control ILI definition, commonly used by participatory surveillance in Europe, performed better in tracking ARI than ILI when applied to GrippeNet.fr data. Conclusion: Evaluation of the epidemic intensity from crowdsourced data requires epidemic and intensity threshold estimations from several consecutive seasons. The study provides a standardised analytical framework for crowdsourced surveillance showing high sensitivity in detecting influenza-related changes in the population. It contributes to improve the comparability of epidemics across seasons and with sentinel systems. In France, GrippeNet.fr may supplement the ILI sentinel network after ARI surveillance discontinuation in 2014.

The potential economic value of influenza vaccination for healthcare workers in The Netherlands

Background

Despite the clinical evidence, influenza vaccination coverage of healthcare workers remains low. To assess the health economic value of implementing an influenza immunization program among healthcare workers (HCW) in University Medical Centers (UMCs) in the Netherlands, a cost‐benefit model was developed using a societal perspective.

Methods/Patients

The model was based on a trial performed among all UMCs in the Netherlands that included both hospital staff and patients admitted to the pediatrics and internal medicine departments. The model structure and parameters estimates were based on the trial and complemented with literature research, and the impact of uncertainty explored with sensitivity analyses.

Results

In a base‐case scenario without vaccine coverage, influenza‐related annual costs were estimated at € 410 815 for an average UMC with 8000 HCWs and an average occupancy during the influenza period of 6000 hospitalized patients. Of these costs, 82% attributed to the HCWs and 18% were patient‐related. With a vaccination coverage of 15.47%, the societal program’s savings were € 2861 which corresponds to a saving of € 270.53 per extended hospitalization. Univariate sensitivity analyses show that the results are most sensitive to changes in the model parameters vaccine effectiveness in reducing influenza‐like illness (ILI) and the vaccination‐related costs.

Conclusion

In addition to the decreased burden of patient morbidity among hospitalized patients, the effects of the hospital immunization program slightly outweigh the economic investments. These outcomes may support healthcare policymakers’ recommendations about the influenza vaccination program for healthcare workers.

Increased colon cancer risk after severe Salmonella infection

BACKGROUND

Colon cancer constitutes one of the most frequent malignancies. Previous studies showed that Salmonella manipulates host cell signaling pathways and that Salmonella Typhimurium infection facilitates colon cancer development in genetically predisposed mice. This epidemiological study examined whether severe Salmonella infection, usually acquired from contaminated food, is associated with increased colon cancer risk in humans.

METHODS AND FINDINGS

We performed a nationwide registry-based study to assess colon cancer risk after diagnosed Salmonella infection. National infectious disease surveillance records (1999-2015) for Dutch residents aged ≥20 years when diagnosed with salmonellosis (n = 14,264) were linked to the Netherlands Cancer Registry. Salmonella-infected patients were laboratory-confirmed under medical consultation after 1-2 weeks of illness. These datasets also contained information on Salmonella serovar and type of infection. Colon cancer risk (overall and per colon subsite) among patients with a diagnosed Salmonella infection was compared with expected colon cancer risk in the general population. Data from the nationwide registry of histo- and cytopathology (PALGA) and Statistics Netherlands (CBS) allowed assessing potential effects of age, gender, latency, socioeconomic status, genetic predisposition, inflammatory bowel disease (IBD), and tumor features. We found that compared to the general population, colon cancer risk was significantly increased (standardized incidence ratio [SIR] 1.54; 95%CI 1.09-2.10) among patients with Salmonella infection diagnosed <60 years of age. Such increased risk concerned specifically the ascending/transverse colon (SIR 2.12; 95%CI 1.38-3.09) after S. Enteritidis infection (SIR 2.97; 95%CI 1.73-4.76). Salmonellosis occurred more frequently among colon cancer patients with pre-infectious IBD, a known risk factor for colon cancer. Colon tumors of patients with a history of Salmonella infection were mostly of low grade.

CONCLUSIONS

Patients diagnosed with severe salmonellosis have an increased risk of developing cancer in the ascending/transverse parts of the colon. This risk concerns particularly S. Enteritidis infection, suggesting a contribution of this major foodborne pathogen to colon cancer development.

Healthcare-seeking behaviour in case of influenza-like illness in the French general population and factors associated with a GP consultation: an observational prospective study

Background

GP consultation rates for influenza-like illness (ILI) are poorly known in France and there is a paucity of literature on this topic. In the few articles that have been published, the results are heterogeneous.

Aim

The aim of the present study was to estimate the proportion of ILI inducing a GP consultation, and to assess its determinants.

Design & setting

Participants of a French web-based cohort study who reported ≥1 ILI episode between 2012 and 2015 were included. Sociodemographic characteristics, access to health care, and health status variables were collected.

Method

Healthcare-seeking behaviour was analysed and factors associated with a GP consultation identified using a conditional logistic regression.

Results

Of the 6023 ILI episodes reported, 1961 (32.6%) led to a GP consultation, with no difference between those at risk of influenza complications and those not (P = 0.42). A GP consultation was more frequent for individuals living in a rural area (odds ratio [OR] = 1.21, 95% confidence interval [CI] = 1.02 to 1.43); those with a lower educational level (OR = 1.43, 95% CI = 1.18 to 1.74); those using the internet to find information about influenza (OR = 1.63, 95% CI = 1.30 to 2.03); patients presenting with worrying symptoms (fever, cough, dyspnoea, sputum, or asthenia); patients having a negative perception of their own health status (OR = 1.51, 95% CI = 1.07 to 2.13; and those having declared a personal doctor (OR = 2.86, 95% CI = 1.72 to 4.76). A GP consultation was less frequent for individuals using alternative medicine (OR = 0.68, 95% CI = 0.58 to 0.78).

Conclusion

This study allows the identification of specific factors associated with GP consultation for an ILI episode. These findings may help to coordinate health information campaigns and to raise awareness, especially among individuals at risk of influenza complications.

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.

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design

Background

Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic “big data” from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics.

Objective

The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county.

Methods

An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source.

Results

The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning of a winter influenza season has an exponential growth of infected individuals. For prediction modeling, linear regression was applied on 7-day periods at the time in order to find the peak timing, whereas a derivate of a normal distribution density function was used to find the peak intensity. We found that the integrated detection and prediction method detected the 2008-09 winter influenza season on its starting day (optimal timeliness 0 days), whereas the predicted peak was estimated to occur 7 days ahead of the factual peak and the predicted peak intensity was estimated to be 26% lower than the factual intensity (6.3 compared with 8.5 influenza-diagnosis cases/100,000).

Conclusions

Our detection and prediction method is one of the first integrated methods specifically designed for local application on influenza data electronically available for surveillance. The performance of the method in a retrospective study indicates that further prospective evaluations of the methods are justified.

High added value of a population-based participatory surveillance system for community acute gastrointestinal, respiratory and influenza-like illnesses in Sweden, 2013-2014 using the web

In 2013-2014, the Public Health Agency of Sweden developed a web-based participatory surveillance system, Hӓlsorapport, based on a random sample of individuals reporting symptoms weekly online, to estimate the community incidence of self-reported acute gastrointestinal (AGI), acute respiratory (ARI) and influenza-like (ILI) illnesses and their severity. We evaluated Hӓlsorapport's acceptability, completeness, representativeness and its data correlation with other surveillance data. We calculated response proportions and Spearman correlation coefficients (r) between (i) incidence of illnesses in Hӓlsorapport and (ii) proportions of specific search terms to medical-advice website and reasons for calling a medical advice hotline. Of 34 748 invitees, 3245 (9·3%) joined the cohort. Participants answered 81% (139 013) of the weekly questionnaires and 90% (16 351) of follow-up questionnaires. AGI incidence correlated with searches on winter-vomiting disease [r = 0·81, 95% confidence interval (CI) 0·69-0·89], and ARI incidence correlated with searches on cough (r = 0·77, 95% CI 0·62-0·86). ILI incidence correlated with the web query-based estimated incidence of ILI patients consulting physicians (r = 0·63, 95% CI 0·42-0·77). The high response to different questionnaires and the correlation with other syndromic surveillance systems suggest that Hӓlsorapport offers a reasonable representation of AGI, ARI and ILI patterns in the community and can complement traditional and syndromic surveillance systems to estimate their burden in the community.

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.

Comparison of different collection methods for reported adverse events following pandemic and seasonal influenza vaccination

BACKGROUND

During the 2009/2010 season, information on adverse events after administration of seasonal and pandemic influenza vaccines was collected by different active surveys in the Netherlands. In the present paper, we compared data from a paper-based questionnaire with data from a web-based questionnaire with respect to outcomes and target population, in order to guide future influenza vaccine safety monitoring.

METHODS

The paper-based survey collected data from patients who attended primary care practices in the province of Utrecht for influenza vaccination. The web-based survey recruited participants from the general population all provinces of the Netherlands. To analyze the association between study approach and the reported local and systemic adverse events, a generalized estimation equation model was applied. We adjusted for age, gender, comorbidity, previous vaccination and socio-economic status score.

RESULTS

No significant differences were found between the two studies approaches in reporting local reactions (OR: 0.98, 95% CI 0.88-1.10) and systemic AEs (OR: 1.12, 95% CI 0.99-1.27). There were important differences in the age groups that responded. The elderly were more represented in the paper-based survey where participants were recruited via GPs (79%⩾60years) compared to 37% in the web-based survey where participants were recruited via internet.

CONCLUSION

The paper-based survey with recruitment of participants through GPs is more representative for the target group of influenza vaccination compared to the web-based survey with recruitment of participants via internet. A web-based approach with recruitment of participants via internet seems more suitable for situations where information about adverse events on a national level is desirable. We recommend to recruit participants for a web-based survey during mass vaccinations sessions by GPs to comply with the recommendations of the European Centre for Disease Prevention Control.

Combining Healthcare-Based and Participatory Approaches to Surveillance: Trends in Diarrheal and Respiratory Conditions Collected by a Mobile Phone System by Community Health Workers in Rural Nepal

Background

Surveillance systems are increasingly relying upon community-based or crowd-sourced data to complement traditional facilities-based data sources. Data collected by community health workers during the routine course of care could combine the early warning power of community-based data collection with the predictability and diagnostic regularity of facility data. These data could inform public health responses to epidemics and spatially-clustered endemic diseases. Here, we analyze data collected on a daily basis by community health workers during the routine course of clinical care in rural Nepal. We evaluate if such community-based surveillance systems can capture temporal trends in diarrheal diseases and acute respiratory infections.

Methods

During the course of their clinical activities from January to December 2013, community health workers recorded healthcare encounters using mobile phones. In parallel, we accessed condition-specific admissions from 2011–2013 in the hospital from which the community health program was based. We compared diarrhea and acute respiratory infection rates from both the hospital and the community, and assigned three categories of local disease activity (low, medium, and high) to each week in each village cluster with categories determined by tertiles. We compared condition-specific mean hospital rates across categories using ANOVA to assess concordance between hospital and community-collected data.

Results

There were 2,710 cases of diarrhea and 373 cases of acute respiratory infection reported by community health workers during the one-year study period. At the hospital, the average weekly incidence of diarrhea and acute respiratory infections over the three-year period was 1.8 and 3.9 cases respectively per 1,000 people in each village cluster. In the community, the average weekly rate of diarrhea and acute respiratory infections was 2.7 and 0.5 cases respectively per 1,000 people. Both diarrhea and acute respiratory infections exhibited significant differences between the three categories of disease rate burden (diarrhea p = 0.009, acute respiratory infection p = 0.001) when comparing community health worker-collected rates to hospital rates.

Conclusion

Community-level data on diarrhea and acute respiratory infections modestly correlated with hospital data for the same condition in each village each week. Our experience suggests that community health worker-collected data on mobile phones may be a feasible adjunct to other community- and healthcare-related data sources for surveillance of such conditions. Such systems are vitally needed in resource-limited settings like rural Nepal.

Influenza-like Illness in Households with Children of Preschool Age

BACKGROUND

Influenza-like illness (ILI) is the leading cause of medical consultation amongst preschool children, who may contribute to spreading ILI-causing agents within the household. We aimed to determine the societal burden (incidence, health-care consumption and productivity loss) and correlates of ILI in households with preschool children.

METHODS

A survey was performed in the Netherlands during October 2012 to October 2014. Monthly, 2000 households with children younger than 4 years were invited to report their symptoms and related medical care, productivity loss and putative risk exposures for 1 preschool child and 1 parent.

RESULTS

Eight thousand seven hundred and sixty-eight child-parent pairs were enrolled. ILI incidence was 2.81 episodes/child-year and 1.72 episodes/parent-year. Amongst those with ILI, health-care utilization was 35.7% (children) and 17.7% (parents). Work absenteeism was 45.7% (median 2 workdays lost) and day-care absenteeism was 22.8% (median 1 day missed). Chronic respiratory conditions, developmental disabilities, parental occupation in health care/child care, having a sibling and attending day care for ≤12 months increased childhood ILI risk. Parental ILI risk increased with having chronic respiratory conditions, developmentally disabled day-care-attending children and female gender in interaction with unemployment and multiple day-care-attending children. Breastfeeding infants 6-month-old or younger and attending day care for >24 months decreased childhood ILI risk. Pregnancy, occupation in health care and having ≥3 children decreased parental ILI risk. Parents of ILI-affected children had a concurrent 4-fold higher ILI risk.

CONCLUSION

ILI in households with preschool children has a considerable societal impact. Risk-mitigating initiatives seem justified for day-care attendees, mothers, people with chronic respiratory conditions, and children with developmental disabilities. Children attending day care for >2 years acquire some protection to ILI.

Influmeter - an online tool for self-reporting of influenza-like illness in Denmark

Background In October 2013, we implemented 'Influmeter', a web-based influenza-like illness (ILI) self-reporting system, to monitor ILI in the general population in a timely fashion, to provide data for estimations of the burden of influenza and to gain experience with online surveillance systems, in Denmark. After the season 2013/2014 we evaluated the system to decide on its future use. Methods Influmeter study participants provided personal details upon enrolment and reported symptoms weekly within predefined categories. We compared distribution of Influmeter participants with the Danish population, by sex, age, region, chronic diseases and educational level. We calculated the proportion of participants reporting symptoms of ILI weekly and the proportion of Influmeter ILI cases seeking medical assistance, using the Danish and the EU ILI case definitions. Further, we compared timing of increased ILI rates in Influmeter with existing Danish sentinel ILI surveillance using the Danish case definition. Results Compared with the Danish population, Influmeter had more females (p < 0.001) and persons with a higher education (p < 0.001), while the age group 0-24 was under-represented (p < 0.001). Influmeter ILI activity peaked 1 week before the exceeding of the sentinel epidemic threshold. Depending on ILI case definition 16-22% of ILI cases sought medical assistance. Conclusion Influmeter was useful in the timely monitoring of ILI activity in the population that did not seek medical assistance in relation to ILI. We recommend continuation of the system, targeted enrolment of the young and future analyses adjusted for uneven representation relative to the underlying population.

Ten-year performance of Influenzanet: ILI time series, risks, vaccine effects, and care-seeking behaviour

Recent public health threats have propelled major innovations on infectious disease monitoring, culminating in the development of innovative syndromic surveillance methods. Influenzanet is an internet-based system that monitors influenza-like illness (ILI) in cohorts of self-reporting volunteers in European countries since 2003. We investigate and confirm coherence through the first ten years in comparison with ILI data from the European Influenza Surveillance Network and demonstrate country-specific behaviour of participants with ILI regarding medical care seeking. Using regression analysis, we determine that chronic diseases, being a child, living with children, being female, smoking and pets at home, are all independent predictors of ILI risk, whereas practicing sports and walking or bicycling for locomotion are associated with a small risk reduction. No effect for using public transportation or living alone was found. Furthermore, we determine the vaccine effectiveness for ILI for each season.

Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems

During the last 30years it has become commonplace for epidemiological studies to collect locational attributes of disease data. Although this advancement was driven largely by the introduction of handheld global positioning systems (GPS), and more recently, smartphones and tablets with built-in GPS, the collection of georeferenced disease data has moved beyond the use of handheld GPS devices and there now exist numerous sources of crowdsourced georeferenced disease data such as that available from georeferencing of Google search queries or Twitter messages. In addition, cartography has moved beyond the realm of professionals to crowdsourced mapping projects that play a crucial role in disease control and surveillance of outbreaks such as the 2014 West Africa Ebola epidemic. This paper provides a comprehensive review of a range of innovative sources of spatial animal and human health data including data warehouses, mHealth, Google Earth, volunteered geographic information and mining of internet-based big data sources such as Google and Twitter. We discuss the advantages, limitations and applications of each, and highlight studies where they have been used effectively.

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.

The representativeness of a European multi-center network for influenza-like-illness participatory surveillance

Background

The Internet is becoming more commonly used as a tool for disease surveillance. Similarly to other surveillance systems and to studies using online data collection, Internet-based surveillance will have biases in participation, affecting the generalizability of the results. Here we quantify the participation biases of Influenzanet, an ongoing European-wide network of Internet-based participatory surveillance systems for influenza-like-illness.

Methods

In 2011/2012 Influenzanet launched a standardized common framework for data collection applied to seven European countries. Influenzanet participants were compared to the general population of the participating countries to assess the representativeness of the sample in terms of a set of demographic, geographic, socio-economic and health indicators.

Results

More than 30,000 European residents registered to the system in the 2011/2012 season, and a subset of 25,481 participants were selected for this study. All age classes (10 years brackets) were represented in the cohort, including under 10 and over 70 years old. The Influenzanet population was not representative of the general population in terms of age distribution, underrepresenting the youngest and oldest age classes. The gender imbalance differed between countries. A counterbalance between gender-specific information-seeking behavior (more prominent in women) and Internet usage (with higher rates in male populations) may be at the origin of this difference. Once adjusted by demographic indicators, a similar propensity to commute was observed for each country, and the same top three transportation modes were used for six countries out of seven. Smokers were underrepresented in the majority of countries, as were individuals with diabetes; the representativeness of asthma prevalence and vaccination coverage for 65+ individuals in two successive seasons (2010/2011 and 2011/2012) varied between countries.

Conclusions

Existing demographic and national datasets allowed the quantification of the participation biases of a large cohort for influenza-like-illness surveillance in the general population. Significant differences were found between Influenzanet participants and the general population. The quantified biases need to be taken into account in the analysis of Influenzanet epidemiological studies and provide indications on populations groups that should be targeted in recruitment efforts.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2458-14-984) contains supplementary material, which is available to authorized users.

Web-based participatory surveillance of infectious diseases: the Influenzanet participatory surveillance experience

To overcome the limitations of the state‐of‐the‐art influenza surveillance systems in Europe, we established in 2008 a European‐wide consortium aimed at introducing an innovative information and communication technology approach for a web‐based surveillance system across different European countries, called Influenzanet. The system, based on earlier efforts in The Netherlands and Portugal, works with the participation of the population in each country to collect real‐time information on the distribution of influenza‐like illness cases through web surveys administered to volunteers reporting their symptoms (or lack of symptoms) every week during the influenza season. Such a large European‐wide web‐based monitoring infrastructure is intended to rapidly identify public health emergencies, contribute to understanding global trends, inform data‐driven forecast models to assess the impact on the population, optimize the allocation of resources, and help in devising mitigation and containment measures. In this article, we describe the scientific and technological issues faced during the development and deployment of a flexible and readily deployable web tool capable of coping with the requirements of different countries for data collection, during either a public health emergency or an ordinary influenza season. Even though the system is based on previous successful experience, the implementation in each new country represented a separate scientific challenge. Only after more than 5 years of development are the existing platforms based on a plug‐and‐play tool that can be promptly deployed in any country wishing to be part of the Influenzanet network, now composed of The Netherlands, Belgium, Portugal, Italy, the UK, France, Sweden, Spain, Ireland, and Denmark.

Epidemiology and viral etiology of the influenza-like illness in corsica during the 2012-2013 Winter: an analysis of several sentinel surveillance systems

Influenza-like illness (ILI) surveillance is important to identify circulating and emerging/reemerging strains and unusual epidemiological trends. The present study aimed to give an accurate picture of the 2012-2013 ILI outbreak in Corsica by combining data from several surveillance systems: general practice, emergency general practice, hospital emergency units, intensive care units, and nursing homes. Twenty-eight respiratory viruses were retrospectively investigated from patients in general practice with ILI. Sequence analysis of the genetic changes in the hemagglutinin gene of influenza viruses (A(H1N1)pdm2009, A(H3N2) and B) was performed. The trends in ILI/influenza consultation rates and the relative illness ratios (RIRs) of having an ILI consultation were estimated by age group for the different surveillance systems analyzed. Of the 182 ILI patients enrolled by general practitioners, 57.7% tested positive for influenza viruses. Phylogenetic analyses suggested a genetic drift for influenza B and A(H3N2) viruses. The ILI/influenza surveillance systems showed similar trends and were well correlated. In accordance with virological data, the RIRs of having an ILI consultation were highest among the young (<15 years old) and decreased with age. No clusters of acute respiratory illness were declared by the sentinel nursing homes. This study is noteworthy in that it is the first extensive description of the 2012-2013 ILI outbreak in Corsica as monitored through several surveillance systems. To improve ILI surveillance in Corsica, a consortium that links together the complementary regional surveillance ILI systems described here is being implemented.

Public health for the people: participatory infectious disease surveillance in the digital age

The 21^st century has seen the rise of Internet-based participatory surveillance systems for infectious diseases. These systems capture voluntarily submitted symptom data from the general public and can aggregate and communicate that data in near real-time. We reviewed participatory surveillance systems currently running in 13 different countries. These systems have a growing evidence base showing a high degree of accuracy and increased sensitivity and timeliness relative to traditional healthcare-based systems. They have also proven useful for assessing risk factors, vaccine effectiveness, and patterns of healthcare utilization while being less expensive, more flexible, and more scalable than traditional systems. Nonetheless, they present important challenges including biases associated with the population that chooses to participate, difficulty in adjusting for confounders, and limited specificity because of reliance only on syndromic definitions of disease limits. Overall, participatory disease surveillance data provides unique disease information that is not available through traditional surveillance sources.

Utilizing syndromic surveillance data for estimating levels of influenza circulation

The availability of weekly Web-based participatory surveillance data on self-reported influenza-like illness (ILI), defined here as self-reported fever and cough/sore throat, over several influenza seasons allows for estimation of the incidence of influenza infection in population cohorts. We demonstrate this using syndromic data reported through the Influenzanet surveillance platform in the Netherlands. We used the 2011-2012 influenza season, a low-incidence season that began late, to assess the baseline rates of self-reported ILI during periods of low influenza circulation, and we used ILI rates above that baseline level from the 2012-1013 season, a major influenza season, to estimate influenza attack rates for that period. The latter conversion required estimates of age-specific probabilities of self-reported ILI given influenza (Flu) infection (P(ILI | Flu)), which were obtained from separate data (extracted from Hong Kong, China, household studies). For the 2012-2013 influenza season in the Netherlands, we estimated combined influenza A/B attack rates of 29.2% (95% credible interval (CI): 21.6, 37.9) among survey participants aged 20-49 years, 28.3% (95% CI: 20.7, 36.8) among participants aged 50-60 years, and 5.9% (95% CI: 0.4, 11.8) among participants aged ≥61 years. Estimates of influenza attack rates can be obtained in other settings using analogous, multiseason surveillance data on self-reported ILI together with separate, context-specific estimates of P(ILI | Flu).

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.

Incidence and risk factors for influenza-like-illness in the UK: online surveillance using Flusurvey

Background

Influenza 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.

Methods

Upon 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.

Results

5943 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.

Conclusions

Our 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.

Respiratory symptoms in households as an effective marker for influenza-like illness surveillance in the community

To effectively track the growth of influenza, we piloted an online system to monitor influenza-like illness (ILI) in the community in one district of Hong Kong. Four syndromic markers, namely fever, respiratory symptoms, fever with respiratory symptoms, fever and/or respiratory symptoms, either of the individual or of the household, were collected during the study period from June 2012 to October 2013. A total of 132 residents of Tuen Mun District reported syndromic markers at the individual and household levels on a weekly basis. Temporal patterns of these markers were compared with data derived from laboratory surveillance by dynamic linear regression. Household respiratory symptoms were found to be an effective syndromic marker, pre-dating overall laboratory virus surveillance results on influenza diseases in two influenza seasons by 3-4 weeks. To conclude, respiratory symptoms can be a good marker predicting the onset of the influenza season in the community, and is particularly useful with regard to data from households, even if the sample size may not be a large one.

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

BACKGROUND

"Influenzanet" is a network of Internet-based platforms aimed at collecting real-time data for influenza surveillance in several European countries. More than 30,000 European volunteers participate every year in the study, representing one of the largest existing Internet-based multicenter cohorts. Each week during the influenza season, participants are asked to report their symptoms (if any) along with a set of additional questions.

OBJECTIVE

Focusing on the first influenza season of 2011-12, when the Influenzanet system was completely harmonized within a common framework in Sweden, the United Kingdom, the Netherlands, Belgium, France, Italy, and Portugal, we investigated the propensity of users to regularly come back to the platform to provide information about their health status. Our purpose was to investigate demographic and behavioral factors associated with participation in follow-up.

METHODS

By means of a multilevel analysis, we evaluated the association between regular participation during the season and sociodemographic and behavioral characteristics as measured by a background questionnaire completed by participants on registration.

RESULTS

We found that lower participation in follow-up was associated with lower educational status (odds ratio [OR] 0.80, 95% CI 0.75-0.85), smoking (OR 0.64, 95% CI 0.59-0.70), younger age (OR ranging from 0.30, 95% CI 0.26-0.33 to 0.70, 95% CI 0.64-0.77), not being vaccinated against seasonal influenza (OR 0.77, 95% CI 0.72-0.84), and living in a household with children (OR 0.69, 95% CI 0.65-0.74). Most of these results hold when single countries are analyzed separately.

CONCLUSIONS

Given the opportunistic enrollment of self-selected volunteers in the Influenzanet study, we have investigated how sociodemographic and behavioral characteristics may be associated with follow-up participation in the Influenzanet cohort. The study described in this paper shows that, overall, the most important determinants of participation are related to education and lifestyle: smoking, lower education level, younger age, people living with children, and people who have not been vaccinated against seasonal influenza tend to have a lower participation in follow-up. Despite the cross-country variation, the main findings are similar in the different national cohorts, and indeed the results are found to be valid also when performing a single-country analysis. Differences between countries do not seem to play a crucial role in determining the factors associated with participation in follow-up.

Internet-based syndromic monitoring of acute respiratory illness in the general population of Germany, weeks 35/2011 to 34/2012

Binary file ES_Abstracts_Final_ECDC.txt matches

Comparing the impact of two concurrent infectious disease outbreaks on The Netherlands population, 2009, using disability-adjusted life years

In 2009 two notable outbreaks, Q fever and the novel influenza A(H1N1)pdm09, occurred in The Netherlands. Using a composite health measure, disability-adjusted life years (DALYs), the outbreaks were quantified and compared. DALYs were calculated using standardized methodology incorporating age- and sex-stratified data in a disease progression model; years lost due to disability and years of life lost were computed by outcome. Nationally, influenza A(H1N1)pdm09 caused more DALYs (24 484) than Q fever (5797). However, Q fever was 8·28 times more severe [497 DALYs/1000 symptomatic cases (DP1SC)] than A(H1N1)pdm09 (60 DP1SC). The A(H1N1)pdm09 burden is largely due to mortality while the Q fever burden is due primarily to long-term sequelae. Intervention prioritization for influenza should support patients in a critical condition while for Q fever it should target immediate containment and support for patients with long-term sequelae. Burden estimates provide guidance for focusing intervention options during outbreaks of infectious diseases.

Effectiveness of 2012-2013 influenza vaccine against influenza-like illness in general population: estimation in a French web-based cohort

Most of the methods used for estimating the influenza vaccine effectiveness (IVE) target the individuals who have an influenza-like illness (ILI) rather than virologically-proven influenza and access the healthcare system. The objective of this study was to estimate the 2012-2013 IVE in general French population, using a cohort of volunteers registered on GrippeNet.fr, an online surveillance system for ILI. The IVE estimations were obtained through a logistic regression, and analyses were also performed by focusing on at-risk population of severe influenza, and by varying inclusion period and ILI definition. Overall, 1996 individuals were included in the analyses. The corrected IVE was estimated to 49% (20 to 67) for the overall population, and 32% (0 to 58) for the at-risk population. Three covariables appeared with a significant effect on the occurrence of at least one ILI during the epidemic: the age (P = 0.045), the presence of a child in the household (P<10(-3)), and the frequency of cold/flu (P<10(-3)). Comparable results were found at epidemic peak time in the hypothesis of real-time feed of data. In this study, we proposed a novel, follow-up, web-based method to reveal seasonal vaccine effectiveness, which enables analysis in a portion of the population that is not tracked by the health care system in most VE studies.

An evidence synthesis approach to estimating the incidence of seasonal influenza in the Netherlands

Objectives

To estimate, using Bayesian evidence synthesis, the age-group-specific annual incidence of symptomatic infection with seasonal influenza in the Netherlands over the period 2005–2007.

Methods

The Netherlands population and age group distribution for 2006 defined the base population. The number of influenza-like illness (ILI) cases was estimated from sentinel surveillance data and adjusted for underascertainment using the estimated proportion of ILI cases that do not consult a general practitioner. The estimated number of symptomatic influenza (SI) cases was based on indirect evidence from the surveillance of ILI cases and the proportions of laboratory-confirmed influenza cases in the 2004/5, 2005/6 and 2006/7 respiratory years. In scenario analysis, the number of SI cases prevented by increasing vaccination uptake within the 65 + age group was estimated.

Results

The overall symptomatic infection attack rate (SIAR) over the period 2005–2007 was estimated at 2·5% (95% credible interval [CI]: 2·1–3·2%); 410 200 SI cases (95% CI: 338 500–518 600) were estimated to occur annually. Age-group-specific SIARs were estimated for <5 years at 4·9% (2·1–13·7%), for 5–14 years at 3·0% (2·0–4·7%), for 15–44 years at 2·6% (2·1–3·2%), for 45–64 years at 1·9% (1·4–2·5%) and for 65 + years at 1·7% (1·0–3·0%). Under assumed vaccination uptake increases of 5% and 15%, 1970 and 5310 SI cases would be averted.

Conclusions

By synthesising the available information on seasonal influenza and ILI from diverse sources, the annual extent of symptomatic infection can be derived. These estimates are useful for assessing the burden of seasonal influenza and for guiding vaccination policy.

Medical and economic burden of influenza in the elderly population in central and eastern European countries

Influenza affects 5-15% of the population during an epidemic. In Western Europe, vaccination of at-risk groups forms the cornerstone of influenza prevention. However, vaccination coverage of the elderly (> 65 y) is often low in Central and Eastern Europe (CEE); potentially because a paucity of country-specific data limits evidence-based policy making. Therefore the medical and economic burden of influenza were estimated in elderly populations in the Czech Republic, Hungary, Kazakhstan, Poland, Romania, and Ukraine. Data covering national influenza vaccination policies, surveillance and reporting, healthcare costs, populations, and epidemiology were obtained via literature review, open-access websites and databases, and interviews with experts. A simplified model of patient treatment flow incorporating cost, population, and incidence/prevalence data was used to calculate the influenza burden per country. In the elderly, influenza represented a large burden on the assessed healthcare systems, with yearly excess hospitalization rates of ~30/100,000. Burden varied between countries and was likely influenced by population size, surveillance system, healthcare provision, and vaccine coverage. The greatest burden was found in Poland, where direct costs were over EUR 5 million. Substantial differences in data availability and quality were identified, and to fully quantify the burden of influenza in CEE, influenza reporting systems should be standardized. This study most probably underestimates the real burden of influenza, however the public health problem is recognized worldwide, and will further increase with population aging. Extending influenza vaccination of the elderly may be a cost-effective way to reduce the burden of influenza in CEE.

Comparison of five influenza surveillance systems during the 2009 pandemic and their association with media attention

Background

During the 2009 influenza pandemic period, routine surveillance of influenza-like-illness (ILI) was conducted in The Netherlands by a network of sentinel general practitioners (GPs). In addition during the pandemic period, four other ILI/influenza surveillance systems existed. For pandemic preparedness, we evaluated the performance of the sentinel system and the others to assess which of the four could be useful additions in the future. We also assessed whether performance of the five systems was influenced by media reports during the pandemic period.

Methods

The trends in ILI consultation rates reported by sentinel GPs from 20 April 2009 through 3 January 2010 were compared with trends in data from the other systems: ILI cases self-reported through the web-based Great Influenza Survey (GIS); influenza-related web searches through Google Flu Trends (GFT); patients admitted to hospital with laboratory-confirmed pandemic influenza, and detections of influenza virus by laboratories. In addition, correlations were determined between ILI consultation rates of the sentinel GPs and data from the four other systems. We also compared the trends of the five surveillance systems with trends in pandemic-related newspaper and television coverage and determined correlation coefficients with and without time lags.

Results

The four other systems showed similar trends and had strong correlations with the ILI consultation rates reported by sentinel GPs. The number of influenza virus detections was the only system to register a summer peak. Increases in the number of newspaper articles and television broadcasts did not precede increases in activity among the five surveillance systems.

Conclusions

The sentinel general practice network should remain the basis of influenza surveillance, as it integrates epidemiological and virological information and was able to maintain stability and continuity under pandemic pressure. Hospital and virological data are important during a pandemic, tracking the severity, molecular and phenotypic characterization of the viruses and confirming whether ILI incidence is truly related to influenza virus infections. GIS showed that web-based, self-reported ILI can be a useful addition, especially if virological self-sampling is added and an epidemic threshold could be determined. GFT showed negligible added value.