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The first cases of COVID-19 caused by the SARS-CoV-2 virus were reported in China in December 2019. The disease has since spread globally. Many countries have instated measures to slow the spread of the virus. Information about the spread of the virus in a country can inform the gradual reopening of a country and help to avoid a second wave of infections. Our study focuses on Denmark, which is opening up when this study is performed (end-May 2020) after a lockdown in mid-March.We perform a phylogenetic analysis of 742 publicly available Danish SARS-CoV-2 genome sequences and put them into context using sequences from other countries.Our findings are consistent with several introductions of the virus to Denmark from independent sources. We identify several chains of mutations that occurred in Denmark. In at least one case we find evidence that the virus spread from Denmark to other countries. A number of the mutations found in Denmark are non-synonymous, and in general there is a considerable variety of strains. The proportions of the most common haplotypes remain stable after lockdown.Employing phylogenetic methods on Danish genome sequences of SARS-CoV-2, we exemplify how genetic data can be used to trace the introduction of a virus to a country. This provides alternative means for verifying existing assumptions. For example, our analysis supports the hypothesis that the virus was brought to Denmark by skiers returning from Ischgl. On the other hand, we identify transmission routes which suggest that Denmark was part of a network of countries among which the virus was being transmitted. This challenges the common narrative that Denmark only got infected from abroad. Our analysis concerning the ratio of haplotypes does not indicate that the major haplotypes appearing in Denmark have a different degree of virality.

Non-Pharmaceutical Public Health Interventions (NPHIs) have been used by different countries to control the spread of the COVID-19. Despite available evidence regarding the effectiveness of NPHSs, there is still no consensus about how policymakers can trust these results. Studies on the effectiveness of NPHSs are single studies conducted in specific communities. Therefore, they cannot individually prove if these interventions have been effective in reducing the spread of the infection and its adverse health outcomes. In this systematic review, we aimed to examine the effects of NPHIs on the COVID-19 case growth rate, death growth rate, Intensive Care Unit (ICU) admission, and reproduction number in countries, where NPHIs have been implemented. We searched relevant electronic databases, including Medline (via PubMed), Scopus, CINAHL, Web of Science, etc. from late December 2019 to February 1, 2021. The key terms were primarily drawn from Medical Subject Heading (MeSh and Emtree), literature review, and opinions of experts. Peer-reviewed quasi-experimental studies were included in the review. The PROSPERO registration number is CRD42020186855. Interventions were NPHIs categorized as lockdown, stay-at-home orders, social distancing, and other interventions (mask-wearing, contact tracing, and school closure). We used PRISMA 2020 guidance for abstracting the data and used Cochrane Effective Practice and Organization of Practice (EPOC) Risk of Bias Tool for quality appraisal of the studies. Hartung-Knapp-Sidik-Jonkman random-effects model was performed. Main outcomes included COVID-19 case growth rate (percentage daily changes), COVID-19 mortality growth rate (percentage daily changes), COVID-19 ICU admission (percentage daily changes), and COVID-19 reproduction number changes. Our search strategies in major databases yielded 12,523 results, which decreased to 7,540 articles after eliminating duplicates. Finally, 35 articles qualified to be included in the systematic review among which 23 studies were included in the meta-analysis. Although studies were from both low-income and high-income countries, the majority of them were from the United States (13 studies) and China (five studies). Results of the meta-analysis showed that adoption of NPHIs has resulted in a 4.68% (95% CI, -6.94 to -2.78) decrease in daily case growth rates, 4.8% (95 CI, -8.34 to -1.40) decrease in daily death growth rates, 1.90 (95% CI, -2.23 to -1.58) decrease in the COVID-19 reproduction number, and 16.5% (95% CI, -19.68 to -13.32) decrease in COVID-19 daily ICU admission. A few studies showed that, early enforcement of lockdown, when the incidence rate is not high, contributed to a shorter duration of lockdown and a lower increase of the case growth rate in the post-lockdown era. The majority of NPHIs had positive effects on restraining the COVID-19 spread. With the problems that remain regarding universal access to vaccines and their effectiveness and considering the drastic impact of the nationwide lockdown and other harsh restrictions on the economy and people’s life, such interventions should be mitigated by adopting other NPHIs such as mass mask-wearing, patient/suspected case isolation strategies, and contact tracing. Studies need to address the impact of NPHIs on the population’s other health problems than COVID-19.

To accurately interpret COVID-19 seroprevalence surveys, knowledge of serum-IgG responses to SARS-CoV-2 with a better understanding of patients who do not seroconvert, is imperative. This study aimed to describe serum-IgG responses to SARS-CoV-2 in a cohort of patients with both severe and mild COVID-19, including extended studies of patients who remained seronegative more than 90 days post symptom onset.SARS-CoV-2-specific IgG antibody levels were quantified using two clinically validated and widely used commercial serological assays (Architect, Abbott Laboratories and iFlash 1800, YHLO), detecting antibodies against the spike and nucleocapsid proteins.Forty-seven patients (mean age 49 years, 38% female) were included. All (15/15) patients with severe symptoms and 29/32 (90.6%) patients with mild symptoms of COVID-19 developed SARS-CoV-2-specific IgG antibodies in serum. Time to seroconversion was significantly shorter (median 11 vs. 22 days, P = 0.04) in patients with severe compared to mild symptoms. Of the three patients without detectable IgG-responses after90 days, all had detectable virus-neutralizing antibodies and in two, spike-protein receptor binding domain-specific IgG was detected with an in-house assay. Antibody titers were preserved during follow-up and all patients who seroconverted, irrespective of the severity of symptoms, still had detectable IgG levels75 days post symptom onset.Patients with severe COVID-19 both seroconvert earlier and develop higher concentrations of SARS-CoV-2-specific IgG than patients with mild symptoms. Of those patients who not develop detectable IgG antibodies, all have detectable virus-neutralizing antibodies, suggesting immunity. Our results showing that not all COVID-19 patients develop detectable IgG using two validated commercial clinical methods, even over time, are vital for the interpretation of COVID-19 seroprevalence surveys.

Novel coronavirus (named SARS-CoV-2) can spread widely in confined settings including hospitals, cruise ships, prisons, and places of worship. In particular, a healthcare-associated outbreak could become the epicenter of coronavirus disease (COVID-19). This study aimed to evaluate the effects of different intervention strategies on the hospital outbreak within a tertiary hospital. A mathematical model was developed for the COVID-19 transmission within a 2500-bed tertiary hospital of South Korea. The SEIR (susceptible-exposed-infectious-recovered) model with a compartment of doctor, nurse, patient, and caregiver was constructed. The effects of different intervention strategies such as front door screening, quarantine unit for newly admitted patients, early testing of suspected infected people, and personal protective equipment for both medical staff and visitors were evaluated. The model suggested that the early testing (within eight hours) of infected cases and monitoring the quarantine ward for newly hospitalized patients are effective measures for decreasing the incidence of COVID-19 within a hospital (81.3% and 70% decrease of number of incident cases, respectively, during 60 days). Front door screening for detecting suspected cases had only 42% effectiveness. Screening for prohibiting the admission of COVID-19 patients was more effective than the measures for patients before emergency room or outpatient clinic. This model suggests that under the assumed conditions, some effective measures have a great influence on the incidence of COVID-19 within a hospital. The implementation of the preventive measures could reduce the size of a hospital outbreak.

In this paper, we provide a retrospective cohort study with patients that have been hospitalized for general or intensive care unit admission due to COVID-19, between March 3 and July 29, 2020, in the state of Bahia, Brazil. We aim to correlate those patients' demographics, symptoms and comorbidities, with the risk of mortality from COVID-19, length of hospital stay, and time from diagnosis to definitive outcome. On the basis of a dataset provided by the Health Secretary of the State of Bahia, we selected 3,896 hospitalized patients from a total of 154,868 COVID-19 patients that included non-hospitalized patients and patients with invalid registration in the dataset. Then, we statistically analyzed whether there was a significant correlation between the patient record data and the COVID-19 pandemic, and our main findings reinforced by the use of a multivariable logistic regression were that older age (Odds Ratio [OR] = 1.03, 95% Confidence Interval [CI] = 1.03-1.04, p-value (p)0.001), an initial symptom of shortness of breath (OR = 1.88, 95% CI = 1.60-2.20, p0.001), and the presence of comorbidities, mainly chronic kidney disease (OR = 2.41, 95% CI = 1.67-3.48, p0.001) are related to an increased risk of mortality from COVID-19. On the other hand, sore throat (OR = 0.74, 95% CI = 0.58-0.95, p = 0.02) and length of hospital stay (OR = 0.96, 95% CI = 0.58-0.95, p0.001) are more related to a reduced risk of mortality from COVID-19. Moreover, a multivariable linear regression conducted with statistically significant variables (p0.05) showed that age (OR = 0.97, 95% CI = 0.95-0.98, p0.001) and time from diagnosis to definitive outcome (OR = 1.67, 95% CI = 1.64-1.71, p0.001) are associated with the length of hospital stay.

IntroductionPatients with COVID-19 usually recover and return to normal health, however some patients may have symptoms that last for weeks or even months after recovery. This persistent state of ill health is known as Long COVID if it continues for more than 12 weeks and are not explained by an alternative diagnosis. Long Covid has been overlooked in low and middle income countries. Therefore, we conducted an online survey among the COVID-19 survivors in the community to explore their Long COVID symptoms, factors associated with Long COVID and how Long COVID affected their work.MethodsThis was a cross sectional study conducted from July to September 2021, during the implementation of a nationwide movement control order (MCO). Data was collected using the REDCap electronic data capture tool. The questionnaire was distributed in social and news media. The questionnaire covers information such as socio-demographic characteristics, existing comorbidities, self-perception on health, information on the acute COVID-19 condition and treatment received, symptoms and duration of post-COVID condition and effects on occupation. Results: A total of 732 COVID-19 survivors responded. There were slightly more females (58.7%), younger and more highly educated respondents. More than half of them were overweight or obese and about two third were free of comorbidities. Among these respondents, about 56% were without or with mild symptoms during their acute COVID-19 conditions. A total of 21.1% of the respondents reported to experience Long COVID. The most commonly reported symptoms for Long COVID were fatigue, brain fog, depression, anxiety, insomnia, arthralgia or myalgia. Females had 58% higher odds (95% CI: 1.02, 2.45) of experiencing Long COVID. Patients with moderate and severe levels of acute COVID-19 symptoms had OR of 3.01 (95% CI: 1.21, 7.47) and 3.62 (95% CI: 1.31, 10.03) respectively for Long COVID.ConclusionThis study provides additional insight on the symptoms and duration of post-COVID symptoms as well as the associated factors with Long COVID among COVID-19 survivors in Malaysia. Recognition of Long COVID and its associated factors is important in planning prevention, rehabilitation, clinical management to improve recovery and long-term COVID-19 outcomes.

To investigate whether people who think they have had COVID-19 are less likely to report engaging with lockdown measures compared with those who think they have not had COVID-19.On-line cross-sectional survey.Data were collected between 20th and 22nd April 2020.6149 participants living in the UK aged 18 years or over.Perceived immunity to COVID-19, self-reported adherence to social distancing measures (going out for essential shopping, nonessential shopping, and meeting up with friends/family; total out-of-home activity), worry about COVID-19 and perceived risk of COVID-19 to oneself and people in the UK. Knowledge that cough and high temperature / fever are the main symptoms of COVID-19. We used logistic regression analyses and one-way ANOVAs to investigate associations between believing you had had COVID-19 and binary and continuous outcomes respectively.In this sample, 1493 people (24.3%) thought they had had COVID-19 but only 245 (4.0%) reported having received a positive test result. Reported test results were often incongruent with participants' belief that they had had COVID-19. People who believed that they had had COVID-19 were: more likely to agree that they had some immunity to COVID-19; less likely to report adhering to lockdown measures; less worried about COVID-19; and less likely to know that cough and high temperature / fever are two of the most common symptoms of COVID-19.At the time of data collection, the percentage of people in the UK who thought they had already had COVID-19 was about twice the estimated infection rate. Those who believed they had had COVID-19 were more likely to report leaving home. This may contribute to transmission of the virus. Clear communications to this growing group are needed to explain why protective measures continue to be important and to encourage sustained adherence.

The 2019 novel coronavirus (renamed SARS-CoV-2, and generally referred to as the COVID-19 virus) has spread to 184 countries with over 1.5 million confirmed cases. Such major viral outbreaks demand early elucidation of taxonomic classification and origin of the virus genomic sequence, for strategic planning, containment, and treatment. This paper identifies an intrinsic COVID-19 virus genomic signature and uses it together with a machine learning-based alignment-free approach for an ultra-fast, scalable, and highly accurate classification of whole COVID-19 virus genomes. The proposed method combines supervised machine learning with digital signal processing (MLDSP) for genome analyses, augmented by a decision tree approach to the machine learning component, and a Spearman's rank correlation coefficient analysis for result validation. These tools are used to analyze a large dataset of over 5000 unique viral genomic sequences, totalling 61.8 million bp, including the 29 COVID-19 virus sequences available on January 27, 2020. Our results support a hypothesis of a bat origin and classify the COVID-19 virus as Sarbecovirus, within Betacoronavirus. Our method achieves 100% accurate classification of the COVID-19 virus sequences, and discovers the most relevant relationships among over 5000 viral genomes within a few minutes, ab initio, using raw DNA sequence data alone, and without any specialized biological knowledge, training, gene or genome annotations. This suggests that, for novel viral and pathogen genome sequences, this alignment-free whole-genome machine-learning approach can provide a reliable real-time option for taxonomic classification.

Endemic human coronaviruses (HCoVs) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are members of the family Coronaviridae. Comparing the findings of the infections caused by these viruses would help reveal the novel characteristics of SARS-CoV-2 and provide insight into the unique pathogenesis of SARS-CoV-2 infection. This study aimed to compare the clinical and radiological characteristics of SARS-CoV-2 and endemic HCoVs infection in adult hospitalized patients with community-acquired pneumonia (CAP). This study was performed at a university-affiliated tertiary hospital in the Republic of Korea, between January 1, 2015, and July 31, 2020. A total of 109 consecutive patients who were over 18 years of age with confirmed SARS-CoV-2 and endemic HCoVs were enrolled. Finally, 19 patients with SARS-CoV-2 CAP were compared to 40 patients with endemic HCoV CAP. Flu-like symptoms such as cough, sore throat, headache, myalgia, and prolonged fever were more common in SARS-CoV-2 CAP, whereas clinical findings suggestive of bacterial pneumonia such as dyspnea, leukocytosis with left shift, and increased C-reactive protein were more common in endemic HCoV CAP. Bilateral peripherally distributed ground-glass opacities (GGOs) were typical radiologic findings in SARS-CoV-2 CAP, whereas mixed patterns of GGOs, consolidations, micronodules, and pleural effusion were observed in endemic HCoV CAP. Coinfection was not observed in patients with SARS-CoV-2 CAP, but was observed in more than half of the patients with endemic HCoV CAP. There were distinctive differences in the clinical and radiologic findings between SARS-CoV-2 and endemic HCoV CAP. Further investigations are required to elucidate the mechanism underlying this difference. Follow-up observations are needed to determine if the presentation of SARS-CoV-2 CAP changes with repeated infection.

The COVID-19 pandemic has posed major challenges to all aspects of healthcare. Malta's population density, large proportion of elderly and high prevalence of diabetes and obesity put the country at risk of uncontrolled viral transmission and high mortality. Despite this, Malta achieved low mortality rates compared to figures overseas. The aim of this paper is to identify key factors that contributed to these favorable outcomes.This is a retrospective, observational, nationwide study which evaluates outcomes of patients during the first wave of the pandemic in Malta, from the 7th of March to the 24th of April 2020. Data was collected on demographics and mode of transmission. Hospitalization rates to Malta's main general hospital, Mater Dei Hospital, length of in-hospital stay, intensive care unit admissions and 30-day mortality were also analyzed.There were 447 confirmed cases in total; 19.5% imported, 74.2% related to community transmission and 6.3% nosocomially transmitted. Ninety-three patients (20.8%) were hospitalized, of which 4 were children. Patients with moderate-severe disease received hydroxychloroquine and azithromycin, in line with evidence available at the time. A total of 4 deaths were recorded, resulting in an all-cause mortality of 0.89%. Importantly, all admitted patients with moderate-severe disease survived to 30-day follow up.Effective public health interventions, widespread testing, remote surveillance of patients in the community and a low threshold for admission are likely to have contributed to these favorable outcomes. Hospital infection control measures were key in preventing significant nosocomial spread. These concepts can potentially be applied to stem future outbreaks of viral diseases. Patients with moderate-severe disease had excellent outcomes with no deaths reported at 30-day follow up.

As the number of cases of COVID-19 continues to grow, local health services are at risk of being overwhelmed with patients requiring intensive care. We develop and implement an algorithm to provide optimal re-routing strategies to either transfer patients requiring Intensive Care Units (ICU) or ventilators, constrained by feasibility of transfer. We validate our approach with realistic data from the United Kingdom and Spain. In the UK, we consider the National Health Service at the level of trusts and define a 4-regular geometric graph which indicates the four nearest neighbours of any given trust. In Spain we coarse-grain the healthcare system at the level of autonomous communities, and extract similar contact networks. Through random search optimisation we identify the best load sharing strategy, where the cost function to minimise is based on the total number of ICU units above capacity. Our framework is general and flexible allowing for additional criteria, alternative cost functions, and can be extended to other resources beyond ICU units or ventilators. Assuming a uniform ICU demand, we show that it is possible to enable access to ICU for up to 1000 additional cases in the UK in a single step of the algorithm. Under a more realistic and heterogeneous demand, our method is able to balance about 600 beds per step in the Spanish system only using local sharing, and over 1300 using countrywide sharing, potentially saving a large percentage of these lives that would otherwise not have access to ICU.

SummaryBackgroundSuperinfections, including invasive pulmonary aspergillosis (IPA), are well-known complications of critically ill patients with severe viral pneumonia. Aim of this study was to evaluate the incidence, risk factors and outcome of IPA in critically ill patients with severe COVID-19 pneumonia.MethodsWe prospectively screened 32 critically ill patients with severe COVID-19 pneumonia for a time period of 28 days using a standardized study protocol for oberservation of developement of COVID-19 associated invasive pulmonary aspergillosis (CAPA). We collected laboratory, microbiological, virological and clinical parameters at defined timepoints in combination with galactomannan-antigen-detection from bronchial aspirates. We used logistic regression analyses to assess if COVID-19 was independently associated with IPA and compared it with matched controls.FindingsCAPA was diagnosed at a median of 4 days after ICU admission in 11/32 (34%) of critically ill patients with severe COVID-19 pneumonia as compared to 8% in the control cohort.In the COVID-19 cohort, mean age, APACHE II score and ICU mortality were higher in patients with CAPA than in patients without CAPA (36% versus 9.5%; pInterpretationCAPA is highly prevalent and associated with a high mortality rate. COVID-19 is independently associated with invasive pulmonary aspergillosis. A standardized screening and diagnostic approach as presented in our study can help to identify affected patients at an early stage.FundingNone

BackgroundThe World Health Organization declared the outbreak of COVID-19 as a pandemic on 11 March 2020. Healthcare workers are directly involved in the prevention, diagnosis, treatment, and care of patients with COVID-19.This study aims to assess the prevalence of anxiety and its associated factors towards the COVID-19 outbreak among healthcare workers in a Hospital of Ethiopia.MethodsA Hospital-based survey study was conducted on a total of 305 Healthcare workers in a Hospital of Ethiopia. Bivariable and multivariable logistic regression were used to analyze data between independent variables with anxiety. Variables with a p-value of ResultsThe prevalence of CVID-19 anxiety was 63%. In multivariate logistic regression, age of 30–39 (AOR, 3.05; 95% CI, (1.70, 5.47) and age of ≥40 (AOR, 11.32; 95% CI (3.37, 37.98), being married (AOR, 3.56; 95% CI, (2.30, 6.38), having chronic illness (AOR, 3.43; 95% CI, (1.59,7.43), having suspected COVID-19 family members (AOR, 5.20; 95% CI, (2.11, 12.78), and not having an access to PPEs (AOR, 2.55; 95% CI, (1.43, 4.56) were statistically significantly associated with anxiety.ConclusionBeing married, having a chronic illness, having suspected COVID-19 family members, not having access to PPEs, and age greater than or equal to 30 years were identified as risk factors for anxiety of Healthcare Workers towards COVID-19.

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

We describe a method to estimate individual risks of hospitalization and death attributable to non-household and household transmission of SARS-CoV-2 using available public data on confirmed-case incidence data along with estimates of the clinical fraction, timing of transmission, isolation adherence, secondary infection risks, contact rates, and case-hospitalization and case-fatality ratios. Using the method, we estimate that risks for a 90-day period at the median daily summertime U.S. county confirmed COVID-19 case incidence of 10.8 per 100,000 and pre-pandemic contact rates range from 0.4 to 8.9 per 100,000 for the four deciles of age between 20 and 60 years. The corresponding 90-day period risk of hospitalization ranges from 13.7 to 69.2 per 100,000. Assuming a non-household secondary infection risk of 4% and pre-pandemic contact rates, the share of transmissions attributable to household settings ranges from 73% to 78%. These estimates are sensitive to the parameter assumptions; nevertheless, they are comparable to the COVID-19 hospitalization and fatality rates observed over the time period. We conclude that individual risk of hospitalization and death from SARS-CoV-2 infection is calculable from publicly available data sources. Access to publicly reported infection incidence data by setting and other exposure characteristics along with setting specific estimates of secondary infection risk would allow for more precise individual risk estimation.

The current study investigated the clinical manifestations and outcomes of different age groups of patients with overseas imported COVID-19. In total, 53 COVID-19 patients admitted to the designated Beijing Xiaotangshan Hospital between March 16 and April 15 of 2020 were included. Based on the percentage of disease aggravation during hospital stay according to CT, the patients were divided into two groups: ≤40 years (group A; n = 41) and >40 years (group B; n = 12). The demographic data, epidemiological history, disease courses, potential complications, clinical symptoms, lab indices, chest CT outcomes, treatment protocols and turnovers of the two groups were compared. According to clinical typing, compared with group A, group B had a significantly greater proportion of the common type of COVID-19 (P

The ongoing COVID-19 pandemic has overwhelmingly demonstrated the need to accurately evaluate the effects of implementing new or altering existing nonpharmaceutical interventions. Since these interventions applied at the societal level cannot be evaluated through traditional experimental means, public health officials and other decision makers must rely on statistical and mathematical epidemiological models. Nonpharmaceutical interventions are typically focused on contacts between members of a population, and yet most epidemiological models rely on homogeneous mixing which has repeatedly been shown to be an unrealistic representation of contact patterns. An alternative approach is individual based models (IBMs), but these are often time intensive and computationally expensive to implement, requiring a high degree of expertise and computational resources. More often, decision makers need to know the effects of potential public policy decisions in a very short time window using limited resources. This paper presents a computation algorithm for an IBM designed to evaluate nonpharmaceutical interventions. By utilizing recursive relationships, our method can quickly compute the expected epidemiological outcomes even for large populations based on any arbitrary contact network. We utilize our methods to evaluate the effects of various mitigation measures in the District of Columbia, USA, at various times and to various degrees.Rcode for our method is provided in the supplementry material, thereby allowing others to utilize our approach for other regions.

The coronavirus disease 2019 (Covid-19) pandemic, caused by SARS-CoV-2, has resulted in a global testing supply shortage. In response, pooled testing has emerged as a promising strategy that can immediately increase testing capacity. In pooled sample testing, multiple samples are combined (or pooled) together and tested as a single unit. If the pool is positive, the individual samples can then be individually tested to identify the positive case(s). Here, we provide support for the adoption of sample pooling with the point-of-care Cepheid Xpert® Xpress SARS-CoV-2 molecular assay. Corroborating previous findings, the limit of detection of this assay was comparable to laboratory-developed reverse-transcription quantitative PCR SARS-CoV-2 tests, with observed detection below 100 copies/mL. The Xpert® Xpress assay detected SARS-CoV-2 after samples with minimum viral loads of 461 copies/mL were pooled in groups of six. Based on these data, we recommend the adoption of pooled testing with the Xpert® Xpress SARS-CoV-2 assay where warranted based on public health needs. The suggested number of samples per pool, or the pooling depth, is unique for each point-of-care testing site and can be determined by the positive test rates. To statistically determine appropriate pooling depth, we have calculated the pooling efficiency for numerous combinations of pool sizes and test rates. This information is included as a supplemental dataset that we encourage public health authorities to use as a guide to make recommendations that will maximize testing capacity and resource conservation.

Background/aimThe coronavirus disease 2019 (COVID-19) had become a big threat worldwide. Liver injury is not uncommon in patients with COVID-19, and clarifying its characteristics is needed. This study aimed to identify factors associated with liver injury and to develop a new classification of predictive severity in patients with COVID-19.MethodsConfirmed patients with COVID-19 (n = 60) were recruited retrospectively from Musashino Red Cross Hospital. The factors of liver injury especially on the elevation of liver enzymes (aspartate aminotransferase [AST] and alanine aminotransferase [ALT]) were analyzed. Grading was assessed according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0.ResultsDuring a median hospitalization follow-up of 15 (4-41) days, 51 (85.0%) patients had COVID-19 pneumonia. In clinical courses, oxygenation was needed for 25 (41.6%) patients and intubation was needed for 9 (15.0%) patients. A total of 27 (45.0%) patients had gastrointestinal symptoms (GS), such as appetite loss, diarrhea, and nausea. A logistic regression analysis revealed that C-reactive protein (CRP) at baseline, oxygenation, intubation, and GS were significant factors of liver injury. Based on these results, patients were classified into three groups: group 1, no oxygenation pneumonia; group 2, pneumonia with oxygenation or GS; and group 3, intubation. We classified 25 (41.7%), 26 (43.3%), and 9 (15.0%) patients into mild, moderate, and severe groups, respectively. The peak of AST and ALT levels was significantly stratified with this criteria (mild [median AST, 28 IU/L; median ALT, 33 IU/L], moderate [median AST, 48 IU/L; median ALT, 47.5 IU/L], and severe [median AST, 109 IU/L; median ALT, 106 IU/L]; PConclusionCOVID-19-related liver injury was significantly stratified based on GS and severity of pneumonia.

BackgroundThe COVID-19 pandemic is an unprecedented public health threat, both in scope and response. With no vaccine available, the public is advised to practice non-pharmaceutical interventions (NPI) including social distancing, mask-wearing, and washing hands. However, little is known about public perceptions of the effectiveness of these measures, and high perceived effectiveness is likely to be critical in order to achieve widespread adoption of NPI.MethodsIn May 2020, we conducted a cross-sectional survey among U.S. adults (N = 3,474). The primary outcome was a six-item measure assessing perceived effectiveness of recommended behaviors to prevent SARS-CoV-2 infection from 1 (not at all effective) to 5 (extremely effective). The sample was divided into "higher" and "lower" perceived effectiveness groups. Covariates included demographics, healthcare characteristics, and health beliefs. Variables that were significant at pResultsMean age was 45.5 years and most participants were non-Hispanic White (63%) and female (52.4%). The high perceived effectiveness group was slightly larger than the low perceived effectiveness group (52.7% vs. 47.3%). Almost all health belief variables were significant in the best-fit regression model. COVID-19-related worry (aOR = 1.82; 95% CI = 1.64-2.02), and perceived threat to physical health (aOR = 1.32; 95% CI = 1.20-1.45) were positively associated with perceived effectiveness while perceived severity of COVID-19 (0.84; 95% CI = 0.73-0.96) and perceived likelihood of infection (0.85; 95% CI = 0.77-0.94) switched directions in the adjusted model and were negatively associated with perceived effectiveness.ConclusionsThis research indicates people generally believe NPI are effective, but there was variability based on health beliefs and there are mixed rates of engagement in these behaviors. Public health efforts should focus on increasing perceived severity and threat of SARS-CoV-2-related disease, while promoting NPI as effective in reducing threat.

COVID-19 is spreading worldwide, causing various social problems. The aim of the present study was to verify the reliability and validity of the Japanese version of the Fear of COVID-19 Scale (FCV-19S) and to ascertain FCV-19S effects on assessment of Japanese people's coping behavior. After back-translation of the scale, 450 Japanese participants were recruited from a crowdsourcing platform. These participants responded to the Japanese FCV-19S, the Japanese versions of the Hospital Anxiety and Depression scale (HADS) and the Japanese versions of the Perceived Vulnerability to Disease (PVD), which assesses coping behaviors such as stockpiling and health monitoring, reasons for coping behaviors, and socio-demographic variables. Results indicated the factor structure of the Japanese FCV-19S as including seven items and one factor that were equivalent to those of the original FCV-19S. The scale showed adequate internal reliability (α = .87; ω = .92) and concurrent validity, as indicated by significantly positive correlations with the Hospital Anxiety and Depression Scale (HADS; anxiety, r = .56; depression, r = .29) and Perceived Vulnerability to Disease (PVD; perceived infectability, r = .32; germ aversion, r = .29). Additionally, the FCV-19S not only directly increased all coping behaviors (β = .21 - .36); it also indirectly increased stockpiling through conformity reason (indirect effect, β = .04; total effect, β = .31). These results suggest that the Japanese FCV-19S psychometric scale has equal reliability and validity to those of the original FCV-19S. These findings will contribute further to the investigation of various difficulties arising from fear about COVID-19 in Japan.

Background This study aims to describe the epidemiology of COVID-19 patients in a Swiss university hospital. Methods This retrospective observational study included all adult patients hospitalized with a laboratory confirmed SARS-CoV-2 infection from March 1 to March 25, 2020. We extracted data from electronic health records. The primary outcome was the need to mechanical ventilation at day 14. We used multivariate logistic regression to identify risk factors for mechanical ventilation. Follow-up was of at least 14 days. Results 145 patients were included in the multivariate model, of whom 36 (24.8%) needed mechanical ventilation at 14 days. The median time from symptoms onset to mechanical ventilation was 9·5 days (IQR 7.00, 12.75). Multivariable regression showed increased odds of mechanical ventilation with age (OR 1.09 per year, 95% CI 1.03–1.16, p = 0.002), in males (OR 6.99, 95% CI 1.68–29.03, p = 0.007), in patients who presented with a qSOFA score ≥2 (OR 7.24, 95% CI 1.64–32.03, p = 0.009), with bilateral infiltrate (OR 18.92, 3.94–98.23, p Conclusions This study gives some insight in the epidemiology and clinical course of patients admitted in a European tertiary hospital with SARS-CoV-2 infection. Age, male sex, high qSOFA score, CRP of 40 mg/l or greater and a bilateral radiological infiltrate could help clinicians identify patients at high risk for mechanical ventilation.

Background Coronavirus disease 2019 (COVID-19) has quickly spread throughout the country and the world since first broke out in Wuhan, China. The outbreak that started from January 22, 2020, in Fujian Province has been controlled as the number of indigenous cases has not increased since March. We aimed to describe the clinical characteristics of patients with COVID-19 in Fujian Province, China. Methods In this retrospective, multicenter study, we collected and analyzed the epidemiological, clinical, and laboratory data of all cases confirmed by nucleic acid tests in five designated hospitals in Fujian Province between January 22 and February 27, 2020. All patients were followed up until discharge. COVID-19 severity was classified as mild, moderate, severe, or critical. Results Of 199 discharged patients with COVID-19, 105 patients were male, with a median age of 46.3 years, and 17 patients were severe, and 5 patients were critical on admission. Hypertension and diabetes were the most common comorbidities. The symptoms at illness onset were mainly fever (76.4%), cough (60.8%), and myalgia or fatigue (27.6%). A total of 96.5% of patients had abnormal imaging findings on chest computed tomography. Lymphopenia (37.2%) and hypoxemia (13.6%) were observed. Acute respiratory distress syndrome and respiratory failure occurred in 9 patients (4.5%) and 8 patients (4.0%) respectively. One patient died and the others were cured and discharged with the median hospital stay of 19 days. Old age was negatively correlated with lymphocyte count (r = - 0.296, p < 0.001) and oxygenation index (r = - 0.263, p = 0.001). Bivariate regression analysis revealed that old age (≥ 75 years), hypertension, diabetes, and lymphopenia were correlated with the severity of COVID-19. Conclusions Patients in Fujian Province were mostly nonsevere cases with mild or moderate symptoms, and had a lower mortality than patients in Wuhan (4.3%-15%). Older age, hypertension, diabetes, and lymphopenia were risk factors for severity of COVID-19.

Digital, Many affected counties have had experienced a shortage of personal protective equipment (PPE) during the coronavirus disease (COVID-19) pandemic. We aimed to investigate the needs of healthcare professionals and the technical difficulties faced by them during the initial outbreak. A cross-sectional web-based survey was conducted among the healthcare workforce in the most populous cities from three Latin American countries in April 2020. In total, 1,082 participants were included. Of these, 534 (49.4%), 263 (24.3%), and 114 (10.5%) were physicians, nurses, and other professionals, respectively. At least 70% of participants reported a lack of PPE. The most common shortages were shortages in gown coverall suits (643, 59.4%), N95 masks (600, 55.5%), and face shields (569, 52.6%). Professionals who performed procedures that generated aerosols reported shortages more frequently (p, Ciencias Médicas y de la Salud

Introduction The COVID-19 pandemic has unveiled widespread shortages of personal protective equipment including N95 respirators. Several centers are developing reusable stop-gap respirators as alternatives to disposable N95 respirators during public health emergencies, using techniques such as 3D-printing, silicone moulding and plastic extrusion. Effective sealing of the mask, combined with respiratory filters should achieve 95% or greater filtration of particles less than 1um. Quantitative fit-testing (QNFT) data from these stop-gap devices has not been published to date. Our team developed one such device, the “SSM”, and evaluated it using QNFT. Methods Device prototypes were iteratively evaluated for comfort, breathability and communication, by team members wearing them for 15-30min. The fit and seal were assessed by positive and negative pressure user seal checks. The final design was then formally tested by QNFT, according to CSA standard Z94.4–18 in 40 volunteer healthcare providers. An overall fit-factor >100 is the passing threshold. Volunteers were also tested by QNFT on disposable N95 masks which had passed qualitative fit testing (QLFT) by institutional Occupational Health and Safety Department. Results The SSM scored 3.5/5 and 4/5 for comfort and breathability. The median overall harmonic mean fit-factors of disposable N95 and SSM were 137.9 and 6316.7 respectively. SSM scored significantly higher than disposable respirators in fit-test runs and overall fit-factors (p Conclusions We present the design and validation of a reusable N95 stop-gap filtering facepiece respirator that can match existent commercial respirators. This sets a precedence for adoption of novel stop-gap N95 respirators in emergency situations.

Background and purpose The objective of our systematic review is to identify prognostic factors that may be used in decision-making related to the care of patients infected with COVID-19. Data sources We conducted highly sensitive searches in PubMed/MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL) and Embase. The searches covered the period from the inception date of each database until April 28, 2020. No study design, publication status or language restriction were applied. Study selection and data extraction We included studies that assessed patients with confirmed or suspected SARS-CoV-2 infectious disease and examined one or more prognostic factors for mortality or disease severity. Reviewers working in pairs independently screened studies for eligibility, extracted data and assessed the risk of bias. We performed meta-analyses and used GRADE to assess the certainty of the evidence for each prognostic factor and outcome. Results We included 207 studies and found high or moderate certainty that the following 49 variables provide valuable prognostic information on mortality and/or severe disease in patients with COVID-19 infectious disease: Demographic factors (age, male sex, smoking), patient history factors (comorbidities, cerebrovascular disease, chronic obstructive pulmonary disease, chronic kidney disease, cardiovascular disease, cardiac arrhythmia, arterial hypertension, diabetes, dementia, cancer and dyslipidemia), physical examination factors (respiratory failure, low blood pressure, hypoxemia, tachycardia, dyspnea, anorexia, tachypnea, haemoptysis, abdominal pain, fatigue, fever and myalgia or arthralgia), laboratory factors (high blood procalcitonin, myocardial injury markers, high blood White Blood Cell count (WBC), high blood lactate, low blood platelet count, plasma creatinine increase, high blood D-dimer, high blood lactate dehydrogenase (LDH), high blood C-reactive protein (CRP), decrease in lymphocyte count, high blood aspartate aminotransferase (AST), decrease in blood albumin, high blood interleukin-6 (IL-6), high blood neutrophil count, high blood B-type natriuretic peptide (BNP), high blood urea nitrogen (BUN), high blood creatine kinase (CK), high blood bilirubin and high erythrocyte sedimentation rate (ESR)), radiological factors (consolidative infiltrate and pleural effusion) and high SOFA score (sequential organ failure assessment score). Conclusion Identified prognostic factors can help clinicians and policy makers in tailoring management strategies for patients with COVID-19 infectious disease while researchers can utilise our findings to develop multivariable prognostic models that could eventually facilitate decision-making and improve patient important outcomes. Systematic review registration Prospero registration number: CRD42020178802. Protocol available at: https://www.medrxiv.org/content/10.1101/2020.04.08.20056598v1.

The Infectious Diseases Society of America has identified the use of SARS-CoV-2 genomic load for prognostication purposes as a key research question. We designed a retrospective cohort study that included adult patients with COVID-19 pneumonia who had at least 2 positive nasopharyngeal tests at least 24 hours apart to study the correlation between the change in the genomic load of SARS-CoV-2, as reflected by the Cycle threshold (Ct) value of the RT-PCR, with change in clinical status. The Sequential Organ Failure Assessment (SOFA) score was used as a surrogate for patients’ clinical status. Among 457 patients with COVID-19 pneumonia between 3/31/2020-4/10/2020, we identified 42 patients who met the inclusion criteria. The median initial SOFA score was 2 (IQR 2–3). 20 out of 42 patients had a lower SOFA score on their subsequent tests. We identified a statistically significant inverse correlation between the change in SOFA score and change in the Ct value with a decrease in SOFA score by 0.05 (SE 0.02; p

BackgroundThe novel coronavirus is pandemic around the world. Several researchers have given the evidence of impacts of COVID-19 on the respiratory, cardiovascular and gastrointestinal system. Studies still have debated on kidney injury of COVID-19 patients. The purpose of the meta-analysis was to evaluate the association of kidney impairment with the development of COVID-19.MethodsThe PubMed, Embase and MedRxiv databases were searched until May 1, 2020. We extracted data from eligible studies to summarize the clinical manifestations and laboratory indexes of kidney injury on COVID-19 infection patients and further compared the prevalence of acute kidney injury (AKI) and the mean differences of three biomarkers between in ICU/severe and non-ICU/non-severe cases. Heterogeneity was evaluated using the I2method.ResultsIn the sum of 24 studies with 10180 patients were included in this analysis. The pooled prevalence of AKI, increased serum creatinine (Scr), increased blood urea nitrogen (BUN), increased D-dimer, proteinuria and hematuria in patients with COVID-19 were 16.2%, 8.3%, 6.2%, 49.8%, 50.1% and 30.3% respectively. Moreover, the means of Scr, BUN and D-dimer were shown 6.4-folds, 1.8-folds and 0.67-folds, respectively, higher in ICU/severe cases than in corresponding non-ICU/non-severe patients. The prevalence of AKI was about 30 folds higher in ICU/severe patients compared with the non-ICU/non-severe cases.ConclusionsOverall, we assessed the incidences of the clinic and laboratory features of kidney injury in COVID-19 patients. And kidney dysfunction may be a risk factor for COVID-19 patients developing into the severe condition. In reverse, COVID-19 can also cause damage to the kidney.

Testing, tracking and tracing abilities have been identified as pivotal in helping countries to safely reopen activities after the first wave of the COVID-19 virus. Contact tracing apps give the unprecedented possibility to reconstruct graphs of daily contacts, so the question is: who should be tested? As human contact networks are known to exhibit community structure, in this paper we show that the Kemeny constant of a graph can be used to identify and analyze bridges between communities in a graph. Our ‘Kemeny indicator’ is the value of the Kemeny constant in the new graph that is obtained when a node is removed from the original graph. We show that testing individuals who are associated with large values of the Kemeny indicator can help in efficiently intercepting new virus outbreaks, when they are still in their early stage. Extensive simulations provide promising results in early identification and in blocking the possible ‘super-spreaders’ links that transmit disease between different communities.

Aims The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia. Methods This was an observational prospective study that comprised consecutive patients with COVID-19 pneumonia admitted to hospital from 21 February to 6 April 2020. The patients’ medical history, demographic, epidemiologic and clinical data were collected in an electronic patient chart. The dataset was used to train predictive models using an established machine learning framework leveraging a hybrid approach where clinical expertise is applied alongside a data-driven analysis. The study outcome was the onset of moderate to severe respiratory failure defined as PaO2/FiO2 ratio Results A total of 198 patients contributed to generate 1068 usable observations which allowed to build 3 predictive models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth “boosted mixed model” included 20 variables was selected from the model 3, achieved the best predictive performance (AUC = 0.84) without worsening the FN rate. Its clinical performance was applied in a narrative case report as an example. Conclusion This study developed a machine model with 84% prediction accuracy, which is able to assist clinicians in decision making process and contribute to develop new analytics to improve care at high technology readiness levels.

© 2020 Megnin-Viggars et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background Until a vaccine is developed, a test, trace and isolate strategy is the most effective method of controlling the COVID-19 outbreak. Contact tracing and case isolation are common methods for controlling infectious disease outbreaks. However, the effectiveness of any contact tracing system rests on public engagement. Numerous factors may influence an individual’s willingness to engage with a contact tracing system. Understanding these factors has become urgent during the COVID-19 pandemic. Objective To identify facilitators and barriers to uptake of, and engagement with, contact tracing during infectious disease outbreaks. Method A rapid systematic review was conducted to identify papers based on primary research, written in English, and that assessed facilitators, barriers, and other factors associated with the uptake of, and engagement with, a contact tracing system. Principal findings Four themes were identified as facilitators to the uptake of, and engagement with, contact tracing: collective responsibility; personal benefit; co-production of contact tracing systems; and the perception of the system as efficient, rigorous and reliable. Five themes were identified as barriers to the uptake of, and engagement with, contact tracing: privacy concerns; mistrust and/or apprehension; unmet need for more information and support; fear of stigmatization; and mode-specific challenges. Conclusions By focusing on the factors that have been identified, contact tracing services are more likely to get people to engage with them, identify more potentially ill contacts, and reduce transmission.

The novel coronavirus 2019 (COVID-19) global pandemic has drastically affected the world economy, raised public anxiety, and placed a substantial psychological burden on the governments and healthcare professionals by affecting over 4.7 million people worldwide. As a preventive measure to minimise the risk of community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in India, a nationwide lockdown was imposed initially for 21 days to limit the movement of 1.3 billion people. These restrictions continue in most areas, with a conditional relaxation occurring in a few Indian states. In an attempt to assess the emerging mutants of SARS-CoV-2 and determine their spread in India, we analysed 112 complete genomes of SARS-CoV-2 in a time-lapse manner. We found 72 distinct SARS-CoV-2 haplotypes, defined by 143 polymorphic sites and high haplotype diversity, suggesting that this virus possesses a high evolutionary potential. We also demonstrated that early introduction of SARS-CoV-2 into India was from China, Italy and Iran and observed signs of community spread of the virus following its rapid demographic expansion since its first outbreak in the country. Additionally, we identified 18 mutations in the SARS-CoV-2 spike glycoprotein and a few selected mutations showed to increase stability, binding affinity, and molecular flexibility in the overall tertiary structure of the protein that may facilitate interaction between the receptor binding domain (RBD) of spike protein and the human angiotensin-converting enzyme 2 (ACE2) receptor. The study provides a pragmatic view of haplotype-dependent spread of SARS-CoV-2 in India which could be important in tailoring the pharmacologic treatments to be more effective for those infected with the most common haplotypes. The findings based on the time-lapse sentinel surveillance of SARS-CoV-2 will aid in the development of a real-time practical framework to tackle the ongoing, fast-evolving epidemic challenges in the country.

SARS-CoV-2 antibody tests are available in various formats, detecting different viral target proteins and antibody subclasses. The specificity and sensitivity of SARS-CoV-2 antibody tests are known to vary and very few studies have addressed the performance of these tests in COVID-19 patient groups at different time points. We here compared the sensitivity and specificity of seven commercial (SNIBE, Epitope, Euroimmun, Roche, Abbott, DiaSorin, Biosensor) and two in-house LIPS assays (LIPS N and LIPS S-RBD) IgG/total Ab tests in serum samples from 97 COVID-19 patients and 100 controls, and correlated the results with the patients' clinical data and the time-point the test was performed. We found a remarkable variation in the sensitivity of antibody tests with the following performance: LIPS N (91.8%), Epitope (85.6%), Abbott and in-house LIPS S-RBD (both 84.5%), Roche (83.5%), Euroimmun (82.5%), DiaSorin (81.4%), SNIBE (70.1%), and Biosensor (64.9%). The overall agreement between the tests was between 71-95%, whereas the specificity of all tests was within 98-100%. The correlation with patients' clinical symptoms score ranged from strongest in LIPS N (ρ = 0.41; p

BackgroundAfter claiming nearly five hundred thousand lives globally, the COVID-19 pandemic is showing no signs of slowing down. While the UK, USA, Brazil and parts of Asia are bracing themselves for the second wave-or the extension of the first wave-it is imperative to identify the primary social, economic, environmental, demographic, ethnic, cultural and health factors contributing towards COVID-19 infection and mortality numbers to facilitate mitigation and control measures.MethodsWe process several open-access datasets on US states to create an integrated dataset of potential factors leading to the pandemic spread. We then apply several supervised machine learning approaches to reach a consensus as well as rank the key factors. We carry out regression analysis to pinpoint the key pre-lockdown factors that affect post-lockdown infection and mortality, informing future lockdown-related policy making.FindingsPopulation density, testing numbers and airport traffic emerge as the most discriminatory factors, followed by higher age groups (above 40 and specifically 60+). Post-lockdown infected and death rates are highly influenced by their pre-lockdown counterparts, followed by population density and airport traffic. While healthcare index seems uncorrelated with mortality rate, principal component analysis on the key features show two groups: states (1) forming early epicenters and (2) experiencing strong second wave or peaking late in rate of infection and death. Finally, a small case study on New York City shows that days-to-peak for infection of neighboring boroughs correlate better with inter-zone mobility than the inter-zone distance.InterpretationStates forming the early hotspots are regions with high airport or road traffic resulting in human interaction. US states with high population density and testing tend to exhibit consistently high infected and death numbers. Mortality rate seems to be driven by individual physiology, preexisting condition, age etc., rather than gender, healthcare facility or ethnic predisposition. Finally, policymaking on the timing of lockdowns should primarily consider the pre-lockdown infected numbers along with population density and airport traffic.

The global COVID-19 pandemic is causing unprecedented job loss and financial strain. It is unclear how those most directly experiencing economic impacts may seek assistance from disparate safety net programs. To identify self-reported economic hardship and enrollment in major safety net programs before and early in the COVID-19 pandemic, we compared individuals with COVID-19 related employment or earnings reduction with other individuals. We created a set of questions related to COVID-19 economic impact that was added to a cross-sectional, nationally representative online survey of American adults (age ≥18, English-speaking) in the AmeriSpeak panel fielded from April 23–27, 2020. All analyses were weighted to account for survey non-response and known oversampling probabilities. We calculated unadjusted bivariate differences, comparing people with and without COVID-19 employment and earnings reductions with other individuals. Our study looked primarily at awareness and enrollment in seven major safety net programs before and since the pandemic (Medicaid, health insurance marketplaces/exchanges, unemployment insurance, food pantries/free meals, housing/renters assistance, SNAP, and TANF). Overall, 28.1% of all individuals experienced an employment reduction (job loss or reduced earnings). Prior to the pandemic, 39.0% of the sample was enrolled in ≥1 safety net program, and 50.0% of individuals who subsequently experienced COVID-19 employment reduction were enrolled in at least one safety net program. Those who experienced COVID-19 employment reduction versus those who did not were significantly more likely to have applied or enrolled in ≥1 program (45.9% versus 11.7%, p

As a novel concept of responding to disease epidemics, Fangcang shelter hospitals were deployed to expand the health system's capacity and provide medical services for non-severe COVID-19 patients during the outbreak in Wuhan. To give insights on patient management within Fangcang hospitals, we conducted a retrospective analysis to: 1) describe the characteristics of the patients admitted to Fangcang hospitals and 2) explore risk factors for longer length of stay (LOS). We enrolled 136 confirmed COVID-19 patients, including asymptomatic patients and those with mild symptoms, who were hospitalized in the Wuti Fangcang Hospital. 58 patients completed the treatment and discharged before 1 March 2020. After describing patients' demographic and clinical characteristics, exposure history, treatment received and time course of the disease, we conducted linear regression analysis to identify factors influencing LOS. We found that patients having fever before admission were hospitalized 3.5 days (95%CI 1.39 to 5.63, p = 0.002) longer than those without fever and that patients having bilateral pneumonia were hospitalized 3.4 days (95%CI 0.49 to 6.25, p = 0.023) longer than those with normal CT scan results. We also found weak evidence suggesting that patients with diabetes were hospitalized 3.2 days longer than those without diabetes (95%CI -0.2 to 6.56, p = 0.065). However, we observed no significant differences in LOS between symptomatic and asymptomatic patients and between patients who received treatment and those without treatment. Longer duration of hospitalization among non-severe COVID-19 patients is associated with having fever, bilateral pneumonia on CT scan and diabetes. However, being asymptomatic and using supportive medications at the early stage of infection do not have significant influences on LOS. Our study is a single-centered study with relatively small sample size. The findings provide evidence for predicting hospital bed demand in a novel response scenario and may help decision-makers in preparing for ramping up the health system capacity.

As the COVID19 spread in the US continues to grow, local and state officials face difficult decisions about when and how to transition to a new normal. We developed an agent-based simulation model to project the infection spread; outcomes include the number of COVID19 infections and resulting severe outcomes, and the need for hospital capacity under social distancing, particularly, shelter-in-place and voluntary quarantine. We populated the model using COVID19-specific parameters for the natural history of the disease and data from Georgia on the agents interactions and demographics. The simulation study covered a six-month period, testing different social distancing scenarios, including baselines (no-intervention or school closure only) and combinations of shelter-in-place and voluntary quarantine with different timelines and compliance levels. The outcomes are compared at the state and community levels. Main outcomes are the number and percentage of cumulative and daily new and symptomatic and asymptomatic infections, hospitalizations, and deaths; COVID19-related demand for hospital beds, ICU beds, and ventilators. Results: The combined intervention of shelter-in-place followed by voluntary quarantine reduced peak infections from 180,000 under no intervention and 120,000 under school closure, respectively, to below 80,000, and delayed the peak from April to June or later. Increasing shelter-in-place duration from four to five weeks yielded 3-14% and 4-6% decrease in cumulative infection and fatality rates, respectively. Regardless of the shelter-in-place duration, increasing voluntary quarantine compliance decreased daily new infections from almost 80,000 to 50,000, and decreased cumulative infection rate by 50%. The total number of fatalities ranged from 6,150 to 17,900 under different scenarios. Peak infection date varied across scenarios and counties; on average, increasing shelter-in-place duration delayed the peak day by 7 days across counties. The peak percentage is similar across rural and urban counties. Region D is estimated to have the highest COVID19-related healthcare needs with 7,357 hospital beds, 1,141 ICU beds, and 558 ventilators. Conclusions and Relevance Shelter-in-place followed by voluntary quarantine substantially reduce COVID19 infections, healthcare resource needs, and severe outcomes; delay the peak; and enable better preparedness. Time of the peak is projected to vary across locations, enabling reallocation of health system capacity.

Public health emergency of SARS-CoV-2 has facilitated diagnostic testing as a related medical countermeasure against COVID-19 outbreak. Numerous serologic antibody tests have become available through an expedited federal emergency use only process. This paper highlights the analytical characteristic of an ELISA based assay by AnshLabs and three random access immunoassay (RAIA) by DiaSorin, Roche, and Abbott that have been approved for emergency use authorization (EUA), at a tertiary academic center in a low disease-prevalence area. The AnshLabs gave higher estimates of sero-prevalence, over the three RAIA methods. For positive results, AnshLabs had 93.3% and 100% agreement with DiaSorin or Abbott and Roche respectively. For negative results, AnshLabs had 74.3% and 78.3% agreement with DiaSorin and Roche or Abbott respectively. All discrepant samples that were positive by AnshLabs and negative by RAIA tested positive by all-in-one step SARS-CoV-2 Total (COV2T) assay performed on the automated Siemens Advia Centaur XPT analyzer. None of these methods, however, are useful in early diagnosis of SARS-CoV-2.

Introduction An increase in the incidence of OHCA during the COVID-19 pandemic has been recently demonstrated. However, there are no data about how the COVID-19 epidemic influenced the treatment of OHCA victims. Methods We performed an analysis of the Lombardia Cardiac Arrest Registry comparing all the OHCAs occurred in the Provinces of Lodi, Cremona, Pavia and Mantua (northern Italy) in the first 100 days of the epidemic with those occurred in the same period in 2019. Results The OHCAs occurred were 694 in 2020 and 520 in 2019. Bystander cardiopulmonary resuscitation (CPR) rate was lower in 2020 (20% vs 31%, p Conclusion Compared to 2019, during the 2020 COVID-19 outbreak we observed a lower attitude of laypeople to start CPR, while resuscitation attempts by BLS and ALS staff were not influenced by suspected/confirmed infection, even at univariable analysis.

The spread of COVID-19 implied a large and fast increase of demand for intensive care services. To face this increase in demand, health care systems need to adapt their response by increasing hospital beds, intensive care unit (ICU) capacity and by (re-)deploying doctors and other personnel. This paper proposes a forecast approach based on the Vector Error Correction model for the daily counts of hospitalized patients with symptoms and of patients in ICU, using publicly available data on the current COVID-19 outbreak in Italy, Switzerland and Spain. The level of analysis is the local government managing the health care system response, which corresponds to regions for Italy. The one-week-ahead forecasts are validated with out-of-sample data over successive weeks; they are found to provide timely and robust prediction of ICU capacity needs in Lombardy, the most-affected Italian region, starting from the sample of the first 2 weeks of data. The same methodology is successfully validated on other Italian regions, Switzerland and Spain. This approach may be used in other countries/regions/provinces to help adapt the health care system response to COVID-19 (or other similar disease); for this purpose, the open-source software code to produce the forecasts is provided with the paper.

To circumvent the limited availability of RNA extraction reagents, we aimed to develop a protocol for direct RT-qPCR to detect SARS-CoV-2 in nasopharyngeal swabs without RNA extraction. Nasopharyngeal specimens positive for SARS-CoV-2 and other coronaviruses collected in universal viral transport (UVT) medium were pre-processed by several commercial and laboratory-developed methods and tested by RT-qPCR assays without RNA extraction using different RT-qPCR master mixes. The results were compared to that of standard approach that involves RNA extraction. Incubation of specimens at 65°C for 10 minutes along with the use of TaqPath™ 1-Step RT-qPCR Master Mix provides higher analytical sensitivity for detection of SARS-CoV-2 RNA than many other conditions tested. The optimized direct RT-qPCR approach demonstrated a limit of detection of 6.6x103 copy/ml and high reproducibility (co-efficient of variation = 1.2%). In 132 nasopharyngeal specimens submitted for SARS-CoV-2 testing, the sensitivity, specificity and accuracy of our optimized approach were 95%, 99% and 98.5%, respectively, with reference to the standard approach. Also, the RT-qPCR CT values obtained by the two methods were positively correlated (Pearson correlation coefficient r = 0.6971, p = 0.0013). The rate of PCR inhibition by the direct approach was 8% compared to 9% by the standard approach. Our simple approach to detect SARS-CoV-2 RNA by direct RT-qPCR may help laboratories continue testing for the virus despite reagent shortages or expand their testing capacity in resource limited settings.

BackgroundIn the early phase of the Covid-19 pandemic, mainly data related to the burden of care required by infected patients were reported. The aim of this study was to illustrate the timeline of actions taken and to measure and analyze their impact on surgical patients.MethodThis is a retrospective review of actions to limit Covid-19 spread and their impact on surgical activity in a Swiss tertiary referral center. Data on patient care, human resources and hospital logistics were collected. Impact on surgical activity was measured by comparing 6-week periods before and after the first measures were taken.ResultsAfter the first Swiss Covid-19 case appeared on February 25, progressively restrictive measures were taken over a period of 23 days. Covid-19 positive inpatients increased from 5 to 131, and ICU patients from 2 to 31, between days 10 and 30, respectively, without ever overloading resources. A 43% decrease of elective visceral surgical procedures was observed after Covid-19 (295 vs 165, pConclusionWhile allowing for maximal care of Covid-19 patients during the pandemic, the shift of resources limited the access to elective surgical care, with less impact on cancer care.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, in late 2019 and Covid-19, a disease caused by SARS-CoV-2 became a pandemic in March 2020. As the pandemic still unfolds, uncertainty circles around the impact of SARS-CoV-2 infection on patients with chronic diseases, including autoimmune diseases such as multiple sclerosis (MS). To diminish the risk of SARS-CoV-2 infection and lessen the impact of the Covid-19 pandemic on the healthcare of MS patients, it is essential to understand knowledge, attitudes, and various behavioral practices related to Covid-19 among MS patients. Therefore, this study aimed to look at the behavioral practices related to Covid-19 among patients with MS. A total of 176 MS patients diagnosed at least one year before the survey were conveniently sampled online in Saudi Arabia and their data collected using a structured interview questionnaire in electronic Google form. We determined the reliability of the questionnaire by measuring its internal consistency in a pilot sample of 30 participants. Overall, more than 80% of participants had good knowledge and attitudes towards Covid-19. However, this did not correlate well with the impact on healthcare (r = 0.06). Our study revealed that 46% of participants were anxious about taking their medication, and 32% of participants missed their hospital appointments. Furthermore, 15% of the participants had a relapse but did not go to the hospital because of the pandemic, 15.9% stopped their DMTs, and 35.2% missed drug infusions or refills. Our study revealed overall good knowledge and attitudes related to Covid-19 among MS patients. However, the healthcare impact was considerable, as 32% of the participants missed their hospital appointments, and another 15% had a relapse. This highlights the significance of the impact of the Covid-19 pandemic on the healthcare of patients with MS. Measures to mitigate the effect of the pandemic on healthcare service delivery to patients with MS, such as telemedicine, should be strongly encouraged.

The current coronavirus pandemic is an unprecedented public health challenge that is having a devastating economic impact on households. Using a sample of 230,540 respondents to an online survey from 17 countries in Latin America and the Caribbean, the study shows that the economic impacts are large and unequal: 45 percent of respondents report that a household member has lost their job and, among households owning small businesses, 59 percent of respondents report that a household member has closed their business. Among households with the lowest income prior to the pandemic, 71 percent report that a household member lost their job and 61 percent report that a household member has closed their business. Declines in food security and health are among the disproportionate impacts. The findings provide evidence that the current public health crisis will exacerbate economic inequality and provides some of the first estimates of the impact of the pandemic on the labor market and well-being in developing countries.

In Bangladesh, an array of measures have been adopted to control the rapid spread of the COVID-19 epidemic. Such general population control measures could significantly influence perception, knowledge, attitudes, and practices (KAP) towards COVID-19. Here, we assessed KAP towards COVID-19 immediately after the lock-down measures were implemented and during the rapid rise period of the outbreak. Online-based cross-sectional study conducted from March 29 to April 19, 2020, involving Bangladeshi residents aged 12–64 years, recruited via social media. After consenting, participants completed an online survey assessing socio-demographic variables, perception, and KAP towards COVID-19. Of the 2017 survey participants, 59.8% were male, the majority were students (71.2%), aged 21–30 years (57.9%), having a bachelor's degree (61.0%), having family income >30,000 BDT (50.0%), and living in urban areas (69.8). The survey revealed that 48.3% of participants had more accurate knowledge, 62.3% had more positive attitudes, and 55.1% had more frequent practices regarding COVID-19 prevention. Majority (96.7%) of the participants agreed ‘COVID-19 is a dangerous disease’, almost all (98.7%) participants wore a face mask in crowded places, 98.8% agreed to report a suspected case to health authorities, and 93.8% implemented washing hands with soap and water. In multiple logistic regression analyses, COVID-19 more accurate knowledge was associated with age and residence. Sociodemographic factors such as being older, higher education, employment, monthly family income >30,000 BDT, and having more frequent prevention practices were the more positive attitude factors. More frequent prevention practice factors were associated with female sex, older age, higher education, family income > 30,000 BDT, urban area residence, and having more positive attitudes. To improve KAP of general populations is crucial during the rapid rise period of a pandemic outbreak such as COVID-19. Therefore, development of effective health education programs that incorporate considerations of KAP-modifying factors is needed.

BackgroundHydroxychloroquine (HCQ) is widely used in the treatment of malaria, rheumatologic disease such as lupus, and most recently, COVID-19. These uses raise concerns about its safe use in the setting of glucose-6-phosphate dehydrogenase (G6PD) deficiency, especially as 11% of African American men carry the G6PD A- variant. However, limited data exist regarding the safety of HCQ in this population.Study design and methodsRecently, we created a novel "humanized" mouse model containing the G6PD deficiency A- variant (Val68Met) using CRISPR technology. We tested the effects of high-dose HCQ administration over 5 days on hemolysis in our novel G6PD A- mice. In addition to standard hematologic parameters including plasma hemoglobin, erythrocyte methemoglobin, and reticulocytes, hepatic and renal function were assessed after HCQ.ResultsResidual erythrocyte G6PD activity in G6PD A- mice was ~6% compared to wild-type (WT) littermates. Importantly, we found no evidence of clinically significant intravascular hemolysis, methemoglobinemia, or organ damage in response to high-dose HCQ.ConclusionsThough the effects of high doses over prolonged periods was not assessed, this study provides early, novel safety data of the use of HCQ in the setting of G6PD deficiency secondary to G6PD A-. In addition to novel safety data for HCQ, to our knowledge, we are the first to present the creation of a "humanized" murine model of G6PD deficiency.

The SARS-CoV-2 virion responsible for the current world-wide pandemic COVID-19 has a characteristic Spike protein (S) on its surface that embellishes both a prefusion state and fusion state. The prefusion Spike protein (S) is a large trimeric protein where each protomer may be in a so-called Up state or Down state, depending on the configuration of its receptor binding domain (RBD) within its distal, prefusion S1 domain. The Up state is believed to allow binding of the virion to ACE-2 receptors on human epithelial cells, whereas the Down state is believed to be relatively inactive or reduced in its binding behavior. We have performed detailed all-atom, dominant energy landscape mappings for noncovalent interactions (charge, partial charge, and van der Waals) of the SARS-CoV-2 Spike protein in its static prefusion state based on two recent and independent experimental structure publications. We included both interchain interactions and intrachain (domain) interactions in our mappings in order to determine any telling differences (different so-called “glue” points) between residues in the Up and Down state protomers. The S2 proximal, fusion domain demonstrated no appreciable energetic differences between Up and Down protomers, including interchain as well as each protomer’s intrachain, S1-S2 interactions. However, the S1 domain interactions across neighboring protomers, which include the RBD-NTD cross chain interactions, showed significant energetic differences between Up-Down and Down-Down neighboring protomers. This included, for example, a key RBD residue ARG357 in the Up-Down interaction and a three residue sequence ALA520-PRO521-ALA522, associated with a turn structure in the RBD of the Up state protomer, acting as a stabilizing interaction with the NTD of its neighbor protomer. Additionally, our intra chain dominant energy mappings within each protomer, identified a significant “glue” point or possible “latch” for the Down state protomer between the S1 subdomain, SD1, and the RBD domain of the same protomer that was completely missing in the Up state protomer analysis. Ironically, this dominant energetic interaction in the Down state protomer involved the backbone atoms of the same three residue sequence ALA520-PRO521-ALA522 of the RBD with the amino acid R-group of GLN564 in the SD1 domain. Thus, this same three residue sequence acts as a stabilizer of the RBD in the Up conformation through its interactions with its neighboring NTD chain and a kind of latch in the Down state conformation through its interactions with its own SD1 domain. The dominant interaction energy residues identified here are also conserved across reported variations of SARS-CoV-2, as well as the closely related virions SARS-Cov and the bat corona virus RatG13. We conducted preliminary molecular dynamics simulations across 0.1 μ seconds to see if this latch provided structural stability and indeed found that a single point mutation (Q564G) resulted in the latch releasing transforming the protomer from the Down to the Up state conformation. Full trimeric Spike protein studies of the same mutation across all protomers, however, did not exhibit latch release demonstrating the critical importance of interchain interactions across the S1 domain, including RBD-NTD neighboring chain interactions. Therapies aimed at disrupting these noncovalent interactions could be a viable route for the physico-chemical mitigation of this deadly virion.

Background: Healthcare professionals (HCPs) on the front lines against COVID-19 may face increased workload, and stress. Understanding HCPs’ risk for burnout is critical to supporting HCPs and maintaining the quality of healthcare during the pandemic. Methods: To assess exposure, perceptions, workload, and possible burnout of HCPs during the COVID-19 pandemic we conducted a cross-sectional survey. The main outcomes and measures were HCPs’ self-assessment of burnout and other experiences and attitudes associated with working during the COVID-19 pandemic. Findings: A total of 2,707 HCPs from 60 countries participated in this study. Fifty-one percent of HCPs reported burnout. Burnout was associated with work impacting household activities (RR=1·57, 95% CI=1·39-1·78, P