Using SARS-CoV-2 Sequencing Data to Identify Reinfection Cases in the Global Emerging Infections Surveillance Program, United States
Deanna Muehleman, Bill Gruner, Vivian Hogan, Padraic Fanning, Carol Garrett, Jennifer Meyer, Kelsey Lanter, Sarah Purves, Laurie DeMarcus, Jeffrey Thervil, Bismark Kwaah, Paul Sjoberg, Elizabeth Macias, and Anthony Fries
Author affiliation: US Air Force School of Aerospace Medicine and Defense Centers for Public Health, Dayton, Ohio, USA (D. Muehleman, B. Gruner, V. Hogan, P. Fanning, C. Garrett, J. Meyer, K. Lanter, S. Purves, L. Demarcus, J. Thervil, B. Kwaah, P. Sjoberg, E. Macias, A. Fries); JYG Innovations, Dayton (D. Muehleman, B. Gruner, S. Purves); Henry Jackson Foundation, Rockville, MD, USA (V. Hogan); ERP360 Solutions Group LLC, Washington, DC, USA (P. Fanning, J. Meyer, K. Lanter); Innovative Element LLC, Washington (L. Demarcus, J. Thervil, B. Kwaah, P. Sjoberg)
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Figure 5
Figure 5. SARS-CoV-2 nucleotide changes in study using sequencing data to identify reinfection cases in Department of Defense Global Respiratory Pathogen Surveillance Program, United States. Tamura-Nei p-distances were determined relative to the number of days between specimen collection dates for continuing infections (A) and reinfections (B). A) Number of nucleotide substitutions correlated with the amount of time between specimen collections in patients who had continuing infections (p = 0.0021). Expected SARS-CoV-2 mutation rate was 1 single nucleotide variant per 2 weeks. B) No relationship was observed between number of nucleotide substitutions and time in reinfection cases (p = 0.137).
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