Cofilin, an intracellular marker for HIV-associated CD4 T-cell motility dysregulation, shed light on the mechanisms of incomplete immune reconstitution in the patients with HIV

Modeling SARS-CoV-2 and HBV co-dynamics with optimal control

Clinical reports have shown that chronic hepatitis B virus (HBV) patients co-infected with SARS-CoV-2 have a higher risk of complications with liver disease than patients without SARS-CoV-2. In this work, a co-dynamical model is designed for SARS-CoV-2 and HBV which incorporates incident infection with the dual diseases. Existence of boundary and co-existence endemic equilibria are proved. The occurrence of backward bifurcation, in the absence and presence of incident co-infection, is investigated through the proposed model. It is noted that in the absence of incident co-infection, backward bifurcation is not observed in the model. However, incident co-infection triggers this phenomenon. For a special case of the study, the disease free and endemic equilibria are shown to be globally asymptotically stable. To contain the spread of both infections in case of an endemic situation, the time dependent controls are incorporated in the model. Also, global sensitivity analysis is carried out by using appropriate ranges of the parameter values which helps to assess their level of sensitivity with reference to the reproduction numbers and the infected components of the model. Finally, numerical assessment of the control system using various intervention strategies is performed, and reached at the conclusion that enhanced preventive efforts against incident co-infection could remarkably control the co-circulation of both SARS-CoV-2 and HBV.

COVID-19 Case Fatality Rate and Factors Contributing to Mortality in Ethiopia: A Systematic Review of Current Evidence

Background

The ongoing novel coronavirus disease 2019 (COVID-19) is triggering significant morbidity and mortality due to its contagious nature and absence of definitive management. In Ethiopia, despite a number of primary studies have been conducted to estimate the case fatality rate (CFR) of COVID-19, no review study has attempted to summarize the findings to better understand the nature of pandemics and the virulence of the disease.

Objective

To summarize the CFR of COVID-19 and factors contributing to mortality in Ethiopia.

Methods

PRISMA guideline was followed. PubMed, Science Direct, CINAHL, SCOPUS, Hinari, and Google Scholar were systematically searched using pre-specified keywords. Observational studies ie, cohort, cross-sectional, and case-control studies were included. The Newcastle-Ottawa scale adapted for observational studies was used to assess the quality of included studies. CFR was defined as the proportion of COVID-19 cases with the outcome of death within a given period. Factors contributing to COVID-19 mortality at p-value <0.05 were described narratively from the eligible articles.

Results

A total of 13 observational studies were included in this study. Consequently, this review confirmed the CFR of COVID-19 in Ethiopia ranges between 1–20%. Additionally, comorbid conditions, older age group, male sex, substance use, clinical manifestations (abnormal oxygen saturation level, atypical lymphocyte count, fever, and shortness of breath), disease severity, and history of surgery/trauma increased the likelihood of death from COVID-19 death.

Conclusion

This study shows that the range of CFR of COVID-19 in Ethiopia is almost equivalent to other countries, despite the country’s low testing capacity and case detection rate in reference to its total population. Comorbid diseases, older age group, male sex, cigarette smoking, alcohol drinking, clinical manifestations and disease severity, and history of surgery/trauma were factors contributing to COVID-19 mortality in Ethiopia. Therefore, given the alarming global situation and rapidly evolving large-scale pandemics, urgent interdisciplinary interventions should be implemented in those vulnerable groups to lessen the risk of mortality. Furthermore, the CFR of COVID-19 should be estimated from all treatment and rehabilitation centers in the country, as underestimation could be linked to a lack of preparedness and mitigation. A large set of prospective studies are also compulsory to better understand the CFR of COVID-19 in Ethiopia.

The influence of mask use on the spread of COVID-19 during pandemic in New York City

In New York City, the situation of COVID-19 is so serious that it has caused hundreds of thousands of people to be infected due to its strong infectivity. The desired effect of wearing masks by the public is not ideal, though increasingly recommended by the WHO. In order to reveal the potential effect of mask use, we posed a dynamical model with the effective coverage of wearing face masks to assess the impact of mask use on the COVID-19 transmission. We obtained the basic reproduction number  R 0 which determined the global dynamics. According to the implement of policies in New York City, we divided the transmission of COVID-19 in three stages. Based on mathematical model and data, we obtain the mean value  R 0 = 1 . 822 in the first stage of New York City, while  R 0 = 0 . 6483 in the second stage due to that the US Centers for Disease Control and Prevention (CDC) recommended the public wear masks on April 3, 2020,  R 0 = 1 . 024 in the third stage after reopening. It was found that if the effective coverage rate of mask use  α exceed a certain value  α c = 0 . 182 , COVID-19 can be well controlled in the second stage of New York City. Additionally, when the effective coverage of masks reaches a certain level  α = 0 . 5 , the benefits are not obvious with the increased coverage rate compared to the cost of medical resources. Moreover, if the effective coverage of mask use in public reaches 20% in the first stage, then the cumulative confirmed cases will be reduced about 50% by 03 April, 2020. Our results demonstrated a new insight on the effect of mask use in controlling the transmission of COVID-19.

A New Scoring Model to Diagnose COVID-19 Using Lung Ultrasound in the Emergency Department

Background

Several studies have reported the predictors of the prognosis in COVID-19 patients; however, smoking, X-ray findings of pulmonary congestion, and A-profile and areas of consolidation in LUS are independent predictors for COVID-19 infection. The new score had a sensitivity of 93.8% and a specificity of 58% for the prediction of COVID-19. Mortality in COVID-19 patients is significantly correlated with age, fever duration, cardiac history, and B-profile and areas of consolidation in LUS. However, it is negatively correlated with initial O2 saturation and ejection fraction. This study aimed to design a new scoring model to diagnose COVID-19 using bedside lung ultrasound (LUS) in the emergency department (ED).

Results

Eighty-two patients were recruited. Fifty patients (61%) were negative for COVID-19, and 32 (39%) were positive. Sixty-four patients (78%) recovered while 18 patients (22%) died. COVID-19 patients had more AB-profile and more areas of consolidation than the non-COVID-19 group (p<0.001). Smoking, congestion in X-ray, A-profile, and abnormal A line in LUS are independent predictors for COVID-19 infection. The score had a sensitivity of 93.8% and a specificity of 58% for the prediction of COVID-19. Mortality in COVID-19 patients is significantly correlated with age, fever duration, cardiac history, and B-profile and areas of consolidation in LUS. However, it is negatively correlated with initial O2 saturation and ejection fraction.

Conclusions

In conclusion, the application of our new score can stratify patients presented to ED with suspected COVID-19 pneumonia, considering that it is a good negative test. Moreover, this score may have a good impact on the safety of medical personnel.

Trial registration

ClinicalTrials.gov Identifier: NCT05077202. Registered October 14, 2021 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT05077202

Global analysis of within-host SARS-CoV-2/HIV coinfection model with latency

The coronavirus disease 2019 (COVID-19) is a respiratory disease caused by a virus called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this paper, we analyze a within-host SARS-CoV-2/HIV coinfection model. The model is made up of eight ordinary differential equations. These equations describe the interactions between healthy epithelial cells, latently infected epithelial cells, productively infected epithelial cells, SARS-CoV-2 particles, healthy CD 4 + T cells, latently infected CD 4 + T cells, productively infected CD 4 + T cells, and HIV particles. We confirm that the solutions of the developed model are bounded and nonnegative. We calculate the different steady states of the model and derive their existence conditions. We choose appropriate Lyapunov functions to show the global stability of all steady states. We execute some numerical simulations to assist the theoretical contributions. Based on our results, weak CD 4 + T cell immunity in SARS-CoV-2/HIV coinfected patients causes an increase in the concentrations of productively infected epithelial cells and SARS-CoV-2 particles. This may lead to severe SARS-CoV-2 infection in HIV patients. This result agrees with many studies that discussed the high risk of severe infection and death in HIV patients when they get SARS-CoV-2 infection. On the other hand, increasing the death rate of infected epithelial cells during the latency period can reduce the severity of SARS-CoV-2 infection in HIV patients. More studies are needed to understand the dynamics of SARS-CoV-2/HIV coinfection and find better ways to treat this vulnerable group of patients.

SARS-CoV-2 Not Detectable in Ocular Specimens of a Patient with a Past Infection

Purpose: To present a a case study that aims to investigate the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the ocular tissue samples of a patient previously infected with COVID-19 and determine its transmissibility.Study Design: Case ReportResults: In this case study, SARS-CoV-2 was not detected in the vitreous and uveal tissue samples by RT-PCR for detection of three gene targets in a patient with a past COVID-19 infection 15 days prior to presention with a globe rupture.Conclusions: Our findings suggest that patients with long-term existence of SARS-CoV-2 at low detectable levels may not have active intraocular viral shedding. This is of particular importance as ophthalmic surgical procedures may potentiate virus spread from patients infected with SARS-CoV-2.

Clinical course of severe patients with COVID-19 treated with tocilizumab: report from a cohort study in Spain

Background: We report the long-term outcomes, changes in laboratory parameters, the incidence of secondary nosocomial infections and treatment cost of a Spanish cohort of patients with severe COVID-19 that received tocilizumab (TCZ).Methods: Retrospective cohort of PCR confirmed adult patients who received TCZ from March 1 to 24, 2020 in a tertiary hospital was analyzed. Patients were followed up until 10 May 2020.Results: We included 162 patients (median age 64 years; 70.4% male). At time of TCZ administration, 48.1% of patients were on invasive mechanical ventilation (IMV). Over a median follow-up of 53 days, 46.9% of patients were discharge in good conditions and 19.8% were still hospitalized. The overall mortality was 33.3%, being higher in patients on IMV than those who did not (46.2% vs 26.7%, P < 0.001). A significant improvement in the lymphocyte count, C-reactive protein, lactate dehydrogenase, and D-dimer was observed. Overall, 43.2% patients presented nosocomial infections, causing death in 8%. Infections were more prevalent in ICU units (63.0% vs 17.1%, P < 0.001). The total cost of TCZ was €371,784.Conclusions: Among the patients who used TCZ, one third died, regardless the improvement in some inflammatory biomarkers. The incidence of secondary nosocomial infections was high.

Visualizing the invisible: The effect of asymptomatic transmission on the outbreak dynamics of COVID-19

Understanding the outbreak dynamics of the COVID-19 pandemic has important implications for successful containment and mitigation strategies. Recent studies suggest that the population prevalence of SARS-CoV-2 antibodies, a proxy for the number of asymptomatic cases, could be an order of magnitude larger than expected from the number of reported symptomatic cases. Knowing the precise prevalence and contagiousness of asymptomatic transmission is critical to estimate the overall dimension and pandemic potential of COVID-19. However, at this stage, the effect of the asymptomatic population, its size, and its outbreak dynamics remain largely unknown. Here we use reported symptomatic case data in conjunction with antibody seroprevalence studies, a mathematical epidemiology model, and a Bayesian framework to infer the epidemiological characteristics of COVID-19. Our model computes, in real time, the time-varying contact rate of the outbreak, and projects the temporal evolution and credible intervals of the effective reproduction number and the symptomatic, asymptomatic, and recovered populations. Our study quantifies the sensitivity of the outbreak dynamics of COVID-19 to three parameters: the effective reproduction number, the ratio between the symptomatic and asymptomatic populations, and the infectious periods of both groups. For nine distinct locations, our model estimates the fraction of the population that has been infected and recovered by Jun 15, 2020 to 24.15% (95% CI: 20.48%-28.14%) for Heinsberg (NRW, Germany), 2.40% (95% CI: 2.09%-2.76%) for Ada County (ID, USA), 46.19% (95% CI: 45.81%-46.60%) for New York City (NY, USA), 11.26% (95% CI: 7.21%-16.03%) for Santa Clara County (CA, USA), 3.09% (95% CI: 2.27%-4.03%) for Denmark, 12.35% (95% CI: 10.03%-15.18%) for Geneva Canton (Switzerland), 5.24% (95% CI: 4.84%-5.70%) for the Netherlands, 1.53% (95% CI: 0.76%-2.62%) for Rio Grande do Sul (Brazil), and 5.32% (95% CI: 4.77%-5.93%) for Belgium. Our method traces the initial outbreak date in Santa Clara County back to January 20, 2020 (95% CI: December 29, 2019-February 13, 2020). Our results could significantly change our understanding and management of the COVID-19 pandemic: A large asymptomatic population will make isolation, containment, and tracing of individual cases challenging. Instead, managing community transmission through increasing population awareness, promoting physical distancing, and encouraging behavioral changes could become more relevant.

How should we understand the digital economy in Asia? Critical assessment and research agenda

By Asian digital economy, we refer to high-tech developments, business and social transformations, and information-driven changes in the region's growth. We discuss its background and foundations, significance in Asia and contribution to removal of historical barriers in traditional business. We assess how new value chains are transforming country-level involvement in worldwide manufacturing and note "smiling curve theory" predictions about the global value chain in Asia for high-tech firms and their economies. The takeaway is that the digital economy in Asian nations involves revamping business processes through technology innovation, government policies for growth, and digital entrepreneurship. We analyze the "digital economy and society index", and attributes of nations, societies and economies, as a basis for framing our ideas. We consider research directions prompted by data analytics and AI, the platform economy, digital trade, fintech innovation, and societal and economic sustainability. We further highlight new issues in light of the COVID-19 pandemic.

Treatment Armamentarium of COVID-19: Evolving Strategies and Evidence So Far

The outbreak of SARS-CoV-2 started in Hubei province of China in December 2019 and rapidly spread all over the world. It has infected more than 7 million people worldwide and has pushed half of the world in a state of lockdown. There is an urgent unmet need of interventions both for prevention and treatment of this disease and more than 500 clinical trials are ongoing in this regard. At present, no study with robust methodology have clearly demonstrated benefits of hydroxychloroquine for treatment, preexposure prophylaxis in healthcare workers or post exposure prophylaxis in COrona VIrus Disease-2019. Remdesivir has been shown to have modest benefits in moderate to severe disease, if administered early. Given the rapid pace of clinical information and discoveries, it is important for clinicians to be up to date with the latest, evidence-based treatment options available for this novel disease. Keeping up with this current pace of information, we review the clinical studies of different therapeutic options available to treat SARS-CoV-2.

Spatial analysis and GIS in the study of COVID-19. A review

This study entailed a review of 63 scientific articles on geospatial and spatial-statistical analysis of the geographical dimension of the 2019 coronavirus disease (COVID-19) pandemic. The diversity of themes identified in this paper can be grouped into the following categories of disease mapping: spatiotemporal analysis, health and social geography, environmental variables, data mining, and web-based mapping. Understanding the spatiotemporal dynamics of COVID-19 is essential for its mitigation, as it helps to clarify the extent and impact of the pandemic and can aid decision making, planning and community action. Health geography highlights the interaction of public health officials, affected actors and first responders to improve estimations of disease propagation and likelihoods of new outbreaks. Attempts at interdisciplinary correlation examine health policy interventions for the siting of health/sanitary services and controls, mapping/tracking of human movement, formulation of appropriate scientific and political responses and projection of spatial diffusion and temporal trends. This review concludes that, to fight COVID-19, it is important to face the challenges from an interdisciplinary perspective, with proactive planning, international solidarity and a global perspective. This review provides useful information and insight that can support future bibliographic queries, and also serves as a resource for understanding the evolution of tools used in the management of this major global pandemic of the 21 Century. It is hoped that its findings will inspire new reflections on the COVID-19 pandemic by readers.

First detection of SARS-CoV-2 in untreated wastewaters in Italy

Several studies have demonstrated the advantages of environmental surveillance through the monitoring of sewage for the assessment of viruses circulating in a given community (wastewater-based epidemiology, WBE). During the COVID-19 public health emergency, many reports have described the presence of SARS-CoV-2 RNA in stools from COVID-19 patients, and a few studies reported the occurrence of SARS-CoV-2 in wastewaters worldwide. Italy is among the world's worst-affected countries in the COVID-19 pandemic, but so far there are no studies assessing the presence of SARS-CoV-2 in Italian wastewaters. To this aim, twelve influent sewage samples, collected between February and April 2020 from Wastewater Treatment Plants in Milan and Rome, were tested adapting, for concentration, the standard WHO procedure for Poliovirus surveillance. Molecular analysis was undertaken with three nested protocols, including a newly designed SARS-CoV-2 specific primer set. SARS-CoV-2 RNA detection was accomplished in volumes of 250 ml of wastewaters collected in areas of high (Milan) and low (Rome) epidemic circulation, according to clinical data. Overall, 6 out of 12 samples were positive. One of the positive results was obtained in a Milan wastewater sample collected a few days after the first notified Italian case of autochthonous SARS-CoV-2. The study confirms that WBE has the potential to be applied to SARS-CoV-2 as a sensitive tool to study spatial and temporal trends of virus circulation in the population.

Is it safe to lift COVID-19 travel bans? The Newfoundland story

A key strategy to prevent a local outbreak during the COVID-19 pandemic is to restrict incoming travel. Once a region has successfully contained the disease, it becomes critical to decide when and how to reopen the borders. Here we explore the impact of border reopening for the example of Newfoundland and Labrador, a Canadian province that has enjoyed no new cases since late April, 2020. We combine a network epidemiology model with machine learning to infer parameters and predict the COVID-19 dynamics upon partial and total airport reopening, with perfect and imperfect quarantine conditions. Our study suggests that upon full reopening, every other day, a new COVID-19 case would enter the province. Under the current conditions, banning air travel from outside Canada is more efficient in managing the pandemic than fully reopening and quarantining 95% of the incoming population. Our study provides quantitative insights of the efficacy of travel restrictions and can inform political decision making in the controversy of reopening.

Coronavirus disease 2019 (COVID-19) and pediatric gastroenterology

The coronavirus disease 2019 (COVID-19) is responsible for the new pandemic, which remains an important health and economic challenge worldwide. The causative agent is a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is similar to SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Adult infection with respiratory symptoms was considered in the beginning of the pandemic. Now, it has been reported that SARS-CoV-2 infects children and other organs such as the gastrointestinal tract. SARS-CoV-2 enters the host cells through angiotensin converting enzyme-2 (ACE2) receptors as the main receptor expressed in various organs such as the lungs and gastrointestinal tract. Studies on children and the clinical manifestations of COVID-19 do not completely explain the natural course of infection in children, and precisely how the GI tract is involved is not understood. The present article highlights the gastrointestinal manifestations and pathological findings in children with COVID-19. According to the evidence, SARS-CoV-2 infection is milder in children and may present different clinical symptoms from adults. Common clinical manifestations of pediatric COVID-19 include cough, fever, sore throat, malaise, fatigue, and GI symptoms such as diarrhea, abdominal pain, nausea, and vomiting. Furthermore, liver and pancreatic enzymes may be elevated during the pediatric COVID-19 course. Asymptomatic children carriers are potential sources of infection for adults, especially elderly ones. Diagnosis, treatment, and isolation of children are the most effective ways to control the expansion of the COVID-19 pandemic.