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On both sides of the Atlantic, in Anglo-Saxon countries, the issue of excess mortality due to Covid-19 among members of minorities has emerged as a central social justice issue. Outside the Anglo-Saxon countries, where race and ethnicity are generally recorded, it is difficult to address this issue. However, in France, data for the period up to the end of confinement, mentioning country of birth and place of death, from "état-civil" files, allow comparisons to be made on the determinants of the severity of Covid-19 integrating ethnicity. Regression analyses based on the difference in death counts between the spring of 2020 and the same period of previous years, show that the interweaving of health status, household size and ethnicity accurately reflects the disparities between departmental mortality rates due to Covid-19. People born in Black Africa clearly appear to be in a worse position than those born in the Maghreb, in Asian and European countries, not to mention the natives, in terms of risk of death.

The ongoing COVID-19 outbreak has expanded rapidly throughout China. Major behavioral, clinical, and state interventions are underway currently to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, have affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was well explained by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases are still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China have substantially mitigated the spread of COVID-19. One sentence summary: The spread of COVID-19 in China was driven by human mobility early on and mitigated substantially by drastic control measures implemented since the end of January.

The European response to COVID-19 has revealed an inconvenient truth. Despite having integrated public health concerns across all its policies – be it agriculture, consumer protection, or security –, the Union cannot directly act to save people’s lives. Only member states can do so. Yet when they adopted unilateral measures to counter the spread of the virus, those proved not only ineffective but also disruptive on vital supply chains, by ultimately preventing the flow of essential goods and people across the Union. These fragmented efforts in tackling cross-border health threats have almost immediately prompted political calls for the urgent creation of a European Health Union. Yet this call raises more questions than answers. With the aim to offer a rigorous and timely blueprint to decision-makers and the public at large, this Special Issue of the European Journal of Risk Regulation contextualizes such a new political project within the broader constitutional and institutional framework of EU public health law and policy. By introducing the Special, this paper argues that unless the envisaged Health Union will tackle the root causes of what prevented the Union from effectively responding to COVID-19 – the divergent health capacity across the Union –, it might fall short of its declared objective of strengthening the EU’resilience for cross-border health threats.

SARS-CoV-2 outbreak is the first pandemic of the century. SARS-CoV-2 infection is transmitted through droplets; other transmission routes are hypothesized but not confirmed. So far, it is unclear whether and how SARS-CoV-2 can be transmitted from the mother to the fetus. We demonstrate the transplacental transmission of SARS-CoV-2 in a neonate born to a mother infected in the last trimester and presenting with neurological compromise. The transmission is confirmed by comprehensive virological and pathological investigations. In detail, SARS-CoV-2 causes: (1) maternal viremia, (2) placental infection demonstrated by immunohistochemistry and very high viral load; placental inflammation, as shown by histological examination and immunohistochemistry, and (3) neonatal viremia following placental infection. The neonate is studied clinically, through imaging, and followed up. The neonate presented with neurological manifestations, similar to those described in adult patients. Congenital infection of SARS-CoV-2 has been described, but the transmission routes remain unclear. Here, the authors report evidence of transplacental transmission of SARS-CoV-2 in a neonate born to a mother infected in the last trimester and presenting with neurological compromise.

The first case of coronavirus disease 2019 (COVID-19) in Algeria was reported on 25 February 2020. Since then, it has progressed rapidly and the number of cases grow exponentially each day. In this article, we utilize SEIR modelling to forecast COVID-19 outbreak in Algeria under two scenarios by using the real-time data from March 01 to April 10, 2020. In the first scenario: no control measures are put into place, we estimate that the basic reproduction number for the epidemic in Algeria is 2.1, the number of new cases in Algeria will peak from around late May to early June and up to 82% of the Algerian population will likely contract the coronavirus. In the second scenario, at a certain date T, drastic control measures are taken, people are being advised to self-isolate or to quarantine and will be able to leave their homes only if necessary. We use SEIR model with fast change between fully protected and risky states. We prove that the final size of the epidemic depends strongly on the cumulative number of cases at the date when we implement intervention and on the fraction of the population in confinement. Our analysis shows that the longer we wait, the worse the situation will be and this very quickly produces.

AbstractBluetongue virus (BTV) is an arbovirus transmitted by blood-feeding midges to a wide range of wild and domestic ruminants. In this report, we showed that BTV, through its virulence non-structural protein NS3 (BTV-NS3), is able to activate the MAPK/ERK pathway. In response to growth factors, the MAPK/ERK pathway activates cell survival, differentiation, proliferation and protein translation but can also lead to the production of several inflammatory cytokines. By combining immunoprecipitation of BTV-NS3 and mass spectrometry analysis from both BTV-infected and NS3-transfected cells, we identified the serine/threonine-protein kinase B-Raf (BRAF), a crucial player of the MAPK/ERK pathway, as a new cellular interactor of BTV-NS3. BRAF silencing led to a significant decrease of the MAPK/ERK activation by BTV supporting a model where BTV-NS3 interacts with BRAF to activate this signaling cascade. Furthermore, the intrinsic ability of BTV-NS3 to bind BRAF and activate the MAPK/ERK pathway is conserved throughout multiple serotypes/strains but appears to be specific to BTV compared to other members ofOrbivirusgenus. Inhibition of MAPK/ERK pathway with U0126 reduced viral titers, suggesting that BTV manipulates this pathway for its own replication. Therefore, the activation of the MAPK/ERK pathway by BTV-NS3 could benefit to BTV replication by promoting its own viral protein synthesis but could also explain the deleterious inflammation associated with tissue damages as already observed in severe cases of BT disease. Altogether, our data provide molecular mechanisms to explain the role of BTV-NS3 as a virulence factor and determinant of pathogenesis.ImportanceBluetongue Virus (BTV) is responsible of the non-contagious arthropod-borne disease Bluetongue (BT) transmitted to ruminants by blood-feeding midges. Despite the fact that BTV has been extensively studied, we still have little understanding of the molecular determinants of BTV virulence. In this report, we found that the virulence protein NS3 interacts with BRAF, a key component of the MAPK/ERK pathway. In response to growth factors, this pathway promotes cell survival, increases protein translation but also contributes to the production of inflammatory cytokines. We showed that BTV-NS3 enhances the MAPK/ERK pathway and this activation is BRAF-dependent. Our results demonstrate, at the molecular level, how a single virulence factor has evolved to target a cellular function to ensure its viral replication. On the other hand, our findings could also explain the deleterious inflammation associated with tissue damages as already observed in severe cases of BT disease.

Monitoring the Covid19 pandemic constitutes a critical societal stake that received considerable research efforts. The intensity of the pandemic on a given territory is efficiently measured by the reproduction number, quantifying the rate of growth of daily new infections. Recently, estimates for the time evolution of the reproduction number were produced using an inverse problem formulation with a nonsmooth functional minimization. While it was designed to be robust to the limited quality of the Covid19 data (outliers, missing counts), the procedure lacks the ability to output credibility interval based estimates. This remains a severe limitation for practical use in actual pandemic monitoring by epidemiologists that the present work aims to overcome by use of Monte Carlo sampling. After interpretation of the nonsmooth functional into a Bayesian framework, several sampling schemes are tailored to adjust the nonsmooth nature of the resulting posterior distribution. The originality of the devised algorithms stems from combining a Langevin Monte Carlo sampling scheme with Proximal operators. Performance of the new algorithms in producing relevant credibility intervals for the reproduction number estimates and denoised counts are compared. Assessment is conducted on real daily new infection counts made available by the Johns Hopkins University. The interest of the devised monitoring tools are illustrated on Covid19 data from several different countries.

The model descibes the epidemic dynamics of Covid-19 in a population after vaccination. Using the maximum principale, our goal is to prove the existence of an optimal strategy such that it minimize the number of infected people after vaccination. Finally, some numerical results are provided.