Age-specific mortality and immunity patterns of SARS-CoV-2.

Estimating the size of the coronavirus disease 2019 (COVID-19) pandemic and the infection severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is made challenging by inconsistencies in the available data. The number of deaths associated with COVID-19 is often used as a key indicator for the size of the epidemic, but the observed number of deaths represents only a minority of all infections1,2. In addition, the heterogeneous burdens in nursing homes and the variable reporting of deaths of older individuals can hinder direct comparisons of mortality rates and the underlying levels of transmission across countries3. Here we use age-specific COVID-19-associated death data from 45 countries and the results of 22 seroprevalence studies to investigate the consistency of infection and fatality patterns across multiple countries. We find that the age distribution of deaths in younger age groups (less than 65 years of age) is very consistent across different settings and demonstrate how these data can provide robust estimates of the share of the population that has been infected. We estimate that the infection fatality ratio is lowest among 5-9-year-old children, with a log-linear increase by age among individuals older than 30 years. Population age structures and heterogeneous burdens in nursing homes explain some but not all of the heterogeneity between countries in infection fatality ratios. Among the 45 countries included in our analysis, we estimate that approximately 5% of these populations had been infected by 1 September 2020, and that much higher transmission rates have probably occurred in a number of Latin American countries. This simple modelling framework can help countries to assess the progression of the pandemic and can be applied in any scenario for which reliable age-specific death data are available.

Analytical framework to evaluate and optimize the use of imperfect diagnostics to inform outbreak response: Application to the 2017 plague epidemic in Madagascar.

During outbreaks, the lack of diagnostic "gold standard" can mask the true burden of infection in the population and hamper the allocation of resources required for control. Here, we present an analytical framework to evaluate and optimize the use of diagnostics when multiple yet imperfect diagnostic tests are available. We apply it to laboratory results of 2,136 samples, analyzed with 3 diagnostic tests (based on up to 7 diagnostic outcomes), collected during the 2017 pneumonic (PP) and bubonic plague (BP) outbreak in Madagascar, which was unprecedented both in the number of notified cases, clinical presentation, and spatial distribution. The extent of these outbreaks has however remained unclear due to nonoptimal assays. Using latent class methods, we estimate that 7% to 15% of notified cases were Yersinia pestis-infected. Overreporting was highest during the peak of the outbreak and lowest in the rural settings endemic to Y. pestis. Molecular biology methods offered the best compromise between sensitivity and specificity. The specificity of the rapid diagnostic test was relatively low (PP: 82%, BP: 85%), particularly for use in contexts with large quantities of misclassified cases. Comparison with data from a subsequent seasonal Y. pestis outbreak in 2018 reveal better test performance (BP: specificity 99%, sensitivity: 91%), indicating that factors related to the response to a large, explosive outbreak may well have affected test performance. We used our framework to optimize the case classification and derive consolidated epidemic trends. Our approach may help reduce uncertainties in other outbreaks where diagnostics are imperfect.

An ensemble model based on early predictors to forecast COVID-19 health care demand in France.

Short-term forecasting of the COVID-19 pandemic is required to facilitate the planning of COVID-19 health care demand in hospitals. Here, we evaluate the performance of 12 individual models and 19 predictors to anticipate French COVID-19-related health care needs from September 7, 2020, to March 6, 2021. We then build an ensemble model by combining the individual forecasts and retrospectively test this model from March 7, 2021, to July 6, 2021. We find that the inclusion of early predictors (epidemiological, mobility, and meteorological predictors) can halve the rms error for 14-d­ahead forecasts, with epidemiological and mobility predictors contributing the most to the improvement. On average, the ensemble model is the best or second-best model, depending on the evaluation metric. Our approach facilitates the comparison and benchmarking of competing models through their integration in a coherent analytical framework, ensuring that avenues for future improvements can be identified.

Comparing the Performance of Three Models Incorporating Weather Data to Forecast Dengue Epidemics in Reunion Island, 2018-2019.

We developed mathematical models to analyze a large dengue virus (DENV) epidemic in Reunion Island in 2018-2019. Our models captured major drivers of uncertainty including the complex relationship between climate and DENV transmission, temperature trends, and underreporting. Early assessment correctly concluded that persistence of DENV transmission during the austral winter 2018 was likely and that the second epidemic wave would be larger than the first one. From November 2018, the detection probability was estimated at 10%-20% and, for this range of values, our projections were found to be remarkably accurate. Overall, we estimated that 8% and 18% of the population were infected during the first and second wave, respectively. Out of the 3 models considered, the best-fitting one was calibrated to laboratory entomological data, and accounted for temperature but not precipitation. This study showcases the contribution of modeling to strengthen risk assessments and planning of national and local authorities.

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.

Impact of vaccination against severe COVID-19 in the French population aged 50 years and above: a retrospective population-based study.

BACKGROUND: Given the widespread implementation of COVID-19 vaccination to mitigate the pandemic from the end of 2020, it is important to retrospectively evaluate its impact, in particular by quantifying the number of severe outcomes prevented through vaccination. METHODS: We estimated the number of hospitalizations, intensive care unit (ICU) admissions and deaths directly averted by vaccination in France, in people aged ≥ 50 years, from December 2020 to March 2022, based on (1) the number of observed events, (2) vaccination coverage, and (3) vaccine effectiveness. We accounted for the effect of primary vaccination and the first booster dose, the circulating variants, the age groups, and the waning of vaccine-induced protection over time. RESULTS: An estimated 480,150 (95% CI: 260,072-582,516) hospitalizations, 132,156 (50,409-157,767) ICU admissions and 125,376 (53,792-152,037) deaths were directly averted by vaccination in people aged ≥ 50 years, which corresponds to a reduction of 63.2% (48.2-67.6), 68.7% (45.6-72.4) and 62.7% (41.9-67.1) respectively, compared to what would have been expected without vaccination over the study period. An estimated 5852 (2285-6853) deaths were directly averted among the 50-59 years old, 16,837 (6568-19,473) among the 60-69 years old, 32,136 (13,651-36,758) among the 70-79 years old and 70,551 (31,288-88,953) among the ≥ 80 years old. CONCLUSIONS: The vaccination campaign in France considerably reduced COVID-19 morbidity and mortality, as well as stress on the healthcare system.

Impact of non-pharmaceutical interventions, weather, vaccination, and variants on COVID-19 transmission across departments in France.

BACKGROUND: Multiple factors shape the temporal dynamics of the COVID-19 pandemic. Quantifying their relative contributions is key to guide future control strategies. Our objective was to disentangle the individual effects of non-pharmaceutical interventions (NPIs), weather, vaccination, and variants of concern (VOC) on local SARS-CoV-2 transmission. METHODS: We developed a log-linear model for the weekly reproduction number (R) of hospital admissions in 92 French metropolitan departments. We leveraged (i) the homogeneity in data collection and NPI definitions across departments, (ii) the spatial heterogeneity in the timing of NPIs, and (iii) an extensive observation period (14 months) covering different weather conditions, VOC proportions, and vaccine coverage levels. FINDINGS: Three lockdowns reduced R by 72.7% (95% CI 71.3-74.1), 70.4% (69.2-71.6) and 60.7% (56.4-64.5), respectively. Curfews implemented at 6/7 pm and 8/9 pm reduced R by 34.3% (27.9-40.2) and 18.9% (12.04-25.3), respectively. School closures reduced R by only 4.9% (2.0-7.8). We estimated that vaccination of the entire population would have reduced R by 71.7% (56.4-81.6), whereas the emergence of VOC (mainly Alpha during the study period) increased transmission by 44.6% (36.1-53.6) compared with the historical variant. Winter weather conditions (lower temperature and absolute humidity) increased R by 42.2% (37.3-47.3) compared to summer weather conditions. Additionally, we explored counterfactual scenarios (absence of VOC or vaccination) to assess their impact on hospital admissions. INTERPRETATION: Our study demonstrates the strong effectiveness of NPIs and vaccination and quantifies the role of weather while adjusting for other confounders. It highlights the importance of retrospective evaluation of interventions to inform future decision-making.

Impact of booster vaccination on the control of COVID-19 Delta wave in the context of waning immunity: application to France in the winter 2021/22.

Europe has experienced a large COVID-19 wave caused by the Delta variant in winter 2021/22. Using mathematical models applied to Metropolitan France, we find that boosters administered to ≥ 65, ≥ 50 or ≥ 18 year-olds may reduce the hospitalisation peak by 25%, 36% and 43% respectively, with a delay of 5 months between second and third dose. A 10% reduction in transmission rates might further reduce it by 41%, indicating that even small increases in protective behaviours may be critical to mitigate the wave.

Early chains of transmission of COVID-19 in France, January to March 2020.

IntroductionSARS-CoV-2, the virus that causes COVID-19, has spread rapidly worldwide. In January 2020, a surveillance system was implemented in France for early detection of cases and their contacts to help limit secondary transmissions.AimTo use contact-tracing data collected during the initial phase of the COVID-19 pandemic to better characterise SARS-CoV-2 transmission.MethodsWe analysed data collected during contact tracing and retrospective epidemiological investigations in France from 24 January to 30 March 2020. We assessed the secondary clinical attack rate and characterised the risk of a contact becoming a case. We described chains of transmission and estimated key parameters of spread.ResultsDuring the study period, 6,082 contacts of 735 confirmed cases were traced. The overall secondary clinical attack rate was 4.1% (95% confidence interval (CI): 3.6-4.6), increasing with age of index case and contact. Compared with co-workers/friends, family contacts were at higher risk of becoming cases (adjusted odds ratio (AOR): 2.1, 95% CI: 1.4-3.0) and nosocomial contacts were at lower risk (AOR: 0.3, 95% CI: 0.1-0.7). Of 328 infector/infectee pairs, 49% were family members. The distribution of secondary cases was highly over-dispersed: 80% of secondary cases were caused by 10% of cases. The mean serial interval was 5.1 days (interquartile range (IQR): 2-8 days) in contact tracing pairs, where late transmission events may be censored, and 6.8 (3-8) days in pairs investigated retrospectively.ConclusionThis study increases knowledge of SARS-CoV-2 transmission, including the importance of superspreading events during the onset of the pandemic.

Association between the COVID-19 pandemic and pertussis derived from multiple nationwide data sources, France, 2013 to 2020.

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.

Benefits and risks associated with different uses of the COVID-19 vaccine Vaxzevria: a modelling study, France, May to September 2021.

Thrombosis with thrombocytopenia (TTS) has been identified as a rare adverse event following COVID-19 vaccination with Vaxzevria. We modelled the benefits and risks of Vaxzevria distribution from May to September 2021 in metropolitan France where other vaccines are available, considering French hospitalisation data and European data on TTS. Across different scenarios, benefits of Vaxzevria distribution in people 55 years and older exceeded the risk of death from COVID-19. In young adults, risks were at least of similar magnitude as benefits.

The epidemiology of hepatitis delta virus infection in Cameroon.

OBJECTIVE: To investigate the distribution and risk factors of hepatitis delta virus (HDV) infection in Cameroon. DESIGN: We tested for hepatitis B virus (HBV) surface antigen (HBsAg) and anti-HDV antibody 14 150 samples collected during a survey whose participants were representative of the Cameroonian adult population. The samples had already been tested for hepatitis C virus and HIV antibodies. RESULTS: Overall, 1621/14 150 (weighted prevalence=11.9%) participants were HBsAg positive, among whom 224/1621 (10.6%) were anti-HDV positive. In 2011, the estimated numbers of HBsAg positive and HDV seropositives were 1 160 799 and 122 910 in the 15-49 years age group, respectively. There were substantial regional variations in prevalence of chronic HBV infection, but even more so for HDV (from 1% to 54%). In multivariable analysis, HDV seropositivity was independently associated with living with an HDV-seropositive person (OR=8.80; 95% CI: 3.23 to 24.0), being HIV infected (OR=2.82; 95% CI: 1.32 to 6.02) and living in the South (latitude <4°N) while having rural/outdoor work (OR=15.2; 95% CI: 8.35 to 27.6, when compared with living on latitude ≥4°N and not having rural/outdoor work). CONCLUSION: We found evidence for effective intra-household transmission of HDV in Cameroon. We also identified large differences in prevalence between regions, with cases concentrated in forested areas close to the Equator, as described in other tropical areas. The reasons underlying these geographical variations in HDV prevalence deserve further investigation.

Impact of Zika Virus Emergence in French Guiana: A Large General Population Seroprevalence Survey.

BACKGROUND: Since the identification of Zika virus (ZIKV) in Brazil in May 2015, the virus has spread throughout the Americas. However, ZIKV burden in the general population in affected countries remains unknown. METHODS: We conducted a general population survey in the different communities of French Guiana through individual interviews and serologic survey during June-October 2017. All serum samples were tested for anti-ZIKV immunoglobulin G antibodies using a recombinant antigen-based SGERPAxMap microsphere immunoassay, and some of them were further evaluated through anti-ZIKV microneutralization tests. RESULTS: The overall seroprevalence was estimated at 23.3% (95% confidence interval [CI], 20.9%-25.9%) among 2697 participants, varying from 0% to 45.6% according to municipalities. ZIKV circulated in a large majority of French Guiana but not in the most isolated forest areas. The proportion of reported symptomatic Zika infection was estimated at 25.5% (95% CI, 20.3%-31.4%) in individuals who tested positive for ZIKV. CONCLUSIONS: This study described a large-scale representative ZIKV seroprevalence study in South America from the recent 2015-2016 Zika epidemic. Our findings reveal that the majority of the population remains susceptible to ZIKV, which could potentially allow future reintroductions of the virus.

Hypoglycemic Toxins and Enteroviruses as Causes of Outbreaks of Acute Encephalitis-Like Syndrome in Children, Bac Giang Province, Northern Vietnam.

We investigated the cause of seasonal outbreaks of pediatric acute encephalitis-like syndrome associated with litchi harvests (May-July) in northern Vietnam since 2008. Nineteen cerebrospinal fluid samples were positive for human enterovirus B, and 8 blood samples were positive for hypoglycemic toxins present in litchi fruits. Patients who were positive for hypoglycemic toxins had shorter median times between disease onset and admission, more reports of seizures, more reports of hypoglycemia (glucose level <3 mmol/L), lower median numbers of leukocytes in cerebrospinal fluid, and higher median serum levels of alanine aminotransferase and aspartate transaminase than did patients who were positive for enteroviruses. We suggest that children with rapidly progressing acute encephalitis-like syndrome at the time of the litchi harvest have intoxication caused by hypoglycemic toxins, rather than viral encephalitis, as previously suspected. These children should be urgently treated for life-threatening hypoglycemia.

Response Strategies against Meningitis Epidemics after Elimination of Serogroup A Meningococci, Niger.

To inform epidemic response strategies for the African meningitis belt after a meningococcal serogroup A conjugate vaccine was introduced in 2010, we compared the effectiveness and efficiency of meningitis surveillance and vaccine response strategies at district and health area levels using various thresholds of weekly incidence rates. We analyzed reports of suspected cases from 3 regions in Niger during 2002-2012 (154,392 health area weeks), simulating elimination of serogroup A meningitis by excluding health area years with identification of such cases. Effectiveness was highest for health area surveillance and district vaccination (58-366 cases; thresholds 7-20 cases/100,000 doses), whereas efficiency was optimized with health area vaccination (5.6-7.7 cases/100,000 doses). District-level intervention prevented <6 cases (0.2 cases/100,000 doses). Reducing the delay between epidemic signal and vaccine protection by 2 weeks doubled efficiency. Subdistrict surveillance and response might be most appropriate for meningitis epidemic response after elimination of serogroup A meningitis.

Timeliness of yellow fever surveillance, Central African Republic.

During January 2007-July 2012, a total of 3,220 suspected yellow fever cases were reported in the Central African Republic; 55 were confirmed and 11 case-patients died. Mean delay between onset of jaundice and case confirmation was 16.6 days. Delay between disease onset and blood collection could be reduced by increasing awareness of the population.

Nirsevimab Effectiveness Against Cases of Respiratory Syncytial Virus Bronchiolitis Hospitalised in Paediatric Intensive Care Units in France, September 2023-January 2024.

In September 2023, France was one of the first countries that started a national immunisation campaign with nirsevimab, a new monoclonal antibody against respiratory syncytial virus (RSV). Using data from a network of paediatric intensive care units (PICUs), we aimed to estimate nirsevimab effectiveness against severe cases of RSV bronchiolitis in France. We conducted a case-control study based on the test-negative design and included 288 infants reported by 20 PICUs. We estimated nirsevimab effectiveness at 75.9% (48.5-88.7) in the main analysis and 80.6% (61.6-90.3) and 80.4% (61.7-89.9) in two sensitivity analyses. These real-world estimates confirmed the efficacy observed in clinical studies.

Two-dose measles vaccine effectiveness remains high over time: A French observational study, 2017-2019.

BACKGROUND: From 2008 to 2019, France has experienced a resurgence of measles epidemics. Surveillance data have shown that the proportion of cases vaccinated with two doses of measles-containing vaccine (MCV) increased with age, raising concerns about the duration of vaccine protection. Our objectives were to investigate age-stratified vaccine effectiveness (VE) for the second dose of MCV (MCV2) and to quantify protection levels over time. METHODS: We analyzed data on measles cases aged 2-31 years, reported via mandatory notification to the French measles surveillance system from October 2017 to September 2019. We estimated an age-stratified VE for MCV2 using the screening method, which compares the vaccination status of cases with that of the general population. We improved this method by accounting for natural immunity, exploring four scenarios with four possible levels of natural immunity in the population. In addition, we quantified the decay rate of protection over time, by fitting an exponential decay model among individuals vaccinated in early life. RESULTS: In the baseline analysis (absence of natural immunity), VE estimates were high in all age groups and decreased with age, from 99.6 % (95 % confidence interval: 99.3-99.8) in 2-5 years old to 91.4 % (85.1-95.0) in 26-31 years old. Accounting for natural immunity increased VE in the older age group to 93.2-99.2 % depending on the scenario. We estimated that VE was slowly decreasing over time, with an exponential decay rate of 0.0022/year (0.0017-0.0028), leading to VE of 96.7 % (96.0-97.4) 16 years after MCV2 vaccination. This decline was most compatible with scenario 2, a scenario of 4.4 % naturally immunized, non-vaccinated individuals in the 26-31 years old. CONCLUSION: Our study confirms the continued high effectiveness of two doses of MCV with only slight degradation, decades after immunization. These findings support the importance of achieving a very high vaccination coverage with 2 doses of MCV.

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.