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.
Moritz U. G. Kraemer; Chia-Hung Yang; Bernardo Gutierrez; Chieh-Hsi Wu; Brennan Klein; David M. Pigott; Louis du Plessis; Nuno R. Faria; Ruoran Li; William P. Hanage; +7 more
Moritz U. G. Kraemer; Chia-Hung Yang; Bernardo Gutierrez; Chieh-Hsi Wu; Brennan Klein; David M. Pigott; Louis du Plessis; Nuno R. Faria; Ruoran Li; William P. Hanage; John S. Brownstein; Maylis Layan; Alessandro Vespignani; Huaiyu Tian; Christopher Dye; Oliver G. Pybus; Samuel V. Scarpino;
Countries: United Kingdom, France, United Kingdom, United Kingdom, United Kingdom, United Kingdom, United Kingdom
Project: NIH | MIDAS Center for Communic... (1U54GM088558-01), NIH | MIDAS Center for Communic... (1U54GM088558-01)
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.
AbstractBackgroundCOVID-19 is spreading rapidly in nursing homes (NHs). It is urgent to evaluate the effect of infection prevention and control (IPC) measures to reduce COVID spreading.MethodsWe analysed COVID-19 outbreaks in 12 NH using rRT-PCR for SARS-CoV-2. We estimated secondary attack risks (SARs) and identified cofactors associated with the proportion of infected residents.ResultsThe SAR was below 5%, suggesting a high efficiency of IPC measures. Mask-wearing or establishment of COVID-19 zones for infected residents were associated with lower SAR.ConclusionsWearing masks and isolating potentially infected residents appear to limit SARS-CoV-2 spread in nursing homes.
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.
International audience; Estimation of dynamical systems - in particular, identification of their parameters - is fundamental in computational biology, e.g., pharmacology, virology, or epidemiology, to reconcile model runs with available measurements. Unfortunately, the mean and variance priorities of the parameters must be chosen very appropriately to balance our distrust of the measurements when the data are sparse or corrupted by noise. Otherwise, the identification procedure fails. One option is to use repeated measurements collected in configurations with common priorities - for example, with multiple subjects in a clinical trial or clusters in an epidemiological investigation. This shared information is beneficial and is typically modeled in statistics using nonlinear mixed-effects models. In this paper, we present a data assimilation method that is compatible with such a mixed-effects strategy without being compromised by the potential curse of dimensionality. We define population-based estimators through maximum likelihood estimation. We then develop an equivalent robust sequential estimator for large populations based on filtering theory that sequentially integrates data. Finally, we limit the computational complexity by defining a reduced-order version of this population-based Kalman filter that clusters subpopulations with common observational backgrounds. The performance of the resulting algorithm is evaluated against classical pharmacokinetics benchmarks. Finally, the versatility of the proposed method is tested in an epidemiological study using real data on the hospitalisation of COVID-19 patients in the regions and departments of France.
Understanding the pathogenesis of the SARS-CoV-2 infection is key to developing preventive and therapeutic strategies against COVID-19, in the case of severe illness but also when the disease is mild. The use of appropriate experimental animal models remains central in the in vivo exploration of the physiopathology of infection and antiviral strategies. This study describes SARS-CoV-2 intranasal infection in ferrets and hamsters with low doses of low-passage SARS-CoV-2 clinical French isolate UCN19, describing infection levels, excretion, immune responses and pathological patterns in both animal species. Individual infection with 103 p.f.u. SARS-CoV-2 induced a more severe disease in hamsters than in ferrets. Viral RNA was detected in the lungs of hamsters but not of ferrets and in the brain (olfactory bulb and/or medulla oblongata) of both species. Overall, the clinical disease remained mild, with serological responses detected from 7 days and 10 days post-inoculation in hamsters and ferrets respectively. The virus became undetectable and pathology resolved within 14 days. The kinetics and levels of infection can be used in ferrets and hamsters as experimental models for understanding the pathogenicity of SARS-CoV-2, and testing the protective effect of drugs.
Alice Mac Kain; Ghizlane Maarifi; Sophie-Marie Aicher; Nathalie J. Arhel; Artem Baidaliuk; Thomas Vallet; Quang Dinh Tran; Alexandra Hardy; Maxime Chazal; Françoise Porrot; +11 more
Alice Mac Kain; Ghizlane Maarifi; Sophie-Marie Aicher; Nathalie J. Arhel; Artem Baidaliuk; Thomas Vallet; Quang Dinh Tran; Alexandra Hardy; Maxime Chazal; Françoise Porrot; Molly OhAinle; Jared Carlson-Stevermer; Jennifer Oki; Kevin Holden; Etienne Simon-Loriere; Timothée Bruel; Olivier Schwartz; Nolwenn Jouvenet; Sébastien Nisole; Marco Vignuzzi; Ferdinand Roesch;
AbstractInterferon restricts SARS-CoV-2 replication in cell culture, but only a handful of Interferon Stimulated Genes with antiviral activity against SARS-CoV-2 have been identified. Here, we describe a functional CRISPR/Cas9 screen aiming at identifying SARS-CoV-2 restriction factors. We identified DAXX, a scaffold protein residing in PML nuclear bodies known to limit the replication of DNA viruses and retroviruses, as a potent inhibitor of SARS-CoV-2 and SARS-CoV replication in human cells. Basal expression of DAXX was sufficient to limit the replication of SARS-CoV-2, and DAXX over-expression further restricted infection. In contrast with most of its previously described antiviral activities, DAXX-mediated restriction of SARS-CoV-2 was independent of the SUMOylation pathway. SARS-CoV-2 infection triggered the re-localization of DAXX to cytoplasmic sites and promoted its degradation. Mechanistically, this process was mediated by the viral papain-like protease (PLpro) and the proteasome. Together, these results demonstrate that DAXX restricts SARS-CoV-2, which in turn has evolved a mechanism to counteract its action.
From the beginning of the Covid-19 pandemic in France, many argued that now was the time for action, not ethics, while acknowledging the need for feedback once the crisis had passed. To this end, the Parisian clinical ethics’ center suggested that health professionals, patients, and families come back on difficulties or questions they might have had during the first national lockdown once it was over. We called it ethical debriefs. Between May and September 2021, 31 professionals agreed to participate, but only 1 patient (a retired physician) and no proxy was met. The aim of this article is to share how these health professionals revisited the first months of the crisis. Indeed today, more than one year since Covid started and as what was once unusual is becoming common practice, it is useful not to forget how they reacted, what their questions were and where did their ethical difficulties lie at that time. Now that coming back to normal might be conceivable, all these interviews highlight the importance of a questioning on what caring for patients means nowadays, as well as on the definition of role of medicine in a context of crisis.; Dès les premières semaines de l’épidémie de la Covid-19, en France, plusieurs voix se sont levées pour dire que l’heure n’était pas à la réflexion éthique, mais à l’action, en soulignant néanmoins l’importance d’un retour d’expérience à l’issue de l’urgence. Dans cette visée, le Centre d’éthique clinique de l’AP-HP a proposé, dès la fin du 1er confinement national, à des soignants, comme à des patients ou à des proches, de revenir, s’ils le souhaitaient, sur les questionnements ou les difficultés éthiques rencontrées pendant cette période (ce qu’il a appelé des « relectures éthiques »). Entre mai et septembre 2020, 31 professionnels y ont participé, 1 seul patient (médecin à la retraite) a été rencontré et aucun proche. Cet article souhaite partager la façon dont ces professionnels sont revenus, dans l’après-coup, sur les premiers mois de la crise. Plus d’une année plus tard, à l’heure où ce qui était « inhabituel » commence par devenir « ordinaire », et le « retour à la vie normale » semble à l’horizon, il n’est pas inutile de rappeler leurs réactions, leurs interrogations et leurs malaises. Au croisement des entretiens, c’est un questionnement quant à ce que soigner veut dire aujourd’hui et au rôle de la médecine en contexte de crise que l’on voit émerger.
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.