Estimating Seasonal Drivers in Childhood Infectious Diseases with Continuous Time Models
Abstract
Many important factors affect the spread of childhood infectious disease. To
understand better the fundamental drivers of infectious disease spread, several researchers
have estimated seasonal transmission coefficients using discrete-time models.
This research addresses several shortcomings of the discrete-time approaches,
including removing the need for the reporting interval to match the serial interval
of the disease using infectious disease data from three major cities: New York City,
London, and Bangkok. Using a simultaneous approach for optimization of differential
equation systems with a Radau collocation discretization scheme and total variation
regularization for the transmission parameter profile, this research demonstrates that
seasonal transmission parameters can be effectively estimated using continuous-time
models. This research further correlates school holiday schedules with the transmission
parameter for New York City and London where previous work has already been
done, and demonstrates similar results for a relatively unstudied city in childhood
infectious disease research, Bangkok, Thailand.
Subject
Childhood Infectious DiseaseDisease Modeling
Continuous Time Modeling
Transmission Parameter
Radau Collocation on Finite Elements
Total Variation Regularization
Citation
Abbott, George H. (2010). Estimating Seasonal Drivers in Childhood Infectious Diseases with Continuous Time Models. Master's thesis, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /ETD -TAMU -2010 -05 -7661.