Hospital Epidemics Tracker (HEpiTracker): Description and pilot study of a mobile app to track COVID-19 in hospital workers

Joan B Soriano, Esteve Fernández, Álvaro de Astorza, Luis A Pérez de Llano, Alberto Fernández-Villar, Dolors Carnicer-Pont, Bernardino Alcázar-Navarrete, Arturo García, Aurelio Morales, María Lobo, Marcos Maroto, Eloy Ferreras, Cecilia Soriano, Carlos Del Rio-Bermudez, Lorena Vega-Piris, Xavier Basagaña, Josep Muncunill, Borja G Cosio, Sara Lumbreras, Carlos Catalina, José María Alzaga, David Gómez Quilón, Carlos Alberto Valdivia, Celia de Lara, Julio Ancochea, Joan B Soriano, Esteve Fernández, Álvaro de Astorza, Luis A Pérez de Llano, Alberto Fernández-Villar, Dolors Carnicer-Pont, Bernardino Alcázar-Navarrete, Arturo García, Aurelio Morales, María Lobo, Marcos Maroto, Eloy Ferreras, Cecilia Soriano, Carlos Del Rio-Bermudez, Lorena Vega-Piris, Xavier Basagaña, Josep Muncunill, Borja G Cosio, Sara Lumbreras, Carlos Catalina, José María Alzaga, David Gómez Quilón, Carlos Alberto Valdivia, Celia de Lara, Julio Ancochea

Abstract

Background: Hospital workers have been the most frequently and severely affected professional group during the COVID-19 pandemic, and have a big impact on transmission. In this context, innovative tools are required to measure the symptoms compatible with COVID-19, the spread of infection, and testing capabilities within hospitals in real time.

Objective: We aimed to develop and test an effective and user-friendly tool to identify and track symptoms compatible with COVID-19 in hospital workers.

Methods: We developed and pilot tested Hospital Epidemics Tracker (HEpiTracker), a newly designed app to track the spread of COVID-19 among hospital workers. Hospital staff in 9 hospital centers across 5 Spanish regions (Andalusia, Balearics, Catalonia, Galicia, and Madrid) were invited to download the app on their phones and to register their daily body temperature, COVID-19-compatible symptoms, and general health score, as well as any polymerase chain reaction and serological test results.

Results: A total of 477 hospital staff participated in the study between April 8 and June 2, 2020. Of note, both health-related (n=329) and non-health-related (n=148) professionals participated in the study; over two-thirds of participants (68.8%) were health workers (43.4% physicians and 25.4% nurses), while the proportion of non-health-related workers by center ranged from 40% to 85%. Most participants were female (n=323, 67.5%), with a mean age of 45.4 years (SD 10.6). Regarding smoking habits, 13.0% and 34.2% of participants were current or former smokers, respectively. The daily reporting of symptoms was highly variable across participating hospitals; although we observed a decline in adherence after an initial participation peak in some hospitals, other sites were characterized by low participation rates throughout the study period.

Conclusions: HEpiTracker is an already available tool to monitor COVID-19 and other infectious diseases in hospital workers. This tool has already been tested in real conditions. HEpiTracker is available in Spanish, Portuguese, and English. It has the potential to become a customized asset to be used in future COVID-19 pandemic waves and other environments.

Trial registration: ClinicalTrials.gov NCT04326400; https://ichgcp.net/clinical-trials-registry/NCT04326400.

Keywords: COVID-19; app; coronavirus; e-medicine; monitoring; surveillance; symptoms.

Conflict of interest statement

Conflicts of Interest: None declared.

©Joan B Soriano, Esteve Fernández, Álvaro de Astorza, Luis A Pérez de Llano, Alberto Fernández-Villar, Dolors Carnicer-Pont, Bernardino Alcázar-Navarrete, Arturo García, Aurelio Morales, María Lobo, Marcos Maroto, Eloy Ferreras, Cecilia Soriano, Carlos Del Rio-Bermudez, Lorena Vega-Piris, Xavier Basagaña, Josep Muncunill, Borja G Cosio, Sara Lumbreras, Carlos Catalina, José María Alzaga, David Gómez Quilón, Carlos Alberto Valdivia, Celia de Lara, Julio Ancochea. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 21.09.2020.

Figures

Figure 1
Figure 1
HEpiTracker graphical display and screens.
Figure 2
Figure 2
Distribution of HEpiTracker coverage in each hospital by calendar day (April 8 to May 30, 2020) as of June 2, 2020. ICO: Institut Català d'Oncologia.
Figure 3
Figure 3
HEpiTracker results by hospital and by calendar day.

References

    1. Doroshow D, Podolsky S, Barr J. Biomedical Research in Times of Emergency: Lessons From History. Annals of Internal Medicine. 2020 Aug 18;173(4):297–299. doi: 10.7326/m20-2076.
    1. Black JRM, Bailey C, Przewrocka J, Dijkstra KK, Swanton C. COVID-19: the case for health-care worker screening to prevent hospital transmission. The Lancet. 2020 May;395(10234):1418–1420. doi: 10.1016/s0140-6736(20)30917-x.
    1. Zhao G. [Taking preventive measures immediately: evidence from China on COVID-19] Gac Sanit. 2020 May;34(3):217–219. doi: 10.1016/j.gaceta.2020.03.002.
    1. World Health Organization WHO coronavirus disease (COVID-19) pandemic. [2020-08-20]. .
    1. Mahase E. Covid-19: Medical leaders call for rapid review to prepare for second wave. BMJ. 2020 Jun 24;369:m2529. doi: 10.1136/bmj.m2529.
    1. Centro Nacional de Epidemiología Situación y evolución de la pandemia de COVID-19 en España. COVID-19 en España. [2020-08-20]. .
    1. Centers for Disease Control and Prevention Symptoms of Coronavirus (COVID-19) [2020-08-20]. .
    1. Munster VJ, Koopmans M, van Doremalen N, van Riel D, de Wit E. A Novel Coronavirus Emerging in China - Key Questions for Impact Assessment. N Engl J Med. 2020 Feb 20;382(8):692–694. doi: 10.1056/NEJMp2000929.
    1. Valls J, Tobías Aurelio, Satorra P, Tebé Cristian. [COVID19-Tracker: a shiny app to analise data on SARS-CoV-2 epidemic in Spain] Gac Sanit. 2020 Apr 27; doi: 10.1016/j.gaceta.2020.04.002.
    1. Pérez Sust P, Solans O, Fajardo JC, Medina Peralta M, Rodenas P, Gabaldà J, Garcia Eroles L, Comella A, Velasco Muñoz C, Sallent Ribes J, Roma Monfa R, Piera-Jimenez J. Turning the Crisis Into an Opportunity: Digital Health Strategies Deployed During the COVID-19 Outbreak. JMIR Public Health Surveill. 2020 May 04;6(2):e19106. doi: 10.2196/19106.
    1. Zamberg I, Manzano S, Posfay-Barbe K, Windisch O, Agoritsas T, Schiffer E. A Mobile Health Platform to Disseminate Validated Institutional Measurements During the COVID-19 Outbreak: Utilization-Focused Evaluation Study. JMIR Public Health Surveill. 2020 Apr 14;6(2):e18668. doi: 10.2196/18668.
    1. Fagherazzi G, Goetzinger C, Rashid MA, Aguayo GA, Huiart L. Digital Health Strategies to Fight COVID-19 Worldwide: Challenges, Recommendations, and a Call for Papers. J Med Internet Res. 2020 Jun 16;22(6):e19284. doi: 10.2196/19284.
    1. HEpiTracker HEpiTracker home site. [2020-08-20]. .
    1. Koo D, Thacker SB. In snow's footsteps: Commentary on shoe-leather and applied epidemiology. Am J Epidemiol. 2010 Oct 15;172(6):737–9. doi: 10.1093/aje/kwq252.
    1. Tong SYC. Genomic polish for shoe-leather epidemiology. Nat Rev Microbiol. 2013 Jan 3;11(1):8–8. doi: 10.1038/nrmicro2935.
    1. Topol E. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. New York, NY, USA: Basic Books; 2018.
    1. Aselsis Consulting. [2020-08-20].
    1. Open Source ERP and CRM. ODOO. [2020-08-20].
    1. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. The Lancet. 2007 Oct;370(9596):1453–1457. doi: 10.1016/S0140-6736(07)61602-X.
    1. Horton R. Offline: COVID-19 and the ethics of memory. The Lancet. 2020 Jun;395(10239):1750. doi: 10.1016/S0140-6736(20)31279-4. doi: 10.1016/s0140-6736(20)31279-4.
    1. Fincham JE. Response rates and responsiveness for surveys, standards, and the Journal. Am J Pharm Educ. 2008 May 15;72(2):43. doi: 10.5688/aj720243.
    1. Smith LH, VanderWeele TJ. Bounding Bias Due to Selection. Epidemiology. 2019 Jul;30(4):509–516. doi: 10.1097/EDE.0000000000001032.
    1. Bort-Roig J, Puig-Ribera A, Contreras RS, Chirveches-Pérez E, Martori JC, Gilson ND, McKenna J. Monitoring sedentary patterns in office employees: validity of an m-health tool (Walk@Work-App) for occupational health. Gac Sanit. 2018 Nov;32(6):563–566. doi: 10.1016/j.gaceta.2017.05.004.
    1. Vokinger KN, Nittas V, Witt CM, Fabrikant SI, von Wyl V. Digital health and the COVID-19 epidemic: an assessment framework for apps from an epidemiological and legal perspective. Swiss Med Wkly. 2020 May 04;150:w20282. doi: 10.4414/smw.2020.20282.
    1. Schinköthe T, Gabri MR, Mitterer M, Gouveia P, Heinemann V, Harbeck N, Subklewe M. A Web- and App-Based Connected Care Solution for COVID-19 In- and Outpatient Care: Qualitative Study and Application Development. JMIR Public Health Surveill. 2020 Jun 01;6(2):e19033. doi: 10.2196/19033.
    1. Zamberg I, Manzano S, Posfay-Barbe K, Windisch O, Agoritsas T, Schiffer E. A Mobile Health Platform to Disseminate Validated Institutional Measurements During the COVID-19 Outbreak: Utilization-Focused Evaluation Study. JMIR Public Health Surveill. 2020 Apr 14;6(2):e18668. doi: 10.2196/18668.
    1. Szinay D, Jones A, Chadborn T, Brown J, Naughton F. Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review. J Med Internet Res. 2020 Mar 23; doi: 10.2196/17572. doi: 10.2196/17572.
    1. Sauro J, Zarolia P. SUPR-Qm: A Questionnaire to Measure the Mobile App User Experience. J Usability Stud. 2017 Nov;13:A.
    1. Zhou L, Bao J, Setiawan IMA, Saptono A, Parmanto B. The mHealth App Usability Questionnaire (MAUQ): Development and Validation Study. JMIR mHealth uHealth. 2019 Apr 11;7(4):e11500. doi: 10.2196/11500.
    1. Softlution. [2020-08-20]. .
    1. Wiersinga WJ, Rhodes A, Cheng AC, Peacock SJ, Prescott HC. Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review. JAMA. 2020 Jul 10; doi: 10.1001/jama.2020.12839.
    1. Soriano JB. Humanistic Epidemiology: Love in the time of cholera, COVID-19 and other outbreaks. Eur J Epidemiol. 2020 Apr 25;35(4):321–324. doi: 10.1007/s10654-020-00639-y.
    1. Gerli A, Centanni S, Miozzo M, Virchow J, Sotgiu G, Canonica G, Soriano J. COVID-19 mortality rates in the European Union, Switzerland, and the UK: effect of timeliness, lockdown rigidity, and population density. Minerva Med. 2020 Jul 02;:2. doi: 10.23736/S0026-4806.20.06702-6.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe