Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France
Abstract Background COVID-19 pandemic highlighted the need for real-time monitoring of diseases evolution to rapidly adapt restrictive measures. This prospective multicentric study aimed at investigating radiological markers of COVID-19-related emergency activity as global estimators of pandemic evo...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-07-01
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| Series: | Insights into Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13244-021-01040-3 |
| _version_ | 1819137186654584832 |
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| author | Amandine Crombé Jean-Christophe Lecomte Nathan Banaste Karim Tazarourte Mylène Seux Hubert Nivet Vivien Thomson Guillaume Gorincour |
| author_facet | Amandine Crombé Jean-Christophe Lecomte Nathan Banaste Karim Tazarourte Mylène Seux Hubert Nivet Vivien Thomson Guillaume Gorincour |
| author_sort | Amandine Crombé |
| collection | DOAJ |
| description | Abstract Background COVID-19 pandemic highlighted the need for real-time monitoring of diseases evolution to rapidly adapt restrictive measures. This prospective multicentric study aimed at investigating radiological markers of COVID-19-related emergency activity as global estimators of pandemic evolution in France. We incorporated two sources of data from March to November 2020: an open-source epidemiological dataset, collecting daily hospitalisations, intensive care unit admissions, hospital deaths and discharges, and a teleradiology dataset corresponding to the weekly number of CT-scans performed in 65 emergency centres and interpreted remotely. CT-scans specifically requested for COVID-19 suspicion were monitored. Teleradiological and epidemiological time series were aligned. Their relationships were estimated through a cross-correlation function, and their extremes and breakpoints were compared. Dynamic linear models were trained to forecast the weekly hospitalisations based on teleradiological activity predictors. Results A total of 100,018 CT-scans were included over 36 weeks, and 19,133 (19%) performed within the COVID-19 workflow. Concomitantly, 227,677 hospitalisations were reported. Teleradiological and epidemiological time series were almost perfectly superimposed (cross-correlation coefficients at lag 0: 0.90–0.92). Maximal number of COVID-19 CT-scans was reached the week of 2020-03-23 (1 086 CT-scans), 1 week before the highest hospitalisations (23,542 patients). The best valid forecasting model combined the number of COVID-19 CT-scans and the number of hospitalisations during the prior two weeks and provided the lowest mean absolute percentage (5.09%, testing period: 2020-11-02 to 2020-11-29). Conclusion Monitoring COVID-19 CT-scan activity in emergencies accurately and instantly predicts hospitalisations and helps adjust medical resources, paving the way for complementary public health indicators. |
| first_indexed | 2024-12-22T10:46:52Z |
| format | Article |
| id | doaj.art-2a20a678a26b4808894efe7a26ace15a |
| institution | Directory Open Access Journal |
| issn | 1869-4101 |
| language | English |
| last_indexed | 2024-12-22T10:46:52Z |
| publishDate | 2021-07-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Insights into Imaging |
| spelling | doaj.art-2a20a678a26b4808894efe7a26ace15a2022-12-21T18:28:54ZengSpringerOpenInsights into Imaging1869-41012021-07-0112111310.1186/s13244-021-01040-3Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland FranceAmandine Crombé0Jean-Christophe Lecomte1Nathan Banaste2Karim Tazarourte3Mylène Seux4Hubert Nivet5Vivien Thomson6Guillaume Gorincour7Imadis TeleradiologyImadis TeleradiologyImadis TeleradiologyEmergency Department, CHU Edouard Herriot, Hospices Civils de LyonImadis TeleradiologyImadis TeleradiologyImadis TeleradiologyImadis TeleradiologyAbstract Background COVID-19 pandemic highlighted the need for real-time monitoring of diseases evolution to rapidly adapt restrictive measures. This prospective multicentric study aimed at investigating radiological markers of COVID-19-related emergency activity as global estimators of pandemic evolution in France. We incorporated two sources of data from March to November 2020: an open-source epidemiological dataset, collecting daily hospitalisations, intensive care unit admissions, hospital deaths and discharges, and a teleradiology dataset corresponding to the weekly number of CT-scans performed in 65 emergency centres and interpreted remotely. CT-scans specifically requested for COVID-19 suspicion were monitored. Teleradiological and epidemiological time series were aligned. Their relationships were estimated through a cross-correlation function, and their extremes and breakpoints were compared. Dynamic linear models were trained to forecast the weekly hospitalisations based on teleradiological activity predictors. Results A total of 100,018 CT-scans were included over 36 weeks, and 19,133 (19%) performed within the COVID-19 workflow. Concomitantly, 227,677 hospitalisations were reported. Teleradiological and epidemiological time series were almost perfectly superimposed (cross-correlation coefficients at lag 0: 0.90–0.92). Maximal number of COVID-19 CT-scans was reached the week of 2020-03-23 (1 086 CT-scans), 1 week before the highest hospitalisations (23,542 patients). The best valid forecasting model combined the number of COVID-19 CT-scans and the number of hospitalisations during the prior two weeks and provided the lowest mean absolute percentage (5.09%, testing period: 2020-11-02 to 2020-11-29). Conclusion Monitoring COVID-19 CT-scan activity in emergencies accurately and instantly predicts hospitalisations and helps adjust medical resources, paving the way for complementary public health indicators.https://doi.org/10.1186/s13244-021-01040-3Coronavirus infectionsTeleradiologyPublic healthForecasting |
| spellingShingle | Amandine Crombé Jean-Christophe Lecomte Nathan Banaste Karim Tazarourte Mylène Seux Hubert Nivet Vivien Thomson Guillaume Gorincour Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France Insights into Imaging Coronavirus infections Teleradiology Public health Forecasting |
| title | Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France |
| title_full | Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France |
| title_fullStr | Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France |
| title_full_unstemmed | Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France |
| title_short | Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France |
| title_sort | emergency teleradiological activity is an epidemiological estimator and predictor of the covid 19 pandemic in mainland france |
| topic | Coronavirus infections Teleradiology Public health Forecasting |
| url | https://doi.org/10.1186/s13244-021-01040-3 |
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