Applying particle filtering in both aggregated and age-structured population compartmental models of pre-vaccination measles.

ABSTRACT: Measles is a highly transmissible disease and is one of the leading causes of death among young children under 5 globally. While the use of ongoing surveillance data and-recently-dynamic models offer insight on measles dynamics, both suffer notable shortcomings when applied to measles outbreak prediction. In this paper, we apply the Sequential Monte Carlo approach of particle filtering, incorporating reported measles incidence for Saskatchewan during the pre-vaccination era, using an adaptation of a previously contributed measles compartmental model. To secure further insight, we also perform particle filtering on an age structured adaptation of the model in which the population is divided into two interacting age groups-children and adults. The results indicate that, when used with a suit

SUBMITTER: Li X 

PROVIDER: S-EPMC6214536 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature