The DIOS framework for optimizing infectious disease surveillance: Numerical methods for simulation and multi-objective optimization of surveillance network architectures.

ABSTRACT: Infectious disease surveillance systems provide vital data for guiding disease prevention and control policies, yet the formalization of methods to optimize surveillance networks has largely been overlooked. Decisions surrounding surveillance design parameters-such as the number and placement of surveillance sites, target populations, and case definitions-are often determined by expert opinion or deference to operational considerations, without formal analysis of the influence of design parameters on surveillance objectives. Here we propose a simulation framework to guide evidence-based surveillance network design to better achieve specific surveillance goals with limited resources. We define evidence-based surveillance design as an optimization problem, acknowledging the many operational

SUBMITTER: Cheng Q 

PROVIDER: S-EPMC7744064 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature