Predicting the age of field Anopheles mosquitoes using mass spectrometry and deep learning

Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance is needed. Survival of Anopheles mosquitoes is key for epidemiological monitoring of malaria transmission and evaluation of vector control strategies targeting mosquito longevity, as the risk of pathogen transmission increases with mosquito age. However, the available tools to estimate field mosquito age are often approximate and time-consuming. Here, we show a rapid method that combines matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry with deep learning for mosquito age prediction. Using 2763 mass spectra from the head, legs, and thorax of 251 field-collected Anopheles arabiensis mosquitoes, we developed deep learning models that achieved a best mean absolute error of 1.74 days. We also demonstrate consistent performance at two ecological sites in Senegal, supported by age-related protein changes. Our approach is promising for malaria control and the field of vector biology, benefiting other disease vectors like Aedes mosquitoes.

Septin-dependent defense mechanisms against Pseudomonas aeruginosa are stalled in cystic fibrosis bronchial epithelial cells

Airway epithelial cells form a physical barrier against inhaled pathogens and coordinate innate immune responses in the lungs. Bronchial cells in people with cystic fibrosis (pwCF) are colonized by Pseudomonas aeruginosa because of the accumulation of mucus in the lower airways and an altered immune response. This leads to chronic inflammation, lung tissue damage, and accelerated decline in lung function. Thus, identifying the molecular factors involved in the host response in the airways is crucial for developing new therapeutic strategies. The septin (SEPT) cytoskeleton is involved in tissue barrier integrity and anti-infective responses. SEPT7 is critical for maintaining SEPT complexes and for sensing pathogenic microbes. In the lungs, SEPT7 may be involved in the epithelial barrier resistance to infection; however, its role in cystic fibrosis (CF) P. aeruginosa infection is unknown. This study aimed to investigate the role of SEPT7 in controlling P. aeruginosa infection in bronchial epithelial cells, particularly in CF. The study findings showed that SEPT7 encages P. aeruginosa in bronchial epithelial cells and its inhibition downregulates the expression of other SEPTs. In addition, P. aeruginosa does not regulate SEPT7 expression. Finally, we found that inhibiting SEPT7 expression in bronchial epithelial cells (BEAS-2B 16HBE14o- and primary cells) resulted in higher levels of internalized P. aeruginosa and decreased IL-6 production during infection, suggesting a crucial role of SEPT7 in the host response against this bacterium. However, these effects were not observed in the CF cells (16HBE14o-/F508del and primary cells) which may explain the persistence of infection in pwCF. The study findings suggest the modification of SEPT7 expression as a potential approach for the anti-infective control of P. aeruginosa, particularly in CF.

Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha

SARS-CoV-2 variants of concern (VOCs) circulated cryptically before being identified as a threat, delaying interventions. Here we studied the drivers of such silent spread and its epidemic impact to inform future response planning. We focused on Alpha spread out of the UK. We integrated spatio-temporal records of international mobility, local epidemic growth and genomic surveillance into a Bayesian framework to reconstruct the first three months after Alpha emergence. We found that silent circulation lasted from days to months and decreased with the logarithm of sequencing coverage. Social restrictions in some countries likely delayed the establishment of local transmission, mitigating the negative consequences of late detection. Revisiting the initial spread of Alpha supports local mitigation at the destination in case of emerging events.

Airway infections as a risk factor for Pseudomonas aeruginosa acquisition and chronic colonisation in children with cystic fibrosis

BACKGROUND

Pseudomonas aeruginosa (Pa) infection is detrimental to people with cystic fibrosis (pwCF). Several clinical and genetic factors predispose to early Pa infections. However, the role of earlier infections with other pathogens on the risk of Pa infection in paediatric pwCF remains unknown.

METHODS

Using Kaplan-Meier method, we computed the cumulative incidences of bacterial and fungal initial acquisition (IA) and chronic colonisation (CC) in 1,231 French pwCF under 18 years of age for methicillin-susceptible and resistant Staphylococcus aureus (MSSA and MRSA), Stenotrophomonas maltophilia, Haemophilus influenzae, Achromobacter xylosoxidans, and Aspergillus species. Previous infections were analysed as Pa-IA and Pa-CC risk factors using Cox regression models.

RESULTS

By 2 years of age, 65.5% pwCF had experienced at least one bacterial or fungal IA, and 27.9% had experienced at least one CC. The median age of Pa-IA was 5.1 years, and Pa-CC was present in 25% pwCF by 14.7 years. While 50% acquired MSSA at 2.1 years, 50% progressed to chronic MSSA colonisation at 8.4 years. At 7.9 and 9.7 years, 25% pwCF were infected by S. maltophilia and Aspergillus spp., respectively. The risk of Pa-IA and Pa-CC increased with IAs of all other species, with hazard ratios (HR) up to 2.19 (95% Confidence interval (CI) 1.18-4.07). The risk of Pa-IA increased with the number of previous bacterial/fungal IAs (HR=1.89, 95% CI 1.57-2.28), with a 16% increase per additional pathogen; same trend was noted for Pa-CC.

CONCLUSIONS

This study establishes that the microbial community in CF airways can modulate Pa occurrence. At the dawn of targeted therapies, it paves the way for characterizing future trends and evolution of infections.

Spatial and Ecological Factors Modulate the Incidence of Anti-NMDAR Encephalitis-A Systematic Review

Anti-NMDAR encephalitis has been associated with multiple antigenic triggers (i.e., ovarian teratomas, prodromal viral infections) but whether geographic, climatic, and environmental factors might influence disease risk has not been explored yet. We performed a systematic review and a meta-analysis of all published papers reporting the incidence of anti-NMDAR encephalitis in a definite country or region. We performed several multivariate spatial autocorrelation analyses to analyze the spatial variations in the incidence of anti-NMDA encephalitis depending on its geographical localization and temperature. Finally, we performed seasonal analyses in two original datasets from France and Greece and assessed the impact of temperature using an exposure-lag-response model in the French dataset. The reported incidence of anti-NMDAR encephalitis varied considerably among studies and countries, being higher in Oceania and South America (0.2 and 0.16 per 100,000 persons-year, respectively) compared to Europe and North America (0.06 per 100,000 persons-year) (p < 0.01). Different regression models confirmed a strong negative correlation with latitude (Pearson's R = -0.88, p < 0.00001), with higher incidence in southern hemisphere countries far from the equator. Seasonal analyses showed a peak of cases during warm months. Exposure-lag-response models confirmed a positive correlation between extreme hot temperatures and the incidence of anti-NMDAR encephalitis in France (p = 0.03). Temperature analyses showed a significant association with higher mean temperatures and positive correlation with higher ultraviolet exposure worldwide. This study provides the first evidence that geographic and climatic factors including latitude, mean annual temperature, and ultraviolet exposure, might modify disease risk.

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.

Global patterns and drivers of influenza decline during the COVID-19 pandemic

OBJECTIVES

The influenza circulation reportedly declined during the COVID-19 pandemic in many countries. The occurrence of this change has not been studied worldwide nor its potential drivers.

METHODS

The change in the proportion of positive influenza samples reported by country and trimester was computed relative to the 2014-2019 period using the FluNet database. Random forests were used to determine predictors of change from demographical, weather, pandemic preparedness, COVID-19 incidence, and pandemic response characteristics. Regression trees were used to classify observations according to these predictors.

RESULTS

During the COVID-19 pandemic, the influenza decline relative to prepandemic levels was global but heterogeneous across space and time. It was more than 50% for 311 of 376 trimesters-countries and even more than 99% for 135. COVID-19 incidence and pandemic preparedness were the two most important predictors of the decline. Europe and North America initially showed limited decline despite high COVID-19 restrictions; however, there was a strong decline afterward in most temperate countries, where pandemic preparedness, COVID-19 incidence, and social restrictions were high; the decline was limited in countries where these factors were low. The "zero-COVID" countries experienced the greatest decline.

CONCLUSION

Our findings set the stage for interpreting the resurgence of influenza worldwide.

Screening and vaccination against COVID-19 to minimise school closure: a modelling study

BACKGROUND

Schools were closed extensively in 2020-21 to counter SARS-CoV-2 spread, impacting students' education and wellbeing. With highly contagious variants expanding in Europe, safe options to maintain schools open are urgently needed. By estimating school-specific transmissibility, our study evaluates costs and benefits of different protocols for SARS-CoV-2 control at school.

METHODS

We developed an agent-based model of SARS-CoV-2 transmission in schools. We used empirical contact data in a primary and a secondary school and data from pilot screenings in 683 schools during the alpha variant (B.1.1.7) wave in March-June, 2021, in France. We fitted the model to observed school prevalence to estimate the school-specific effective reproductive number for the alpha (Ralpha) and delta (B.1.617.2; Rdelta) variants and performed a cost-benefit analysis examining different intervention protocols.

FINDINGS

We estimated Ralpha to be 1·40 (95% CI 1·35-1·45) in the primary school and 1·46 (1·41-1·51) in the secondary school during the spring wave, higher than the time-varying reproductive number estimated from community surveillance. Considering the delta variant and vaccination coverage in Europe as of mid-September, 2021, we estimated Rdelta to be 1·66 (1·60-1·71) in primary schools and 1·10 (1·06-1·14) in secondary schools. Under these conditions, weekly testing of 75% of unvaccinated students (PCR tests on saliva samples in primary schools and lateral flow tests in secondary schools), in addition to symptom-based testing, would reduce cases by 34% (95% CI 32-36) in primary schools and 36% (35-39) in secondary schools compared with symptom-based testing alone. Insufficient adherence was recorded in pilot screening (median ≤53%). Regular testing would also reduce student-days lost up to 80% compared with reactive class closures. Moderate vaccination coverage in students would still benefit from regular testing for additional control-ie, weekly testing 75% of unvaccinated students would reduce cases compared with symptom-based testing only, by 23% in primary schools when 50% of children are vaccinated.

INTERPRETATION

The COVID-19 pandemic will probably continue to pose a risk to the safe and normal functioning of schools. Extending vaccination coverage in students, complemented by regular testing with good adherence, are essential steps to keep schools open when highly transmissible variants are circulating.

FUNDING

EU Framework Programme for Research and Innovation Horizon 2020, Horizon Europe Framework Programme, Agence Nationale de la Recherche, ANRS-Maladies Infectieuses Émergentes.

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-d–ahead 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.

SLC6A14 Impacts Cystic Fibrosis Lung Disease Severity via mTOR and Epithelial Repair Modulation

Cystic fibrosis (CF), due to pathogenic variants in CFTR gene, is associated with chronic infection/inflammation responsible for airway epithelium alteration and lung function decline. Modifier genes induce phenotype variability between people with CF (pwCF) carrying the same CFTR variants. Among these, the gene encoding for the amino acid transporter SLC6A14 has been associated with lung disease severity and age of primary airway infection by the bacteria Pseudomonas aeruginosa. In this study, we investigated whether the single nucleotide polymorphism (SNP) rs3788766, located within SLC6A14 promoter, is associated with lung disease severity in a large French cohort of pwCF. We also studied the consequences of this SNP on SLC6A14 promoter activity using a luciferase reporter and the role of SLC6A14 in the mechanistic target of rapamycin kinase (mTOR) signaling pathway and airway epithelial repair. We confirm that SLC6A14 rs3788766 SNP is associated with lung disease severity in pwCF (p = 0.020; n = 3,257, pancreatic insufficient, aged 6–40 years old), with the minor allele G being deleterious. In bronchial epithelial cell lines deficient for CFTR, SLC6A14 promoter activity is reduced in the presence of the rs3788766 G allele. SLC6A14 inhibition with a specific pharmacological blocker reduced ³H-arginine transport, mTOR phosphorylation, and bronchial epithelial repair rates in wound healing assays. To conclude, our study highlights that SLC6A14 genotype might affect lung disease severity of people with cystic fibrosis via mTOR and epithelial repair mechanism modulation in the lung.

SARS-CoV-2 in Nursing Homes: Analysis of Routine Surveillance Data in Four European Countries

Transmission of SARS-CoV-2 in nursing homes is poorly documented. Using surveillance data of 228 European private nursing homes, we estimated weekly SARS-CoV-2 incidences among 21,467 residents and 14,371 staff members, compared to that in the general population, between August 3, 2020, and February 20, 2021. We studied the outcomes of "episodes of introduction" where one case was first detected and computed attack rates, reproduction ratio (R), and dispersion parameter (k). Out of 502 episodes of SARS-CoV-2 introduction, 77.1% (95%CI, 73.2%-80.6%) led to additional cases. Attack rates were highly variable, ranging from 0.4% to 86.5%. The R was 1.16 (95%CI, 1.11-1.22) with k at 2.5 (95%CI, 0.5-4.5). The timing of viral circulation in nursing homes did not mirror that in the general population (p-values<0.001). We estimated the impact of vaccination in preventing SARS-CoV-2 transmission. Before vaccination's roll-out, a cumulated 5,579 SARS-CoV-2 infections were documented among residents and 2,321 among staff. Higher staffing ratio and previous natural immunization reduced the probability of an outbreak following introduction. Despite strong preventive measures, transmission likely occurred, regardless of building characteristics. Vaccination started on January 15, 2021, and coverage reached 65.0% among residents, and 42.0% among staff by February 20, 2021. Vaccination yielded a 92% reduction (95%CI, 71%-98%) of outbreak probability, and lowered R to 0.87 (95%CI, 0.69-1.10). In the post-pandemic era, much attention will have to be paid to multi-lateral collaboration, policy making, and prevention plans.

Adherence and sustainability of interventions informing optimal control against the COVID-19 pandemic

Background

After one year of stop-and-go COVID-19 mitigation, in the spring of 2021 European countries still experienced sustained viral circulation due to the Alpha variant. As the prospect of entering a new pandemic phase through vaccination was drawing closer, a key challenge remained on how to balance the efficacy of long-lasting interventions and their impact on the quality of life.

Methods

Focusing on the third wave in France during spring 2021, we simulate intervention scenarios of varying intensity and duration, with potential waning of adherence over time, based on past mobility data and modeling estimates. We identify optimal strategies by balancing efficacy of interventions with a data-driven "distress" index, integrating intensity and duration of social distancing.

Results

We show that moderate interventions would require a much longer time to achieve the same result as high intensity lockdowns, with the additional risk of deteriorating control as adherence wanes. Shorter strict lockdowns are largely more effective than longer moderate lockdowns, for similar intermediate distress and infringement on individual freedom.

Conclusions

Our study shows that favoring milder interventions over more stringent short approaches on the basis of perceived acceptability could be detrimental in the long term, especially with waning adherence.

Lockdown impact on age-specific contact patterns and behaviours, France, April 2020

BackgroundMany countries implemented national lockdowns to contain the rapid spread of SARS-CoV-2 and avoid overburdening healthcare capacity.AimWe aimed to quantify how the French lockdown impacted population mixing, contact patterns and behaviours.MethodsWe conducted an online survey using convenience sampling and collected information from participants aged 18 years and older between 10 April and 28 April 2020.ResultAmong the 42,036 survey participants, 72% normally worked outside their home, and of these, 68% changed to telework during lockdown and 17% reported being unemployed during lockdown. A decrease in public transport use was reported from 37% to 2%. Participants reported increased frequency of hand washing and changes in greeting behaviour. Wearing masks in public was generally limited. A total of 138,934 contacts were reported, with an average of 3.3 contacts per individual per day; 1.7 in the participants aged 65 years and older compared with 3.6 for younger age groups. This represented a 70% reduction compared with previous surveys, consistent with SARS-CoV2 transmission reduction measured during the lockdown. For those who maintained a professional activity outside home, the frequency of contacts at work dropped by 79%.ConclusionThe lockdown affected the population's behaviour, work, risk perception and contact patterns. The frequency and heterogeneity of contacts, both of which are critical factors in determining how viruses spread, were affected. Such surveys are essential to evaluate the impact of lockdowns more accurately and anticipate epidemic dynamics in these conditions.

SARS-CoV-2 transmission across age groups in France and implications for control

The shielding of older individuals has been proposed to limit COVID-19 hospitalizations while relaxing general social distancing in the absence of vaccines. Evaluating such approaches requires a deep understanding of transmission dynamics across ages. Here, we use detailed age-specific case and hospitalization data to model the rebound in the French epidemic in summer 2020, characterize age-specific transmission dynamics and critically evaluate different age-targeted intervention measures in the absence of vaccines. We find that while the rebound started in young adults, it reached individuals aged ≥80 y.o. after 4 weeks, despite substantial contact reductions, indicating substantial transmission flows across ages. We derive the contribution of each age group to transmission. While shielding older individuals reduces mortality, it is insufficient to allow major relaxations of social distancing. When the epidemic remains manageable (R close to 1), targeting those most contributing to transmission is better than shielding at-risk individuals. Pandemic control requires an effort from all age groups.

Computerized decision support system (CDSS) use for surveillance of antimicrobial resistance in urinary tract infections in primary care

BACKGROUND

Hospital-based surveillance of antimicrobial resistance may be irrelevant as a guide to antimicrobial use for urinary tract infections (UTIs) in primary care.

OBJECTIVES

To highlight the value of online computerized decision support systems (CDSS) in providing information on the surveillance of antimicrobial resistance in community-acquired UTIs.

METHODS

We collected the susceptibility profile for key antibiotics by type of UTI involving Escherichia coli from 2017 to 2020, using queries for UTI (Q-UTI) submitted to a French CDSS. We compared these results with those from the MedQual French surveillance system for community-acquired UTI and the European Antimicrobial Resistance Surveillance Network (EARS-NET) for invasive infections.

RESULTS

We collected 43 591 Q-UTI, of which 10 192 (23%) involved E. coli: 40% cystitis, 32% male-UTI, and 27% pyelonephritis. Resistance was 41.3% (95% CI, 40.3%-42.2%) for amoxicillin, 16.6% (95% CI, 15.9%-17.3%) for fluoroquinolones, 6.6% (95% CI, 6.1%-7.0%) for third-generation cephalosporins (3GC), and 5.7% (95% CI, 5.2%-6.1%) for aminoglycosides. Resistance to amoxicillin was lower than that reported in MedQual (42.7%, P value = 0.004), and in EARS-NET (55.2%, P value < 0.001). For fluoroquinolones, resistance was higher than in MedQual (12.0%, P value < 0.001) and EARS-NET (15.8%, P value = 0.041). In complicated pyelonephritis and male UTI, fluoroquinolone resistance peaked at ∼20%. For 3GC, all UTI had higher resistance than in MedQual (3.5%, P value < 0.001), but lower than in EARS-NET (9.5%, P value < 0.001). Aminoglycoside resistance was not reported by MedQual, and was lower than in EARS-NET (7.1%, P value < 0.001).

CONCLUSIONS

CDSS can inform prescribers in real-time about the ecology and surveillance of E. coli resistance in community-acquired UTI. In complicated upper UTIs, they can underline the risk of empirical use of fluoroquinolones and suggest preferential use of 3GC.

Low-Coverage Whole Genome Sequencing of Cell-Free DNA From Immunosuppressed Cancer Patients Enables Tumor Fraction Determination and Reveals Relevant Copy Number Alterations

Cell-free DNA (cfDNA) analysis is a minimally invasive method that can be used to detect genomic abnormalities by directly testing a blood sample. This method is particularly useful for immunosuppressed patients, who are at high risk of complications from tissue biopsy. The cfDNA tumor fraction (TF) varies greatly across cancer type and between patients. Thus, the detection of molecular alterations is highly dependent on the circulating TF. In our study, we aimed to calculate the TF and characterize the copy number aberration (CNA) profile of cfDNA from patients with rare malignancies occurring in immunosuppressed environments or immune-privileged sites. To accomplish this, we recruited 36 patients: 19 patients with non-Hodgkin lymphoma (NHL) who were either human immunodeficiency virus (HIV)-positive or organ transplant recipients, 5 HIV-positive lung cancer patients, and 12 patients with glioma. cfDNA was extracted from the patients' plasma and sequenced using low-coverage whole genome sequencing (LC-WGS). The cfDNA TF was then calculated using the ichorCNA bioinformatic algorithm, based on the CNA profile. In parallel, we performed whole exome sequencing of patient tumor tissue and cfDNA samples with detectable TFs. We detected a cfDNA TF in 29% of immune-suppressed patients (one patient with lung cancer and six with systemic NHL), with a TF range from 8 to 70%. In these patients, the events detected in the CNA profile of cfDNA are well-known events associated with NHL and lung cancer. Moreover, cfDNA CNA profile correlated with the CNA profile of matched tumor tissue. No tumor-derived cfDNA was detected in the glioma patients. Our study shows that tumor genetic content is detectable in cfDNA from immunosuppressed patients with advanced NHL or lung cancer. LC-WGS is a time- and cost-effective method that can help select an appropriate strategy for performing extensive molecular analysis of cfDNA. This technique also enables characterization of CNAs in cfDNA when sufficient tumor content is available. Hence, this approach can be used to collect useful molecular information that is relevant to patient care.

Common communicable diseases in the general population in France during the COVID-19 pandemic

In France, social distancing measures have been adopted to contain the spread of COVID-19, culminating in national Lockdowns. The use of hand washing, hydro-alcoholic rubs and mask-wearing also increased over time. As these measures are likely to impact the transmission of many communicable diseases, we studied the changes in common infectious diseases incidence in France during the first year of COVID-19 circulation. We examined the weekly incidence of acute gastroenteritis, chickenpox, acute respiratory infections and bronchiolitis reported in general practitioner networks since January 2016. We obtained search engine query volume for French terms related to these diseases and sales data for relevant drugs over the same period. A periodic regression model was fit to disease incidence, drug sales and search query volume before the COVID-19 period and extrapolated afterwards. We compared the expected values with observations made in 2020. During the first lockdown period, incidence dropped by 67% for gastroenteritis, by 79% for bronchiolitis, by 49% for acute respiratory infection and 90% for chickenpox compared to the past years. Reductions with respect to the expected incidence reflected the strength of implemented measures. Incidence in children was impacted the most. Reduction in primary care consultations dropped during a short period at the beginning of the first lockdown period but remained more than 95% of the expected value afterwards. In primary care, the large decrease in reported gastroenteritis, chickenpox or bronchiolitis observed during the period where many barrier measures were implemented imply that the circulation of common viruses was reduced and informs on the overall effect of these measures.

Risk factors for Pseudomonas aeruginosa airway infection and lung function decline in children with cystic fibrosis

Background Cystic fibrosis (CF) lung disease is characterised by recurrent Pseudomonas aeruginosa (Pa) infections, leading to structural lung damage and decreased survival. The epidemiology of Pa infection and its impact on lung function in people with CF (pwCF), especially in recent birth cohorts, remain uncertain. Methods We included 1,231 French pwCF under 18 years of age. Age at initial acquisition (Pa-IA), chronic colonisation (Pa-CC), and duration from Pa-IA to Pa-CC were estimated using the Kaplan-Meier method. Demographic, clinical, and genetic characteristics were analysed as risk factors for Pa infection using Cox regression models. Lung function decline was assessed by modelling percent-predicted forced expiratory volume in 1 s (ppFEV1) before Pa infection, after Pa-IA, and after Pa-CC. Results Among the 1,231 pwCF, 50% had Pa-IA by the age of 5.1 years [95% confidence interval (CI) 3.8-6.2] and 25% had Pa-CC by the age of 14.7 years (95% CI 12.1 to ∞). We observed that CF-related diabetes and liver disease were risk factors for Pa, while gender, CFTR variants, and CF centre size were not. Genetic variants of TNF, DCTN4, SLC9A3, and CAV2 were confirmed to be associated with Pa. The annual rate of ppFEV1 decline before Pa was -0.38% predicted/year (95% CI -0.59 to -0.18), which decreased significantly after Pa-IA to -0.93% predicted/year (95% CI -1.14 to -0.71) and after Pa-CC to -1.51% predicted/year (95% CI -1.86 to -1.16). Conclusions We identified and replicated several risk factors associated with Pa infection and showed its deleterious impact on lung function in young pwCF. This large-scale study confirmed that Pa airway infection is a major determinant of lung disease severity.

A modelling study investigating short and medium-term challenges for COVID-19 vaccination: From prioritisation to the relaxation of measures

BACKGROUND

The roll-out of COVID-19 vaccines is a multi-faceted challenge whose performance depends on pace of vaccination, vaccine characteristics and heterogeneities in individual risks.

METHODS

We developed a mathematical model accounting for the risk of severe disease by age and comorbidity, and transmission dynamics. We compared vaccine prioritisation strategies in the early roll-out stage and quantified the extent to which measures could be relaxed as a function of the vaccine coverage achieved in France.

FINDINGS

Prioritizing at-risk individuals reduces morbi-mortality the most if vaccines only reduce severity, but is of less importance if vaccines also substantially reduce infectivity or susceptibility. Age is the most important factor to consider for prioritization; additionally accounting for comorbidities increases the performance of the campaign in a context of scarce resources. Vaccinating 90% of ≥65 y.o. and 70% of 18-64 y.o. before autumn 2021 with a vaccine that reduces severity by 90% and susceptibility by 80%, we find that control measures reducing transmission rates by 15-27% should be maintained to remain below 1000 daily hospital admissions in France with a highly transmissible variant (basic reproduction number R0  = 4). Assuming 90% of ≥65 y.o. are vaccinated, full relaxation of control measures might be achieved with a vaccine coverage of 89-100% in 18-64 y.o or 60-69% of 0-64 y.o.

INTERPRETATION

Age and comorbidity-based vaccine prioritization strategies could reduce the burden of the disease. Very high vaccination coverage may be required to completely relax control measures. Vaccination of children, if possible, could lower coverage targets necessary to achieve this objective.

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.

A computerized decision support system (CDSS) for antibiotic prescription in primary care-Antibioclic: implementation, adoption and sustainable use in the era of extended antimicrobial resistance

OBJECTIVES

To describe the implementation and use of a computerized decision support system (CDSS) for antibiotic prescription in primary care in France (Antibioclic). The CDSS targets 37 infectious diseases and has been freely available on a website since 2011.

METHODS

Description and implementation of the architecture of a CDSS for antibiotic prescription in general practice. Analysis of the queries made between 2012 and 2018 on the CDSS by GPs. Analysis of two cross-sectional studies of users in 2014 and 2019.

RESULTS

The number of queries increased from a median of 796/day [IQR, 578-989] in 2012 to 11 125/day [5592-12 505] in 2018. Unique users increased from 414/day [245-494] in 2012 to 5365/day [2891-5769] in 2018. Time taken to make a query was 2 min [1.9-2.1]. Among 3 542 347 queries in 2018, 78% were for adults. Six situations accounted for ≥50% of queries: cystitis; acute otitis media; acute sinusitis; community-acquired pneumonia; sore throat; and pyelonephritis. Queries concerned pathologies for which antibiotic prescription was necessary (64%), was conditional on additional clinical steps (34%) or was not recommended (2%). Most users (81%) were GPs, with median age of 38 years [31-52] and 58% were female. Among the 4016 GPs who responded to the surveys, the vast majority (96%) reported using the CDSS during the consultation, with 24% systematically using Antibioclic to initiate an antibiotic course and 93% having followed the CDSS recommendation for the latest prescription. Most GPs were comfortable using the CDSS in front of a patient.

CONCLUSIONS

Antibioclic has been adopted and is widely used in primary care in France. Its interoperability could allow its adaptation and implementation in other countries.

Lockdown as a last resort option in case of COVID-19 epidemic rebound: a modelling study

Background

Given its high economic and societal cost, policymakers might be reluctant to implement a large-scale lockdown in case of coronavirus disease (COVID-19) epidemic rebound. They may consider it as a last resort option if alternative control measures fail to reduce transmission.

Aim

We developed a modelling framework to ascertain the use of lockdown to ensure intensive care unit (ICU) capacity does not exceed a peak target defined by policymakers.

Methods

We used a deterministic compartmental model describing transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the trajectories of COVID-19 patients in healthcare settings, accounting for age-specific mixing patterns and an increasing probability of severe outcomes with age. The framework is illustrated in the context of metropolitan France.

Results

The daily incidence of ICU admissions and the number of occupied ICU beds are the most robust indicators to decide when a lockdown should be triggered. When the doubling time of hospitalisations estimated before lockdown is between 8 and 20 days, lockdown should be enforced when ICU admissions reach 3.0–3.7 and 7.8–9.5 per million for peak targets of 62 and 154 ICU beds per million (4,000 and 10,000 beds for metropolitan France), respectively. When implemented earlier, the lockdown duration required to get back below a desired level is also shorter.

Conclusions

We provide simple indicators and triggers to decide if and when a last-resort lockdown should be implemented to avoid saturation of ICU. These metrics can support the planning and real-time management of successive COVID-19 pandemic waves.

Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection

The efficacy of digital contact tracing against coronavirus disease 2019 (COVID-19) epidemic is debated: Smartphone penetration is limited in many countries, with low coverage among the elderly, the most vulnerable to COVID-19. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact and epidemiological information to describe exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity, and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for the elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan.

Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection

The efficacy of digital contact tracing against coronavirus disease 2019 (COVID-19) epidemic is debated: Smartphone penetration is limited in many countries, with low coverage among the elderly, the most vulnerable to COVID-19. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact and epidemiological information to describe exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity, and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for the elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan.

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.

Psychosocial risk factors for increased emergency hospital utilization by sickle cell disease patients: a systematic review protocol

OBJECTIVE

To assess psychosocial risk factors for increased emergency hospital utilization by sickle cell patients.

INTRODUCTION

Emergency hospital utilization by sickle cell disease patients is high but heterogeneous between patients and in a given patient over time. Psychosocial factors affect emergency hospital utilization and are a possible target to improve the management of sickle cell disease.

INCLUSION CRITERIA

This review will include all original quantitative studies evaluating the impact of psychosocial risk factors on emergency hospital utilization by sickle cell disease patients. There will be no language restriction.

METHODS

PubMed, Embase, CINAHL, PubPsych, LiSSa, and Web of Science will be searched using a peer-reviewed search strategy. Study selection and extraction of data will be performed independently by two authors. Discrepancies will be solved by consensus or, if needed, by a third author. The authors will assess study quality, as well as perform a narrative synthesis of included studies, and where possible, meta-analyses with evaluation of heterogeneity and publication bias.

SYSTEMATIC REVIEW REGISTRATION NUMBER

PROSPERO CRD42019140435.

Modelling safe protocols for reopening schools during the COVID-19 pandemic in France

As countries in Europe implement strategies to control the COVID-19 pandemic, different options are chosen regarding schools. Through a stochastic age-structured transmission model calibrated to the observed epidemic in Île-de-France in the first wave, we explored scenarios of partial, progressive, or full school reopening. Given the uncertainty on children's role, we found that reopening schools after lockdown may increase COVID-19 cases, yet protocols exist to keep the epidemic controlled. Under a scenario with stable epidemic activity if schools were closed, reopening pre-schools and primary schools would lead to up to 76% [67, 84]% occupation of ICU beds if no other school level reopened, or if middle and high schools reopened later. Immediately reopening all school levels may overwhelm the ICU system. Priority should be given to pre- and primary schools allowing younger children to resume learning and development, whereas full attendance in middle and high schools is not recommended for stable or increasing epidemic activity. Large-scale test and trace is required to keep the epidemic under control. Ex-post assessment shows that progressive reopening of schools, limited attendance, and strong adoption of preventive measures contributed to a decreasing epidemic after lifting the first lockdown.

Underdetection of cases of COVID-19 in France threatens epidemic control

As countries in Europe gradually relaxed lockdown restrictions after the first wave, test-trace-isolate strategies became critical to maintain the incidence of coronavirus disease 2019 (COVID-19) at low levels^1,2. Reviewing their shortcomings can provide elements to consider in light of the second wave that is currently underway in Europe. Here we estimate the rate of detection of symptomatic cases of COVID-19 in France after lockdown through the use of virological³ and participatory syndromic⁴ surveillance data coupled with mathematical transmission models calibrated to regional hospitalizations². Our findings indicate that around 90,000 symptomatic infections, corresponding to 9 out 10 cases, were not ascertained by the surveillance system in the first 7 weeks after lockdown from 11 May to 28 June 2020, although the test positivity rate did not exceed the 5% recommendation of the World Health Organization (WHO)⁵. The median detection rate increased from 7% (95% confidence interval, 6-8%) to 38% (35-44%) over time, with large regional variations, owing to a strengthening of the system as well as a decrease in epidemic activity. According to participatory surveillance data, only 31% of individuals with COVID-19-like symptoms consulted a doctor in the study period. This suggests that large numbers of symptomatic cases of COVID-19 did not seek medical advice despite recommendations, as confirmed by serological studies^6,7. Encouraging awareness and same-day healthcare-seeking behaviour of suspected cases of COVID-19 is critical to improve detection. However, the capacity of the system remained insufficient even at the low epidemic activity achieved after lockdown, and was predicted to deteriorate rapidly with increasing incidence of COVID-19 cases. Substantially more aggressive, targeted and efficient testing with easier access is required to act as a tool to control the COVID-19 pandemic. The testing strategy will be critical to enable partial lifting of the current restrictive measures in Europe and to avoid a third wave.

Trajectories of Hospitalization in COVID-19 Patients: An Observational Study in France

Describing the characteristics of COVID-19 patients in the hospital is of importance to assist in the management of hospital capacity in the future. Here, we analyze the trajectories of 1321 patients admitted to hospitals in northern and eastern France. We found that the time from onset to hospitalization decreased with age, from 7.3 days in the 20-65 year-olds to 4.5 in the >80 year-olds (p < 0.0001). Overall, the length of stay in the hospital was 15.9 days, and the death rate was 20%. One patient out of four was admitted to the intensive care unit (ICU) for approximately one month. The characteristics of trajectories changed with age: fewer older patients were admitted to the ICU and the death rate was larger in the elderly. Admission shortly after onset was associated with increased mortality (odds-ratio (OR) = 1.8, Confidence Interval (CI) 95% [1.3, 2.6]) as well as male sex (OR = 2.1, CI 95% [1.5, 2.9]). Time from admission within the hospital to the transfer to ICU was short. The age- and sex-adjusted mortality rate decreased over the course of the epidemic, suggesting improvement in care over time. In the SARS-CoV-2 epidemic, the urgent need for ICU at admission and the prolonged length of stay in ICU are a challenge for bed management and organization of care.

Impact of lockdown on COVID-19 epidemic in Île-de-France and possible exit strategies

BACKGROUND

More 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.

METHODS

We 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.

RESULTS

We 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.

CONCLUSIONS

As 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.

Tracing and analysis of 288 early SARS-CoV-2 infections outside China: A modeling study

BACKGROUND

In the early months of 2020, a novel coronavirus disease (COVID-19) spread rapidly from China across multiple countries worldwide. As of March 17, 2020, COVID-19 was officially declared a pandemic by the World Health Organization. We collected data on COVID-19 cases outside China during the early phase of the pandemic and used them to predict trends in importations and quantify the proportion of undetected imported cases.

METHODS AND FINDINGS

Two hundred and eighty-eight cases have been confirmed out of China from January 3 to February 13, 2020. We collected and synthesized all available information on these cases from official sources and media. We analyzed importations that were successfully isolated and those leading to onward transmission. We modeled their number over time, in relation to the origin of travel (Hubei province, other Chinese provinces, other countries) and interventions. We characterized the importation timeline to assess the rapidity of isolation and epidemiologically linked clusters to estimate the rate of detection. We found a rapid exponential growth of importations from Hubei, corresponding to a doubling time of 2.8 days, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the successive weeks. Time from travel to detection has considerably decreased since first importation, from 14.5 ± 5.5 days on January 5, 2020, to 6 ± 3.5 days on February 1, 2020. However, we estimated 36% of detection of imported cases. This study is restricted to the early phase of the pandemic, when China was the only large epicenter and foreign countries had not discovered extensive local transmission yet. Missing information in case history was accounted for through modeling and imputation.

CONCLUSIONS

Our findings indicate that travel bans and containment strategies adopted in China were effective in reducing the exportation growth rate. However, the risk of importation was estimated to increase again from other sources in South East Asia. Surveillance and management of traveling cases represented a priority in the early phase of the epidemic. With the majority of imported cases going undetected (6 out of 10), countries experienced several undetected clusters of chains of local transmissions, fueling silent epidemics in the community. These findings become again critical to prevent second waves, now that countries have reduced their epidemic activity and progressively phase out lockdown.

Excess cases of influenza-like illnesses synchronous with coronavirus disease (COVID-19) epidemic, France, March 2020

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.

Novel coronavirus (2019-nCoV) early-stage importation risk to Europe, January 2020

As at 27 January 2020, 42 novel coronavirus (2019-nCoV) cases were confirmed outside China. We estimate the risk of case importation to Europe from affected areas in China via air travel. We consider travel restrictions in place, three reported cases in France, one in Germany. Estimated risk in Europe remains high. The United Kingdom, Germany and France are at highest risk. Importation from Beijing and Shanghai would lead to higher and widespread risk for Europe.

Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study

BACKGROUND

The novel coronavirus disease 2019 (COVID-19) epidemic has spread from China to 25 countries. Local cycles of transmission have already occurred in 12 countries after case importation. In Africa, Egypt has so far confirmed one case. The management and control of COVID-19 importations heavily rely on a country's health capacity. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of COVID-19.

METHODS

We used data on the volume of air travel departing from airports in the infected provinces in China and directed to Africa to estimate the risk of importation per country. We determined the country's capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulations Monitoring and Evaluation Framework; and vulnerability, using the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing most to their risk.

FINDINGS

Countries with the highest importation risk (ie, Egypt, Algeria, and South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (ie, Nigeria, Ethiopia, Sudan, Angola, Tanzania, Ghana, and Kenya) have variable capacity and high vulnerability. We identified three clusters of countries that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and the city of Beijing, respectively.

INTERPRETATION

Many countries in Africa are stepping up their preparedness to detect and cope with COVID-19 importations. Resources, intensified surveillance, and capacity building should be urgently prioritised in countries with moderate risk that might be ill-prepared to detect imported cases and to limit onward transmission.

FUNDING

EU Framework Programme for Research and Innovation Horizon 2020, Agence Nationale de la Recherche.

Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study

BACKGROUND

The novel coronavirus disease 2019 (COVID-19) epidemic has spread from China to 25 countries. Local cycles of transmission have already occurred in 12 countries after case importation. In Africa, Egypt has so far confirmed one case. The management and control of COVID-19 importations heavily rely on a country's health capacity. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of COVID-19.

METHODS

We used data on the volume of air travel departing from airports in the infected provinces in China and directed to Africa to estimate the risk of importation per country. We determined the country's capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulations Monitoring and Evaluation Framework; and vulnerability, using the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing most to their risk.

FINDINGS

Countries with the highest importation risk (ie, Egypt, Algeria, and South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (ie, Nigeria, Ethiopia, Sudan, Angola, Tanzania, Ghana, and Kenya) have variable capacity and high vulnerability. We identified three clusters of countries that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and the city of Beijing, respectively.

INTERPRETATION

Many countries in Africa are stepping up their preparedness to detect and cope with COVID-19 importations. Resources, intensified surveillance, and capacity building should be urgently prioritised in countries with moderate risk that might be ill-prepared to detect imported cases and to limit onward transmission.

FUNDING

EU Framework Programme for Research and Innovation Horizon 2020, Agence Nationale de la Recherche.

Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study

BACKGROUND

The novel coronavirus disease 2019 (COVID-19) epidemic has spread from China to 25 countries. Local cycles of transmission have already occurred in 12 countries after case importation. In Africa, Egypt has so far confirmed one case. The management and control of COVID-19 importations heavily rely on a country's health capacity. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of COVID-19.

METHODS

We used data on the volume of air travel departing from airports in the infected provinces in China and directed to Africa to estimate the risk of importation per country. We determined the country's capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulations Monitoring and Evaluation Framework; and vulnerability, using the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing most to their risk.

FINDINGS

Countries with the highest importation risk (ie, Egypt, Algeria, and South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (ie, Nigeria, Ethiopia, Sudan, Angola, Tanzania, Ghana, and Kenya) have variable capacity and high vulnerability. We identified three clusters of countries that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and the city of Beijing, respectively.

INTERPRETATION

Many countries in Africa are stepping up their preparedness to detect and cope with COVID-19 importations. Resources, intensified surveillance, and capacity building should be urgently prioritised in countries with moderate risk that might be ill-prepared to detect imported cases and to limit onward transmission.

FUNDING

EU Framework Programme for Research and Innovation Horizon 2020, Agence Nationale de la Recherche.

Model-based Respondent-driven sampling analysis for HIV prevalence in brazilian MSM

Respondent Driven Sampling study (RDS) is a population sampling method developed to study hard-to-reach populations. A sample is obtained by chain-referral recruitment in a network of contacts within the population of interest. Such self-selected samples are not representative of the target population and require weighing observations to reduce estimation bias. Recently, the Network Model-Assisted (NMA) method was described to compute the required weights. The NMA method relies on modeling the underlying contact network in the population where the RDS was conducted, in agreement with directly observable characteristics of the sample such as the number of contacts, but also with more difficult-to-measure characteristics such as homophily or differential characteristics according to the response variable. Here we investigated the use of the NMA method to estimate HIV prevalence from RDS data when information on homophily is limited. We show that an iterative procedure based on the NMA approach allows unbiased estimations even in the case of strong population homophily and differential activity and limits bias in case of preferential recruitment. We applied the methods to determine HIV prevalence in men having sex with men in Brazilian cities and confirmed a high prevalence of HIV in these populations from 3.8% to 22.1%.

Factors associated with influenza-like-illness: a crowdsourced cohort study from 2012/13 to 2017/18

Background

Influenza generates a significant societal impact on morbidity, mortality, and associated costs. The study objective was to identify factors associated with influenza-like-illness (ILI) episodes during seasonal influenza epidemics among the general population.

Methods

A prospective study was conducted with the GrippeNet.fr crowdsourced cohort between 2012/13 and 2017/18. After having completed a yearly profile survey detailing socio-demographic, lifestyle and health characteristics, participants reported weekly data on symptoms. Factors associated with at least one ILI episode per influenza epidemic, using the European Centre for Disease Prevention and Control case definition, were analyzed through a conditional logistic regression model.

Results

From 2012/13 to 2017/18, 6992 individuals participated at least once, and 61% of them were women (n = 4258). From 11% (n = 469/4140 in 2013/14) to 29% (n = 866/2943 in 2012/13) of individuals experienced at least one ILI during an influenza epidemic. Factors associated with higher risk for ILI were: gender female (OR = 1.29, 95%CI [1.20; 1.40]), young age (< 5 years old: 3.12 [2.05; 4.68]); from 5 to 14 years old: 1.53 [1.17; 2.00]), respiratory allergies (1.27 [1.18; 1.37]), receiving a treatment for chronic disease (1.20 [1.09; 1.32]), being overweight (1.18 [1.08; 1.29]) or obese (1.28 [1.14; 1.44]), using public transport (1.17 [1.07; 1.29]) and having contact with pets (1.18 [1.09; 1.27]). Older age (≥ 75 years old: 0.70 [0.56; 0.87]) and being vaccinated against influenza (0.91 [0.84; 0.99]) were found to be protective factors for ILI.

Conclusions

This ILI risk factors analysis confirms and further completes the list of factors observed through traditional surveillance systems. It indicates that crowdsourced cohorts are effective to study ILI determinants at the population level. These findings could be used to adapt influenza prevention messages at the population level to reduce the spread of the disease.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7174-6) contains supplementary material, which is available to authorized users.

Close proximity interactions support transmission of ESBL-K. pneumoniae but not ESBL-E. coli in healthcare settings

Antibiotic-resistance of hospital-acquired infections is a major public health issue. The worldwide emergence and diffusion of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae, including Escherichia coli (ESBL-EC) and Klebsiella pneumoniae (ESBL-KP), is of particular concern. Preventing their nosocomial spread requires understanding their transmission. Using Close Proximity Interactions (CPIs), measured by wearable sensors, and weekly ESBL-EC-and ESBL-KP-carriage data, we traced their possible transmission paths among 329 patients in a 200-bed long-term care facility over 4 months. Based on phenotypically defined resistance profiles to 12 antibiotics only, new bacterial acquisitions were tracked. Extending a previously proposed statistical method, the CPI network's ability to support observed incident-colonization episodes of ESBL-EC and ESBL-KP was tested. Finally, mathematical modeling based on our findings assessed the effect of several infection-control measures. A potential infector was identified in the CPI network for 80% (16/20) of ESBL-KP acquisition episodes. The lengths of CPI paths between ESBL-KP incident cases and their potential infectors were shorter than predicted by chance (P = 0.02), indicating that CPI-network relationships were consistent with dissemination. Potential ESBL-EC infectors were identified for 54% (19/35) of the acquisitions, with longer-than-expected lengths of CPI paths. These contrasting results yielded differing impacts of infection control scenarios, with contact reduction interventions proving less effective for ESBL-EC than for ESBL-KP. These results highlight the widely variable transmission patterns among ESBL-producing Enterobacteriaceae species. CPI networks supported ESBL-KP, but not ESBL-EC spread. These outcomes could help design more specific surveillance and control strategies to prevent in-hospital Enterobacteriaceae dissemination.

SERPINA1 Z allele is associated with cystic fibrosis liver disease

PURPOSE

The SERPINA1 Z allele is associated with cystic fibrosis (CF)-related liver disease (CFLD), a common manifestation in patients with CF. We estimated CFLD incidence based on the SERPINA1 genotype in 3328 CF patients with CFLD-phenotype information.

METHODS

The associations of SERPINA1 Z (rs28929474) and S (rs17580) alleles with age at CFLD onset and the development of CFLD-related complications (severe liver disease with cirrhosis, portal hypertension, esophageal varices) were analyzed.

RESULTS

Overall, 3% of patients carried the SERPINA1 Z allele and 13% carried the S allele. The cumulative incidence of CFLD increased more rapidly in patients carrying the Z allele (hazard ratio [HR] = 1.6; 95% confidence interval [CI] = 1.1-2.4, P = 0.019), reaching 47% by age 25 compared with 30% in noncarriers. Increased risk was similar for patients with severe CFLD (HR = 1.5, 95% CI = 0.7-3.2, P = 0.31) but failed to reach significance due to a limited sample size of Z-allele carriers. No significant effect was found for the S allele.

CONCLUSION

CF patients carrying the SERPINA1 Z allele had an increased risk of developing CFLD and related complications compared with noncarriers. Routine SERPINA1 Z genotyping upon CF diagnosis is warranted for identifying patients worthy of closer liver disease monitoring.

Modeling the impact of changes in day-care contact patterns on the dynamics of varicella transmission in France between 1991 and 2015

Annual incidence rates of varicella infection in the general population in France have been rather stable since 1991 when clinical surveillance started. Rates however show a statistically significant increase over time in children aged 0-3 years, and a decline in older individuals. A significant increase in day-care enrolment and structures' capacity in France was also observed in the last decade. In this work we investigate the potential interplay between an increase of contacts of young children possibly caused by earlier socialization in the community and varicella transmission dynamics. To this aim, we develop an age-structured mathematical model, informed with historical demographic data and contact matrix estimates in the country, accounting for longitudinal linear increase of early childhood contacts. While the reported overall varicella incidence is well reproduced independently of mixing variations, age-specific empirical trends are better captured by accounting for an increase in contacts among pre-school children in the last decades. We found that the varicella data are consistent with a 30% increase in the number of contacts at day-care facilities, which would imply a 50% growth in the contribution of 0-3y old children to overall yearly infections in 1991-2015. Our findings suggest that an earlier exposure to pathogens due to changes in day-care contact patterns, represents a plausible explanation for the epidemiological patterns observed in France. Obtained results suggest that considering temporal changes in social factors in addition to demographic ones is critical to correctly interpret varicella transmission dynamics.

SLC26A9 Gene Is Associated With Lung Function Response to Ivacaftor in Patients With Cystic Fibrosis

Ivacaftor is a drug used to treat cystic fibrosis (CF) patients carrying specific gating CFTR mutations. Interpatient variability in the lung response has been shown to be partly explained by rs7512462 in the Solute Carrier Family 26 Member 9 (SLC26A9) gene. In an independent and larger cohort, we aimed to evaluate whether SLC26A9 variants contribute to the variability of the lung phenotype and if they influence the lung response to ivacaftor. We genotyped the French CF Gene Modifier Study cohort (n = 4,840) to investigate whether SLC26A9 variants were involved in the lung phenotype heterogeneity. Their influence in the response to ivacaftor was tested in the 30 treated patients who met the inclusion criteria: older than 6 years of age, percent-predicted forced expiratory volume measured in 1 s (FEV_1pp) in the 3 months before treatment initiation ranging between 40 and 90%. Response to treatment was determined by the change in FEV_1pp from baseline, averaged in 15–75 days, and the 1st-year post-treatment. We observed that SLC26A9 variants were not associated with lung function variability in untreated patients and that gain of lung function in patients treated with ivacaftor was similar to clinical trials. We confirmed that rs7512462 was associated with variability in ivacaftor-lung response, with a significant reduction in lung function improvement for patients with the C allele. Other SLC26A9 SNPs also contributed to the ivacaftor-response. Interindividual variability in lung response to ivacaftor is associated with SLC26A9 variants in French CF patients. Pharmacogenomics and personalized medicine will soon be part of CF patient care.

Improving early epidemiological assessment of emerging Aedes-transmitted epidemics using historical data

Model-based epidemiological assessment is useful to support decision-making at the beginning of an emerging Aedes-transmitted outbreak. However, early forecasts are generally unreliable as little information is available in the first few incidence data points. Here, we show how past Aedes-transmitted epidemics help improve these predictions. The approach was applied to the 2015-2017 Zika virus epidemics in three islands of the French West Indies, with historical data including other Aedes-transmitted diseases (chikungunya and Zika) in the same and other locations. Hierarchical models were used to build informative a priori distributions on the reproduction ratio and the reporting rates. The accuracy and sharpness of forecasts improved substantially when these a priori distributions were used in models for prediction. For example, early forecasts of final epidemic size obtained without historical information were 3.3 times too high on average (range: 0.2 to 5.8) with respect to the eventual size, but were far closer (1.1 times the real value on average, range: 0.4 to 1.5) using information on past CHIKV epidemics in the same places. Likewise, the 97.5% upper bound for maximal incidence was 15.3 times (range: 2.0 to 63.1) the actual peak incidence, and became much sharper at 2.4 times (range: 1.3 to 3.9) the actual peak incidence with informative a priori distributions. Improvements were more limited for the date of peak incidence and the total duration of the epidemic. The framework can adapt to all forecasting models at the early stages of emerging Aedes-transmitted outbreaks.

Characterizing and Comparing the Seasonality of Influenza-Like Illnesses and Invasive Pneumococcal Diseases Using Seasonal Waveforms

The seasonalities of influenza-like illnesses (ILIs) and invasive pneumococcal diseases (IPDs) remain incompletely understood. Experimental evidence indicates that influenza-virus infection predisposes to pneumococcal disease, so that a correspondence in the seasonal patterns of ILIs and IPDs might exist at the population level. We developed a method to characterize seasonality by means of easily interpretable summary statistics of seasonal shape-or seasonal waveforms. Nonlinear mixed-effects models were used to estimate those waveforms based on weekly case reports of ILIs and IPDs in 5 regions spanning continental France from July 2000 to June 2014. We found high variability of ILI seasonality, with marked fluctuations of peak amplitudes and peak times, but a more conserved epidemic duration. In contrast, IPD seasonality was best modeled by a markedly regular seasonal baseline, punctuated by 2 winter peaks in late December to early January and January to February. Comparing ILI and IPD seasonal waveforms, we found indication of a small, positive correlation. Direct models regressing IPDs on ILIs provided comparable results, even though they estimated moderately larger associations. The method proposed is broadly applicable to diseases with unambiguous seasonality and is well-suited to analyze spatially or temporally grouped data, which are common in epidemiology.

High emergency organ allocation rule in lung transplantation: a simulation study

The scarcity of suitable organ donors leads to protracted waiting times and mortality in patients awaiting lung transplantation. This study aims to assess the short- and long-term effects of a high emergency organ allocation policy on the outcome of lung transplantation.

We developed a simulation model of lung transplantation waiting queues under two allocation strategies, based either on waiting time only or on additional criteria to prioritise the sickest patients. The model was informed by data from the United Network for Organ Sharing. We compared the impact of these strategies on waiting time, waiting list mortality and overall survival in various situations of organ scarcity.

The impact of a high emergency allocation strategy depends largely on the organ supply. When organ supply is sufficient (>95 organs per 100 patients), it may prevent a small number of early deaths (1 year survival: 93.7% against 92.4% for waiting time only) without significant impact on waiting times or long-term survival. When the organ/recipient ratio is lower, the benefits in early mortality are larger but are counterbalanced by a dramatic increase of the size of the waiting list. Consequently, we observed a progressive increase of mortality on the waiting list (although still lower than with waiting time only), a deterioration of patients’ condition at transplant and a decrease of post-transplant survival times.

High emergency organ allocation is an effective strategy to reduce mortality on the waiting list, but causes a disruption of the list equilibrium that may have detrimental long-term effects in situations of significant organ scarcity.

High emergency organ allocation is effective to reduce waiting list mortality when organ supply is sufficienthttp://ow.ly/KD1930fPs8I

Universal or targeted approach to prevent the transmission of extended-spectrum beta-lactamase-producing Enterobacteriaceae in intensive care units: a cost-effectiveness analysis

OBJECTIVE

Several control strategies have been used to limit the transmission of multidrug-resistant organisms in hospitals. However, their implementation is expensive and effectiveness of interventions for the control of extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-PE) spread is controversial. Here, we aim to assess the cost-effectiveness of hospital-based strategies to prevent ESBL-PE transmission and infections.

DESIGN

Cost-effectiveness analysis based on dynamic, stochastic transmission model over a 1-year time horizon.

PATIENTS AND SETTING

Patients hospitalised in a hypothetical 10-bed intensive care unit (ICU) in a high-income country.

INTERVENTIONS

Base case scenario compared with (1) universal strategies (eg, improvement of hand hygiene (HH) among healthcare workers, antibiotic stewardship), (2) targeted strategies (eg, screening of patient for ESBL-PE at ICU admission and contact precautions or cohorting of carriers) and (3) mixed strategies (eg, targeted approaches combined with antibiotic stewardship).

MAIN OUTCOMES AND MEASURES

Cases of ESBL-PE transmission, infections, cost of intervention, cost of infections, incremental cost per infection avoided.

RESULTS

In the base case scenario, 15 transmissions and five infections due to ESBL-PE occurred per 100 ICU admissions, representing a mean cost of €94 792. All control strategies improved health outcomes and reduced costs associated with ESBL-PE infections. The overall costs (cost of intervention and infections) were the lowest for HH compliance improvement from 55%/60% before/after contact with a patient to 80%/80%.

CONCLUSIONS

Improved compliance with HH was the most cost-saving strategy to prevent the transmission of ESBL-PE. Antibiotic stewardship was not cost-effective. However, adding antibiotic restriction strategy to HH or screening and cohorting strategies slightly improved their effectiveness and may be worthy of consideration by decision-makers.

Role of DNA methylation at the placental RTL1 gene locus in type 1 diabetes

Genome-wide association studies (GWAS) have identified more than 40 T1D loci associated with type 1 diabetes (T1D). How these polymorphisms interact with environmental factors to trigger T1D is unknown, but recent evidence suggests that epigenetic mechanisms could play a role. To begin to explore the contribution of epigenetics to T1D, we have examined DNA methylation in a pilot study of whole blood cells DNA from 10 young T1D patients and 10 young controls. Through the study of >900 000 CG loci across a diverse set of functionally relevant genomic regions using a custom DNA methylation array, we identified 250 T1D-differentially methylated region (DMR) at p < 0.05 and 1 DMR using next a permutation-based multiple testing correction method. This DMR is located in an imprinted region previously associated with T1D on the chromosome 14 that encompasses RTL1 gene and 2 miRNAs (miR136 and miR432). Using pyrosequencing-based bisulfite PCR, we replicated this association in a different and larger set of T1D patients and controls. DNA methylation at this DMR was inversely correlated with RTL1 gene expression and positively correlated with miR136 expression in human placentas. The DMR identified in this study presents suggestive evidence for altered methylation site in T1D and provide a promising new candidate gene. RTL1 is essential for placental permeability function in the mid-to-late fetal stages. We suggest that hypo-methylation could increase the fetal exposure to environmental factors in T1D susceptibility.

Automated detection of hospital outbreaks: A systematic review of methods

OBJECTIVES

Several automated algorithms for epidemiological surveillance in hospitals have been proposed. However, the usefulness of these methods to detect nosocomial outbreaks remains unclear. The goal of this review was to describe outbreak detection algorithms that have been tested within hospitals, consider how they were evaluated, and synthesize their results.

METHODS

We developed a search query using keywords associated with hospital outbreak detection and searched the MEDLINE database. To ensure the highest sensitivity, no limitations were initially imposed on publication languages and dates, although we subsequently excluded studies published before 2000. Every study that described a method to detect outbreaks within hospitals was included, without any exclusion based on study design. Additional studies were identified through citations in retrieved studies.

RESULTS

Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). The evaluation of the algorithms was often solely descriptive (n = 15), but more complex epidemiological criteria were also investigated (n = 10). The performance measures varied widely between studies: e.g., the sensitivity of an algorithm in a real world setting could vary between 17 and 100%.

CONCLUSION

Even if outbreak detection algorithms are useful complementary tools for traditional surveillance, the heterogeneity in results among published studies does not support quantitative synthesis of their performance. A standardized framework should be followed when evaluating outbreak detection methods to allow comparison of algorithms across studies and synthesis of results.