Estimated COVID-19 Periodicity and Correlation with SARS-CoV-2 Spike Protein S1 Antigenic Diversity, United States

Emergence of antigenically diverse SARS-CoV-2 variants may be correlated with temporal circulation patterns. We analyzed positive SARS-CoV-2 tests in the United States reported to a national, laboratory-based surveillance network and unique amino acid sequences of the S1 region of the spike protein reported to national genomic surveillance during October 2020-September 2024. We estimated SARS-CoV-2 dominant periodicities using a discrete Fourier transform, described S1 variation using the Simpson diversity index (SDI), and estimated Spearman cross-correlation coefficients between percentage change in SDI and percentage positivity. SARS-CoV-2 activity consistently peaked during July-September and December-February, and dominant periodicities were at weeks 52.2 and 26.1. Percentage positivity and percentage change in SDI were negatively correlated (ρ = -0.30; p<0.001). SARS-CoV-2 peaks occurred in late summer and winter, a pattern likely related to rapid SARS-CoV-2 evolution and cyclical diversity. Monitoring associations between percentage positivity and SDI can help forecast expected surges and optimize prevention and preparedness.

Authors

Publication Details

Journal
Emerging infectious diseases
Published
2025-07-24
DOI
https://doi.org/10.3201/eid3108.250451
Citations
4
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
5.58
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimated COVID-19 Periodicity and Correlation with SARS-CoV-2 Spike Protein S1 Antigenic Diversity, United States

Peter W. Cook, Amber Winn, Benjamin J. Silk, Lakshmi Panagiotakopoulos et al.
4 citations
Emerging infectious diseases
SARS-CoV-2 and COVID-19 Research
5.58
article

Estimated COVID-19 Periodicity and Correlation with SARS-CoV-2 Spike Protein S1 Antigenic Diversity, United States

Peter W. Cook, Amber Winn, Benjamin J. Silk, Lakshmi Panagiotakopoulos, C. Kevin, Clinton R. Paden, Juan E. De Castro, Erica Billig Rose
article en
4 citations

Abstract

Emergence of antigenically diverse SARS-CoV-2 variants may be correlated with temporal circulation patterns. We analyzed positive SARS-CoV-2 tests in the United States reported to a national, laboratory-based surveillance network and unique amino acid sequences of the S1 region of the spike protein reported to national genomic surveillance during October 2020-September 2024. We estimated SARS-CoV-2 dominant periodicities using a discrete Fourier transform, described S1 variation using the Simpson diversity index (SDI), and estimated Spearman cross-correlation coefficients between percentage change in SDI and percentage positivity. SARS-CoV-2 activity consistently peaked during July-September and December-February, and dominant periodicities were at weeks 52.2 and 26.1. Percentage positivity and percentage change in SDI were negatively correlated (ρ = -0.30; p<0.001). SARS-CoV-2 peaks occurred in late summer and winter, a pattern likely related to rapid SARS-CoV-2 evolution and cyclical diversity. Monitoring associations between percentage positivity and SDI can help forecast expected surges and optimize prevention and preparedness.

Emerging infectious diseasesVol. 31(8)
Zero hunger
Openalex Percentile: Top 4%
SARS-CoV-2 and COVID-19 Research
5.58
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.

Estimated COVID-19 Periodicity and Correlation with SARS-CoV-2 Spike Protein S1 Antigenic Diversity, United States — Peter W. Cook, Amber Winn, et al. · Emerging infectious diseases (2025) | TGRS Research Map | TGRS