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Published in: BMC Public Health 1/2021

Open Access 01-12-2021 | Public Health | Research article

COVID-19 hotspots through clusters analysis in France (may–October 2020): where should we track the virus to mitigate the spread?

Authors: Guillaume Spaccaferri, Clémentine Calba, Pascal Vilain, Loïc Garras, Cécile Durand, Corinne Pilorget, Nahida Atiki, Pascale Bernillon, Laëtitia Bosc, Erica Fougère, Jean-Baptiste Hanon, Valérie Henry, Caroline Huchet-Kervella, Mélanie Martel, Valérie Pontiès, Damien Mouly, Enguerrand Rolland du Roscoat, Stéphane Le Vu, Jean-Claude Desenclos, Anne Laporte, Patrick Rolland, Regional MONIC group

Published in: BMC Public Health | Issue 1/2021

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Abstract

Background

In France, the lifting of the lockdown implemented to control the COVID-19 first wave in 2020 was followed by a reinforced contact-tracing (CT) strategy for the early detection of cases and transmission chains. We developed a reporting system of clusters defined as at least three COVID-19 cases, within seven days and belonging to the same community or having participated in the same gathering, whether they know each other or not. The aim of this study was to describe the typology and criticality of clusters reported between the two lockdowns in France to guide future action prioritisation.

Methods

In this study we describe the typology and criticality of COVID-19 clusters between the two lockdowns implemented in France (between May and end of October 2020). Clusters were registered in a national database named “MONIC” (MONItoring des Clusters), established in May 2020. This surveillance system identified the most affected communities in a timely manner. A level of criticality was defined for each cluster to take into consideration the risk of spreading within and outside the community of occurrence, and the health impact within the community. We compared the level of criticality according to the type of community in which the cluster occurred using Pearson’s chi-square tests.

Results

A total of 7236 clusters were reported over the study period, particularly in occupational environment (25.1%, n = 1813), elderly care structures (21.9%, n = 1586), and educational establishments (15.9%, n = 1154). We show a shift over time of the most affected communities in terms of number of clusters. Clusters reported in occupational environment and the personal sphere had increased during summer while clusters reported in educational environment increased after the start of the school year. This trend mirrors change of transmission pattern overtime according to social contacts. Among all reported clusters, 43.1% had a high level of criticality with significant differences between communities (p < 0.0001). A majority of clusters had a high level of criticality in elderly care structures (82.2%), in disability care centres (56.6%), and health care facilities (51.7%).

Conclusion

These results highlight the importance of targeting public health action based on timely sustained investigations, testing capacity and targeted awareness campaigns. The emergence of new SARS-CoV-2 variants strengthen these public health recommendations and the need for rapid and prioritise vaccination campaigns.
Literature
1.
go back to reference Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, Xia J', Yu T, Zhang X, Zhang L Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395(10223):507–513. https://doi.org/10.1016/S0140-6736(20)30211-7. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, Xia J', Yu T, Zhang X, Zhang L Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395(10223):507–513. https://​doi.​org/​10.​1016/​S0140-6736(20)30211-7.
4.
go back to reference Dehning J, Zierenberg J, Spitzner FP, Wibral M, Neto JP, Wilczek M, et al. Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions. Science. 2020;369(6500). Dehning J, Zierenberg J, Spitzner FP, Wibral M, Neto JP, Wilczek M, et al. Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions. Science. 2020;369(6500).
6.
go back to reference Santé publique France. Guide pour l’identification et l’investigation de situations de cas groupés de COVID-19. Saint-Maurice: Santé publique France [cited 2020 dec 17]. Available from: www.santepubliquefrance.fr Santé publique France. Guide pour l’identification et l’investigation de situations de cas groupés de COVID-19. Saint-Maurice: Santé publique France [cited 2020 dec 17]. Available from: www.​santepubliquefra​nce.​fr
10.
go back to reference Waltenburg MA, Victoroff T, Rose CE, Butterfield M, Jervis RH, Fedak KM, et al. Update: COVID-19 among workers in meat and poultry processing facilities—United States, April–May 2020. Morb Mortal Wkly Rep. 2020;68(29). Waltenburg MA, Victoroff T, Rose CE, Butterfield M, Jervis RH, Fedak KM, et al. Update: COVID-19 among workers in meat and poultry processing facilities—United States, April–May 2020. Morb Mortal Wkly Rep. 2020;68(29).
Metadata
Title
COVID-19 hotspots through clusters analysis in France (may–October 2020): where should we track the virus to mitigate the spread?
Authors
Guillaume Spaccaferri
Clémentine Calba
Pascal Vilain
Loïc Garras
Cécile Durand
Corinne Pilorget
Nahida Atiki
Pascale Bernillon
Laëtitia Bosc
Erica Fougère
Jean-Baptiste Hanon
Valérie Henry
Caroline Huchet-Kervella
Mélanie Martel
Valérie Pontiès
Damien Mouly
Enguerrand Rolland du Roscoat
Stéphane Le Vu
Jean-Claude Desenclos
Anne Laporte
Patrick Rolland
Regional MONIC group
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-021-11857-8

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