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We designed a cohort study of changes in viral load after infection with Omicron BA.5.2.48 in a population working in public health industry. The response of Ct values over time was dynamically reflected by multiple imputation for missing values and the construction of a GAM model of Ct values. The file contains data and implemented code.

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SARS-CoV-2_viral-load_trajectories

We engineered a viral load change after infection with Omicron BA.5.2.48 in a population working in the public health industry. The response of Ct values over time was dynamically reflected by multiple imputation for missing values and the construction of a generalized additive model (GAM) of Ct values. The file contains data and implemented code.

"raw_data.csv" records the results of fluorogenic quantitative PCR after collecting throat swabs (sheet1) and nasal swabs (sheet2) for each person every day, and organizes them into a comparative format (sheet3). "all_1.csv" is the data after multiple imputation based on the raw data. The implementation codes of multiple imputation and GAM construction are all in "cohort_MI&GAM.R"

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We designed a cohort study of changes in viral load after infection with Omicron BA.5.2.48 in a population working in public health industry. The response of Ct values over time was dynamically reflected by multiple imputation for missing values and the construction of a GAM model of Ct values. The file contains data and implemented code.

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