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App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data

BACKGROUND: COVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. OBJECTIVE: To determine the distribution pattern of COVID-19 symptoms as well as possible unr...

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Autores principales: Zens, Martin, Brammertz, Arne, Herpich, Juliane, Südkamp, Norbert, Hinterseer, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480999/
https://www.ncbi.nlm.nih.gov/pubmed/32791493
http://dx.doi.org/10.2196/21956
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author Zens, Martin
Brammertz, Arne
Herpich, Juliane
Südkamp, Norbert
Hinterseer, Martin
author_facet Zens, Martin
Brammertz, Arne
Herpich, Juliane
Südkamp, Norbert
Hinterseer, Martin
author_sort Zens, Martin
collection PubMed
description BACKGROUND: COVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. OBJECTIVE: To determine the distribution pattern of COVID-19 symptoms as well as possible unreported symptoms, we created an app-based self-reporting tool. METHODS: The COVID-19 Symptom Tracker is an app-based daily self-reporting tool. Between April 8 and May 15, 2020, a total of 22,327 individuals installed this app on their mobile device. An initial questionnaire asked for demographic information (age, gender, postal code) and past medical history comprising relevant chronic diseases. The participants were reminded daily to report whether they were experiencing any symptoms and if they had been tested for SARS-CoV-2 infection. Participants who sought health care services were asked additional questions regarding diagnostics and treatment. Participation was open to all adults (≥18 years). The study was completely anonymous. RESULTS: In total, 11,829 (52.98%) participants completed the symptom questionnaire at least once. Of these, 291 (2.46%) participants stated that they had undergone an RT-PCR (reverse transcription-polymerase chain reaction) test for SARS-CoV-2; 65 (0.55%) reported a positive test result and 226 (1.91%) a negative one. The mean number of reported symptoms among untested participants was 0.81 (SD 1.85). Participants with a positive test result had, on average, 5.63 symptoms (SD 2.82). The most significant risk factors were diabetes (odds ratio [OR] 8.95, 95% CI 3.30-22.37) and chronic heart disease (OR 2.85, 95% CI 1.43-5.69). We identified chills, fever, loss of smell, nausea and vomiting, and shortness of breath as the top five strongest predictors for a COVID-19 infection. The odds ratio for loss of smell was 3.13 (95% CI 1.76-5.58). Nausea and vomiting (OR 2.84, 95% CI 1.61-5.00) had been reported as an uncommon symptom previously; however, our data suggest a significant predictive value. CONCLUSIONS: Self-reported symptom tracking helps to identify novel symptoms of COVID-19 and to estimate the predictive value of certain symptoms. This aids in the development of reliable screening tools. Clinical screening with a high pretest probability allows for the rapid identification of infections and the cost-effective use of testing resources. Based on our results, we suggest that loss of smell and taste be considered cardinal symptoms; we also stress that diabetes is a risk factor for a highly symptomatic course of COVID-19 infection.
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spelling pubmed-74809992020-10-02 App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data Zens, Martin Brammertz, Arne Herpich, Juliane Südkamp, Norbert Hinterseer, Martin J Med Internet Res Short Paper BACKGROUND: COVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. OBJECTIVE: To determine the distribution pattern of COVID-19 symptoms as well as possible unreported symptoms, we created an app-based self-reporting tool. METHODS: The COVID-19 Symptom Tracker is an app-based daily self-reporting tool. Between April 8 and May 15, 2020, a total of 22,327 individuals installed this app on their mobile device. An initial questionnaire asked for demographic information (age, gender, postal code) and past medical history comprising relevant chronic diseases. The participants were reminded daily to report whether they were experiencing any symptoms and if they had been tested for SARS-CoV-2 infection. Participants who sought health care services were asked additional questions regarding diagnostics and treatment. Participation was open to all adults (≥18 years). The study was completely anonymous. RESULTS: In total, 11,829 (52.98%) participants completed the symptom questionnaire at least once. Of these, 291 (2.46%) participants stated that they had undergone an RT-PCR (reverse transcription-polymerase chain reaction) test for SARS-CoV-2; 65 (0.55%) reported a positive test result and 226 (1.91%) a negative one. The mean number of reported symptoms among untested participants was 0.81 (SD 1.85). Participants with a positive test result had, on average, 5.63 symptoms (SD 2.82). The most significant risk factors were diabetes (odds ratio [OR] 8.95, 95% CI 3.30-22.37) and chronic heart disease (OR 2.85, 95% CI 1.43-5.69). We identified chills, fever, loss of smell, nausea and vomiting, and shortness of breath as the top five strongest predictors for a COVID-19 infection. The odds ratio for loss of smell was 3.13 (95% CI 1.76-5.58). Nausea and vomiting (OR 2.84, 95% CI 1.61-5.00) had been reported as an uncommon symptom previously; however, our data suggest a significant predictive value. CONCLUSIONS: Self-reported symptom tracking helps to identify novel symptoms of COVID-19 and to estimate the predictive value of certain symptoms. This aids in the development of reliable screening tools. Clinical screening with a high pretest probability allows for the rapid identification of infections and the cost-effective use of testing resources. Based on our results, we suggest that loss of smell and taste be considered cardinal symptoms; we also stress that diabetes is a risk factor for a highly symptomatic course of COVID-19 infection. JMIR Publications 2020-09-09 /pmc/articles/PMC7480999/ /pubmed/32791493 http://dx.doi.org/10.2196/21956 Text en ©Martin Zens, Arne Brammertz, Juliane Herpich, Norbert Südkamp, Martin Hinterseer. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 09.09.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Short Paper
Zens, Martin
Brammertz, Arne
Herpich, Juliane
Südkamp, Norbert
Hinterseer, Martin
App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data
title App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data
title_full App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data
title_fullStr App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data
title_full_unstemmed App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data
title_short App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data
title_sort app-based tracking of self-reported covid-19 symptoms: analysis of questionnaire data
topic Short Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480999/
https://www.ncbi.nlm.nih.gov/pubmed/32791493
http://dx.doi.org/10.2196/21956
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