%0 Journal Article %T Association between the COVID-19 pandemic and pertussis derived from multiple nationwide data sources, France, 2013 to 2020 %+ Biodiversité et Epidémiologie des Bactéries pathogènes - Biodiversity and Epidemiology of Bacterial Pathogens %+ CHU Necker - Enfants Malades [AP-HP] %+ Institut Mondor de Recherche Biomédicale (IMRB) %+ Association Clinique et Thérapeutique Infantile du Val de Marne (ACTIV) %+ Groupe de Pathologie Infectieuse Pédiatrique [Paris] (GPIP) %+ Centre de Recherche Clinique [Créteil] (CRC) %+ Association Française de Pédiatrie Ambulatoire (AFPA) %+ Santé publique France - French National Public Health Agency [Saint-Maurice, France] %+ Equipe 1 : EPOPé - Épidémiologie Obstétricale, Périnatale et Pédiatrique (CRESS - U1153) %+ Centre national de Référence de la Coqueluche et autres Bordetelloses - National Reference Center for Whooping Cough and other Bordetella infections (CNR) %+ Laboratoire CERBA [Saint Ouen l'Aumône] %+ Eurofins Biomnis %+ Modélisation mathématique des maladies infectieuses - Mathematical modelling of Infectious Diseases %+ Institut Pasteur [Paris] (IP) %A Matczak, Soraya %A Levy, Corinne %A Fortas, Camille %A Cohen, Jérémie %A Béchet, Stéphane %A Aït El Belghiti, Fatima %A Guillot, Sophie %A Trombert-Paolantoni, Sabine %A Jacomo, Véronique %A Savitch, Yann %A Paireau, Juliette %A Brisse, Sylvain %A Guiso, Nicole %A Lévy-Bruhl, Daniel %A Cohen, Robert %A Toubiana, Julie %< avec comité de lecture %@ 1560-7917 %J Eurosurveillance %I European Centre for Disease Prevention and Control %V 27 %N 25 %P 2100933 %8 2022-06-23 %D 2022 %R 10.2807/1560-7917.ES.2022.27.25.2100933 %M 35748301 %Z Life Sciences [q-bio]/Human health and pathology/Infectious diseasesJournal articles %X BackgroundInterventions to mitigate the COVID-19 pandemic may impact other respiratory diseases.AimsWe aimed to study the course of pertussis in France over an 8-year period including the beginning of the COVID-19 pandemic and its association with COVID-19 mitigation strategies, using multiple nationwide data sources and regression models.MethodsWe analysed the number of French pertussis cases between 2013 and 2020, using PCR test results from nationwide outpatient laboratories (Source 1) and a network of the paediatric wards from 41 hospitals (Source 2). We also used reports of a national primary care paediatric network (Source 3). We conducted a quasi-experimental interrupted time series analysis, relying on negative binomial regression models. The models accounted for seasonality, long-term cycles and secular trend, and included a binary variable for the first national lockdown (start 16 March 2020).ResultsWe identified 19,039 pertussis cases from these data sources. Pertussis cases decreased significantly following the implementation of mitigation measures, with adjusted incidence rate ratios of 0.10 (95% CI: 0.04–0.26) and 0.22 (95% CI: 0.07–0.66) for Source 1 and Source 2, respectively. The association was confirmed in Source 3 with a median of, respectively, one (IQR: 0–2) and 0 cases (IQR: 0–0) per month before and after lockdown (p = 0.0048).ConclusionsThe strong reduction in outpatient and hospitalised pertussis cases suggests an impact of COVID-19 mitigation measures on pertussis epidemiology. Pertussis vaccination recommendations should be followed carefully, and disease monitoring should be continued to detect any resurgence after relaxation of mitigation measures. %G English %2 https://pasteur.hal.science/pasteur-03930066/document %2 https://pasteur.hal.science/pasteur-03930066/file/eurosurv-27-25-2.pdf %L pasteur-03930066 %U https://pasteur.hal.science/pasteur-03930066 %~ PASTEUR %~ CNRS %~ CNAM %~ APHP %~ IMRB %~ UPEC %~ CHU-UNIV-PARIS5 %~ INRAE %~ UNIV-PARIS %~ UNIVERSITE-PARIS %~ UP-SANTE %~ CRESS %~ TEST3-HALCNRS %~ TEST4-HALCNRS %~ HESAM-CNAM %~ HESAM %~ FRM %~ MATH-MODEL-INFECT-DISEASES %~ PASTEUR_UMR2000 %~ RESEAU-EAU %~ TEST5-HALCNRS