Effects of Age on Transmission of SARS-CoV-2 Throughout the COVID-19 Pandemic
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Date
2024-05
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The Ohio State University
Abstract
Throughout the COVID-19 pandemic, SARS-CoV-2 transmission and individual recovery rates differed by age. Transmission was highest among school-aged children and most recovered very quickly. In contrast, transmission was lowest among older individuals, but most took longer to recover and suffered a higher degree of disease-induced mortality. Most of the previous studies that investigated age-specific patterns of SARS-CoV-2 transmission were completed when the pandemic first began or during school reopening decision times. The difference in age-group contributions to transmission over the entire pandemic duration remains unclear. One approach to quantify both transmission and recovery rates over the course of the pandemic for different age groups is to use computational models calibrated with COVID-19 case count data. We designed a modified SIR model, which mathematically models disease transmission between susceptible (S), exposed (E), infected (I), and recovered (R) individuals in a population. We modified the SEIR model for SARS-CoV-2 transmission by including categories for individuals who were vaccinated, infected but not yet infectious (exposed), hospitalized, and deceased. After coding the model in R, we then used COVID-19 case count data from Chicago, Illinois to fit the model. The SARS-CoV-2 transmission rates were quantified for each age group, and we found the highest transmission among school-aged children for some parts of the pandemic. There were also some periods of the pandemic where middle-aged individuals had the highest transmission rates. A contact matrix was produced to quantify transmission between and within age groups during the first month of the COVID-19 pandemic. This research will help to define the trends in SARS-CoV-2 transmission and recovery rates across age groups throughout the pandemic. The SEIR model used in this study could also be used to study other acute, immunizing infectious diseases, or to analyze data from past pandemics.
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Keywords
COVID-19, Transmission rates, SIR model