Emergence of novel SARS-CoV-2 variants keeps slowing down

Abstract Background Although COVID-19 pandemic has no longer been classified as an international public health emergency of concern after May 2023, multiple variants with different characteristics keep emerging. Given the complex spatial-temporal characteristics of epidemics, responding to potential changes in variants is a significant public health challenge. Serotypes are defined as unique variants within specific immune response characteristics, which are used in the study of various pathogens. The sero-epidemiological features of COVID-19 may offer new insight into public health. Methods Based on the global SARS-CoV-2 genome deposition data in Our World in Data (OWID) based on GISAID from March 1, 2021 to May 3, 2024, we analyzed the epidemic features of different variants based on the serotype concept and combined with cross-sectional studies. Results In the dataset comprising variants from 58 countries or regions with complete information, we calculated the median duration times of epidemic, the median epidemic peak times for Serotypes Ⅱ-Ⅴ and the median alternation times of epidemic for Serotypes I-Ⅱ to Ⅴ-Ⅵ respectively. There are linear relationships for these time period between the epidemics of Serotypes Ⅱ, Ⅲ, Ⅳ and Ⅴ, except the longer duration time for Serotype I. By constructing a simple linear regression and curve regression equation, the emerging of a new serotype can be predicted with the time around 2025, or even later. Conclusion The gradually-increased prevalence periods for SARS-CoV-2 serotypes except Serotype I may suggest a slowing down mutation rate. Understanding the epidemic time of different serotypes can provide insight into the surveillance and forecasting of COVID-19.

Authors

Institutions

Publication Details

Journal
BMC Public Health
Published
2026-08-21
DOI
https://doi.org/10.1186/s12889-026-28818-8
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Emergence of novel SARS-CoV-2 variants keeps slowing down

Kaida Ning, Jiayi Liu, George F. Gao, Peipei Guo et al.
BMC Public Health
SARS-CoV-2 and COVID-19 Research
article

Emergence of novel SARS-CoV-2 variants keeps slowing down

Kaida Ning, Jiayi Liu, George F. Gao, Peipei Guo, Xinxue Liu, Jiaxin Li, Jiahui Si, Jiayu Sang, Jiani Zhang, Wei Ma, Xin Sun, Zhuoran Huang
article en

Abstract

Abstract Background Although COVID-19 pandemic has no longer been classified as an international public health emergency of concern after May 2023, multiple variants with different characteristics keep emerging. Given the complex spatial-temporal characteristics of epidemics, responding to potential changes in variants is a significant public health challenge. Serotypes are defined as unique variants within specific immune response characteristics, which are used in the study of various pathogens. The sero-epidemiological features of COVID-19 may offer new insight into public health. Methods Based on the global SARS-CoV-2 genome deposition data in Our World in Data (OWID) based on GISAID from March 1, 2021 to May 3, 2024, we analyzed the epidemic features of different variants based on the serotype concept and combined with cross-sectional studies. Results In the dataset comprising variants from 58 countries or regions with complete information, we calculated the median duration times of epidemic, the median epidemic peak times for Serotypes Ⅱ-Ⅴ and the median alternation times of epidemic for Serotypes I-Ⅱ to Ⅴ-Ⅵ respectively. There are linear relationships for these time period between the epidemics of Serotypes Ⅱ, Ⅲ, Ⅳ and Ⅴ, except the longer duration time for Serotype I. By constructing a simple linear regression and curve regression equation, the emerging of a new serotype can be predicted with the time around 2025, or even later. Conclusion The gradually-increased prevalence periods for SARS-CoV-2 serotypes except Serotype I may suggest a slowing down mutation rate. Understanding the epidemic time of different serotypes can provide insight into the surveillance and forecasting of COVID-19.

BMC Public Health
ActionAid (US), Shandong University (CN), Chinese Academy of Sciences (CN), University of Oxford (GB), Institute of Microbiology (CN), Peng Cheng Laboratory (CN), Columbia University (US)
National Natural Science Foundation of China, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 88%
SARS-CoV-2 and COVID-19 Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.