Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study

Trends, Treatment Approaches, and In-Hospital Mortality for Acute Coronary Syndrome in Japan During the Coronavirus Disease 2019 Pandemic

Aim: The coronavirus disease 2019 (COVID-19) pandemic has left negative spillover effects on the entire health care system. Previous studies have suggested significant declines in cases of acute coronary syndrome (ACS) and primary percutaneous coronary intervention (PCI) during the COVID-19 pandemic.

Methods: We performed a quasi-experimental, retrospective cohort study of ACS hospitalisations by using a multi-institutional administrative claims database in Japan. We used interrupted time series analyses to ascertain impacts on cases, treatment approaches, and in-hospital mortality before and after Japan’s state of emergency to respond to COVID-19. The primary outcome was the change in ACS cases per week.

Results: A total of 30,198 ACS cases (including 21,612 acute myocardial infarction and 8,586 unstable angina) were confirmed between 1^st July 2018 and 30^th June 2020. After the state of emergency, an immediate decrease was observed in ACS cases per week (-18.3%; 95% confidence interval, -13.1 to -23.5%). No significant differences were found in the severity of Killip classification (P=0.51) or cases of fibrinolytic therapy (P=0.74). The impact of the COVID-19 pandemic on in-hospital mortality in ACS patients was no longer observed after adjustment for clinical characteristics (adjusted odds ratio, 0.93; 95% confidence interval, 0.78 to 1.12;P=0.49).

Conclusions: We demonstrated the characteristics and trends of ACS cases in a Japanese population by applying interrupted time series analyses. Our findings provide significant insights into the association between COVID-19 and decreases in ACS hospitalisations during the pandemic.

Post-covid syndrome in individuals admitted to hospital with covid-19: retrospective cohort study

OBJECTIVE

To quantify rates of organ specific dysfunction in individuals with covid-19 after discharge from hospital compared with a matched control group from the general population.

DESIGN

Retrospective cohort study.

SETTING

NHS hospitals in England.

PARTICIPANTS

47 780 individuals (mean age 65, 55% men) in hospital with covid-19 and discharged alive by 31 August 2020, exactly matched to controls from a pool of about 50 million people in England for personal and clinical characteristics from 10 years of electronic health records.

MAIN OUTCOME MEASURES

Rates of hospital readmission (or any admission for controls), all cause mortality, and diagnoses of respiratory, cardiovascular, metabolic, kidney, and liver diseases until 30 September 2020. Variations in rate ratios by age, sex, and ethnicity.

RESULTS

Over a mean follow-up of 140 days, nearly a third of individuals who were discharged from hospital after acute covid-19 were readmitted (14 060 of 47 780) and more than 1 in 10 (5875) died after discharge, with these events occurring at rates four and eight times greater, respectively, than in the matched control group. Rates of respiratory disease (P<0.001), diabetes (P<0.001), and cardiovascular disease (P<0.001) were also significantly raised in patients with covid-19, with 770 (95% confidence interval 758 to 783), 127 (122 to 132), and 126 (121 to 131) diagnoses per 1000 person years, respectively. Rate ratios were greater for individuals aged less than 70 than for those aged 70 or older, and in ethnic minority groups compared with the white population, with the largest differences seen for respiratory disease (10.5 (95% confidence interval 9.7 to 11.4) for age less than 70 years v 4.6 (4.3 to 4.8) for age ≥70, and 11.4 (9.8 to 13.3) for non-white v 5.2 (5.0 to 5.5) for white individuals).

CONCLUSIONS

Individuals discharged from hospital after covid-19 had increased rates of multiorgan dysfunction compared with the expected risk in the general population. The increase in risk was not confined to the elderly and was not uniform across ethnicities. The diagnosis, treatment, and prevention of post-covid syndrome requires integrated rather than organ or disease specific approaches, and urgent research is needed to establish the risk factors.

Multiorgan impairment in low-risk individuals with post-COVID-19 syndrome: a prospective, community-based study

OBJECTIVE

To assess medium-term organ impairment in symptomatic individuals following recovery from acute SARS-CoV-2 infection.

DESIGN

Baseline findings from a prospective, observational cohort study.

SETTING

Community-based individuals from two UK centres between 1 April and 14 September 2020.

PARTICIPANTS

Individuals ≥18 years with persistent symptoms following recovery from acute SARS-CoV-2 infection and age-matched healthy controls.

INTERVENTION

Assessment of symptoms by standardised questionnaires (EQ-5D-5L, Dyspnoea-12) and organ-specific metrics by biochemical assessment and quantitative MRI.

MAIN OUTCOME MEASURES

Severe post-COVID-19 syndrome defined as ongoing respiratory symptoms and/or moderate functional impairment in activities of daily living; single-organ and multiorgan impairment (heart, lungs, kidneys, liver, pancreas, spleen) by consensus definitions at baseline investigation.

RESULTS

201 individuals (mean age 45, range 21-71 years, 71% female, 88% white, 32% healthcare workers) completed the baseline assessment (median of 141 days following SARS-CoV-2 infection, IQR 110-162). The study population was at low risk of COVID-19 mortality (obesity 20%, hypertension 7%, type 2 diabetes 2%, heart disease 5%), with only 19% hospitalised with COVID-19. 42% of individuals had 10 or more symptoms and 60% had severe post-COVID-19 syndrome. Fatigue (98%), muscle aches (87%), breathlessness (88%) and headaches (83%) were most frequently reported. Mild organ impairment was present in the heart (26%), lungs (11%), kidneys (4%), liver (28%), pancreas (40%) and spleen (4%), with single-organ and multiorgan impairment in 70% and 29%, respectively. Hospitalisation was associated with older age (p=0.001), non-white ethnicity (p=0.016), increased liver volume (p<0.0001), pancreatic inflammation (p<0.01), and fat accumulation in the liver (p<0.05) and pancreas (p<0.01). Severe post-COVID-19 syndrome was associated with radiological evidence of cardiac damage (myocarditis) (p<0.05).

CONCLUSIONS

In individuals at low risk of COVID-19 mortality with ongoing symptoms, 70% have impairment in one or more organs 4 months after initial COVID-19 symptoms, with implications for healthcare and public health, which have assumed low risk in young people with no comorbidities.

TRIAL REGISTRATION NUMBER

NCT04369807; Pre-results.

Weak humoral immune reactivity among residents of long-term care facilities following one dose of the BNT162b2 mRNA COVID-19 vaccine

Background

Several Canadian provinces are extending the interval between COVID-19 vaccine doses to increase population vaccine coverage more rapidly. However, immunogenicity of these vaccines after one dose is incompletely characterized, particularly among the elderly, who are at greatest risk of severe COVID-19.

Methods

We assessed SARS-CoV-2 humoral responses pre-vaccine and one month following the first dose of BNT162b2 mRNA vaccine, in 12 COVID-19 seronegative residents of long-term care facilities (median age, 82 years), 18 seronegative healthcare workers (HCW; median age, 36 years) and 4 convalescent HCW. Total antibody responses to SARS-CoV-2 nucleocapsid (N) and spike protein receptor binding domain (S/RBD) were assessed using commercial immunoassays. We quantified IgG and IgM responses to S/RBD and determined the ability of antibodies to block S/RBD binding to ACE2 receptor using ELISA. Neutralizing antibody activity was also assessed using pseudovirus and live SARS-CoV-2.

Results

After one vaccine dose, binding antibodies against S/RBD were ~4-fold lower in residents compared to HCW (p<0.001). Inhibition of ACE2 binding was 3-fold lower in residents compared to HCW (p=0.01) and pseudovirus neutralizing activity was 2-fold lower (p=0.003). While six (33%) seronegative HCW neutralized live SARS-CoV-2, only one (8%) resident did (p=0.19). In contrast, convalescent HCW displayed 7- to 20-fold higher levels of binding antibodies and substantial ability to neutralize live virus after one dose.

Interpretation

Extending the interval between COVID-19 vaccine doses may pose a risk to the elderly due to lower vaccine immunogenicity in this group. We recommend that second doses not be delayed in elderly individuals.

Assessing the Impact of the Covid-19 Pandemic on US Mortality: A County-Level Analysis

Background.

Covid-19 excess deaths refer to increases in mortality over what would normally have been expected in the absence of the Covid-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to Covid-19. In this study, we take advantage of county-level variation in Covid-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to Covid-19 varies across subsets of counties defined by sociodemographic and health characteristics.

Methods and Findings.

In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct Covid-19 and all-cause mortality occurring in U.S. counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a ten week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more Covid-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black and 59.6% non-Hispanic White. 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and Covid-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to Covid-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than Covid-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to Covid-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of Covid-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to Covid-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics.

Conclusions.

In this study, we found that direct Covid-19 death counts in the United States in 2020 substantially underestimated total excess mortality attributable to Covid-19. Racial and socioeconomic inequities in Covid-19 mortality also increased when excess deaths not assigned to Covid-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

Evolution of Pathology Patterns in Persons Who Died From COVID-19 in Italy: A National Study Based on Death Certificates

Background: In Italy, during the first epidemic wave of 2020, the peak of coronavirus disease 2019 (COVID-19) mortality was reached at the end of March. Afterward, a progressive reduction was observed until much lower figures were reached during the summer, resulting from the contained circulation of SARS-CoV-2. This study aimed to determine if and how the pathological patterns of the individuals deceased from COVID-19 changed during the phases of epidemic waves in terms of: (i) main cause of death, (ii) comorbidities, and (iii) complications related to death. Methods: Death certificates of persons who died and tested positive for SARS-CoV-2, provided by the National Surveillance system, were coded according to ICD rev10. Deaths due to COVID-19 were defined as those in which COVID-19 was the underlying cause of death. Results: The percentage of COVID-19 deaths varied over time. It decreased in the downward phase of the epidemic curve (76.6 vs. 88.7%). In February-April 2020, hypertensive heart disease was mentioned as a comorbidity in 18.5% of death certificates, followed by diabetes (15.9% of cases), ischemic heart disease (13.1%), and neoplasms (12.1%). In May-September, the most frequent comorbidity was neoplasms (17.3% of cases), followed by hypertensive heart disease (14.9%), diabetes (14.8%), and dementia/Alzheimer's disease (11.9%). The most mentioned complications in both periods were pneumonia and respiratory failure with a frequency far higher than any other condition (78.4% in February-April 2020 and 63.7% in May-September 2020). Discussion: The age of patients dying from COVID-19 and their disease burden increased in the May-September 2020 period. A more serious disease burden was observed in this period, with a significantly higher frequency of chronic pathologies. Our study suggests better control of the virus' lethality in the second phase of the epidemic, when the health system was less burdened. Moreover, COVID-19 care protocols had been created in hospitals, and knowledge about the diagnosis and treatment of COVID-19 had improved, potentially leading to more accurate diagnosis and better treatment. All these factors may have improved survival in patients with COVID-19 and led to a shift in mortality to older, more vulnerable, and complex patients.

Ensemble learning for poor prognosis predictions: A case study on SARS-CoV-2

OBJECTIVE

Risk prediction models are widely used to inform evidence-based clinical decision making. However, few models developed from single cohorts can perform consistently well at population level where diverse prognoses exist (such as the SARS-CoV-2 [severe acute respiratory syndrome coronavirus 2] pandemic). This study aims at tackling this challenge by synergizing prediction models from the literature using ensemble learning.

MATERIALS AND METHODS

In this study, we selected and reimplemented 7 prediction models for COVID-19 (coronavirus disease 2019) that were derived from diverse cohorts and used different implementation techniques. A novel ensemble learning framework was proposed to synergize them for realizing personalized predictions for individual patients. Four diverse international cohorts (2 from the United Kingdom and 2 from China; N = 5394) were used to validate all 8 models on discrimination, calibration, and clinical usefulness.

RESULTS

Results showed that individual prediction models could perform well on some cohorts while poorly on others. Conversely, the ensemble model achieved the best performances consistently on all metrics quantifying discrimination, calibration, and clinical usefulness. Performance disparities were observed in cohorts from the 2 countries: all models achieved better performances on the China cohorts.

DISCUSSION

When individual models were learned from complementary cohorts, the synergized model had the potential to achieve better performances than any individual model. Results indicate that blood parameters and physiological measurements might have better predictive powers when collected early, which remains to be confirmed by further studies.

CONCLUSIONS

Combining a diverse set of individual prediction models, the ensemble method can synergize a robust and well-performing model by choosing the most competent ones for individual patients.

Electrocardiographic findings at presentation and clinical outcome in patients with SARS-CoV-2 infection

Aims

The main severe complications of SARS-CoV-2 infection are pneumonia and respiratory distress syndrome. Recent studies, however, reported that cardiac injury, as assessed by troponin levels, is associated with a worse outcome in these patients. No study hitherto assessed whether the simple standard electrocardiogram (ECG) may be helpful for risk stratification in these patients.

Methods and results

We studied 324 consecutive patients admitted to our Emergency Department with a confirmed diagnosis of SARS-CoV-2 infection. Standard 12-lead ECG recorded on admission was assessed for cardiac rhythm and rate, atrioventricular and intraventricular conduction, abnormal Q/QS wave, ST segment and T wave changes, corrected QT interval, and tachyarrhythmias. At a mean follow-up of 31 ± 11 days, 44 deaths occurred (13.6%). Most ECG variables were significantly associated with mortality, including atrial fibrillation (P = 0.002), increasing heart rate (P = 0.002), presence of left bundle branch block (LBBB; P < 0.001), QRS duration (P <0 .001), a QRS duration of ≥110 ms (P < 0.001), ST segment depression (P < 0.001), abnormal Q/QS wave (P = 0.034), premature ventricular complexes (PVCs; P = 0.051), and presence of any ECG abnormality [hazard ratio (HR) 4.58; 95% confidence interval (CI) 2.40–8.76; P < 0.001]. At multivariable analysis, QRS duration (P = 0.002), QRS duration ≥110 ms (P = 0.03), LBBB (P = 0.014) and presence of any ECG abnormality (P = 0.04) maintained a significant independent association with mortality.

Conclusion

Our data show that standard ECG can be helpful for an initial risk stratification of patients admitted for SARS-CoV-2 infectious disease.

Collaborative Platform Trials to Fight COVID-19: Methodological and Regulatory Considerations for a Better Societal Outcome

For the development of coronavirus disease 2019 (COVID‐19) drugs during the ongoing pandemic, speed is of essence whereas quality of evidence is of paramount importance. Although thousands of COVID‐19 trials were rapidly started, many are unlikely to provide robust statistical evidence and meet regulatory standards (e.g., because of lack of randomization or insufficient power). This has led to an inefficient use of time and resources. With more coordination, the sheer number of patients in these trials might have generated convincing data for several investigational treatments. Collaborative platform trials, comparing several drugs to a shared control arm, are an attractive solution. Those trials can utilize a variety of adaptive design features in order to accelerate the finding of life‐saving treatments. In this paper, we discuss several possible designs, illustrate them via simulations, and also discuss challenges, such as the heterogeneity of the target population, time‐varying standard of care, and the potentially high number of false hypothesis rejections in phase II and phase III trials. We provide corresponding regulatory perspectives on approval and reimbursement, and note that the optimal design of a platform trial will differ with our societal objective and by stakeholder. Hasty approvals may delay the development of better alternatives, whereas searching relentlessly for the single most efficacious treatment may indirectly diminish the number of lives saved as time is lost. We point out the need for incentivizing developers to participate in collaborative evidence‐generation initiatives when a positive return on investment is not met.

UK prevalence of underlying conditions which increase the risk of severe COVID-19 disease: a point prevalence study using electronic health records

BACKGROUND

Characterising the size and distribution of the population at risk of severe COVID-19 is vital for effective policy and planning. Older age, and underlying health conditions, are associated with higher risk of death from COVID-19. This study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom.

METHODS

We used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to estimate the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region with binomial exact confidence intervals. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status.

RESULTS

On 5 March 2019, 24.4% of the UK population were at risk due to a record of at least one underlying health condition, including 8.3% of school-aged children, 19.6% of working-aged adults, and 66.2% of individuals aged 70 years or more. 7.1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1.6% of the population had a new diagnosis of cancer in the past 5 y.

CONCLUSIONS

The population at risk of severe COVID-19 (defined as either aged ≥70 years, or younger with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals. Our national estimates broadly support the use of Global Burden of Disease modelled estimates in other countries. We provide age- and region- stratified prevalence for each condition to support effective modelling of public health interventions and planning of vaccine resource allocation. The high prevalence of health conditions among older age groups suggests that age-targeted vaccination strategies may efficiently target individuals at higher risk of severe COVID-19.

The prediction of the lifetime of the new coronavirus in the USA using mathematical models

The World Health Organization (WHO) on December 31, 2019, was informed of several cases of respiratory diseases of unknown origin in the city of Wuhan in the Chinese Province of Hubei, the clinical manifestations of which were similar to those of viral pneumonia and manifested as fever, cough, and shortness of breath. And, the disease caused by the virus is named the new coronavirus disease 2019 and it will be abbreviated as 2019-nCoV and COVID-19. As of January 30, 2020, the WHO classified this epidemic as a global health emergency (Chung et al. in Radiology 295(1):202-207, 2020). It is an international real-life problem. Due to deaths, globally everyone is under fear. Now, it is the responsibility of researchers to give hope to the people. In this article, we aim to better protect people and general pandemic preparedness by predicting the lifetime of the disease-causing virus using three mathematical models. This article deals with a complex real-life problem people face all over the world, an international real-life problem. The main focus is on the USA due to large infection and death due to coronavirus and thereby the life of every individual is uncertain. The death counts of the USA from February 29 to April 22, 2020, are used in this article as a data set. The death counts of the USA are fitted by the solutions of three mathematical models and a solution to an international problem is achieved. Based on the death rate, the lifetime of the coronavirus COVID-19 is predicted as 1464.76 days from February 29, 2020. That is, after March 2024 there will be no death in the USA due to COVID-19 if everyone follows the guidelines of WHO and the advice of healthcare workers. People and government can get prepared for this situation and many lives can be saved. It is the contribution of soft computing. Finally, this article suggests several steps to control the spread and severity of the disease. The research work, the lifetime prediction presented in this article is entirely new and differs from all other articles in the literature.

Excess All-Cause Deaths during Coronavirus Disease Pandemic, Japan, January-May 20201

To provide insight into the mortality burden of coronavirus disease (COVID-19) in Japan, we estimated the excess all-cause deaths for each week during the pandemic, January–May 2020, by prefecture and age group. We applied quasi-Poisson regression models to vital statistics data. Excess deaths were expressed as the range of differences between the observed and expected number of all-cause deaths and the 95% upper bound of the 1-sided prediction interval. A total of 208–4,322 all-cause excess deaths at the national level indicated a 0.03%–0.72% excess in the observed number of deaths. Prefecture and age structure consistency between the reported COVID-19 deaths and our estimates was weak, suggesting the need to use cause-specific analyses to distinguish between direct and indirect consequences of COVID-19.

Assessing relative COVID-19 mortality: a Swiss population-based study

OBJECTIVE

Severity of the COVID-19 has been previously reported in terms of absolute mortality in SARS-CoV-2 positive cohorts. An assessment of mortality relative to mortality in the general population is presented.

DESIGN

Retrospective population-based study.

SETTING

Individual information on symptomatic confirmed SARS-CoV-2 patients and subsequent deaths from any cause were compared with the all-cause mortality in the Swiss population of 2018. Starting 23 February 2020, mortality in COVID-19 patients was monitored for 80 days and compared with the population mortality observed in the same time of year starting 23 February 2018.

PARTICIPANTS

5 102 300 inhabitants of Switzerland aged 35-95 without COVID-19 (general population in spring 2018) and 20 769 persons tested positively for COVID-19 during the first wave in spring 2020.

MEASUREMENTS

Sex-specific and age-specific mortality rates were estimated using Cox proportional hazards models. Absolute probabilities of death were predicted and risk was assessed in terms of relative mortality by taking the ratio between the sex-specific and age-specific absolute mortality in COVID-19 patients and the corresponding mortality in the 2018 general population.

RESULTS

Absolute mortalities increased with age and were higher for males compared with females, both in the general population and in positively tested persons. A confirmed SARS-CoV-2 infection substantially increased the probability of death across all patient groups at least eightfold. The highest relative mortality risks were observed among males and younger patients. Male COVID-19 patients exceeded the population hazard for males (HR 1.21, 95% CI 1.02 to 1.44). An additional year of age increased the population hazard in COVID-19 patients only marginally (HR 1.00, 95% CI 1.00 to 1.01).

CONCLUSIONS

Healthcare professionals, decision-makers and societies are provided with an additional population-adjusted assessment of COVID-19 mortality risk. In combination with absolute measures of risk, the relative risks presented here help to develop a more comprehensive understanding of the actual impact of COVID-19.

Change point detection for COVID-19 excess deaths in Belgium

Emerging at the end of 2019, COVID-19 has become a public health threat to people worldwide. Apart from deaths with a positive COVID-19 test, many others have died from causes indirectly related to COVID-19. Therefore, the COVID-19 confirmed deaths underestimate the influence of the pandemic on society; instead, the measure of ‘excess deaths’ is a more objective and comparable way to assess the scale of the epidemic and formulate lessons. One common practical issue in analysing the impact of COVID-19 is to determine the ‘pre-COVID-19′ period and the ‘post-COVID-19′ period. We apply a change point detection method to identify any change points using excess deaths in Belgium.

Biological Significance of Anti-SARS-CoV-2 Antibodies: Lessons Learned From Progressive Multifocal Leukoencephalopathy

OBJECTIVE

To discuss the pathogenic and diagnostic relevance of cellular and humoral immune responses against severe acute respiratory syndrome novel coronavirus (SARS-COV-2) and pertinent observations made in progressive multifocal leukoencephalopathy (PML).

METHODS

Review of pertinent literature. RESULTS: There is at least 1 precedent for an antibody response against a viral pathogen that fails to provide host protection in the absence of immune-competent CD4+ T cells. PML is an infection of the CNS caused by JC virus (JCV), which commonly occurs during treatment with the therapeutic monoclonal antibody natalizumab. In this context, the humoral immune response fails to prevent JCV reactivation, and elevated anti-JCV serum indices are associated with a higher PML incidence. The more relevant immune-competent cells in host defense against JCV appear to be T cells. T cell-mediated responses are also detectable in convalescing patients with SARS-COV-2 irrespective of the humoral immune response.

CONCLUSION

Based on pathogenic lessons learned from PML under natalizumab therapy, we suggest the incorporation of functional assays that determine neutralizing properties of SARS-CoV-2-specific antibodies. In addition, we outline the potential role of T-cell detection assays in determining herd immunity in a given population or in studying therapeutic responses to vaccines.

Pandemics and pathology: a reflection on influenza, HIV/AIDS and SARS (COVID-19) pandemic infections

The COVID-19 pandemic has reminded pathologists of our significant roles in the management and understanding of rapidly spreading and dangerous pathogens, from identifying the agent to characterizing the clinical pathology to managing the dead. Cellular pathology - through autopsy - has depicted the main features: viral pneumonitis, acute lung injury, organising pneumonia, secondary bacterial pneumonia, thrombophilia and infarction, and systemic inflammatory response syndrome with multi-organ failure. These are similar to another viral pandemic of the 20th century, H1N1 influenza; but contrast with the second major more complicated pandemic, that of HIV/AIDS. The outcomes of these infections are compared, along with seasonal influenza and SARS-1-CoV disease. Work to be done on COVID-19 includes characterisation of the emerging 'long COVID' syndrome, and monitoring the complications of therapies and vaccination programs.

Prediction of the confirmed cases and deaths of global COVID-19 using artificial intelligence

The outbreak of coronavirus disease 2019 (COVID-19) has seriously affected the environment, ecology, economy, society, and human health. With the global epidemic dynamics becoming more and more serious, the prediction and analysis of the confirmed cases and deaths of COVID-19 has become an important task. We develop an artificial neural network (ANN) for modeling of the confirmed cases and deaths of COVID-19. The confirmed cases and deaths data are collected from January 20 to November 11, 2020 by the World Health Organization (WHO). By introducing root mean square error (RMSE), correlation coefficient (R), and mean absolute error (MAE), statistical indicators of the prediction model are verified and evaluated. The size of training and test confirmed cases and death base employed in the model is optimized. The best simulating performance with RMSE, R, and MAE is realized using the 7 past days' cases as input variables in the training and test dataset. And the estimated R are 0.9948 and 0.9683, respectively. Compared with different algorithms, experimental simulation shows that trainbr algorithm has better performance than other algorithms in reproducing the amount of the confirmed cases and deaths. This study shows that the ANN model is suitable for predicting the confirmed cases and deaths of COVID-19 in the future. Using the ANN model, we also predict the confirmed cases and deaths of COVID-19 from June 5, 2020 to November 11, 2020. During the predicting period, the R, RMSE, and MAE for new infected confirmed cases of COVID-19 are 0.9848, 17,554, and 12,229, respectively; the R, RMSE, and MAE for new confirmed deaths of COVID-19 are 0.8593, 631.8, and 463.7, respectively. The predicted confirmed cases and deaths of COVID-19 are very close to the actual confirmed cases and deaths. The results show that continuous and strict control measures should be taken to prevent the further spread of the epidemic.

Protocol for a patient-reported experience measures (PREMs) survey of patients discharged during the COVID-19 pandemic and their family caregivers

INTRODUCTION

In the Swiss canton of Valais, the first cases of SARS-CoV-2 were detected on 28 February 2020. Discharged patients' and their family caregivers' experiences in relation to safety, quality of care, trust and communication during the COVID-19 hospitalisation period remain unexplored. The study aims to collect the patient-reported experience measures (PREMs) survey of patients discharged during the COVID-19 pandemic and their family caregivers.

METHODS AND ANALYSIS

Patients aged ≥18 years, hospitalised between 28 February and 11 May 2020 and then discharged home, plus their family caregivers will be invited to complete a self-administrated questionnaire made up of 14 closed questions and 1 open-ended question. The questionnaire will include items on the patient's hospital trajectory and assess the interpersonal trust placed in nurses and physicians based on Krajewska-Kułak et al's Trust in Nurse Scale and Anderson et al's Trust in Physician Scale. Participants' perceived stress will be assessed using Cohen et al's Perceived Stress Scale. Feelings of safety will be examined based on Dryhurst et al's questionnaire on Risk Perception During Pandemics. After ethical clearance, data will be collected using a postal paper questionnaire and via an online web link. Descriptive and inferential statistics will be computed, and the open question will undergo a qualitative thematic analysis. We will analyse perceptions of the different hospital trajectories experienced by patients undergoing surgery with and without a SARS-CoV-2 infection.

ETHICS AND DISSEMINATION

The Human Research Ethics Committee of Vaud (2020-02025) authorised this study. Gathering experiences and learning about the impact of the COVID-19 pandemic on the social determinants of health among discharged patients and families fit in well with the Triple Aim framework and the PREMs survey. The study will formulate recommendations to support interventions in the face of the second wave of COVID-19 pandemic and their effects on patients' and their family caregivers' experiences.

Years of life lost to COVID-19 in 81 countries

Understanding the mortality impact of COVID-19 requires not only counting the dead, but analyzing how premature the deaths are. We calculate years of life lost (YLL) across 81 countries due to COVID-19 attributable deaths, and also conduct an analysis based on estimated excess deaths. We find that over 20.5 million years of life have been lost to COVID-19 globally. As of January 6, 2021, YLL in heavily affected countries are 2-9 times the average seasonal influenza; three quarters of the YLL result from deaths in ages below 75 and almost a third from deaths below 55; and men have lost 45% more life years than women. The results confirm the large mortality impact of COVID-19 among the elderly. They also call for heightened awareness in devising policies that protect vulnerable demographics losing the largest number of life-years.

Risk Factors and Effects of the Morbus: COVID-19 through the Biopsychosocial Model and Ecological Systems Approach to Social Work Practice

Utilizing the biopsychosocial model and the ecological systems theory, this disquisition explores on the risk factors associated with the COVID-19 pandemic. The discourse shows the interconnectedness of biological, psychological, and social domains in expatiating on the COVID-19 pandemic. It calls for the need to strengthen the resilience of the global community in the face of health outbreaks such as COVID-19. It emphasizes on the perspectives that pandemics are managed before they emerge through building systems that are resilient. Thus, it appreciates the need for a therapeutic milieu as a building block to resilience. The article calls for the adoption of a developmental stance to analyzing health outbreaks and clinical issues. The adumbration shows the reciprocity effects of the health outbreak [macrocosms] and individual factors [microcosms]. To its end, the paper implies that COVID-19 is a call for integration toward effective health planning between social policy formulators, urban and rural planners, epidemiologists, development practitioners, clinicians, researchers to mention but a few. Ultimately, the paper calls for social workers to consider a developmental-clinical social work approach which helps foster "health in all policies" so as to build resilience against the morbus and limit the proliferation of diseases.

"Factors influencing the outcome of COVID-19 patients admitted in a tertiary care hospital, Madurai.- a cross-sectional study"

Introduction

COVID19* is a new disease with significant mortality risk. Because of the scarcity of the study on factors associated with the mortality in Tamil Nadu present study was done to determine the factors associated with the outcome of the COVID19 patients admitted in a tertiary care hospital, Madurai.

Methodology

4530 lab confirmed COVID19 patients admitted from March to August 31st^, 2020; excluding the non-responders or who gave incomplete information were included in the study. Data retrieved from Case Investigation Forms *filled through telephonic interview. Chi -square test, Univariate and multivariate logistic regression were used to find out the association between the factors and risk of death(outcome).

Results

Out of 4530 COVID19 positive patients 381(8.4%) died and 4149(91.6%) were discharged. Using multivariate logistic regression* following were the factors predicted to be associated with mortality:Age group <17yrs(PR = 4.12),30-44yrs(PR = 2.28),45-59(PR = 3.12),60-69(PR = 4.26) and ≥ 70(PR = 7.05); male gender(PR = 1.26); breathlessness at the time of admission(PR = 7.05); with 1symptom (PR = 2.58), 2symptoms(PR = 3.16) and ≥ 3 symptoms(PR = 2.45); chronic kidney disease(PR = 3.07), malignancy(PR = 2.39); other chronic diseases(PR = 1.89); having only diabetes(PR = 1.58); diabetes with hypertension (PR = 1.70); diabetes with heart disease(PR = 1.94); Hypertension with heart disease(PR = 2.30); diabetes with hypertension and heart disease(PR = 1.58). Survival probability* was more than 90% when patient gets admitted within a week after symptom onset,<80% for between 7 and 10 days and declines thereafter.

Conclusion

Early insights into factors associated with COVID-19 deaths have been generated in the context of a global health emergency *which may help the treating physician.

The Age Structure, Stringency Policy, Income, and Spread of Coronavirus Disease 2019: Evidence From 209 Countries

This article aims at answering the following questions: (1) What is the influence of age structure on the spread of coronavirus disease 2019 (COVID-19)? (2) What can be the impact of stringency policy (policy responses to the coronavirus pandemic) on the spread of COVID-19? (3) What might be the quantitative effect of development levelincome and number of hospital beds on the number of deaths due to the COVID-19 epidemic? By employing the methodologies of generalized linear model, generalized moments method, and quantile regression models, this article reveals that the shares of median age, age 65, and age 70 and older population have significant positive impacts on the spread of COVID-19 and that the share of age 70 and older people in the population has a relatively greater influence on the spread of the pandemic. The second output of this research is the significant impact of stringency policy on diminishing COVID-19 total cases. The third finding of this paper reveals that the number of hospital beds appears to be vital in reducing the total number of COVID-19 deaths, while GDP per capita does not affect much the level of deaths of the COVID-19 pandemic. Finally, this article suggests some governmental health policies to control and decrease the spread of COVID-19.

Who should be prioritized for COVID-19 vaccination in China? A descriptive study

BACKGROUND

All countries are facing decisions about which population groups to prioritize for access to COVID-19 vaccination after the first vaccine products have been licensed, at which time supply shortages are inevitable. Our objective is to define the key target populations, their size, and priority for a COVID-19 vaccination program in the context of China.

METHODS

On the basis of utilitarian and egalitarian principles, we define and estimate the size of tiered target population groups for a phased introduction of COVID-19 vaccination, considering evolving goals as vaccine supplies increase, detailed information on the risk of illness and transmission, and past experience with vaccination during the 2009 influenza pandemic. Using publicly available data, we estimated the size of target population groups, and the number of days needed to vaccinate 70% of the target population. Sensitivity analyses considered higher vaccine coverages and scaled up vaccine delivery relative to the 2009 pandemic.

RESULTS

Essential workers, including staff in the healthcare, law enforcement, security, nursing homes, social welfare institutes, community services, energy, food and transportation sectors, and overseas workers/students (49.7 million) could be prioritized for vaccination to maintain essential services in the early phase of a vaccination program. Subsequently, older adults, individuals with underlying health conditions and pregnant women (563.6 million) could be targeted for vaccination to reduce the number of individuals with severe COVID-19 outcomes, including hospitalizations, critical care admissions, and deaths. In later stages, the vaccination program could be further extended to target adults without underlying health conditions and children (784.8 million), in order to reduce symptomatic infections and/or to stop virus transmission. Given 10 million doses administered per day, and a two-dose vaccination schedule, it would take 1 week to vaccinate essential workers but likely up to 7 months to vaccinate 70% of the overall population.

CONCLUSIONS

The proposed framework is general but could assist Chinese policy-makers in the design of a vaccination program. Additionally, this exercise could be generalized to inform other national and regional strategies for use of COVID-19 vaccines, especially in low- and middle-income countries.

Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19

OBJECTIVES

Reporting of COVID-19 cases, deaths and testing has often lacked context for appropriate assessment of disease burden within risk groups. The research considers how routine surveillance data might provide initial insights and identify risk factors, setting COVID-19 deaths early in the pandemic into context. This will facilitate the understanding of wider consequences of a pandemic from the earliest stage, reducing fear, aiding in accurately assessing disease burden and ensuring appropriate disease mitigation.

SETTING

UK, 2020.

PARTICIPANTS

The study is a secondary analysis of routine, public domain, surveillance data and information from Office for National Statistics (ONS), National Health Service (NHS) 111 and Public Health England (PHE) on deaths and disease.

PRIMARY AND SECONDARY OUTCOME MEASURES

Our principal focus is ONS data on deaths mentioning COVID-19 on the death certificate. We also consider information provided in NHS 111 and PHE data summaries.

RESULTS

Deaths with COVID-19 significantly contributed to, yet do not entirely explain, abnormally elevated all-cause mortality in the UK from weeks 12-18 of 2020. Early in the UK epidemic, COVID-19 was the greatest threat to those with underlying illness, rarely endangering people aged under 40 years. COVID-19-related death rates differed by region, possibly reflecting underlying population structure. Risk of COVID-19-related death was greater for healthcare and social care staff and black, Asian and minority ethnic individuals, having allowed for documented risk factors.

CONCLUSION

Early contextualisation of public health data is critical to recognising who gets sick, when and why. Understanding at-risk groups facilitates a targeted response considering indirect consequences of society's reaction to a pandemic alongside disease-related impacts. COVID-19-related deaths mainly mirror historical patterns, and excess non-COVID-19-related deaths partly reflect reduced access to and uptake of healthcare during lockdown. Future outbreak response will improve through better understanding of connectivity between disease monitoring systems to aid interpretation of disease risk patterns, facilitating nuanced mitigation measures.

Risk prediction of COVID-19 incidence and mortality in a large multi-national hemodialysis cohort: implications for management of the pandemic in outpatient hemodialysis settings

Background

Experiences from the first wave of the 2019 coronavirus disease (COVID-19) pandemic can aid in the development of future preventive strategies. To date, risk prediction models for COVID-19-related incidence and outcomes in hemodialysis (HD) patients are missing.

Methods

We developed risk prediction models for COVID-19 incidence and mortality among HD patients. We studied 38 256 HD patients from a multi-national dialysis cohort between 3 March and 3 July 2020. Risk prediction models were developed and validated, based on predictors readily available in outpatient HD units. We compared mortality among patients with and without COVID-19, matched for age, sex and diabetes.

Results

During the observational period, 1259 patients (3.3%) acquired COVID-19. Of these, 62% were hospitalized or died. Mortality was 22% among COVID-19 patients with odds ratios 219.8 [95% confidence interval (CI) 80.6–359] to 342.7 (95% CI 60.6–13 595.1), compared to matched patients without COVID-19. Since the first wave of the pandemic affected most European countries during the study, the risk prediction model for incidence of COVID-19 was developed and validated in European patients only [N = 22 826 area under the ROC curve(AUC)_Dev 0.64, AUC_Val 0.69]. The model for prediction of mortality was developed in all COVID-19 patients (AUC_Dev 0.71, AUC_Val 0.78). Angiotensin receptor blockers were independently associated with a lower incidence of COVID-19 in European patients.

Conclusions

We identified modifiable risk factors for COVID-19 incidence and outcome in HD patients. Our risk prediction tools can be readily applied in clinical practice. This can aid in the development of preventive strategies for future waves of COVID-19.

Predictors for the severe coronavirus disease 2019 (COVID-19) infection in patients with underlying liver disease: a retrospective analytical study in Iran

Risk factors for clinical outcomes of COVID-19 pneumonia have not yet been well established in patients with underlying liver diseases. Our study aimed to describe the clinical characteristics and outcomes of COVID-19 infection among patients with underlying liver diseases and determine the risk factors for severe COVID-19 among them. In a retrospective analytical study, 1002 patients with confirmed COVID-19 pneumonia were divided into two groups: patients with and without underlying liver diseases. The admission period was from 5 March to 14 May 2020. The prevalence of underlying conditions, Demographic data, clinical parameters, laboratory data, and participants' outcomes were evaluated. Logistic regression was used to estimate the predictive factors. Eighty-one (8%) of patients had underlying liver diseases. The frequencies of gastrointestinal symptoms such as diarrhea and vomiting were significantly higher among patients with liver diseases (48% vs. 25% and 46.1% vs. 30% respectively, both P < 0.05). Moreover, ALT and AST were significantly higher among patients with liver diseases (54.5 ± 45.6 vs. 37.1 ± 28.4, P = 0.013 and 41.4 ± 27.2 vs. 29.2 ± 24.3, P = 0.028, respectively). Additionally, the mortality rate was significantly high in patients with liver disease (12.4% vs. 7%, P = 0.018). We also observed that the parameters such as neutrophil to leukocyte ratio [Odds Ratio Adjusted (ORAdj) 1.81, 95% CI 1.21-3.11, P = 0.011] and blood group A (ORAdj 1.59, 95% CI 1.15-2.11, P = 0.001) were associated with progression of symptoms of COVID-19. The presence of underlying liver diseases should be considered one of the poor prognostic factors for worse outcomes in patients with COVID-19.

Obesity during the COVID-19 pandemic: both cause of high risk and potential effect of lockdown? A population-based electronic health record study

OBJECTIVES

Obesity is a modifiable risk factor for coronavirus disease 2019 (COVID-19)-related mortality. We estimated excess mortality in obesity, both 'direct', through infection, and 'indirect', through changes in health care, and also due to potential increasing obesity during lockdown.

STUDY DESIGN

The study design of this study is a retrospective cohort study and causal inference methods.

METHODS

In population-based electronic health records for 1,958,638 individuals in England, we estimated 1-year mortality risk ('direct' and 'indirect' effects) for obese individuals, incorporating (i) pre-COVID-19 risk by age, sex and comorbidities, (ii) population infection rate and (iii) relative impact on mortality (relative risk [RR]: 1.2, 1.5, 2.0 and 3.0). Using causal inference models, we estimated impact of change in body mass index (BMI) and physical activity during 3-month lockdown on 1-year incidence for high-risk conditions (cardiovascular diseases, diabetes, chronic obstructive pulmonary disease and chronic kidney disease), accounting for confounders.

RESULTS

For severely obese individuals (3.5% at baseline), at 10% population infection rate, we estimated direct impact of 240 and 479 excess deaths in England at RR 1.5 and 2.0, respectively, and indirect effect of 383-767 excess deaths, assuming 40% and 80% will be affected at RR = 1.2. Owing to BMI change during the lockdown, we estimated that 97,755 (5.4%: normal weight to overweight, 5.0%: overweight to obese and 1.3%: obese to severely obese) to 434,104 individuals (15%: normal weight to overweight, 15%: overweight to obese and 6%: obese to severely obese) would be at higher risk for COVID-19 over one year.

CONCLUSIONS

Prevention of obesity and promotion of physical activity are at least as important as physical isolation of severely obese individuals during the pandemic.

National Profiles of Coronavirus Disease 2019 Mortality Risks by Age Structure and Preexisting Health Conditions

BACKGROUND AND OBJECTIVES

Although individual age and preexisting health conditions are well-documented risk factors for coronavirus disease 2019 (COVID-19) mortality, it is unclear whether these 2 factors capture unique dimensions of risk for epidemic severity at the national level. In addition, no studies have examined whether national distributions of these factors are associated with epidemic experiences to date.

RESEARCH DESIGN AND METHODS

Drawing on surveys of older adults from 42 countries and estimated case fatality ratios by age and preexisting health conditions, we document and compare national profiles of COVID-19 mortality risks among older adults. We develop 2 measures of national risk profiles: one based on age structures and another based on distributions of preexisting health conditions. Our analysis compares these constructs and documents their associations with national COVID-19 mortality rates.

RESULTS

National profiles of COVID-19 mortality risk based on age structure and preexisting health conditions are moderately uncorrelated, capturing different aspects of risk. Both types of national risk profiles correlate meaningfully with countries' COVID-19 mortality experiences to date.

DISCUSSION AND IMPLICATIONS

Measures of population age structure are readily available for every country in the world, while cross-national measures of older adult population health are more limited. In the COVID-19 crisis, these factors give different pictures of the countries with high and low risks of COVID-19 mortality. Moreover, our results suggest that both types of national risk profiles based on population health reflect current COVID-19 mortality severity in several countries, highlighting the need for more cross-national comparative data on older adult population health.

The Burden of Malnutrition and Fatal COVID-19: A Global Burden of Disease Analysis

Background: Although reasonable to assume, it is not yet clear whether malnourished countries are at higher risk for severe or fatal coronavirus disease 2019 (COVID-19). This study aims to identify the countries where prevalent malnutrition may be a driving factor for fatal disease after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods: Using estimates from the Global Burden of Disease 2019, country-level burden of malnutrition was quantified using four indicators: death rates for child growth failure (underweight, stunting, and/or wasting) and years lived with disability (YLD) attributed to iron and vitamin A deficiencies and high body mass index (BMI). Global mortality descriptors of the ongoing COVID-19 pandemic were extracted from the European Centre for Disease Prevention and Control, and case fatality ratios (CFRs) were calculated introducing a lag time of 10 weeks after the first death of a confirmed case. Bivariate analyses for 172 countries were carried out for malnutrition indicators and fatal COVID-19. Correlations between burden indicators were characterized by Spearman's rank correlation coefficients (ρ) and visually by scatterplots. Restricted cubic splines and underlying negative binomial regressions adjusted for countries' age-structure, prevalent chronic comorbidities related to COVID-19, population density, and income group were used to explore non-linear relationships. Results: Stratified by the World Bank income group, a moderate positive association between YLD rates for iron deficiency and CFRs for COVID-19 was observed for low-income countries (ρ = 0.60, p = 0.027), whereas no clear indications for the association with child growth failure, vitamin A deficiency, or high BMI were found (ρ < 0.30). Countries ranking high on at least three malnutrition indicators and presenting also an elevated CFR for COVID-19 are sub-Saharan African countries, namely, Angola, Burkina Faso, Chad, Liberia, Mali, Niger, Sudan, and Tanzania, as well as Yemen and Guyana. Conclusions: Population-level malnutrition appears to be related to increased rates of fatal COVID-19 in areas with an elevated burden of undernutrition, such as countries in the Sahel strip. COVID-19 response plans in malnourished countries, vulnerable to fatal COVID-19, should incorporate food security, nutrition, and social protection as a priority component in order to reduce COVID-19 fatality.

Perceptions of Romanian Physicians on Lockdowns for COVID-19 Prevention

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) was declared a pandemic in March 2020, triggering important changes for the entire society and healthcare systems, as well as significant lockdown measures aimed to limit the disease spread. We herein intended to catch the dynamic of Romanian physicians' perceptions of COVID-19 impact. For this purpose, after a literature review, a 30-item questionnaire was designed. The questionnaire was twice distributed online, about 1 month apart, during which partial relaxation measures were decreed in Romania. The questionnaire was voluntarily filled in by Romanian physicians who were willing to participate in the study. A total of 214 physicians answered the questionnaire upon its first release, and 199 respondents were registered upon its second release, most of whom (94.9%) were involved in clinical work, with one-third working in units dedicated to COVID-19 patients. In parallel with the relaxation of lockdown measures, along with increased confidence in the efficiency of protective measures (46.7% vs. 31.3%), separation from household members decreased from 36.9% to 22.1%. Nevertheless, the feeling of rejection felt by doctors remained similar (22.4% vs. 24.6%). Furthermore, answers regarding the clinical picture, diagnostic approach, and treatment options are discussed. Most of therapeutic options considered for SARS-CoV-2 treatment (e.g., lopinavir/ritonavir, oseltamivir, hydroxychloroquine, azithromycin, tocilizumab, and convalescent plasma) failed to confirm significant efficiency. On the contrary, vaccines for widescale use are already available despite the initial skepticism. In the beginning of the pandemic, 25.2% (18.2% vs. 32.2%) considered that there will not be an effective COVID-19 vaccine, while 41.6% (43.0% vs. 40.2%) thought that a vaccine would be available after at least 12 months. In conclusion, initially, following only a 1 month period, Romanian physicians' intention to consider treatments such as hydroxychloroquine or lopinavir/ritonavir for COVID-19 decreased significantly. Moreover, confidence in the efficiency of available protective measures increased, and the rates of separation from household members decreased.

Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile

The current coronavirus disease 2019 (COVID-19) pandemic has impacted dense urban populations particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality patterns, and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. We find that among all age groups, there is a strong association between socioeconomic status and both mortality -measured either by direct COVID-19 attributed deaths or excess deaths- and public health capacity. Specifically, we show that behavioral factors like human mobility, as well as health system factors such as testing volumes, testing delays, and test positivity rates are associated with disease outcomes. These robust patterns suggest multiple possibly interacting pathways that can explain the observed disease burden and mortality differentials: (i) in lower socioeconomic status municipalities, human mobility was not reduced as much as in more affluent municipalities; (ii) testing volumes in these locations were insufficient early in the pandemic and public health interventions were applied too late to be effective; (iii) test positivity and testing delays were much higher in less affluent municipalities, indicating an impaired capacity of the health-care system to contain the spread of the epidemic; and (iv) infection fatality rates appear much higher in the lower end of the socioeconomic spectrum. Together, these findings highlight the exacerbated consequences of health-care inequalities in a large city of the developing world, and provide practical methodological approaches useful for characterizing COVID-19 burden and mortality in other segregated urban centers.

Risk of adverse outcome of COVID-19 among patients in secure psychiatric services: observational cohort study

BACKGROUND

Secure forensic mental health services treat patients with high rates of treatment-resistant psychoses. High rates of obesity and medical comorbidities are common. Population-based studies have identified high-risk groups in the event of SARS-CoV-2 infection, including those with problems such as obesity, lung disease and immune-compromising conditions. Structured assessment tools exist to ascertain the risk of adverse outcome in the event of SARS-CoV-2 infection.

AIMS

To assess risk of adverse outcome in the event of SARS-CoV-2 infection in a complete population of forensic psychiatry patients using structured assessment tools.

METHOD

All patients of a national forensic mental health service (n = 141) were rated for risk of adverse outcome in the event of SARS-CoV-2 infection, using two structured tools, the COVID-Age tool and the COVID-Risk tool.

RESULTS

We found high rates of relevant physical comorbidities. Mean chronological age was 45.5 years (s.d. = 11.4, median 44.1), mean score on the COVID-Age tool was 59.1 years (s.d. = 19.4, median 58.0), mean difference was 13.6 years (s.d. = 15.6), paired t = 10.9, d.f. = 140, P < 0.001. Three patients (2.1%) were chronologically over 70 years of age, compared with 43 (30.5%) with a COVID-Age over 70 (χ2 = 6.99, d.f. = 1, P = 0.008, Fisher's exact test P = 0.027).

CONCLUSIONS

Patients in secure forensic psychiatric services represent a high-risk group for adverse outcomes in the event of SARS-COV-2 infection. Population-based guidance on self-isolation and other precautions based on chronological age may not be sufficient. There is an urgent need for better physical health research and treatment in this group.

Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity

Patients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyzed the transcriptomes of 605,904 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observed a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD epithelial cells expressed higher levels of genes linked directly to the efficiency of viral replication and innate immune response. Additionally, we identified basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection.

Adolescents' and parents' anxiety during COVID-19: is there a role of cyberchondriasis and emotion regulation through the internet?

COVID-19 pandemic period presents a unique context for the investigation of anxiety symptoms among adolescents and their parents. This study investigated adolescents' and their parents' anxiety symptoms, the effects of parental cyberchondriasis and adolescents' emotion regulation on anxiety symptoms. The sample consisted of 155 adolescents (x̅ = 14.63, SD = 2.04) and one of their parents (N = 155). The results showed that after controlling for adolescents' gender and emotion regulation, parental cyberchondriasis and anxiety accounted for an important variance in adolescents' anxiety. Especially higher parental anxiety and compulsion were associated with higher anxiety, whereas higher distress was associated with lower anxiety. Besides, two dimensions of cyberchondriasis, compulsion, and distress, together with adolescent anxiety, predicted parental anxiety during COVID-19. While compulsion was negatively associated with anxiety, distress, and adolescent anxiety were positively associated with it. The dimensions of cyberchondriasis affected anxiety differently among adolescents and their parents. The results were discussed in terms of the implications for intervention from the ecological viewpoint.

Coronavirus: the science behind infection control and human exposure

Coronavirus SARS-2 (SARS-CoV-2) is the virus responsible for the disease known as COVID-19. The global community is struggling with the health and economic repercussions of this novel disease, and this article is part of a series that seeks to explore and explain the science behind the foci of infection control measures being considered at both the individual and population health levels. Understanding the factors influencing the ability of this virus to select an appropriate host, breach initial defences and successfully assume a new reservoir from which to disseminate and disperse infective viral particles is considered here. Brief reference is made to infection control measures such as effective hand hygiene, glove usage, environmental decontamination and social distancing guidance against the context of the specific evidence around COVID-19 transmission. Predictors of poorer outcome are introduced in the light of these being target themes for therapeutic development.

Place and causes of acute cardiovascular mortality during the COVID-19 pandemic

OBJECTIVE

To describe the place and causes of acute cardiovascular death during the COVID-19 pandemic.

METHODS

Retrospective cohort of adult (age ≥18 years) acute cardiovascular deaths (n=5 87 225) in England and Wales, from 1 January 2014 to 30 June 2020. The exposure was the COVID-19 pandemic (from onset of the first COVID-19 death in England, 2 March 2020). The main outcome was acute cardiovascular events directly contributing to death.

RESULTS

After 2 March 2020, there were 28 969 acute cardiovascular deaths of which 5.1% related to COVID-19, and an excess acute cardiovascular mortality of 2085 (+8%). Deaths in the community accounted for nearly half of all deaths during this period. Death at home had the greatest excess acute cardiovascular deaths (2279, +35%), followed by deaths at care homes and hospices (1095, +32%) and in hospital (50, +0%). The most frequent cause of acute cardiovascular death during this period was stroke (10 318, 35.6%), followed by acute coronary syndrome (ACS) (7 098, 24.5%), heart failure (6 770, 23.4%), pulmonary embolism (2 689, 9.3%) and cardiac arrest (1 328, 4.6%). The greatest cause of excess cardiovascular death in care homes and hospices was stroke (715, +39%), compared with ACS (768, +41%) at home and cardiogenic shock (55, +15%) in hospital.

CONCLUSIONS AND RELEVANCE

The COVID-19 pandemic has resulted in an inflation in acute cardiovascular deaths, nearly half of which occurred in the community and most did not relate to COVID-19 infection suggesting there were delays to seeking help or likely the result of undiagnosed COVID-19.

Weight Status and Body Composition Dynamics in Children and Adolescents During the COVID-19 Pandemic

Introduction: The preventive measures taken in attempt to prevent COVID-19 spread lead to closure of schools and leisure time activities. The impact of the pandemic on pediatric weight status is unclear, reports from around the world predict grave consequences with increasing obesity. We aimed to examine the change in body composition parameters of children and adolescents during the pandemic. Materials and Methods: An observational study of 220 pediatric subjects (109 boys; mean current age 11.8 ± 3.3 years; 37 with underweight, 123 with normal weight, and 60 with overweight/obesity) who underwent height and body composition measurements by bioelectrical impedance analysis, Tanita MC-780MA, GMON Professional Software before and during the pandemic. Height, body mass index (BMI) and muscle-to-fat ratio (MFR) z-scores were calculated. Data collected from the participants' medical files included home address for socioeconomic position calculation, pubertal stage, and self-reported sleep duration and physical activity performance. Results: The vast majority of the cohort (81.8%) had stable or improved MFR z-scores during the pandemic. MFR z-scores significantly increased in subjects with underweight (p = 0.05) and normal weight (p = 0.008), but not in subjects with overweight/obesity (p = 0.169). There were significant associations in BMI z-scores (r = 0.961, p < 0.001) and MFR z-scores (r = 0.854, p < 0.001) before and during the pandemic. A multivariate linear regression model identified socioeconomic position, pre-pandemic BMI z-scores, pre-pandemic MFR z-scores, and physical activity levels during the pandemic as predictors for delta MFR z-scores (F = 12.267, p < 0.001). Age, sex, pre-pandemic physical activity, and the time that had elapsed between initiation of the first nationwide lockdown and the BIA assessment during the pandemic did not emerge as predictors for delta MFR z-score. Conclusions: Our encouraging findings demonstrate improvement in body composition parameters of subjects with underweight and normal weight and stability in subjects with overweight/obesity. Engagement in physical activity during the pandemic predicted improvement, while lower socioeconomic position predicted deterioration.

Trends in suicide in Japan by gender during the COVID-19 pandemic, up to September 2020

Suicide is an extreme consequence of the psychological burden associated with the coronavirus disease 2019 (COVID-19) counter-measures. A quasi-Poisson regression was applied to monthly suicide mortality data obtained from the National Police Agency to estimate the gender-specific excess/exiguous suicide deaths during the COVID-19 pandemic in Japan up to September 2020. We found excess suicide deaths among women in July, August and September, but not among men. Our results indicate the importance of COVID-19 related suicide prevention, especially for women. Timely access to mental health care and financial and social support is urgently needed, as is optimal treatment for mental illness.

Impact of Relaxing Covid-19 Social Distancing Measures on Rural North Wales: A Simulation Analysis

Background: Social distancing policies aimed to limit Covid-19 across the UK were gradually relaxed between May and August 2020, as peak incidences passed. Population density is an important driver of national incidence rates; however peak incidences in rural regions may lag national figures by several weeks. We aimed to forecast the timing of peak Covid-19 mortality rate in rural North Wales.

Methods: Covid-19 related mortality data up to 7/5/2020 were obtained from Public Health Wales and the UK Government. Sigmoidal growth functions were fitted by non-linear least squares and model averaging used to extrapolate mortality to 24/8/2020. The dates of peak mortality incidences for North Wales, Wales and the UK; and the percentage of predicted mortality at 24/8/2020 were calculated.

Results: The peak daily death rates in Wales and the UK were estimated to have occurred on the 14/04/2020 and 15/04/2020, respectively. For North Wales, this occurred on the 07/05/2020, corresponding to the date of analysis. The number of deaths reported in North Wales on 07/05/2020 represents 33% of the number predicted to occur by 24/08/2020, compared with 74 and 62% for Wales and the UK, respectively.

Conclusion: Policies governing the movement of people in the gradual release from lockdown are likely to impact significantly on areas–principally rural in nature–where cases of Covid-19, deaths and immunity are likely to be much lower than in populated areas. This is particularly difficult to manage across jurisdictions, such as between England and Wales, and in popular holiday destinations.

Development and external validation of a COVID-19 mortality risk prediction algorithm: a multicentre retrospective cohort study

OBJECTIVE

This study aimed to develop and externally validate a COVID-19 mortality risk prediction algorithm.

DESIGN

Retrospective cohort study.

SETTING

Five designated tertiary hospitals for COVID-19 in Hubei province, China.

PARTICIPANTS

We routinely collected medical data of 1364 confirmed adult patients with COVID-19 between 8 January and 19 March 2020. Among them, 1088 patients from two designated hospitals in Wuhan were used to develop the prognostic model, and 276 patients from three hospitals outside Wuhan were used for external validation. All patients were followed up for a maximal of 60 days after the diagnosis of COVID-19.

METHODS

The model discrimination was assessed by the area under the receiver operating characteristic curve (AUC) and Somers' D test, and calibration was examined by the calibration plot. Decision curve analysis was conducted.

MAIN OUTCOME MEASURES

The primary outcome was all-cause mortality within 60 days after the diagnosis of COVID-19.

RESULTS

The full model included seven predictors of age, respiratory failure, white cell count, lymphocytes, platelets, D-dimer and lactate dehydrogenase. The simple model contained five indicators of age, respiratory failure, coronary heart disease, renal failure and heart failure. After cross-validation, the AUC statistics based on derivation cohort were 0.96 (95% CI, 0.96 to 0.97) for the full model and 0.92 (95% CI, 0.89 to 0.95) for the simple model. The AUC statistics based on the external validation cohort were 0.97 (95% CI, 0.96 to 0.98) for the full model and 0.88 (95% CI, 0.80 to 0.96) for the simple model. Good calibration accuracy of these two models was found in the derivation and validation cohort.

CONCLUSION

The prediction models showed good model performance in identifying patients with COVID-19 with a high risk of death in 60 days. It may be useful for acute risk classification.

WEB CALCULATOR

We provided a freely accessible web calculator (https://www.whuyijia.com/).

New statistical RI index allow to better track the dynamics of COVID-19 outbreak in Italy

COVID-19 pandemic in Italy displayed a spatial distribution that made the tracking of its time course quite difficult. The most relevant anomaly was the marked spatial heterogeneity of COVID-19 diffusion. Lombardia region accounted for around 60% of fatal cases (while hosting 15% of Italian population). Moreover, 86% of fatalities concentrated in four Northern Italy regions. The 'explosive' outbreak of COVID-19 in Lombardia at the very beginning of pandemic fatally biased the R-like statistics routinely used to control the disease dynamics. To (at least partially) overcome this bias, we propose a new index RI = dH/dI (daily derivative ratio of H and I, given H = Healed and I = Infected), corresponding to the ratio between healed and infected patients relative daily changes. The proposed index is less flawed than R by the uncertainty related to the estimated number of infected persons and allows to follow (and possibly forecast) epidemic dynamics in a largely model-independent way. To analyze the dynamics of the epidemic, starting from the beginning of the virus spreading-when data are insufficient to make an estimate by adopting SIR model-a "sigmoidal family with delay" logistic model was introduced. That approach allowed in estimating the epidemic peak using the few data gathered even before mid-March. Based on this analysis, the peak was correctly predicted to occur by end of April. Analytical methodology of the dynamics of the epidemic we are proposing herein aims to forecast the time and intensity of the epidemic peak (forward prediction), while allowing identifying the (more likely) beginning of the epidemic (backward prediction). In addition, we established a relationship between hospitalization in intensive care units (ICU) versus deaths daily rates by avoiding the necessity to rely on precise estimates of the infected fraction of the population The joint evolution of the above parameters over time allows for a trustworthy and unbiased estimation of the dynamics of the epidemic, allowing us to clearly detect the qualitatively different character of the 'so-called' second wave with respect to the previous epidemic peak.

COVID-19 mortality effects of underlying health conditions in India: a modelling study

OBJECTIVE

To model how known COVID-19 comorbidities affect mortality rates and the age distribution of mortality in a large lower-middle-income country (India), and to identify which health conditions drive differences with high-income countries.

DESIGN

Modelling study.

SETTING

England and India.

PARTICIPANTS

Individual data were obtained from the fourth round of the District Level Household Survey and Annual Health Survey in India, and aggregate data were obtained from the Health Survey for England and the Global Burden of Disease, Risk Factors and Injuries Studies.

MAIN OUTCOME MEASURES

The primary outcome was the modelled age-specific mortality in each country due to each COVID-19 mortality risk factor (diabetes, hypertension, obesity and respiratory illness, among others). The change in overall mortality and in the share of deaths under age 60 from the combination of risk factors was estimated in each country.

RESULTS

Relative to England, Indians have higher rates of diabetes (10.6% vs 8.5%) and chronic respiratory disease (4.8% vs 2.5%), and lower rates of obesity (4.4% vs 27.9%), chronic heart disease (4.4% vs 5.9%) and cancer (0.3% vs 2.8%). Population COVID-19 mortality in India, relative to England, is most increased by uncontrolled diabetes (+5.67%) and chronic respiratory disease (+1.88%), and most reduced by obesity (-5.47%), cancer (-3.65%) and chronic heart disease (-1.20%). Comorbidities were associated with a 6.26% lower risk of mortality in India compared with England. Demographics and population health explain a third of the difference in share of deaths under age 60 between the two countries.

CONCLUSIONS

Known COVID-19 health risk factors are not expected to have a large effect on mortality or its age distribution in India relative to England. The high share of COVID-19 deaths from people under age 60 in low- and middle-income countries (LMICs) remains unexplained. Understanding the mortality risk associated with health conditions prevalent in LMICs, such as malnutrition and HIV/AIDS, is essential for understanding differential mortality.

Glucocorticoids with low-dose anti-IL1 anakinra rescue in severe non-ICU COVID-19 infection: A cohort study

BACKGROUND

The optimal treatment for patients with severe coronavirus-19 disease (COVID-19) and hyper-inflammation remains debated.

MATERIAL AND METHODS

A cohort study was designed to evaluate whether a therapeutic algorithm using steroids with or without interleukin-1 antagonist (anakinra) could prevent death/invasive ventilation. Patients with a ≥5-day evolution since symptoms onset, with hyper-inflammation (CRP≥50mg/L), requiring 3-5 L/min oxygen, received methylprednisolone alone. Patients needing ≥6 L/min received methylprednisolone + subcutaneous anakinra daily either frontline or in case clinical deterioration upon corticosteroids alone. Death rate and death or intensive care unit (ICU) invasive ventilation rate at Day 15, with Odds Ratio (OR) and 95% CIs, were determined according to logistic regression and propensity scores. A Bayesian analysis estimated the treatment effects.

RESULTS

Of 108 consecutive patients, 70 patients received glucocorticoids alone. The control group comprised 63 patients receiving standard of care. In the corticosteroid±stanakinra group (n = 108), death rate was 20.4%, versus 30.2% in the controls, indicating a 30% relative decrease in death risk and a number of 10 patients to treat to avoid a death (p = 0.15). Using propensity scores a per-protocol analysis showed an OR for COVID-19-related death of 0.9 (95%CI [0.80-1.01], p = 0.067). On Bayesian analysis, the posterior probability of any mortality benefit with corticosteroids+/-anakinra was 87.5%, with a 7.8% probability of treatment-related harm. Pre-existing diabetes exacerbation occurred in 29 of 108 patients (26.9%).

CONCLUSION

In COVID-19 non-ICU inpatients at the cytokine release phase, corticosteroids with or without anakinra were associated with a 30% decrease of death risk on Day 15.

Factors Associated with Psychological Distress and Brief Resilient Coping Level During the COVID-19 Pandemic Among Health-Care Professionals in Dessie, Ethiopia

Background

The outbreak of Coronavirus Disease 2019 (COVID-19) has caused serious threats to people’s health and lives in the world. The health-care professionals are bravely fighting on the front lines of the pandemic everywhere in the world. Our study is the first to study psychological distress and coping status among health-care professionals of Dessie town, Ethiopia during the unbridled time of the COVID-19 outbreak.

Methods

A cross-sectional internet-based study was conducted between June 20 and July 13, 2020. The questionnaires included the demographic information, COVID-19 related questions, Kasseler-10 to assess psychological distress level and Brief Resilient Coping Scale, and Oslo-3 social support scale questionnaire were employed.

Results

A total of 423 participants were involved in the study with a response rate of 100%. The mean age of respondents was 34.5 years (SD = ±8.45 years). The prevalence of psychological distress among participants was 42%. Of these 18%, 11%, and 13% had mild, moderate, and severe psychological distress levels. Being married, being nurses and pharmacies, current substance users, working in emergency and outpatient departments, history of chronic medical illness, brief resilient coping level, and social support level were particularly associated with high psychological distress.

Conclusion

Health-care professionals are experiencing a substantial level of psychological distress. In addition to other modifying factors coping level and social support was a significant predictor of psychological distress among health-care professionals. These findings should inform the implementation of interventions that increase coping resilience and social support to mitigate the impact of psychological distress among health-care professionals.

Outcome of Hospitalization for COVID-19 in Patients with Interstitial Lung Disease. An International Multicenter Study

Rationale: The impact of coronavirus disease (COVID-19) on patients with interstitial lung disease (ILD) has not been established.Objectives: To assess outcomes in patients with ILD hospitalized for COVID-19 versus those without ILD in a contemporaneous age-, sex-, and comorbidity-matched population.Methods: An international multicenter audit of patients with a prior diagnosis of ILD admitted to the hospital with COVID-19 between March 1 and May 1, 2020, was undertaken and compared with patients without ILD, obtained from the ISARIC4C (International Severe Acute Respiratory and Emerging Infection Consortium Coronavirus Clinical Characterisation Consortium) cohort, admitted with COVID-19 over the same period. The primary outcome was survival. Secondary analysis distinguished idiopathic pulmonary fibrosis from non-idiopathic pulmonary fibrosis ILD and used lung function to determine the greatest risks of death.Measurements and Main Results: Data from 349 patients with ILD across Europe were included, of whom 161 were admitted to the hospital with laboratory or clinical evidence of COVID-19 and eligible for propensity score matching. Overall mortality was 49% (79/161) in patients with ILD with COVID-19. After matching, patients with ILD with COVID-19 had significantly poorer survival (hazard ratio [HR], 1.60; confidence interval, 1.17-2.18; P = 0.003) than age-, sex-, and comorbidity-matched controls without ILD. Patients with an FVC of <80% had an increased risk of death versus patients with FVC ≥80% (HR, 1.72; 1.05-2.83). Furthermore, obese patients with ILD had an elevated risk of death (HR, 2.27; 1.39-3.71).Conclusions: Patients with ILD are at increased risk of death from COVID-19, particularly those with poor lung function and obesity. Stringent precautions should be taken to avoid COVID-19 in patients with ILD.

Individual and community-level risk for COVID-19 mortality in the United States

Reducing COVID-19 burden for populations will require equitable and effective risk-based allocations of scarce preventive resources, including vaccinations¹. To aid in this effort, we developed a general population risk calculator for COVID-19 mortality based on various sociodemographic factors and pre-existing conditions for the US population, combining information from the UK-based OpenSAFELY study with mortality rates by age and ethnicity across US states. We tailored the tool to produce absolute risk estimates in future time frames by incorporating information on pandemic dynamics at the community level. We applied the model to data on risk factor distribution from a variety of sources to project risk for the general adult population across 477 US cities and for the Medicare population aged 65 years and older across 3,113 US counties, respectively. Validation analyses using 54,444 deaths from 7 June to 1 October 2020 show that the model is well calibrated for the US population. Projections show that the model can identify relatively small fractions of the population (for example 4.3%) that might experience a disproportionately large number of deaths (for example 48.7%), but there is wide variation in risk across communities. We provide a web-based risk calculator and interactive maps for viewing community-level risks.