Correcting for reporting delay: an example using dengue fever data

Abstract

One complication to infectious disease forecasting efforts is delay in reporting of cases, where real-time data often under-report the true disease burden. This pair of R scripts (1) provides example code demonstrating several strategies to account for the reporting delay and improve disease forecasts and (2) applies these methods using publicly-available data on dengue fever case reporting in Puerto Rico from 1990 to 2009.