COVID-19 In France Research Articles

Biomarkers of COVID-19 short-term worsening: a multiparameter analysis within the prospective multicenter COVIDeF cohort.

During a pandemic like COVID-19, hospital resources are constrained and accurate severity triage of the patients is required. The objective of this study is to estimate the predictive performances of candidate biomarkers for short-term worsening (STW) of COVID-19. Prospective, multicenter (20 hospitals in Paris) cohort study of consecutive COVID-19 patients with systematic biobanking at admission, during the first waves of COVID-19 in France in 2020 (COVIDeF cohort). Consecutive COVID-19 patients were screened for inclusion. They were excluded in presence of severity criteria defined by either an ICU admission, mechanical ventilation (including noninvasive ventilation), acute respiratory distress, or in-hospital death before sampling. Routine blood tests measured during usual care and centralized systematic measurement of creatine kinase, C-reactive protein (CRP), procalcitonin, soluble urokinase plasminogen activator receptor (suPAR), high-sensitive troponin T (TnT-hs), N terminal pro-B natriuretic peptide (NT-proBNP), calprotectin, platelet factor 4, mid-regional pro-adrenomedullin (MR-proADM), and proendothelin were performed. The primary outcome was STW, defined by a severity criteria within 7 days. A backward stepwise logistic regression model and a 'best subset' approach were used to identify independent association, and the area under the receiving operator characteristics (AUROC) was computed. Five hundred and eleven patients were analyzed, of whom 60 (11.7%) experienced STW. Median time to occurrence of a severity criteria was 3 days. At admission, lower values of eosinophils, lymphocytes, platelets, alanine aminotransferase, and higher values of neutrophils, creatinine, urea, CRP, TnT-hs, suPAR, NT-proBNP, calprotectin, procalcitonin, MR-proADM, and proendothelin were predictive of worsening. Stepwise logistic regression identified three biomarkers significantly associated with worsening: CRP [adjusted odds ratio (aOR): 1.10, 95% confidence interval (95% CI): 1.06-1.15 for a 10-unit increase, AUROC: 0.73 (0.66-0.79)], procalcitonin [aOR: 0.42, 95% CI: 0.22-0.81, AUROC: 0.69 (0.64-0.88)], and MR-proADM [aOR: 2.85, 95% CI: 1.74-4.69, AUROC: 0.75 (0.69-0.81)]. These biomarkers outperformed clinical variables except diabetes and cancer comorbidities. In this multicenter prospective study that assessed a large panel of biomarkers for COVID-19 patients, CRP, procalcitonin, and MR-proADM were independently associated with the risk of STW. ClinicalTrials.gov NCT04352348.

COPD Exacerbations Before and During COVID-19 in France, Germany, Italy, the UK and the US.

Exacerbations of chronic obstructive pulmonary disease (COPD) were reported less frequently during the COVID-19 pandemic. We report real-world data on COPD exacerbation rates before and during this pandemic. Exacerbation patterns were analysed using electronic medical records or claims data of patients with COPD before (2017-2019) and during the COVID-19 pandemic (2020 through early 2022) in France, Germany, Italy, the United Kingdom and the United States. Data from each country were analysed separately. The proportions of patients with COPD receiving maintenance treatment were also estimated. The proportion of patients with exacerbations fell 45-78% across five countries in 2020 versus 2019. Exacerbation rates in most countries were reduced by >50% in 2020 compared with 2019. The proportions of patients with an exacerbation increased in most countries in 2021. Across each country, seasonal exacerbation increases seen during autumn and winter in pre-pandemic years were absent during the first year of the pandemic. The percentage of patients filling COPD prescriptions across each country increased by 4.53-22.13% in 2019 to 9.94-34.17% in 2021. Early, steep declines in exacerbation rates occurred in 2020 versus 2019 across all five countries and were accompanied by a loss of the seasonal pattern of exacerbation.

Questioning the "Ease" in disease: Was living with HIV a burden or boost during the first wave of Covid-19 in France? A qualitative study (COVIDHIV).

Clinical research has focused on risk factors and treatment for severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), particularly in people with a comorbidity including the human immunodeficiency virus (HIV), but little attention has been paid to the care pathway. This article aims to show how living with HIV may have been a biopsychosocial burden or boost in care pathways for Covid-19. People living with HIV (PLHIV) from 9 clinical centers were invited to participate in this qualitative study. The sampling was purposive with a maximum variation in their sociodemographic profiles. Semi-structured interviews were conducted until data saturation, then coded for thematic analysis, using an inductive general approach. We interviewed 34 PLHIV of which 20 had SARS-COV-2 once. They were 24 males, 26 born in France; median age: 55. Twenty had a CD4 number above 500, and all were on antiretroviral therapy (ART). HIV appeared as a burden when Covid-19 symptoms reminded HIV seroconversion, fear of contamination, and triggered questions about ART effectiveness. HIV was not considered relevant when diagnosing Covid-19, caused fear of disclosure when participants sought SARS-COV-2 testing, and its care in hospitals was disrupted by the pandemic. ART-pill fatigue caused avoidance for Covid-19 treatment. As a boost, living with HIV led participants to observe symptoms, to get advice from healthcare professionals, and screening access through them. Some participants could accept the result of screening or a clinical diagnosis out of resilience. Some could consider ART or another drug prescribed by their HIV specialist help them to recover from Covid-19. Living with HIV could function as a burden and/or a boost in the care pathways for Covid-19, according to patients' relationship to their HIV history, comorbidities and representation of ART. Covid-19 in PLHIV needs further qualitative study to gain a more comprehensive assessment of the pandemic's consequences on their lives and coping strategies.

The health state of France before COVID-19 pandemic between 1990 and 2019: an analysis of the Global Burden of Disease study 2019

France faces nowadays some major challenges regarding its health care system including medically underserved areas, social health inequalities, and hospital pressures. Various indicators and sources of data allow us to describe the health status of a population and, consequently, to assess the impact of these challenges. We assessed the burden of diseases before COVID-19 in France in 2019 and its evolution from 1990 to 2019, and compared it with Western European countries. We used specific Global Burden of Diseases (GBD) metrics: socio-demographic index (SDI), life expectancy (LE), healthy life expectancy (HALE), years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) with their 95% uncertainty interval (95% UI). We compared French age-standardized metrics to those for other Western European Countries for both sexes and also between 1990 and 2019. We also described the specific causes of these different metrics. We observed for life expectancy at birth in France a trend to an improvement over time from 77.2 (95% UI: 77.2-77.3) years in 1990 to 82.9 (82.7-83.1) in 2019, which represented the seventh highest life expectancy among 23 Western European countries. HALE at birth in France increased from 67.0 (64.0-69.7) to 71.5 (68.1-74.5), which represented the fourth highest HALE among 23 Western European countries. In France, the total number of DALY per 100.000 population tended to decrease from 25,192 (22,374-28,351) in 1990 to 18,782 (16,408-21,920) in 2019. As compared to other European countries, the burden due to cardiovascular diseases was lower. Neoplasms and cardio-vascular diseases were the two leading causes of YLLs. Mental and musculoskeletal disorders were the two leading causes of YLDs. Overall, these results highlight a clear trend of improvement in the health status in France with certain differences between western European countries. The health policy makers need to devise interventional strategies to reduce the burden of diseases and injuries, with specific attention to causes such as cancers, cardiovascular diseases, mental health and musculoskeletal disorders. Bill & Melinda Gates Foundation.

Estimating the population effectiveness of interventions against COVID-19 in France: A modelling study

BackgroundNon-pharmaceutical interventions (NPIs) and vaccines have been widely used to manage the COVID-19 pandemic. However, uncertainty persists regarding the effectiveness of these interventions due to data quality issues, methodological challenges, and differing contextual factors. Accurate estimation of their effects is crucial for future epidemic preparedness. MethodsTo address this, we developed a population-based mechanistic model that includes the impact of NPIs and vaccines on SARS-CoV-2 transmission and hospitalization rates. Our statistical approach estimated all parameters in one step, accurately propagating uncertainty. We fitted the model to comprehensive epidemiological data in France from March 2020 to October 2021. With the same model, we simulated scenarios of vaccine rollout. ResultsThe first lockdown was the most effective, reducing transmission by 84 % (95 % confidence interval (CI) 83–85). Subsequent lockdowns had diminished effectiveness (reduction of 74 % (69–77) and 11 % (9–18), respectively). A 6 pm curfew was more effective than one at 8 pm (68 % (66–69) vs. 48 % (45–49) reduction), while school closures reduced transmission by 15 % (12–18). In a scenario without vaccines before November 2021, we predicted 159,000 or 168 % (95 % prediction interval (PI) 70-315) more deaths and 1,488,000 or 300 % (133-492) more hospitalizations. If a vaccine had been available after 100 days, over 71,000 deaths (16,507–204,249) and 384,000 (88,579–1,020,386) hospitalizations could have been averted. ConclusionOur results highlight the substantial impact of NPIs, including lockdowns and curfews, in controlling the COVID-19 pandemic. We also demonstrate the value of the 100 days objective of the Coalition for Epidemic Preparedness Innovations (CEPI) initiative for vaccine availability.

Optimal policy for control of epidemics with constrained time intervals and region-based interactions

<p>We introduce a policy model coupled with the susceptible–infected- recovered (SIR) epidemic model to study interactions between policy-making and the dynamics of epidemics. We considered both single-region policies as well as game-theoretic models involving interactions among several regions and hierarchical interactions among policy-makers modeled as multi-layer games. We assumed that the policy functions are piece-wise constant with a minimum time interval for each policy stage, considering that policies cannot change frequently in time or be easily followed. The optimal policy was obtained by minimizing a cost function that consists of an implementation cost, an impact cost, and, in the case of multi-layer games, a non-compliance cost. We show, in a case study of COVID-19 in France, that when the cost function is reduced to the impact cost and parameterized as the final epidemic size, the solution approximates that of the optimal control in Bliman et al, (2021) for a sufficiently small minimum policy time interval. For a larger time interval, however, the optimal policy is a step down function, quite different from the step up structure typically deployed during the COVID-19 pandemic. In addition, we present a counterfactual study of how the pandemic would have evolved if herd immunity was reached during the second wave in the county of Los Angeles, California. Finally, we study a case of three interacting counties with and without a governing state.</p>

HTA149 Handling Uncertainty in Health-Economic Assessments: Experience From COVID-19 in France

HTA149 Handling Uncertainty in Health-Economic Assessments: Experience From COVID-19 in France

Understanding public attitudes during Covid-19 in France with Polanyi and Gramsci: a political economy of an epidemiological and economic disaster

Understanding public attitudes during Covid-19 in France with Polanyi and Gramsci: a political economy of an epidemiological and economic disaster

Monitoring the reproductive number of COVID-19 in France: Comparative estimates from three datasets.

The effective reproduction number (Rt) quantifies the average number of secondary cases caused by one person with an infectious disease. Near-real-time monitoring of Rt during an outbreak is a major indicator used to monitor changes in disease transmission and assess the effectiveness of interventions. The estimation of Rt usually requires the identification of infected cases in the population, which can prove challenging with the available data, especially when asymptomatic people or with mild symptoms are not usually screened. The purpose of this study was to perform sensitivity analysis of Rt estimates for COVID-19 surveillance in France based on three data sources with different sensitivities and specificities for identifying infected cases. We applied a statistical method developed by Cori et al. to estimate Rt using (1) confirmed cases identified from positive virological tests in the population, (2) suspected cases recorded by a national network of emergency departments, and (3) COVID-19 hospital admissions recorded by a national administrative system to manage hospital organization. Rt estimates in France from May 27, 2020, to August 12, 2022, showed similar temporal trends regardless of the dataset. Estimates based on the daily number of confirmed cases provided an earlier signal than the two other sources, with an average lag of 3 and 6 days for estimates based on emergency department visits and hospital admissions, respectively. The COVID-19 experience confirmed that monitoring temporal changes in Rt was a key indicator to help the public health authorities control the outbreak in real time. However, gaining access to data on all infected people in the population in order to estimate Rt is not straightforward in practice. As this analysis has shown, the opportunity to use more readily available data to estimate Rt trends, provided that it is highly correlated with the spread of infection, provides a practical solution for monitoring the COVID-19 pandemic and indeed any other epidemic.

Predictors of mental well-being over the first lockdown period due to the COVID-19 pandemic in France. A repeated cross-sectional study.

Numerous studies have investigated the positive and negative effects of potential predictors of well-being during lockdowns due to COVID-19. Yet, little is known on whether these effects significantly changed with time spent in lockdown. In the current study, we described the association of mental well-being with a large number of background characteristics (e.g., socio-demographic or health-related factors), COVID-related factors, and coping strategies, over the duration of the first lockdown due to COVID-19 in France. A nationwide online survey was conducted over 7 of the 8 weeks of the 1st lockdown in France, i.e., from 25 March 2020 to 10 May 2020. The level of mental well-being was reported using the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). We also measured various background characteristics (e.g., age, sex, education, health issues), COVID-related factors (e.g., health and economic risks, agreement with lockdown), and coping strategies. Our analytical strategy enabled us to disentangle effects aggregated over the study period from those that linearly vary with time spent in lockdown. Our final dataset included 18,957 participants. The level of mental well-being dropped gradually from the third to the eighth week of lockdown [49.7 (sd 7.9) to 45.5 (sd 10.6)]. Time in lockdown was associated with a decrease in well-being (for each additional 10 days of lockdown: B = -0.30, 95%CI: -0.62, -0.15). Factors that showed significantly negative and positive effects on well-being as time in lockdown progressed were (for each additional 10 days of lockdown): having current psychiatric problems (B = -0.37; 95%CI: -0.63, -0.04), worries about having access to personal protective equipment (B = -0.09; 95%CI: -0.18, -0.01), coping by having positive beliefs about the future of the pandemics (B = 0.29; 95%CI: 0.04, 0.62), being supported by neighbors (B = 0.24; 95%CI: 0.04, 0.44), and being involved in collective actions (B = 0.23; 95%CI: 0.04, 0.46). Participants from our sample saw a drop in their mental well-being throughout the first period of COVID-19 lockdown. Policymakers should be mindful of factors contributing to greater deterioration of mental well-being over time, such as having current psychiatric issues. Promoting collective actions and local support from neighbors may alleviate the deterioration of mental well-being over time.

Pathogen threat increases electoral success for conservative parties: Results from a natural experiment with COVID-19 in France.

Pathogen threat increases electoral success for conservative parties: Results from a natural experiment with COVID-19 in France.

Echocardiography Can Improve the Selection of Mechanical Support Strategies for Patients With Severe COVID-19 Respiratory Distress Syndrome.

To the Editor: I read with interest the study by Beyls et al.1 which compared the different clinical characteristics and outcomes of patients with COVID-19–related respiratory distress syndrome (CARDS) requiring veno-venous extracorporeal membrane oxygenation (VV-ECMO) during the three epidemic waves of COVID-19 in France. Despite the increasing knowledge on the particularities of severe COVID-19 and the growing experience in the management of severe CARDS, that study revealed a massive increase in the 90 day mortality of patients undergoing VV-ECMO during the second epidemic wave. One plausible explanation for that important observation could be the fact that over the course of the pandemic, new variants of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have continuously emerged. Because the different waves of infection were mainly associated with one or more SARS-CoV-2 “variants of concern” (VOC) with different pathogenicity, it appears obvious that the pathogenicity of the dominant VOC in an infection wave can have important impacts on the outcomes of patients with severe COVID-19. Indeed, the Delta/B.1.617.2 variant, which was dominant during the second wave, is known to be associated with higher risk of death than both the previously dominant VOCs (i.e., Alpha/B.1.1.7, Beta/B.1.351 and Gamma/P.1) and the Omicron/B1.1.529 variant which became the dominant VOC during third wave.2,3 The excessively high mortality rate (i.e., 85.7%1) of patients supported by ECMO during the second wave deserves particular attention because a renewed appearance of more pathogenic VOCs cannot be ruled out. The high incidence of extensive pulmonary thrombotic microangiopathy associated with severe ventilation-perfusion mismatch, increased resistance in the pulmonary circulation and frequent afterload-induced right ventricular (RV) failure, which were identified as distinct features of severe CARDS (especially in infections caused by the Delta/B.1.617.2 variant) were often the leading cause of death attributed to COVID-19.4,5 Early detection of patients with increasing RV hemodynamic overloading can facilitate the selection of the most appropriate management (including the requirement of ECMO or a combined respiratory and circulatory support), which can be decisive for the patients’ survival.4 In severe RV afterload mismatch, the RV output decreases substantially, and RV dilation-related tricuspid regurgitation can rapidly increase. In such situations, attempting to treat the underlying etiology of impaired gas exchange using VV-ECMO alone may become insufficient.4 Considering the high incidence and the deleterious prognostic impact of right heart involvement in severe COVID-19 it seems likely that this was also the major cause of the high mortality rate documented by Beyls et al.1 for their ECMO-supported patients (92% with VV-ECMO) during the second wave. Thus, close monitoring of the right heart in patients with CARDS associated with hemodynamic instability, already before overt RV failure develops, could substantially improve therapeutic decision-making. It is therefore difficult to understand the still limited use of routine echocardiography for the surveillance of hospitalized patients with COVID-19. Echocardiography can improve the identification of patients with CARDS requiring ECMO therapy, the selection of the most appropriate support strategy (VV-ECMO, veno-arterial-ECMO, or VV-ECMO plus RV or left ventricle temporary percutaneous mechanical support) and also the weaning decision-making after cardiopulmonary amelioration during the support.

Priming congruence and COVID-19 vaccination intention: a mediation analysis.

This study took place at the height of the fifth wave of COVID-19 in France, coinciding with stigmatizing communication toward the unvaccinated. We hypothesized that adherence to this communication would facilitate or inhibit the effects of priming on vaccination intention, depending on whether the priming included a dimension of connection to others. In a convenience online French sample (N = 1800, M age = 26.30), vaccination intention was asked after love priming, no love/prejudice priming, materialism priming, or a control condition. Participants also reported their adherence to restrictive measures, i.e., media control, vaccination pass, and mandatory vaccination. Vaccination intention was higher in the no love/prejudice and materialism conditions than in the love and control conditions. Adherence to restrictive measures mediated the effect of prejudice or materialism priming on intention to get vaccinated. Implications of these results are discussed in light of the socially situated cognition perspective and the congruence of (a) a societal context of communication toward the vaccine and the unvaccinated, (b) the participant's degree of adherence to that communication, (c) the theme of priming, whether or not related to feeling connected to others. Implications of materialism priming are discussed, and the effect of commitment on intention to get vaccinated.

Correcting the reproduction number for time-varying tests: A proposal and an application to COVID-19 in France.

We provide a novel way to correct the effective reproduction number for the time-varying amount of tests, using the acceleration index (Baunez et al., 2021) as a simple measure of viral spread dynamics. Not correcting results in the reproduction number being a biased estimate of viral acceleration and we provide a formal decomposition of the resulting bias, involving the useful notions of test and infectivity intensities. When applied to French data for the COVID-19 pandemic (May 13, 2020-October 26, 2022), our decomposition shows that the reproduction number, when considered alone, characteristically underestimates the resurgence of the pandemic, compared to the acceleration index which accounts for the time-varying volume of tests. Because the acceleration index aggregates all relevant information and captures in real time the sizable time variation featured by viral circulation, it is a more parsimonious indicator to track the dynamics of an infectious disease outbreak in real time, compared to the equivalent alternative which would combine the reproduction number with the test and infectivity intensities.

Modeling the impact of national and regional lockdowns on the 2020 spring wave of COVID-19 in France

Several countries have implemented lockdowns to control their COVID-19 epidemic. However, questions like “where” and “when” still require answers. We assessed the impact of national and regional lockdowns considering the French first epidemic wave of COVID-19 as a case study. In a regional lockdown scenario aimed at preventing intensive care units (ICU) saturation, almost all French regions would have had to implement a lockdown within 10 days and 96% of ICU capacities would have been used. For slowly growing epidemics, with a lower reproduction number, the expected delays between regional lockdowns increase. However, the public health costs associated with these delays tend to grow with time. In a quickly growing pandemic wave, defining the timing of lockdowns at a regional rather than national level delays by a few days the implementation of a nationwide lockdown but leads to substantially higher morbidity, mortality, and stress on the healthcare system.

The burden of hospitalisations for COVID-19 in France: a study of all cases in the national insurance claims database in 2020

ABSTRACT Background The economic consequences of the recent COVID-19 pandemic were substantial. However, direct medical costs in France have not been determined. Objective To describe patient characteristics, intensity of care, mortality, and direct medical costs in patients hospitalised for COVID-19 infections in France. Study design A retrospective study of the French national hospital claims database for 2020. Setting Hospital care. Patients or other participants All patients hospitalised for COVID-19 in 2020 were included and classified by hospitalisation duration into acute phase and prolonged COVID-19. Intervention Stratification by intensity of care (Level 1: no or low-flow oxygen support; Level 2: non-invasive ventilation; Level 3: mechanical ventilation). Main outcome measure Cost of hospital care in 2020 Euros from a payer perspective. Results 199,455 patients were hospitalised for COVID-19 in France in 2020. 17,824 patients (8.9%) received mechanical ventilation and 32,602 patients (16.3%) died. Mean per patient cost was €5,510 ± 7,142. This cost was highest in patients receiving Level 3 care, patients aged >80 years and in those with prolonged COVID. Conclusion The economic burden of hospitalisations for COVID-19 infections in France during 2020 was substantial. The study provides robust baseline data to benchmark advances in the standard of care and to nurture epidemiological models.

EPH4 Burden and Characteristics of COVID-19 in France During 2020 Based on National Hospital Database

EPH4 Burden and Characteristics of COVID-19 in France During 2020 Based on National Hospital Database

Using hospital data for monitoring the dynamics of COVID-19 in France

The objective of this article is to show how daily hospital data can be used to monitor the evolution of the COVID-19 epidemic in France. A piecewise defined dynamic model allows to fit very well the available hospital admission, death and discharge data. The change-points detected correspond to moments when the dynamics of the epidemic changed abruptly. It is therefore a surveillance tool, not a forecasting tool. In other words, it can be used effectively to warn of a restart of epidemic activity, but it is not designed to assess the impact of a new lockdown or the emergence of a new variant.The model, data and fits are implemented in an interactive web application.

An improved epidemiological-unscented Kalman filter (hybrid SEIHCRDV-UKF) model for the prediction of COVID-19. Application on real-time data

The prevalence of COVID-19 has been the most serious health challenge of the 21th century to date, concerning national health systems on a daily basis, since December 2019 when it appeared in Wuhan City. Nevertheless, most of the proposed mathematical methodologies aiming to describe the dynamics of an epidemic, rely on deterministic models that are not able to reflect the true nature of its spread. In this paper, we propose a SEIHCRDV model – an extension/improvement of the classic SIR compartmental model – which also takes into consideration the populations of exposed, hospitalized, admitted in intensive care units (ICU), deceased and vaccinated cases, in combination with an unscented Kalman filter (UKF), providing a dynamic estimation of the time dependent system's parameters. The stochastic approach is considered necessary, as both observations and system equations are characterized by uncertainties. Apparently, this new consideration is useful for examining various pandemics more effectively. The reliability of the model is examined on the daily recordings of COVID-19 in France, over a long period of 265 days. Two major waves of infection are observed, starting in January 2021, which signified the start of vaccinations in Europe providing quite encouraging predictive performance, based on the produced NRMSE values. Special emphasis is placed on proving the non-negativity of SEIHCRDV model, achieving a representative basic reproductive number R0 and demonstrating the existence and stability of disease equilibria according to the formula produced to estimateR0. The model outperforms in predictive ability not only deterministic approaches but also state-of-the-art stochastic models that employ Kalman filters. Furthermore, the relevant analysis supports the importance of vaccination, as even a small increase in the dialy vaccination rate could lead to a notable reduction in mortality and hospitalizations.

Monitoring the reproduction number of COVID-19 in France: estimates compared from 3 datasets

Abstract Background The effective reproduction number (Rt) represents the average number of secondary cases generated by an infected person. During an outbreak, near-real-time monitoring of Rt constitutes a key indicator for detecting changes in disease transmission and assessing the effectiveness of interventions. The estimation of Rt usually requires identifying infected cases in the population which is in practice challenging from available data. The purpose of this study was to compare Rt estimates for COVID-19 surveillance in France based on three data sources of different sensitivity and specificity for identifying infected cases. Methods By applying a statistical method developed by Cori et al., we estimated Rt using (1) confirmed cases identified from positive virological tests among the tested population (2) suspected cases recorded by a national network of emergency departments (3) hospital admissions for COVID-19 recorded by a national administrative system to manage hospital's organization. Results From June 2020 to March 2022, the estimates of Rt in France showed similar temporal trends regardless of the dataset. Estimates based on the daily number of confirmed cases provided an earlier signal that the two other sources, with a lag of 3 and 6 days compared to estimates based on emergency department visits and hospital admissions, respectively. Conclusions The COVID-19 experience has proven that monitoring temporal changes in Rt was a key indicator to help public health authorities controlling the outbreak in real time. Having data on infected people in the population to estimate the Rt is not straightforward in practice. As this study has shown, the opportunity of using more readily available data, provided that it is highly correlated with the spread of infection, gives a practical solution for monitoring the COVID-19 epidemic and any epidemic in general. Key messages • The effective reproduction number (Rt) is a key parameter to monitor transmission during epidemics but its estimation from available data is often a critical issue. • Based on COVID-19 experience, data sufficiently correlated with the spread of infection may be appropriate to estimate Rt and monitor its temporal trend.