National case fatality rates of the COVID-19 pandemic

Abstract

Objectives The case fatality rate (CFR) of Coronavirus disease 2019 (COVID-19) varies significantly between countries. We aimed to describe the associations of health indicators with the national CFRs of COVID-19. Methods We identified health indicators for each country potentially associated with the national CFRs of COVID-19. We extracted data for 18 variables from international administrative data sources for 34 member countries of the Organization for Economic Co-operation and Development (OECD). We excluded the collinear variables and examined the 16 variables in multivariable analysis. A dynamic web-based model was developed to analyse and display the associations for the CFRs of COVID-19. We followed the Guideline for Accurate and Transparent Health Estimates Reporting (GATHER). Results In multivariable analysis, the variables significantly associated with the increased CFRs were percent of obesity in ages >18 years ( β = 3.26, 95% CI = [1.20, 5.33], p = 0.003), tuberculosis incidence ( β = 3.15, 95% CI = [1.09, 5.22], p = 0.004), duration (days) since first death due to COVID-19 ( β = 2.89, 95% CI = [0.83, 4.96], p = 0.008), median age ( β = 2.83, 95% CI = [0.76, 4.89], p = 0.009). The COVID-19 test rate ( β = -3.54, 95% CI = [-5.60, -1.47], p = 0.002), hospital bed density ( β = -2.47, 95% CI = [-4.54, -0.41], p = 0.021), and rural population ratio ( β = -2.19, 95% CI = [-4.25, -0.13], p = 0.039) decreased the CFR. Conclusions The pandemic hits the population dense cities. Available hospital beds should be increased. Test capacity should be increased to enable more effective diagnostic tests. Older patients, and patients with obesity, and their caregivers should be warned about a potentially increased risk.

Human cell receptors: potential drug targets to combat COVID-19

“…Unlike SARS-CoV and SARS-CoV-2, the MERS-CoV entry inside human cells has been confirmed by a crystal structure of complex RBD of MERS-CoV and DPP4 (Petrosillo et al 2020 ; Wang et al 2013 , 2014 ; Tai et al 2020 ). Further, the MERS-CoV’s RBD has two subdomains: a core that is highly similar to the RBD of SARS-CoV (Wang et al 2013 ), and a receptor-binding subdomain, which associates with the DPP4 β-propeller.…”

“…Also, HKU4 and HKU5 are bat coronaviruses belonging to betacoronaviruses (Wang et al 2014 ). Another bat SARS-like coronavirus, SL-CoV-RaTG13 (Zhou et al 2020a ) (betacoronavirus (Malaiyan et al 2020 )) is a distinct clade from MERS-CoV (Petrosillo et al 2020 ; Zhou et al 2020a ; Malaiyan et al 2020 ). Nevertheless, the SARS-CoV-2 shares a close resemblance to SL-CoV-RaTG13 (sequence identity 96%) compared to SARS-CoV (sequence identity 79%) and MERS-CoV (sequence identity 50%) (Kim et al 2020 ; Lu et al 2020 ; Zhou et al 2020a ).…”

“…The novel disease COVID-19 caused by SARS-CoV-2 has recently been announced pandemic by WHO (Xu et al 2020 ). The virus has been spreading with epidemic features from Wuhan of China to other Asian countries, with cases now reported worldwide (Petrosillo et al 2020 ). Initially, the virus was represented as 2019-nCoV.…”

“…Initially called disease-X, it was later named COVID-19 by WHO (Liu et al 2020a ). Although the casualty rate of COVID-19 is 2.3%, which is lesser than the SARS-CoV infection that causes SARS (9.5%), and much lower than the MERS-CoV infection that causes MERS (34.4%), while its clinical features are more related to SARS (Petrosillo et al 2020 , 2020 ). Phylogenetically, the SARS-CoV-2 is more closely related to SARS-CoV (sequence identity 79%) than to MERS-CoV (sequence identity 50%) (Kim et al 2020 ; Lu et al 2020 ).…”

Prophylactic use of Hydroxychloroquine among Physicians working in Pandemic Hospitals

“…Older age and having chronic diseases are considered as well known risk factors for COVID-19 [11]. In our study, older age and having any comorbidities were associated with increased HQN use (Table 3).…”