title: Etiologic Subtypes of Ischemic Stroke in SARS-COV-2 Virus patients

text: Objective: To describe the ischemic stroke etiopathogenesis related to COVID-19 in a cohort of NYC hospitals. Background: Extra-pulmonary involvement of COVID-19 has been reported in the hepatic, renal and hematological systems. Most neurological manifestations are non-focal but few have reported the characteristics of ischemic strokes or investigated its pathophysiology. Methods: Over the last 6 weeks, data from four centers in New York City were collected to review the possible ischemic stroke types seen in COVID-19 positive patients. Their presentation, demographics, other related vascular risk factors, associated laboratory and coagulation markers, as well as imaging and outcomes were collected. Results: In our study, age range of patients was 25-75 with no significant male preponderance. 70% presented for acute hospitalization due the stroke. About a fifth did not have common risk factors for ischemic stroke like diabetes and hypertension. None had history of atrial fibrillation or smoking. 50% had poor outcome with four ending in mortality and one in a critical condition due ARDS. All had high Neutrophil/Lymphocyte ratio except one who demonstrated some neurological recovery. In 70% of our cases, D-dimer levels were collected, and all showed mild to severe elevation. None of the emergent large vessel occlusion (LVO) cases had known cardiac risk factors but two out of five were found to have cardiac abnormalities during the course of their hospitalization. All LVOs had hypercoagulable lab markers especially elevated D-dimer and/or Fibrinogen. The LVO patients were younger and sicker with a median age of 46 and mean NIHSS of 24 as opposed to non-LVOs with a median age of 62 and mean NIHSS of 6 respectively. Conclusion: COVID-19 related ischemic events can be small vessel, branch emboli or large vessel occlusions. The latter is often associated with either a hypercoagulable state or cardio-embolism. Patient outcomes were worse when multi-organ or pulmonary system failure prevailed. Keywords: COVID-19, Acute Ischemic strokes, Emergent Large Vessel Occlusion, Mechanical Thrombectomy


title: Influenza and other respiratory viral infections associated with absence from school among schoolchildren in Pittsburgh, Pennsylvania, USA: a cohort study

text: Background: Information on the etiology and age-specific burden of respiratory viral infections among school-aged children remains limited. Methods: We conducted a cohort study to determine the etiology of ILI (influenza like illness) among 2,519 K-12 students during the 2012-13 influenza season. We obtained nasal swabs from students with ILI-related absences. Generalized linear mixed-effect regressions determined associations of outcomes, including ILI and laboratory-confirmed respiratory virus infection, with school grade and other covariates. Results: Overall, 459 swabs were obtained from 552 ILI-related absences. Respiratory viruses were found in 292 (63.6%) samples. Influenza was found in 189 (41.2%) samples. with influenza B found in 134 (70.9%). Rates of influenza B were significantly higher in grades 1 (10.1%, 95% CI 6.8%-14.4%), 2 (9.7%, 6.6%-13.6%), 3 (9.3%, 6.3%-13.2%), and 4 (9.9%, 6.8%-13.8%) than in kindergarteners (3.2%, 1.5%-6.0%). After accounting for grade, sex and self-reported vaccination status, influenza B infection risk was lower among kindergarteners in half-day programs compared to kindergarteners in full-day programs (OR = 0.19; 95% CI 0.08-0.45). Conclusions: ILI and influenza infection is concentrated in younger schoolchildren. Reduced infection by respiratory viruses is associated with a truncated school day for kindergarteners, but requires further investigation in other grades and populations.


title: Public activities preceding the onset of acute respiratory infection syndromes in adults in England - implications for the use of social distancing to control pandemic respiratory infections.

text: Background: Social distancing measures may reduce the spread of emerging respiratory infections however, there is little empirical data on how exposure to crowded places affects risk of acute respiratory infection. Methods: We used a case-crossover design nested in a community cohort to compare self-reported measures of activities during the week before infection onset and baseline periods. The design eliminates the effect of non-time-varying confounders. Time-varying confounders were addressed by exclusion of illnesses around the Christmas period and seasonal adjustment. Results: 626 participants had paired data from the week before 1005 illnesses and the week before baseline. Each additional day of undertaking the following activities in the prior week was associated with illness onset: Spending more than five minutes in a room with someone (other than a household member) who has a cold (Seasonally adjusted OR 1·15, p=0·003); use of underground trains (1·31, p=0·036); use of supermarkets (1·32, p<0·001); attending a theatre, cinema or concert (1·26, p=0·032); eating out at a café, restaurant or canteen (1·25, p=0·003); and attending parties (1·47, p<0·001). Undertaking the following activities at least once in the previous week was associated with illness onset: using a bus, (aOR 1.48, p=0.049), shopping at small shops (1.9, p<0.002) attending a place of worship (1.81, p=0.005). Conclusions: Exposure to potentially crowded places, public transport and to individuals with a cold increases risk of acquiring circulating acute respiratory infections. This suggests social distancing measures can have an important impact on slowing transmission of emerging respiratory infections.


title: Nonmedical Masks in Public for Respiratory Pandemics: Droplet Retention by Two-Layer Textile Barrier Fully Protects Germ-free Mice from Bacteria in Droplets

text: Due to the shortage of masks during the pandemic, we recently demonstrated that household textiles are effective environmental droplet barriers (EDBs) with identical droplet retention potential as medical masks. To further promote the implementation of a universal community droplet reduction solution based on a synchronized encouragement/enforcement of mask utilization by the public based on widely available textiles (mask fabrication without the need for sewing machines), here we conducted a study using germ-free mice to determine to what extent textiles were effective in vivo. Using a bacterial-suspension spray simulation model of droplet ejection (mimicking a sneeze), we quantified the extent by which 100% cotton textile prevented the contamination of germ-free animals on the other side of the textile-barrier (simulating a properly worn mask). Of relevance, all mice protected with textiles remained germ-free after two sprays (inoculation dose: >600 bacterial droplet units per 56.75cm2) compared to the contamination of mice not protected by a textile (0/12 vs 6/6, Fisher’s exact, p<0.0001). In a second phase of the experiment with 12 germ-free mice exposed again to 10-fold more droplets remained germ-free, while 100% of mice at 180cm became colonized with a single spray (0/8 vs 4/4, Fisher exact, p=0.002). Collectively, barriers protected all mice (even with low-density textiles, heavy vs. light fabric, T-test, p=0.0028) when using textile-EDB to cover the cages (0/20 vs 10/10, Fisher exact, p<0.0001). This study demonstrated, in vivo, that widely available household textiles are 100% effective at preventing contamination of the environment and the exposed animals by microbe-carrying droplets.


title: Age-adjusted associations between comorbidity and outcomes of COVID-19: a review of the evidence

text: Background: Current evidence suggests that older people and people with underlying comorbidities are at increased risk of severe disease and death following hospitalisation with COVID-19. As comorbidity increases with age, it is necessary to understand the age-adjusted relationship between comorbidity and COVID-19 outcomes, in order to enhance planning capabilities and our understanding of COVID-19. Methods: We conducted a rapid, comprehensive review of the literature up to 10 April 2020, to assess the international empirical evidence on the association between comorbidities and severe or critical care outcomes of COVID-19, after accounting for age, among hospitalised patients with COVID-19. Results: After screening 579 studies, we identified seven studies eligible for inclusion and these were synthesised narratively. All were from China. The emerging evidence base mostly indicates that after adjustment for age (and in some cases other potential confounders), obesity, hypertension, diabetes mellitus, chronic obstructive airways disease (COPD), and cancer are all associated with worse outcomes. The largest study, using a large nationwide sample of COVID-19 patients in China, found that those with multiple comorbidities had more than twice the risk of a severe outcome or death compared with patients with no comorbidities, after adjusting for age and smoking (HR=2.59, 95% CI 1.61, 4.17). Conclusions: This review summarises for clinicians, policymakers, and academics the most robust evidence to date on this topic, to inform the management of patients and control measures for tackling the pandemic. Given the intersection of comorbidity with ethnicity and social disadvantage, these findings also have important implications for health inequalities. As the pandemic develops, further research should confirm these trends in other settings outside China and explore mechanisms by which various underlying health conditions increase risk of severe COVID-19.


title: Covid-19 and anxiety: A review of psychological impacts of infectious disease outbreaks

text: Context: The advent of coronavirus disease 2019 (COVID-19) has caused confusion, changed people’s living conditions, including commuting restrictions, fear of disease transmission, and closure of schools and businesses, and brought about devastating psychological impacts, like anxiety. However, most studies only have focused on clinical data. Evidence Acquisition: In this short review, the psychological effects of COVID-19 and its association with anxiety were examined. Accordingly, the electronic databases, including PubMed, Medline, Elsevier, and Science Direct were reviewed for relevant studies that have conducted since 2007. Results: The current study was carried out to indicate that COVID-19 has negative psychological problems other than mortality. A review of the studies performed in other parts of the world showed that COVID-19 has caused several psychological impacts, including increased anxiety. Conclusions: By an increase in the prevalence rate of COVID-19 and its resulted restrictions, the level of anxiety increases, as well; therefore, raising public awareness of the disease and providing positive psychological programs in the media aimed at controlling stress can reduce anxiety in society.


title: Modeling the impact of human mobility and travel restrictions on the potential spread of SARS-CoV-2 in Taiwan

text: Background: As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. Methods: Here, in collaboration with Facebook Data for Good, we built metapopulation models that incorporate human movement data with the goals of identifying the high risk areas of disease spread and assessing the potential effects of local travel restrictions in Taiwan. We compared the impact of intracity vs. intercity travel restrictions on both the total number of infections and the speed of outbreak spread and developed an interactive application that allows users to vary inputs and assumptions. Findings: We found that intracity travel reductions have a higher impact on overall infection numbers than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. We also identified the most highly connected areas that may serve as sources of importation during an outbreak. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Interpretation: In Taiwan, most cases to date were imported or linked to imported cases. To prepare for the potential spread within Taiwan, we utilized Facebook's aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. Both intracity and intercity movement affect outbreak dynamics, with the former having more of an impact on the total numbers of cases and the latter impacting geographic scope. These findings have important implications for guiding future policies for travel restrictions during outbreaks in Taiwan.


title: State-wise estimates of current hospital beds, intensive care unit (ICU) beds and ventilators in India: Are we prepared for a surge in COVID-19 hospitalizations?

text: Background The rapid spread of COVID-19 globally has prompted policymakers to evaluate the capacity of health care infrastructure in their communities. Many hard-hit localities have witnessed a large influx of severe cases that strained existing hospitals. As COVID-19 spreads in India, it is essential to evaluate the country's capacity to treat severe cases. Methods We combined data on public and private sector hospitals in India to produce state level estimates of hospital beds, ICU beds, and mechanical ventilators. Based on the number of public sector hospitals from the 2019 National Health Profile (NHP) of India and the relative proportions of public and private health care facilities from the National Sample Survey (NSS) 75th round (2017-2018), we estimated capacity in each Indian state and union territory (UT). We assumed that 5% of all hospital beds were ICU beds and that 50% of ICU beds were equipped with ventilators. Results We estimated that India has approximately 1.9 million hospital beds, 95,000 ICU beds and 48,000 ventilators. Nationally, resources are concentrated in the private sector (hospital beds: 1,185,242 private vs 713,986 public; ICU beds: 59,262 private vs 35,699 public; ventilators: 29,631 private vs. 17,850 public). Our findings suggest substantial variation in available resources across states and UTs. Conclusion Some projections shave suggested a potential need for approximately 270,000 ICU beds in an optimistic scenario, over 2.8 times the estimated number of total available ICU beds in India. Additional resources will likely be required to accommodate patients with severe COVID-19 infections in India.


African nations step up efforts to prevent spread of coronavirus


docid: vhzwnwpv

title: Functional pathways in respiratory tract microbiome separate COVID-19 from community-acquired pneumonia patients

text: In response to the global pandemic of the last four months, some progress has been made in understanding the molecular-level host interactions of the new coronavirus SARS-CoV-2 responsible for COVID-19. However, when the virus enters the body it interacts not only with the host but also with the micro-organisms already inhabiting the host. Understanding the virus-hostmicrobiome interactions can yield additional insights into the biological processes perturbed by the viral invasion. We carry out a comparative functional analysis of bronchoalveolar lavage fluid of eight COVID-19, twenty-five community-acquired pneumonia (CAP) patients and twenty healthy controls. The resulting functional profiles clearly separate the cohorts, even more sharply than just their corresponding taxonomic profiles. We also detect distinct pathway signatures in the respiratory tract microbiome that consistently distinguish COVID-19 patients from both the CAP and healthy cohorts. These include increased vitamin, drug, nucleotide, and energy metabolism during SARS-CoV-2 infection, contrasted with decreased amino acid and carbohydrate metabolism. This comparative analysis indicates consistent differences in COVID-19 respiratory tract metatranscriptomes compared to CAP and healthy samples.


title: Seroprevalence of IgG antibodies against SARS coronavirus 2 in Belgium: a prospective cross-sectional study of residual samples

text: Background In the first weeks of the COVID-19 epidemic in Belgium, a repetitive national serum collection was set up to monitor age-related exposure through emerging SARS-CoV-2 antibodies. First objective was to estimate the baseline seroprevalence and seroincidence using serial survey data that covered the start of a national lock-down period installed soon after the epidemic was recognized. Methods A prospective serial cross-sectional seroprevalence study, stratified by age, sex and region, started with two collections in April 2020. In residual sera taken outside hospitals and collected by diagnostic laboratories, IgG antibodies against S1 proteins of SARS-CoV-2 were measured with a semi-quantitative commercial ELISA. Seropositivity (cumulative, by age category and sex) and seroincidence over a 3 weeks period were estimated for the Belgian population. Findings In the first collection, IgG antibodies were detected in 100 out of 3910 samples, whereas in the second collection 193 out of 3391 samples were IgG positive. The weighted overall seroprevalence increased from 2.9% (95% CI 2.3 to 3.6) to 6.0% (95% CI 5.1 to 7.1), reflected in a seroincidence estimate of 3.1% (95% CI 1.9 to 4.3). Age-specific seroprevalence significantly increased in the age categories 20-30, 80-90 and [≥]90. No significant sex effect was observed. Interpretation During the start of epidemic mitigation by lockdown, a small but increasing fraction of the Belgian population showed serologically detectable signs of exposure to SARS-CoV-2. Funding This independent researcher-initiated study acknowledges financial support from the Antwerp University Fund, the Flemish Research Fund, and European Horizon 2020.


title: An ecological study of socioeconomic predictors in detection of COVID-19 cases across neighborhoods in New York City

text: Abstract Background: New York City was the first major urban center of the COVID-19 pandemic in the USA. Cases are clustered in the city, with certain neighborhoods experiencing more cases than others. We investigate whether potential socioeconomic factors can explain between-neighborhood variation in the number of detected COVID-19 cases. Methods: Data were collected from 177 Zip Code Tabulation Areas (ZCTA) in New York City (99.9% of the population). We fit multiple Bayesian Besag-York-Mollié (BYM) mixed models using positive COVID-19 tests as the outcome and a set of 10 representative economic, demographic, and health-care associated ZCTA-level parameters as potential predictors. The BYM model includes both spatial and nonspatial random effects to account for clustering and overdispersion. Results: Multiple different regression approaches indicated a consistent, statistically significant association between detected COVID-19 cases and dependent (under 18 or 65+ years old) population, male to female ratio, and median household income. In the final model, we found that an increase of only 1% in dependent population is associated with a 2.5% increase in detected COVID-19 cases (95% confidence interval (CI): 1.6% to 3.4%, p < 0.0005). An increase of 1 male per 100 females is associated with a 1.0% (95% CI: 0.6% to 1.5%, p < 0.0005) increases in detected cases. A decrease of $10,000 median household income is associated with a 2.5% (95% CI: 1.0% to 4.1% p = 0.002) increase in detected COVID-19 cases. Conclusions: Our findings indicate associations between neighborhoods with a large dependent population, those with a high proportion of males, and low-income neighborhoods and detected COVID-19 cases. Given the elevated mortality in aging populations, the study highlights the importance of public health management during and after the current COVID-19 pandemic. Further work is warranted to fully understand the mechanisms by which these factors may have affected the number of detected cases, either in terms of the true number of cases or access to testing.


title: Clinical Utility of SARS-CoV-2 Whole Genome Sequencing in Deciphering Source of Infection

text: The novel coronavirus disease (COVID-19) pandemic caused by SARS-CoV-2 is a major threat to humans. Recently, we encountered two seemingly separate COVID-19 clusters in a tertiary care medical center. Whole viral genome sequencing detected the haplotype of the SARS-CoV-2 genome and the two clusters were successfully distinguished by the viral genome haplotype. Concurrently, there were nine COVID-19 patients clinically unlinked to clusters #1 or #2 that necessitated the determination of the source of infection. Such patients had similar haplotypes to that in cluster #2 but were devoid of two rare mutations characteristic to cluster #2. This suggested that these nine cases of "probable community infection" indeed had community infection and were not derived from cluster #2. Whole viral genome sequencing of SARS-CoV-2 is a powerful measure not only for monitoring the global trend of SARS-CoV-2 but also for identifying the source of infection of COVID-19 at a level of institution.


docid: mylzrvtj

title: Intelligent Fake News Detection: A Systematic Mapping

text: Context: The speed with which the Fake News spread today has encouraged work in various areas to minimize the damage and the public insecurity caused by their proliferation. Objective: To characterize and analyze Fake News threat detection. Method: Systematic Mapping, since the area youthfulness still prevents a complete meta-analysis. Results: The most used algorithms were LSTM (17.14%), Naive-Bayes and Similarity Algorithm (11.43%). Conclusions: There is still the absence of more controlled experiments in the Big Data context. Fake News is a national security problem, requiring effective solutions to combat it. Situations like the Covid-19 virus (coronavirus) reinforce this fact.


title: Magnitude and time-course of excess mortality during COVID-19 outbreak: population-based empirical evidence from highly impacted provinces in northern Italy

text: Background: The real impact of SARS-CoV-2 on overall mortality remains uncertain and surveillance reports attributed to COVID-19 a limited amount of deaths during the outbreak. Aim of this study is to assess the excess mortality (EM) during COVID-19 outbreak in highly impacted areas of northern Italy. Methods: We analyzed data on deaths occurred in the first four months of 2020 in health protection agencies (HPA) of Bergamo and Brescia (Lombardy), building a time-series of daily number of deaths and predicting the daily standardized mortality ratio (SMR) and cumulative number of excess deaths (ED) through a Poisson generalized additive model of the observed counts in 2020, using 2019 data as a reference. Results: We estimated 5740 (95% Credible Set (CS): 5552-5936) ED in the HPA of Bergamo and 3703 (95% CS: 3535 - 3877) in Brescia, corresponding to 2.55 (95% CS: 2.50-2.61) and 1.93 (95% CS: 1.89-1.98) folds increase in the number of deaths. The ED wave started a few days later in Brescia, but the daily estimated SMR peaked at the end of March in both HPAs, roughly two weeks after the introduction of lock-down measures, with significantly higher estimates in Bergamo (9.4, 95% CI: 9.1-9.7). Conclusion: EM was significantly larger than that officially attributed to COVID-19, disclosing its hidden burden likely due to indirect effects on health system. Time-series analyses highlighted the impact of lockdown restrictions, with a lower EM in the HPA where there was a smaller delay between the epidemic outbreak and their enforcement.


title: LAC: How to mitigate against loss of confidentiality in CARES Act

text: When the demise of the federal law and regulation protecting substance use disorder (SUD) treatment record confidentiality was quickly sealed with the passages of the Coronavirus Aid, Relief, and Economic Security (CARES) Act March 27 (see ?CARES Act eliminates most of 42 CFR Part 2,? ADAW, April 6, https://onlinelibrary wiley com/doi/10 1002/adaw 32678), the Legal Action Center (LAC) was right there with patients, as it still is, decrying the loss of this important safeguard Now, however, it's time for the law firm to do what it does best ? work to get the language as good as it can be in what will be the new regulation In an overview of the CARES Act amendments regarding confidentiality released by LAC last week, this important point was made: Those amendments don't take effect until March 27, 2021


title: SS3D: Sequence similarity in 3D for comparison of protein families

text: Homologous proteins are often compared by pairwise sequence alignment, and structure superposition if the atomic coordinates are available. Unification of sequence and structure data is an important task in structural biology. Here, we present Sequence Similarity 3D (SS3D), a new method for integrating sequence and structure information for comparison of homologous proteins. SS3D quantifies the spatial similarity of residues within a given radius of homologous through-space contacts. The spatial alignments are scored using native BLOSUM and PAM substitution matrices. This work details the SS3D approach and demonstrates its utility through case studies comparing members of several protein families: GPCR, p53, kelch, SUMO, and SARS coronavirus spike protein. We show that SS3D can more clearly highlight biologically important regions of similarity and dissimilarity compared to pairwise sequence alignments or structure superposition alone. SS3D is written in C++, and is available with a manual and tutorial at https://github.com/0x462e41/SS3D/.


Structural biology oriented predicative analysis of immunogenic epitopes on SARS-CoV-2 viral sequence by variable algorithms


title: Analysis on prevention plan of coronavirus disease 2019 (COVID-19) by traditional Chinese medicine in various regions/ 各地区中医药预防新型冠状病毒肺炎（COVID-19）方案分析

text: To analyze the prevention plan of traditional Chinese medicine (TCM) issued by different regions after the spread of coronavirus disease 2019 (COVID-19) in Wuhan, Hubei Province, so as to understand the disease from the perspective of TCM and guide the clinical prevention and medication with TCM. The news and notices published on the internet were collected, from the first case of unexplained pneumonia in Wuhan officially reported on December 8, 2019 to February 1, 2020 in Beijing, Tianjin and other regions, and 13 programs of traditional Chinese medicine containing Chinese materia medica prescriptions to prevent COVID-19. Astragalus membranaceus, Yupingfeng Powder and other traditional Chinese medicines and prescriptions were often used in the 13 prevention programs for reinforcing vital qi. The epidemic occurred in winter, and the scheme was adapted to the local conditions. Ophiopogon japonicus, Scrophularia ningpoensis and other traditional Chinese medicine for nourishing yin and moistening dryness were mostly used in eight areas in the north, and Atractylodes lancea, Agastache rugosa and other aromatic dehumidification traditional Chinese medicine were mostly used in five areas in the south, the prevention plan was adapted to local conditions; Different prescriptions were adopted according to the variability of individuals to reflect the principle of suiting measures. In addition, we should also pay attention to the prevention measures such as isolation of pathogens, good living conditions, adjustment of emotions, diet and nutrition, and proper exercise. The prevention of COVID-19 by traditional Chinese medicine should pay attention to invigorating qi, dialectical prevention of drugs according to different climate, different regions and different groups of people, pay attention to comprehensive prevention, and flexibly use various measures to achieve the best prevention effect.


title: COVID-19 Antibody Seroprevalence in Santa Clara County, California

text: Background Addressing COVID-19 is a pressing health and social concern. To date, many epidemic projections and policies addressing COVID-19 have been designed without seroprevalence data to inform epidemic parameters. We measured the seroprevalence of antibodies to SARS-CoV-2 in Santa Clara County. Methods On 4/3-4/4, 2020, we tested county residents for antibodies to SARS-CoV-2 using a lateral flow immunoassay. Participants were recruited using Facebook ads targeting a representative sample of the county by demographic and geographic characteristics. We report the prevalence of antibodies to SARS-CoV-2 in a sample of 3,330 people, adjusting for zip code, sex, and race/ethnicity. We also adjust for test performance characteristics using 3 different estimates: (i) the test manufacturer's data, (ii) a sample of 37 positive and 30 negative controls tested at Stanford, and (iii) a combination of both. Results The unadjusted prevalence of antibodies to SARS-CoV-2 in Santa Clara County was 1.5% (exact binomial 95CI 1.11-1.97%), and the population-weighted prevalence was 2.81% (95CI 2.24-3.37%). Under the three scenarios for test performance characteristics, the population prevalence of COVID-19 in Santa Clara ranged from 2.49% (95CI 1.80-3.17%) to 4.16% (2.58-5.70%). These prevalence estimates represent a range between 48,000 and 81,000 people infected in Santa Clara County by early April, 50-85-fold more than the number of confirmed cases. Conclusions The population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection is much more widespread than indicated by the number of confirmed cases. Population prevalence estimates can now be used to calibrate epidemic and mortality projections.


title: Clinical assessment and validation of a rapid and sensitive SARS-CoV-2 test using reverse-transcription loop-mediated isothermal amplification

text: Amid the enduring COVID-19 pandemic, there is an urgent need for expanded access to rapid and sensitive SARS-CoV-2 testing worldwide. Here we present a simple clinical workflow that uses a sensitive and highly specific colorimetric reverse-transcription loop-mediated isothermal amplification (RT-LAMP) to detect SARS-CoV-2 and takes forty minutes from sample collection to result. This test requires no specialized equipment and costs a few dollars per sample. Nasopharyngeal samples collected in saline were added either directly (unprocessed) to RT-LAMP reactions or first inactivated by a combined chemical and heat treatment step to inhibit RNases and lyse virions and human cells. The specimens were then amplified with two SARS-CoV-2-specific primer sets and an internal specimen control; the resulting color change was visually interpreted. While direct addition of unprocessed specimens to RT-LAMP reactions could reliably detect samples with abundant SARS-CoV-2, the assay sensitivity markedly increased after the addition of an inactivation step. In 62 clinical samples with a wide range of SARS-CoV-2 nucleic acid concentrations, the assay had 87.5% sensitivity and 100% specificity with a limit of detection at least 25 copies/L, making it an ideal test to rule in infection. To increase sensitivity, samples that tested negative for SARS-CoV-2 by direct sample addition could be reflexed to a purification step, to increase the effective per-reaction sample input volume. In 40 purified samples, the assay yielded a 90% sensitivity and 100% specificity, with a limit of detection comparable to commercially available real-time PCR-based diagnostics that have received Emergency Use Authorization (EUA) from the FDA. This test for SARS-CoV-2 can be performed in a range of settings for a fraction of the price of other available tests, with limited equipment, and without relying on over-burdened supply chains to increase overall testing capacity.


title: The role of corticosteroids in the management of critically ill patients with coronavirus disease 2019 (COVID-19): A meta-analysis

text: Objective: There are no controlled studies on the role of systemic corticosteroids (CS) in patients with coronavirus disease 2019 (COVID-19). In the absence of high-quality evidence, understandably the recommendations from various organizations are cautious. Several randomized controlled trials are underway but shall take time to conclude. We therefore undertook a meta-analysis to ascertain the role of CS in the management of critically ill patients with COVID-19. Data Sources: Electronic databases, including Pubmed, Cochrane library and Embase, were searched, using the keywords of interest and the PICO search technique, from inception to 12th April 2020. Study Selection: Studies highlighting the use of CS in coronavirus infection with severe acute respiratory syndrome (SARS), Middle East Respiratory Syndrome (MERS) and COVID-19 were selected based on pre-determined inclusion criteria. Data extraction: Data was extracted into an excel sheet and transferred to comprehensive meta-analysis software version 3, Biostat Inc., Englewood, NJ, USA, for analysis. Data synthesis: Five studies with SARS-CoV-2 infection were included in the meta-analysis. The rate ratio (RR) for mortality in patients with SARS-CoV-2 infection was 1.26 (95% CI: 0.96-1.65, I2: 74.46), indicating lack of benefit of CS therapy on mortality in critically ill patients with COVID-19. The RR for mortality on analysis of the three studies that particularly reported on patients with significant pulmonary compromise secondary to SARS-CoV-2 infection was neutral (RR: 0.91, 95% CI: 0.63-1.33, I2: 63.38). Conclusions: The use of CS in critically ill patients with COVID-19 did not improve or worsen mortality. Pending further information from controlled studies, CS can be used in critically ill patients with COVID-19 with critical illness related corticosteroid insufficiency and moderate to severe ARDS without the risk of increased mortality.


title: Uncertainty Quantification in Epidemiological Models for COVID-19 Pandemic

text: The main goal of this paper is to develop the forward and inverse modeling of the Coronavirus (COVID-19) pandemic using novel computational methodologies in order to accurately estimate and predict the pandemic. This leads to governmental decisions support in implementing effective protective measures and prevention of new outbreaks. To this end, we use the logistic equation and the SIR system of ordinary differential equations to model the spread of the COVID-19 pandemic. For the inverse modeling, we propose Bayesian inversion techniques, which are robust and reliable approaches, in order to estimate the unknown parameters of the epidemiological models. We use an adaptive Markov-chain Monte-Carlo (MCMC) algorithm for the estimation of a posteriori probability distribution and confidence intervals for the unknown model parameters as well as for the reproduction number. Furthermore, we present a fatality analysis for COVID-19 in Austria, which is also of importance for governmental protective decision making. We perform our analyses on the publicly available data for Austria to estimate the main epidemiological model parameters and to study the effectiveness of the protective measures by the Austrian government. The estimated parameters and the analysis of fatalities provide useful information for decision makers and makes it possible to perform more realistic forecasts of future outbreaks.


title: Immunity Passports for SARS-CoV-2: an online experimental study of the impact of antibody test terminology on perceived risk and behaviour

text: Objective: To assess the impact of describing an antibody-positive test result using the terms Immunity and Passport or Certificate, alone or in combination, on perceived risk of becoming infected with SARS-CoV-2 and intention to continue protective behaviours. Design: 2 by 3 experimental design. Setting: Online with data collected between 28th April and 1st May 2020. Participants: 1,204 adults registered with a UK research panel. Intervention: Participants were randomised to receive one of six descriptions of an antibody test and results showing SARS-CoV-2 antibodies, differing in the terms used to describe the type of test (Immunity vs Antibody) and the test result (Passport vs Certificate vs Test). Main outcome measures: The primary outcome was the proportion of participants perceiving no risk of becoming infected with SARS-CoV-2 given an antibody positive test result. Other outcomes include intended changes to frequency of hand washing and physical distancing. Results: When using the term Immunity (vs Antibody), 19.1% of participants [95% CI: 16.1 to 22.5] (vs 9.8% [95% CI: 7.5 to 12.4]) perceived no risk of catching coronavirus at some point in the future given an antibody-positive test result (AOR: 2.91 [95% CI: 1.52 to 5.55]). Using the terms Passport or Certificate, as opposed to Test, had no significant effect (AOR: 1.24 [95% CI: 0.62 to 2.48] and AOR: 0.96 [95% CI: 0.47 to 1.99] respectively). There was no significant interaction between the effects of the test and result terminology. Across groups, perceiving no risk of infection was associated with an intention to wash hands less frequently (AOR: 2.32 [95% CI: 1.25 to 4.28]) but there was no significant association with intended avoidance of physical contact with others outside of the home (AOR: 1.37 [95% CI: 0.93 to 2.03]). Conclusions: Using the term Immunity (vs Antibody) to describe antibody tests for SARS-CoV-2 increases the proportion of people believing that an antibody-positive result means they have no risk of catching coronavirus in the future, a perception that may be associated with less frequent hand washing. The way antibody testing is described may have implications for the likely impact of testing on transmission rates.


title: WHO-INTEGRATE COVID framework Version 1.0: Criteria and considerations to guide evidence-informed decision-making on non-pharmacological interventions targeting COVID-19

text: Background: Decision-making on matters of public health requires the balancing of numerous, often conflicting factors. One approach to ensure relevancy and comprehensiveness of the criteria underpinning the decision is a broad societal discourse and participatory decision-making process. However, this often was not feasible within the time constraints imposed on by the SARS-CoV-2 pandemic. While not able or intended to replace stakeholder participation, evidence-to-decision frameworks can serve as a tool to approach relevancy and comprehensiveness of the criteria considered, even if not all voices of affected stakeholders could be heard in the process. Objective: The objective of this research project was to develop a decision-making framework adapted to the challenges decision-makers face when deliberating on national and sub-national level on non-pharmacological interventions (NPIs) measures to address the global SARS-CoV-2 pandemic. Methods: We used the WHO-INTEGRATE framework Version 1.0 as a starting point. In phase I, we adapted the framework through brainstorming exercises and application to exemplary case studies. In phase II, we used the best-fit framework synthesis technique with the output of phase I serving as a priori framework. We conducted a content analysis of comprehensive strategy documents intended to guide the policy makers on the phasing out of the lockdown measures in Germany. Based on factors and criteria identified in this process, we adapted previous versions into the WHO-INTEGRATE COVID framework (WICID framework) Version 1.0. Results: Twelve comprehensive strategy documents were included in the content analysis. The revised WICID framework consists of eleven criteria, which are expanded on through 49 aspects contained within them, and the metacriterion quality of evidence. The criteria cover implications for the health of individuals and populations due to and beyond COVID-19, infringement on liberties and fundamental rights, acceptability considerations, societal, environmental, and economic implications, as well as resource and feasibility considerations. Discussion: In a third phase, the framework will be expanded through a comprehensive document analysis focusing on key-stakeholder groups across the society. The WICID framework V1.0 can be a tool to support comprehensive evidence-informed decision-making processes.


docid: ieaaoxmg

title: A vulnerability index for COVID-19: spatial analysis to inform equitable response in Kenya

text: Background: Response to the COVID-19 pandemic calls for precision public health reflecting our improved understanding of who is the most vulnerable and their geographical location. We created three vulnerability indices to identify areas and people who require greater support while elucidating health inequities to inform emergency response in Kenya. Methods: Geospatial indicators were assembled to create three vulnerability indices; social (SVI), epidemiological (EVI) and a composite of the two (SEVI) resolved at 295 sub-counties in Kenya. SVI included nineteen indicators that affect the spread of disease; socio-economic inequities, access to services and population dynamics while EVI comprised five indicators describing comorbidities associated with COVID-19 severe disease progression. The indicators were scaled to a common measurement scale, spatially overlaid via arithmetic mean and equally weighted. The indices were classified into seven classes, 1-2 denoted low-vulnerability and 6-7 high-vulnerability. The population within vulnerabilities classes was quantified. Results: The spatial variation of each index was heterogeneous across Kenya. Forty-nine north-western and partly eastern sub-counties (6.9 m people) were highly vulnerable while 58 sub-counties (9.7 m people) in western and central Kenya were the least vulnerable for SVI. For EVI, 48 sub-counties (7.2 m people) in central and the adjacent areas and 81 sub-counties (13.2 m people) in northern Kenya were the most and least vulnerable respectively. Overall (SEVI), 46 sub-counties (7.0 m people) around central and south-eastern were more vulnerable while 81 sub-counties (14.4 m people) that were least vulnerable. Conclusion: The vulnerability indices created are tools relevant to the county, national government and stakeholders for prioritization and improved planning especially in highly vulnerable sub-counties where cases have not been confirmed. The heterogeneous nature of the vulnerability highlights the need to address social determinants of health disparities, strengthen the health system and establish programmes to cushion against the negative effects of the pandemic.


title: RNA binding regulates TRIM25-mediated RIG-I ubiquitylation

text: TRIM25 is a ubiquitin E3 ligase active in innate immunity and cell fate decisions. Mounting evidence suggests that TRIM25’s E3 ligase activity is regulated by RNAs. However, while mutations affecting RNA-binding have been described, the precise RNA binding site has not been identified nor which domains are involved. Here, we present biophysical evidence for the presence of RNA binding sites on both TRIM25 PRY/SPRY and coiled-coil domains, and map the binding site on the PRY/SPRY with residue resolution. Cooperative RNA-binding of both domains enhances their otherwise transient interaction in solution and increases the E3 ligase activity of TRIM25. Mutational analysis shows that RNA binding affects ubiquitination of RIG-I in mammalian cells. In addition, we present a simple model system for RNA-induced liquid-liquid phase separation of TRIM25 in vitro, resembling previously observed cellular RNA granules, that facilitates the recruitment of RIG-I.


title: Social distance and SARS memory: impact on the public awareness of 2019 novel coronavirus (COVID-19) outbreak

text: This study examines publicly available online search data in China to investigate the spread of public awareness of the 2019 novel coronavirus (COVID-19) outbreak. We found that cities that suffered from SARS and have greater migration ties to the epicentre, Wuhan, had earlier, stronger and more durable public awareness of the outbreak. Our data indicate that forty-eight such cities developed awareness up to 19 days earlier than 255 comparable cities, giving them an opportunity to better prepare. This study suggests that it is important to consider memory of prior catastrophic events as they will influence the public response to emerging threats.


title: Relationship Between Blood Group and Risk of Infection and Death in COVID-19: a live Meta-Analysis

text: Introduction: The relationship between ABO blood group and the incidence of COVID-19 infection and death has been investigated in several studies. The reported results were controversial, so the objective of the present study is to assess the relationship between different blood groups and the onset and mortality of COVID-19 infection using meta-analysis method. Methods: We searched the databases using appropriate MeSH terms. We screened articles on the basis of titles, abstracts, and full texts and the articles that met the inclusion criteria were selected. Quality assessment was done with the Newcastle-Ottawa Scale checklist. The estimated frequency of COVID-19 infection and death in terms of ABO blood group and the overall estimate of the odd ratio between blood group with COVID-19 infection and death was done with 95% confidence interval. Results: The pooled frequency of blood groups A, B, O, and AB among COVID-19 infected individuals was estimated as 36.22%, 24.99%, 29.67%, and 9.29% respectively. The frequency of blood groups A, B, O, and AB among the dead cases due to COVID-19 infection was estimated as 40%, 23%, 29%, and 8% respectively. The odd ratio of COVID-19 infection for blood group A versus the other blood groups was estimated 1.16 (CI 95%: 1.02-1.33). The corresponding figures for blood groups O and AB versus other blood groups were estimated as 0.73 (CI 95%: 0.60-0.88) and 1.25(CI 95%: 0.84-1.86) respectively. Conclusion: This meta-analysis showed that individuals with blood group A are at higher risk for COVID-19 infection while those with blood group O are at lower risk. Although the odds ratio of death for AB blood group was non-significant, it was considerable.


title: Research updates of diagnosis and treatment of COVID-19/ 新型冠状病毒肺炎诊治研究进展

text: From December 2019, the outbreak of corona virus disease 2019 (COVID-19) hits Hubei Province of China. It causes severe acute respiratory syndrome in some patients and notable number of cases died of multiple organ failures. SARS-CoV-2 mainly spread by respiratory droplets and close contact. It is highly infectious and has been found in many countries and regions around the world. So far, no specific vaccine and specific drugs against SARS-CoV-2 have been developed for clinical use. This article reviews the virological characteristics, clinical symptoms, infection mechanism, epidemiology, research progress and clinical effect of COVID-19. It could provide new insights for clinical prevention of COVID-19.


title: Potential of DNA intercalating alkaloids and other plant secondary metabolites against SARS-CoV-2 causing COVID-19

text: Many plants produce secondary metabolites (PSMs) with antiviral activities. Among the antiviral PSMs, lipophilic terpenoids in essential oils can disturb the lipid envelope of viruses. Phenols and polyphenols (flavonoids, rosmarinic acid and tannins) attack viral proteins present in the viral membrane or inside the virus particle. Both phenolics and essential oils are active against free viral particles but not-or to a lesser degree-after a virus has entered a host cell. Another group of PSMs is directed against DNA or RNA. These are DNA intercalators such as sanguinarine, berberine, emetine and other isoquinoline alkaloids, ss-carboline, and quinoline alkaloids such as quinine, cinchonine, dictamine and skimmianine. The DNA intercalators stabilize double-stranded nucleic acids and inhibit the replication, transcription, and translation of genetic material. These alkaloids can inhibit viral development and viral replication in cells, as shown for SARS-CoV-1 and other viruses. Since chloroquine (which is also a DNA intercalator and a chemical derivative of the alkaloid quinine) is apparently clinically helpful against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, it is assumed that intercalating alkaloids, or the medicinal plants producing them, may be interesting candidates for the development of new antiviral drugs for the treatment of coronavirus disease 2019 (COVID-19).


title: Novel Spatiotemporal Feature Extraction Parallel Deep Neural Network for Forecasting Confirmed Cases of Coronavirus Disease 2019

text: The coronavirus disease 2019 pandemic continues as of March 26 and spread to Europe on approximately February 24. A report from April 29 revealed 1.26 million confirmed cases and 125 928 deaths in Europe. This study proposed a novel deep neural network framework, COVID-19Net, which parallelly combines a convolutional neural network (CNN) and bidirectional gated recurrent units (GRUs). Three European countries with severe outbreaks were studied Germany, Italy, and Spain to extract spatiotemporal feature and predict the number of confirmed cases. The prediction results acquired from COVID-19Net were compared to those obtained using a CNN, GRU, and CNN-GRU. The mean absolute error, mean absolute percentage error, and root mean square error, which are commonly used model assessment indices, were used to compare the accuracy of the models. The results verified that COVID-19Net was notably more accurate than the other models. The mean absolute percentage error generated by COVID-19Net was 1.447 for Germany, 1.801 for Italy, and 2.828 for Spain, which were considerably lower than those of the other models. This indicated that the proposed framework can accurately predict the accumulated number of confirmed cases in the three countries and serve as a crucial reference for devising public health strategies.


title: Analysis of Ten Microsecond simulation data of SARS-CoV-2 dimeric main protease

text: The authors have withdrawn this manuscript because of a violation of research ethics. Unknown to the first author, the corresponding author - the main designer of the project - did not obtain consent for the use of a data-set. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author”


title: The ability of single genes vs full genomes to resolve time and space in outbreak analysis

text: Inexpensive pathogen genome sequencing has had a transformative effect on the field of phylodynamics, where ever increasing volumes of data have promised real-time insight into outbreaks of infectious disease. As well as the sheer volume of pathogen isolates being sequenced, the sequencing of whole pathogen genomes, rather than select loci, has allowed phylogenetic analyses to be carried out at finer time scales, often approaching serial intervals for infections caused by rapidly evolving RNA viruses. Despite its utility, whole genome sequencing of pathogens has not been adopted universally and targeted sequencing of loci is common in some pathogen-specific fields. In this study we aim to highlight the utility of sequencing whole genomes of pathogens by re-analysing a well-characterised collection of Ebola virus sequences in the form of complete viral genomes (~19kb long) or the rapidly evolving glycoprotein (GP, ~2kb long) gene. We quantify changes in phylogenetic, temporal, and spatial inference resolution as a result of this reduction in data and compare these to theoretical expectations. We propose a simple intuitive metric for quantifying temporal resolution, i.e. the time scale over which sequence data might be informative of various processes as a quick back-of-the-envelope calculation of statistical power available to molecular clock analyses.


title: Investigation of potential Chinese materia medica and its monomers in treatment of coronavirus disease 2019 (COVID-19) based on angiotensin converting enzyme II (ACE2) receptor/ 以血管紧张素转换酶II（ACE2）为受体挖掘治疗新型冠状病毒肺炎（COVID-19）潜在中药及单体成分

text: Objective: To investigate the mechanism of treating COVID-19 with traditional Chinese medicine and monomers with ACE2 as receptor. Methods： Chinese materia medica and monomers acting on angiotensin converting enzyme II (ACE2) receptor was retrieved by TCMSP database. UniProt, GeneCards and other databases were used to query the gene names corresponding to the target of Chinese medicine monomer, and then Cytoscape 3.6.1 was used to construct the compound-target (gene) network. DAVID was used to carry out the gene ontology (GO) functional enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis to predict its mechanism of action. Results： There were 54 targets in the puerarin-target network, including AKT1, VEGFA, TNF, etc. GO function enrichment analysis revealed 554 GO items (P < 0.05), including 486 biological process (BP) items, 26 cell component (CC) items, and 42 molecular function (MF) items. There were 162 signaling pathways (P < 0.05) involved in small cell lung cancer, non-small cell lung cancer, renin-angiotensin system pathway, etc. The results of molecular docking showed that the affinity of puerarin with ACE2 and hydrolase of SARS-CoV-2 was similar to the recommended drugs. Conclusion: Puerarin may regulate multiple signaling pathways by binding ACE2 to AGTR1, NOS3, HIF1A and other targets and regulating multiple signaling pathways, which may have therapeutic effects on COVID-19.


title: Planning for the aftershocks: a model of post-acute care needs for hospitalized COVID-19 patients

text: Since its emergence in late 2019, COVID-19 has caused significant global morbidity and mortality, overwhelming health systems. Considerable attention has been paid to the burden COVID-19 has put on acute care hospitals, with numerous models projecting hospitalizations and ICU needs for the duration of the pandemic. However, less attention has been paid to where these patients may go if they require additional care following hospital discharge. As COVID-19 patients recover from severe infections, many of them require additional care. Yet with post-acute care facilities averaging 85% capacity prior to the pandemic and the significant potential for outbreaks, consideration of the downstream effects of the surge of hospitalized COVID-19 patients is critical. Here, we present a method for projecting COVID-19 post-acute care needs. Our model is designed to take the output from any of the numerous epidemiological models (hospital discharges) and estimate the flow of patients to post-acute care services, thus providing a similar surge planning model for post-acute care services. Using data from the University of Utah Hospital, we find that for those who require specialized post-acute care, the majority require either home health care or skilled nursing facilities. Likewise, we find the expected peak in post-acute care occurs about two weeks after the expected peak for acute care hospitalizations, a result of the duration of hospitalization. This short delay between acute care and post-acute care surges highlights the importance of considering the organization necessary to accommodate the influx of recovering COVID patients and protect non-COVID patients prior to the peak in acute care hospitalizations. We developed this model to guide policymakers in addressing the "aftershocks" of discharged patients requiring further supportive care; while we only show the outcomes for discharges based on preliminary data from the University of Utah Hospital, we suggest alternative uses for our model including adapting it to explore potential alternative strategies for addressing the surge in acute care facilities during future pandemic waves.


title: Targeted Proteomics for the Detection of SARS-CoV-2 Proteins

text: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The rapid, sensitive and specific diagnosis of SARS-CoV-2 by fast and unambiguous testing is widely recognized to be critical in responding the current outbreak. Since the current testing capacity by conventional PCR based methods is insufficient because of shortages of supplies such as RNA extraction kits and PCR reagents, alternative and/or complementary testing assays should be developed. Here, we exploit the potential of targeted mass spectrometry based proteomic technologies to solve the current issue of insufficient SARS-CoV-2 diagnostic testing capacity. We have assessed the limit of detection by parallel reaction monitoring (PRM) on an Orbitrap Eclipse mass spectrometer for target tryptic peptides of several SARS-CoV-2 proteins from a sample of virus infected Vero cells. For Nucleocapsid protein the limit of detection was found to be in the mid-attomole range (0.9 × 10−12 g), which would theoretically correspond to approximately 10,000 SARS-CoV-2 particles, under the assumption that all viral proteins are assembled in macromolecular virus particles. Whether or not this sensitivity is sufficient to play a role in SARS-CoV-2 detection in patient material such as swabs or body fluids largely depends on the amount of viral proteins present in such samples and is subject of further research. If yes, mass spectrometry based methods could serve as a complementary protein based diagnostic tool and further steps should be focused on sample preparation protocols and on improvements in sample throughput.


title: Social Disadvantage, Politics, and SARS-CoV-2 Trends: A County-Level Analysis of United States Data

text: Background: Understanding the epidemiology of SARS-CoV-2 is essential for public health control efforts. Social, demographic, and political characteristics at the US county level might be associated with the trajectories of SARS-CoV-2 case incidence. Objective: To understand how underlying social, demographic, and political characteristics at the US county level might be associated with the trajectories of SARS-CoV-2 case incidence. Design: Retrospective analysis of the trajectory of reported SARS-CoV-2 case counts at the US county level during June 1, 2020 - June 30,2020 and social, demographic, and political characteristics of the county. Setting: United States. Participants: Reported SARS-CoV-2 cases. Exposures: Metropolitan designation, Social Deprivation Index (SDI), 2016 Republican Presidential Candidate Victory. Main Outcomes and Measures: SARS-CoV-2 case incidence. Results: 1023/3142 US counties were included in the analysis. 678 (66.3%) had increasing SARS-CoV-2 case counts between June 1 - June 30, 2020. In univariate analysis, counties with increasing case counts had a significantly higher SDI (median 48, IQR 24 - 72) than counties with non-increasing case counts (median 40, IQR 19 - 66; p=0.009). In the multivariable model, metropolitan areas of 250,000 - 1 million population, higher percentage of Black residents and a 10-point or greater Republican victory were independently associated with increasing case counts. Limitations: The data examines county-level voting patterns and does not account for individual voting behavior, subjecting this work to the potential for ecologic fallacy. Conclusion: Increasing case counts of SARS-CoV-2 in the US are likely driven by a combination of social disadvantage, social networks, and behavioral factors. Addressing social disadvantage and differential belief systems that may correspond with political alignment will be essential for pandemic control.


title: Regenerative tourism needs diverse economic practices

text: Calls for a new relationship between tourism and capitalism have intensified as a result of COVID-19. The pandemic has exposed massive vulnerabilities in the tourism operating system, the effects of which have fallen unevenly across different groups and subsectors of tourism. Critics have been quick to point out capitalism’s emphasis on resource exploitation, growth and profit is to blame and that tourism destinations have never been encouraged to foster diverse economic practices which would enhance resilient communities and regenerative tourism. The diverse economies framework envisages the co-existence of capitalist, alternative capitalist and non-capitalist practices and provides a pathway to more resilient and regenerative tourism practices in tourism. Tourism industry cases are used to illustrate the innovation inherent in diverse economic practices (enterprise, exchange, labour, transactions, property etc.) and illustrate their natural resilience as a result. Post COVID-19, a regenerative tourism that incorporates diverse economic practices will guide tourism practices worldwide to withstand future exigencies.


title: Diagnostic accuracy of a host response point-of-care test for identifying COVID-19

text: Rationale Management of the COVID-19 pandemic is hampered by long delays associated with centralised laboratory PCR testing. In hospitals this leads to poor patient flow and nosocomial transmission and rapid, accurate diagnostic tests are urgently required. The FebriDx is a point-of-care test that detects an antiviral host response protein in finger prick blood within 10 minutes, but its accuracy for the detection of COVID-19 is unknown. Objectives To evaluate the diagnostic accuracy of FebriDx in hospitalised patients during the first wave of the pandemic. Methods Measures of diagnostic accuracy were calculated based on FebriDx results compared to the reference standard of PCR, and stratified by duration of symptoms. A multivariable predictive model was developed and underwent internal validation. Results FebriDx was performed on 251 patients and gave a valid result in 248. 118 of 248 (48%) were PCR positive for COVID-19. Sensitivity of FebriDx for the identification of COVID-19 was 93% (110/118; 95% CI 87 to 97%) and specificity was 86% (112/130; 95%CI 79 to 92%). Positive and negative likelihood ratios were 6.73 (95%CI 4.37 to 10.37) and 0.08 (95%CI 0.04 to 0.15) respectively. In the multivariate model diagnosis of COVID-19 was not significantly influenced by clinical symptoms and signs, and FebriDx accuracy was not improved by restricting testing to those with duration of symptoms of less than seven days. Conclusions During the first wave of the pandemic, FebriDx had high sensitivity for the identification of COVID-19 in hospitalised adults and could be deployed as a front door triage tool.


title: The First Wave of COVID-19 in Israel - Initial Analysis of Publicly Available Data

text: The first case of COVID-19 was confirmed in Israel on February 21, 2020. Within approximately 30 days, the total number of confirmed cases climbed up to 1,000, accompanied by a doubling period of less than 3 days. About one week later, after this number exceeded 4,000 cases, and following some extremely strict measures taken by the Israeli government, the daily detection rate started a sharp decrease from the peak value of 1,131 down to slightly more than 100 new confirmed cases on April 30. Motivated by this encouraging data, similar to the trends observed in many other countries, along with the growing economic pressures, the Israeli government started relaxing its emergency regulations as part of an "exit strategy". This article attempts to analyze the currently available data on Israel and a country of similar size (Sweden) in order to understand the local dynamics of COVID-19, assess the effect of the implemented intervention measures, and discuss some plausible scenarios for the foreseeable future.


title: Modeling the COVID-19 outbreak in the United States

text: The COVID-19 contagion has developed at an alarming rate in the US and as of April 24, 2020, tens of thousands of people have already died from the disease. In the event of an outbreak like such, forecasting the extent of the mortality that will occur is crucial to aid the implementation of effective interventions. Mortality depends on two factors: the case fatality rate and the case incidence. We combine a cohort-based model that determines case fatality rates along with a modified logistic model that evaluates the case incidence to determine the number of deaths in all the US states over time; the model is also able to include the impact of interventions. Both models yield exceptional goodness-of-fit. The model predicted a range of death outcomes (79k to 246k) all of which are considerably greater than the figures presented in mainstream media. This model can be used more effectively than current models to estimate the number of deaths during an outbreak, allowing for better planning.


title: Artificial Intelligence (AI) Provided Early Detection of the Coronavirus (COVID-19) in China and Will Influence Future Urban Health Policy Internationally

text: Predictive computing tools are increasingly being used and have demonstrated successfulness in providing insights that can lead to better health policy and management However, as these technologies are still in their infancy stages, slow progress is being made in their adoption for serious consideration at national and international policy levels However, a recent case evidences that the precision of Artificial Intelligence (AI) driven algorithms are gaining in accuracy AI modelling driven by companies such as BlueDot and Metabiota anticipated the Coronavirus (COVID-19) in China before it caught the world by surprise in late 2019 by both scouting its impact and its spread From a survey of past viral outbreaks over the last 20 years, this paper explores how early viral detection will reduce in time as computing technology is enhanced and as more data communication and libraries are ensured between varying data information systems For this enhanced data sharing activity to take place, it is noted that efficient data protocols have to be enforced to ensure that data is shared across networks and systems while ensuring privacy and preventing oversight, especially in the case of medical data This will render enhanced AI predictive tools which will influence future urban health policy internationally


title: Vicarious traumatization in the general public, members, and non-members of medical teams aiding in COVID-19 control

text: Since December 2019, more than 79,000 people have been diagnosed with infection of the Corona Virus Disease 2019 (COVID-19). A large number of medical staff were dispersed for Wuhan city and Hubei province to aid COVID-19 control. Psychological stress, especially vicarious traumatization (VT) caused by the COVID-19 pandemic, should not be ignored. To address this concern, the study employed a total of 214 general public (GP) and 526 nurses to evaluate VT scores via a mobile app-based questionnaire. Results showed that the VT scores slightly increased across periods of aiding COVID-19 control, although no statistical difference was noted (P = 0.083). However, the study found lower scores for VT in nurses [median = 69; interquartile range (IQR) = 56-85] than those of the GP (median = 75.5; IQR = 62-88.3) (P = 0.017). In addition, the VT scores for front-line nurses (FLNs; median = 64; IQR = 52-75), including scores for physiological and psychological responses, were significantly lower than those of non-front-line nurses (nFLNs; median = 75.5; IQR = 63-92) (P < 0.001). Interestingly, the VT scores of the GP were significantly higher than those of the FLNs (P < 0.001). However, no statistical difference was observed compared with those of nFLNs (P > 0.05). Importantly, nFLNs are more likely to suffer from VT, which might be related to two factors, namely, gender [odds ratio (OR) = 3.1717; 95% confidence interval (CI) = 4.247-18.808; P = 0.002] and fertility [OR = 2.072; 95%CI = 0.626-24.533; P = 0.039]. Therefore, increased attention should be paid to the psychological problems of the medical staff, especially nFLNs, and GP under the situation of the spread and control of COVID-19. Early strategies that aim to prevent and treat VT in medical staff and GP are extremely necessary.


title: Early behavior of Madrid Covid-19 disease outbreak: A mathematical model

text: Introduction: Madrid Covid-19 disease outbreak started on 28 February 2020 and since then it became the main Covid-19 disease cluster in Spain. On 26 March 2020, a total of 17166 cases were already reported, with 2090 deaths. Globally a R0 index of 2-3 has been reported. We aimed to build an experimental mathematical model that help to analyze the early characteristics of Madrid Covid-19 disese outbreak and to explore the actual R0 index on Madrid Covid-19 outbreak. Material and Methods: A simulated mathematical model was built, based on a SIR epidemiological model and the reported characteristics of Wuhan Covid-19 disease outbreak. Monte Carlo simulations were further done to estimate the R0 value over time in the Madrid Covid-19 disease outbreak. Results: Mean estimated R0 value along the early period is of 2.22 (+/- 1.21 SD). A significant increase of 0.093 (+/- 0.037, p=0.025) in R0 value each day of outbreak is found. Conclussions: Our proposed Mathematical Simulation model may be useful to evaluate early characteristics of this outbreak. The present work is the first reported estimation of R0 value in the Spanish Madrid Covid-19 outbreak, with similar results to the previous reported in the Wuhan outbreak, although it may suggest a slightly increase on R0 along time.


title: Changing patterns of mortality during the COVID-19 pandemic: population-based modelling to understand palliative care implications

text: Background COVID-19 has directly and indirectly caused high mortality worldwide. Aim To explore patterns of mortality during the COVID-19 pandemic and implications for palliative care provision, planning, and research. Design Descriptive analysis and population-based modelling of routine data. Participants and setting All deaths registered in England and Wales between 7th March and 15th May 2020. We described the following mortality categories by age, gender and place of death: 1) baseline deaths (deaths that would typically occur in a given period) 2) COVID-19 deaths 3) additional deaths not directly attributed to COVID-19. We estimated the proportion of COVID-19 deaths among people who would be in their last year of life in the absence of the pandemic, using simple modelling with explicit assumptions. Results During the first 10 weeks of the pandemic there were 101,615 baseline deaths, 41,105 COVID-19 deaths and 14,520 additional deaths. Deaths in care homes increased by 220% compared to home and hospital deaths which increased by 77% and 90%. Hospice deaths fell by 20%. Additional deaths were among older people (86% aged [≥]75 years), and most occurred in care homes (56%) and at home (43%). We estimate that 44% (38% to 50%) of COVID-19 deaths occurred among people who would have been in their last year of life in the absence of the pandemic. Conclusions Healthcare systems must ensure availability of palliative care to support people with severe COVID-19 in community and hospital settings. Integrated models of palliative care in care homes are urgently needed.


title: The biomechanical role of extra-axonemal structures in shaping the flagellar beat of Euglena

text: We propose and discuss a model for flagellar mechanics in Euglena gracilis. We show that the peculiar non-planar shapes of its beating flagellum, dubbed “spinning lasso”, arise from the mechanical interactions between two of its inner components, namely, the axoneme and the paraflagellar rod. The spontaneous shape of the axoneme and the resting shape of the paraflagellar rod are incompatible. The complex non-planar configurations of the coupled system emerge as the energetically optimal compromise between the two antagonistic components. The model is able to reproduce the experimentally observed flagellar beats and their characteristic spinning lasso geometric signature, namely, travelling waves of torsion with alternating sing along the length of the flagellum.


title: Whole blood immunophenotyping uncovers immature neutrophil-to-VD2 T-cell ratio as an early prognostic marker for severe COVID-19

text: SARS-CoV-2 is the novel coronavirus responsible for the current COVID-19 pandemic. Severe complications are observed only in a small proportion of infected patients but the cellular mechanisms underlying this progression are still unknown. Comprehensive flow cytometry of whole blood samples from 54 COVID-19 patients revealed a dramatic increase in the number of immature neutrophils. This increase strongly correlated with disease severity and was associated with elevated IL-6 and IP-10 levels, two key players in the cytokine storm. The most pronounced decrease in cell counts was observed for CD8 T-cells and VD2 γδ T-cells, which both exhibited increased differentiation and activation. ROC analysis revealed that the count ratio of immature neutrophils to CD8 or VD2 T-cells predicts pneumonia onset (0.9071) as well as hypoxia onset (0.8908) with high sensitivity and specificity. It would thus be a useful prognostic marker for preventive patient management and improved healthcare resource management.


title: A flexible load sharing system and implementation to anticipate and organise transfers based on ICU demand in the context of COVID-19 pandemic

text: As the number of cases of COVID-19 continues to grow exponentially, local health services are likely to be overwhelmed with patients requiring intensive care. We develop and implement an algorithm to provide optimal re-routing strategies to transfer patients requiring Intensive Care Units (ICU) between hospitals within NHS trusts, constrained by feasibility of transfer. We coarse-grain the NHS system at the level of NHS trusts and, subsequently cover the whole set of geopositioned trusts to extract a 4-regular geometric graph which indicates, for a given trust, its four nearest neighbors. Estimates of weekly ICU demand can be extrapolated from an age structured epidemiological model by considering contagion-to-ICU likelihood estimates, and through random search optimisation we identify the best load sharing strategy. The cost function to minimise is based on the total number of ICU units above capacity and we implement and test two optimisation strategies. Our framework is flexible allowing for additional criteria, different cost functions, and this methodology is general enough that it can easily be extended to optimise other resources beyond ICU units or ventilators. Assuming a uniform ICU demand across trusts, we show that using our method it is possible to enable access to ICU treatment to up to 1000 cases nationally in a single step of the algorithm, leading to potentially saving a large percentage of these lives that would otherwise not have access to ICU if no load sharing was implemented.


title: Trends and prediction in daily incidence of novel coronavirus infection in China, Hubei Province and Wuhan City: an application of Farr law

text: Background: The recent outbreak of novel coronavirus (2019-nCoV) has infected tens of thousands of patients in China. Studies have forecasted future trends of the incidence of 2019-nCoV infection, but appeared unsuccessful. Farr law is a classic epidemiology theory/practice for predicting epidemics. Therefore, we used and validated a model based on Farr law to predict the daily-incidence of 2019-nCoV infection in China and 2 regions of high-incidence. Methods: We extracted the 2019-nCoV incidence data of China, Hubei Province and Wuhan City from websites of the Chinese and Hubei health commissions. A model based on Farr law was developed using the data available on Feb. 8, 2020, and used to predict daily-incidence of 2019-nCoV infection in China, Hubei Province and Wuhan City afterward. Results: We observed 50,995 (37001 on or before Feb. 8) incident cases in China from January 16 to February 15, 2020. The daily-incidence has peaked in China, Hubei Providence and Wuhan City, but with different downward slopes. If no major changes occur, our model shows that the daily-incidence of 2019-nCoV will drop to single-digit by February 25 for China and Hubei Province, but by March 8 for Wuhan city. However, predicted 75% confidence intervals of daily-incidence in all 3 regions of interest had an upward trend. The predicted trends overall match the prospectively-collected data, confirming usefulness of these models. Conclusions: This study shows the daily-incidence of 2019-nCoV in China, Hubei Province and Wuhan City has reached the peak and was decreasing. However, there is a possibility of upward trend.


title: Nearly Perfect Forecasting of the Total COVID-19 Cases in India: A Numerical Approach

text: There are standard computational and statistical techniques of forecasting the spread pattern of a pandemic. In this article, we are going to show how close the forecasts can be if we use a simple numerical approach that can be worked out using just a scientific calculator. Using a few recent data, short term forecasts can be found very easily. In this numerical technique, we need not make any assumptions, unlike in the cases of using computational and statistical methods. Such numerical forecasts would be nearly perfect unless the pandemic suddenly starts retarding during the period of the forecasts naturally or otherwise.


title: Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2): An Emerging Zoonotic Respiratory Pathogen in Humans

text: Two highly human pathogenic coronaviruses outbreak in the beginning of 21st century i e Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2002 and 2012 respectively caused high pathogenicity and fatality rates in human populations Recently, a new coronavirus named as SARS-CoV-2 or nCoV-2019 was first reported in Wuhan, China in December 2019 which is responsible for an acute human respiratory illness referred as Coronavirus Disease (COVID-19), an ongoing pandemic SARS-CoV-2 is the third known highly pathogenic virus affecting human population This virus spread globally within few weeks of first identification and nearly 5 52 million confirmed cases with more than 3,47,000 deaths reported as of May 25, 2020 Till date, there are no specific anti-viral drugs, therapies or vaccines to contain and prevent this infectious pathogen outbreak The global spread of this virus to over 210 countries resulted in both human and economic losses, highlighting the need for an immediate imperative research exploration on prophylactic and therapeutic measures Current knowledge and understanding of the pathogenesis of similar coronavirus SARS-CoV and MERS-CoV might be helpful for the rapid development of treatment strategies to prevent the further spread of this virus In this review, we recapitulate the topical understanding on the structure, pathogenesis and epidemiology of SARS-CoV-2 that has emerged as a major health concern worldwide


title: Spread of virus during soccer matches

text: In the present study, the exposure to virus during soccer matches is calculated. Tracking data from 14 elite matches was used. One player in each match was carrying a virus. The exposure score (measured in seconds) was calculated as time spent closer than 1.5m from the infected player or time spent in an exponentially declining zone where the infected player was positioned earlier. The results reveal that, on average, each player was exposed for 87.8s per match.


title: Coronavirus Disease 2019 (COVID-19) in Cancer Patients

text: The Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become the most talked-about clinical entity in early 2020. As an infection that spreads easily and has a significant mortality rate, it has caused global panic rarely seen before. Many of the measures taken by governments worldwide will have long-lasting impacts on the wellbeing of the population at large. It has been widely reported that the most vulnerable patients have been most negatively affected by SARS-CoV-2 (COVID-19). In this study, we have tried to search the currently available data on the outcomes of infected cancer patients. Most of the data points to the very challenging nature of treating such patients. Their overall outcomes seem to be worse than in the general population, and it may be difficult to differentiate which potential complications are a result of the primary oncologic disease versus the infection. Management presents its own set of challenges, including but not limited to, deciding whether postponing cancer treatment until the infection resolves is going to benefit the patient and how to organize all aspects of patient care when social contact is as limited as it is for patients newly diagnosed with COVID-19. We believe that as more data becomes available, it is going to be necessary to publish detailed guidelines on how to approach this unique clinical challenge.


title: Loss of Taste and Smell as Distinguishing Symptoms of COVID-19

text: Olfactory and taste dysfunctions have emerged as symptoms of COVID-19. Among individuals with COVID-19 enrolled in a household study, loss of taste and/or smell was the fourth most commonly reported symptom (26/42; 62%), and among household contacts, it had the highest positive predictive value (83%; 95% CI: 55-95%) for COVID-19. These findings support consideration of loss of taste and/or smell in possible case identification and testing prioritization for COVID-19.


title: Current Evidence of the Pharmacological Treatments for Novel Coronavirus Disease 2019 (COVID-19) A Scoping Review

text: Background: As of May 2 2020, 3,267,184 confirmed cases of COVID-19 and 229,971 COVID-19-caused deaths have been reported worldwide. Currently, there is limited clarity on the pharmacological treatments available for the novel coronavirus. We systematically identified the current evidence and ongoing research on the pharmacological treatments for COVID-19. Methods: We conducted a scoping review using PRISMA-ScR. Observational studies, including cohort studies and case series, as well as experimental studies, including randomized controlled trials (RCTs) and non-RCTs were searched electronically on April 7, 2020 and by hand on May 1, 2020. PubMed, EMBASE, and Cochrane library databases were searched along with seven trial registries. The inclusion criteria were patients with confirmed COVID-19 who received pharmacological therapies, including hydroxychloroquine and chloroquine, lopinavir/ritonavir, remdesivir, tocilizumab, and favipiravir. Results: We identified 222 studies on pharmacological treatment of the novel coronavirus. We included 11 of these studies in this review, including the ones on hydroxychloroquine and chloroquine (one cohort), lopinavir/ritonavir (one RCT, three cohorts, and two case series), remdesivir (one RCT and one case series), tocilizumab (one case series), and favipiravir (one RCT). In the three RCTs carried out in China, both lopinavir/ritonavir and remdesivir did not show any significant earlier clinical improvement in case of severe infection [Hazard ratio (HR): 1.31, p=0.09 and HR: 1.24, p=0.24, respectively], The clinical recovery rate on day seven was not significantly different between the favipiravir and arbidol groups (p=0.14) for moderate patients, although the duration of pyrexia and cough in the favipiravir group was significantly shorter as compared to the arbidol group (p<0.01). There are 135 ongoing RCTs, including 72 for hydroxychloroquine and chloroquine, 29 for lopinavir/ritonavir, 14 for remdesivir, 16 for tocilizumab, and 4 for favipiravir. Conclusion: The clinical effectiveness and safety of these drugs for the treatment of COVID-19 remains unclear owing to the lack of large, high-quality RCTs. However, in the event of emerging infectious diseases, we need to repeatedly and systematically update the best available evidence to avoid misleading information.


title: Molecular docking and dynamics simulation of FDA approved drugs with the main protease from 2019 novel coronavirus

text: Design and development of an effective drug to combat the 2019 novel coronavirus remains a challenge. Therefore, it is of interest to study the binding features of 1615 FDA approved drugs with the recently known 2019-nCoV main protease structure having high sequence homology with that from SARS-CoV. We document the binding features of top 10 drugs with the target protein. We further report that Conivaptan and Azelastine are mainly involved in hydrophobic interactions with active site residues. Both drugs can maintain close proximity to the binding pocket of main protease during simulation. However, these data need further in vitro and in vivo evaluation to repurpose these two drugs against 2019-nCoV.


title: A Mental Health First Aid Service in an Italian University Public Hospital during the Coronavirus Disease 2019 Outbreak

text: The recent outbreak of coronavirus disease 2019 (COVID-19) has been extremely stressful and has produced fear and anxiety throughout the population, representing a psychological emergency This work aimed at presenting a mental health first aid service established within an Italian university public hospital context to address four different population targets (i e , people vulnerable to mental health problems, health-care professionals, people in isolation, and general citizenship) Specifically, the organizational structure comprising four different areas (i e , management, clinical, communication, and research) and first data collected from the foundation of the service until 3 May 2020 are presented Findings indicated that anxiety and fear of contagion were the main motivations prompting both the general population and health-care professionals to ask for a psychological help Furthermore, findings indicate that clients' current quality of life was perceived as lower than in the past but also that imagined in the future, highlighting the importance of psychological first aid interventions This service may represent an example for helping mental health professionals in developing similar services in their local realities, promoting health and individual and community resilience


title: Influenza C and D viral load in cattle correlates with bovine respiratory disease (BRD): Emerging role of orthomyxoviruses in the pathogenesis of BRD

text: Bovine respiratory disease (BRD) is the costliest disease affecting the cattle industry globally. Despite decades of research, the pathophysiology of BRD is not yet fully understood. It is widely believed that viruses predispose cattle to bacterial infection by causing direct damage to the respiratory tract and interfering with the immune system, leading to bacterial pneumonia. BRD remains a major challenge despite extensive vaccination against all major viral pathogens associated with the disease. Orthomyxoviruses (Influenza C & D viruses), have recently been found to infect cattle throughout the United States and are implicated to play a role in BRD. Here, we use the largest cohort study to date to investigate the association of influenza viruses in cattle with BRD. Cattle (n=599) from 3 locations were individually observed and scored for respiratory symptoms using the McGuirk scoring system. Deep pharyngeal and mid-nasal swabs were collected from each animal and were tested quantitatively for bovine viral diarrhea virus, bovine herpesvirus 1, bovine respiratory syncytial virus, bovine coronavirus, influenza C virus (ICV) and influenza D virus (IDV) by real-time PCR. Cattle that have higher viral loads of IDV and ICV also have greater numbers of co-infecting viruses than controls. More strikingly, in BRD-symptomatic cattle, the geometric mean of detectable IDV viral RNA was nearly 2 logs higher in co-infected animals (1.30×104) than those singly infected with IDV (2.19×102). This is strong evidence that viral coinfections can lead to higher replication of IDV. Our results strongly suggest that orthomyxoviruses may be significant contributors to BRD.


title: Missing clinical trial data: the knowledge gap in the safety of potential COVID-19 drugs

text: Abstract (290/300 words) Objectives: Several drugs are being repurposed for the treatment of the coronavirus disease 2019 (COVID-19) pandemic based on in vitro or early clinical findings. As these drugs are being used in varied regimens and dosages, it is important to enable synthesis of existing safety data from clinical trials. However, availability of safety information is limited by a lack of timely reporting of clinical trial results on public registries or through academic publication. We aimed to analyse the knowledge gap in safety data by quantifying the number of missing clinical trial results for drugs potentially being repurposed for COVID-19. Design: ClinicalTrials.gov was searched for 19 drugs that have been identified as potential treatments for COVID-19. Relevant clinical trials for any prior indication were listed by identifier (NCT number) and checked for timely result reporting (within 395 days of the primary completion date). Additionally, PubMed and Google Scholar were searched using the NCT number to identify publications of results not listed on the registry. A second, blinded search of 10% of trials was conducted to assess reviewer concordance. Results: Of 3754 completed trials, 1516 (40.4%) did not post results on ClinicalTrials.gov or in the academic literature. 1172 (31.2%) completed trials had tabular results on ClinicalTrials.gov. A further 1066 (28.4%) completed trials had results from the literature search, but did not report results on ClinicalTrials.gov. Key drugs missing clinical trial results include hydroxychloroquine (37.0% completed trials unreported), favipiravir (77.8%) and lopinavir (40.5%). Conclusion: There is an important evidence gap for the safety of drugs being repurposed for COVID-19. This uncertainty could cause a large burden of additional morbidity and mortality during the pandemic. We recommend caution in experimental drug use for non-severe disease and urge clinical trial sponsors to report missing results retrospectively.


docid: xapokjgd

title: Impact of Congestive Heart Failure and Role of Cardiac Biomarkers in COVID-19 patients: A Systematic Review and Meta-Analysis

text: Background: Coronavirus disease 2019 (COVID-19) has been reported to cause worse outcomes in patients with underlying cardiovascular disease, especially in patients with acute cardiac injury, which is determined by elevated levels of high-sensitivity troponin. There is a paucity of data on the impact of congestive heart failure (CHF) on outcomes in COVID-19 patients. Methods: We conducted a literature search of PubMed/Medline, EMBASE, and Google Scholar databases from 11/1/2019 till 06/07/2020, and identified all relevant studies reporting cardiovascular comorbidities, cardiac biomarkers, disease severity, and survival. Pooled data from the selected studies were used for metanalysis to identify the impact of risk factors and cardiac biomarker elevation on disease severity and/or mortality. Results: We collected pooled data on 5,967 COVID-19 patients from 20 individual studies. We found that both non-survivors and those with severe disease had an increased risk of acute cardiac injury and cardiac arrhythmias, our pooled relative risk (RR) was - 8.52 (95% CI 3.63-19.98) (p<0.001); and 3.61 (95% CI 2.03-6.43) (p=0.001), respectively. Mean difference in the levels of Troponin-I, CK-MB, and NT-proBNP was higher in deceased and severely infected patients. The RR of in-hospital mortality was 2.35 (95% CI 1.18-4.70) (p=0.022) and 1.52 (95% CI 1.12-2.05) (p=0.008) among patients who had pre-existing CHF and hypertension, respectively. Conclusion: Cardiac involvement in COVID-19 infection appears to significantly adversely impact patient prognosis and survival. Pre-existence of CHF and high cardiac biomarkers like NT-pro BNP and CK-MB levels in COVID-19 patients correlates with worse outcomes. Keywords: Acute cardiac injury; cardiac arrhythmia; mortality risk; cardiac biomarkers, COVID-19.


title: Does Copper treating of commonly touched surfaces reduce healthcare acquired infections? A Systematic Review and meta-analysis

text: Background Healthcare acquired infections (HAIs) cause substantial morbidity and mortality. Copper appears to have strong viricidal properties under laboratory conditions. Aim We conducted a systematic review to examine the potential effect of copper treating of commonly touched surfaces in healthcare facilities. Methods We included controlled trials comparing the effect of copper-treated surfaces (furniture or bed linens) in hospital rooms versus standard rooms on hospital acquired infections (HAIs). Two reviewers independently screened retrieved articles, extracted data, and assessed the risk of bias of included studies. The primary outcome was the occurrence of healthcare acquired infections. Findings We screened 638 records; 7 studies comprising 12362 patients were included. All of included studies were judged to be at high risk in [≥]2 of the 7 domains of bias. All 7 included studies reported the effect of copper-treated surfaces HAIs. Overall, we found low quality evidence of a potential clinical importance that copper-treated hard surfaces and/or bed linens and clothes reduced healthcare acquired infections by 27% (RR 0.73; 95% CI 0.57 to 0.94). Conclusion Given the clinical and economic costs of healthcare acquired infections, the potentially protective effect of copper-treated surfaces appears important. The current evidence is insufficient to make a strong positive recommendation. However, it would appear worthwhile and urgent to conduct larger-scale publicly funded clinical trials of the impact of copper coating.


title: Further analysis of the impact of distancing upon the COVID-19 pandemic

text: This paper questions various claims from the paper "Social distancing strategies for curbing the COVID-19 epidemic" by Kissler, Tedijanto, Lipsitch, and Grad: most importantly, the claim that China's "intense" distancing measures achieved only a 60% reduction in R0.


title: Coronavirus Disease 2019 (COVID-19) Pandemic and Economic Impact

text: In less than two decades, the world has experienced three outbreaks of deadly Coronaviruses, including the recent pandemic of Coronavirus Disease 2019 (COVID-19) in China. COVID-19 posed an emergency of international concerns, and cases have been reported in more than 200 countries/regions that resulted in health, lives, and economic losses. China’s economic growth is projected to fall to 5.6% this year, the International Monetary Fund (IMF) projected that policy investment and tax policies to implement $3.3 trillion and contributes further $4.5 trillion. IMF forecasts grow from 3.7% of global gross domestic product (GDP) in 2019 to 9.9% in 2020. GDP ratio projected from 3.0% in 2019 to grow 10.7% in 2020, the US ratio expected to increase from 5.8% to 15.7%. France, Germany, Italy, Japan, and the United Kingdom (UK) each reported public sector funding programs totalling > 10% of their yearly GDP. There is a dire need for regional and international co-operation to extend hands to prevent further spreading of COVID-19.


title: Are Our COVID Warriors Cared-for Enough?A Nationwide Survey on Stress Among Doctors During the COVID-19 Pandemic

text: Limited and uneven accessibility to healthcare is a major impediment in the fight against the COVID-19 pandemic which continues on inexorably, across various parts of the globe. We conducted a nationwide survey of a large sample of Indian doctors to measure levels of perceived stress, identify risk factors for severe stress and assess their response to current issues related to safety and well-being of the HCP community. The survey found severely stressed doctors to be younger (<45years), of female gender working in the ICU setting and insecure regarding their finances. Concern regarding PPE shortages and ethical dilemmas of rationing care are factors inducing severe stress amongst doctors working in ICU settings. This is the first such survey done in the context of the COVID-19 pandemic from the Indian sub-continent. The findings have important implications on the International healthcare community, especially across Africa, Asia & South America where the contagion continues to wreak havoc. The survey has identified factors which adversely impact the mental health of doctors during this Pandemic. This can act as a valuable guide for governmental authorities, professional organisations and hospital managements to establish support systems at multiple levels for these COVID Warriors.


title: Angiotensin Converting Enzyme Inhibitors and Angiotensin Receptor Blockers and Outcome of COVID-19 : A Systematic Review and Meta-analysis

text: Importace: There is conflicting evidence about the role of angiotensin converting enzymes inhibitors (ACEIs) and angiotensin receptors blockers (ARBs) in the pathogenesis and outcome of patients infected with acute severe respiratory syndrome coronavirus 2 (SASR-CoV-2) virus and growing public concern. Methods: We systematically reviewed the literature and performed a meta-analysis using inverse variance random effect models including all studies that evaluate the role of ACEIs/ARBs and reported adjusted odds ratio. Results: Nine studies met our eligibility criteria that enrolled a population of 58615 patients infected with SASR-CoV-2. Prior use of ACEIs/ARBs were associated with significant reduction of inpatient mortality among infected patients with SASR-CoV-2, adjusted odds ratio from 4 studies 0.33, 95% confidence interval ( 0.22,0.49) with zero in between studies heterogeneity and with significant reduction of critical or fatal outcome , pooled adjusted odds ratio from 5 studies 0.32,95% confidence interval ( 0.22,0.46) with no in between studies heterogeneity. Conclusion: Our findings suggest that prior use ACEIs /ARBs is associated with a decreased risk of death or critical outcome among SASR-CoV-2 infected patients.This findings is limited by the observational nature of included studies.However, it provides a reassurance to the public not to stop prescribed ACEIs /ARBs due to fear of severe COVID-19. It also calls upon investigators and ethics committee to reconsider the ongoing randomized trials of discontinuation of these drugs.