Global COVID-19 fatality analysis reveals Hubei-like countries potentially with severe outbreaks.
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ABSTRACT:
SUBMITTER: Lv B
PROVIDER: S-EPMC7194645 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The crude case fatality rate (CFR), because of the calculation method, is the most accurate when the pandemic is over since there is a possibility of the delay between disease onset and outcomes. Adjusted crude CFR measures can better explain the pandemic situation by improving the CFR estimation. However, no study has thoroughly investigated the COVID-19 adjusted CFR of the South Asian Association For Regional Cooperation (SAARC) countries. This study estimated both survival interval and underreporting adjusted CFR of COVID-19 for these countries. Moreover, we assessed the crude CFR between genders and across age groups and observed the CFR changes due to the imposition of fees on COVID-19 tests in Bangladesh. Using the daily records up to October 9, we implemented a statistical method to remove the delay between disease onset and outcome bias, and due to asymptomatic or mild symptomatic cases, reporting rates lower than 50% (95% CI: 10%-50%) bias in crude CFR. We found that Afghanistan had the highest CFR, followed by Pakistan, India, Bangladesh, Nepal, Maldives, and Sri Lanka. Our estimated crude CFR varied from 3.708% to 0.290%, survival interval adjusted CFR varied from 3.767% to 0.296% and further underreporting adjusted CFR varied from 1.096% to 0.083%. Furthermore, the crude CFRs for men were significantly higher than that of women in Afghanistan (4.034% vs. 2.992%) and Bangladesh (1.739% vs. 1.337%) whereas the opposite was observed in Maldives (0.284% vs. 0.390%), Nepal (0.006% vs. 0.007%), and Pakistan (2.057% vs. 2.080%). Besides, older age groups had higher risks of death. Moreover, crude CFR increased from 1.261% to 1.572% after imposing the COVID-19 test fees in Bangladesh. Therefore, the authorities of countries with higher CFR should be looking for strategic counsel from the countries with lower CFR to equip themselves with the necessary knowledge to combat the pandemic. Moreover, caution is needed to report the CFR.
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Project description:An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19), however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020. We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death probability under specific combinations of key predictors. Among the 21,392 patients, 1,020 (4.77%) died of COVID-19. Multivariable analyses showed that factors, including age (≥60 versus <45 years, hazard ratio [HR] = 7.32; 95% confidence interval [CI], 5.42, 9.89), sex (male versus female, HR = 1.31; 95% CI, 1.15, 1.50), severity of the disease (critical versus mild, HR = 39.98; 95% CI, 29.52, 48.86), comorbidity (HR = 1.40; 95% CI, 1.23, 1.60), highest body temperature (>39°C versus <39°C, HR = 1.28; 95% CI, 1.09, 1.49), white blood cell counts (>10 × 109/L versus (4-10) × 109/L, HR = 1.69; 95% CI, 1.35, 2.13), and lymphocyte counts (<0.8 × 109/L versus (0.8-4) × 109/L, HR = 1.26; 95% CI, 1.06, 1.50) were significantly associated with case fatality of COVID-19 patients. Individuals of an older age, who were male, with comorbidities, and had a critical illness had the highest death probability, with 21%, 36%, 46%, and 54% within 1-4 weeks after the symptom onset. Risk factors, including demographic characteristics, clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19. Our predictive model can provide scientific evidence for a more rational, evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19.
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