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Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses
BACKGROUND: Unprecedented lockdown measures have been introduced in countries worldwide to mitigate the spread and consequences of COVID-19. Although attention has been focused on the effects of these measures on epidemiological indicators relating directly to the infection, there is increased recog...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7561445/ https://www.ncbi.nlm.nih.gov/pubmed/32997640 http://dx.doi.org/10.2196/21364 |
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author | Mehl, Alicia Bergey, Francois Cawley, Caoimhe Gilsdorf, Andreas |
author_facet | Mehl, Alicia Bergey, Francois Cawley, Caoimhe Gilsdorf, Andreas |
author_sort | Mehl, Alicia |
collection | PubMed |
description | BACKGROUND: Unprecedented lockdown measures have been introduced in countries worldwide to mitigate the spread and consequences of COVID-19. Although attention has been focused on the effects of these measures on epidemiological indicators relating directly to the infection, there is increased recognition of their broader health implications. However, assessing these implications in real time is a challenge, due to the limitations of existing syndromic surveillance data and tools. OBJECTIVE: The aim of this study is to explore the added value of mobile phone app–based symptom assessment tools as real-time health insight providers to inform public health policy makers. METHODS: A comparative and descriptive analysis of the proportion of all self-reported symptoms entered by users during an assessment within the Ada app in Germany and the United Kingdom was conducted between two periods, namely before and after the implementation of “Phase One” COVID-19 measures. Additional analyses were performed to explore the association between symptom trends and seasonality, and symptom trends and weather. Differences in the proportion of unique symptoms between the periods were analyzed using a Pearson chi-square test and reported as log2 fold changes. RESULTS: Overall, 48,300-54,900 symptomatic users reported 140,500-170,400 symptoms during the Baseline and Measures periods in Germany. Overall, 34,200-37,400 symptomatic users in the United Kingdom reported 112,100-131,900 symptoms during the Baseline and Measures periods. The majority of symptomatic users were female (Germany: 68,600/103,200, 66.52%; United Kingdom: 51,200/71,600, 72.74%). The majority were aged 10-29 years (Germany: 68,500/100,000, 68.45%; United Kingdom: 50,900/68,800, 73.91%), and about one-quarter were aged 30-59 years (Germany: 26,200/100,000, 26.15%; United Kingdom: 14,900/68,800, 21.65%). Overall, 103 symptoms were reported either more or less frequently (with statistically significant differences) during the Measures period as compared to the Baseline period, and 34 of these were reported in both countries. The following mental health symptoms (log2 fold change, P value) were reported less often during the Measures period: inability to manage constant stress and demands at work (–1.07, P<.001), memory difficulty (–0.56, P<.001), depressed mood (–0.42, P<.001), and impaired concentration (–0.46, P<.001). Diminished sense of taste (2.26, P<.001) and hyposmia (2.20, P<.001) were reported more frequently during the Measures period. None of the 34 symptoms were found to be different between the same dates in 2019. In total, 14 of the 34 symptoms had statistically significant associations with weather variables. CONCLUSIONS: Symptom assessment apps have an important role to play in facilitating improved understanding of the implications of public health policies such as COVID-19 lockdown measures. Not only do they provide the means to complement and cross-validate hypotheses based on data collected through more traditional channels, they can also generate novel insights through a real-time syndromic surveillance system. |
format | Online Article Text |
id | pubmed-7561445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-75614452020-10-31 Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses Mehl, Alicia Bergey, Francois Cawley, Caoimhe Gilsdorf, Andreas JMIR Mhealth Uhealth Original Paper BACKGROUND: Unprecedented lockdown measures have been introduced in countries worldwide to mitigate the spread and consequences of COVID-19. Although attention has been focused on the effects of these measures on epidemiological indicators relating directly to the infection, there is increased recognition of their broader health implications. However, assessing these implications in real time is a challenge, due to the limitations of existing syndromic surveillance data and tools. OBJECTIVE: The aim of this study is to explore the added value of mobile phone app–based symptom assessment tools as real-time health insight providers to inform public health policy makers. METHODS: A comparative and descriptive analysis of the proportion of all self-reported symptoms entered by users during an assessment within the Ada app in Germany and the United Kingdom was conducted between two periods, namely before and after the implementation of “Phase One” COVID-19 measures. Additional analyses were performed to explore the association between symptom trends and seasonality, and symptom trends and weather. Differences in the proportion of unique symptoms between the periods were analyzed using a Pearson chi-square test and reported as log2 fold changes. RESULTS: Overall, 48,300-54,900 symptomatic users reported 140,500-170,400 symptoms during the Baseline and Measures periods in Germany. Overall, 34,200-37,400 symptomatic users in the United Kingdom reported 112,100-131,900 symptoms during the Baseline and Measures periods. The majority of symptomatic users were female (Germany: 68,600/103,200, 66.52%; United Kingdom: 51,200/71,600, 72.74%). The majority were aged 10-29 years (Germany: 68,500/100,000, 68.45%; United Kingdom: 50,900/68,800, 73.91%), and about one-quarter were aged 30-59 years (Germany: 26,200/100,000, 26.15%; United Kingdom: 14,900/68,800, 21.65%). Overall, 103 symptoms were reported either more or less frequently (with statistically significant differences) during the Measures period as compared to the Baseline period, and 34 of these were reported in both countries. The following mental health symptoms (log2 fold change, P value) were reported less often during the Measures period: inability to manage constant stress and demands at work (–1.07, P<.001), memory difficulty (–0.56, P<.001), depressed mood (–0.42, P<.001), and impaired concentration (–0.46, P<.001). Diminished sense of taste (2.26, P<.001) and hyposmia (2.20, P<.001) were reported more frequently during the Measures period. None of the 34 symptoms were found to be different between the same dates in 2019. In total, 14 of the 34 symptoms had statistically significant associations with weather variables. CONCLUSIONS: Symptom assessment apps have an important role to play in facilitating improved understanding of the implications of public health policies such as COVID-19 lockdown measures. Not only do they provide the means to complement and cross-validate hypotheses based on data collected through more traditional channels, they can also generate novel insights through a real-time syndromic surveillance system. JMIR Publications 2020-10-09 /pmc/articles/PMC7561445/ /pubmed/32997640 http://dx.doi.org/10.2196/21364 Text en ©Alicia Mehl, Francois Bergey, Caoimhe Cawley, Andreas Gilsdorf. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 09.10.2020. 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 JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Mehl, Alicia Bergey, Francois Cawley, Caoimhe Gilsdorf, Andreas Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses |
title | Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses |
title_full | Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses |
title_fullStr | Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses |
title_full_unstemmed | Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses |
title_short | Syndromic Surveillance Insights from a Symptom Assessment App Before and During COVID-19 Measures in Germany and the United Kingdom: Results From Repeated Cross-Sectional Analyses |
title_sort | syndromic surveillance insights from a symptom assessment app before and during covid-19 measures in germany and the united kingdom: results from repeated cross-sectional analyses |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7561445/ https://www.ncbi.nlm.nih.gov/pubmed/32997640 http://dx.doi.org/10.2196/21364 |
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