Critical care for severe coronavirus disease 2019: a population-based study from a province with low case-fatality rate in China.
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ABSTRACT:
SUBMITTER: Liao XL
PROVIDER: S-EPMC7862801 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
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Critical care for severe coronavirus disease 2019: a population-based study from a province with low case-fatality rate in China.
Liao Xue-Lian XL Chen Hong H Li Zhen Z Wang Bo B Zhang Zhong-Wei ZW Li Wei-Min WM Liang Zong-An ZA Tang Jin J Wang Jian J Shi Rui R Jin Xiao-Dong XD Kang Yan Y
Chinese medical journal 20201103 1
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Project description:BackgroundJeju island had the seventh highest incidence rate of coronavirus disease 2019 (COVID-19) but showed the lowest case fatality rate among 17 provinces of Korea, which may be associated with comorbidities and geographic differences. This study aimed to analyze the epidemiological and clinical characteristics of patients with COVID-19 and evaluate the risk factors for severe COVID-19 in Jeju island, Korea.Materials and methodsAll patients with COVID-19 admitted between February 20, 2020, and June 19, 2021, at a single center were retrospectively enrolled in this study. The severity of illness was defined using five categories (asymptomatic, mild, moderate, severe, and critical) according to the National Institute of Health criteria. Then, patients with severe and critical illness were grouped into a severe group, whereas patients with asymptomatic, mild, and moderate illness were grouped into a non-severe group. Multivariate logistic regression analysis was performed using risk factors that were found to be significantly associated with the severe group.ResultsThis study included 348 patients with a median age was 57 years, and 37.5% were aged 60 or older. Among them, 43.4% were male and 10.9% were asymptomatic, whereas 41.4%, 33.9%, 12.9%, and 1.1% had mild, moderate, severe, and critical illness. The all-cause mortality of patients with COVID-19 was 0.28% (1/348). Among confirmed patients with COVID-19, exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was mainly within Jeju island (75.9%). The mean body mass index was 24.09 ± 4.04 kg/m², the median comorbidity index score was low in each group (0 in asymptomatic; 1 in mild; 1 in moderate; 1 in severe; and 2 in critical group, P <0.548). In the multivariable analysis, male sex [odds ratio (OR), 6.37; 95% confidence interval (CI), 2.69 - 15.13; P <0.001], ≥65 years of age (OR, 2.68; 95% CI, 1.18 - 6.10; P <0.019), chronic pulmonary disease (OR, 6.10; 95% CI, 1.40 - 26.61; P = 0.016), and length of fever duration (OR, 1.33; 95% CI, 1.19 - 1.49; P <0.001) were independently associated with severe COVID-19.ConclusionThe most relevant risk factors of COVID-19 severity were male sex, older age, underlying chronic lung diseases, and duration of fever during hospitalization. The risk factors for severe COVID-19 were not significantly different from those reported in other studies. However, a lower proportion of the older population among confirmed SARS-CoV-2 cases might contribute to the lower fatality rate than the national rate.
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Project description:The aim of this study is to provide a more accurate representation of COVID-19's case fatality rate (CFR) by performing meta-analyses by continents and income, and by comparing the result with pooled estimates. We used multiple worldwide data sources on COVID-19 for every country reporting COVID-19 cases. On the basis of data, we performed random and fixed meta-analyses for CFR of COVID-19 by continents and income according to each individual calendar date. CFR was estimated based on the different geographical regions and levels of income using three models: pooled estimates, fixed- and random-model. In Asia, all three types of CFR initially remained approximately between 2.0% and 3.0%. In the case of pooled estimates and the fixed model results, CFR increased to 4.0%, by then gradually decreasing, while in the case of random-model, CFR remained under 2.0%. Similarly, in Europe, initially, the two types of CFR peaked at 9.0% and 10.0%, respectively. The random-model results showed an increase near 5.0%. In high-income countries, pooled estimates and fixed-model showed gradually increasing trends with a final pooled estimates and random-model reached about 8.0% and 4.0%, respectively. In middle-income, the pooled estimates and fixed-model have gradually increased reaching up to 4.5%. in low-income countries, CFRs remained similar between 1.5% and 3.0%. Our study emphasizes that COVID-19 CFR is not a fixed or static value. Rather, it is a dynamic estimate that changes with time, population, socioeconomic factors, and the mitigatory efforts of individual countries.
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Project description:Background: The novel Severe Acute Respiratory Syndrome Coronavirus-2 has led to a global pandemic in which case fatality rate (CFR) has varied from country to country. This study aims to identify factors that may explain the variation in CFR across countries. Methods: We identified 24 potential risk factors affecting CFR. For all countries with over 5000 reported COVID-19 cases, we used country-specific datasets from the WHO, the OECD, and the United Nations to quantify each of these factors. We examined univariable relationships of each variable with CFR, as well as correlations among predictors and potential interaction terms. Our final multivariable negative binomial model included univariable predictors of significance and all significant interaction terms. Results: Across the 39 countries under consideration, our model shows COVID-19 case fatality rate was best predicted by time to implementation of social distancing measures, hospital beds per 1000 individuals, percent population over 70 years, CT scanners per 1 million individuals, and (in countries with high population density) smoking prevalence. Conclusion: Our model predicted an increased CFR for countries that waited over 14 days to implement social distancing interventions after the 100th reported case. Smoking prevalence and percentage population over the age of 70 years were also associated with higher CFR. Hospital beds per 1000 and CT scanners per million were identified as possible protective factors associated with decreased CFR.
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Project description:The True Infection Rate (TIR) in the whole population of each country and the Infection Fatality Rate (IFR) for coronavirus disease 2019 (COVID-19) are unknown although they are important parameters. We devised a simple method to infer TIR and IFR based on the open data. The prevalence rate of the Polymerase Chain Reaction (PCR) tests among the population (Examination Rate; ER) and the positive rate of PCR tests (Infection Rate; IR) for 66 countries were picked up at a website 5 times from April 10th to June 13th, 2020, and the trajectory of each country was drawn over the IR vs. ER plot. IR and ER showed a strong negative correlation for some countries, and TIR was estimated by extrapolating the regression line when the correlation coefficient was between -0.99 and -1. True/Identified Case Ratio (TICR) and IFR were also calculated using the estimated TIR. The estimated TIR well coincided with local antibody surveys. Estimated IFR took on a wide range of values up to 10%: generally high in the Western countries. The estimated IFR of Singapore was very low (0.018%), which may be related to the reported gene mutation causing the attenuation of the viral virulence.
| S-EPMC8704731 | biostudies-literature
Project description:As of 1 November 2020, estimated case-fatality rates associated with coronavirus disease 2019 are not uniformly patterned across the world and differ substantially in magnitude. Given the global spatial heterogeneity in case-fatality rates, we applied the Blinder-Oaxaca regression decomposition technique to identify how putative sociodemographic, structural, and environmental sources influence variation in case-fatality rates. We show that compositional and associational differences in country-level risk factors explain a substantial proportion of the coronavirus disease 2019-related case-fatality rate gap across nations. Asian countries fair better vis-à-vis case-fatality rate differences mainly due to variation in returns to sociodemographic, structural, and environmental sources among their citizens, relative to those who share similar attributes but live in Europe or North America. The variation in case-fatality rate is driven by Asian populations being better able to buffer the harmful effects of the very risk factors purported to exacerbate the risk of coronavirus disease 2019-related death. The dire circumstances in which we find ourselves demand better understanding of how preexisting conditions across countries contribute to observed disparities in case-fatality rates.
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| S-EPMC7484610 | biostudies-literature
Project description:Since the 2009 influenza pandemic, the Netherlands has used a weekly death monitoring system to estimate deaths in excess of expectations. We present estimates of excess deaths during the ongoing coronavirus disease (COVID-19) epidemic and 10 previous influenza epidemics. Excess deaths per influenza epidemic averaged 4,000. The estimated 9,554 excess deaths (41% in excess) during the COVID-19 epidemic weeks 12-19 of 2020 appeared comparable to the 9,373 excess deaths (18%) during the severe influenza epidemic of 2017-18. However, these deaths occurred in a shorter time, had a higher peak, and were mitigated by nonpharmaceutical control measures. Excess deaths were 1.8-fold higher than reported laboratory-confirmed COVID-19 deaths (5,449). Based on excess deaths and preliminary results from seroepidemiologic studies, we estimated the infection-fatality rate to be 1%. Monitoring of excess deaths is crucial for timely estimates of disease burden for influenza and COVID-19. Our data complement laboratory-confirmed COVID-19 death reports and enable comparisons between epidemics.
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Project description:Background: Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne disease with high mortality. However, detailed analysis is lacking to explore the complex effect of sex with age or comorbidities. Methods: A retrospective cohort study was performed among 2,938 SFTS patients entered during 2011-2020 in Xinyang, China. The case fatality rate (CFR) was estimated for their association with sex, age, and comorbidities by an interactive way. The difference of immune response between sex was explored in an age dependent way. Results: An overall CFR of 15.3% (450/2,938) was obtained, which appeared to be higher in males than in females [17.7% vs. 13.6%, adjusted odds ratio (aOR) = 1.24; 95% CI, 1.00-1.53; P = 0.048] and increased dramatically with age (P < 0.001). The associations between sex and SFTS fatal outcome were age-dependent and varied according to the status of comorbidities. The mortality-related risk conferred by older age was more pronounced in males, with aOR (95% CI) to be 5.76 (3.75-8.84) vs. 5.30 (3.54-7.95) in female. Sex-stratified analysis disclosed significant associations between death and comorbidities among female patients (aOR = 1.87, 95% CI: 1.40-2.49; P < 0.001), while none among males. Among females, the significant associations between presence of comorbidity and fatal outcome differed among age groups, with aOR (95% CI) decreased from 2.28 (1.16-4.46) in ≤60 years, to 2.06 (1.34-3.18) in 60-70 years and further to 1.55 (0.97-2.47) in >70 years. Altogether 194 SFTS patients were randomly selected for the test of B cells, natural killer (NK) cells, CD4 cells percentages, and anti-SFTSV IgM antibody level, the results revealed that males >60 years had significantly decreased percentages of B cells, CD4 cells, lower anti-SFTSV IgM antibody titer, and increased level of NK cells than male aged ≤60 years, while none of these age specific differences was observed in the females. This finding underlies the more pronounced age specific difference in CFR among male than female. Conclusions: Males had a significantly higher mortality of SFTS than did females, and more likely to be affected by aging for SFTS mortality. This difference can be explained by the effect from comorbidities and the host immunity. It is essential to take a sex- and age-based approach to SFTS treatment and management.
| S-EPMC8552034 | biostudies-literature
Project description:ObjectiveSince the outbreak of the coronavirus disease 2019 (COVID-19) in December of 2019 in China, estimating the pandemic's case fatality rate (CFR) has been the focus and interest of many stakeholders. In this manuscript, we prove that the method of using the cumulative CFR is static and does not reflect the trend according to the daily change per unit of time.MethodsA proportion meta-analysis was carried out on the CFR in every country reporting COVID-19 cases. Based on these results, we performed a meta-analysis for a global COVID-19 CFR. Each analysis was performed using two different calculations of CFR: according to the calendar date and according to the days since the outbreak of the first confirmed case. We thus explored an innovative and original calculation of CFR, concurrently based on the date of the first confirmed case as well as on a daily basis.ResultsFor the first time, we showed that using meta-analyses according to the calendar date and days since the outbreak of the first confirmed case, were different.ConclusionWe propose that a CFR according to days since the outbreak of the first confirmed case might be a better predictor of the current CFR of COVID-19 and its kinetics.
| S-EPMC7462556 | biostudies-literature
Project description:BackgroundZhejiang Province is one of the five provinces in China that had the highest incidence of novel coronavirus disease (COVID-19). Zhejiang, ranked fourth highest in COVID-19 incidence, is located in the Yangtze River Delta region of southeast China. This study was undertaken to identify the space-time characteristics of COVID-19 in Zhejiang.MethodsData on COVID-19 cases in Zhejiang Province from January to July 2020 were obtained from this network system. Individual information on cases and deaths was imported, and surveillance information, including demographic characteristics and geographic and temporal distributions, was computed by the system. The Knox test was used to identify possible space-time interactions to test whether cases that are close in distance were also close in time. Network analysis was performed to determine the relationship among the cases in a transmission community and to try to identify the key nodes.ResultsIn total, 1475 COVID-19 cases and 1 fatal case were reported from January to July 2020 in Zhejiang Province, China. Most of the cases occurred before February 15th, which accounted for 90.10%. The imported cases increased and became the main risk in Zhejiang Province after February 2020. The risk areas showed strong heterogeneity according to the Knox test. The areas at short distances within 1 kilometer and at brief periods within 5 days presented relatively high risk. The numbers of subcommunities for the four clusters were 12, 9, 6 and 4. There was obvious heterogeneity in the modularity of subcommunities. The maximum values of the node centrality for the four clusters were 2.9474, 4.3706, 4.1080 and 2.7500.ConclusionsCOVID-19 was brought under control over a short period in Zhejiang Province. Imported infections from outside of mainland China then became a new challenge. The effects of spatiotemporal interaction exhibited interval heterogeneity. The characteristics of transmission showed short range and short term risks. The importance to the cluster of each case was detected, and the key patients were identified. It is suggested that we should focus on key patients in complex conditions and in situations with limited control resources.
| S-EPMC8448332 | biostudies-literature