Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong

Kidney injury in COVID-19 patients, drug development and their renal complications: Review study

Since December 2019, the world was encountered a new disease called coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although SARS-CoV-2 initially causes lung damage, it also affects many other organs, including the kidneys, and on average, 5–23% of people with COVID-19 develop the symptoms of acute kidney injury (AKI), including elevated blood creatinine and urea, hematuria, proteinuria, and histopathological damages. The exact mechanism is unknown, but the researchers believe that SARS-CoV-2 directly and indirectly affects the kidneys. The direct pathway is by binding the virus to ACE2 receptor in the kidney, damage to cells, the renin-angiotensin system disturbances, activating coagulation pathways, and damaging the renal vascular endothelium. The initial evidence from studying the kidney tissue in postmortem patients is more in favor of the direct pathway. The indirect pathway is created by increased cytokines and cytokine storm, sepsis, circulatory disturbances, hypoxemia, as well as using the nephrotoxic drugs. Using renal tissue biopsy and autopsy in the patients with COVID-19, recent studies found evidence for a predominant indirect pathway in AKI induction by SARS-CoV-2. Besides, some studies showed that the degree of acute tubular injury (ATI) in autopsies from COVID-19 victims is milder compared to AKI degree. We review the mechanism of AKI induction and the renal side effects of the most common drugs used to treat COVID-19 after the overview of the latest findings on SARS-CoV-2 pathogenicity.

Clinical guidelines “Chronic diarrhea in adults”

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Using a household-structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic

We explore strategies of contact tracing, case isolation and quarantine of exposed contacts to control the SARS-CoV-2 epidemic using a branching process model with household structure. This structure reflects higher transmission risks among household members than among non-household members. We explore strategic implementation choices that make use of household structure, and investigate strategies including two-step tracing, backwards tracing, smartphone tracing and tracing upon symptom report rather than test results. The primary model outcome is the effect of contact tracing, in combination with different levels of physical distancing, on the growth rate of the epidemic. Furthermore, we investigate epidemic extinction times to indicate the time period over which interventions must be sustained. We consider effects of non-uptake of isolation/quarantine, non-adherence, and declining recall of contacts over time. Our results find that, compared to self-isolation of cases without contact tracing, a contact tracing strategy designed to take advantage of household structure allows for some relaxation of physical distancing measures but cannot completely control the epidemic absent of other measures. Even assuming no imported cases and sustainment of moderate physical distancing, testing and tracing efforts, the time to bring the epidemic to extinction could be in the order of months to years. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Estimating the case fatality ratio for COVID-19 using a time-shifted distribution analysis

Estimating the case fatality ratio (CFR) for COVID-19 is an important aspect of public health. However, calculating CFR accurately is problematic early in a novel disease outbreak, due to uncertainties regarding the time course of disease and difficulties in diagnosis and reporting of cases. In this work, we present a simple method for calculating the CFR using only public case and death data over time by exploiting the correspondence between the time distributions of cases and deaths. The time-shifted distribution (TSD) analysis generates two parameters of interest: the delay time between reporting of cases and deaths and the CFR. These parameters converge reliably over time once the exponential growth phase has finished. Analysis is performed for early COVID-19 outbreaks in many countries, and we discuss corrections to CFR values using excess-death and seroprevalence data to estimate the infection fatality ratio (IFR). While CFR values range from 0.2% to 20% in different countries, estimates for IFR are mostly around 0.5-0.8% for countries that experienced moderate outbreaks and 1-3% for severe outbreaks. The simplicity and transparency of TSD analysis enhance its usefulness in characterizing a new disease as well as the state of the health and reporting systems.

Innate lymphoid cells and disease tolerance in SARS-CoV-2 infection

Risk of severe COVID-19 increases with age, is greater in males, and is associated with lymphopenia, but not with higher burden of SARS-CoV-2. It is unknown whether effects of age and sex on abundance of specific lymphoid subsets explain these correlations. This study found that the abundance of innate lymphoid cells (ILCs) decreases more than 7-fold over the human lifespan — T cell subsets decrease less than 2-fold — and is lower in males than in females. After accounting for effects of age and sex, ILCs, but not T cells, were lower in adults hospitalized with COVID-19, independent of lymphopenia. Among SARS-CoV-2-infected adults, the abundance of ILCs, but not of T cells, correlated inversely with odds and duration of hospitalization, and with severity of inflammation. ILCs were also uniquely decreased in pediatric COVID-19 and the numbers of these cells did not recover during follow-up. In contrast, children with MIS-C had depletion of both ILCs and T cells, and both cell types increased during follow-up. In both pediatric COVID-19 and MIS-C, ILC abundance correlated inversely with inflammation. Blood ILC mRNA and phenotype tracked closely with ILCs from lung. Importantly, blood ILCs produced amphiregulin, a protein implicated in disease tolerance and tissue homeostasis, and the percentage of amphiregulin-producing ILCs was higher in females than in males. These results suggest that, by promoting disease tolerance, homeostatic ILCs decrease morbidity and mortality associated with SARS-CoV-2 infection, and that lower ILC abundance accounts for increased COVID-19 severity with age and in males.

Factors Associated With the Intention to Participate in Coronavirus Disease 2019 Frontline Prevention Activities Among Nursing Students in Vietnam: An Application of the Theory of Planned Behavior

Introduction: Medical students have been serving as a key part of the frontline health workforce responding to the coronavirus disease 2019 (COVID-19) pandemic globally. Their contribution is especially important in the resource-scarce settings of developing nations such as Vietnam. Yet, the intention of medical students, in particular, nursing students, to participate in COVID-19 frontline prevention activities has not been well-understood. This study aimed to examine factors associated with the intentionto participate in COVID-19 frontline prevention activities among Vietnamese nursing students.

Methods: A cross-sectional study was conducted on a total of 597 students in December 2020 in Hanoi, Vietnam. Information regarding the socioeconomic characteristics of participants, their source of COVID-19 related knowledge, and their perception and attitude toward participating in COVID-19 frontline activities [based on Theory of Planned Behavior (TPB)] was collected. A hierarchical regression model was employed to examine the association between intentions of students and associated factors.

Results: A positive intention to participate in COVID-19 frontline prevention activities was found (mean score of 25.3 over 35; SD = 4.4; min = 5; max = 35). Attitude toward behavior, subjective norms, and perceived behavioral control (PBC) was found to be significantly associated with the intention of students. These variables explained the 37% variation in the intention of students in the model. Among three factors, subjective norm showed the strongest correlation with intention of students (β = 0.358; p < 0.001). Obtaining information from official sources and community was also found to be positively correlated with intention to participate.

Conclusion: Most of the respondents reported a positive intention to participate in COVID-19 frontline prevention activities. The findings suggested that the TPB was a good instrument to predict the intention to perform behavior among Vietnamese students. Enhancing the positive attitude of students, encouraging family and community supports, and providing adequately essential resources will contribute to optimizing the participation of students to confront COVID-19.

Targeting liquid-liquid phase separation of SARS-CoV-2 nucleocapsid protein promotes innate antiviral immunity by elevating MAVS activity

Patients with Coronavirus disease 2019 exhibit low expression of interferon-stimulated genes, contributing to a limited antiviral response. Uncovering the underlying mechanism of innate immune suppression and rescuing the innate antiviral response remain urgent issues in the current pandemic. Here we identified that the dimerization domain of the SARS-CoV-2 nucleocapsid protein (SARS2-NP) is required for SARS2-NP to undergo liquid-liquid phase separation with RNA, which inhibits Lys63-linked poly-ubiquitination and aggregation of MAVS and thereby suppresses the innate antiviral immune response. Mice infected with an RNA virus carrying SARS2-NP exhibited reduced innate immunity, an increased viral load and high morbidity. Notably, we identified SARS2-NP acetylation at Lys375 by host acetyltransferase and reported frequently occurring acetylation-mimicking mutations of Lys375, all of which impaired SARS2-NP liquid-liquid phase separation with RNA. Importantly, a peptide targeting the dimerization domain was screened out to disrupt the SARS2-NP liquid-liquid phase separation and demonstrated to inhibit SARS-CoV-2 replication and rescue innate antiviral immunity both in vitro and in vivo.

Investigation of the Efficiency of Mask Wearing, Contact Tracing, and Case Isolation during the COVID-19 Outbreak

Case isolation and contact tracing are two essential parts of control measures to prevent the spread of COVID-19, however, additional interventions, such as mask wearing, are required. Taiwan successfully contained local COVID-19 transmission after the initial imported cases in the country in early 2020 after applying the above-mentioned interventions. In order to explain the containment of the disease spread in Taiwan and understand the efficiency of different non-pharmaceutical interventions, a mathematical model has been developed. A stochastic model was implemented in order to estimate the effectiveness of mask wearing together with case isolation and contact tracing. We investigated different approaches towards mask usage, estimated the effect of the interventions on the basic reproduction number (R0), and simulated the possibility of controlling the outbreak. With the assumption that non-medical and medical masks have 20% and 50% efficiency, respectively, case isolation works on 100%, 70% of all people wear medical masks, and R0 = 2.5, there is almost 80% probability of outbreak control with 60% contact tracing, whereas for non-medical masks the highest probability is only about 20%. With a large proportion of infectiousness before the onset of symptoms (40%) and the presence of asymptomatic cases, the investigated interventions (isolation of cases, contact tracing, and mask wearing by all people), implemented on a high level, can help to control the disease spread. Superspreading events have also been included in our model in order to estimate their impact on the outbreak and to understand how restrictions on gathering and social distancing can help to control the outbreak. The obtained quantitative results are in agreement with the empirical COVID-19 data in Taiwan.

Estimate the Trend of COVID-19 Outbreak in China: a Statistical and Inferential Analysis on Provincial-level Data

The ongoing COVID-19 epidemic spreads with strong transmission power in every part of China. Analyses of the trend is highly need when the Chinese government makes plans and policies on epidemic control. This paper provides an estimation process on the trend of COVID-19 outbreak using the provincial-level data of the confirmed cases. On the basis of the previous studies, we introduce an effective and practical method to compute accurate basic reproduction numbers (R 0 s) in each province-level division of China. The statistical results show a non-stop downward trend of the R 0 s in China, and confirm that China has made significant progress on the epidemic control by lowering the provincial R 0 s from 10 or above to 3.21 or less. In the inferential analysis, we introduce an effective AR(n) model for the trend forecasting. The inferential results imply that the nationwide epidemic risk will fall to a safe level by the end of April in China, which matches the actual situation. The results provide more accurate method and information about COVID-19.

Matrix-Based Formulation of Heterogeneous Individual-Based Models of Infectious Diseases: Using SARS Epidemic as a Case Study

Heterogeneities of individual attributes and behaviors play an important role in the complex process of epidemic spreading. Compared to differential equation-based system dynamical models of infectious disease transmission, individual-based epidemic models exhibit the advantage of providing a more detailed description of realities to capture heterogeneities across a population. However, the higher granularity and resolution of individual-based epidemic models comes with the cost of increased computational complexities, which result in difficulty in formulating individual-based epidemic models with mathematics. Furthermore, it requires great effort to understand and reproduce existing individual-based epidemic models presented by previous researchers. We proposed a mathematical formulation of heterogeneous individual-based epidemic models using matrices. Matrices and vectors were applied to represent individual attributes and behaviors. We derived analytical results from the matrix-based formulations of individual epidemic models, and then designed algorithms to force the computation of matrix-based individual epidemic models. Finally, we used a SARS epidemic control as a case study to verify the matrix-based formulation of heterogeneous individual-based epidemic models.

Aging and Options to Halt Declining Immunity to Virus Infections

Immunosenescence is a process associated with aging that leads to dysregulation of cells of innate and adaptive immunity, which may become dysfunctional. Consequently, older adults show increased severity of viral and bacterial infections and impaired responses to vaccinations. A better understanding of the process of immunosenescence will aid the development of novel strategies to boost the immune system in older adults. In this review, we focus on major alterations of the immune system triggered by aging, and address the effect of chronic viral infections, effectiveness of vaccination of older adults and strategies to improve immune function in this vulnerable age group.

The Incubation Period of COVID-19: Current Understanding and Modeling Technique

This chapter aims to answer the following questions regarding the incubation period of COVID-19. Why is understanding the incubation period of COVID-19 important? How long is the incubation time, and what are the associating factors? How should the incubation period be modeled given the current pandemic situation? Where should we go from here? As a critical epidemiological metric, the incubation period is of public health and clinical importance. While the incubation time of COVID-19 is generally similar to that of SARS and MERS, recent studies identifying factors that impact the incubation period of COVID-19, travel history, for example, only tell part of the story. Therefore, in addition to reviewing current findings, this chapter also explores the modeling technique and future research directions of the incubation period of COVID-19.

SARS-CoV-2 rapidly adapts in aged BALB/c mice and induces typical pneumonia

Age is a risk factor for coronavirus disease 2019 (COVID-19) associated morbidity and mortality in humans; hence, in this study, we compared the course of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection in young and aged BALB/c mice. We found that SARS-CoV-2 isolates replicated in the respiratory tracts of 12-month-old (aged) mice and caused pathological features of pneumonia upon intranasal infection. In contrast, rapid viral clearance was observed 5 days following infection in 2-month-old (young) mice with no evidence of pathological changes in the lungs. Infection with SARS-CoV-2 elicited significantly upregulated production of cytokines, especially interleukin 6 and interferon gamma, in aged mice; whereas this response was much weaker in young mice. Subsequent challenge of infected aged BALB/c mice with SARS-CoV-2 resulted in neutralized antibody responses, a significantly reduced viral burden in the lungs, and inflammation mitigation. Deep sequencing showed a panel of mutations potentially associated with the enhanced infection in aged BALB/c mice, such as the Q498H mutations which are located at the receptor binding domain (RBD) of the spike (S) protein. We further found that the isolates can not only multiply in the respiratory tract of mice but also cause disease in aged mice. Overall, viral replication and rapid adaption in aged BALB/c mice were associated with pneumonia, confirming that the age-related susceptibility to SARS-CoV-2 in mice resembled that in humans.ImportanceAged BALB/c model are in use as a model of disease caused by SARS-CoV-2. Our research demonstrated SARS-CoV-2 can rapidly adapt in aged BALB/c mice through causing mutations at the RBD of the S protein. Moreover, SARS-CoV-2-infected aged BALB/c mice indicated that alveolar damage, interstitial pneumonia, and inflammatory immune responses were similar to the clinical manifestations of human infections. Therefore, our aged BALB/c challenge model will be useful for further understanding the pathogenesis of SARS-CoV-2 and for testing vaccines and antiviral agents.

Insurance and Epidemics: SARS, West Nile Virus and Nipah Virus

Severe acute respiratory syndrome (SARS) reminds us that sudden disease emergence is a permanent part of our world-and should be anticipated in our planning. Historically the emergence of new diseases has had little or no impact beyond a small, localized cluster of infections. However, given just the right conditions, a highly virulent pathogen can suddenly spread across time and space with massive consequences, as has occurred on several occasions in human history. In the wake of the SARS outbreak, we are now forced to confront the unpleasant fact that human activities are increasing the frequency and severity of these kinds of emergences. The idea of more frequent biological ''invasions'' with economic and societal impacts comparable to SARS, presents stakeholders in the global economy with unprecedented new risks, challenges and even opportunities. As a major contributor to economic stability, the insurance industry must follow these trends very closely and develop scenarios to anticipate these events.

Covid-19 and kidney injury: Pathophysiology and molecular mechanisms

The novel coronavirus (SARS-CoV-2) has turned into a life-threatening pandemic disease (Covid-19). About 5% of patients with Covid-19 have severe symptoms including septic shock, acute respiratory distress syndrome, and the failure of several organs, while most of them have mild symptoms. Frequently, the kidneys are involved through direct or indirect mechanisms. Kidney involvement mainly manifests itself as proteinuria and acute kidney injury (AKI). The SARS-CoV-2-induced kidney damage is expected to be multifactorial; directly it can infect the kidney podocytes and proximal tubular cells and based on an angiotensin-converting enzyme 2 (ACE2) pathway it can lead to acute tubular necrosis, protein leakage in Bowman's capsule, collapsing glomerulopathy and mitochondrial impairment. The SARS-CoV-2-driven dysregulation of the immune responses including cytokine storm, macrophage activation syndrome, and lymphopenia can be other causes of the AKI. Organ interactions, endothelial dysfunction, hypercoagulability, rhabdomyolysis, and sepsis are other potential mechanisms of AKI. Moreover, lower oxygen delivery to kidney may cause an ischaemic injury. Understanding the fundamental molecular pathways and pathophysiology of kidney injury and AKI in Covid-19 is necessary to develop management strategies and design effective therapies.

COVID-19: Current understanding of its Pathophysiology, Clinical presentation and Treatment

BACKGROUND

The severe acute respiratory syndrome (SARS) coronavirus-2 is a novel coronavirus belonging to the family Coronaviridae and is now known to be responsible for the outbreak of a series of recent acute atypical respiratory infections originating in Wuhan, China. The disease caused by this virus, termed coronavirus disease 19 or simply COVID-19, has rapidly spread throughout the world at an alarming pace and has been declared a pandemic by the WHO on March 11, 2020. In this review, an update on the pathophysiology, clinical presentation and the most recent management strategies for COVID-19 has been described.

MATERIALS AND METHODS

A search was conducted for literature and various articles/case reports from 1997 to 2020 in PUBMED/MEDLINE for the keywords coronavirus, SARS, Middle East respiratory syndrome and mRNA virus.

RESULTS AND CONCLUSIONS

COVID-19 has now spread globally with increasing morbidity and mortality among all populations. In the absence of a proper and effective antibody test, the diagnosis is presently based on a reverse-transcription PCR of nasopharyngeal and oropharyngeal swab samples. The clinical spectrum of the disease presents in the form of a mild, moderate or severe illness. Most patients are either asymptomatic carriers who despite being without symptoms have the potential to be infectious to others coming in close contact, or have a mild influenza-like illness which cannot be differentiated from a simple upper respiratory tract infection. Moderate and severe cases require hospitalisation as well as intensive therapy which includes non-invasive as well as invasive ventilation, along with antipyretics, antivirals, antibiotics and steroids. Complicated cases may require treatment by immunomodulatory drugs and plasma exchange therapy. The search for an effective vaccine for COVID-19 is presently in full swing, with pharmaceutical corporations having started human trials in many countries.

The challenges of data usage for the United States' COVID-19 response

During the coronavirus pandemic, policy makers need to interpret available public health data to make decisions affecting public health. However, the United States’ coronavirus response faced data gaps, inadequate and inconsistent definitions of data across different governmental jurisdictions, ambiguous timing in reporting, problems in accessing data, and changing interpretations from scientific institutions. These present numerous problems for the decision makers relying on this information. This paper documents some of the data pitfalls in coronavirus public health data reporting, as identified by the authors in the course of supporting data management for New England’s coronavirus response. We provide recommendations for individuals to collect data more effectively during emergency situations such as a COVID-19 surge, as well as recommendations for institutions to provide more meaningful data for various users to access. Through this, we hope to motivate action to avoid data pitfalls during public health responses in the future.

A review of the COVID-19 pandemic and its interaction with environmental media

Viruses are biologically active parasites that only exist inside a host they are submicroscopic level. The novel coronavirus disease, or COVID-19, is generally caused by the SARS-CoV-2 virus and is comparable to severe acute respiratory syndrome (SARS). As a result of globalization, natural alterations or changes in the SARS-CoV-2 have created significant risks to human health over time. These viruses can live and survive in different ways in the atmosphere unless they reach another host body. At this stage, we will discuss the details of the transmission and detection of this deadly SARS-CoV-2 virus via certain environmental media, such as the atmosphere, water, air, sewage water, soil, temperature, relative humidity, and bioaerosol, to better understand the diffusion, survival, infection potential and diagnosis of COVID-19.

On realized serial and generation intervals given control measures: The COVID-19 pandemic case

The SARS-CoV-2 pathogen is currently spreading worldwide and its propensity for presymptomatic and asymptomatic transmission makes it difficult to control. The control measures adopted in several countries aim at isolating individuals once diagnosed, limiting their social interactions and consequently their transmission probability. These interventions, which have a strong impact on the disease dynamics, can affect the inference of the epidemiological quantities. We first present a theoretical explanation of the effect caused by non-pharmaceutical intervention measures on the mean serial and generation intervals. Then, in a simulation study, we vary the assumed efficacy of control measures and quantify the effect on the mean and variance of realized generation and serial intervals. The simulation results show that the realized serial and generation intervals both depend on control measures and their values contract according to the efficacy of the intervention strategies. Interestingly, the mean serial interval differs from the mean generation interval. The deviation between these two values depends on two factors. First, the number of undiagnosed infectious individuals. Second, the relationship between infectiousness, symptom onset and timing of isolation. Similarly, the standard deviations of realized serial and generation intervals do not coincide, with the former shorter than the latter on average. The findings of this study are directly relevant to estimates performed for the current COVID-19 pandemic. In particular, the effective reproduction number is often inferred using both daily incidence data and the generation interval. Failing to account for either contraction or mis-specification by using the serial interval could lead to biased estimates of the effective reproduction number. Consequently, this might affect the choices made by decision makers when deciding which control measures to apply based on the value of the quantity thereof.

The generation and serial intervals are epidemiological quantities used to describe and predict an ongoing epidemic outbreak. These quantities are related to the contact pattern of individuals, since infection events can take place if infectious and susceptible individuals have a contact. Therefore, intervention measures that reduce the interactions between members of the population are expected to affect both the realized generation and serial intervals. For the current COVID-19 pandemic unprecedented interventions have been adopted worldwide, e.g. strict lockdown, isolation and quarantine, which influence the realized value of generation and serial intervals. The extent of the effect thereof depends on the efficacy of the control measure in place, on the relationship between symptom onset and infectiousness and on the proportion of infectious individuals that can be detected. To get more insight on this, we present an investigation that highlights the effect of quarantine and isolation on realized generation and serial intervals. In particular, we show that not only their variances but also their mean values can differ, suggesting that the use of the mean serial interval as a proxy for the mean generation time can lead to biased estimates of epidemiological quantities.

Quantifying the risk of indoor drainage system in multi-unit apartment building as a transmission route of SARS-CoV-2

The COVID-19 pandemic has had a profound impact on human society. The isolation of SARS-CoV-2 from patients' feces on human cell line raised concerns of possible transmission through human feces including exposure to aerosols generated by toilet flushing and through the indoor drainage system. Currently, routes of transmission, other than the close contact droplet transmission, are still not well understood. A quantitative microbial risk assessment was conducted to estimate the health risks associated with two aerosol exposure scenarios: 1) toilet flushing, and 2) faulty connection of a floor drain with the building's main sewer pipe. SARS-CoV-2 data were collected from the emerging literature. The infectivity of the virus in feces was estimated based on a range of assumption between viral genome equivalence and infectious unit. The human exposure dose was calculated using Monte Carlo simulation of viral concentrations in aerosols under each scenario and human breathing rates. The probability of COVID-19 illness was generated using the dose-response model for SARS-CoV-1, a close relative of SARS-CoV-2, that was responsible for the SARS outbreak in 2003. The results indicate the median risks of developing COVID-19 for a single day exposure is 1.11 × 10-10 and 3.52 × 10-11 for toilet flushing and faulty drain scenario, respectively. The worst case scenario predicted the high end of COVID-19 risk for the toilet flushing scenario was 5.78 × 10-4 (at 95th percentile). The infectious viral loads in human feces are the most sensitive input parameter and contribute significantly to model uncertainty.

Serial interval and incubation period of COVID-19: a systematic review and meta-analysis

BACKGROUND

Understanding the epidemiological parameters that determine the transmission dynamics of COVID-19 is essential for public health intervention. Globally, a number of studies were conducted to estimate the average serial interval and incubation period of COVID-19. Combining findings of existing studies that estimate the average serial interval and incubation period of COVID-19 significantly improves the quality of evidence. Hence, this study aimed to determine the overall average serial interval and incubation period of COVID-19.

METHODS

We followed the PRISMA checklist to present this study. A comprehensive search strategy was carried out from international electronic databases (Google Scholar, PubMed, Science Direct, Web of Science, CINAHL, and Cochrane Library) by two experienced reviewers (MAA and DBK) authors between the 1st of June and the 31st of July 2020. All observational studies either reporting the serial interval or incubation period in persons diagnosed with COVID-19 were included in this study. Heterogeneity across studies was assessed using the I2 and Higgins test. The NOS adapted for cross-sectional studies was used to evaluate the quality of studies. A random effect Meta-analysis was employed to determine the pooled estimate with 95% (CI). Microsoft Excel was used for data extraction and R software was used for analysis.

RESULTS

We combined a total of 23 studies to estimate the overall mean serial interval of COVID-19. The mean serial interval of COVID-19 ranged from 4. 2 to 7.5 days. Our meta-analysis showed that the weighted pooled mean serial interval of COVID-19 was 5.2 (95%CI: 4.9-5.5) days. Additionally, to pool the mean incubation period of COVID-19, we included 14 articles. The mean incubation period of COVID-19 also ranged from 4.8 to 9 days. Accordingly, the weighted pooled mean incubation period of COVID-19 was 6.5 (95%CI: 5.9-7.1) days.

CONCLUSIONS

This systematic review and meta-analysis showed that the weighted pooled mean serial interval and incubation period of COVID-19 were 5.2, and 6.5 days, respectively. In this study, the average serial interval of COVID-19 is shorter than the average incubation period, which suggests that substantial numbers of COVID-19 cases will be attributed to presymptomatic transmission.

Lung Protection vs. Infection Resolution: Interleukin 10 Suspected of Double-Dealing in COVID-19

The pathological processes by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that make the virus a major threat to global health are insufficiently understood. Inefficient viral clearance at any stage is a hallmark of coronavirus disease 2019 (COVID-19). Disease severity is associated with increases in peripheral blood cytokines among which interleukin 10 (IL-10) increases particularly early and independent of patient age, which is not seen in active SARS-CoV infection. Here, we consider the known multi-faceted immune regulatory role of IL-10, both in protecting the lung from injury and in defense against infections, as well as its potential cellular source. While the absence of an IL-10 response in SARS is thought to contribute to early deterioration, we suspect IL-10 to protect the lung from early immune-mediated damage and to interfere with viral clearance in COVID-19. This may further both viral spread and poor outcome in many high-risk patients. Identifying the features of the viral genotype, which specifically underlie the different IL-10 dynamics as an etiological endotype and the different viral load kinetics and outcomes as clinical phenotype, may unveil a new immune evasive strategy of SARS-CoV-2.

Meteorological factors and COVID-19 incidence in 190 countries: An observational study

Novel corona virus disease 2019 (COVID-19), which first emerged in December 2019, has become a pandemic. This study aimed to investigate the associations between meteorological factors and COVID-19 incidence and mortality worldwide. This study included 1,908,197 confirmed cases of and 119,257 deaths from COVID-19 from 190 countries between 23 January and 13 April, 2020. We used a distributed lag non-linear model with city-/country-level random intercept to investigate the associations between COVID19 incidence and daily temperature, relative humidity, and wind speed. A series of confounders were considered in the analysis including demographics, socioeconomics, geographic locations, and political strategies. Sensitivity analyses were performed to examine the robustness of the associations. The COVID-19 incidence showed a stronger association with temperature than with relative humidity or wind speed. An inverse association was identified between the COVID-19 incidence and temperature. The corresponding 14-day cumulative relative risk was 1.28 [95% confidence interval (CI), 1.20-1.36] at 5 °C, and 0.75 (95% CI, 0.65-0.86) at 22 °C with reference to the risk at 11 °C. An inverse J-shaped association was observed between relative humidity and the COVID-19 incidence, with the highest risk at 72%. A higher wind speed was associated with a generally lower incidence of COVID-19, although the associations were weak. Sensitivity analyses generally yielded similar results. The COVID-19 incidence decreased with the increase of temperature. Our study suggests that the spread of COVID-19 may slow during summer but may increase during winter.

SARS-CoV-2, SARS and MERS: Three formidable coronaviruses which have originated from bats

The recent continuously emerging rampancy of novel coronavirus (SARS-CoV-2) that started in Wuhan in late December 2019 has become an international public health emergency and is still spreading rapidly in the world. Up to October 11, 2020, 37.109.6851 confirmed cases of COVID-19 have been announced with 2.8 percent death, which means 1.070.355 confirmed death cases. At the moment, a specific vaccine or drug for the new coronavirus is not available; thus, the development of a drug with far-reaching HCoV inhibitory activity is an urgent medical need. It is, however, vital to first comprehend the nature of this family and other coronaviruses that have caused the outbreak. Here, we relate the epidemiological and virological characteristics of the COVID-19, SARS, and MERS rampancy.

SARS-CoV-2 spillover transmission due to recombination event

In late 2019, a novel Coronavirus emerged in China. Perceiving the modulating factors of cross-species virus transmission is critical to elucidate the nature of virus emergence. Using bioinformatics tools, we analyzed the mapping of the SARS-CoV-2 genome, modeling of protein structure, and analyze the evolutionary origin of SARS-CoV-2, as well as potential recombination events. Phylogenetic tree analysis shows that SARS-CoV-2 has the closest evolutionary relationship with Bat-SL-CoV-2 (RaTG13) at the scale of the complete virus genome, and less similarity to Pangolin-CoV. However, the Receptor Binding Domain (RBD) of SARS-CoV-2 is almost identical to Pangolin-CoV at the aa level, suggesting that spillover transmission probably occurred directly from pangolins, but not bats. Further recombination analysis revealed the pathway for spillover transmission from Bat-SL-CoV-2 and Pangolin-CoV. Here, we provide evidence for recombination event between Bat-SL-CoV-2 and Pangolin-CoV that resulted in the emergence of SARS-CoV-2. Nevertheless, the role of mutations should be noted as another influencing factor in the continuing evolution and resurgence of novel SARS-CoV-2 variants.

Comparison of acute pneumonia caused by SARS-COV-2 and other respiratory viruses in children: a retrospective multi-center cohort study during COVID-19 outbreak

BACKGROUND

Until January 18, 2021, coronavirus disease-2019 (COVID-19) has infected more than 93 million individuals and has caused a certain degree of panic. Viral pneumonia caused by common viruses such as respiratory syncytial virus, rhinovirus, human metapneumovirus, human bocavirus, and parainfluenza viruses have been more common in children. However, the incidence of COVID-19 in children was significantly lower than that in adults. The purpose of this study was to describe the clinical manifestations, treatment and outcomes of COVID-19 in children compared with those of other sources of viral pneumonia diagnosed during the COVID-19 outbreak.

METHODS

Children with COVID-19 and viral pneumonia admitted to 20 hospitals were enrolled in this retrospective multi-center cohort study. A total of 64 children with COVID-19 were defined as the COVID-19 cohort, of which 40 children who developed pneumonia were defined as the COVID-19 pneumonia cohort. Another 284 children with pneumonia caused by other viruses were defined as the viral pneumonia cohort. The epidemiologic, clinical, and laboratory findings were compared by Kolmogorov-Smirnov test, t-test, Mann-Whitney U test and Contingency table method. Drug usage, immunotherapy, blood transfusion, and need for oxygen support were collected as the treatment indexes. Mortality, intensive care needs and symptomatic duration were collected as the outcome indicators.

RESULTS

Compared with the viral pneumonia cohort, children in the COVID-19 cohort were mostly exposed to family members confirmed to have COVID-19 (53/64 vs. 23/284), were of older median age (6.3 vs. 3.2 years), and had a higher proportion of ground-glass opacity (GGO) on computed tomography (18/40 vs. 0/38, P < 0.001). Children in the COVID-19 pneumonia cohort had a lower proportion of severe cases (1/40 vs. 38/284, P = 0.048), and lower cases with high fever (3/40 vs. 167/284, P < 0.001), requiring intensive care (1/40 vs. 32/284, P < 0.047) and with shorter symptomatic duration (median 5 vs. 8 d, P < 0.001). The proportion of cases with evaluated inflammatory indicators, biochemical indicators related to organ or tissue damage, D-dimer and secondary bacterial infection were lower in the COVID-19 pneumonia cohort than those in the viral pneumonia cohort (P < 0.05). No statistical differences were found in the duration of positive PCR results from pharyngeal swabs in 25 children with COVID-19 who received antiviral drugs (lopinavir-ritonavir, ribavirin, and arbidol) as compared with duration in 39 children without antiviral therapy [median 10 vs. 9 d, P = 0.885].

CONCLUSION

The symptoms and severity of COVID-19 pneumonia in children were no more severe than those in children with other viral pneumonia. Lopinavir-ritonavir, ribavirin and arbidol do not shorten the duration of positive PCR results from pharyngeal swabs in children with COVID-19. During the COVID-19 outbreak, attention also must be given to children with infection by other pathogens infection.

Regional Variability in COVID-19 Case Fatality Rate in Canada, February-December 2020

A total of 475,214 COVID-19 cases, including 13,659 deaths, had been recorded in Canada as of 15 December 2020. The daily reports of confirmed cases and deaths in Canada prior to 15 December 2020 were obtained from publicly available sources and used to examine regional variations in case fatality rate (CFR). Based on a factor of underestimation and the duration of time from symptom onset to death, the time-delay adjusted CFR for COVID-19 was estimated in the four most affected provinces (Quebec, Ontario, Alberta, and British Columbia) and nationwide. The model-based adjusted CFR was higher than the crude CFR throughout the pandemic, primarily owing to the incorporation in our estimation of the delay between case reports and deaths. The adjusted CFR in Canada was estimated to be 3.36% nationwide. At the provincial level, the adjusted CFR was the highest in Quebec (5.13%)—where the proportion of deaths among older individuals was also the highest among the four provinces—followed by Ontario (3.17%), British Columbia (1.97%), and Alberta (1.13%). Provincial-level variations in CFR were considerable, suggesting that public health interventions focused on densely populated areas and elderly individuals can ameliorate the mortality burden of the COVID-19 pandemic.

Differential diagnosis of coronavirus disease 2019 pneumonia or influenza A pneumonia by clinical characteristics and laboratory findings

Background

Pneumonia caused by the 2019 novel Coronavirus (COVID‐2019) shares overlapping signs and symptoms, laboratory findings, imaging features with influenza A pneumonia. We aimed to identify their clinical characteristics to help early diagnosis.

Methods

We retrospectively retrieved data for laboratory‐confirmed patients admitted with COVID‐19–induced or influenza A–induced pneumonia from electronic medical records in Ningbo First Hospital, China. We recorded patients' epidemiological and clinical features, as well as radiologic and laboratory findings.

Results

The median age of influenza A cohort was higher and it exhibited higher temperature and higher proportion of pleural effusion. COVID‐19 cohort exhibited higher proportions of fatigue, diarrhea and ground‐glass opacity and higher levels of lymphocyte percentage, absolute lymphocyte count, red‐cell count, hemoglobin and albumin and presented lower levels of monocytes, c‐reactive protein, aspartate aminotransferase, alkaline phosphatase, serum creatinine. Multivariate logistic regression analyses showed that fatigue, ground‐glass opacity, and higher level of albumin were independent risk factors for COVID‐19 pneumonia, while older age, higher temperature, and higher level of monocyte count were independent risk factors for influenza A pneumonia.

Conclusions

In terms of COVID‐19 pneumonia and influenza A pneumonia, fatigue, ground‐glass opacity, and higher level of albumin tend to be helpful for diagnosis of COVID‐19 pneumonia, while older age, higher temperature, and higher level of monocyte count tend to be helpful for the diagnosis of influenza A pneumonia.

The value of infectious disease modeling and trend assessment: a public health perspective

INTRODUCTION

Disease outbreaks of acquired immunodeficiency syndrome, severe acute respiratory syndrome, pandemic H1N1, H7N9, H5N1, Ebola, Zika, Middle East respiratory syndrome, and recently COVID-19 have raised the attention of the public over the past half-century. Revealing the characteristics and epidemic trends are important parts of disease control. The biological scenarios including transmission characteristics can be constructed and translated into mathematical models, which can help to predict and gain a deeper understanding of diseases.

AREAS COVERED

This review discusses the models for infectious diseases and highlights their values in the field of public health. This information will be of interest to mathematicians and clinicians, and make a significant contribution toward the development of more specific and effective models. Literature searches were performed using the online database of PubMed (inception to August 2020).

EXPERT OPINION

Modeling could contribute to infectious disease control by means of predicting the scales of disease epidemics, indicating the characteristics of disease transmission, evaluating the effectiveness of interventions or policies, and warning or forecasting during the pre-outbreak of diseases. With the development of theories and the ability of calculations, infectious disease modeling would play a much more important role in disease prevention and control of public health.

Current concepts in the development of therapeutics against human and animal coronavirus diseases by targeting NP

The coronavirus (CoV) infects a broad range of hosts including humans as well as a variety of animals. It has gained overwhelming concerns since the emergence of deadly human coronaviruses (HCoVs), severe acute respiratory syndrome coronavirus (SARS-CoV) in 2003, followed by Middle East respiratory syndrome coronavirus (MERS-CoV) in 2015. Very recently, special attention has been paid to the novel coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 due to its high mobility and mortality. As the COVID-19 pandemic continues, despite vast research efforts, the effective pharmaceutical interventions are still not available for clinical uses. Both expanded knowledge on structure insights and the essential function of viral nucleocapsid (N) protein are key basis for the development of novel, and potentially, a broad-spectrum inhibitor against coronavirus diseases. This review aimed to delineate the current research from the perspective of biochemical and structural study in cell-based assays as well as virtual screen approaches to identify N protein antagonists targeting not only HCoVs but also animal CoVs.

Estimating Unreported COVID-19 Cases with a Time-Varying SIR Regression Model

BACKGROUND

Potential unreported infection might impair and mislead policymaking for COVID-19, and the contemporary spread of COVID-19 varies in different counties of the United States. It is necessary to estimate the cases that might be underestimated based on county-level data, to take better countermeasures against COVID-19. We suggested taking time-varying Susceptible-Infected-Recovered (SIR) models with unreported infection rates (UIR) to estimate factual COVID-19 cases in the United States.

METHODS

Both the SIR model integrated with unreported infection rates (SIRu) of fixed-time effect and SIRu with time-varying parameters (tvSIRu) were applied to estimate and compare the values of transmission rate (TR), UIR, and infection fatality rate (IFR) based on US county-level COVID-19 data.

RESULTS

Based on the US county-level COVID-19 data from 22 January (T1) to 20 August (T212) in 2020, SIRu was first tested and verified by Ordinary Least Squares (OLS) regression. Further regression of SIRu at the county-level showed that the average values of TR, UIR, and IFR were 0.034%, 19.5%, and 0.51% respectively. The ranges of TR, UIR, and IFR for all states ranged from 0.007-0.157 (mean = 0.048), 7.31-185.6 (mean = 38.89), and 0.04-2.22% (mean = 0.22%). Among the time-varying TR equations, the power function showed better fitness, which indicated a decline in TR decreasing from 227.58 (T1) to 0.022 (T212). The general equation of tvSIRu showed that both the UIR and IFR were gradually increasing, wherein, the estimated value of UIR was 9.1 (95%CI 5.7-14.0) and IFR was 0.70% (95%CI 0.52-0.95%) at T212.

INTERPRETATION

Despite the declining trend in TR and IFR, the UIR of COVID-19 in the United States is still on the rise, which, it was assumed would decrease with sufficient tests or improved countersues. The US medical system might be largely affected by severe cases amidst a rapid spread of COVID-19.

Mathematical prediction of the spreading rate of COVID-19 using entropy-based thermodynamic model

In the COVID-19 pandemic era, undoubtedly mathematical modeling helps epidemiological scientists and authorities to take informing decisions about pandemic planning, wise resource allocation, introducing relevant non-pharmaceutical interventions and implementation of social distancing measures. The current coronavirus disease (COVID-19) emerged in the end of 2019, Wuhan, China, spreads quickly in the world. In this study, an entropy-based thermodynamic model has been used for predicting and spreading the rate of COVID-19. In our model, all the epidemic details were considered into a single time-dependent parameter. The parameter was analytically determined using four constraints, including the existence of an inflexion point and a maximum value. Our model has been layout-based the Shannon entropy and the maximum rate of entropy production of postulated complex system. The results show that our proposed model fits well with the number of confirmed COVID-19 cases in daily basis. Also, as a matter of fact that Shannon entropy is an intersection of information, probability theory, (non)linear dynamical systems and statistical physics, the proposed model in this study can be further calibrated to fit much better on COVID-19 observational data, using the above formalisms.

A review: novel coronavirus (COVID-19): an evidence-based approach

The World Health Organization in China was informed about the cases of pneumonia of unknown antecedent ailments. Since then, there have been over 141 million cases globally of 2019 novel coronavirus (Covid-19), 3.01 million deaths, and over 80.4 million recovered. Clinical research of novel agents represent opportunities to inform real-time public health action. In 2018 there was a systematic review to identify priority research questions for Severe Acute Respiratory Syndrome-related coronavirus and Middle East Respiratory Syndrome-related coronavirus. Here, we review information available on COVID-19 and provide evidenced-based approaches in clinical research for the current COVID-19 outbreak.

Liver Chemistries in Patients With COVID-19 Who Were Discharged Alive or Died: A Meta-analysis

Although abnormal liver chemistries are linked to a higher risk of coronavirus disease 2019 (COVID-19)-related death, liver manifestations may be diverse and even confusing. Thus, we performed a meta-analysis of published liver manifestations and described the liver damage in patients with COVID-19 who died or discharged alive. We searched PubMed, Google Scholar, medRxiv, bioRxiv, the Cochrane Library, Embase, and three Chinese electronic databases through April 22, 2020. We analyzed pooled data on liver chemistries stratified by the main clinical outcome of COVID-19, using a fixed or random-effects model. In our meta-analysis of 19 studies, which included a total of 4,103 patients, the pooled mean alanine aminotransferase and aspartate aminotransferase levels were, respectively, 31.7 IU/L and 51.0 IU/L in the patients with COVID-19 who died and 27.7 IU/L and 32.9 IU/L in those discharged alive (both P < 0.0001). Compared with the patients discharged alive, those who died tended to have lower albumin levels but longer prothrombin time and higher international normalized ratio. Conclusion: In this meta-analysis, according to the main clinical outcome of COVID-19, we comprehensively describe three patterns of liver impairment related to COVID-19: hepatocellular injury, cholestasis, and hepatocellular disfunction. The patients who died from COVID-19 tended to have different liver chemistries from those discharged alive. Special caution should be given to the patients with a relatively higher index of liver chemistries.

Temporal evolution, most influential studies and sleeping beauties of the coronavirus literature

Following the outbreak of SARS-CoV-2 disease, within less than 8 months, the 50 years-old scholarly literature of coronaviruses grew to nearly three times larger than its size prior to 2020. Here, temporal evolution of the coronavirus literature over the last 30 years (N = 43,769) is analysed along with its subdomain of SARS-CoV-2 articles (N = 27,460) and the subdomain of reviews and meta-analytic studies (N = 1027). The analyses are conducted through the lenses of co-citation and bibliographic coupling of documents. (1) Of the N = 1204 review and meta-analytical articles of the coronavirus literature, nearly 88% have been published and indexed during the first 8 months of 2020, marking an unprecedented attention to reviews and meta-analyses in this domain, prompted by the SARS-CoV-2 pandemic. (2) The subset of 2020 SARS-CoV-2 articles is bibliographically distant from the rest of this literature published prior to 2020. Individual articles of the SARS-CoV-2 segment with a bridging role between the two bodies of articles (i.e., before and after 2020) are identifiable. (3) Furthermore, the degree of bibliographic coupling within the 2020 SARS-CoV-2 cluster is much poorer compared to the cluster of articles published prior to 2020. This could, in part, be explained by the higher diversity of topics that are studied in relation to SARS-CoV-2 compared to the literature of coronaviruses published prior to the SARS-CoV-2 disease. (4) The analyses on the subset of SARS-CoV-2 literature identified studies published prior to 2020 that have now proven highly instrumental in the development of various clusters of publications linked to SARS-CoV-2. In particular, the so-called "sleeping beauties" of the coronavirus literature with an awakening in 2020 were identified, i.e., previously published studies of this literature that had remained relatively unnoticed for several years but gained sudden traction in 2020 in the wake of the SARS-CoV-2 outbreak. This work documents the historical development of the literature on coronaviruses as an event-driven literature and as a domain that exhibited, arguably, the most exceptional case of publication burst in the history of science. It also demonstrates how scholarly efforts undertaken during peace time or prior to a disease outbreak could suddenly play a critical role in prevention and mitigation of health disasters caused by new diseases.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11192-021-04036-4.

Naturally Occurring Animal Coronaviruses as Models for Studying Highly Pathogenic Human Coronaviral Disease

Coronaviruses (CoVs) comprise a large group of positive stranded RNA viruses that infect a diverse host range including birds and mammals. Infection with CoVs typically presents as mild to severe respiratory or enteric disease, but CoVs have the potential to cause significant morbidity or mortality in highly susceptible age groups. CoVs have exhibited a penchant for jumping species barriers throughout history with devastating effects. The emergence of highly pathogenic or infectious CoVs in humans over the past 20 years, including severe acute respiratory syndrome CoV (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and most recently severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), underscores the significant threat that CoV spillovers pose to humans. Similar to the emergence of SARS-CoV-2, CoVs have been devastating to commercial animal production over the past century, including infectious bronchitis virus in poultry and bovine CoV, as well as the emergence and reemergence of multiple CoVs in swine including transmissible gastroenteritis virus, porcine epidemic diarrhea virus, and porcine deltacoronavirus. These naturally occurring animal CoV infections provide important examples for understanding CoV disease as many animal CoVs have complex pathogenesis similar to SARS-CoV-2 and can shed light on the ongoing SARS-CoV-2 outbreak. We provide an overview and update regarding selected existing animal CoVs and their primary host species, diseases caused by CoVs, how CoVs jump species, whether these CoVs pose an outbreak risk or risk to humans, and how we can mitigate these risks.

Personal protective equipment in the siege of respiratory viral pandemics: strides made and next steps

Introduction: In December 2019, SARS-CoV-2 originated from China, and spread rapidly to several countries, bringing a frightening scarcity of personal protective equipment (PPE). The CDC recommends N95 or higher-level particulate filtering respirators as part of the PPE while caring for patients with COVID-19, with facemasks as an alternative; and cloth face-coverings in public where social distancing of at least 6 ft. is not feasible. With new evidence about the efficacy of facemasks, knowledge gaps remain.Areas covered: This reviews the history of respiratory viral pandemics and PPE use, exploring the influenza pandemics of the 20^th and 21^st century, and prior coronavirus pandemics. A literature search of PubMed and google was done between March 22^nd to May 2^nd, and on September 28, 2020. The evidence for PPE is described, to delineate their efficacy and 'best safe' practices. Solutions to ameliorate pandemic preparedness to meet surge-capacity to efficiently combat future pandemics, should they arise, are discussed.Expert opinion: PPE, when used appropriately in addition to other infection control measures, is effective protection during respiratory viral pandemics. The current evidence suggests that wearing facemasks in the community is protective, especially if used consistently and correctly with other infection control measures such as hand hygiene.

SARS-CoV-2 (COVID-19): What Do We Know About Children? A Systematic Review

BACKGROUND

Few pediatric cases of coronavirus disease 2019 (COVID-19) have been reported and we know little about the epidemiology in children, although more is known about other coronaviruses. We aimed to understand the infection rate, clinical presentation, clinical outcomes, and transmission dynamics for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in order to inform clinical and public health measures.

METHODS

We undertook a rapid systematic review and narrative synthesis of all literature relating to SARS-CoV-2 in pediatric populations. The search terms also included SARS-CoV and MERS-CoV. We searched 3 databases and the COVID-19 resource centers of 11 major journals and publishers. English abstracts of Chinese-language papers were included. Data were extracted and narrative syntheses conducted.

RESULTS

Twenty-four studies relating to COVID-19 were included in the review. Children appear to be less affected by COVID-19 than adults by observed rate of cases in large epidemiological studies. Limited data on attack rate indicate that children are just as susceptible to infection. Data on clinical outcomes are scarce but include several reports of asymptomatic infection and a milder course of disease in young children, although radiological abnormalities are noted. Severe cases are not reported in detail and there are few data relating to transmission.

CONCLUSIONS

Children appear to have a low observed case rate of COVID-19 but may have rates similar to adults of infection with SARS-CoV-2. This discrepancy may be because children are asymptomatic or too mildly infected to draw medical attention and be tested and counted in observed cases of COVID-19.

Impact of Fundamental Diseases on Patients With COVID-19

OBJECTIVES

In December 2019, a new type of coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appeared in Wuhan, China. Serious outbreaks of coronavirus disease 2019 (COVID-19), related to the SARS-CoV-2 virus, have occurred throughout China and the world. Therefore, we intend to shed light on its potential clinical and epidemiological characteristics.

METHODS

In this retrospective study, we included 50 confirmed fatal cases of SARS-CoV-2 reported on Chinese official media networks from January 16, 2020, to February 5, 2020. All the cases were confirmed by local qualified medical and health institutions. Specific information has been released through official channels. According to the contents of the reports, we recorded in detail the gender, age, first symptom date, death date, primary symptoms, chronic fundamental diseases, and other data of the patients, and carried out analyses and discussion.

RESULTS

In total, 50 fatal cases were reported: median age was 70 y old, and males were 2.33 times more likely to die than females. The median number of days from the first symptom to death was 13, and that length of time tended to be shorter among people aged 65 and older compared with those younger than 65 (12 days vs 17 days; P = 0.046). Therefore, the older patients had fewer number of days from the first symptom to death (r = -0.40; P = 0.012).

CONCLUSIONS

In our study, we found that most of the deaths were elderly men with chronic fundamental diseases, and their COVID-19 progression to death time was shorter. At the same time, we demonstrated that older men are more likely to become infected with COVID-19, and the risk of death is positively correlated with age.

Infectious diseases epidemiology, quantitative methodology, and clinical research in the midst of the COVID-19 pandemic: Perspective from a European country

Starting from historic reflections, the current SARS-CoV-2 induced COVID-19 pandemic is examined from various perspectives, in terms of what it implies for the implementation of non-pharmaceutical interventions, the modeling and monitoring of the epidemic, the development of early-warning systems, the study of mortality, prevalence estimation, diagnostic and serological testing, vaccine development, and ultimately clinical trials. Emphasis is placed on how the pandemic had led to unprecedented speed in methodological and clinical development, the pitfalls thereof, but also the opportunities that it engenders for national and international collaboration, and how it has simplified and sped up procedures. We also study the impact of the pandemic on clinical trials in other indications. We note that it has placed biostatistics, epidemiology, virology, infectiology, and vaccinology, and related fields in the spotlight in an unprecedented way, implying great opportunities, but also the need to communicate effectively, often amidst controversy.

The behaviour of infection, survival and testing effort variables of SARS-CoV-2: A theoretical modelling based on optimization technique

BACKGROUND

The experiences of SARS-CoV-2 are different in nature among the different states of the world. Studies on survival analysis of such pandemic mainly based on differential equation analysis, but the main limitation of such models is non-universal applicability. Consideration of improper functional relation in case of identification, survival and testing effort variables of the disease may be the cause of such non-universal applicability.

METHODS

Present study using optimization techniques try to find the general functional form for the variables like identification of the carrier's and testing effort. The study uses both the discrete and continuous time procedure of optimization technique. The main objective of the study is to institute relation between the identified carrier's and effort taken for identification.

RESULTS

The study considers test as the pseudo variable for effort of identification. The study found that the relationship between test and identified is not a linear one, rather it is nonlinear quadratic type. The study does not go for using data driven methods to verify the results.

Inhibition of SARS-CoV 3CL protease by flavonoids

There were severe panics caused by Severe Acute Respiratory Syndrome (SARS) and Middle-East Respiratory Syndrome-Coronavirus. Therefore, researches targeting these viruses have been required. Coronaviruses (CoVs) have been rising targets of some flavonoids. The antiviral activity of some flavonoids against CoVs is presumed directly caused by inhibiting 3C-like protease (3CLpro). Here, we applied a flavonoid library to systematically probe inhibitory compounds against SARS-CoV 3CLpro. Herbacetin, rhoifolin and pectolinarin were found to efficiently block the enzymatic activity of SARS-CoV 3CLpro. The interaction of the three flavonoids was confirmed using a tryptophan-based fluorescence method, too. An induced-fit docking analysis indicated that S1, S2 and S3' sites are involved in binding with flavonoids. The comparison with previous studies showed that Triton X-100 played a critical role in objecting false positive or overestimated inhibitory activity of flavonoids. With the systematic analysis, the three flavonoids are suggested to be templates to design functionally improved inhibitors.

Seroprevalence of SARS-CoV-2 antibodies in children of United Kingdom healthcare workers: a prospective multicentre cohort study protocol

BACKGROUND

A novel coronavirus SARS-CoV-2 has been responsible for a worldwide pandemic. Children typically have very mild, or no, symptoms of infection. This makes estimations of seroprevalence in children difficult. Research is therefore required to determine the seroprevalence of SARS-CoV-2 antibodies in children. The primary objective of this study is to report the seroprevalence of SARS-CoV-2 IgM and/or IgG antibodies in healthy children at baseline, 2 months and 6 months. This is the only longitudinal UK study of seroprevalence in an exclusively paediatric population. Determining the changing seroprevalence is of vital public health importance and can help inform decisions around the lifting of paediatric specific social distancing measures such as school closures and the cancellation of routine paediatric hospital services.

METHODS AND ANALYSIS

1000 healthy children of healthcare workers aged between 2 and 15 years will be recruited from five UK sites (Belfast, Cardiff, Glasgow, London and Manchester). The children will undergo phlebotomy at baseline, 2 months and 6 months to measure IgM and/or IgG positivity to SARS-CoV-2. A sample size of 675 patients is required to detect a 5% change in seroprevalence at each time point assuming an alpha of 0.05 and a beta of 0.2. Adjusted probabilities for the presence of IgG and/or IgM antibodies and of SARS-CoV-2 infection will be reported using logistic regression models where appropriate.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the London - Chelsea Research Ethics Committee (REC Reference-20/HRA/1731) and the Belfast Health & Social Care Trust Research Governance (Reference 19147TW-SW). Results of this study will be made available as preprints and submitted for publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT0434740; Results.

The recent challenges of highly contagious COVID-19, causing respiratory infections: Symptoms, diagnosis, transmission, possible vaccines, animal models, and immunotherapy

COVID-19 is highly contagious pathogenic viral infection initiated from Wuhan seafood wholesale market of China on December 2019 and spread rapidly around the whole world due to onward transmission. This recent outbreak of novel coronavirus (CoV) was believed to be originated from bats and causing respiratory infections such as common cold, dry cough, fever, headache, dyspnea, pneumonia, and finally Severe Acute Respiratory Syndrome (SARS) in humans. For this widespread zoonotic virus, human-to-human transmission has resulted in nearly 83 lakh cases in 213 countries and territories with 4,50,686 deaths as on 19 June 2020. This review presents a report on the origin, transmission, symptoms, diagnosis, possible vaccines, animal models, and immunotherapy for this novel virus and will provide ample references for the researchers toward the ongoing development of therapeutic agents and vaccines and also preventing the spread of this disease.

The recent challenges of highly contagious COVID-19, causing respiratory infections: Symptoms, diagnosis, transmission, possible vaccines, animal models, and immunotherapy

COVID-19 is highly contagious pathogenic viral infection initiated from Wuhan seafood wholesale market of China on December 2019 and spread rapidly around the whole world due to onward transmission. This recent outbreak of novel coronavirus (CoV) was believed to be originated from bats and causing respiratory infections such as common cold, dry cough, fever, headache, dyspnea, pneumonia, and finally Severe Acute Respiratory Syndrome (SARS) in humans. For this widespread zoonotic virus, human-to-human transmission has resulted in nearly 83 lakh cases in 213 countries and territories with 4,50,686 deaths as on 19 June 2020. This review presents a report on the origin, transmission, symptoms, diagnosis, possible vaccines, animal models, and immunotherapy for this novel virus and will provide ample references for the researchers toward the ongoing development of therapeutic agents and vaccines and also preventing the spread of this disease.

[Human coronaviruses]

Four coronaviruses cause frequent and most often mild respiratory infections in humans: HCoV-OC43, HCoV-229E, HCoV-NL63 and HCoV-HKU 1. In addition to these endemic human coronaviruses, three new coronaviruses of zoonotic origin have emerged in the human population over the past 20 years. SARS-CoV (-1) appeared in 2003, MERS-CoV appeared in 2012, and SARS-CoV-2 appeared in 20l9. These three coronaviruses are the causative agents of a severe respiratory syndrome. The epidemic of the severe acute respiratory syndrome (SARS) due to SARS-CoV-l affected approximately 8,000 individuals and caused approximately 800 deaths but was brought under control within a few months. MERS-CoV has caused more than 2,500 cases since 20l2 with a mortality of around 35 %. SARS-CoV-2 is currently responsible for a major pandemic with significant mortality in the elderly or in patients with underlying diseases.

Neither ACEIs nor ARBs are associated with respiratory distress or mortality in COVID-19 results of a prospective study on a hospital-based cohort

Considerable concern has emerged for the potential harm in the use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor inhibitors (ARBs) in COVID-19 patients, given that ACEIs and ARBs may increase the expression of ACE2 receptors that represent the way for coronavirus 2 to entry into the cell and cause severe acute respiratory syndrome. Assess the effect of ACEI/ARBs on outcome in COVID-19 patients. Hospital-based prospective study. A total of 431 patients consecutively presenting at the Emergency Department and found to be affected by COVID-19 were assessed. Relevant clinical and laboratory variables were recorded, focusing on the type of current anti hypertensive treatment. Outcome variables were NO, MILD, SEVERE respiratory distress (RD) operationally defined and DEATH. Hypertension was the single most frequent comorbidity (221/431 = 51%). Distribution of antihypertensive treatment was: ACEIs 77/221 (35%), ARBs 63/221 (28%), OTHER than ACEIs or ARBs 64/221 (29%). In 17/221 (8%) antihypertensive medication was unknown. The proportion of patients taking ACEIs, ARBs or OTHERs who developed MILD or SEVERE RD was 43/77 (56%), 33/53 (52%), 39/64 (61%) and 19/77 (25%), 16/63 (25%) and 16/64 (25%), respectively, with no statistical difference between groups. Despite producing a RR for SEVERE RD of 2.59 (95% CI 1.93-3.49), hypertension was no longer significant in a logistic regression analysis that identified age, CRP and creatinine as the sole independent predictors of SEVERE RD and DEATH. ACEIs and ARBs do not promote a more severe outcome of COVID-19. There is no reason why they should be withheld in affected patients.

Time-dependent changes in the clinical characteristics and prognosis of hospitalized COVID-19 patients in Wuhan, China: A retrospective study

Cases of coronavirus disease 2019 (COVID-19) have been breaking out around the world recently. However, the dynamic changes in the clinical symptoms and prognosis of COVID-19 patients remain unknown. According to the onset time of initial clinical symptoms, 843 COVID-19 patients admitted between Jan 22 and Feb 14, 2020 were divided into three groups: group A (Jan 21 to Jan 25, n = 324), group B (Jan 26 to Jan 31, n = 358) and group C (Feb 1 to Feb 10, n = 161). Data on the demographics, symptoms, first laboratory results, treatments and outcomes (within 12 days of hospitalization) were collected. The results showed that the median duration from symptom onset to admission shortened over time (13, 10 and 5 days, respectively, p < 0.05). Fewer patients had fever symptoms and bilateral pneumonia in group C than in the group A and B. Laboratory results showed that white blood cell, neutrophil, and platelet counts, lactic acid and D-dimer levels were lower, while lymphocyte, CD3, and CD8 counts were higher in group C. In addition, group C had more mild-moderate cases and fewer severe cases than the other two groups. More importantly, the incidence of complications (18.5%, 14.2% and 11.2%, respectively, p < 0.05) and all-cause mortality (11.7%, 8.4%, and 5.6%, respectively, p < 0.05) decreased over time. The clinical characteristics and prognosis of COVID-19 patients changed over time. Improved prognosis was found at a later stage.

Inference of COVID-19 epidemiological distributions from Brazilian hospital data

Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreover, the mathematical modelling of the pandemic generally. We determine epidemiological distributions for patients hospitalized with COVID-19 using a large dataset (N = 21 000 - 157 000) from the Brazilian Sistema de Informação de Vigilância Epidemiológica da Gripe database. A joint Bayesian subnational model with partial pooling is used to simultaneously describe the 26 states and one federal district of Brazil, and shows significant variation in the mean of the symptom-onset-to-death time, with ranges between 11.2 and 17.8 days across the different states, and a mean of 15.2 days for Brazil. We find strong evidence in favour of specific probability density function choices: for example, the gamma distribution gives the best fit for onset-to-death and the generalized lognormal for onset-to-hospital-admission. Our results show that epidemiological distributions have considerable geographical variation, and provide the first estimates of these distributions in a low and middle-income setting. At the subnational level, variation in COVID-19 outcome timings are found to be correlated with poverty, deprivation and segregation levels, and weaker correlation is observed for mean age, wealth and urbanicity.