The DIOS framework for optimizing infectious disease surveillance: Numerical methods for simulation and multi-objective optimization of surveillance network architectures
Fig 4
Results from Pareto optimization under the spatially smooth disease scenario (ρ = 0.3).
(A) Mean squared error of log predicted disease prevalence (OFV1) and variance of causal effect estimate (OFV2) of the Pareto set (colored dots) and all other candidate sites (hollow dots). (B) Locations of the Pareto set (colored triangles) colored coded as in Panel A. Black triangles represent initially enrolled sites, and gray dots represent unchosen candidate sites. Background color in Panel B represents log prevalence when ρ = 0.3 using the same color scheme as in Fig 2C, while contour lines represent levels of risk factor X.