Coronavirus Mortality Research Articles

Risk factors for death in hospitalized COVID-19 patients in Africa: A systematic review and meta-analysis.

The coronavirus disease 2019 has quickly spread worldwide since it first appeared in Wuhan, China, in late 2019. The most affected country in Africa was South Africa. This study aimed to identify the risk factors for death in hospitalized COVID-19 patients in Africa. We conducted a systematic review following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We searched articles from the following database: PubMed, Embase, Cochrane Library, Medline, and COVID-19 Research Database. We used Google Scholar for gray literature. The language used in this article was English. The last search was conducted on January 15, 2023. Pooled HRs, or ORs, and 95% confidence intervals, were calculated separately to identify the risk factors for death in hospitalized COVID-19 patients. Heterogeneity was assessed by Cochran's Q statistic and the I2 test. The Egger test was used to assess publication bias. Subgroup analysis was performed to determine the source of heterogeneity. Data analysis was performed using Stata version 17. A P value < .05 was considered significant. A total of 16,600 articles were obtained from the database search; finally, 16 articles met the inclusion criteria and were eligible for data extraction. The analysis revealed that the pooled prevalence of mortality in hospitalized COVID-19 patients was 13.9%. Advanced age was a significant risk factor for death in hospitalized COVID-19 patients, with the pooled coronavirus mortality HR and OR being 3.73 (95% CI: 2.27-5.19) and 1.04 (95% CI: 1.02-1.06), respectively. In addition, male gender (pOR 1.23; 95% CI: 1.07-1.40), patients with diabetes mellitus (DM) (pOR 1.26; 95% CI: 1.01-1.51), hypertension (HTN) (pOR 1.56; 95% CI: 1.27-1.85), chronic kidney disease (CKD) (pHR 5.43; 95% CI: 0.18-10.67), severe or critical conditions (pOR 9.04; 95% CI: 3.14-14.94) had a significantly increased risk of coronavirus-related mortality. The main limitations of the present study stem from the predominant use of published studies, which could introduce publication bias. According to this study, advanced age, male gender, hypertension, diabetes mellitus, chronic kidney disease, and severe or critical condition were clinical risk factors associated with death outcomes in hospitalized COVID-19 patients in Africa.

Do sporting events amplify airborne virus transmission? Causal evidence from US professional team sports

We analyze the impact of professional sporting events on local seasonal influenza mortality to develop evidence on the role played by spectator attendance at sporting events in airborne virus transmission. Results from a difference-in-differences model applied to data from a sample of US cities that gained new professional sports teams over the period 1962–2016 show that the presence of games in these cities increased local influenza mortality by between 4% and 24%, depending on the sport, relative to cities with no professional sports teams and relative to mortality in those cities before a new team arrived. Influenza mortality fell in cities with teams in some years when work stoppages occurred in sports leagues. Health policy decisions, and decisions about the subsidization of professional sports, should take into account the role played by sporting events in increasing airborne virus transmission and local influenza and coronavirus mortality.

Diabetes Risk Factor and Its Relationship to Increasing Coronavirus (COVID-19) Mortality Rate in United States in 2019-2022: An Epidemiological Study

As an effort to understand the effect of diabetes on the increasing rate of COVID-19 infection, we embarked upon a detailed statistical analysis of various datasets that include COVID-19 infection and mortality rate, diabetes and diseases that may contribute to the severity and risk factor of diabetes in individuals and this impact on COVID-19 and the mortality rate. These diseases include respiratory diseases, cardiovascular diseases, and obesity. Equally significant is the statistical analysis on ethnicity, age, and sex on COVID-19 infection as well as mortality rate. Their possible contributions to increasing the severity and risk factor of diabetes as a risk to mortality to individuals who have COVID-19. Objectives: The ultimate objectives of this investigation are as follow: 1) Is there a risk factor of diabetes on COVID-19 infection and increasing mortality rate? 2) To what extent do other disease conditions that include, obesity, heart failure, and respiratory diseases influence the severity and risk factor of diabetes on increasing COVID-19 infection and mortality rate? 3) To what extent does age, race, and gender increase the mortality of COVID-19 and increase the severity and risk factor of diabetes on COVID-19 mortality rate? 4) How and why COVID-19 virus increases the risk of diabetes in children? 5) Diabetes and COVID-19: Who is most at Risk? Lastly, understanding the misconception of COVID-19 and diabetes.

Comparison of the Autoregressive Vector VAR with the Dynamic Error Correction Vector DVECM for Modeling COVID-19 Deaths

In this article, the Vector Auto-Regressive model and the Dynamic Error Correction Vector Model will be used in modeling data representing the number of deaths due to infection with the COVD-19 virus as a dependent variable and the variable platelet rate in the blood as an independent variable and finding the model equations that represent the relationship between the two variables using the two models and then estimating the equations that were obtained by estimating the two models using the least squares method, then choosing the best estimated equation from each model, and then, using the standard error of the regression and the coefficient of determination, selecting the best equations from the two models. The Dynamic Error Correction Vector Model is superior to the Vector Auto-Regressive model in assessing the link between corona virus mortality and the proportion of platelets in the blood, according to the analysis carried out using the E-Views application, and that there is a direct relationship through the equation for the Dynamic Error Correction Vector Model between the deaths of the corona virus and the proportion of platelets in the blood in the long term, which is logical as a result of the increase in the impact of the deaths of the Corona virus, the increase in the platelet rate, and thus the increase in the deaths of the corona virus.

Predictors of intensive care unit admission and mortality in SARS-CoV-2 infection: A cross sectional study at a tertiary care hospital

BackgroundThe transmissibility and associated morbidity and mortality of severe acute respiratory syndrome-related coronavirus (SARS-Cov-2), have overwhelmed worldwide healthcare systems, resulting in an urgent need to understand this virus and its associated effects. The aim of our study was to identify patient symptoms, clinical characteristics, laboratory, and radiology findings that are associated with serious morbidity and mortality in COVID-19 patients. MethodsA cross sectional study was conducted in Jaber Al Ahmad Hospital, the designated COVID-19 center in Kuwait between August 1st, 2020 and January 31st, 2021. The main outcomes measured in this study were to identify variables associated with intensive care unit (ICU) admission, as proxy for serious morbidity, and in hospital mortality. ResultsTwo hundred and seventy-six patients were included in the study. Thirty-six (13%) patients were admitted to intensive care unit (ICU) and 33 (12%) patients expired. On multivariate analysis we found having elevated fibrinogen [OR 1.39, 95% CI 1.08–1.64, P = 0.04], low estimated glomerular filtration rate (eGFR) [OR 0.89, 95% CI 0.81–0.95, P = 0.02], and having bilateral patchy lung shadowing [OR 6.68, 95% CI 1.85–15.28, P < 0.01] to be significantly associated with increase odds of ICU admission. Elevated CRP [OR 1.25, 95% CI 1.10–1.98, P < 0.01], low eGFR [OR 0.95, 95% CI 0.90–0.99, P = 0.05] and having ischemic heart disease [OR 7.03, 95% CI 1.60–46.42, P = 0.04] were independently associated with increased odds of mortality. ConclusionCertain inflammatory and coagulopathy markers, and having certain lung radiological features, in addition to having medical comorbidities, specifically, ischemic heart disease and renal impairment are key predictors for serious morbidity and mortality in patients infected with COVID-19. These should be incorporated into medical institutes risk assessment tools used by physicians and policy makers to instigate, prioritize, and reprioritize care in patients with COVID-19 and instigate preventative strategy to reduce the impact of future outbreak.

AGE-RELATED CHARACTERISTICS OF COVID-19 COURSES IN INPATIENS OF EMDICAL SETTINGS IN POLTAVA REGION

The investigation of factors that may affect the severity of coronavirus infection and mortality has been one of the main areas of medical research. At the present stage, among the possible risk factors of severe COVID-19 course there is the influence of age as a predictor of disease progression in inpatient. Objective: to determine the clinical and laboratory characteristics of the course of coronavirus disease COVID-19 depending on the age of hospitalized patients in Poltava region. Materials and methods: a retrospective cohort follow-up study was conducted involving 150 patients with a laboratory-confirmed diagnosis of "Acute respiratory disease COVID-19" at the Poltava Regional Clinical Infectious Diseases Hospital. Patients were divided into 2 age groups: 60 to 95 years and 18 to 59 years Statistical processing was carried out using SPSS Statistics 25.0 software. Results and conclusions: the study has found that the clinical and laboratory characteristics of the course of coronavirus disease COVID-19 are typical except for some features: hospitalized patients over 60 years were significantly more likely to have severe (p = 0.037) and critical (p = 0.063) course of the disease, require oxygen support (p = 0.001), in particular using low oxygen flows (p = 0.027). Leukocytosis was diagnosed 3.4 times more often in patients older than 60 years (p = 0.032), while leukopenia (p = 0.022) and thrombocytopenia were 2.2 times more often in people younger than 60 years. 0.0041). Severe disease was significantly more common in hospitalized women under 60 years of age than in men of the same age (p = 0.046).

Targeting of neutrophil activation in the early phase of the disease for prevention of Coronavirus disease-19 severity.

The prevention of the disease severity seems critical for reducing the mortality of Coronavirus (CoV) disease‐19. The neutrophils play a key role in the induction of severity. It is proposed here that inhibition of neutrophil activation and/or cascade reactions of complement, leading to this cell activation at the early phase of the disease, is a potential tool to inhibit aggravation of the disease. The need for appropriate timing in intervention is emphasized as follows. (1) Intervention at the very early stage of severe acute respiratory syndrome‐CoV‐2 infection may harm the defensive host response to the infection because of the critical function of neutrophils in this response, and (2) intervention at too late a stage will not stop the infiltration of fully activated neutrophils that produce large amounts of toxic substances.

The Role of Pre-Pandemic Investments in the Health Sector, Additional Fiscal Measures and Anti-Epidemic Policies in the Suppression of COVID-19: The Case of 15 Developed Countries

The paper seeks to identify the causes of the significant differences in the efficiency of the response to the COVID-19 pandemic between 15 developed countries. Geographic location, pre-pandemic investment in healthcare system capacity for preventing and managing the epidemic suppression process, and additional fiscal spending (which, in addition to public health investment, includes support measures for the economy) did not significantly affect the coronavirus mortality rate. In order to obtain a more accurate answer regarding the link between additional fiscal spending and the coronavirus mortality rate, we have specifically analyzed the role of the vaccination rate in the entire population because vaccine production is significantly funded through additional fiscal spending, while vaccine distribution is entirely funded through additional fiscal spending. We conclude that the overall vaccination rate has a significant impact on the COVID-19 mortality rate, i.e. that there is a negative correlation between the two. Moreover, countries that responded efficiently to the pandemic timely implemented anti-epidemic measures following the recommendations of the World Health Organization; they were characterized by a high level of public confidence in government measures and had clear and transparent communication with their citizens. With regard to economic activity, we also definitely conclude that countries with a below average mortality rate, which timely implemented strict anti-epidemic measures following WHO recommendations and had clear and transparent communication with their citizens, experienced without exception a milder decline in GDP in 2020 than average, which suggests that the best way to preserve economic activity is to preserve human lives. Regarding the relationship between additional fiscal spending and unemployment trends, we conclude that most countries with a below average mortality rate had additional fiscal spending below average and a minority of countries above average, but also that all countries, with the exception of Australia, had a below average rise in the unemployment rate.

Association between coronavirus disease morbidity and mortality rates and BCG vaccination policies in OECD countries. Authors' reply.

We appreciate the reviewer's comment to our article on the correlation between the national BCG vaccination policy and coronavirus disease 2019 among Organisation for Economic Co-operation and Development countries as of April 20, 2020. In this letter, we further updated the data up to November 1, 2020, and found that the updated results also arrive at the similar conclusion as the accepted article.

Psychosocial Challenges of Cancer Patients During the Coronavirus 2019 Epidemic

Since December 2019, the coronavirus has affected all aspects of our lives worldwide. This deadly crisis, for which no health care system was fully prepared, has created enormous pressures on health care delivery and has directly and indirectly affected the treatment of many common diseases. Cancer patients are a vulnerable group in the current epidemic due to their immunodeficiency status due to cancer and various anti-cancer therapies [1]. Research shows that cancer patients are at greater risk for more severe infections and subsequent complications, especially if surgery or chemotherapy is given in the month before the coronavirus infection [2]. These conditions have led to a significant increase in coronavirus mortality in cancer patients [3].

Venetoclax with Azacitidine or Low Dose Cytarabine As an Alternative to Intensive Chemotherapy in Fit Adults during the COVID19 Pandemic: Real World Data from the UK National Health Service

Venetoclax with Azacitidine or Low Dose Cytarabine As an Alternative to Intensive Chemotherapy in Fit Adults during the COVID19 Pandemic: Real World Data from the UK National Health Service

COVID-19 and all-cause-mortality; differential trends between countries and selected states of India

By 22nd January 2021, the Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus had infected over 98 million and 10.6 million individuals globally and in India, with 1.7 million and 153, 067 deaths, respectively. Case Fatality rates (CFR) due to coronavirus disease 2019 (COVID 19) have varied significantly between countries. In order to understand the true impact of the pandemic, we should report coronavirus (COVID-19) mortality in the context of all-cause and non-COVID-19 mortality, and compare with previous years. The consequences of the pandemic have been, and will be, different in different settings within and across countries. To compare the all-cause mortality in the year 2020 with previous years in three selected states of India correlate it to the burden of COVID19 and compare all-cause mortality between three states of India to four high income countries. We provide quantitative data in three states across India (Himachal Pradesh, Kerala and Odisha) and compare with high-income countries to illustrate the importance of context-specific data monitoring and public health responses. There was a 1.9% increase in deaths, with 2.8% decrease in births in 2020, compared to 2019 in Himachal Pradesh, 13.3 and 9.2% decrease in Kerala and 16.7% and 21.4% decrease in Odisha. There was a direct correlation of all cause mortality to CFR on comparison between three states of India and despite the enormous burden of COVID19 in India all-cause mortality was lower compared to previous years in addition to the CFR due to COVID 19 being lower than in selected HICs.

Mortality-related risk factors of COVID-19: a systematic review and meta-analysis of 42 studies and 423,117 patients

BackgroundMortality rates of coronavirus disease-2019 (COVID-19) continue to rise across the world. The impact of several risk factors on coronavirus mortality has been previously reported in several meta‐analyses limited by small sample sizes. In this systematic review, we aimed to summarize available findings on the association between comorbidities, complications, smoking status, obesity, gender, age and D-dimer, and risk of mortality from COVID-19 using a large dataset from a number of studies.MethodElectronic databases including Google Scholar, Cochrane Library, Web of Sciences (WOS), EMBASE, Medline/PubMed, COVID-19 Research Database, and Scopus, were systematically searched till 31 August 2020. We included all human studies regardless of language, publication date or region. Forty-two studies with a total of 423,117 patients met the inclusion criteria. To pool the estimate, a mixed-effect model was used. Moreover, publication bias and sensitivity analysis were evaluated.ResultsThe findings of the included studies were consistent in stating the contribution of comorbidities, gender, age, smoking status, obesity, acute kidney injury, and D-dimer as a risk factor to increase the requirement for advanced medical care. The analysis results showed that the pooled prevalence of mortality among hospitalized patients with COVID-19 was 17.62% (95% CI 14.26–21.57%, 42 studies and 423,117 patients). Older age has shown increased risk of mortality due to coronavirus and the pooled odds ratio (pOR) and hazard ratio (pHR) were 2.61 (95% CI 1.75–3.47) and 1.31 (95% CI 1.11–1.51), respectively. A significant association were found between COVID-19 mortality and male (pOR = 1.45; 95% CI 1.41–1.51; pHR = 1.24; 95% CI 1.07–1.41), and current smoker (pOR = 1.42; 95% CI 1.01–1.83). Furthermore, risk of mortality among hospitalized COVID-19 patients is highly influenced by patients with Chronic Obstructive Pulmonary Disease (COPD), Cardiovascular Disease (CVD), diabetes, hypertension, obese, cancer, acute kidney injury and increase D-dimer.ConclusionChronic comorbidities, complications, and demographic variables including acute kidney injury, COPD, diabetes, hypertension, CVD, cancer, increased D-dimer, male gender, older age, current smoker, and obesity are clinical risk factors for a fatal outcome associated with coronavirus. The findings could be used for disease’s future research, control and prevention.

Echocardiography in suspected coronavirus infection: indications, limitations and impact on clinical management

ObjectivesTo describe the use of echocardiography in patients hospitalised with suspected coronavirus infection and to assess its impact on clinical management.MethodsWe studied 79 adults from a prospective registry of inpatients...

Utility of early warning scores to predict mortality in COVID-19 patients: A retrospective observational study.

Background:Coronavirus disease 2019 (COVID19) has evolved as a global pandemic. The patients with COVID-19 infection can present as mild, moderate, and severe disease forms. The reported mortality of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection is around 6.6%, which is lower than that of SARS-CoV and (middle east respiratory syndrome CoV). However, the fatality rate of COVID-19 infection is higher in the geriatric age group and in patients with multiple co-morbidities. The study aimed to evaluate the utility of early warning scores (EWS) to predict mortality in patients with moderate to severe COVID-19 infection.Methods:This retrospective study was carried out in a tertiary care institute of Uttarakhand. Demographic and clinical data of the admitted patients with moderate-to-severe COVID-19 infection were collected from the hospital record section and utilized to calculate the EWS-National early warning score (NEWS), modified early warning score (MEWS), Rapid Acute Physiology Score (RAPS), rapid emergency medicine score (REMS), and worthing physiological scoring system (WPS).Results:The area under the curve for NEWS, MEWS, RAPS, REMS, and WPS was 0.813 (95% confidence interval [CI]; 0.769–0.858), 0.770 (95% CI; 0.717–0.822), 0.755 (95% CI; 0.705–0.805), 0.892 (95% CI; 0.859–0.924), and 0.892 (95% CI; 0.86–0.924), respectively.Conclusion:The EWS at triage can be used for early assessment of severity as well as predict mortality in patients with COVID-19 patients.

Epidemiological features of age-gender distribution of coronavirus infection COVID-19 incidence and mortality (review)

The review of available literature sources and Internet resources for 2019–2021 is presented. It is devoted to the age-gender characteristics of the incidence of COVID-19, as well as mortality and mortality as a result of coronavirus infection in the world and in the Russian Federation as of May 2021. It is established that the main number of cases of new coronavirus infection is concentrated among the young working population from 40 to 59 years. At the same time, some countries have their own characteristics with a shift to younger age groups. There were no significant differences between men and women, with the exception of the age group of 85 years and older, where the female population prevails. The analysis of lethality showed that the most vulnerable groups are those over 80 years of age.

Influence of Economic and Political Variables on the Mortality Rate per Covid-19

Purpose: The global pandemic caused by Covid-19 has caused millions of infected and dead people around the world, generating an unprecedented crisis, and affecting the economy of all countries. The aim of this work is to analyze whether some of the most influential and determining variables of the economic level and welfare of a country, such as GDP, HDI or public debt, have a significant influence on the coronavirus mortality rate in the countries most affected by the pandemic. It is also examined whether the level of policies adopted as measured by the Government Response Stringency Index influences this rate. Design/Methodology/Approach: The countries with the highest number of Covid-19 cases at the beginning of the year 2021 were taken into account and the variables to be analyzed for these countries were obtained from different databases. A multiple regression was performed to determine whether the variables mentioned above have an influence on the mortality rate due to Covid-19. Findings: The results obtained show that GDP per capita has a positive influence and that lower public debt (expressed as a percentage of GDP) can contribute to reducing the number of deaths. In addition, the level of policies adopted by countries has a significant influence. The more restrictive these policies are, the lower the number of deaths per 100,000 inhabitants. This demonstrates the effectiveness of certain measures such as school closures or border closures. Practical Implications: the article provides recommendations on politics and Covid-19. It will be necessary to continue in this line of measures and propose a series of policies, such as mobility restrictions, perimeter confinements or mandatory teleworking or online teaching, to reduce the total number of deaths due to coronavirus and start economic reconstruction. Originality/Value: Significant findings on economic and political variables affecting Covid-19 mortality have been found.

Short-term forecasts of expected deaths

We introduce a method for making short-term mortality forecasts of a few months, illustrating it by estimating how many deaths might have happened if some major shock had not occurred. We apply the method to assess excess mortality from March to June 2020 in Denmark and Sweden as a result of the first wave of the coronavirus pandemic; associated policy interventions; and behavioral, healthcare, social, and economic changes. We chose to compare Denmark and Sweden because reliable data were available and because the two countries are similar but chose different responses to COVID-19: Denmark imposed a rather severe lockdown; Sweden did not. We make forecasts by age and sex to predict expected deaths if COVID-19 had not struck. Subtracting these forecasts from observed deaths gives the excess death count. Excess deaths were lower in Denmark than Sweden during the first wave of the pandemic. The later/earlier ratio we propose for shortcasting is easy to understand, requires less data than more elaborate approaches, and may be useful in many countries in making both predictions about the future and the past to study the impact on mortality of coronavirus and other epidemics. In the application to Denmark and Sweden, prediction intervals are narrower and bias is less than when forecasts are based on averages of the last 5 y, as is often done. More generally, later/earlier ratios may prove useful in short-term forecasting of illnesses and births as well as economic and other activity that varies seasonally or periodically.

Application of Distribution-Delay Models to Estimating the Hospitalized Mortality Rate of Covid-19 According to Delay Effect of Hospitalizations Counts

Introduction:The COVID-19 infectious epidemic has become a serious worry all over the world, including Iran. The high outbreak of disease ranked Iran as second in Asia and 11th in the world. Given the growing progress of this epidemic in infecting and killing individuals, it is essential to forecast the delay effect of the number of hospitalized upon the hospitalized mortality rate. Methods: In this study, we used the daily Hospitalization cases of COVID-19 of IRAN for the period of 15-May 2020 to 5-Oct 2020 which were obtained from the online database. Five distribution delay models were compared for estimating and forecasting. Results: Based on measurement errors DDM selected as the best model for forecasting the number of death. According to this model, the long-run effects show that observing the effect of hospitalization counts on death counts takes an average of five days and the long-run hospitalized mortality rate was 12%. Conclusion: The overall hospitalized mortality rate of COVID-19 in Iran is less than the global rate of 15%. The mean of delay effect of daily hospitalization on mortality is approximately 5 days. Our findings showed distributed delay model (DDM) has better performance in the forecasting of the future behavior of the Coronavirus mortality, and providing to government and health care decision- makers the possibility to predict the outcomes of their decision on public health.

Clinical manifestations and outcomes of coronavirus disease-19 in heart transplant recipients: a multicentre case series with a systematic review and meta-analysis.

SummaryAvailable data on clinical presentation and mortality of coronavirus disease‐2019 (COVID‐19) in heart transplant (HT) recipients remain limited. We report a case series of laboratory‐confirmed COVID‐19 in 39 HT recipients from 3 French heart transplant centres (mean age 54.4 ± 14.8 years; 66.7% males). Hospital admission was required for 35 (89.7%) cases including 14/39 (35.9%) cases being admitted in intensive care unit. Immunosuppressive medications were reduced or discontinued in 74.4% of the patients. After a median follow‐up of 54 (19–80) days, death and death or need for mechanical ventilation occurred in 25.6% and 33.3% of patients, respectively. Elevated C‐reactive protein and lung involvement ≥50% on chest computed tomography (CT) at admission were associated with an increased risk of death or need for mechanical ventilation. Mortality rate from March to June in the entire 3‐centre HT recipient cohort was 56% higher in 2020 compared to the time‐matched 2019 cohort (2% vs. 1.28%, P = 0.15). In a meta‐analysis including 4 studies, pre‐existing diabetes mellitus (OR 3.60, 95% CI 1.43–9.06, I 2 = 0%, P = 0.006) and chronic kidney disease stage III or higher (OR 3.79, 95% CI 1.39–10.31, I 2 = 0%, P = 0.009) were associated with increased mortality. These findings highlight the aggressive clinical course of COVID‐19 in HT recipients.