A global federated real-world data and analytics platform for research.

Objective: This article describes a scalable, performant, sustainable global network of electronic health record data for biomedical and clinical research. Materials and Methods: TriNetX has created a technology platform characterized by a conservative security and governance model that facilitates collaboration and cooperation between industry participants, such as pharmaceutical companies and contract research organizations, and academic and community-based healthcare organizations (HCOs). HCOs participate on the network in return for access to a suite of analytics capabilities, large networks of de-identified data, and more sponsored trial opportunities. Industry participants provide the financial resources to support, expand, and improve the technology platform in return for access to network data, which provides increased efficiencies in clinical trial design and deployment. Results: TriNetX is a growing global network, expanding from 55 HCOs and 7 countries in 2017 to over 220 HCOs and 30 countries in 2022. Over 19 000 sponsored clinical trial opportunities have been initiated through the TriNetX network. There have been over 350 peer-reviewed scientific publications based on the network's data. Conclusions: The continued growth of the TriNetX network and its yield of clinical trial collaborations and published studies indicates that this academic-industry structure is a safe, proven, sustainable path for building and maintaining research-centric data networks.

Vaccine allocation policy optimization and budget sharing mechanism using reinforcement learning

The optimal allocation of vaccines to population subgroups over time is a challenging health care management problem. In the context of a pandemic, the interaction between vaccination policies adopted by multiple agents and the cooperation (or lack thereof) creates a complex environment that affects the global transmission dynamics of the disease. In this study, we take the perspective of decision-making agents that aim to minimize the size of their susceptible populations and must allocate vaccine under limited supply. We assume that vaccine efficiency rates are unknown to agents and we propose a reinforcement learning approach based on Thompson sampling to learn mean vaccine efficiency rates over time. Furthermore, we develop a budget-balanced resource sharing mechanism to promote cooperation among agents. We apply the proposed framework to the COVID-19 pandemic. We use a raster model of the world where agents represent the main countries worldwide and interact in a global mobility network to generate multiple problem instances. Our numerical results show that the proposed vaccine allocation policy achieves a larger reduction in the number of susceptible individuals, infections and deaths globally compared to a population-based policy. In addition, we show that, under a fixed global vaccine allocation budget, most countries can reduce their national number of infections and deaths by sharing their budget with countries with which they have a relatively high mobility exchange. The proposed framework can be used to improve policy-making in health care management by national and global health authorities.

Building an i2b2-Based Population Repository for COVID-19 Research.

Reuse of Electronic Health Records (EHRs) for specific diseases such as COVID-19 requires data to be recorded and persisted according to international standards. Since the beginning of the COVID-19 pandemic, Hospital Universitario 12 de Octubre (H12O) evolved its EHRs: it identified, modeled and standardized the concepts related to this new disease in an agile, flexible and staged way. Thus, data from more than 200,000 COVID-19 cases were extracted, transformed, and loaded into an i2b2 repository. This effort allowed H12O to share data with worldwide networks such as the TriNetX platform and the 4CE Consortium.

Le déconfinement de 2020 s’est-il accompagné d’un effet « boom » des infections sexuellement transmissibles ?

Introduction Le confinement strict de mars 2020, visant à contenir la pandémie de SARS-CoV-2, a réduit l’accès aux soins et les interactions sociales. Nous avons souhaité en étudier les conséquences sur l’incidence des infections sexuellement transmissibles (IST). Matériel et méthodes Étude rétrospective, multicentrique, des tests de dépistage du Chlamydia trachomatis (CT), du gonocoque (NG), de la syphilis, du VIH et du VHB réalisés dans les CeGIDD du Grand Est, entre le 18/03 et le 31/08/2020 avec analyse en 4 sous-périodes : confinement strict (18/03–10/05)/limitation des déplacements dans un périmètre de 100km (11/05–01/06)/1re partie des levées de restriction en juin (02/06–30/06)/2e partie en juillet–août (01/07–31/07), comparativement aux mêmes périodes de 2018 et 2019. Résultats Durant la période de confinement strict, le nombre de tests effectués était significativement réduit (–95 %) avec une incidence de chaque IST stable, avec des observations similaires pendant la période de déplacement restreint (baisse>50 % des dépistages totaux). Dès le mois de juin, alors que le nombre de tests effectués devenait comparable à celui des années antérieures, on commençait à noter une hausse significative des infections à CT de +8 % et +20 % comparativement à juin 2019 et 2018, alors que l’incidence des autres IST restait alors constante. En juillet–août, l’incidence globale des IST était de +25 % et de +21 %, avec majoration des infections à CT de +46 % et de +56 % par rapport à 2019 et 2018, respectivement. Discussion Nous rapportons ici une augmentation de l’incidence globale des IST durant l’été 2020 dans la région Grand Est, comparativement à l’été 2019 et 2018, marquée surtout par une hausse de l’incidence des cas de CT, suggérant un impact des mesures sanitaires sur le comportement sexuel de la population étudiée. Deux études rétrospectives européennes ont également montré cette tendance à la baisse des tests totaux de dépistages des IST en 2020, avec hausse des cas de CT une fois les restrictions sanitaires levées. Cette recrudescence des cas de CT et son observation précoce dès le déconfinement pourraient suggérer, du fait de l’accessibilité réduite aux CeGIDD pendant le confinement et du caractère principalement asymptomatique des infections à CT, que le comportement des jeunes sexuellement actifs n’ait pas été restreint par le confinement, voire au contraire s’est libéré, comme par opposition à la restriction des libertés. Conclusion Le déconfinement s’est accompagné d’une augmentation d’incidence des IST, que l’on pourrait décrire comme un « IST-boom » durant l’été 2020. Il est important que la communauté médicale en soit informée, notamment pour les IST asymptomatiques, Chlamydia trachomatis en premier lieu, ayant possiblement échappé aux dépistages et qui sont actuellement latentes.

Sex Differences in the Evolution of Neutralizing Antibodies to Severe Acute Respiratory Syndrome Coronavirus 2.

We measured anti-spike (S), nucleoprotein (N), and neutralizing antibodies in sera from 308 healthcare workers with a positive reverse-transcription quantitative polymerase chain reaction result for severe acute respiratory syndrome coronavirus 2 and with mild disease, collected at 2 timepoints up to 6 months after symptom onset. At month 1, anti-S and -N antibody levels were higher in male participants aged >50 years and participants with a body mass index (BMI) >25 kg/m2. At months 3-6, anti-S and anti-N antibodies were detected in 99% and 59% of individuals, respectively. Anti-S antibodies and neutralizing antibodies declined faster in men than in women, independent of age and BMI, suggesting an association of sex with evolution of the humoral response.

Evolution of antibody responses up to 13 months after SARS-CoV-2 infection and risk of reinfection.

BACKGROUND: Assessment of the kinetics of SARS-CoV-2 antibodies is essential in predicting risk of reinfection and durability of vaccine protection. METHODS: This is a prospective, monocentric, longitudinal, cohort clinical study. Healthcare workers (HCW) from Strasbourg University Hospital were enrolled between April 6th and May 7th, 2020 and followed up to 422 days. Serial serum samples were tested for antibodies against the Receptor Binding Domain (RBD) of the spike protein and nucleocapsid protein (N) to characterize the kinetics of SARS-CoV-2 antibodies and the incidence of reinfection. Live-neutralization assays were performed for a subset of samples before and after vaccination to analyze sensitivity to SARS-CoV-2 variants. FINDINGS: A total of 4290 samples from 393 convalescent COVID-19 and 916 COVID-19 negative individuals were analyzed. In convalescent individuals, SARS-CoV-2 antibodies followed a triphasic kinetic model with half-lives at month (M) 11-13 of 283 days (95% CI 231-349) for anti-N and 725 days (95% CI 623-921) for anti-RBD IgG, which stabilized at a median of 1.54 log BAU/mL (95% CI 1.42-1.67). The incidence of SARS-CoV-2 infections was 12.22 and 0.40 per 100 person-years in COVID-19-negative and COVID-19-positive HCW, respectively, indicating a relative reduction in the incidence of SARS-CoV-2 reinfection of 96.7%. Live-virus neutralization assay revealed that after one year, variants D614G and B.1.1.7, but less so B.1.351, were sensitive to anti-RBD antibodies at 1.4 log BAU/mL, while IgG ≥ 2.0 log BAU/mL strongly neutralized all three variants. These latter anti-RBD IgG titers were reached by all vaccinated HCW regardless of pre-vaccination IgG levels and type of vaccine. INTERPRETATION: Our study demonstrates a long-term persistence of anti-RBD antibodies that may reduce risk of reinfection. By significantly increasing cross-neutralizing antibody titers, a single-dose vaccination strengthens protection against variants. FUN1DING: None.

Severe COVID-19 Patients Show an Increase in Soluble TNFR1 and ADAM17, with a Relationship to Mortality.

Overproduction of inflammatory cytokines is a keystone event in COVID-19 pathogenesis; TNF and its receptors (TNFR1 and TNFR2) are critical pro-inflammatory molecules. ADAM17 releases the soluble (sol) forms of TNF, TNFR1, and TNFR2. This study evaluated TNF, TNFRs, and ADAM17 at the protein, transcriptional, and gene levels in COVID-19 patients with different levels of disease severity. In total, 102 patients were divided into mild, moderate, and severe condition groups. A group of healthy donors (HD; n = 25) was included. Our data showed that solTNFR1 and solTNFR2 were elevated among the COVID-19 patients (p < 0.0001), without increasing the transcriptional level. Only solTNFR1 was higher in the severe group as compared to the mildly ill (p < 0.01), and the level was higher in COVID-19 patients who died than those that survived (p < 0.0001). The solTNFR1 level had a discrete negative correlation with C-reactive protein (p = 0.006, Rho = -0.33). The solADAM17 level was higher in severe as compared to mild disease conditions (p < 0.01), as well as in COVID-19 patients who died as compared to those that survived (p < 0.001). Additionally, a potential association between polymorphism TNFRSF1A:rs767455 and a severe degree of disease was suggested. These data suggest that solTNFR1 and solADAM17 are increased in severe conditions. solTNFR1 should be considered a potential target in the development of new therapeutic options.

Serologic responses to SARS-CoV-2 infection among hospital staff with mild disease in eastern France.

BACKGROUND: The serologic response of individuals with mild forms of SARS-CoV-2 infection is poorly characterized. METHODS: Hospital staff who had recovered from mild forms of PCR-confirmed SARS-CoV-2 infection were tested for anti-SARS-CoV-2 antibodies using two assays: a rapid immunodiagnostic test (99.4% specificity) and the S-Flow assay (~99% specificity). The neutralizing activity of the sera was tested with a pseudovirus-based assay. FINDINGS: Of 162 hospital staff who participated in the investigation, 160 reported SARS-CoV-2 infection that had not required hospital admission and were included in these analyses. The median time from symptom onset to blood sample collection was 24 days (IQR: 21-28, range 13-39). The rapid immunodiagnostic test detected antibodies in 153 (95.6%) of the samples and the S-Flow assay in 159 (99.4%), failing to detect antibodies in one sample collected 18 days after symptom onset (the rapid test did not detect antibodies in that patient). Neutralizing antibodies (NAbs) were detected in 79%, 92% and 98% of samples collected 13-20, 21-27 and 28-41 days after symptom onset, respectively (P = 0.02). INTERPRETATION: Antibodies against SARS-CoV-2 were detected in virtually all hospital staff sampled from 13 days after the onset of COVID-19 symptoms. This finding supports the use of serologic testing for the diagnosis of individuals who have recovered from SARS-CoV-2 infection. The neutralizing activity of the antibodies increased overtime. Future studies will help assess the persistence of the humoral response and its associated neutralization capacity in recovered patients. FUNDINGS: The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.