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Studying the progress and trend of the novel coronavirus pneumonia (COVID-19) transmission mode will help effectively curb its spread. Some commonly used infectious disease prediction models are introduced. The hybrid model is proposed, which overcomes the disadvantages of the logistic model's inability to predict the number of confirmed diagnoses and the drawbacks of too many tuning parameters of the SEIR (Susceptible, Exposed, Infectious, Recovered) model. The realization and superiority of the prediction of the proposed model are proven through experiments. At the same time, the influence of different initial values of the parameters that need to be debugged on the hybrid model is further studied, and the mean error is used to quantify the prediction effect. By forecasting epidemic size and peak time and simulating the effects of public health interventions, this paper aims to clarify the transmission dynamics of COVID-19 and recommend operation suggestions to slow down the epidemic. It is suggested that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviours are critical to slow down the epidemic. [ABSTRACT FROM AUTHOR]

Globally, public health measures like face masks, hand hygiene and maintaining social distancing have been implemented to delay and reduce local transmission of COVID-19. To date there is emerging evidence to provide effectiveness and compliance to intervention measures on COVID-19 due to rapid spread of the disease. We synthesized evidence of community interventions and innovative practices to mitigate COVID-19 as well as previous respiratory outbreak infections which may share some aspects of transmission dynamics with COVID-19. In the study, we systematically searched the literature on community interventions to mitigate COVID-19, SARS (severe acute respiratory syndrome), H1N1 Influenza and MERS (middle east respiratory syndrome) epidemics in PubMed, Google Scholar, World Health Organization (WHO), MEDRXIV and Google from their inception until May 30, 2020 for up-to-date published and grey resources. We screened records, extracted data, and assessed risk of bias in duplicates. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. This study is registered with PROSPERO (CRD42020183064). Of 41,138 papers found, 17 studies met the inclusion criteria in various settings in Low- and Middle-Income Countries (LMICs). One of the papers from LMICs originated from Africa (Madagascar) with the rest from Asia 9 (China 5, Bangladesh 2, Thailand 2); South America 5 (Mexico 3, Peru 2) and Europe 2 (Serbia and Romania). Following five studies on the use of face masks, the risk of contracting SARS and Influenza was reduced OR 0.78 and 95% CI = 0.36–1.67. Equally, six studies on hand hygiene practices reported a reduced risk of contracting SARS and Influenza OR 0.95 and 95% CI = 0.83–1.08. Further two studies that looked at combined use of face masks and hand hygiene interventions showed the effectiveness in controlling the transmission of influenza OR 0.94 and 95% CI = 0.58–1.54. Nine studies on social distancing intervention demonstrated the importance of physical distance through closure of learning institutions on the transmission dynamics of disease. The evidence confirms the use of face masks, good hand hygiene and social distancing as community interventions are effective to control the spread of SARS and influenza in LMICs. However, the effectiveness of community interventions in LMICs should be informed by adherence of the mitigation measures and contextual factors taking into account the best practices. The study has shown gaps in adherence/compliance of the interventions, hence a need for robust intervention studies to better inform the evidence on compliance of the interventions. Nevertheless, this rapid review of currently best available evidence might inform interim guidance on similar respiratory infectious diseases like Covid-19 in Kenya and similar LMIC context. [ABSTRACT FROM AUTHOR]

The transmission dynamics of the coronavirus—COVID-19—have challenged humankind at almost every level. Currently, research groups around the globe are trying to figure out such transmission dynamics under special conditions such as separation policies enforced by governments. Mathematical and computational models, like the compartmental model or the agent-based model, are being used for this purpose. This paper proposes an agent-based model, called INFEKTA, for simulating the transmission of infectious diseases, not only the COVID-19, under social distancing policies. INFEKTA combines the transmission dynamic of a specific disease, (according to parameters found in the literature) with demographic information (population density, age, and genre of individuals) of geopolitical regions of the real town or city under study. Agents (virtual persons) can move, according to its mobility routines and the enforced social distancing policy, on a complex network of accessible places defined over an Euclidean space representing the town or city. The transmission dynamics of the COVID-19 under different social distancing policies in Bogotá city, the capital of Colombia, is simulated using INFEKTA with one million virtual persons. A sensitivity analysis of the impact of social distancing policies indicates that it is possible to establish a 'medium' (i.e., close 40% of the places) social distancing policy to achieve a significant reduction in the disease transmission. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic model to describe and forecast the dynamics of the coronavirus disease COVID-19 transmission. The model is based on an approach previously used to describe the Middle East Respiratory Syndrome (MERS) epidemic. This methodology is used to describe the COVID-19 dynamics in six countries where the pandemic is widely spread, namely China, Italy, Spain, France, Germany, and the USA. For this purpose, data from the European Centre for Disease Prevention and Control (ECDC) are adopted. It is shown how the model can be used to forecast new infection cases and new deceased and how the uncertainties associated to this prediction can be quantified. This approach has the advantage of being relatively simple, grouping in few mathematical parameters the many conditions which affect the spreading of the disease. On the other hand, it requires previous data from the disease transmission in the country, being better suited for regions where the epidemic is not at a very early stage. With the estimated parameters at hand, one can use the model to predict the evolution of the disease, which in turn enables authorities to plan their actions. Moreover, one key advantage is the straightforward interpretation of these parameters and their influence over the evolution of the disease, which enables altering some of them, so that one can evaluate the effect of public policy, such as social distancing. The results presented for the selected countries confirm the accuracy to perform predictions. [ABSTRACT FROM AUTHOR]

Background: Early identification of a patient with infection who may develop sepsis is of utmost importance. Unfortunately, this remains elusive because no single clinical measure or test can reflect complex pathophysiological changes in patients with sepsis. However, multiple clinical and laboratory parameters indicate impending sepsis and organ dysfunction. Screening tools using these parameters can help identify the condition, such as SIRS, quick SOFA (qSOFA), National Early Warning Score (NEWS), or Modified Early Warning Score (MEWS). We aim to externally validate qSOFA, SIRS, and NEWS/NEWS2/MEWS for in-hospital mortality among adult patients with suspected infection who presenting to the emergency department. Methods and analysis: PASSEM study is an international prospective external validation cohort study. For 9 months, each participating center will recruit consecutive adult patients who visited the emergency departments with suspected infection and are planned for hospitalization. We will collect patients' demographics, vital signs measured in the triage, initial white blood cell count, and variables required to calculate Charlson Comorbidities Index; and follow patients for 90 days since their inclusion in the study. The primary outcome will be 30-days in-hospital mortality. The secondary outcome will be intensive care unit (ICU) admission, prolonged stay in the ICU (i.e., ≥72 hours), and 30- as well as 90-days all-cause mortality. The study started in December 2021 and planned to enroll 2851 patients to reach 200 in-hospital death. The sample size is adaptive and will be adjusted based on prespecified consecutive interim analyses. Discussion: PASSEM study will be the first international multicenter prospective cohort study that designated to externally validate qSOFA score, SIRS criteria, and EWSs for in-hospital mortality among adult patients with suspected infection presenting to the ED in the Middle East region. Study registration: The study is registered at ClinicalTrials.gov (NCT05172479). [ABSTRACT FROM AUTHOR]

In response to the outbreak of the coronavirus disease 2019 (Covid-19), governments worldwide have introduced multiple restriction policies, known as non-pharmaceutical interventions (NPIs). However, the relative impact of control measures and the long-term causal contribution of each NPI are still a topic of debate. We present a method to rigorously study the effectiveness of interventions on the rate of the time-varying reproduction number Rt and on human mobility, considered here as a proxy measure of policy adherence and social distancing. We frame our model using a causal inference approach to quantify the impact of five governmental interventions introduced until June 2020 to control the outbreak in 113 countries: confinement, school closure, mask wearing, cultural closure, and work restrictions. Our results indicate that mobility changes are more accurately predicted when compared to reproduction number. All NPIs, except for mask wearing, significantly affected human mobility trends. From these, schools and cultural closure mandates showed the largest effect on social distancing. We also found that closing schools, issuing face mask usage, and work-from-home mandates also caused a persistent reduction on Rt after their initiation, which was not observed with the other social distancing measures. Our results are robust and consistent across different model specifications and can shed more light on the impact of individual NPIs. [ABSTRACT FROM AUTHOR]

Background: Severe coronavirus disease 2019 (COVID-19) patients frequently require mechanical ventilation (MV) and undergo prolonged periods of bed rest with restriction of activities during the intensive care unit (ICU) stay. Our aim was to address the degree of mobilization in critically ill patients with COVID-19 undergoing to MV support. Methods: Retrospective single-center cohort study. We analyzed patients' mobility level, through the Perme ICU Mobility Score (Perme Score) of COVID-19 patients admitted to the ICU. The Perme Mobility Index (PMI) was calculated [PMI = ΔPerme Score (ICU discharge–ICU admission)/ICU length of stay], and patients were categorized as "improved" (PMI > 0) or "not improved" (PMI ≤ 0). Comparisons were performed with stratification according to the use of MV support. Results: From February 2020, to February 2021, 1,297 patients with COVID-19 were admitted to the ICU and assessed for eligibility. Out of those, 949 patients were included in the study [524 (55.2%) were classified as "improved" and 425 (44.8%) as "not improved"], and 396 (41.7%) received MV during ICU stay. The overall rate of patients out of bed and able to walk ≥ 30 meters at ICU discharge were, respectively, 526 (63.3%) and 170 (20.5%). After adjusting for confounders, independent predictors of improvement of mobility level were frailty (OR: 0.52; 95% CI: 0.29–0.94; p = 0.03); SAPS III Score (OR: 0.75; 95% CI: 0.57–0.99; p = 0.04); SOFA Score (OR: 0.58; 95% CI: 0.43–0.78; p < 0.001); use of MV after the first hour of ICU admission (OR: 0.41; 95% CI: 0.17–0.99; p = 0.04); tracheostomy (OR: 0.54; 95% CI: 0.30–0.95; p = 0.03); use of extracorporeal membrane oxygenation (OR: 0.21; 95% CI: 0.05–0.8; p = 0.03); neuromuscular blockade (OR: 0.53; 95% CI: 0.3–0.95; p = 0.03); a higher Perme Score at admission (OR: 0.35; 95% CI: 0.28–0.43; p < 0.001); palliative care (OR: 0.05; 95% CI: 0.01–0.16; p < 0.001); and a longer ICU stay (OR: 0.79; 95% CI: 0.61–0.97; p = 0.04) were associated with a lower chance of mobility improvement, while non-invasive ventilation within the first hour of ICU admission and after the first hour of ICU admission (OR: 2.45; 95% CI: 1.59–3.81; p < 0.001) and (OR: 2.25; 95% CI: 1.56–3.26; p < 0.001), respectively; and vasopressor use (OR: 2.39; 95% CI: 1.07–5.5; p = 0.03) were associated with a higher chance of mobility improvement. Conclusion: The use of MV reduced mobility status in less than half of critically ill COVID-19 patients. [ABSTRACT FROM AUTHOR]

Background: The available data to determine the chronic obstructive pulmonary disease (COPD) burden in Saudi Arabia are scarce. Therefore, this study closely examines and tracks the trends of the COPD burden in Saudi Arabia from 1990 to 2019 using the dataset of the Global Burden of Disease (GBD) 2019. Methods: This study used the GBD 2019 dataset to analyse the COPD prevalence, incidence, morbidity and mortality rates in the Saudi Arabian population from 1990 to 2019, stratified by sex and age. The age-standardised rate was used to determine the prevalence, incidence, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life years (DALYs) and deaths. Results: In 2019, an estimated 434,560.64 people (95% Uncertainty Interval (UI) 396,011.72–473,596.71) had COPD in Saudi Arabia, corresponding to an increase of 329.82% compared with the number of diagnosed people in 1990 [101,104.05 (95% UI 91,334.4–111,223.91)]. The prevalence rate of COPD increased by 49%, from 1,381.26 (1,285.35–1,484.96) cases per 100,000 in 1990 to 2,053.04 (1918.06–2194.29) cases per 100,000 in 2019, and this trend was higher in males than females. The incidence rate of COPD in 2019 was 145.06 (136.62–154.76) new cases per 100,000, representing an increase of 43.4% from the 1990 incidence rate [101.18 (95.27–107.86)]. In 2019, the DALYs rate was 508.15 (95% UI 434.85–581.58) per 100,000 population. This was higher in males than females, with a 14.12% increase among males. In 2019, YLLs contributed to 63.6% of DALYs due to COPD. The death rate due to COPD was 19.6 (95% UI 15.94–23.39) deaths per 100 000 in 2019, indicating a decrease of 41.44% compared with the death rate in 1990 [33.55 deaths per 100 000 (95% UI 25.13–47.69)]. In 2019, COPD deaths accounted for 1.65% (1.39–1.88) of the total of deaths in Saudi Arabia and 57% of all deaths caused by chronic respiratory diseases. Conclusion: Over the period 1990–2019, the prevalence and incidence of COPD in Saudi Arabia have been steadily rising. Even though COPD morbidity and death rates have been decreasing, they remain higher in men and older age. The holistic assessment and interventions with careful attention to optimising the community-based primary care management, such as screening for early diagnosis, smoking cessation programs and pulmonary rehabilitation, are likely to be the most successful strategies to reduce the burden of COPD in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Background: COVID-19, SARS and MERS are diseases that present an important health burden worldwide. This situation demands resource allocation to the healthcare system, affecting especially middle- and low-income countries. Thus, identifying the main cost drivers is relevant to optimize patient care and resource allocation. Objective: To systematically identify and summarize the current status of knowledge on direct medical hospitalization costs of SARS, MERS, or COVID-19 in Upper-Middle-Income Countries. Methods: We conducted a systematic review across seven key databases (PubMed, EMBASE, BVS Portal, CINAHL, CRD library, MedRxiv and Research Square) from database inception to February 2021. Costs extracted were converted into 2021 International Dollars using the Purchasing Power Parity-adjusted. The assessment of quality was based on the protocol by the BMJ and CHEERS. PROSPERO 2020: CRD42020225757. Results: No eligible study about SARS or MERS was recovered. For COVID-19, five studies presented cost analysis performed in Brazil, China, Iran, and Turkey. Regarding total direct medical costs, the lowest cost per patient at ward was observed in Turkey ($900.08), while the highest in Brazil ($5,093.38). At ICU, the lowest was in Turkey ($2,984.78), while the highest was in China ($52,432.87). Service care was the most expressive (58% to 88%) cost driver of COVID-19 patients at ward. At ICU, there was no consensus between service care (54% to 87%) and treatment (72% to 81%) as key burdens of total cost. Conclusion: Our findings elucidate the importance of COVID-19 on health-economic outcomes. The marked heterogeneity among studies leaded to substantially different results and made challenging the comparison of data to estimate pooled results for single countries or regions. Further studies concerning cost estimates from standardized analysis may provide clearer data for a more substantial analysis. This may help care providers and policy makers to organize care for patients in the most efficient way. [ABSTRACT FROM AUTHOR]

Background: Populations seem to respond differently to the global pandemic of severe acute respiratory syndrome coronavirus 2. Recent studies show individual variability in both susceptibility and clinical response to COVID-19 infection. People with chronic obstructive pulmonary disease (COPD) constitute one of COVID-19 risk groups, being already associated with a poor prognosis upon infection. This study aims contributing to unveil the underlying reasons for such prognosis in people with COPD and the variability in the response observed across worldwide populations, by looking at the genetic background as a possible answer to COVID-19 infection response heterogeneity. Methods: SNPs already associated with susceptibility to COVID-19 infection (rs286914 and rs12329760) and severe COVID-19 with respiratory failure (rs657152 and rs11385942) were assessed and their allelic frequencies used to calculate the probability of having multiple risk alleles. This was performed on a Portuguese case-control COPD cohort, previously clinically characterized and genotyped from saliva samples, and also on worldwide populations (European, Spanish, Italian, African, American and Asian), using publicly available frequencies data. A polygenic risk analysis was also conducted on the Portuguese COPD cohort for the two mentioned phenotypes, and also for hospitalization and survival to COVID-19 infection. Findings: No differences in genetic risk for COVID-19 susceptibility, hospitalization, severity or survival were found between people with COPD and the control group (all p-values > 0.01), either considering risk alleles individually, allelic combinations or polygenic risk scores. All populations, even those with European ancestry (Portuguese, Spanish and Italian), showed significant differences from the European population in genetic risk for both COVID-19 susceptibility and severity (all p-values < 0.0001). Conclusion: Our results indicate a low genetic contribution for COVID-19 infection predisposition or worse outcomes observed in people with COPD. Also, our study unveiled a high genetic heterogeneity across major world populations for the same alleles, even within European sub-populations, demonstrating the need to build a higher resolution European genetic map, so that differences in the distribution of relevant alleles can be easily accessed and used to better manage diseases, ultimately, safeguarding populations with higher genetic predisposition to such diseases. [ABSTRACT FROM AUTHOR]

Background: The global epidemic of novel coronavirus pneumonia (COVID-19) has resulted in substantial healthcare resource consumption. Since patients' hospital length of stay (LoS) is at stake in the process, an investigation of COVID-19 patients' LoS and its risk factors becomes urgent for a better understanding of regional capabilities to cope with COVID-19 outbreaks. Methods: First, we obtained retrospective data of confirmed COVID-19 patients in Sichuan province via National Notifiable Diseases Reporting System (NNDRS) and field surveys, including their demographic, epidemiological, clinical characteristics and LoS. Then we estimated the relationship between LoS and the possibly determinant factors, including demographic characteristics of confirmed patients, individual treatment behavior, local medical resources and hospital grade. The Kaplan-Meier method and the Cox Proportional Hazards Model were applied for single factor and multi-factor survival analysis. Results: From January 16, 2020 to March 4, 2020, 538 human cases of COVID-19 infection were laboratory-confirmed, and were hospitalized for treatment, including 271 (50%) patients aged ≥ 45, 285 (53%) males, and 450 patients (84%) with mild symptoms. The median LoS was 19 (interquartile range (IQR): 14–23, range: 3–41) days. Univariate analysis showed that age and clinical grade were strongly related to LoS (P<0.01). Adjusted multivariate analysis showed that the longer LoS was associated with those aged ≥ 45 (Hazard ratio (HR): 0.74, 95% confidence interval (CI): 0.60–0.91), admission to provincial hospital (HR: 0.73, 95% CI: 0.54–0.99), and severe illness (HR: 0.66, 95% CI: 0.48–0.90). By contrast, the shorter LoS was linked with residential areas with more than 5.5 healthcare workers per 1,000 population (HR: 1.32, 95% CI: 1.05–1.65). Neither gender factor nor time interval from illness onset to diagnosis showed significant impact on LoS. Conclusions: Understanding COVID-19 patients' hospital LoS and its risk factors is critical for governments' efficient allocation of resources in respective regions. In areas with older and more vulnerable population and in want of primary medical resources, early reserving and strengthening of the construction of multi-level medical institutions are strongly suggested to cope with COVID-19 outbreaks. [ABSTRACT FROM AUTHOR]

Background: On 9th January 2020, China CDC reported a novel coronavirus (later named SARS-CoV-2) as the causative agent of the coronavirus disease 2019 (COVID-19). Identifying the first appearance of virus is of epidemiological importance to tracking and mapping the spread of SARS-CoV-2 in a country. We therefore conducted a retrospective observational study to detect SARS-CoV-2 in oropharyngeal samples collected from hospitalized patients with a Severe Acute Respiratory Infection (SARI) enrolled in the DRIVE (Development of Robust and Innovative Vaccine Effectiveness) study in five Italian hospitals (CIRI-IT BIVE hospitals network) (1st November 2019 – 29th February 2020). Objectives: To acquire new information on the real trend in SARS-CoV-2 infection during pandemic phase I and to determine the possible early appearance of the virus in Italy. Materials and methods: Samples were tested for influenza [RT-PCR assay (A/H1N1, A/H3N2, B/Yam, B/Vic)] in accordance with the DRIVE study protocol. Subsequently, swabs underwent molecular testing for SARS-COV-2. [one-step real-time multiplex retro-transcription (RT) PCR]. Results: In the 1683 samples collected, no evidence of SARS-CoV-2 was found. Moreover, 28.3% (477/1683) of swabs were positive for influenza viruses, the majority being type A (358 vs 119 type B). A/H3N2 was predominant among influenza A viruses (55%); among influenza B viruses, B/Victoria was prevalent. The highest influenza incidence rate was reported in patients aged 0–17 years (40.3%) followed by those aged 18–64 years (24.4%) and ≥65 years (14.8%). Conclusions: In Italy, some studies have shown the early circulation of SARS-CoV-2 in northern regions, those most severely affected during phase I of the pandemic. In central and southern regions, by contrast no early circulation of the virus was registered. These results are in line with ours. These findings highlight the need to continue to carry out retrospective studies, in order to understand the epidemiology of the novel coronavirus, to better identify the clinical characteristics of COVID-19 in comparison with other acute respiratory illnesses (ARI), and to evaluate the real burden of COVID-19 on the healthcare system. [ABSTRACT FROM AUTHOR]

Infectious diseases and widespread outbreaks influence different sectors of the economy, including the stock market. In this article, we investigate the effect of EBOV and COVID-19 outbreaks on stock market indices. We employ time-varying and constant bivariate copula methods to measure the dependence structure between the infectious disease equity market volatility index (IEMV) and the stock market indices of several sectors. The results show that the financial and communication services sectors have the highest and the lowest negative dependency on IEMV during the Ebola virus (EBOV) pandemic, respectively. However, the health care and energy sectors have the highest and lowest negative dependency on IEMV during the COVID-19 outbreak, respectively. Therefore, the results confirm the heterogeneous time-varying dependency between infectious diseases and the stock market indices. The finding of our study contributes to the ongoing literature on the impact of disease outbreaks, especially the novel coronavirus outbreak on global large-cap companies in the stock market. [ABSTRACT FROM AUTHOR]

Coronaviruses (CoVs) are a family of viruses that are best known as the causative agents of human diseases like the common cold, Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS) and COVID-19. CoVs spread by human-to-human transmission via droplets or direct contact. There is, however, concern about potential waterborne transmission of SARS-CoV-2, the virus responsible for COVID-19, as it has been found in wastewater facilities and rivers. To date, little is known about the stability of SARS-CoV-2 or any other free coronavirus in aquatic environments. The inactivation of terrestrial CoVs in seawater is rarely studied. Here, we use a porcine respiratory coronavirus (PRCV) that is commonly found in animal husbandry as a surrogate to study the stability of CoVs in natural water. A series of experiments were conducted in which PRCV (strain 91V44) was added to filtered and unfiltered fresh- and saltwater taken from the river Scheldt and the North Sea. Virus titres were then measured by TCID50-assays using swine testicle cell cultures after various incubation times. The results show that viral inactivation of PRCV in filtered seawater can be rapid, with an observed 99% decline in the viral load after just two days, which may depend on temperature and the total suspended matter concentration. PRCV degraded much slower in filtered water from the river Scheldt, taking over 15 days to decline by 99%, which was somewhat faster than the PBS control treatment (T99 = 19.2 days). Overall, the results suggest that terrestrial CoVs are not likely to accumulate in marine environments. Studies into potential interactions with exudates (proteases, nucleases) from the microbial food web are, however, recommended. [ABSTRACT FROM AUTHOR]

Many recent disease outbreaks in humans had a zoonotic virus etiology. Bats in particular have been recognized as reservoirs to a large variety of viruses with the potential to cross-species transmission. In order to assess the risk of bats in Switzerland for such transmissions, we determined the virome of tissue and fecal samples of 14 native and 4 migrating bat species. In total, sequences belonging to 39 different virus families, 16 of which are known to infect vertebrates, were detected. Contigs of coronaviruses, adenoviruses, hepeviruses, rotaviruses A and H, and parvoviruses with potential zoonotic risk were characterized in more detail. Most interestingly, in a ground stool sample of a Vespertilio murinus colony an almost complete genome of a Middle East respiratory syndrome-related coronavirus (MERS-CoV) was detected by Next generation sequencing and confirmed by PCR. In conclusion, bats in Switzerland naturally harbour many different viruses. Metagenomic analyses of non-invasive samples like ground stool may support effective surveillance and early detection of viral zoonoses. [ABSTRACT FROM AUTHOR]

Background: The global pandemic of Coronavirus infectious disease 2019 (COVID-19), caused by SARS-CoV-2, has plunged the world into both social and economic disarray, with vaccines still emerging and a continued paucity of personal protective equipment; the pandemic has also highlighted the potential for rapid emergence of aggressive respiratory pathogens and the need for preparedness. Avian immunoglobulins (IgY) have been previously shown in animal models to protect against new infection and mitigate established infection when applied intranasally. We carried out a proof-of-concept study to address the feasibility of using such antibodies as mucosally-applied prophylaxis against SARS-CoV-2. Methods: Hens were immunized with recombinant S1 spike glycoprotein of the virus, and the resulting IgY was evaluated for binding specificity, inhibition of glycoprotein binding to angiotensin converting enzyme-2 (ACE2) protein (the requisite binding site for the virus), and inhibition of viral replication in Vero cell culture. Results: Titers of anti-S1 glycoprotein IgY were evident in yolks at 14 days post-immunization, peaking at 21 days, and at peak concentrations of 16.8 mg/ml. IgY showed strong and significant inhibition of S1/ACE2 binding interactions, and significantly inhibited viral replication at a concentration of 16.8 mg/ml. Four weeks' collection from eggs of two hens produced a total of 1.55 grams of IgY. Conclusions: In this proof-of-concept study we showed that avian immunoglobulins (IgY) raised against a key virulence factor of the SARS-CoV-2 virus successfully inhibited the critical initial adhesion of viral spike glycoproteins to human ACE2 protein receptors and inhibited viral replication in vitro, in a short period using only two laying hens. We conclude that production of large amounts of IgY inhibiting viral binding and replication of SARS-CoV-2 is feasible, and that incorporation of this or similar material into an intranasal spray and/or other mucosal protecting products may be effective at reducing infection and spread of COVID-19. [ABSTRACT FROM AUTHOR]

Aims: DPP-4 inhibitors are predicted to exert a protective effect on the progression of coronavirus disease 2019 (COVID-19). We conducted this meta-analysis to investigate this hypothesis. Methods: Four databases, namely, PubMed, Web of Science, EMBASE and the Cochrane Library, were used to identify studies on DPP-4 and COVID-19. The outcome indicators were the mortality of COVID-19. Funnel plots, Begg's tests and Egger's tests were used to assess publication bias. Results: Four articles were included with a total of 1933 patients with COVID-19 and type 2 diabetes. The use of DPP-4 inhibitors was negatively associated with the risk of mortality (odds ratio (OR) = 0.58 95% confidence interval (CI), 0.34–0.99). Conclusions: DPP-4 inhibitors may improve the mortality of patients with COVID-19 and type 2 diabetes. As few relevant studies are available, more large-scale studies need to be performed. [ABSTRACT FROM AUTHOR]

A timely detection of patients with tetrahydrobiopterin (BH4) -deficient types of hyperphenylalaninemia (HPABH4) is important for assignment of correct therapy, allowing to avoid complications. Often HPABH4 patients receive the same therapy as phenylalanine hydroxylase (PAH) -deficiency (phenylketonuria) patients—dietary treatment—and do not receive substitutive BH4 therapy until the diagnosis is confirmed by molecular genetic means. In this study, we present a cohort of 30 Russian patients with HPABH4 with detected variants in genes causing different types of HPA. Family diagnostics and biochemical urinary pterin spectrum analyses were carried out. HPABH4A is shown to be the prevalent type, 83.3% of all HPABH4 cases. The mutation spectrum for the PTS gene was defined, the most common variants in Russia were p.Thr106Met—32%, p.Asn72Lys—20%, p.Arg9His—8%, p.Ser32Gly—6%. We also detected 7 novel PTS variants and 3 novel QDPR variants. HPABH4 prevalence was estimated to be 0.5–0.9% of all HPA cases in Russia, which is significantly lower than in European countries on average, China, and Saudi Arabia. The results of this research show the necessity of introducing differential diagnostics for HPABH4 into neonatal screening practice. [ABSTRACT FROM AUTHOR]

Background: SARS-CoV-2 is a rapidly spreading coronavirus responsible for the Covid-19 pandemic, which is characterized by severe respiratory infection. Many factors have been identified as risk factors for SARS-CoV-2, with much early attention being paid to body mass index (BMI), which is a well-known cardiometabolic risk factor. Objective: This study seeks to examine the impact of additional baseline cardiometabolic risk factors including high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), Apolipoprotein A-I (ApoA-I), Apolipoprotein B (ApoB), triglycerides, hemoglobin A1c (HbA1c) and diabetes on the odds of testing positive for SARS-CoV-2 in UK Biobank (UKB) study participants. Methods: We examined the effect of BMI, lipid profiles, diabetes and alcohol intake on the odds of testing positive for SARS-Cov-2 among 9,005 UKB participants tested for SARS-CoV-2 from March 16 through July 14, 2020. Odds ratios and 95% confidence intervals were computed using logistic regression adjusted for age, sex and ancestry. Results: Higher BMI, Type II diabetes and HbA1c were associated with increased SARS-CoV-2 odds (p < 0.05) while HDL-C and ApoA-I were associated with decreased odds (p < 0.001). Though the effect of BMI, Type II diabetes and HbA1c were eliminated when HDL-C was controlled, the effect of HDL-C remained significant when BMI was controlled for. LDL-C, ApoB and triglyceride levels were not found to be significantly associated with increased odds. Conclusion: Elevated HDL-C and ApoA-I levels were associated with reduced odds of testing positive for SARS-CoV-2, while higher BMI, type II diabetes and HbA1c were associated with increased odds. The effects of BMI, type II diabetes and HbA1c levels were no longer significant after controlling for HDL-C, suggesting that these effects may be mediated in part through regulation of HDL-C levels. In summary, our study suggests that baseline HDL-C level may be useful for stratifying SARS-CoV-2 infection risk and corroborates the emerging picture that HDL-C may confer protection against sepsis in general and SARS-CoV-2 in particular. [ABSTRACT FROM AUTHOR]

In the ongoing coronavirus disease 2019 (COVID-19) pandemic, PCR has been widely used for screening patients displaying relevant symptoms. The rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enables prompt diagnosis and the implementation of proper precautionary and isolation measures for the patient. In the present study, we aimed to evaluate the basic assay performance of an innovative PCR system, GeneSoC® (Kyorin Pharmaceutical Co. Ltd., Tokyo, Japan). A total of 1,445 clinical samples were submitted to the clinical laboratory, including confirmed or suspected cases of COVID-19, from February 13 to August 31. Specimen types included nasopharyngeal swabs. The sampling was performed several times for each patient every 2–7 days. Using this system, sequences specific for SARS-CoV-2 RNA could be detected in a sample within 10–15 min using the microfluidic thermal cycling technology. Analytical sensitivity studies showed that GeneSoC® could detect the target sequence of the viral envelope and RNA-dependent RNA-polymerase (RdRp) genes at 5 and 10 copies/μL, respectively. The precision of the GeneSoC® measurements using clinical isolates of the virus at a concentration of 103 copies/μL was favorable for both the genes; within-run repeatability and between-run reproducibility coefficient of variation values were less than 3% and 2%, respectively; and the reproducibility of inter-detection units was less than 5%. Method comparison by LightCycler® 480 showed the positive and negative agreement to be 100% [(174/174) and (1271/1271), respectively]. GeneSoC® proved to be a rapid and reliable detection system for the prompt diagnosis of symptomatic COVID-19 patients and could help reduce the spread of infections and facilitate more rapid treatment of infected patients. [ABSTRACT FROM AUTHOR]

Since its discovery in the Hubei province of China, the global spread of the novel coronavirus SARS-CoV-2 has resulted in millions of COVID-19 cases and hundreds of thousands of deaths. The spread throughout Asia, Europe, and the Americas has presented one of the greatest infectious disease threats in recent history and has tested the capacity of global health infrastructures. Since no effective vaccine is available, isolation techniques to prevent infection such as home quarantine and social distancing while in public have remained the cornerstone of public health interventions. While government and health officials were charged with implementing stay-at-home strategies, many of which had little guidance as to the consequences of how quickly to begin them. Moreover, as the local epidemic curves have been flattened, the same officials must wrestle with when to ease or cease such restrictions as to not impose economic turmoil. To evaluate the effects of quarantine strategies during the initial epidemic, an agent based modeling framework was created to take into account local spread based on geographic and population data with a corresponding interactive desktop and web-based application. Using the state of Massachusetts in the United States of America, we have illustrated the consequences of implementing quarantines at different time points after the initial seeding of the state with COVID-19 cases. Furthermore, we suggest that this application can be adapted to other states, small countries, or regions within a country to provide decision makers with critical information necessary to best protect human health. [ABSTRACT FROM AUTHOR]

Health care workers (HCWs) are at higher risk for SARS-CoV-2 infection and may play a role in transmitting the infection to vulnerable patients and members of the community. This is particularly worrisome in the context of asymptomatic infection. We performed a cross-sectional study looking at asymptomatic SARS-CoV-2 infection in HCWs. We screened asymptomatic HCWs for SARS-CoV-2 via PCR. Complementary viral genome sequencing was performed on positive swab specimens. A seroprevalence analysis was also performed using multiple assays. Asymptomatic health care worker cohorts had a combined swab positivity rate of 29/5776 (0.50%, 95%CI 0.32–0.75) relative to a comparative cohort of symptomatic HCWs, where 54/1597 (3.4%) tested positive for SARS-CoV-2 (ratio of symptomatic to asymptomatic 6.8:1). SARS-CoV-2 seroprevalence among 996 asymptomatic HCWs with no prior known exposure to SARS-CoV-2 was 1.4–3.4%, depending on assay. A novel in-house Coronavirus protein microarray showed differing SARS-CoV-2 protein reactivities and helped define likely true positives vs. suspected false positives. Our study demonstrates the utility of routine screening of asymptomatic HCWs, which may help to identify a significant proportion of infections. [ABSTRACT FROM AUTHOR]

Background: The novel coronavirus (SARS-CoV-2) pandemic spread rapidly worldwide increasing exponentially in Italy. To date, there is lack of studies describing clinical characteristics of the people at high risk of infection. Hence, we aimed (i) to identify clinical predictors of SARS-CoV-2 infection risk, (ii) to develop and validate a score predicting SARS-CoV-2 infection risk, and (iii) to compare it with unspecific scores. Methods: Retrospective case-control study using administrative health-related database was carried out in Southern Italy (Campania region) among beneficiaries of Regional Health Service aged over than 30 years. For each person with SARS-CoV-2 confirmed infection (case), up to five controls were randomly matched for gender, age and municipality of residence. Odds ratios and 90% confidence intervals for associations between candidate predictors and risk of infection were estimated by means of conditional logistic regression. SARS-CoV-2 Infection Score (SIS) was developed by generating a total aggregate score obtained from assignment of a weight at each selected covariate using coefficients estimated from the model. Finally, the score was categorized by assigning increasing values from 1 to 4. Discriminant power was used to compare SIS performance with that of other comorbidity scores. Results: Subjects suffering from diabetes, anaemias, Parkinson's disease, mental disorders, cardiovascular and inflammatory bowel and kidney diseases showed increased risk of SARS-CoV-2 infection. Similar estimates were recorded for men and women and younger and older than 65 years. Fifteen conditions significantly contributed to the SIS. As SIS value increases, risk progressively increases, being odds of SARS-CoV-2 infection among people with the highest SIS value (SIS = 4) 1.74 times higher than those unaffected by any SIS contributing conditions (SIS = 1). Conclusion: Conditions and diseases making people more vulnerable to SARS-CoV-2 infection were identified by the current study. Our results support decision-makers in identifying high-risk people and adopting of preventive measures to minimize the spread of further epidemic waves. [ABSTRACT FROM AUTHOR]

Introduction: Peru is among the top ten countries with the highest number of coronavirus disease 2019 (COVID-19) cases worldwide. The aim of the study was to describe the clinical features of hospitalized adult patients with COVID-19 and to determine the prognostic factors associated with in-hospital mortality. Methods: We conducted a retrospective cohort study among adult patients with COVID-19 admitted to Hospital Cayetano Heredia; a tertiary care hospital in Lima, Peru. The primary outcome was in-hospital mortality. Multivariate Cox proportional hazards regression was used to identify factors independently associated with in-hospital mortality. Results: A total of 369 patients (median age 59 years [IQR:49–68]; 241 (65.31%) male) were included. Most patients (68.56%) reported at least one comorbidity; more frequently: obesity (42.55%), diabetes mellitus (21.95%), and hypertension (21.68%). The median duration of symptoms prior to hospital admission was 7 days (IQR: 5–10). Reported in-hospital mortality was 49.59%. By multiple Cox regression, oxygen saturation (SaO2) values of less than 90% on admission correlated with mortality, presenting 1.86 (95%CI: 1.02–3.39), 4.44 (95%CI: 2.46–8.02) and 7.74 (95%CI: 4.54–13.19) times greater risk of death for SaO2 of 89–85%, 84–80% and <80%, respectively, when compared to patients with SaO2 >90%. Additionally, age >60 years was associated with 1.88 times greater mortality. Conclusions: Oxygen saturation below 90% on admission is a strong predictor of in-hospital mortality in patients with COVID-19. In settings with limited resources, efforts to reduce mortality in COVID-19 should focus on early identification of hypoxemia and timely access to hospital care. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease of 2019 (COVID-19) represents a difficult challenge and could have devastating consequences for the healthcare system and healthcare workers in war-torn countries with poor healthcare facilities such as Yemen. Our study aimed to evaluate the knowledge, preparedness, counselling practices of healthcare workers regarding COVID-19, and the perceived barriers to adequately prevent and control COVID-19 in Yemen. Methods: Healthcare workers (HCWs) from major healthcare facilities participated in this cross-sectional study. A self-administered questionnaire comprising of five main domains (demographics, knowledge, self-preparedness, counselling practice, perceived barriers) was distributed among HCWs after obtaining informed consent. A convenient sampling technique was used. Descriptive and inferential analyses were applied using SPSS software. Results: A total of 1000 participants were initially targeted to participate in the study with 514 (51.4%) responding, of which 55.3% were female. Physicians and nurses constituted the largest proportion of participants, with 39.5% and 33.3%, respectively. The median scores for knowledge, self-preparedness, and counselling practice were 8 (out of 9), 9 (out of 15), and 25 (out of 30), respectively. The physician group showed a statistically significant association with better knowledge compared to the nurse group only, P<0.001. Males had higher preparedness scores than females, p<0.001. Also, the intensive care unit (ICU) and emergency departments presented a statistically significant difference by which the participants from these departments were more prepared compared to the others (e.g. outpatients, paediatrics and surgery) with P < 0.0001. The lack of awareness among the general population about COVID-19 preventive measures was perceived as the most common barrier for the adequate prevention and control of COVID-19 in Yemen (89.1%). Conclusion: The major highlight of this study is that HCWs have, overall, good knowledge, suboptimal preparedness, and adequate counselling practices prior to the outbreak of COVID-19 in Yemen, despite the high number of perceived barriers. However, urgent action and interventions are needed to improve the preparedness of HCWs to manage COVID-19. The perceived barriers also need to be fully addressed by the local healthcare authorities and international organisations working in Yemen for adequate prevention and control measures to be in place in managing COVID-19. [ABSTRACT FROM AUTHOR]

In December 2019, the novel coronavirus pneumonia (COVID-19) occurred in Wuhan, Hubei Province, China. The epidemic quickly broke out and spread throughout the country. Now it becomes a pandemic that affects the whole world. In this study, three models were used to fit and predict the epidemic situation in China: a modified SEIRD (Susceptible-Exposed-Infected-Recovered-Dead) dynamic model, a neural network method LSTM (Long Short-Term Memory), and a GWR (Geographically Weighted Regression) model reflecting spatial heterogeneity. Overall, all the three models performed well with great accuracy. The dynamic SEIRD prediction APE (absolute percent error) of China had been ≤ 1.0% since Mid-February. The LSTM model showed comparable accuracy. The GWR model took into account the influence of geographical differences, with R2 = 99.98% in fitting and 97.95% in prediction. Wilcoxon test showed that none of the three models outperformed the other two at the significance level of 0.05. The parametric analysis of the infectious rate and recovery rate demonstrated that China's national policies had effectively slowed down the spread of the epidemic. Furthermore, the models in this study provided a wide range of implications for other countries to predict the short-term and long-term trend of COVID-19, and to evaluate the intensity and effect of their interventions. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) is a rapidly spreading global pandemic. The clinical characteristics of COVID-19 have been reported; however, there is limited research investigating the clinical characteristics of COVID-19 in the Middle East. This study aims to investigate the clinical, radiological and therapeutic characteristics of patients diagnosed with COVID19 in Saudi Arabia. Methods: This study is a retrospective single-centre case series study. We extracted data for patients who were admitted to the Al-Noor Specialist Hospital with a PCR confirming SARS-COV-2 between 12th and 31st of March 2020. Descriptive statistics were used to describe patients' characteristics. Continuous data were reported as mean ± SD. Chi-squared test/Fisher test were used as appropriate to compare proportions for categorical variables. Results: A total of 150 patients were hospitalised for COVID-19 during the study period. The mean age was 46.1 years (SD: 15.3 years). The most common comorbidities were hypertension (28.8%, n = 42) and diabetes mellitus (26.0%, n = 38). Regarding the severity of the hospitalised patients, 105 patients (70.0%) were mild, 29 (19.3%) were moderate, and 16 patients (10.7%) were severe or required ICU care. Conclusion: This case series provides clinical, radiological and therapeutic characteristics of hospitalised patients with confirmed COVID-19 in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease 2019 (COVID-19) pandemic poses an unprecedented challenge to health-care systems around the world. As approximately one-third of the world´s population is living under "lockdown" conditions, medical resources are being reallocated and hospital admissions are limited to emergencies. We examined the decision-making impact of these actions and their effects on access to hospital treatment in patients with neurosurgical conditions. Methods: This retrospective cohort study analyzes hospital admissions of two major neurosurgical services in Germany during the nationwide lockdown period (March 16th to April 16th, 2020). Spinal or cranial conditions requiring immediate hospital admission and treatment constituted emergencies. Results: A total of 243 in-patients were treated between March 16th and April 16th 2020 (122 patients at the University Medical Center Mainz, 121 patients at the University Medical Center Göttingen). Of these, 38.0±16% qualified as emergency admission. Another 1,688 admissions were reviewed during the same periods in 2018 and 2019, providing a frame of reference. Overall, emergency admissions declined by 44.7±0.7% during lockdown. Admissions for cranial emergencies fell by 48.1±4.44%, spinal emergencies by 30.9±14.6%. Conclusion: Above findings indicate that in addition to postponing elective procedures, emergency admissions were dramatically curtailed during the COVID-19 lockdown. As this surely is unexpected and unintended, reasons are undoubtedly complex. As consequences in morbidity and mortality are still unpredictable, efforts should be made to accommodate all patients in need of hospital access going forward. [ABSTRACT FROM AUTHOR]

Over the past decade, outbreaks of new or reemergent viruses such as severe acute respiratory syndrome (SARS) virus, Middle East respiratory syndrome (MERS) virus, and Zika have claimed thousands of lives and cost governments and healthcare systems billions of dollars. Because the appearance of new or transformed diseases is likely to continue, the detection and characterization of emergent diseases is an important problem. We describe a Bayesian statistical model that can detect and characterize previously unknown and unmodeled diseases from patient-care reports and evaluate its performance on historical data. [ABSTRACT FROM AUTHOR]

Middle East respiratory syndrome-coronavirus (MERS-CoV) is an emerging virus that causes severe disease with fatal outcomes; however, there are currently no approved vaccines or specific treatments against MERS-CoV. Here, we developed a novel bivalent vaccine against MERS-CoV and rabies virus (RV) using the replication-incompetent P-gene-deficient RV (RVΔP), which has been previously established as a promising and safe viral vector. MERS-CoV spike glycoprotein comprises S1 and S2 subunits, with the S1 subunit being a primary target of neutralizing antibodies. Recombinant RVΔP, which expresses S1 fused with transmembrane and cytoplasmic domains together with 14 amino acids from the ectodomains of the RV-glycoprotein (RV-G), was developed using a reverse genetics method and named RVΔP-MERS/S1. Following generation of RVΔP-MERS/S1 and RVΔP, our analysis revealed that they shared similar growth properties, with the expression of S1 in RVΔP-MERS/S1-infected cells confirmed by immunofluorescence and western blot, and the immunogenicity and pathogenicity evaluated using mouse infection experiments. We observed no rabies-associated signs or symptoms in mice inoculated with RVΔP-MERS/S1. Moreover, virus-specific neutralizing antibodies against both MERS-CoV and RV were induced in mice inoculated intraperitoneally with RVΔP-MERS/S1. These findings indicate that RVΔP-MERS/S1 is a promising and safe bivalent-vaccine candidate against both MERS-CoV and RV. [ABSTRACT FROM AUTHOR]

Despite low infectious potential of extrapulmonary tuberculosis (EPTB), it poses significant clinical challenges in terms of diagnosis and treatment monitoring. Understanding the main demographical risk factors for disease characteristics of EPTB plays a crucial role in speeding up diagnosis process and improving overall clinical experience. The aim of this study was to investigate the main demographical and clinical risk factors for EPTB among adults and adolescents for the first time in Saudi Arabia. A cross-sectional multicenter study was carried out on a collection of 902 extrapulmonary Mycobacterium tuberculosis complex (MTBC) isolates with demographical and clinical data. All isolates were subjected to spoligotyping and 24-loci based MIRU-VNTR typing. The association between two potential variables was assessed using odd ratios (OR) calculations. Independent risk factors for EPTB and diseases characteristics of EPTB were identified using multivariate regression model analyses. Gender was found to be significantly associated with lymph node, gastrointestinal, central nervous system and urogenital TB. Lymph node TB showed statistical association to age group below 25 years, non-Saudis and South East Asian ethnicity. While gastrointestinal TB demonstrated an association with patients above 60 years old, and Saudis. Multivariate analysis showed that gender is an independent risk factor to urogenital TB (p 0.03) and lymph node TB (p 0.005). On the other hands, South Asian (p 0.01) and South East Asian (p 0.03) ethnicities were both identified as independent risk factors significantly associated with EPTB. MTBC lineages, site of infections, gender, HIV and smear positivity showed no significant association. Nationwide qualitative-studies are highly warranted in the future to further understand the main demographic risk factors for disease characteristics of EPTB. [ABSTRACT FROM AUTHOR]

The largest nosocomial outbreak of Middle East respiratory syndrome (MERS) occurred in South Korea in 2015. Health Care Personnel (HCP) are at high risk of acquiring MERS-Coronavirus (MERS-CoV) infections, similar to the severe acute respiratory syndrome (SARS)-Coronavirus (SARS-CoV) infections first identified in 2003. This study described the similarities and differences in epidemiological and clinical characteristics of 183 confirmed global MERS cases and 98 SARS cases in Taiwan associated with HCP. The epidemiological findings showed that the mean age of MERS-HCP and total MERS cases were 40 (24~74) and 49 (2~90) years, respectively, much older than those in SARS [SARS-HCP: 35 (21~68) years, p = 0.006; total SARS: 42 (0~94) years, p = 0.0002]. The case fatality rates (CFR) was much lower in MERS-HCP [7.03% (9/128)] or SARS-HCP [12.24% (12/98)] than the MERS-non-HCP [36.96% (34/92), p<0.001] or SARS-non-HCP [24.50% (61/249), p<0.001], however, no difference was found between MERS-HCP and SARS-HCP [p = 0.181]. In terms of clinical period, the days from onset to death [13 (4~17) vs 14.5 (0~52), p = 0.045] and to discharge [11 (5~24) vs 24 (0~74), p = 0.010] and be hospitalized days [9.5 (3~22) vs 22 (0~69), p = 0.040] were much shorter in MERS-HCP than SARS-HCP. Similarly, days from onset to confirmation were shorter in MERS-HCP than MERS-non-HCP [6 (1~14) vs 10 (1~21), p = 0.044]. In conclusion, the severity of MERS-HCP and SARS-HCP was lower than that of MERS-non-HCP and SARS-non-HCP due to younger age and early confirmation in HCP groups. However, no statistical difference was found in MERS-HCP and SARS-HCP. Thus, prevention of nosocomial infections involving both novel Coronavirus is crucially important to protect HCP. [ABSTRACT FROM AUTHOR]

Middle East respiratory syndrome coronavirus (MERS-CoV) is an emerging human pathogen related to SARS virus. In vitro studies indicate this virus may have a broad host range suggesting an increased pandemic potential. Genetic and epidemiological evidence indicate camels serve as a reservoir for MERS virus but the mechanism of cross species transmission is unclear and many questions remain regarding the susceptibility of humans to infection. Deep sequencing data was obtained from the nasal samples of three camels that had been experimentally infected with a human MERS-CoV isolate. A majority of the genome was covered and average coverage was greater than 12,000x depth. Although only 5 mutations were detected in the consensus sequences, 473 intrahost single nucleotide variants were identified. Many of these variants were present at high frequencies and could potentially influence viral phenotype and the sensitivity of detection assays that target these regions for primer or probe binding. [ABSTRACT FROM AUTHOR]

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe acute respiratory failure and considerable extrapumonary organ dysfuction with substantial high mortality. For the limited number of autopsy reports, small animal models are urgently needed to study the mechanisms of MERS-CoV infection and pathogenesis of the disease and to evaluate the efficacy of therapeutics against MERS-CoV infection. In this study, we developed a transgenic mouse model globally expressing codon-optimized human dipeptidyl peptidase 4 (hDPP4), the receptor for MERS-CoV. After intranasal inoculation with MERS-CoV, the mice rapidly developed severe pneumonia and multi-organ damage, with viral replication being detected in the lungs on day 5 and in the lungs, kidneys and brains on day 9 post-infection. In addition, the mice exhibited systemic inflammation with mild to severe pneumonia accompanied by the injury of liver, kidney and spleen with neutrophil and macrophage infiltration. Importantly, the mice exhibited symptoms of paralysis with high viral burden and viral positive neurons on day 9. Taken together, this study characterizes the tropism of MERS-CoV upon infection. Importantly, this hDPP4-expressing transgenic mouse model will be applicable for studying the pathogenesis of MERS-CoV infection and investigating the efficacy of vaccines and antiviral agents designed to combat MERS-CoV infection. [ABSTRACT FROM AUTHOR]

Motivation: Illumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous k-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term “error correction” to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous k-mers in the output reads and preserving the most true k-mers, and we introduce a composite statistic π that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available. Results: We produce trimmed and error-corrected reads that result in assemblies with longer contigs and fewer errors. We compared QuorUM against several published error correctors and found that it is the best performer in most metrics we use. QuorUM is efficiently implemented making use of current multi-core computing architectures and it is suitable for large data sets (1 billion bases checked and corrected per day per core). We also demonstrate that a third-party assembler (SOAPdenovo) benefits significantly from using QuorUM error-corrected reads. QuorUM error corrected reads result in a factor of 1.1 to 4 improvement in N50 contig size compared to using the original reads with SOAPdenovo for the data sets investigated. Availability: QuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at . Contact: . [ABSTRACT FROM AUTHOR]

Rapid and reliable laboratory diagnosis of persons suspected of Middle East respiratory syndrome coronavirus (MERS-CoV) infection is important for timely implementation of infection control practices and disease management. In addition, monitoring molecular changes in the virus can help elucidate chains of transmission and identify mutations that might influence virus transmission efficiency. This was illustrated by a recent laboratory investigation we conducted on an imported MERS-CoV case in Greece. Two oropharyngeal swab specimens were collected on the 1st and 2nd day of patient hospitalization and tested using two real-time RT-PCR (rRT-PCR) assays targeting the UpE and Orf-1a regions of the MERS-CoV genome and RT-PCR and partial sequencing of RNA-dependent RNA polymerase and nucleocapsid genes. Serum specimens were also collected and serological test were performed. Results from the first swab sample were inconclusive while the second swab was strongly positive for MERS-CoV RNA by rRT-PCR and confirmed positive by RT-PCR and partial gene sequencing. Positive serologic test results further confirmed MERS-CoV infection. Full-length nucleocapsid and spike gene coding sequences were later obtained from the positive swab sample. Phylogenetic analysis revealed that the virus was closely related to recent human-derived MERS-CoV strains obtained in Jeddah and Makkah, Saudi Arabia, in April 2014 and dromedary camels in Saudi Arabia and Qatar. These findings were consistent with the patient’s history. We also identified a unique amino acid substitution in the spike receptor binding domain that may have implications for receptor binding efficiency. Our initial inconclusive rRT-PCR results highlight the importance of collecting multiple specimens from suspect MERS-CoV cases and particularly specimens from the lower respiratory tract. [ABSTRACT FROM AUTHOR]

The Middle East respiratory syndrome coronavirus (MERS-CoV), an emerging human coronavirus, causes severe acute respiratory illness with a 35% mortality rate. In light of the recent surge in reported infections we have developed asymmetric five-primer reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays for detection of MERS-CoV. Isothermal amplification assays will facilitate the development of portable point-of-care diagnostics that are crucial for management of emerging infections. The RT-LAMP assays are designed to amplify MERS-CoV genomic loci located within the open reading frame (ORF)1a and ORF1b genes and upstream of the E gene. Additionally we applied one-step strand displacement probes (OSD) for real-time sequence-specific verification of LAMP amplicons. Asymmetric amplification effected by incorporating a single loop primer in each assay accelerated the time-to-result of the OSD-RT-LAMP assays. The resulting assays could detect 0.02 to 0.2 plaque forming units (PFU) (5 to 50 PFU/ml) of MERS-CoV in infected cell culture supernatants within 30 to 50 min and did not cross-react with common human respiratory pathogens. [ABSTRACT FROM AUTHOR]