Prediction Intervals for Zika Rate

• Activity Number: 289 - Contributed Poster Presentations: Section on Statistics in Epidemiology
• Type: Contributed
• Date/Time: Tuesday, August 9, 2022 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Marwah Soliman* and Colin M Gallagher
• Companies: Clemson University and Clemson University
• Keywords: zika rate; Generalized Pareto distribution; deep learning; Quantile regression; Conformal method

Abstract

As per the records of the World Health Organization, the first formally reported incidence of Zika virus occurred in Brazil in May 2015. The disease then rapidly spread to other countries in Americas and East Asia, affecting more than 1,000,000 people. Zika virus is primarily transmitted through bites of infected mosquitoes of the species Aedes (Aedes aegypti and Aedes albopictus). The abundance of mosquitoes and, as a result, the prevalence of Zika virus infections are common in areas which have high precipitation, high temperature, and high population density. In this paper we compare interval estimation of Zika prevalence from a variety of models . where we looked at the prediction intervals coverage and width using different statistical and machine learning methods.