Figure 1. Time series plots of daily confirmed COVID-19 cases (in
black), COVID-19 deaths (in red), and influenza positive cases in
2015-2019 (in light blue) and in 2020 (in dark blue).
We obtained the daily confirmations of COVID-19 cases and deaths for 216
countries or regions, during February 2020 - August 2020, and weekly
influenza confirmations during 2015 to current week, from World Health
Organization [1,2]. We showed data of four countries (two from
Europe and two from Asia which caught a lot of attention in the early
phase of the pandemic) in Figure 1. Research of other 49 countries or
regions are listed in the supplementary. The time series (in common log
scale on vertical axis) of confirmed cases showed two waves. Based on
this observation, we divided the transmission of the disease into two
phases: Phase I before June 1 and Phase II after June 1 for confirmed
cases; and Phase I before June 10 and Phase II after June 10 for deaths.
For deaths, we choose the truncated time ten days later to account for
the delay between confirmation and deaths [3]. We compared the raw
case fatality rate (CFR) of Phase I and Phase II for all countries or
regions.
In our supplementary data in the appendix, for each country, we break
down the data for Phase I or Phase II. The column “case_pre” is the
total of confirmed cases before June 1 and the column “case_post” is
the total of confirmed cases after June 1 up to July 26. Accordingly,
the column of “death_pre” is the infection death before June 10 and
the column “death_post” is the infection death after June 10 up to
August 6. We define the raw case fatality rates (CFR) as\(r_{1}\)=\(\frac{death\_pre}{case\_pre}\) and\(r_{2}\)=\(\frac{death\_post}{case\_post}\). Then the change in CFR
is reduction= \(\frac{r_{1}-r_{2}}{r_{1}}\). Based on our analysis,
among all 53 hardest-hit countries or regions (supplementary Table 1),
43 of them had an apparent reduction in CFR. Only ten remaining
countries or regions had an increase in CFR (negative reduction). The
decrease in the CFR might indicate the severity of the global pandemic
is becoming better. The potential reason for such decrease is worth
further investigation. We propose the following hypotheses that could
contribute to the decrease of CFR in the second phase. First, the
apparent higher CFR in the first phase could be a harvest effect, namely
a large number of elderly and individual with health conditions (the
group at risk) likely died in the first phase, especially in these
countries with a high infection rate, and this risk group run low in the
second phase. If a country or region (such as Hong Kong) was spared from
the first phase, of course it is not surprising to see an increase in
CFR. Second, the age structure of infected changed due to a variety of
reasons, e.g. social movement in many countries might involve more
healthier young individuals. Third, the virus might evolve such that
young health adults become more susceptible, thus lead to a reduced CFR.
Forth, favourable climate might lead to reduced CFR (e.g. warmer weather
in north hemisphere and improved air quality due to city lockdown
[4-6]). Last but not least, improved timely treatment and enhanced
massive testing could reduce the deaths and increase the number of
cases, thus a reduced CFR in the second phase.
We show time series plots of eight countries in supplementary figure,
where only Iran faces an increase in the raw CFR and a table summarizes
results of 53 countries or regions. The weekly influenza laboratory
confirmations for the previous five years may be used as a proxy of the
weather, since it is well known that influenza seasonality is driven by
temperature and humidity. Thus we may wonder whether favourable weather
may contribute to a reduce CFR for COVID-19. The sharp drop in influenza
cases in 2020 (dark bold curve), compared to previous years, may be due
to social distancing and possible interference with COVID-10 infection.
Thus it is informative to compare the COVID-19 and influenza in these
plots. Individual data or age grouped data are needed to further clarify
the phenomenon. The finding is nevertheless of significance to inform
public and for policy making.