Interior-Point Methods for Estimating Seasonal Parameters in Discrete-Time Infectious Disease Models

Daniel P. Word, James K. Young, Derek A. T. Cummings, Sopon Iamsirithaworn, Carl D. Laird, Danny Barash
2013 PLoS ONE  
Infectious diseases remain a significant health concern around the world. Mathematical modeling of these diseases can help us understand their dynamics and develop more effective control strategies. In this work, we show the capabilities of interior-point methods and nonlinear programming (NLP) formulations to efficiently estimate parameters in multiple discrete-time disease models using measles case count data from three cities. These models include multiplicative measurement noise and
more » ... ate seasonality into multiple model parameters. Our results show that nearly identical patterns are estimated even when assuming seasonality in different model parameters, and that these patterns show strong correlation to school term holidays across very different social settings and holiday schedules. We show that interior-point methods provide a fast and flexible approach to parameterizing models that can be an alternative to more computationally intensive methods.
doi:10.1371/journal.pone.0074208 pmid:24167542 pmcid:PMC3805536 fatcat:ojjh3n3pzfgqroguydbq5x57q4