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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Apr 29, 2020
Date Accepted: Oct 30, 2020

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

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

Lwin MO, Lu J, Sheldenkar A, Panchapakesan C, Tan YR, Yap P, Chen MI, Chow VT, Thoon KC, Yung CF, Ang LW, Ang BS

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

JMIR Mhealth Uhealth 2020;8(12):e19712

DOI: 10.2196/19712

PMID: 33284126

PMCID: 7752531

Assessing the effectiveness of a mobile-based influenza-like illness surveillance system (FluMob) among healthcare workers in Singapore: A two-year surveillance study

  • May Oo Lwin; 
  • Jiahui Lu; 
  • Anita Sheldenkar; 
  • Chitra Panchapakesan; 
  • Yi Roe Tan; 
  • Peiling Yap; 
  • Mark I. Chen; 
  • Vincent T.K. Chow; 
  • Koh Cheng Thoon; 
  • Chee Fu Yung; 
  • Li Wei Ang; 
  • Brenda S.P. Ang

ABSTRACT

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. Studies also adopted a passive surveillance approach and have not fully investigated the effectiveness of the systems and its determinants.

Objective:

This research presents the efficiency of a mobile-based surveillance system of ILI, termed FluMob, among healthcare workers (HCWs) from a targeted surveillance approach. Particularly, this study evaluates the effectiveness of the system for ILI surveillance pertaining to its participation engagement and surveillance power. Also, the study aims to identify 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. Six hundred and ninety clinical and non-clinical hospital staffs participated in the study for 18 months and were prompted via application notifications to submit a survey listing eighteen acute respiratory symptoms (e.g., fever, cough, sore throat) on a weekly basis. There was a study disruption due to the downtime of the system for unexpected maintenance and the end of the participation incentive between May and July in 2017.

Results:

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

Conclusions:

This research found that mobile-based ILI surveillance systems among HCWs 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. Also, 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.


 Citation

Please cite as:

Lwin MO, Lu J, Sheldenkar A, Panchapakesan C, Tan YR, Yap P, Chen MI, Chow VT, Thoon KC, Yung CF, Ang LW, Ang BS

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

JMIR Mhealth Uhealth 2020;8(12):e19712

DOI: 10.2196/19712

PMID: 33284126

PMCID: 7752531

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