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\begin{document}
\title{Case fatality and recovery rates of COVID-19 outbreak: Comparison
between high, middle- and low-income countries}
\author[1]{Ashis Talukder}%
\author[2,2]{Sheikh Mohammed Shariful Islam}%
\affil[1]{Khulna University}%
\affil[2]{Deakin University}%
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\date{\today}
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\begin{abstract}
The number of cases and mortality from COVID-19 is changing rapidly
worldwide. We analyzed the case fatality rate (CFR) and recovery rate
(RR) from COVID-19 using recent data. By using the information of CFR
and RR, we made a comparison between high and middle or low-income
countries to understand the current global outbreak. We further ranked
the countries based on their CFR and RR from higher to lower.%
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\textbf{Title Page}
\textbf{Case fatality and recovery rates of COVID-19 outbreak:
Comparison between high, middle- and low-income countries}
\textbf{Running Head: COVID-19 case fatality and recovery rates}
\textbf{Ashis Talukder\textsuperscript{1}*, Sheikh Mohammed Shariful
Islam\textsuperscript{2}}
\textsuperscript{1} Statistics Discipline, Khulna University,
Khulna-9208, Bangladesh.
\textsuperscript{2} Institute for Physical Activity and Nutrition,
Deakin University, Melbourne, VIC 3125, Australia.
\textsuperscript{\textbf{*}}\textbf{Corresponding Author:} Ashis
Talukder;\textbf{E-mail address:} ashistalukder3168@ku.ac.bd
\textbf{Detailed Address of Corresponding Author:}
Ashis Talukder
Assistant Professor
Statistics Discipline
Khulna University, Khulna-9208, Bangladesh
E-mail: \emph{ashistalukder3168@ku.ac.bd}
Contact no.: +8801772063507
\textbf{Case fatality and recovery rates of COVID-19 outbreak:
Comparison between high, middle- and low-income countries}
The number of cases and mortality from COVID-19 is changing rapidly
worldwide. We analyzed the case fatality rate (CFR) and recovery rate
(RR) from COVID-19 using recent data. By using the information of CFR
and RR, we made a comparison between high and middle or low-income
countries to understand the current global outbreak. We further ranked
the countries based on their CFR and RR from higher to lower.
We considered 38 countries reporting at least 100 deaths on
12\textsuperscript{th} April 2020 by worldometer {[}1{]}. A Poisson
distribution model (a probability distribution widely used to count
data) was considered to estimate the overall case fatality and recovery
rate from COVID-19 using the following formula:
\(\text{P\ }\left(x;\mu\right)=\frac{e^{-\mu}\mu^{x}}{x!}\);\(x=0,1,2,\ldots\ldots.\)
Here, \(x\) represents the number of deaths or recovery due
to COVID-19 and \(\mu\) represents the fatality or recovery
rate due to the disease. We used the following formula to calculate CFR
and RR:
\begin{equation}
CFR=\frac{Number\ of\ deaths\ due\ to\ COVID-19}{Total\ number\ of\ confirmed\ cases\ of\ COVID-19}\nonumber \\
\end{equation}\begin{equation}
RR=\frac{Number\ of\ patients\ recovered\ from\ COVID-19}{Total\ number\ of\ confirmed\ cases\ of\ COVID-19}\nonumber \\
\end{equation}
The calculated rates and estimated value of the overall death and
recovery rates with 95\% confidence interval are shown in Supplementary
Table 1 (see, supplementary material). Results show that CFR was
relatively higher for Algeria (15.07\%) compared to other countries. The
CFR for Italy, UK, Belgium, France, Netherland, and Spain was more than
10\%. Among these 38 countries, Russia (0.86\%) had the lowest CFR.
On the other hand, the recovery rate (RR) from COVID-19 was much higher
in China (94.43\%) indicating that in China, people were recovering
quickly from COVID-19 than other countries. Apart from China, only five
countries (South Korea, Iran, Switzerland, Germany and Austria) showed
RR more than 45\%. RR was relatively higher than CFR in most of the
countries, which is encouraging (see, Figure 1). However, ten countries
including Norway, Portugal, Ireland, Dominican Republic, Brazil,
Philippines, Sweden, Indonesia, Netherland and the UK, the CFR was
higher than RR (see, Figure 1). Among these ten countries, Ireland, the
UK, Norway, Brazil and Netherland had the worst RR (less than one)
compared to other countries. Moreover, the estimated death rate and
recovery rate suggest that on an average, for every 100 confirmed
COVID-19 patients, more than five patients might die
{[}\(estimate=5.86;95\%\ CI\ (5.85,\ 5.88)\){]} and more than 20 patients will recover
{[}\(estimate=20.22;95\%\ CI\ (20.19,\ 20.25)\){]} from COVID-19.
Although the number of cases and deaths were higher in high-income
countries, the case fatality rate was relatively high in most of the
low-and middle-income countries (see, Figure 2). A possible reason for
this difference may be the lack of national and health systems
preparedness, lack of awareness about COVID-19 among the people and poor
health facilities and infrastructures in these countries. Furthermore,
it is a possibility that many cases and death remained undetected in
these low-income countries due to lack of testing and diagnosis.
Therefore, concerned authorities in low-and middle-income countries
should consider performing more tests to correctly identify the COVID-19
patients and provide better symptomatic treatments to facilitate
recovery since there exist no effective vaccines or medications for this
disease {[}2{]}. Also, social isolation and lockdown policies may play a
crucial role to reduce the current fatalities due to COVID-19 in
low-and-middle-income countries like it did in some high-income
countries.
\textbf{Funding Information}
No fund has been received
\textbf{Declaration of competing interest}
The author has no conflict of interest to disclosure
\textbf{References}
\begin{enumerate}
\tightlist
\item
Worldometer. Available on: https://www.worldometers.info/coronavirus/
\item
Wang D, Hu B, Hu C, et al. Clinical characteristics of 138
hospitalized patients with 2019 novel coronavirus-infected pneumonia
in Wuhan, China. JAMA. 2020; 323: 1061.
\end{enumerate}\selectlanguage{english}
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