• COVID-19
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AbstractIn the spreading of infectious diseases, an important number to determine is how many other people will be infected on average by anyone who has become infected themselves. This is known as the reproduction number. This paper describes a non-parametric inverse method for extracting the full transfer function of infection, of which the reproduction number is the integral. The method is demonstrated by applying it to the timeline of hospitalisation admissions for covid-19 in the Netherlands up to May 20 2020, which is publicly available from the site of the Dutch National Institute of Public Health and the Environment (rivm.nl).

Abstract Background Coronaviruses pose a serious threat to global health as evidenced by Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and COVID-19. SARS Coronavirus (SARS-CoV), MERS Coronavirus (MERS-CoV), and the novel coronavirus, previously dubbed 2019-nCoV, and now officially named SARS-CoV-2, are the causative agents of the SARS, MERS, and COVID-19 disease outbreaks, respectively. Safe vaccines that rapidly induce potent and long-lasting virus-specific immune responses against these infectious agents are urgently needed. The coronavirus spike (S) protein, a characteristic structural component of the viral envelope, is considered a key target for vaccines for the prevention of coronavirus infection. Methods We first generated codon optimized MERS-S1 subunit vaccines fused with a foldon trimerization domain to mimic the native viral structure. In variant constructs, we engineered immune stimulants (RS09 or flagellin, as TLR4 or TLR5 agonists, respectively) into this trimeric design. We comprehensively tested the pre-clinical immunogenicity of MERS-CoV vaccines in mice when delivered subcutaneously by traditional needle injection, or intracutaneously by dissolving microneedle arrays (MNAs) by evaluating virus specific IgG antibodies in the serum of vaccinated mice by ELISA and using virus neutralization assays. Driven by the urgent need for COVID-19 vaccines, we utilized this strategy to rapidly develop MNA SARS-CoV-2 subunit vaccines and tested their pre-clinical immunogenicity in vivo by exploiting our substantial experience with MNA MERS-CoV vaccines. Findings Here we describe the development of MNA delivered MERS-CoV vaccines and their pre-clinical immunogenicity. Specifically, MNA delivered MERS-S1 subunit vaccines elicited strong and long-lasting antigen-specific antibody responses. Building on our ongoing efforts to develop MERS-CoV vaccines, promising immunogenicity of MNA-delivered MERS-CoV vaccines, and our experience with MNA fabrication and delivery, including clinical trials, we rapidly designed and produced clinically-translatable MNA SARS-CoV-2 subunit vaccines within 4 weeks of the identification of the SARS-CoV-2 S1 sequence. Most importantly, these MNA delivered SARS-CoV-2 S1 subunit vaccines elicited potent antigen-specific antibody responses that were evident beginning 2 weeks after immunization. Interpretation MNA delivery of coronaviruses-S1 subunit vaccines is a promising immunization strategy against coronavirus infection. Progressive scientific and technological efforts enable quicker responses to emerging pandemics. Our ongoing efforts to develop MNA-MERS-S1 subunit vaccines enabled us to rapidly design and produce MNA SARS-CoV-2 subunit vaccines capable of inducing potent virus-specific antibody responses. Collectively, our results support the clinical development of MNA delivered recombinant protein subunit vaccines against SARS, MERS, COVID-19, and other emerging infectious diseases.

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.

Psychiatric patients are at high risk for contracting COVID-19, and inpatient psychiatric units face substantial risks of institutional outbreaks. Here, the authors describe an algorithm for testing and triage in a large psychiatric facility designed to prevent local COVID-19 transmission. The algorithm is based on expert opinion and clinical experience between March and April of 2020, during which the institution cared for 47 COVID-19 positive psychiatric inpatients. The implementation of the algorithm is designed to mitigate COVID-19 transmission, preserve the safest and least restrictive treatment environment for psychiatric inpatients, and provide a model adaptable to other institutional settings.

Previous meta-analyses were conducted during the initial phases of the COVID-19 pandemic, which utilized a smaller pool of data. The current meta-analysis aims to provide additional (and updated) evidence related to the psychological impact among healthcare workers. The search strategy was developed by a medical librarian and bibliographical databases, including Medline, Embase, CINAHL, PsycINFO, and Scopus were searched for studies examining the impact of the COVID-19 pandemic on the psychological health of healthcare workers. Articles were screened by three reviewers. Heterogeneity among studies was assessed by I2 statistic. The random-effects model was utilized to obtain the pooled prevalence. A subgroup analysis by region, gender, quality of study, assessment methods, healthcare profession, and exposure was performed. Publication bias was assessed by Funnel plot and Egger linear regression test. Sixty-five studies met the inclusion criteria and the total sample constituted 79,437 participants. The pooled prevalence of anxiety, depression, stress, post-traumatic stress syndrome, insomnia, psychological distress, and burnout was 34.4%, 31.8%, 40.3%, 11.4%, 27.8%, 46.1%, and 37.4% respectively. The subgroup analysis indicated higher anxiety and depression prevalence among females, nurses, and frontline responders than males, doctors, and second-line healthcare workers. This study highlights the need for designing a targeted intervention to improve resilience and foster post-traumatic growth among frontline responders.

Surveying large swaths of the public for antibodies to the new coronavirus promises to show how widespread undiagnosed infections are, how deadly the virus really is, and whether enough of the population has become immune for social distancing measures to be eased But the first batch of results has generated more controversy than clarity The survey results, from Germany, the Netherlands, and several locations in the United States, find that anywhere from 2% to 30% of certain populations have already been infected with the virus The numbers imply that confirmed COVID-19 cases are an even smaller fraction of the true number of people infected than many had estimated and that the vast majority of infections are mild But many scientists question the accuracy of the antibody tests and complain that several of the research groups announced their findings in the press rather than in preprints or published papers, where their data could be scrutinized Critics are also wary because some of the researchers are on record advocating for an early end to lockdowns and other control measures, and claim the new prevalence figures support that call

Background: This is the first phylodynamic study attempted on SARS-CoV-2 genomes from India to infer the current state of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution using phylogenetic network and growth trends. Materials & Methods: Out of 286 retrieved whole genomes from India, 138 haplotypes were used to build a phylogenetic network. The birth–death serial model (BDSIR) package of BEAST2 was used to calculate the reproduction number of SARS-CoV-2. Population dynamics were investigated using the stamp date method as implemented in BEAST2 and BEAST 1.10.4. Results: A median-joining network revealed two ancestral clusters. A high basic reproduction number of SARS-CoV-2 was found. An exponential rise in the effective population size of Indian isolates was detected. Conclusion: The phylogenetic network reveals dual ancestry and possibility of community transmission of SARS-CoV-2 in India.

The pandemic creates unprecedented challenges to society and to health care systems around the world. Like all crises, these provide a unique opportunity to rethink the fundamental limiting assumptions and institutional inertia of our established systems. These inertial assumptions have obscured deeply rooted problems in health care and deflected attempts to address them. As hospitals begin to welcome all patients back, they should resist the temptation to go back to business as usual. Instead, they should retain the more deliberative, explicit, and transparent ways of thinking that have informed the development of crisis standards of care. The key lesson to be learned from those exercises in rational deliberation is that justice must be the ethical foundation of all standards of care. Justice demands that hospitals take a safety-net approach to providing services that prioritizes the most vulnerable segments of society, continue to expand telemedicine in ways that improve access without exacerbating disparities, invest in community-based care, and fully staff hospitals and clinics on nights and weekends.