Parameter Estimation, Sensitivity Analysis and Optimal Control of a Periodic Epidemic Model with Application to HRSV in Florida

TL;DR

This paper develops a periodic SEIRS model for HRSV in Florida, fitting real data, analyzing sensitivity and cost-effectiveness, and optimizing treatment strategies for better clinical decision-making.

Contribution

It introduces a novel application of a periodic SEIRS model to real surveillance data and formulates an optimal control problem for HRSV treatment.

Findings

Model accurately fits Florida HRSV data

Sensitivity analysis identifies key parameters affecting outbreaks

Optimal control suggests effective treatment strategies

Abstract

A state wide Human Respiratory Syncytial Virus (HRSV) surveillance system was implemented in Florida in 1999 to support clinical decision-making for prophylaxis of premature infants. The research presented in this paper addresses the problem of fitting real data collected by the Florida HRSV surveillance system by using a periodic SEIRS mathematical model. A sensitivity and cost-effectiveness analysis of the model is done and an optimal control problem is formulated and solved with treatment as the control variable.