Use of Mobile Symptoms Tracking in Battling the COVID-19 Pandemic
This topic entails the use of technology in self-reporting symptoms, primarily as a means to battle the COVID-19 pandemic. We do attempt to inform the reader of the potentials beyond the current pandemic.
The importance of such technologies, given their efficacy, became apparent very early into the COVID-19 pandemic due to the virus’s fast-moving nature and its varying effects on different individuals of different characteristics and demographics.
Studies that have been examined have used mobile applications for self-reporting, collecting and storing the questionnaires answered by individual reporters, and analyzed the collected data. The studies’ primary goal was to find patterns emerging out of the collected data and provide a proof of concept of the potential use case of such methods in combating the pandemic, with an eye on other potential use cases of similar methods outside the context of the pandemic — namely individualized medicine.
Many such studies started early on in mid-March. They were providing preliminary results as soon as mid to late April. Delivering some evidence in emerging patterns of population’s behavior and reported symptoms and its potential ramifications in the direction of the development and spread of the virus in some geographical regions before regional health authorities provided official reports. They further managed to find associations between symptoms and the odds ratio (OR) for a positive test and between risk factors and their OR with a positive test.
All studies that were considered have found complex symptoms (having two or more symptoms in specific categories of symptoms) are much more instructive in having predictive value than a single symptom in an individual. This phenomenon was due to the prevalence of some symptoms in other conditions unrelated to SARS-CoV-2 as well.
This approach proved to be adding to the arsenal of methods useful for battling COVID-19 due to its predictive power in all three areas mentioned above. The technique would also be helpful to move scarce resources to more vulnerable or in need places.
Combining other known but novel methods and technologies such as Machine Learning has furthered our understanding of the disease at a much faster pace than would be possible with more conventional methods.
The use cases beyond the COVID-19 pandemic, although briefly looked at, is worthy of further studies. The potentials include but are not limited to individualized medicine, the study of novel diseases, and further understanding of the known infections, especially in an individual or demographical context.
References:
1. M. Zens, A. Brammertz, J. Herpich, N. Südkamp, M. Hinterseer. App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data. J Med Internet Res2020, 22, 9, e21956. DOI: 10.2196/21956
2. K. Yamamoto,T.Takahashi,M.Urasaki, Y. Nagayasu,T.Shimamoto, Y. Tateyama,K.Matsuzaki,D.Kobayashi, S. Kubo,S.Mito,T.Abe,H.Matsuura,T.Iwami T. Health Observation App for COVID-19 Symptom Tracking Integrated With Personal Health Records: Proof of Concept and Practical Use Study. JMIR Mhealth Uhealth2020, 8, 7, e19902. DOI: 10.2196/19902
3. D. A. Drew et al. Rapid implementation of mobile technology for real-time epidemiology of COVID-19. Science2020: 1362–1367