التفاصيل البيبلوغرافية
| العنوان: |
App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden. |
| المؤلفون: |
Kennedy, Beatrice, Fitipaldi, Hugo, Hammar, Ulf, Maziarz, Marlena, Tsereteli, Neli, Oskolkov, Nikolay, Varotsis, Georgios, Franks, Camilla A., Nguyen, Diem, Spiliopoulos, Lampros, Adami, Hans-Olov, Björk, Jonas, Engblom, Stefan, Fall, Katja, Grimby-Ekman, Anna, Litton, Jan-Eric, Martinell, Mats, Oudin, Anna, Sjöström, Torbjörn, Timpka, Toomas |
| المصدر: |
Nature Communications; 4/21/2022, Vol. 13 Issue 1, p1-12, 12p |
| مصطلحات موضوعية: |
HOSPITAL admission & discharge, COVID-19, SYMPTOMS, DIAGNOSTIC use of polymerase chain reaction, COVID-19 testing, MOBILE apps |
| مصطلحات جغرافية: |
SWEDEN |
| مستخلص: |
The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance. We enrolled 143,531 study participants (≥18 years) who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Here, we include data from 19,161 self-reported PCR tests to create a symptom-based model to estimate the individual probability of symptomatic COVID-19, with an AUC of 0.78 (95% CI 0.74–0.83) in an external dataset. These individual probabilities are employed to estimate daily regional COVID-19 prevalence, which are in turn used together with current hospital data to predict next week COVID-19 hospital admissions. We show that this hospital prediction model demonstrates a lower median absolute percentage error (MdAPE: 25.9%) across the five most populated regions in Sweden during the first pandemic wave than a model based on case notifications (MdAPE: 30.3%). During the second wave, the error rates are similar. When we apply the same model to an English dataset, not including local COVID-19 test data, we observe MdAPEs of 22.3% and 19.0% during the first and second pandemic waves, respectively, highlighting the transferability of the prediction model. The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance using daily symptom reports from study participants. Here, the authors show how syndromic surveillance can be used to estimate regional COVID-19 prevalence and to predict later COVID-19 hospital admissions. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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