Can we start to ignore the SARS-CoV-2 disease?
Nesteruk, I.
Show abstract
Current WHO reports claim a decline in COVID-19 testing. Many countries are reporting no new infections. In particular, USA, China and Japan have registered no cases and COVID-19 related deaths since May 15, 2023. To discuss consequences of ignoring SARS-CoV-2 infection, we compare endemic characteristics of the disease in 2023 with ones estimated before using 2022 datasets. The accumulated numbers of cases and deaths reported to WHO by 10 most infected countries and global figures were used to calculate the average daily numbers of cases and deaths per capita (DCC and DDC) and case fatality rates (CFR) for two periods in 2023. The average values of daily deaths per million still vary between 0.12 and 0.41. It means that annual global number of COVID-19 related deaths is still approximately twice higher than the seasonal influenza mortality. Increase of CFR values in 2023 show that SARS-CoV-2 infection is still dangerous despite of increasing the vaccination level. Very low CFR figures in South Korea and very high ones in the UK 4 need further investigations.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Prediction of Daily New COVID-19 Cases - Difficulties and Possible Solutions 97%
- Prediction and control of COVID-19 infection based on a hybrid intelligent model 96%
- Explaining the Effective Reproduction Number of COVID-19 through Mobility and Enterprise Statistics: Evidence from the First Wave in Japan 96%
Similar papers in this journal
- A new, simple method of describing COVID-19 trajectory and dynamics in any country based on Johnson Cumulative Distribution Function fitting 96%
- Distribution of Incubation Period of COVID-19 in the Canadian Context: Modeling and Computational Study 95%
- Model Based Estimation of the SARS-CoV-2 Immunization Level in Austria and Consequences for Herd Immunity Effects 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.