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.

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.

Estimated protection against COVID-19 based on predicted neutralisation titres from multiple antibody measurements in a longitudinal cohort, France, April 2020 to November 2021.

BackgroundThe risk of SARS-CoV-2 (re-)infection remains present given waning of vaccine-induced and infection-acquired immunity, and ongoing circulation of new variants.AimTo develop a method that predicts virus neutralisation and disease protection based on variant-specific antibody measurements to SARS-CoV-2 antigens.MethodsTo correlate antibody and neutralisation titres, we collected 304 serum samples from individuals with either vaccine-induced or infection-acquired SARS-CoV-2 immunity. Using the association between antibody and neutralisation titres, we developed a prediction model for SARS-CoV-2-specific neutralisation titres. From predicted neutralising titres, we inferred protection estimates to symptomatic and severe COVID-19 using previously described relationships between neutralisation titres and protection estimates. We estimated population immunity in a French longitudinal cohort of 905 individuals followed from April 2020 to November 2021.ResultsWe demonstrated a strong correlation between anti-SARS-CoV-2 antibodies measured using a low cost high-throughput assay and antibody response capacity to neutralise live virus. Participants with a single vaccination or immunity caused by infection were especially vulnerable to symptomatic or severe COVID-19. While the median reduced risk of COVID-19 from Delta variant infection in participants with three vaccinations was 96% (IQR: 94-98), median reduced risk among participants with infection-acquired immunity was only 42% (IQR: 22-66).ConclusionOur results are consistent with data from vaccine effectiveness studies, indicating the robustness of our approach. Our multiplex serological assay can be readily adapted to study new variants and provides a framework for development of an assay that would include protection estimates.

Impact of BNT162b2 Vaccination and Isolation on SARS-CoV-2 Transmission in Israeli Households: An Observational Study.

Several studies have characterized the effectiveness of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. However, estimates of their impact on transmissibility remain limited. Here, we evaluated the impact of isolation and vaccination (7 days after the second dose) on SARS-CoV-2 transmission within Israeli households. From December 2020 to April 2021, confirmed cases were identified among health-care workers of the Sheba Medical Centre and their family members. Recruited households were followed up with repeated PCR for at least 10 days after case confirmation. Data were analyzed using a data augmentation Bayesian framework. A total of 210 households with 215 index cases were enrolled; 269 out of 667 (40%) susceptible household contacts developed a SARS-CoV-2 infection. Of those, 170 (63%) developed symptoms. Compared with unvaccinated and unisolated adult/teenager (aged >12 years) contacts, vaccination reduced the risk of infection among unisolated adult/teenager contacts (relative risk (RR) = 0.21, 95% credible interval (CrI): 0.08, 0.44), and isolation reduced the risk of infection among unvaccinated adult/teenager (RR = 0.12, 95% CrI: 0.06, 0.21) and child contacts (RR = 0.17, 95% CrI: 0.08, 0.32). Infectivity was reduced in vaccinated cases (RR = 0.25, 95% CrI: 0.06, 0.77). Within households, vaccination reduces both the risk of infection and of transmission if infected. When contacts were unvaccinated, isolation also led to important reductions in the risk of transmission.

Zika Virus Circulation in Mali.

The circulation of Zika virus (ZIKV) in Mali has not been clearly characterized. Therefore, we conducted a serologic survey of 793 asymptomatic volunteers >15 years of age (2016), and 637 blood donors (2013) to assess the seroprevalence of ZIKV infection in 2 ecoclimatic regions of Mali, tropical savannah and warm semiarid region, using ELISA and seroneutralization assays. The overall seroprevalence was ≈12% and increased with age, with no statistical difference between male and female participants. In the warm semiarid study sites we detected immunological markers of an outbreak that occurred in the late 1990s in 18% (95% CI 13%-23%) of participants. In tropical savannah sites, we estimated a low rate of endemic transmission, with 2.5% (95% CI 2.0%-3.1%) of population infected by ZIKV annually. These data demonstrate the circulation of ZIKV in Mali and provide evidence of a previously unidentified outbreak that occurred in the late 1990s.

Aggressive or moderate drug therapy for infectious diseases? Trade-offs between different treatment goals at the individual and population levels.

Antimicrobial resistance is one of the major public health threats of the 21st century. There is a pressing need to adopt more efficient treatment strategies in order to prevent the emergence and spread of resistant strains. The common approach is to treat patients with high drug doses, both to clear the infection quickly and to reduce the risk of de novo resistance. Recently, several studies have argued that, at least in some cases, low-dose treatments could be more suitable to reduce the within-host emergence of antimicrobial resistance. However, the choice of a drug dose may have consequences at the population level, which has received little attention so far. Here, we study the influence of the drug dose on resistance and disease management at the host and population levels. We develop a nested two-strain model and unravel trade-offs in treatment benefits between an individual and the community. We use several measures to evaluate the benefits of any dose choice. Two measures focus on the emergence of resistance, at the host level and at the population level. The other two focus on the overall treatment success: the outbreak probability and the disease burden. We find that different measures can suggest different dosing strategies. In particular, we identify situations where low doses minimize the risk of emergence of resistance at the individual level, while high or intermediate doses prove most beneficial to improve the treatment efficiency or even to reduce the risk of resistance in the population.

Seroprevalence of hepatitis E virus among blood donors on Corsica, France, 2017.

BackgroundHepatitis E virus (HEV) is an emerging zoonotic pathogen and an important cause of acute viral hepatitis in European countries. Corsica Island has been previously identified as a hyperendemic area for HEV.AimOur aim was to characterise the prevalence and titres of IgG antibodies to HEV among blood donors on Corsica and establish a model of the annual force of infection.MethodsBetween September 2017 and January 2018, 2,705 blood donations were tested for anti-HEV IgG using the Wantai HEV IgG enzyme immunoassay.ResultsThe overall seroprevalence was 56.1%. In multivariate analysis, seroprevalence was higher in men than in women (60.0% vs 52.2%; p < 0.01), increased with age and was significantly higher among donors born on Corsica (60.6% vs 53.2%; p < 0.01). No significant difference was observed between the five districts of the island. IgG anti-HEV titres were mostly low (70% of positive donors had titres < 3 IU/mL). In Corsican natives, increasing seroprevalence by age could be explained by models capturing a loss of immunity (annual probability of infection: 4.5%; duration of immunity: 55 years) or by age-specific probabilities of infection (3.8% for children, 1.3% for adults).ConclusionWe confirmed the high HEV seroprevalence on Corsica and identified three aspects that should be further explored: (i) the epidemiology in those younger than 18 years, (ii) common sources of contamination, in particular drinking water, that may explain the wide exposure of the population, and (iii) the actual protection afforded by the low IgG titres observed and the potential susceptibility to secondary HEV infection.

Assessing the public health impact of tolerance-based therapies with mathematical models.

Disease tolerance is a defense strategy against infections that aims at maintaining host health even at high pathogen replication or load. Tolerance mechanisms are currently intensively studied with the long-term goal of exploiting them therapeutically. Because tolerance-based treatment imposes less selective pressure on the pathogen it has been hypothesised to be "evolution-proof". However, the primary public health goal is to reduce the incidence and mortality associated with a disease. From this perspective, tolerance-based treatment bears the risk of increasing the prevalence of the disease, which may lead to increased mortality. We assessed the promise of tolerance-based treatment strategies using mathematical models. Conventional treatment was implemented as an increased recovery rate, while tolerance-based treatment was assumed to reduce the disease-related mortality of infected hosts without affecting recovery. We investigated the endemic phase of two types of infections: acute and chronic. Additionally, we considered the effect of pathogen resistance against conventional treatment. We show that, for low coverage of tolerance-based treatment, chronic infections can cause even more deaths than without treatment. Overall, we found that conventional treatment always outperforms tolerance-based treatment, even when we allow the emergence of pathogen resistance. Our results cast doubt on the potential benefit of tolerance-based over conventional treatment. Any clinical application of tolerance-based treatment of infectious diseases has to consider the associated detrimental epidemiological feedback.

Kinetics of aggregation with a finite number of particles and application to viral capsid assembly.

The formation of a viral capsid can be seen as a time-dependent process generated by the arrival of aggregates of various sizes at a nucleation site. Based on a model where aggregates arrive at a Poissonian rate to form a capsid particle, we develop kinetics assembly equations, that account for a finite size cluster and thus for rejection of too large aggregate. The model is derived under the assumption that the aggregate distribution has reached an exponential steady state. To account for the stochastic nature of the aggregates arrival, we also derive a stochastic equation to compute the mean time for a cluster to be formed. We find that this time has a minimum for a unique aggregate distribution. We obtain asymptotic expression for this time that we compare with numerically simulations. Finally, we find the mean size of the largest aggregate forming a viral capsid.

Heterogeneity of AMPA receptor trafficking and molecular interactions revealed by superresolution analysis of live cell imaging.

Simultaneous tracking of many thousands of individual particles in live cells is possible now with the advent of high-density superresolution imaging methods. We present an approach to extract local biophysical properties of cell-particle interaction from such newly acquired large collection of data. Because classical methods do not keep the spatial localization of individual trajectories, it is not possible to access localized biophysical parameters. In contrast, by combining the high-density superresolution imaging data with the present analysis, we determine the local properties of protein dynamics. We specifically focus on AMPA receptor (AMPAR) trafficking and estimate the strength of their molecular interaction at the subdiffraction level in hippocampal dendrites. These interactions correspond to attracting potential wells of large size, showing that the high density of AMPARs is generated by physical interactions with an ensemble of cooperative membrane surface binding sites, rather than molecular crowding or aggregation, which is the case for the membrane viral glycoprotein VSVG. We further show that AMPARs can either be pushed in or out of dendritic spines. Finally, we characterize the recurrent step of influenza trajectories. To conclude, the present analysis allows the identification of the molecular organization responsible for the heterogeneities of random trajectories in cells.

Residence times of receptors in dendritic spines analyzed by stochastic simulations in empirical domains.

Analysis of high-density superresolution imaging of receptors reveals the organization of dendrites at nanoscale resolution. We present here an apparently novel method that uses local statistics extracted from short-range trajectories for the simulations of long-range trajectories in empirical live cell images. Based on these empirical simulations, we compute the residence time of a receptor in dendritic spines that accounts for receptors' local interactions and geometrical membrane organization. We report here that depending on the type of the spine, the residence time varies from 1 to 5 min. Moreover, we show that there exists transient organized structures, previously described as potential wells that can regulate the trafficking of receptors to dendritic spine: the simulation results suggest that receptor trafficking is regulated by transient structures.

Seroprevalence of anti-HEV IgG in children: very early exposure in young children in a hyperendemic region.

Background and objectives: Hepatitis E virus (HEV) can be considered an emerging zoonotic pathogen and is an important cause of acute viral hepatitis in high-income countries. Corsica has been identified as a hyperendemic region for HEV. We aimed to characterize the prevalence of IgG among children and estimate the annual force of infection of HEV. Methods: From April 2020 to June 2021, we collected 856 "residual sera" in 13 medical biology laboratories. Sera were tested using the Wantaï HEV IgG assay. Data were weighted according to the distribution by sex and age of the real Corsican population. Serocatalytic models were applied to assess the annual force of infection of HEV. Results: The weighted seroprevalence was 30.33% [27.15-34.0]. The seroprevalence was only associated with increasing age (7.25-40.52%; p < 0.001). The annual probability of infection was 5.4% for adults and children above 10-year-old and 2.2% for children under 10 yo. Conclusion: Our study demonstrates that in the hyperendemic island of Corsica, (i) exposure of the population to HEV is homogeneous at the spatial level with no difference between genders; (ii) HEV exposure occurs from birth, resulting in 7.4% seropositivity at the age of 4 years; and (iii) super exposure is observed after the age of 9 years. Accordingly, specific studies should be conducted to determine the breadth of the situation identified in our study. The role of the environment and its contamination by domestic or wild swine excreta should be investigated using a One Health approach.

SARS-CoV-2 IgG seroprevalence surveys in blood donors before the vaccination campaign, France 2020-2021.

We conducted a cross-sectional study for SARS-CoV-2 anti-S1 IgG prevalence in French blood donors (n = 32605), from March-2020 to January-2021. A mathematical model combined seroprevalence with a daily number of hospital admissions to estimate the probability of hospitalization upon infection and determine the number of infections while correcting for antibody decay. There was an overall seroprevalence increase over the study period and we estimate that ∼15% of the French population had been infected by SARS-CoV-2 by January-2021. The infection/hospitalization ratio increased with age, from 0.31% (18-30yo) to 4.5% (61-70yo). Half of the IgG-S1 positive individuals had no detectable antibodies 4 to 5 months after infection. The seroprevalence in group O donors (7.43%) was lower (p = 0.003) than in A, B, and AB donors (8.90%). We conclude, based on seroprevalence data and mathematical modeling, that a large proportion of the French population was unprotected against severe disease prior to the vaccination campaign.

Selection for infectivity profiles in slow and fast epidemics, and the rise of SARS-CoV-2 variants.

Evaluating the characteristics of emerging SARS-CoV-2 variants of concern is essential to inform pandemic risk assessment. A variant may grow faster if it produces a larger number of secondary infections ("R advantage") or if the timing of secondary infections (generation time) is better. So far, assessments have largely focused on deriving the R advantage assuming the generation time was unchanged. Yet, knowledge of both is needed to anticipate the impact. Here, we develop an analytical framework to investigate the contribution of both the R advantage and generation time to the growth advantage of a variant. It is known that selection on a variant with larger R increases with levels of transmission in the community. We additionally show that variants conferring earlier transmission are more strongly favored when the historical strains have fast epidemic growth, while variants conferring later transmission are more strongly favored when historical strains have slow or negative growth. We develop these conceptual insights into a new statistical framework to infer both the R advantage and generation time of a variant. On simulated data, our framework correctly estimates both parameters when it covers time periods characterized by different epidemiological contexts. Applied to data for the Alpha and Delta variants in England and in Europe, we find that Alpha confers a+54% [95% CI, 45-63%] R advantage compared to previous strains, and Delta +140% [98-182%] compared to Alpha, and mean generation times are similar to historical strains for both variants. This work helps interpret variant frequency dynamics and will strengthen risk assessment for future variants of concern.

Mutations in genes of the SARS-CoV-2 virus have generated new variants of concern, like Alpha, Delta, and more recently Omicron. These strains contain genetic modifications that help the virus spread more easily as well as altering the severity of the illness it causes. This has led to rising numbers of infections, known as epidemic waves, in many parts of the world. Tracking new variants of concern is crucial to protecting the public. To do this, scientists monitor how many people one person with the virus can infect, also known as the number of secondary infections. They may also measure when in the course of the illness an individual may pass along the virus to others. Together, these metrics help determine how fast and large an outbreak caused by a new variant will grow. The more people the new variant infects and the quicker it spreads, the more likely it is to replace existing strains of the virus. So far, most studies have assumed that the growth rate of a new variant solely depends on the number of secondary infections, and the timing of secondary infections is often not considered. To address this, Blanquart et al. built a mathematical model that combines both these parameters to determine the growth rate of new viral strains. The model showed that variants which rapidly cause secondary infections have a larger growth advantage over existing strains when the virus is more easily transmitted between individuals and the epidemic spreads rapidly. But when there is less transmission and the epidemic is declining, variants that generate secondary infections after a longer time have an advantage. For example, when control measures like mask wearing or social distancing are in place, delayed secondary infections may be more advantageous. Blanquart et al. then applied their model to data from the Alpha and Delta variant outbreaks in the United Kingdom. They found that Alpha and Delta did not change the timing of secondary infections compared to previously circulating strains. But the Alpha variant had a 54% transmission advantage over previous strains and the Delta variant had a 140% transmission advantage over Alpha. Taken together, these findings suggest that the timing of secondary infections and transmission rates both play an important role in how quickly a virus spreads. The new mathematical model created by Blanquart et al. may help epidemiologists better predict the trajectory of new SARS-CoV-2 variants and determine how to best control their spread.

Reconstructing Mayotte 2018-19 Rift Valley Fever outbreak in humans by combining serological and surveillance data.

BACKGROUND: Rift Valley Fever (RVF) is a zoonosis that affects large parts of Africa and the Arabian Peninsula. RVF virus (RVFV) is transmitted to humans through contacts with infected animals, animal products, mosquito bites or aerosols. Its pathogenesis in humans ranges from asymptomatic forms to potentially deadly haemorrhagic fevers, and the true burden of human infections during outbreaks is generally unknown. METHODS: We build a model fitted to both passive surveillance data and serological data collected throughout a RVF epidemic that occurred in Mayotte Island in 2018-2019. RESULTS: We estimate that RVFV infected 10,797 (95% CrI 4,728-16,127) people aged ≥15 years old in Mayotte during the entire outbreak, among which only 1.2% (0.67%-2.2%) were reported to the syndromic surveillance system. RVFV IgG seroprevalence in people ≥15 years old was estimated to increase from 5.5% (3.6%-7.7%) before the outbreak to 12.9% (10.4%-16.3%) thereafter. CONCLUSIONS: Our results suggest that a large part of RVFV infected people present subclinical forms of the disease and/or do not reach medical care that could lead to their detection by the surveillance system. This may threaten the implementation of exhaustive RVF surveillance and adequate control programs in affected countries.

Rift Valley Fever (RVF) is a disease caused by a virus transmitted from livestock animals to humans by mosquito bites, aerosols or direct contact with infected animals or animal products. In some parts of Africa and the Arabian Peninsula, the virus can lead to large outbreaks in both humans and animals. Despite some infected people developing severe forms of the disease, some experience no or mild symptoms. Therefore, infection is often not detected by surveillance systems based on the reporting of symptoms by patients. Here, we use data collected during a RVF outbreak that occurred in 2018­2019 in Mayotte Island, in the Indian Ocean, to model the course of the outbreak in humans. We estimate that, throughout the epidemic, only 1.2% of infected people were detected by the surveillance system. Our results highlight that most human cases may go unreported during RVF outbreaks, making it difficult to monitor the burden of infections.

Transmission dynamics of Q fever in French Guiana: A population-based cross-sectional study.

Background: Q fever is a zoonosis caused by Coxiella burnetii which is among the major agents of community-acquired pneumonia in French Guiana. Despite its relatively high incidence, its epidemiology in French Guiana remains unclear, and all previous studies have considered transmission from livestock unlikely, suggesting that a wild reservoir is responsible for transmission. Methods: A country-wide seroprevalence survey of 2697 participants from French Guiana was conducted. Serum samples were tested for phase II IgG antibodies by ELISA and indirect immunofluorescence assays (IFAs). Factors associated with Q fever were investigated, and a serocatalytic model was used to reconstruct the annual force of infection. Findings: The overall weighted seroprevalence was estimated at 9.6% (95% confidence interval (CI): 8.2%-11.0%). The model revealed constant, low-level circulation across French Guiana, particularly affecting middle-aged males (odds ratio (OR): 3.0, 95% credible interval (CrI): 1.7-5.8) and individuals living close to sheep farms (OR: 4, 95% CrI: 1.5-12). The overall annual number of cases was estimated at 579 (95% CrI: 492-670). In the region around Cayenne, the main urban municipality, the high seroprevalence was explained by an outbreak that may have occurred between 1996 and 2003 and that infected 10% (95% CrI: 6.9%-14%) of the population and males and females alike. Interpretation: This study reveals for the first time Q fever dynamics of transmission and the role of domestic livestock in transmission in French Guiana and highlights the urgent need to reinforce Q fever surveillance in livestocks of the entire Guianese territory. Funding: This study was supported by the "European Regional Development Fund" under EPI-ARBO grant agreement (GY0008695), the "Regional Health Agency of French Guiana" and the "National Center of Spatial Studies". The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Evolution of outcomes for patients hospitalised during the first 9 months of the SARS-CoV-2 pandemic in France: A retrospective national surveillance data analysis.

BACKGROUND: As SARS-CoV-2 continues to spread, a thorough characterisation of healthcare needs and patient outcomes, and how they have changed over time, is essential to inform planning. METHODS: We developed a probabilistic framework to analyse detailed patient trajectories from 198,846 hospitalisations in France during the first nine months of the pandemic. Our model accounts for the varying age- and sex- distribution of patients, and explore changes in outcome probabilities as well as length of stay. FINDINGS: We found that there were marked changes in the age and sex of hospitalisations over the study period. In particular, the proportion of hospitalised individuals that were >80y varied between 27% and 48% over the course of the epidemic, and was lowest during the inter-peak period. The probability of hospitalised patients entering ICU dropped from 0·25 (0·24-0·26) to 0·13 (0·12-0·14) over the four first months as case numbers fell, before rising to 0·19 (0·19-0·20) during the second wave. The probability of death followed a similar trajectory, falling from 0·25 (0·24-0·26) to 0·10 (0·09-0·11) after the first wave before increasing again during the second wave to 0·19 (0·18-0·19). Overall, we find both the probability of death and the probability of entering ICU were significantly correlated with COVID-19 ICU occupancy. INTERPRETATION: There are large scale trends in patients outcomes by age, sex and over time. These need to be considered in ongoing healthcare planning efforts. FUNDING: INCEPTION.

Quantitative evaluation of the infection dynamics of bovine brucellosis in Tanzania.

Brucellosis is endemic in Tanzania. A cross-sectional study was conducted at 17 cattle farms in agro-pastoral areas in Tanzania to identify risk factors associated with the within-farm prevalence of bovine brucellosis and to quantitatively assess the infection dynamics through disease modelling. Cattle blood sampling and interviews with farmers using a structured questionnaire were conducted. A total of 673 serum samples were screened using the Rose-Bengal plate test (RBPT), and sero-positivity of RBPT-positive samples was confirmed using a competitive enzyme-linked immunosorbent assay. Zero-inflated binomial regression was performed for univariable and multivariable risk factor analyses of within-farm prevalence. Several susceptible-infectious (SI) models were compared based on deviance information criteria, and age-dependent force of infection (FOI) was measured using age-specific prevalence data for the 10 infection-positive farms. Using the diagnoses of cows on the 17 farms, the basic reproduction number, R0, was also calculated. The farm-level prevalence and animal-level adjusted prevalence were 58.8 % (10/17, 95 % confidence interval: 33.5-80.6 %) and 7.0 % (28/673, 95 % credible interval: 5.7-8.4 %), respectively. The risk factor for high within-farm prevalence was introduction of cattle from other herds. A mathematical model with constant FOI showed the annual probability of infection as 1.4 % (95 % credible interval: 1.0 %-2.0 %). The R0 was 1.07. The constant FOI could have been due to the predominant mode of infection being transmission of Brucella from contaminated aborted materials during grazing. Direct purchase of infected cattle could facilitate efficient transmission between susceptible animals through abortion.

Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study.

BACKGROUND: Regional monitoring of the proportion of the population who have been infected by SARS-CoV-2 is important to guide local management of the epidemic, but is difficult in the absence of regular nationwide serosurveys. We aimed to estimate in near real time the proportion of adults who have been infected by SARS-CoV-2. METHODS: In this modelling study, we developed a method to reconstruct the proportion of adults who have been infected by SARS-CoV-2 and the proportion of infections being detected, using the joint analysis of age-stratified seroprevalence, hospitalisation, and case data, with deconvolution methods. We developed our method on a dataset consisting of seroprevalence estimates from 9782 participants (aged ≥20 years) in the two worst affected regions of France in May, 2020, and applied our approach to the 13 French metropolitan regions over the period March, 2020, to January, 2021. We validated our method externally using data from a national seroprevalence study done between May and June, 2020. FINDINGS: We estimate that 5·7% (95% CI 5·1-6·4) of adults in metropolitan France had been infected with SARS-CoV-2 by May 11, 2020. This proportion remained stable until August, 2020, and increased to 14·9% (13·2-16·9) by Jan 15, 2021. With 26·5% (23·4-29·8) of adult residents having been infected in Île-de-France (Paris region) compared with 5·1% (4·5-5·8) in Brittany by January, 2021, regional variations remained large (coefficient of variation [CV] 0·50) although less so than in May, 2020 (CV 0·74). The proportion infected was twice as high (20·4%, 15·6-26·3) in 20-49-year-olds than in individuals aged 50 years or older (9·7%, 6·9-14·1). 40·2% (34·3-46·3) of infections in adults were detected in June to August, 2020, compared with 49·3% (42·9-55·9) in November, 2020, to January, 2021. Our regional estimates of seroprevalence were strongly correlated with the external validation dataset (coefficient of correlation 0·89). INTERPRETATION: Our simple approach to estimate the proportion of adults that have been infected with SARS-CoV-2 can help to characterise the burden of SARS-CoV-2 infection, epidemic dynamics, and the performance of surveillance in different regions. FUNDING: EU RECOVER, Agence Nationale de la Recherche, Fondation pour la Recherche Médicale, Institut National de la Santé et de la Recherche Médicale (Inserm).

Model-based assessment of Chikungunya and O'nyong-nyong virus circulation in Mali in a serological cross-reactivity context.

Serological surveys are essential to quantify immunity in a population but serological cross-reactivity often impairs estimates of the seroprevalence. Here, we show that modeling helps addressing this key challenge by considering the important cross-reactivity between Chikungunya (CHIKV) and O'nyong-nyong virus (ONNV) as a case study. We develop a statistical model to assess the epidemiology of these viruses in Mali. We additionally calibrate the model with paired virus neutralization titers in the French West Indies, a region with known CHIKV circulation but no ONNV. In Mali, the model estimate of ONNV and CHIKV prevalence is 30% and 13%, respectively, versus 27% and 2% in non-adjusted estimates. While a CHIKV infection induces an ONNV response in 80% of cases, an ONNV infection leads to a cross-reactive CHIKV response in only 22% of cases. Our study shows the importance of conducting serological assays on multiple cross-reactive pathogens to estimate levels of virus circulation.