COVID-19 Case Fatality Rates Research Articles

Effective Pandemic Response: Lessons from Kauai.

Local health jurisdictions have struggled to protect their communities during the pandemic, and successes are few. The Kauai District Health Office (KDHO) of the Hawaii Department of Health serves a rural island community of 73,000 residents. As a state agency, KDHO works closely with the county mayor and administration. Kauai has experienced comparatively low COVID-19 case and case-fatality rates while maintaining strong community and leadership cohesion. Kauai's response was highly rated by residents in a recent Community Assessment for Public Health Emergency Response survey. In this article, we describe examples of local response efforts in the areas of (1) policy and regulations, (2) health-directed isolation and quarantine, (3) case investigation and contact tracing, (4) testing availability, (5) vaccine rollout and availability, and (6) public information, as well as the factors that have contributed to Kauai's successes. KDHO regularly prioritizes agencywide initiatives that cross program silos; staff have experience using the incident command system in real-world situations; the community health worker team is multicultural, multilingual, and well established; and staff are integral members of the community they serve. Preexisting partnerships were strong, including those with county agencies, healthcare partners, and nongovernmental organizations, which facilitated early and effective collaboration. Response successes include implementation of unified command, coordinated public messaging, early protective measures, effective disease control and outbreak response, attention to secondary impacts of the pandemic, free community testing, mass vaccination, and mobile vaccinations and testing. The value of local health departments engaging regularly and authentically with partners and communities cannot be overstated. It has saved lives on Kauai. Local health jurisdictions should focus on all-hazards and all-staff endeavors to enhance their disaster response effectiveness.

Impact of good governance, economic growth and universal health coverage on COVID-19 infection and case fatality rates in Africa

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has disrupted lives across all countries and communities. It significantly reduced the global economic output and dealt health systems across the world a serious blow. There is growing evidence showing the progression of the COVID-19 pandemic and the impact it has on health systems, which should help to draw lessons for further consolidating and realizing universal health coverage (UHC) in all countries, complemented by more substantial government commitment and good governance, and continued full implementation of crucial policies and plans to avert COVID-19 and similar pandemic threats in the future. Therefore, the objective of the study was to assess the impact of good governance, economic growth and UHC on the COVID-19 infection rate and case fatality rate (CFR) among African countries.MethodsWe employed an analytical ecological study design to assess the association between COVID-19 CFR and infection rate as dependent variables, and governance, economic development and UHC as independent variables. We extracted data from publicly available databases (i.e., Worldometer, Worldwide Governance Indicators, Our World in Data and WHO Global Health Observatory Repository). We employed a multivariable linear regression model to examine the association between the dependent variables and the set of explanatory variables. STATA version 14 software was used for data analysis.ResultsAll 54 African countries were covered by this study. The median observed COVID-19 CFR and infection rate were 1.65% and 233.46%, respectively. Results of multiple regression analysis for predicting COVID-19 infection rate indicated that COVID-19 government response stringency index (β = 0.038; 95% CI 0.001, 0.076; P = 0.046), per capita gross domestic product (GDP) (β = 0.514; 95% CI 0.158, 0.87; P = 0.006) and infectious disease components of UHC (β = 0.025; 95% CI 0.005, 0.045; P = 0.016) were associated with COVID-19 infection rates, while noncommunicable disease components of UHC (β = −0.064; 95% CI −0.114; −0.015; P = 0.012), prevalence of obesity among adults (β = 0.112; 95% CI 0.044; 0.18; P = 0.002) and per capita GDP (β = −0.918; 95% CI −1.583; −0.254; P = 0.008) were associated with COVID-19 CFR.ConclusionsThe findings indicate that good governance practices, favourable economic indicators and UHC have a bearing on COVID-19 infection rate and CFR. Effective health system response through a primary healthcare approach and progressively taking measures to grow their economy and increase funding to the health sector to mitigate the risk of similar future pandemics would require African countries to move towards UHC, improve governance practices and ensure economic growth in order to reduce the impact of pandemics on populations.

Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates.

Although it is widely used as a measure for mortality, the case fatality rate (CFR) ofcoronavirus disease 2019 (COVID-19) can vary over time and fluctuate for many reasons otherthan viral characteristics. To compare the CFRs of different countries in equal measure, weestimated comparable CFRs after adjusting for multiple covariates and examined the mainfactors that contributed to variability in the CFRs among 21 countries. For statistical analysis, time-series cross-sectional data were collected from OurWorld in Data, CoVariants.org, and GISAID. Biweekly CFRs of COVID-19 were estimated bypooled generalized linear squares regression models for the panel data. Covariates includedthe predominant virus variant, reproduction rate, vaccination, national economic status,hospital beds, diabetes prevalence, and population share of individuals older than age 65. Intotal, 21 countries were eligible for analysis. Adjustment for covariates reduced variation in the CFRs of COVID-19 across countriesand over time. Regression results showed that the dominant spread of the Omicron variant,reproduction rate, and vaccination were associated with lower country-level CFRs, whereasage, the extreme poverty rate, and diabetes prevalence were associated with higher countrylevel CFRs. A direct comparison of crude CFRs among countries may be fallacious, especiallyin a cross-sectional analysis. Our study presents an adjusted comparison of CFRs over timefor a more proper comparison. In addition, our findings suggest that comparing CFRs amongdifferent countries without considering their context, such as the epidemic phase, medicalcapacity, surveillance strategy, and socio-demographic traits, should be avoided.

Amplified effect of social vulnerability on health inequality regarding COVID-19 mortality in the USA: the mediating role of vaccination allocation

BackgroundVaccination reduces the overall burden of COVID-19, while its allocation procedure may introduce additional health inequality, since populations characterized with certain social vulnerabilities have received less vaccination and been affected more by COVID-19. We used structural equation modeling to quantitatively evaluate the extent to which vaccination disparity would amplify health inequality, where it functioned as a mediator in the effect pathways from social vulnerabilities to COVID-19 mortality.MethodsWe used USA nationwide county (n = 3112, 99% of the total) level data during 2021 in an ecological study design. Theme-specific rankings of social vulnerability index published by CDC (latest data of 2018, including socioeconomic status, household composition & disability, minority status & language, and housing type & transportation) were the exposure variables. Vaccination coverage rate (VCR) during 2021 published by CDC was the mediator variable, while COVID-19 case fatality rate (CFR) during 2021 published by John Hopkinson University, the outcome variable.ResultsGreater vulnerabilities in socioeconomic status, household composition & disability, and minority status & language were inversely associated with VCR, together explaining 11.3% of the variance of VCR. Greater vulnerabilities in socioeconomic status and household composition & disability were positively associated with CFR, while VCR was inversely associated with CFR, together explaining 10.4% of the variance of CFR. Our mediation analysis, based on the mid-year data (30th June 2021), found that 37.6% (mediation/total effect, 0.0014/0.0037), 10% (0.0003/0.0030) and 100% (0.0005/0.0005) of the effects in the pathways involving socioeconomic status, household composition & disability and minority status & language, respectively, were mediated by VCR. As a whole, the mediation effect significantly counted for 30.6% of COVID-19 CFR disparity. Such a mediation effect was seen throughout 2021, with proportions ranging from 12 to 32%.ConclusionsAllocation of COVID-19 vaccination in the USA during 2021 led to additional inequality with respect to COVID-19 mortality. Viable public health interventions should be taken to guarantee an equitable deployment of healthcare recourses across different population groups.

The COVID-19 third wave in Myanmar following the military coup

Background: COVID-19 seriously hit Myanmar between June and August 2021, a few months after the military coup, though the first and second waves in 2020 were managed effectively by the government. People in Myanmar experienced serious consequences of the COVID-19 pandemic precipitated by the disorganized health system under the military junta. This study aimed to analyse the situation of COVID-19 occurrence and death proportions during its third wave in Myanmar. Methods: An online survey was conducted using a Google form. People with the symptoms of COVID-19 and those who died from COVID-19 between June and August 2021 were eligible to participate. The Google form was extracted into an Excel datasheet and analysed using Stata v16.1. Results: Among the 29,171 participants, 76.7% were over 30 years old and 56.4% were female. A majority of participants were from highly populated regions: Yangon (17,220; 59%) (Business capital), Mandalay (3,740; 12.8%) and Sagaing (1,546; 5.3%). Participants sought health care from telegram/other online services (34%), home care by health care providers (22%), private clinics (13%) and public hospitals run under the military junta (5%). Overall, 15% of participants died, of which, 72% occurred at home and 17% at public hospitals. Significantly higher proportions of deaths were seen among participants over 60 years than other age groups and males (p<0.001). Death proportions at different weeks from June to August 2021 ranged from 12.4% to 17.3%, much higher than the military junta’s reports. Overall, 25% of participants received oxygen therapy. Conclusions: Death proportions in different weeks were consistently over 12%. The majority of participants received tele/online and home treatment services. Most deaths occurred at home. Findings indicated the high COVID-19 case fatality rates with limited access to public hospital care during the third wave. The data suggests that the outcomes were adversely impacted by the military coup.

Global COVID-19 case fatality rates influenced by inequalities in human development and vaccination rates

AimCOVID-19 has exerted distress on virtually every aspect of human life with disproportionate mortality burdens on older individuals and those with underlying medical conditions. Variations in COVID-19 incidence and case fatality rates (CFRs) across countries have incited a growing research interest regarding the effect of social factors on COVID-19 case-loads and fatality rates. We investigated the effect of population median age, inequalities in human development, healthcare capacity, and pandemic mitigation indicators on country-specific COVID-19 CFRs across countries and regions.Subject and methodsUsing population secondary data from multiple sources, we conducted a cross-sectional study and used regional analysis to compare regional differences in COVID-19 CFRs as influenced by the selected indicators.ResultsThe analysis revealed wide variations in COVID-19 CFRs and the selected indicators across countries and regions. Mean CFR was highest for South America at 1.973% (± 0.742) and lowest for Oceania at 0.264% (± 0.107), while the Africa sub-region recorded the lowest scores for pandemic preparedness, vaccination rate, and other indicators. Population Median Age [0.073 (0.033 0.113)], Vaccination Rate [−3.3389 (−5.570.033 −1.208)], and Inequality-Adjusted Human Development Index (IHDI) [−0.014 (−0.023 −0.004)] emerged as statistically significant predictors of COVID-19 CFR, with directions indicating increasing Population Median Age, higher inequalities in human development and low vaccination rate are predictive of higher fatalities from COVID-19.ConclusionRegional differences in COVID-19 CFR may be influenced by underlying differences in sociodemographic and pandemic mitigation indicators. Populations with wide social inequalities, increased population Median Age and low vaccination rates are more likely to suffer higher fatalities from COVID-19.

COVID-19 among Chronic Dialysis Patients after First Year of Pandemic, Argentina.

We performed a descriptive study to characterize effects from COVID-19 among chronic dialysis patients compared with the general population in Argentina during March 2020-February 2021. COVID-19 case-fatality rate of chronic dialysis patients was 10 times the national rate; the age-standardized mortality ratio was 6.8 (95% CI 6.3-7.3).

Revisiting the COVID-19 fatality rate and altitude association through a comprehensive analysis

The emergence of COVID-19 virus has led to a pandemic with staggering morbidity and mortality. There is evidence showing that pre-existing conditions and environmental factors are associated with worse COVID-19 outcomes. Among these conditions, altitude is of particular interest. Altitude has been shown to influence the morbidity and mortality of multiple chronic pathologies such as cardiovascular disease, chronic obstructive pulmonary disease and lung cancer. COVID-19 fatality rate has been associated with as altitude as well, but findings are disputed. Therefore, we revisit this assessment with a comprehensive analysis of the relationship between COVID-19 fatality rates and altitude for the Mountain region of the United States while considering the effect of additional comorbidities and sociodemographic factors. A Generalized Additive Model (GAM) approach using one year of county data adjusted by population density was performed to evaluate associations within states and for the whole region. Our analysis revealed a consistent effect where COVID-19 case-fatality rate is decreased with higher altitude, even when controlling for pre-existing conditions and certain demographic variables. In summary, the work presented provides evidence that suggests that the protective effects of high altitude are likely to be influenced by physiologic factors but demographic trends that are associated with life at high altitude must also be considered.

SAPS 3 as a 28-day mortality predictor in critically ill COVID-19 patients

Background: The case fatality rate (CFR) of COVID-19 was 8.7% in Indonesia on April 2020. Simplified Acute Physiology Score 3 (SAPS 3) has been used to predict the hospital mortality based on different variables including acute physiologic derangements, current conditions and interventions, and previous health status assess the severity of condition during the first hour of admission to the ICU. We assessed SAPS 3 to predict the outcome and mortality of critical COVID-19 patients in ICU over a period of 28 days.
 Methodology: This retrospective cohort study consisted of adult patients admitted to ICU with probable or confirmed COVID-19 in our hospital. We recorded the patients SAPS 3 score from the medical record as well as the 28-day mortality. Validity of the SAPS 3 score was done by the Area Under Curve (AUC) measurement and Hosmer-Lemeshow calibration test.
 Results: The mortality rate of critical COVID-19 patients was 43.8%. The age, intra-hospital location before ICU admission, use of vasoactive drugs (P < 0.0001), focal neurological deficits (P < 0.0001), respiratory failure (P = 0.004), creatinine ≥ 3.5 mg/dL (P = 0.005), and platelets < 50,000 /µL (P = 0.032) were significantly associated with 28-days mortality in the ICU. SAPS 3 showed good discrimination and predictability. The optimal cut-off point was 39 with 70.3% sensitivity and 74.4% specificity.
 Conclusion: SAPS3 score system was valid in predicting the 28-day mortality of COVID-19 patients in the ICU with good discrimination and calibration value; therefore, it is an important predictor tool for early prognosis screening that will help reduce the strain over the ICU resources.
 Abbreviations: CFR: Case Fatality Rate; SAPS 3: Simplified Acute Physiology Score 3; COVID-19: The Coronavirus Disease 2019; ICU: Intensive Care Unit; APACHE: Acute Physiology and Chronic Health Evaluation; SPSS: Statistical Package for Social Sciences; GCS: Glasgow Coma Scale; ROC: Receiver Operating Characteristic; PHEIC: Public Health Emergency of International Concern; OR: Odds Ratio;
 Citation: Sukmono RB, Manggala SK, Priscilla P, Aditianingsih D. SAPS 3 as a 28-day mortality predictor in critically ill COVID-19 patients. Anaesth. pain intensive care 2022;26(5):640-648.
 DOI: 10.35975/apic.v26i5.1986

Changes over Time in Association Patterns between Estimated COVID-19 Case Fatality Rates and Demographic, Socioeconomic and Health Factors in the US States of Florida and New York

The United States struggled exceptionally during the COVID-19 pandemic. For researchers and policymakers, it is of great interest to understand the risk factors associated with COVID-19 when examining data aggregated at a regional level. We examined the county-level association between the reported COVID-19 case fatality rate (CFR) and various demographic, socioeconomic and health factors in two hard-hit US states: New York and Florida. In particular, we examined the changes over time in the association patterns. For each state, we divided the data into three seasonal phases based on observed waves of the COVID-19 outbreak. For each phase, we used tests of correlations to explore the marginal association between each potential covariate and the reported CFR. We used graphical models to further clarify direct or indirect associations in a multivariate setting. We found that during the early phase of the pandemic, the association patterns were complex: the reported CFRs were high, with great variation among counties. As pandemics progressed, especially during the winter phase, socioeconomic factors such as median household income and health-related factors such as the prevalence of adult smokers and mortality rate of respiratory diseases became more significantly associated with the CFR. It is remarkable that common risk factors were identified for both states.

COVID-19, Non-Communicable Diseases, and Behavioral Factors in the Peruvian Population ≥ 15 Years: An Ecological Study during the First and Second Year of the COVID-19 Pandemic.

A range of health-related and behavioral risk factors are associated with COVID-19 incidence and mortality. In the present study, we assess the association between incidence, mortality, and case fatality rate due to COVID-19 and the prevalence of hypertension, obesity, overweight, tobacco and alcohol use in the Peruvian population aged ≥15 years during the first and second year of the COVID-19 pandemic. In this ecological study, we used the prevalence rates of hypertension, overweight, obesity, tobacco, and alcohol use obtained from the Encuesta Demográfica y de Salud Familiar (ENDES) 2020 and 2021. We estimated the crude incidence and mortality rates (per 100,000 habitants) and case fatality rate (%) of COVID-19 in 25 Peruvian regions using data from the Peruvian Ministry of Health that were accurate as of 31 December 2021. Spearman correlation and lineal regression analysis was applied to assess the correlations between the study variables as well as multivariable regression analysis adjusted by confounding factors affecting the incidence and mortality rate and case fatality rate of COVID-19. In 2020, adjusted by confounding factors, the prevalence rate of obesity (β = 0.582; p = 0.037) was found to be associated with the COVID-19 mortality rate (per 100,000 habitants). There was also an association between obesity and the COVID-19 case fatality rate (β = 0.993; p = 0.014). In 2021, the prevalence of obesity was also found to be associated with the COVID-19 mortality rate (β = 0.713; p = 0.028); however, adjusted by confounding factors, including COVID-19 vaccination coverage rates, no association was found between the obesity prevalence and the COVID-19 mortality rate (β = 0.031; p = 0.895). In summary, Peruvian regions with higher obesity prevalence rates had higher COVID-19 mortality and case fatality rates during the first year of the COVID-19 pandemic. However, adjusted by the COVID-19 vaccination coverage, no association between the obesity prevalence rate and the COVID-19 mortality rate was found during the second year of the COVID-19 pandemic.

Treatment and case fatality rate of COVID-19 in Africa.

In Africa, the treatment of COVID-19 depends on each country. Several protocols are observed with real results that we described in this study. The objective of this review was to describe the treatment of COVID-19 and the case fatality rate in African countries, by reviewing the literature on treatment and case fatality in African countries whose data was available through the internet during the writing period until February 7, 2021. The majority of African countries had a treatment based on hydroxychloroquine or chloroquine + azithromycin, used in varying doses depending on the country. The lethality in Africa remains low compared to European and American countries. The same treatment being used in some northern countries does not fully explain the low case fatality.

Case Fatality Rate of COVID-19 and its Relationship to Sociodemographic Characteristics in Ecuador, 2020.

Objective: To analyze sociodemographic factors’ influence on COVID-19 case fatality rate (CFR) in Ecuador on a subnational level. Methods: Publicly available register-based observational study. A retrospective cohort of COVID-19 infections between epidemiological weeks 8–53 in the Ecuadorian public healthcare system was determined from available records. Statistical analyses were conducted to evaluate CFR trends according to factors such as sex, age, location, and healthcare provider. Results: Overall CFR was 9.4%; by canton, median CFR was 5.2%, with some cantons with much higher rates, like Santa Elena (39.1%). Overall CFR decreased during the period, from 16.6% (week 8) to 2.63% (week 53). Being in a rural area was an independent protective factor. Patients over 65 had a hazard ratio of 11.38 (95% CI [11.05, 11.72]). Sex, ethnicity, and treatment from public facilities were also associated with death risk. Conclusion: CFR is a proxy indicator of COVID-19 impact in Ecuador, and this location-based analysis provides new information on the disease’s specific impact subnationally. Overall COVID-19 CFR during the entire period was high, suggesting the need to improve COVID-19 care in Ecuador.

Analyzing self-evaluation capacity scores related to infectious disease control in International Health Regulations during the first year of COVID-19 pandemic

This study aimed to identify changes in the average score of countries' International Health Regulation (IHR) self-evaluation capacity (e-SPAR) in 2020 compared to 2019, and the factors associated with these changes. We collected the data from the World Health Organization (WHO) website in May 2021, then calculated the significant differences between the e-SPAR score in both years. Next, we conducted a test to identify the association between changes in member states' e-SPAR capacity scores and their COVID-19 case fatality rate (CFR), Human Development Index, Civil Liberties, and Government Effectiveness. The results showed that the average e-SPAR scores in 2020 were significantly higher than in 2019. Among the 154 countries, we included in this study, the scores of 98 countries increased in 2020, of which 37.75% were lower-middle-income countries. Meanwhile, among the 56 countries whose scores did not increase, 26 (46.42%) were high-income countries. The COVID-19 CFR was significantly associated with the changes in e-SPAR scores of 154 countries (p < 0.01), as well as the countries whose scores increased (p < 0.05). In conclusion, we consider e-SPAR to still be a useful tool to facilitate countries in monitoring their International Health Regulation (IHR) core capacity progress, especially in infectious disease control to prepare for future pandemics.

COVID-19 risk areas associated with social vulnerability in northeastern Brazil: an ecological study in 2020.

COVID-19 is a major public health concern in this century. The causative agent SARS-CoV-2, is highly contagious and spreads continuously across territories. Spatial analysis is of enormous importance in the process of understanding the disease and its transmission mechanisms. We aimed to identify the risk areas for COVID-19 and analyze their association with social vulnerability in Maceió, Alagoas. The study was conducted in 2020. This is an ecological study to evaluate the incidence, mortality and case fatality rate of COVID-19 and their relationship with 12 indicators of human development and social vulnerability. Multivariate and spatial statistics were applied. A 95% confidence interval and a 5% confidence level were considered. The spatial scan statistic revealed the existence of six high-risk clusters for the incidence of COVID-19. The regression model showed that social indicators, such as literacy of people, residents of private households, households with more than four residents, and resident brown population, were associated with COVID-19 transmission in Maceió-AL. The disease affected localities whose populations are exposed to a context of intense socioeconomic vulnerability. Based on the results, it is necessary to adopt measures that take into account the social determinants of health in order to minimize the damage caused by the pandemic.

Psychological impact on dental students and professionals in a Lima population during COVID-19s wave: a study with predictive models

Peru was the country with the highest COVID-19 case fatality rate worldwide during second wave of infection, with dentists and pre-professional students being susceptible to infection due to clinical procedures they perform. This situation could have generated some kind of psychological disorder within this group. Therefore, the present study aimed to assess how COVID-19 pandemic affected this population group during second wave, in relation to depression, anxiety and stress. This observational and cross-sectional study in 368 Peruvian dentists (186 students and 182 professionals), was carried out during August to November 2021. The DASS-21 Scale was used to diagnose depression, anxiety and stress. For the statistical analysis, Pearson's chi-square test was used, in addition to a logit model using odds ratio (OR) to evaluate depression, anxiety and stress with the following factors: gender, age group, marital status, monthly family income, children, academic level, history of COVID-19, COVID-19 symptomatology, close relative with COVID-19, living with vulnerable people and work dedication. In addition, predictive models were constructed considering all possible significant causes. A significance level of p < 0.05 was considered. Dental students and professionals presented significant differences in levels of depression, anxiety and stress (p < 0.001, p = 0.022, p = 0.001; respectively). Male students were 56% less likely to develop stress (OR 0.44; CI 0.22–0.85) compared to females; while those unmarried were 81% less likely to develop stress (OR 0.19; CI 0.04–0.85). Likewise, those with children were 83% less likely to develop stress (OR 0.17; CI 0.06–0.52) and 65% less likely to develop depression (OR 0.35; CI 0.15–0.80). In addition, COVID-19 asymptomatics were 60% less likely to develop depression (OR 0.40; CI 0.17–0.92). However, having relatives with COVID-19 caused almost three times the probability of developing depression (OR 2.96; CI 1.29–6.79) and twice the probability of developing stress (OR 2.49; CI 1.07–5.78). As for dental professionals, it was noticed that those unmarried had almost three times the probability of developing stress (OR 2.93; CI 1.38–6.23); while those who only worked had twice the probability of developing stress (OR 2.37; CI 1.17–4.78). Dental students had a higher prevalence of depression, anxiety and stress. In addition, having children and being asymptomatic were protective predictors for depression, while being male, unmarried and having children were protective predictors for stress. However, having a relative with COVID-19 was a risk predictor for depression and stress. In professionals, only working and being unmarried were risk predictors for stress.

Fatality assessment and variant risk monitoring for COVID-19 using three new hospital occupancy related metrics.

BackgroundThough case fatality rate (CFR) is widely used to reflect COVID-19 fatality risk, its use is limited by large temporal and spatial variation. Hospital mortality rate (HMR) is also used to assess the severity of COVID-19, but HMR data is not directly available globally. Alternative metrics are needed for COVID-19 severity and fatality assessment.MethodsWe introduce new metrics for COVID-19 fatality risk measurements/monitoring and a new mathematical model to estimate average hospital length of stay for deaths (Ldead) and discharges (Ldis). Multiple data sources were used for our analyses.FindingsWe propose three, new metrics: hospital occupancy mortality rate (HOMR), ratio of total deaths to hospital occupancy (TDHOR), and ratio of hospital occupancy to cases (HOCR), for dynamic assessment of COVID-19 fatality risk. Estimated Ldead and Ldis for 501,079 COVID-19 hospitalizations in 34 US states between 7 August 2020 and 1 March 2021 were 18·2(95%CI:17·9-18·5) and 14·0(95%CI:13·9-14·0) days, respectively. We found the dramatic changes in COVID-19 CFR observed in 27 countries during early stages of the pandemic were mostly caused by undiagnosed cases. Compared to the first week of November 2021, the week mean HOCRs (mimics hospitalization-to-case ratio) for Omicron variant (58·6% of US new cases as of 25 December 2021) decreased 65·16% in the US as of 16 January 2022.InterpretationThe new and reliable measurements described here could be useful for COVID-19 fatality risk and variant-associated risk monitoring.FundingNo specific funding was associated with the present study.

Global burden of SARS-CoV-2 infection, hospitalization and case fatality rate among COVID-19 vaccinated individuals and its associated factors: A systematic review and meta-analysis protocol.

BackgroundCOVID-19 has been the most important public health concern worldwide since 2020. Several vaccines are now available to help in controlling COVID-19 associated morbidity and mortality. This study will aim to provide the global and regional prevalence of SARS-CoV-2 infection as well as an estimate of disease severity among COVID-19 vaccinated individuals.Materials and methodsIn order to determine the global burden of SARS-CoV-2 infection among vaccinated individuals, we will systematically extract and review papers from PubMed/MEDLINE, Excerpta Medica database (EMBASE), Cochrane Central Register of Controlled Trials (CENTRAL), Science direct and Cumulative Index to Nursing and Allied Health Literature (CINAHL). All the studies describing the prevalence and/or disease severity (hospitalization and case fatality rate) data of COVID-19 among individuals who received a partial or complete dose of WHO-approved COVID-19 vaccines will be eligible. A random effect model will be used to calculate the pooled prevalence and to estimate the disease severity. Subgroup analysis will be performed to explore the association between the number of vaccine doses received and the COVID-19 burdens.DiscussionThis systematic review and meta-analysis will provide the global estimate data on pooled prevalence, hospitalization and case fatality rates of COVID-19 among vaccinated individuals. Moreover, the factors associated with reinfection and disease severity will be equally investigated in the meta-analysis. The results of this study will contribute in the understanding and estimation of the global burden of COVID-19 among vaccinated individuals. Findings will provide meaningful information for the success of the current global rollout of COVID-19 vaccination strategies and pave the way for future interventions.Systematic review registrationCRD42021273074.

Risk factors for COVID-19 case fatality rate in people with type 1 and type 2 diabetes mellitus: A nationwide retrospective cohort study of 235,248 patients in the Russian Federation.

The aimTo study the association of demographic, clinical, and laboratory factors and the use of glucose-lowering drugs and anti-coronavirus disease (COVID-19) vaccination with the COVID-19-related case fatality rate (CFR) in diabetes mellitus (DM) patients.MethodsThis study is a nationwide observational cohort study based on the data from the National Diabetes Register (NDR) that is the database containing online clinical information about the population with DM. The outcomes (death or recovery) for COVID-19 were registered in 235,248 patients with DM [type 1 diabetes mellitus (T1DM), n = 11,058; type 2 diabetes mellitus (T2DM), n = 224,190] from March 20, 2020, until November 25, 2021. The unadjusted odds ratio (OR) and 95% confidence interval (CI) were used to estimate the risk factors for CFR. Then the ranging of significant factors was performed and the most vulnerable groups of factors for the lethal outcome were chosen.ResultsThe CFR due to COVID-19 was 8.1% in T1DM and 15.3% in T2DM. Increased CFR was associated with the male population [OR = 1.25 (95% CI: 1.09–1.44) in T1DM and 1.18 (95% CI: 1.15–1.21) in T2DM], age ≥65 years [OR = 4.44 (95% CI: 3.75–5.24) in T1DM and 3.18 (95% CI: 3.09–3.26) in T2DM], DM duration ≥10 years [OR = 2.46 (95% CI: 2.06–2.95) in T1DM and 2.11 (95% CI: 2.06–2.16) in T2DM], body mass index (BMI) ≥30 kg/m2 [OR = 1.95 (95% CI: 1.52–2.50)] in T1DM, HbA1c ≥7% [OR = 1.35 (95% CI: 1.29–1.43)] in T2DM. The atherosclerotic cardiovascular disease (ASCVD) and chronic kidney disease (CKD) were associated with higher CFR in T1DM but not in T2DM. The pre-COVID-19 glucose-lowering therapy in T2DM was differently associated with CFR (OR): 0.61 (95% CI: 0.59–0.62) for metformin, 0.59 (95% CI: 0.57–0.61) for dipeptidyl peptidase-4 inhibitors (DPP-4 inhibitors), 0.46 (95% CI: 0.44–0.49) for sodium-glucose co-transporter-2 (SGLT2) inhibitors, 0.38 (95% CI: 0.29–0.51) for glucagon-like peptide-1 receptor agonists (arGLP-1), 1.34 (95% CI: 1.31–1.37) for sulfonylurea (SU), and 1.47 (95% CI: 1.43–1.51) for insulin. Anti-COVID-19 vaccination was associated with a lower fatality risk in both DM types: OR = 0.07 (95% CI: 0.03–0.20) in T1DM and OR = 0.19 (95% CI: 0.17–0.22) in T2DM.ConclusionsThe results of our study suggest that increased COVID-19-related fatality risk in both T1DM and T2DM patients associated with the male population, older age, longer DM duration, and absence of anti-COVID-19 vaccination. In T2DM, pre-COVID-19 glucose-lowering therapy with metformin, DPP-4 inhibitors, SGLT2 inhibitors, and arGLP-1 had a positive effect on the risk of death. The most vulnerable combination of risk factors for lethal outcome in both DM types was vaccine absence + age ≥65 years + DM duration ≥10 years.

Racial and ethnic disparities in the observed COVID-19 case fatality rate among the U.S. population

PurposeDuring the initial 12 months of the pandemic, racial and ethnic disparities in COVID-19 death rates received considerable attention but it has been unclear whether disparities in death rates were due to disparities in case fatality rates (CFRs), incidence rates or both. We examined differences in observed COVID-19 CFRs between U.S. White, Black/African American, and Latinx individuals during this period.MethodsUsing data from the COVID Tracking Project and the Centers for Disease Control and Prevention COVID-19 Case Surveillance Public Use dataset, we calculated CFR ratios comparing Black and Latinx to White individuals, both overall and separately by age group. We also used a model of monthly COVID-19 deaths to estimate CFR ratios, adjusting for age, gender, and differences across states and time.ResultsOverall Black and Latinx individuals had lower CFRs than their White counterparts. However, when adjusting for age, Black and Latinx had higher CFRs than White individuals among those younger than 65. CFRs varied substantially across states and time.ConclusionsDisparities in COVID-19 case fatality among U.S. Black and Latinx individuals under age 65 were evident during the first year of the pandemic. Understanding racial and ethnic differences in COVID-19 CFRs is challenging due to limitations in available data.