Detecting local transmission in CONUS and Hawaii
In areas of the continental U.S. and Hawaii with ecological conditions amenable to autochthonous Zika virus transmission, instituting robust ZIKV surveillance is crucial to monitoring and preparing for the potential spread of the disease. Public health decision makers have limited resources and a need to implement an efficient surveillance strategy. We provide a quantitative, evidence based approach for comparing surveillance systems, and demonstrate that testing care-seeking individuals (who exhibit at least two Zika symptoms) results in a relatively high probability of detecting transmission, while minimizing testing demand and limiting the occurrence of false positives.
Running the simulation
To run the simulation, use the code 'Simulation Code.R'.
Please note: this code creates a very large dataset. Lowering to 1,000 iterations (n.samples <- 1000) will reduce computation time and provide similar results.