Project description:The COVID-19 epidemic was reported in the Hubei province in China in December 2019 and then spread around the world reaching the pandemic stage at the beginning of March 2020. Since then, several countries went into lockdown. Using a mechanistic-statistical formalism, we estimate the effect of the lockdown in France on the contact rate and the effective reproduction number R e of the COVID-19. We obtain a reduction by a factor 7 (R e = 0.47, 95%-CI: 0.45-0.50), compared to the estimates carried out in France at the early stage of the epidemic. We also estimate the fraction of the population that would be infected by the beginning of May, at the official date at which the lockdown should be relaxed. We find a fraction of 3.7% (95%-CI: 3.0-4.8%) of the total French population, without taking into account the number of recovered individuals before April 1st, which is not known. This proportion is seemingly too low to reach herd immunity. Thus, even if the lockdown strongly mitigated the first epidemic wave, keeping a low value of R e is crucial to avoid an uncontrolled second wave (initiated with much more infectious cases than the first wave) and to hence avoid the saturation of hospital facilities.
Project description:BackgroundMore than half of the global population is under strict forms of social distancing. Estimating the expected impact of lockdown and exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis.MethodsWe use a stochastic age-structured transmission model integrating data on age profile and social contacts in Île-de-France to (i) assess the epidemic in the region, (ii) evaluate the impact of lockdown, and (iii) propose possible exit strategies and estimate their effectiveness. The model is calibrated to hospital admission data before lockdown. Interventions are modeled by reconstructing the associated changes in the contact matrices and informed by mobility reductions during lockdown evaluated from mobile phone data. Different types and durations of social distancing are simulated, including progressive and targeted strategies, with large-scale testing.ResultsWe estimate the reproductive number at 3.18 [3.09, 3.24] (95% confidence interval) prior to lockdown and at 0.68 [0.66, 0.69] during lockdown, thanks to an 81% reduction of the average number of contacts. Model predictions capture the disease dynamics during lockdown, showing the epidemic curve reaching ICU system capacity, largely strengthened during the emergency, and slowly decreasing. Results suggest that physical contacts outside households were largely avoided during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave overwhelming the healthcare system, if conditions return to normal. Extensive case finding and isolation are required for social distancing strategies to gradually relax lockdown constraints.ConclusionsAs France experiences the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.
Project description:In this paper, we use a deterministic epidemic model with memory to estimate the state of the COVID-19 epidemic in France, from early March until mid-December 2020. Our model is in the SEIR class, which means that when a susceptible individual (S) becomes infected, he/she is first exposed (E), i.e. not yet contagious. Then he/she becomes infectious (I) for a certain length of time, during which he/she may infect susceptible individuals around him/her, and finally becomes removed (R), that is, either immune or dead. The specificity of our model is that it assumes a very general probability distribution for the pair of exposed and infectious periods. The law of large numbers limit of such a model is a model with memory (the future evolution of the model depends not only upon its present state, but also upon its past). We present theoretical results linking the (unobserved) parameters of the model to various quantities which are more easily measured during the early stages of an epidemic. We then apply these results to estimate the state of the COVID-19 epidemic in France, using available information on the infection fatality ratio and on the distribution of the exposed and infectious periods. Using the hospital data published daily by Santé Publique France, we gather some information on the delay between infection and hospital admission, intensive care unit (ICU) admission and hospital deaths, and on the proportion of people who have been infected up to the end of 2020.
Project description:We analyze the task-content of occupations operating in about 600 sectors of the economy with a focus on the dimensions that expose workers to contagion risks during the COVID-19 epidemic. We do so in the Italian context, leveraging extremely detailed and granular information from ICP, the Italian equivalent of O*Net (the survey that describes the task content of US occupations). We find that several sectors need physical proximity to operate, mainly in services and retail trade. Workers at risk of complications from COVID-19 (mainly males above the age of 50) are concentrated in sectors characterized by little physical proximity or where working from home is feasible. We then study the sectoral lockdowns put in place by the Italian Government in March 2020. We find that governmental restrictions hit the sectors where the risk of contagion in the workplace was more widespread: the effect is stronger for proximity to the public than that with co-workers. The share of workers who have the possibility to work from home is higher in sectors that were not forced to close. The evidence we provide is useful to identify which activities pose larger risks for contagion among workers in the workplace and where to reinforce safety measures. Supplementary Information The online version contains supplementary material available at 10.1007/s40797-021-00164-1.
Project description:IntroductionThe health crisis linked to the COVID-19 epidemic has required lockdown measures in France and changes in practices in dialysis centers. The objective was to assess the depressive and anxiety symptoms during lockdown in hemodialysis patients and their caregivers.MethodsWe sent, during lockdown period, between April and May 2020, self-questionnaires to voluntary subjects (patients and caregivers), treated by hemodialysis or who worked in hemodialysis in one of the 14 participating centers in France. We analyzed their perception of dialysis sessions (beneficial or worrying), their stress level (VAS rated from 0 to 10), their anxiety and depressive symptoms (Hospital anxiety and depression scale). Factors associated with stress, anxiety and depression were analyzed with multiple linear regression models.Results669 patients and 325 caregivers agreed to participate. 70 % of participants found it beneficial to come to dialysis during confinement. The proportions of subjects with a stress level ≥ 6 linked to the epidemic, confinement, fear of contracting COVID-19 and fear of infecting a loved one were respectively 23.9%, 26.2%, 33.4% and 42%. 39.2% presented with certain (13.7%) or doubtful (19.2%) anxious symptoms. 21.2% presented a certain (7.9%) or doubtful (13.3%) depressive symptomatology. Age, gender, history of psychological disorders and perception of dialysis sessions were associated with levels of stress, anxiety and depression.ConclusionDuring the lockdown period, in France, the majority of hemodialysis patients and caregivers found it beneficial to come to dialysis. One in three subjects had anxiety symptoms and one in five subjects had depressive symptoms.
Project description:Several French regions where coronavirus disease (COVID-19) has been reported currently show a renewed increase in ILI cases in the general practice-based Sentinelles network. We computed the number of excess cases by region from 24 February to 8 March 2020 and found a correlation with the number of reported COVID-19 cases so far. The data suggest larger circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the French population than apparent from confirmed cases.
Project description:ObjectiveAlthough social inequalities in COVID-19 mortality by race, gender and socioeconomic status are well documented, less is known about social disparities in infection rates and their shift over time. We aim to study the evolution of social disparities in infection at the early stage of the epidemic in France with regard to the policies implemented.DesignRandom population-based prospective cohort.SettingFrom May to June 2020 in France.ParticipantsAdults included in the Epidémiologie et Conditions de Vie cohort (n=77 588).Main outcome measuresSelf-reported anosmia and/or ageusia in three categories: no symptom, during the first epidemic peak (in March 2020) or thereafter (during lockdown).ResultsIn all, 2052 participants (1.53%) reported anosmia/ageusia. The social distribution of exposure factors (density of place of residence, overcrowded housing and working outside the home) was described. Multinomial regressions were used to identify changes in social variables (gender, class and race) associated with symptoms of anosmia/ageusia. Women were more likely to report symptoms during the peak and after. Racialised minorities accumulated more exposure risk factors than the mainstream population and were at higher risk of anosmia/ageusia during the peak and after. By contrast, senior executive professionals were the least exposed to the virus with the lower rate of working outside the home during lockdown. They were more affected than lower social classes at the peak of the epidemic, but this effect disappeared after the peak.ConclusionThe shift in the social profile of the epidemic was related to a shift in exposure factors under the implementation of a stringent stay-at-home order. Our study shows the importance to consider in a dynamic way the gender, socioeconomic and race direct and indirect effects of the COVID-19 pandemic, notably to implement policies that do not widen health inequalities.
Project description:The aim of our retrospective study was to evaluate the earliest COVID19-related signal to anticipate requirements of intensive care unit (ICU) beds. Although the number of ICU beds is crucial during the COVID-19 epidemic, there is no recognized early indicator to anticipate it. In the Ile-de-France region, from February 20 to May 5, 2020, emergency medical service (EMS) calls and the response provided (ambulances) together the percentage of positive reverse transcriptase polymerase chain reaction (RT-PCR) tests, general practitioner (GP) and emergency department (ED) visits, and hospital admissions of COVID-19 patients were recorded daily and compared to the number of ICU patients. Correlation curve analysis was performed to determine the best correlation coefficient, depending on the number of days the indicator has been shifted. Primary endpoint was the number of ICU patients. EMS calls, percentage of positive RT-PCR tests, ambulances used, ED and GP visits of COVID-19 patients were strongly associated (R2 ranging between 0.79 to 0.99, all P<0.001) with COVID-19 ICU patients with an anticipation delay of 23, 15, 14, 13, and 12 days respectively. Hospitalization did not anticipate ICU bed requirement. A qualitative analysis of the onset of the second wave period of the epidemic (August 1 to September 15, 2020) in the same region provided similar results. The daily number of COVID19-related telephone calls received by the EMS and corresponding dispatch ambulances, and the proportion of positive RT-PCR tests were the earliest indicators of the number of COVID19 patients requiring ICU care during the epidemic crisis, rapidly followed by ED and GP visits. This information may help health authorities to anticipate a future epidemic, including a second wave of COVID19, or decide additional social measures.