Open AccessLeveraging Pathogen Sequence and Contact Tracing Data to Enhance Vaccine Trials in Emerging Epidemics
Author(s) -
Rebecca Kahn,
Rui Wang,
Sarah V Leavitt,
William P. Hanage,
Marc Lipsitch
Publication year - 2021
Publication title -
epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.901
H-Index - 173
eISSN - 1531-5487
pISSN - 1044-3983
DOI - 10.1097/ede.0000000000001367
Subject(s) - contact tracing , inference , sequence (biology) , computer science , transmission (telecommunications) , estimator , vaccine efficacy , data mining , artificial intelligence , biology , statistics , covid-19 , medicine , mathematics , vaccination , infectious disease (medical specialty) , virology , telecommunications , genetics , disease , pathology
Advance planning of vaccine trials conducted during outbreaks increases our ability to rapidly define the efficacy and potential impact of a vaccine. Vaccine efficacy against infectiousness (VEI) is an important measure for understanding a vaccine's full impact, yet it is currently not identifiable in many trial designs because it requires knowledge of infectors' vaccination status. Recent advances in genomics have improved our ability to reconstruct transmission networks. We aim to assess if augmenting trials with pathogen sequence and contact tracing data can permit them to estimate VEI.