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\begin{document}

\title{Differences in Case-Fatality-Rate of Emerging SARS-CoV-2 Variants}



\author[1]{Jing Liu}%
\author[1]{Haozhen Wei}%
\author[1]{Daihai He}%
\affil[1]{The Hong Kong Polytechnic University}%


\vspace{-1em}



  
  \date{June 14, 2024}


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\selectlanguage{english}
\begin{abstract}
Variants of Severe-Acute-Respiratory-Syndrome Coronavirus-2 (SARS-CoV-2)
has caused tremendous impact globally. It has been widely reported that
the Omicron (B.1.1.529) variant is less deadly than the Delta
(B.1.617.2) variant, presumably due to immunity from vaccination and
previous infection. When measuring the severity of a variant,
Case-Fatality-Rate (CFR) is often estimated. The purpose of this work is
to calculate the change in CFR of different variants over time from a
large number of countries/regions since the start of the pandemic in
2020.%
\end{abstract}%



\sloppy


Differences in Case-Fatality-Rate of Emerging SARS-CoV-2 Variants

Jing Liu\textsuperscript{1}, Haozhen Wei\textsuperscript{1}, Daihai
He\textsuperscript{1,2,+}

\textsuperscript{1} Department of Applied Mathematics, Hong Kong
Polytechnic University, Hong Kong, China

\textsuperscript{2} Research Institute for Future Food, The Hong Kong
Polytechnic University, Hong Kong, China

+ Corresponding author. Email: daihai.he@polyu.edu.hk (DH)

\textbf{Abstract}

Variants of Severe-Acute-Respiratory-Syndrome Coronavirus-2 (SARS-CoV-2)
has caused tremendous impact globally. It has been widely reported that
the Omicron (B.1.1.529) variant is less deadly than the Delta
(B.1.617.2) variant, presumably due to immunity from vaccination and
previous infection. When measuring the severity of a variant,
Case-Fatality-Rate (CFR) is often estimated. The purpose of this work is
to calculate the change in CFR of different variants over time from a
large number of countries/regions since the start of the pandemic in
2020.

\textbf{Keywords:} COVID-19, Omicron variant, Delta variant, CFR

\textbf{Background}

The Coronavirus 2019 (COVID-19) pandemic, caused by the Severe Acute
Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), hit the humankind
tremendously with 528,996,258 reported cases and 6,287,786 reported
deaths by June,2022(Coronaviridae Study Group of the International
Committee on Taxonomy of Viruses, 2020; Worldometers, 2022). The rapid
evaluation of the viruses led to variants with high transmissibility and
high immune evasion ability and posed challenges for prevention and
control (CDC, 2022). Among the new variants, the Delta variant
(B.1.617.2) was first identified in December, 2020 (Yang\&Jeffrey, 2021)
and classified by the World Health Organization (WHO) as Variant of
Concern (VOC) on June, 2021, updated as Variant Being Monitored (VBM) on
April, 2022(CDC, 2022). The Omicron variant (B.1.1.529) was first
detected in specimens collected on November, 2021, and classified as a
Variant of Concern (VOC)(CDC, 2021). Several subvariants of Omicron
variant has been reported so far. Previous studies on the
case-fatality-ratio (CFR) of different variants were conducted in
individual countries. Large-scale comparison across multiple countries
is missing. The CFR is an important indicator of disease severity. Many
factors may affect the estimates. Infection attack rate (proportion of
population being infected) with previous variants, vaccination coverage,
age structure of the population and the medical system preparedness may
affect the CFR in different population/locations. In this work, we
combine the reported cases and deaths and variant proportion over time
in 50 locations to calculate the raw CFR for 7 variants (or
subvariants), thus to get a large-scale picture of the changing pattern
of the severity of SARS-CoV-2.

The Omicron variant spreads faster than the Delta variant due to the
combined effects of increased transmissibility and immune evasion
ability. In South Africa, the proportion of patients with Omicron
infection presenting to emergency departments has fallen to half its
previous level, and the proportion of Omicron patients presenting with
acute respiratory conditions and requiring oxygen therapy and mechanical
ventilation has fallen dramatically(Maslo et al., 2022).

In United States, the number of deaths in the Omicron wave (analyzed
from December 15, 2021 to March 15, 2022) was very similar to that seen
in the Delta wave (analyzed from July 15, 2021 to November 15, 2021).
However, the number of confirmed cumulative cases during this period was
twofold higher with Delta. The CFR of Omicron variant is about half that
of Delta variant in the both US and South Africa (Sigal et~al., 2022).

\textbf{CFR of variants across 51 locations}

Here we extend the comparison to all previous VOCs in 51
counties/regions. We use reported death divided by reported cases in
30-day sliding window with a two-week shift between reported death and
reported cases.

\begin{equation}
\text{Case\ Fatality\ Ratio}\left(CFR\ in\%\right)=\frac{Number\ of\ deaths\ from\ disease\ in\ the\ past\ 30\ days}{Number\ of\ confirmed\ cases\ of\ disease\ in\ the\ past\ 15\ to\ 45\ days}\times 100\%\nonumber \\
 \end{equation}

Based on the biweekly variant proportion data(Hodcroft, 2021; Hannah
Ritchie et al., 2020), we determine the dominant time interval for each
variant in each location when the proportion of a variant is above 50\%
among all samples processed. Namely the raw CFR in a time interval when
the proportion of variant is above 50\% is assigned as the CFR for the
variant in that location. We calculated the mean CFR values for each
variant in its dominant time interval in each location. Figure 1
summarized the mean CFR for each variant across 51 locations.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1. The summary of the mean case-fatality ratio (CFR) during its
dominant time interval in 51 locations for eight variants or
subvariants.

\textbf{Age stratified CFR}

In South Africa, the CFR during Omicron variant dominant time interval
(November 21, 2021, to January 22, 2022) was substantially lower than
that during Delta variant dominant time interval (May 9 to September 18,
2021), for 20+ age groups (see Table 1)(Jassat et al, 2022). This could
be due to implementation of vaccination among adults and infection
induced immunity across all ages.

\textbf{Table} 1. The summary of case-fatality ratio (CFR) of Delta
variant and Omicron variant among different age groups in South Africa.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
CFR & Delta & Omicron & Relative difference\tabularnewline
\midrule
\endhead
All ages & 2.60\% & 0.78\% & 70\%\tabularnewline
Age \textless{}5 years & 0.57\% & 0.48\% & 15.8\%\tabularnewline
Age 5--19 years & 0.06\% & 0.09\% & -50\%\tabularnewline
Age 20--39 years & 0.45\% & 0.24\% & 46.7\%\tabularnewline
Age 40--59 years & 2.54\% & 0.64\% & 74.4\%\tabularnewline
Age [?]60 years & 11.71\% & 2.38\% & 79.7\%\tabularnewline
\bottomrule
\end{longtable}

\par\null

In Table 1, the relative difference is defined as\((1-\frac{CFR\_omicron}{CFR\_delta})\%\). For
all ages, the CFR of Delta variant is more than three-fold of the CFR of
Omicron for overall age group and 40+ ages groups. The 5-19 age group
has the lowest CFR for both variants.

Italy has a high proportion of elderly people (\textgreater{}65 age
accounting 23\% of the population) in 2019, which could have led to a
higher CFR compared to other countries. Among 70-79 age group, the CFR
is about 12.8\% in Italy and 8.0\% in China; among 80+ age group, the
CFR is about 20.2\% in Italy and 14.8\% in China, in early 2020(Onder et
al., 2020). 86\% of patients in the Washington ICU have underlying
chronic conditions such as kidney disease and heart failure(Arentz et
al., 2020). Population age structure and prevalence of comorbidity
influence CFR.

\textbf{Impact of Vaccination}

Zhao et al showed that, in the United Kingdom during May and June 2021,
Delta variant had a smaller CFR than pre-variant and the CFR of
pre-Delta variant dropped substantially while the vaccine coverage
increased and the drop of the CFR of Delta variant is less evident
(probably due to short study period)(Zhao et al., 2021). In the United
States, Johnson et al compared the CFR among unvaccinated and fully
vaccinated individuals in 25 US jurisdictions and the vaccine efficacy
substantially dropped over time (see Table 2) (Johnson et~al., 2021).

\textbf{Table} 2. The summary of case-fatality ratio (CFR) of Delta
variant and Omicron variant in unvaccinated people and fully vaccinated
people in United States.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Time & CFR among Unvaccinated & CFR among Fully vaccinated & Vaccine
Efficacy in reduction CFR\tabularnewline
\midrule
\endhead
Pre-Delta (2021, 4-5) & 1.05\% & 0.10\% & 90.5\%\tabularnewline
Delta emergence (2021, 6) & 1.37\% & 0.24\% & 82.5\%\tabularnewline
Delta predominance (2021, 7-11) & 1.22\% & 0.32\% &
73.8\%\tabularnewline
Omicron emergence (2021, 12) & 0.11\% & 0.03\% & 72.7\%\tabularnewline
\bottomrule
\end{longtable}

\par\null

The vaccine efficacy (VE) is defined as (\(1-\frac{CFR\_vaccinated}{CFR\_unvaccinated})\%\). The VE drop
substantially over time, due to a combined effect of natural waning of
immune protection and immune evasion of Delta and Omicron variant.

\textbf{Limitation}

The work utilized bi-weekly variant sequencing data and reported deaths
and cases. The under reporting of COVID-19 deaths and cases will impact
the estimate of CFR. The CFR is an overestimate of the true
infection-fatality-rate. If the reporting is consistent, the CFR across
variants should be a fair comparison.

\textbf{Conclusion}

In this work, we compared the CFR for seven variants across 51
locations. We showed that the CFR dropped over time, presumably due to
vaccine-induced immune and infection induced immune. The drop from Delta
variant to Omicron variant is substantial and the difference between
subvariants of Omicron is not evident.

\textbf{Ethics approval and consent to participate}

The data used in this study were collected originally via the public
domains, and thus neither ethical approval nor individual consent was
applicable.

\textbf{Availability of materials}

Data are publicly available online.

\textbf{Consent for publication}

Not applicable.

\textbf{Funding}

We were supported by the Collaborative Research Fund (Grant Number HKU
C7123-20G) of the Research Grants Council (RGC) of Hong Kong, China.

\textbf{Acknowledgments}

None.

\textbf{Disclaimer}

The funding agencies had no role in the design and conduct of the study;
collection, management, analysis, and interpretation of the data;
preparation, review, or approval of the manuscript; or decision to
submit the manuscript for publication.

\textbf{Conflict of interests}

All authors have no conflict of interest.

\textbf{Author's contributions}

DH and JL conceived the study, carried out the analysis and drafted the
manuscript. All authors discussed the results, and revised the
manuscript, and approved it for publishing.

\textbf{References}

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