Influenzanet Digital Cohort
Study profileDescription
Influenzanet is a network of web-based surveillance systems in several European countries and monitors influenza-like Illness (ILI) in the general population. Activities in four countries (Belgium, Estonia, France, Italy) are included in VERDI. Influenzanet is a collective system of internet-based tools through which real-time surveillance of self-reported ILI in the community is undertaken. Participation is voluntary, and in any country where the platform is deployed, any member of the public can register and is then prompted on a weekly basis to report any respiratory symptoms (or lack of) during the influenza season.
Countries involved: Italy, Belgium, France, Estonia
Sample size: ~10,000 participants
Related publications:
- McDonald SA, Jan van Hoek A, Paolotti D, Hooiveld M, Meijer A, de Lange M; Infectieradar team; van Gageldonk-Lafeber A, Wallinga J. A statistical modelling approach for determining the cause of reported respiratory syndromes from internet-based participatory surveillance when influenza virus and SARS-CoV-2 are co-circulating. PLOS Digit Health. 2024;3(12):e0000655. Published 2024 Dec 9. doi:10.1371/journal.pdig.0000655
- Kelley K, Gozzi N, Mazzoli M, Paolotti D. Exploring influenza vaccination determinants through digital participatory surveillance. BMC Public Health. 2025;25(1):1345. Published 2025 Apr 10. doi:10.1186/s12889-025-22496-8
- Mazzoli M, Gozzi N, Hermans L, Hens N, Carstens G, van Hoek AJ, Le Hegaret A, Guerrisi C, Turbelin C, Debin M, Colizza V, Obi C, Watson C, Dugerdil A, Flahault A, Paolotti D. Healthcare-seeking behavior and hidden influenza-like-illness across the COVID-19 pandemic: a multi-country participatory surveillance study. medRxiv 2025.10.07.25337476; doi:10.1101/2025.10.07.25337476
- medRxiv 2025.11.17.25338859; doi:10.1101/2025.11.17.25338859
- Calmon L, de Gaetano A, Mazzoli M, Gozzi N, Frigione G, Debin M, Turbelin C, Marmorat R, Perra N, Barrat A, Colizza V, Paolotti D. Assessing dengue knowledge, attitudes and preventive practices using participatory surveillance cohorts. medRxiv 2025.11.05.25339567; doi:10.1101/2025.11.05.25339567
Metadata collected
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| Data collected? | |
| Demographics | |
| Date of birth (full or MM/YY) | ✅ |
| Age at contact | ✅ |
| Sex / gender | ✅ |
| Country of birth | |
| Ethnic group / race / population sector | |
| Income level | |
| Employment / occupation | ✅ |
| Other socio-economic status proxy | ✅ |
| Education level | ✅ |
| Civil status (‘marital’) | ✅ |
| Locality (of health care provision) | ✅ |
| Locality (of residence) | ✅ |
| Household size | ✅ |
| Household composition | ✅ |
| Hospitalisation | |
| Admission / discharge dates or duration | ✅ |
| Episode dates | ✅ |
| Episode type (e.g., general; birth) | |
| Diagnosis (e.g., codes) | |
| Procedures (e.g., codes) | |
| Procedures dates | |
| Dispensed medications | |
| ICU admission | |
| Admission type (planned/emergency) | |
| Hospitalisation for COVID-19 | ✅ |
| Primary care, outpatient care | |
| Date of visit / contact | ✅ |
| Diagnosis codes | |
| Dispensed medications codes | |
| Dispensed medications date | |
| Primary care utilisation summary | |
| Health status and exposures | |
| Height | |
| Weight | |
| Date of anthropometrics | |
| Chronic / co-morbid conditions~ | |
| Medications for chronic conditions | ✅ |
| Smoker in household | |
| Current smoker | ✅ |
| ~ can include obesity | |
| Vaccines | |
| COVID-19 vaccine (timing, doses) | ✅ |
| Type of COVID-19 vaccine | ✅ |
| Other vaccinations / vaccination history | ✅ |
| COVID-19 symptoms & contacts | |
| COVID-19 episodes | ✅ |
| COVID-19 symptoms (type, severity, duration) | ✅ |
| Influenza-like symptoms (type, timing, duration) | ✅ |
| COVID-19 health-seeking behaviour | ✅ |
| COVID-19 contacts in household | ✅ |
| Medications during C-19 episode | ✅ |
| Pregnancy & birth | |
| Date of delivery | |
| Length of gestation | |
| Birthweight | |
| Maternal age at delivery | |
| Pregnancy complications | |
| Smoking pre-pregnancy | |
| Vaccines in pregnancy (non-COVID-19) | |
| Parity / nulliparity | |
| Pre-pregnancy body mass index | |
| Pregnancy outcome (e.g. miscarriage) | |
| Mode of delivery | |
| Sex of baby | |
| Congenital anomalies | |
| Other newborn complications | |
| Placental weight | |
| Antenatal care usage | |
| Currently pregnant | ✅ |
| Death | |
| Date of / age at death | |
| Cause of death | |
| COVID-19 laboratory tests | |
| Sample type tested | ✅ |
| Sample / specimen collection date | |
| SARS-CoV-2 PCR test date | |
| SARS-CoV-2 PCR pos / neg result | ✅ |
| SARS-CoV-2 PCR Ct Value | |
| SARS-CoV-2 LFT test date | |
| SARS-CoV-2 LFT test result | |
| Serology test date | |
| Serology test results | |
| SARS- COV-2 genomic test results | |
| SARS- COV-2 variant/ lineage | |
| Other lab tests | |
| COVID-19 sample collection / storage | |
| Sample type collected | |
| Sample collection date | |
| Sample collection time | |
| Sample processing | |
| Sample quality | |
| Consent to use research sample | |
| Consent to share research sample |