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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Aug 3, 2021
Open Peer Review Period: Aug 3, 2021 - Sep 28, 2021
Date Accepted: Sep 29, 2021
Date Submitted to PubMed: Nov 16, 2021
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

Stewart C, Ranjan Y, Conde P, Rashid Z, Sangkesara H, Bai X, Dobson R, Folarin A

Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

JMIR Res Protoc 2021;10(12):e32587

DOI: 10.2196/32587

PMID: 34784292

PMCID: 8658240

Investigating the use of digital health technology to monitor COVID-19 and its effects: Protocol for Covid Collab, an observational study

  • Callum Stewart; 
  • Yatharth Ranjan; 
  • Pauline Conde; 
  • Zulqarnain Rashid; 
  • Heet Sangkesara; 
  • Xi Bai; 
  • Richard Dobson; 
  • Amos Folarin

ABSTRACT

Background:

The ubiquity of mobile phones and increasing use of wearable fitness trackers offers a wide-ranging window into people’s health and well-being. There are clear advantages in using remote monitoring technologies to gain an insight into health, particularly under the shadow of the current COVID-19 pandemic.

Objective:

The Covid Collab study was set up to investigate the feasibility of identifying, monitoring, and understanding the stratification of COVID-19 infection and recovery through remote monitoring technologies. Additionally, we will assess the impact of the COVID-19 pandemic and associated social measures on people’s behaviour, physical health, and mental well-being.

Methods:

Participants remotely enrolled on the study through the Mass Science app to donate both historic and prospective mobile phone data, fitness tracking wearable data, and regular COVID-19 and mental health related surveys. Data is being recorded for the period of the pandemic, notably including pre, during and post acute infection phase. We plan to carry out analyses in several areas, covering symptomatology, risk factors, machine learning-based classification of illness, and trajectories of recovery, mental well-being, and activity.

Results:

Covid Collab is a crowdsourced study using remote monitoring technologies to investigate the COVID-19 pandemic. As of June 2021 there are over 17000 participants, largely from the United Kingdom, with enrolment ongoing.

Conclusions:

This paper introduces a remotely enrolled crowd-sourced study recording mobile health data throughout the COVID-19 pandemic. The data collected may help investigate a variety of areas, including COVID-19 disease progression, mental wellbeing during the pandemic, and adherence of remote, digitally enrolled participants.


 Citation

Please cite as:

Stewart C, Ranjan Y, Conde P, Rashid Z, Sangkesara H, Bai X, Dobson R, Folarin A

Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

JMIR Res Protoc 2021;10(12):e32587

DOI: 10.2196/32587

PMID: 34784292

PMCID: 8658240

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.

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