A multivariate approach for correcting reporting delas in infectious disease surveillance

Abstract

Frequently, real-time tracking of epidemics is faced with a concerning issue, the reporting delays of cases and deaths. Delays might occur due to logistical problems, laboratory confirmation, and other reasons. Being able to correct the delay is essential to decision making with the goal of containing an epidemic. In some cases, the epidemic might be associated with more than one disease, Dengue and Chikungunya are common examples of this phenomenon. We propose a multivariate model to correct reporting delays and accommodate the above-mentioned cases. The model is estimated using the Integrated Nested Laplace Approximation method with the aim of providing faster results.