Using the near real-time effective reproduction number rt as an early-warning tool for seasonal bronchiolitis and influenza-like illness epidemics.

BACKGROUND: Yearly bronchiolitis and influenza-like illness epidemics in France often involve high morbidity and mortality, which severely impacts healthcare. Epidemics are declared by the French National Institute of Public Health based on syndromic surveillance of primary care and emergency departments (ED), using statistics-based alarms. Although the effective reproduction number (Rt) is used to monitor the dynamics of epidemics, it has never been used as an early warning tool for bronchiolitis or influenza-like illness epidemics in France.We assessed whether Rt is useful for detecting seasonal epidemics by comparing it to the tool currently used (MASS) by epidemiologists to declare epidemic phases. METHODS: We used anonymized ED syndromic data from the Île-de-France region in France from 2010 to 2022. We estimated Rt and compared the indication of accelerated transmission (Rt >1) to the MASS epidemic alarm time points. We computed the difference between those two time points, time to epidemic peak, and the daily cases documented at first indication and peak. RESULTS: Rt provided alarms for influenza-like illness and bronchiolitis epidemics that were, respectively, 6 days (IQR[4;8]) and 64 days (IQR[52;80]) - in median - earlier than the alarms provided by MASS. CONCLUSION: Rt detected earlier signals of bronchiolitis and influenza-like illness epidemics. Using this early-warning indicator in combination with others to declare an annual epidemic could provide opportunities to improve healthcare system readiness.

An unusual outbreak of parvovirus B19 infections, France, 2023 to 2024.

From April 2023 to May 2024, an unusual epidemic of parvovirus B19 (B19V) infections occurred in France. The number of B19V IgM-positive serologies was four times higher than in the previous epidemic in 2019. Clinical data from emergency networks corroborated this observation. Morbidity and mortality consequences were observed in children through all data sources. In adults, the increase was only observed in laboratory-confirmed data. Physicians and decisionmakers should be informed in order to better prevent, diagnose and manage at-risk patients.

Excess mortality in Europe coincides with peaks of COVID-19, influenza and respiratory syncytial virus (RSV), November 2023 to February 2024.

Since the end of November 2023, the European Mortality Monitoring Network (EuroMOMO) has observed excess mortality in Europe. During weeks 48 2023-6 2024, preliminary results show a substantially increased rate of 95.3 (95% CI:  91.7-98.9) excess all-cause deaths per 100,000 person-years for all ages. This excess mortality is seen in adults aged 45 years and older, and coincides with widespread presence of COVID-19, influenza and respiratory syncytial virus (RSV) observed in many European countries during the 2023/24 winter season.

Place of death in France: impact of the first wave (March-May 2020) of the Covid-19 epidemic.

BACKGROUND: The Covid-19 epidemic entailed a major public health issue in France challenging the efficiency of the public health system. The distribution of deaths by place in France may have been affected by the epidemic and mitigation actions. This article presents mortality rate ratios by place of death in France during the first lockdown (17 March - 10 May, 2020) of the Covid-19 epidemic. METHODS: We considered five places of death recorded in death certificates. Deaths in 2020 were compared to deaths from 2015 to 2019. We employed quasi-Poisson regressions in order to stablish mortality rate ratios (MRR) during the Covid-19 epidemic, for all-cause and non-Covid-19 deaths. Analysis was conducted in Metropolitan France, and for three groups of regions defined according to the intensity of the first COVID-19 epidemic wave. RESULTS: A significant increase in all-cause and non-COVID-19 mortality at home was observed for all age groups. Also, an increase in mortality was observed in nursing homes, mostly due to Covid-19. Non-covid-19 mortality in public hospitals decreased significantly in all the country. These trends were mainly observed for cancers. CONCLUSIONS: Overall mortality increased during the first wave of the Covid-19 epidemic. Most Covid-19 deaths took place in public hospitals and nursing homes at old ages. There was a displacement of non-Covid-19 mortality from public hospitals to home and nursing homes, particularly in the most highly exposed area. Among hypotheses to explain such a displacement, population avoidance of hospital care, or redeployment of hospital activity in this emergent context can be cited. Further analysis is needed to understand the reasons of the increase in non-Covid-19 mortality in nursing homes and at home.

Real-time monitoring shows substantial excess all-cause mortality during second wave of COVID-19 in Europe, October to December 2020.

The European monitoring of excess mortality for public health action (EuroMOMO) network monitors weekly excess all-cause mortality in 27 European countries or subnational areas. During the first wave of the coronavirus disease (COVID-19) pandemic in Europe in spring 2020, several countries experienced extraordinarily high levels of excess mortality. Europe is currently seeing another upsurge in COVID-19 cases, and EuroMOMO is again witnessing a substantial excess all-cause mortality attributable to COVID-19.

Excess all-cause mortality during the first wave of the COVID-19 epidemic in France, March to May 2020.

Through a weekly all-cause mortality surveillance system, we observed in France a major all-cause excess mortality from March to May 2020, concomitant with the coronavirus disease (COVID-19) epidemic. The excess mortality was 25,030 deaths, mainly among elderly people. Five metropolitan regions were the most affected, particularly Île-de-France and the Grand-Est regions. Assessing the excess mortality related to COVID-19 is complex because of the potential protective effect of the lockdown period on other causes of mortality.

Large concomitant outbreaks of acute gastroenteritis emergency visits in adults and food-borne events suspected to be linked to raw shellfish, France, December 2019 to January 2020.

On 27 December 2019, the French Public Health Agency identified a large increase in the number of acute gastroenteritis and vomiting visits, both in emergency departments and in emergency general practitioners' associations providing house-calls. In parallel, on 26 and 27 December, an unusual number of food-borne events suspected to be linked to the consumption of raw shellfish were reported through the mandatory reporting surveillance system. This paper describes these concomitant outbreaks and the investigations' results.

Excess all-cause mortality during the COVID-19 pandemic in Europe - preliminary pooled estimates from the EuroMOMO network, March to April 2020.

A remarkable excess mortality has coincided with the COVID-19 pandemic in Europe. We present preliminary pooled estimates of all-cause mortality for 24 European countries/federal states participating in the European monitoring of excess mortality for public health action (EuroMOMO) network, for the period March-April 2020. Excess mortality particularly affected ≥ 65 year olds (91% of all excess deaths), but also 45-64 (8%) and 15-44 year olds (1%). No excess mortality was observed in 0-14 year olds.

Evaluation of the French reactive mortality surveillance system supporting decision making.

BACKGROUND: In France, a mortality syndromic surveillance system was set up with objectives of early detection and reactive evaluation of the impact of expected and unexpected events to support decision makers. This study aims to describe the characteristics of the system and its usefulness for decision makers. METHODS: Anonymized data from the administrative part of death certificates were daily collected from 3062 computerized city halls and were transmitted to Santé publique France in routine. Coverage of the system was measured as the proportion of deaths registered by the system among the complete number of deaths and analyzed by age, month and region. Deaths were described by gender, age and geographical level using proportion. The excess periods of deaths were described based on the comparison of the weekly observed and expected numbers of deaths between 2012 and 2016. RESULTS: The system recorded 77.5% of the national mortality covering the whole territory. About 81% of deaths were aged 65 years old and more. The surveillance system identified mortality variations mainly during winter and summer, for some concomitant with influenza epidemic or heatwave period, and thus provided information for decision makers. CONCLUSION: The ability of the system to detect and follow mortality outbreaks in routine in the whole territory has been demonstrated. It is a useful tool to provide early evaluation of the impact of threats on mortality and alert decision makers to adapt control measures. However, the absence of information on medical causes of death may limit the ability to target recommendations.

Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France.

The 2014/15 influenza epidemic caused a work overload for healthcare facilities in France. The French national public health agency announced the start of the epidemic - based on indicators aggregated at the national level - too late for many hospitals to prepare. It was therefore decided to improve the influenza alert procedure through (i) the introduction of a pre-epidemic alert level to better anticipate future outbreaks, (ii) the regionalisation of surveillance so that healthcare structures can be informed of the arrival of epidemics in their region, (iii) the standardised use of data sources and statistical methods across regions. A web application was developed to deliver statistical results of three outbreak detection methods applied to three surveillance data sources: emergency departments, emergency general practitioners and sentinel general practitioners. This application was used throughout the 2015/16 influenza season by the epidemiologists of the headquarters and regional units of the French national public health agency. It allowed them to signal the first influenza epidemic alert in week 2016-W03, in Brittany, with 11 other regions in pre-epidemic alert. This application received positive feedback from users and was pivotal for coordinating surveillance across the agency's regional units.

Excess all-cause and influenza-attributable mortality in Europe, December 2016 to February 2017.

Since December 2016, excess all-cause mortality was observed in many European countries, especially among people aged ≥ 65 years. We estimated all-cause and influenza-attributable mortality in 19 European countries/regions. Excess mortality was primarily explained by circulation of influenza virus A(H3N2). Cold weather snaps contributed in some countries. The pattern was similar to the last major influenza A(H3N2) season in 2014/15 in Europe, although starting earlier in line with the early influenza season start.

Quality comparison of electronic versus paper death certificates in France, 2010.

BACKGROUND: Electronic death certification was established in France in 2007. A methodology based on intrinsic characteristics of death certificates was designed to compare the quality of electronic versus paper death certificates. METHODS: All death certificates from the 2010 French mortality database were included. Three specific quality indicators were considered: (i) amount of information, measured by the number of causes of death coded on the death certificate; (ii) intrinsic consistency, explored by application of the International Classification of Disease (ICD) General Principle, using an international automatic coding system (Iris); (iii) imprecision, measured by proportion of death certificates where the selected underlying cause of death was imprecise. Multivariate models were considered: a truncated Poisson model for indicator (i) and binomial models for indicators (ii) and (iii). Adjustment variables were age, gender, and cause, place, and region of death. RESULTS: 533,977death certificates were analyzed. After adjustment, electronic death certificates contained 19% [17%-20%] more codes than paper death certificates for people deceased under 65 years, and 12% [11%-13%] more codes for people deceased over 65 years. Regarding deceased under and over 65 respectively, the ICD General Principle could be applied 2% [0%-4%] and 6% [5%-7%] more to electronic than to paper death certificates. The proportion of imprecise death certificates was 51% [46%-56%] lower for electronic than for paper death certificates. CONCLUSION: The method proposed to evaluate the quality of death certificates is easily reproducible in countries using an automatic coding system. According to our criteria, electronic death certificates are better completed than paper death certificates. The transition to electronic death certificates is positive in many aspects and should be promoted.

Reactive surveillance of suicides during the COVID-19 pandemic in France, 2020 to March 2022.

AIMS: Mitigation actions during the COVID-19 pandemic may impact mental health and suicide in general populations. We aimed to analyse the evolution in suicide deaths from 2020 to March 2022 in France. METHODS: Using free-text medical causes in death certificates, we built an algorithm, which aimed to identify suicide deaths. We measured its retrospective performances by comparing suicide deaths identified using the algorithm with deaths which had either a Tenth revision of the International Classification of Diseases (ICD-10) code for 'intentional self-harm' or for 'external cause of undetermined intent' as the underlying cause. The number of suicide deaths from January 2020 to March 2022 was then compared with the expected number estimated using a generalized additive model. The difference and the ratio between the observed and expected number of suicide deaths were calculated on the three lockdown periods and for periods between lockdowns and after the third one. The analysis was stratified by age group and gender. RESULTS: The free-text algorithm demonstrated high performances. From January 2020 to mid-2021, suicide mortality declined during France's three lockdowns, particularly in men. During the periods between and after the two first lockdowns, suicide mortality remained comparable to the expected values, except for men over 85 years old and in 65-84 year-old age group, where a small number of excess deaths was observed in the weeks following the end of first lockdown, and for men aged 45-64 years old, where the decline continued after the second lockdown ended. After the third lockdown until March 2022, an increase in suicide mortality was observed in 18-24 year-old age group for both genders and in men aged 65-84 years old, while a decrease was observed in the 25-44 year-old age group. CONCLUSIONS: This study highlighted the absence of an increase in suicide mortality during France's COVID-19 pandemic and a substantial decline during lockdown periods, something already observed in other countries. The increase in suicide mortality observed in 18-24 year-old age group and in men aged 65-84 years old from mid-2021 to March 2022 suggests a prolonged impact of COVID-19 on mental health, also described on self-harm hospitalizations and emergency department's attendances in France. Further studies are required to explain the factors for this change. Reactive monitoring of suicide mortality needs to be continued since mental health consequences and the increase in suicide mortality may be continued in the future with the international context.

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

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Direct impact of COVID-19 by estimating disability-adjusted life years at national level in France in 2020.

BACKGROUND: The World Health Organization declared a pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), on March 11, 2020. The standardized approach of disability-adjusted life years (DALYs) allows for quantifying the combined impact of morbidity and mortality of diseases and injuries. The main objective of this study was to estimate the direct impact of COVID-19 in France in 2020, using DALYs to combine the population health impact of infection fatalities, acute symptomatic infections and their post-acute consequences, in 28 days (baseline) up to 140 days, following the initial infection. METHODS: National mortality, COVID-19 screening, and hospital admission data were used to calculate DALYs based on the European Burden of Disease Network consensus disease model. Scenario analyses were performed by varying the number of symptomatic cases and duration of symptoms up to a maximum of 140 days, defining COVID-19 deaths using the underlying, and associated, cause of death. RESULTS: In 2020, the estimated DALYs due to COVID-19 in France were 990 710 (1472 per 100 000), with 99% of burden due to mortality (982 531 years of life lost, YLL) and 1% due to morbidity (8179 years lived with disability, YLD), following the initial infection. The contribution of YLD reached 375%, assuming the duration of 140 days of post-acute consequences of COVID-19. Post-acute consequences contributed to 49% of the total morbidity burden. The contribution of YLD due to acute symptomatic infections among people younger than 70 years was higher (67%) than among people aged 70 years and above (33%). YLL among people aged 70 years and above, contributed to 74% of the total YLL. CONCLUSIONS: COVID-19 had a substantial impact on population health in France in 2020. The majority of population health loss was due to mortality. Men had higher population health loss due to COVID-19 than women. Post-acute consequences of COVID-19 had a large contribution to the YLD component of the disease burden, even when we assume the shortest duration of 28 days, long COVID burden is large. Further research is recommended to assess the impact of health inequalities associated with these estimates.

Syndromic surveillance: A key component of population health monitoring during the first wave of the COVID-19 outbreak in France, February-June 2020.

BACKGROUND: The French syndromic surveillance (SyS) system, SurSaUD®, was one of the systems used to monitor the COVID-19 outbreak. AIM: This study described the epidemiological characteristics of COVID-19-related visits to both emergency departments (EDs) and the network of emergency general practitioners known as SOS Médecins (SOSMed) in France from 17 February to 28 June 2020. METHODS: Data on all visits to 634 EDs and 60 SOSMed associations were collected daily. COVID-19-related visits were identified using ICD-10 codes after coding recommendations were sent to all ED and SOSMed doctors. The time course of COVID-19-related visits was described by age group and region. During the lockdown period, the characteristics of ED and SOSMed visits and hospitalisations after visits were described by age group and gender. The most frequent diagnoses associated with COVID-19-related visits were analysed. RESULTS: COVID-19 SyS was implemented on 29 February and 4 March for EDs and SOSMed, respectively. A total of 170,113 ED and 59,087 SOSMed visits relating to COVID-19 were recorded, representing 4.0% and 5.6% of the overall coded activity with a peak in late March representing 22.5% and 25% of all ED and SOSMed visits, respectively. COVID-19-related visits were most frequently reported for women and those aged 15-64 years, although patients who were subsequently hospitalised were more often men and persons aged 65 years and older. CONCLUSION: SyS allowed for population health monitoring of the COVID-19 epidemic in France. As SyS has more than 15 years of historical data with high quality and reliability, it was considered sufficiently robust to contribute to defining the post-lockdown strategy.

Heat exposure and socio-economic vulnerability as synergistic factors in heat-wave-related mortality.

Heat waves may become a serious threat to the health and safety of people who currently live in temperate climates. It was therefore of interest to investigate whether more deprived populations are more vulnerable to heat waves. In order to address the question on a fine geographical scale, the spatial heterogeneity of the excess mortality in France associated with the European heat wave of August 2003 was analysed. A deprivation index and a heat exposure index were used jointly to describe the heterogeneity on the Canton scale (3,706 spatial units). During the heat wave period, the heat exposure index explained 68% of the extra-Poisson spatial variability of the heat wave mortality ratios. The heat exposure index was greater in the most urbanized areas. For the three upper quintiles of heat exposure in the densely populated Paris area, excess mortality rates were twofold higher in the most deprived Cantons (about 20 excess deaths/100,000 people/day) than in the least deprived Cantons (about 10 excess deaths/100,000 people/day). No such interaction was observed for the rest of France, which was less exposed to heat and less heterogeneous in terms of deprivation. Although a marked increase in mortality was associated with heat wave exposure for all degrees of deprivation, deprivation appears to be a vulnerability factor with respect to heat-wave-associated mortality.

Ecological association between a deprivation index and mortality in France over the period 1997 - 2001: variations with spatial scale, degree of urbanicity, age, gender and cause of death.

BACKGROUND: Spatial health inequalities have often been analysed in terms of deprivation. The aim of this study was to create an ecological deprivation index and evaluate its association with mortality over the entire mainland France territory. More specifically, the variations with the degree of urbanicity, spatial scale, age, gender and cause of death, which influence the association between mortality and deprivation, have been described. METHODS: The deprivation index, 'FDep99', was developed at the 'commune'(smallest administrative unit in France) level as the first component of a principal component analysis of four socioeconomic variables. Proxies of the Carstairs and Townsend indices were calculated for comparison. The spatial association between FDep99 and mortality was studied using five different spatial scales, and by degree of urbanicity (five urban unit categories), age, gender and cause of death, over the period 1997-2001. 'Avoidable' causes of death were also considered for subjects aged less than 65 years. They were defined as causes related to risk behaviour and primary prevention (alcohol, smoking, accidents). RESULTS: The association between the FDep99 index and mortality was positive and quasi-log-linear, for all geographic scales. The standardized mortality ratio (SMR) was 24% higher for the communes of the most deprived quintile than for those of the least deprived quintile. The between-urban unit category and between-région heterogeneities of the log-linear associations were not statistically significant. The association was positive for all the categories studied and was significantly greater for subjects aged less than 65 years, for men, and for 'avoidable' mortality. The amplitude and regularity of the associations between mortality and the Townsend and Carstairs indices were lower. CONCLUSION: The deprivation index proposed reflects a major part of spatial socioeconomic heterogeneity, in a homogeneous manner over the whole country. The index may be routinely used by healthcare authorities to observe, analyse, and manage spatial health inequalities.

A New Approach to Compare the Performance of Two Classification Methods of Causes of Death for Timely Surveillance in France.

Timely mortality surveillance in France is based on the monitoring of electronic death certificates to provide information to health authorities. This study aims to analyze the performance of a rule-based and a supervised machine learning method to classify medical causes of death into 60 mortality syndromic groups (MSGs). Performance was first measured on a test set. Then we compared the trends of the monthly numbers of deaths classified into MSGs from 2012 to 2016 using both methods. Among the 60 MSGs, 31 achieved recall and precision over 0.95 for either one or the other method on the test set. On the whole dataset, the correlation coefficient of the monthly numbers of deaths obtained by the two methods were close to 1 for 21 of the 31 MSGs. This approach is useful for analyzing a large number of categories or when annotated resources are limited.

Automatic classification of free-text medical causes from death certificates for reactive mortality surveillance in France.

BACKGROUND: Mortality surveillance is of fundamental importance to public health surveillance. The real-time recording of death certificates, thanks to Electronic Death Registration System (EDRS), provides valuable data for reactive mortality surveillance based on medical causes of death in free-text format. Reactive mortality surveillance is based on the monitoring of mortality syndromic groups (MSGs). An MSG is a cluster of medical causes of death (pathologies, syndromes or symptoms) that meets the objectives of early detection and impact assessment of public health events. The aim of this study is to implement and measure the performance of a rule-based method and two supervised models for automatic free-text cause of death classification from death certificates in order to implement them for routine surveillance. METHOD: A rule-based method was implemented using four processing steps: standardization rules, splitting causes of death using delimiters, spelling corrections and dictionary projection. A supervised machine learning method using a linear Support Vector Machine (SVM) classifier was also implemented. Two models were produced using different features (SVM1 based solely on surface features and SVM2 combining surface features and MSGs classified by the rule-based method as feature vectors). The evaluation was conducted using an annotated subset of electronic death certificates received between 2012 and 2016. Classification performance was evaluated on seven MSGs (Influenza, Low respiratory diseases, Asphyxia/abnormal respiration, Acute respiratory disease, Sepsis, Chronic digestive diseases, and Chronic endocrine diseases). RESULTS: The rule-based method and the SVM2 model displayed a high performance with F-measures over 0.94 for all MSGs. Precision and recall were slightly higher for the rule-based method and the SVM2 model. An error-analysis shows that errors were not specific to an MSG. CONCLUSION: The high performance of the rule-based method and SVM2 model will allow us to set-up a reactive mortality surveillance system based on free-text death certificates. This surveillance will be an added-value for public health decision making.