Leveraging genomic data to improve effective reproduction number estimates

• Grant number: 22/15985-1
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: April 01, 2023
• End date: December 09, 2023
• Field of knowledge: Engineering - Electrical Engineering - Telecommunications
• Principal Investigator: Vitor Heloiz Nascimento
• Grantee: Carlos Augusto Prete Junior
• Supervisor: Kris Parag
• Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: Imperial College London, England
• Associated to the scholarship: 19/21858-0 - Bayesian models for estimating the attack rate of epidemics, BP.DR

Abstract

The effective reproduction number (Rt) is a time-varying parameter used to monitor the evolution of an epidemic which can be inferred using serial interval and incidence data. The SARS-CoV-2 epidemic in Brazil was driven by multiple co-circulating lineages, which may present different serial interval distributions. Despite that, Rt is usually calculated using a fixed serial interval estimate. The increasing availability of SARS-CoV-2 genomic sequences allows inferring lineage-specific serial intervals, as well as the prevalence of each lineage over time in several regions. In this project, we propose to extend an Rt estimation method based on Bayesian recursive filtering and smoothing techniques to estimate the effective reproduction number accounting for lineage-specific serial intervals. We also intend to extract lineage-specific serial intervals from publicly available genomic data using an existing algorithm that uses imputed transmission clusters accounting for indirect transmission pairs to estimate serial intervals. The resulting method will be used to obtain improved effective reproduction number estimates in Brazilian cities. These results will be useful to better understand the transmission dynamics of SARS-CoV-2 lineages circulating in Brazil. (AU)