key: cord-1003790-q50ycc4y authors: Romain-Scelle, Nicolas; Elias, Christelle; Vanhems, Philippe title: COVID-19 vaccine is correlated with favourable epidemiological indicators in the Auvergne-Rhône-Alpes region (France): an ecological study date: 2021-12-22 journal: Vaccine DOI: 10.1016/j.vaccine.2021.12.036 sha: f9f744415cd98043cc67233e4a8ecbee369fae29 doc_id: 1003790 cord_uid: q50ycc4y COVID-19 vaccination has proven to be effective in preventing severe cases, reducing viral load, and transmissibility. The aim of this study was to evaluate the impact of vaccination 11 months after implementation on epidemiological indicators and the effective reproduction number in one French region. We plotted four indicators with vaccination coverage as the explaining variable and estimated the impact of vaccination using the reduction rates in infections and hospital admissions. A reduction of 98% in COVID-19-related hospitalisation 11 months after the vaccine campaign began in January 2021 has been reported while vaccine coverage increased over time. Those results do not make it possible to postulate a causal relationship but do support the effect of vaccination against multiple variants of concern. Non-pharmaceutical measures remain necessary to attain complete epidemic control. Open epidemiological data should be considered to monitor vaccine effectiveness wherever possible. Clinical studies have now demonstrated the benefit of the vaccines beyond protection against the development of severe cases of COVID-19 with an efficacy between 60% and 85% (1,2), a reduction in viral load among asymptomatic carriers (3, 4) and therefore, a reduction in transmissibility (5, 6) .Vaccine coverage requirements to reach herd immunity in the general population have also been estimated to be approximately 70% (7, 8) . Although previously cited estimations were found against strains not yet showing mutations of concern, efficacy of currently available vaccines against the delta variant was found to be comparable regarding hospital admissions and lower (with varying estimates) regarding infection (9, 10) . Additional and convergent results from various locations based on various study designs are needed to confirm the positive impact of the vaccines on the pandemic since health determinants differ from one country to another. The monitoring of the COVID-19 pandemic in France is built on reactive information systems for fast and adapted public health response. Standardised data collection from validated sources by the national public health agency (Santé publique France) enable analysis in real time of epidemiological indicators including national vaccine coverage in various French regions (11). The objective was to report a graphical ecological analysis to correlate the increase in vaccination use by time with the epidemiological indicators of viral circulation in the Auvergne-Rhône-Alpes region, including the effective reproduction number (R e ) until November 15, 2021. This study was conducted in the Auvergne-Rhône-Alpes French administrative region (estimated population in 2020: 8,032,377 inhabitants, capital: Lyon), between January 1 and November 15, 2021. The study region is highlighted in Fig. 3 . We collected the following weekly publicly available epidemiological indicators for all 12 administrative subdivisions (French departments) of the region: SARS-CoV-2 new infection rate (/100,000 person-week), rate of hospital admissions for COVID-19 (/100,000 person-week), proportion of testing positivity for SARS-CoV-2 carriage (/100 persons tested), and vaccine coverage (partial and complete, /100 inhabitants). Partial and complete vaccine coverage are respectively defined as incomplete (lacking one dose) and complete vaccination (excluding boosters) with respect of previous COVID-19 and altered immune response at an individual level according to the French national guidelines from the French "Haute Autorité de Santé". We do not take into account for booster injections, as we do not have sufficient cases and data to provide any meaningful results. Infection data (incidence rate, positivity rate) are collected from the national testing information system, hospital admission data from the victim information system, and vaccination data from the national vaccination information system. We also collected the estimated R e , computed weekly from infection data following the method described in Cori et al. (12) , only available for the entire region. Every dataset used in the analysis was colligated by the national public health agency (Santé publique France), and mandated to be available through the French government open-data platform (11). The information systems collected personal data in compliance with French law and regulations (13) (14) (15) . We plotted pandemic-related indicators (Y axis) as a function of vaccine coverage (X axis) for each day all indicators were estimated. To provide a meaningful visualisation of the lockdown and curfews periods on the figures, regional vaccine coverage observed at the beginning and end of each immunization, all vaccine-related indicators were joined with the epidemiologic indicators using a 14-day lag. The R software (17) with ggplot2 (18) and mgcv (19) packages was used. Penalized cubic regression spline was used to produce tendency lines and their respective confidence interval (with α risk = 0.05). The results regarding hospital admissions must be assessed with respect to the varying advancement of the vaccination campaign among ages: as old age is a determinant risk factor for severe COVID-19, the impact of vaccination is likely associated with an effective coverage among the elderly. By June 1, 2021, within the study region, complete vaccination coverage reached above 75% for individuals aged 75 or more and 58% between 70 and 74, with all other age groups below 37%. By November 15, 2021 , final date of the study period, complete coverage reached 75% at minimum (among individuals aged 20 to 25). This signals a differential impact of vaccination in the first semester of 2021 with a likely stronger effect on hospital admissions than during the second semester. We took advantage of multiple reliable and exhaustive data collection systems to diffuse encouraging trends regarding vaccination effects on the pandemic mitigation effort. Owing to the public effort to make these datasets open to the general public in France and abroad, this class of analysis can be easily replicated in one or multiple nations and to a degree included in the general surveillance of vaccine effectiveness. The present analysis was conducted between January 1 and November 15, 2021, a time-period marked by two emerging variants of concern. The alpha variant reached 45.7% of prevalence among infection cases mid-Febuary, peaked at 89% mid-April and was pushed back to 50% by June 21 as Delta reached 43.1% a week later, and over 90% by July 19 (20) . Those results are coherent with previous literature regarding vaccine efficacy on severe cases and infection and considering the genetic variability of SARS-CoV-2 during the study period, support the effect of vaccination against multiple variants of concern. The Auvergne-Rhone-Alpes region may not be representative of the country, but epidemiological studies performed in this area included a total population of more than 8 million inhabitants and could generate results that could be compared with other areas in France or other countries in Europe with neighbouring demographic indicators such as Switzerland or Austria. In conclusion, these results support an encouraging control of COVID-19 in France since the implementation of vaccinations. Variant emergence, appropriate individual preventive measures, nonpharmaceutical interventions and vaccines constitute the major determinants of the future spread of The incidence rate unit is /100,000 person-week *Interpretation: a 98% reduction in hospital admission rate was observed between December 15, 2020 and November 15, 2021 across the region Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine Post-vaccination SARS-CoV-2 infections and incidence of presumptive B.1.427/B.1.429 variant among healthcare personnel at a northern California academic medical center Decreased SARS-CoV-2 viral load following vaccination. medRxiv Community-level evidence for SARS-CoV-2 vaccine protection of unvaccinated individuals Impact of Vaccination on Household Transmission of SARS-COV-2 in England Estimating the burden of SARS-CoV-2 in France Herd immunity -estimating the level required to halt the COVID-19 epidemics in affected countries Impact of Delta on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK BNT162b2 and mRNA-1273 COVID-19 vaccine effectiveness against the SARS-CoV-2 Delta variant in Qatar A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics Décret n° 2020-551 du 12 mai 2020 relatif aux systèmes d'information mentionnés à l'article 11 de la loi n° 2020-546 du 11 mai 2020 prorogeant l'état d'urgence sanitaire et complétant ses dispositions Décret n° 2020-1690 du 25 décembre 2020 autorisant la création d'un traitement de données à caractère personnel relatif aux vaccinations contre la covid-19 Article R3131-10-1 -Code de la santé publique -Légifrance Vaccine effects and impact of vaccination programmes in post-licensure studies. Vaccine R: A Language and Environment for Statistical Computing Austria: R Foundation for Statistical Computing Elegant Graphics for Data Analysis Generalized Additive Models: An Introduction with R Coronavirus : chiffres clés et évolution de la COVID-19 en France et dans le Monde We thank the following organisations for access to national data: Santé publique France (www.santepubliquefrance.fr), Paris University Hospital (AP-HP, www.aphp.fr), French Health The included departments are named as follows: Ain (01), Allier (03), Ardèche (07), Cantal (15) PV has received grants from Merck Sharp & Dohme and Anios, and consulting fees from Astellas Pharma, Sanofi and Pfizer. These organisations were not involved in the analysis or writing of this manuscript. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.☒ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: PV has received grants from Merck Sharp & Dohme and Anios, and consulting fees from Astellas Pharma, Sanofi and Pfizer. These organisations were not involved in the analysis or writing of this manuscript. The remaining authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.