# 12/04/2018 - Estimation of intervention and spatial spillover effects in cluster randomised trials - Palestrante: Karin Anaya-Izquierdo (University of Bath, UK)

Seminário Conjunto UFSCar/ICMC -12/04/2018 (quinta-feira) – 10h00

LOCAL: Auditório Luiz Antonio Fávaro, ICMC/USP

PALESTRANTE: Karin Anaya-Izquierdo, University of Bath, UK

TÍTULO: Estimation of intervention and spatial spillover effects in cluster randomised trials

RESUMO: We describe a spatial regression methodology for the analysis of cluster randomised trials (CRTs) with count outcomes, taking indirect effects into account. The assumption between cluster independence in CRT's is potentially violated in trials against infectious diseases, whose clusters are often defined geographically, potentially inducing spatial correlation and indirect effects. We use spatial regression models with Gaussian random effects, where the individual outcomes have marginal distributions overdispersed with respect to the Poisson and the corresponding intervention effects have a marginal interpretation. Two types of effect are distinguished and estimated: spillover dependence, which is cross-cluster correlation between individual outcomes; and spillover indirect effect, which is change in the intervention effect depending on the proximity of individuals to those in the intervention arm. Orthogonal regression is used to avoid bias arising from collinearity, a phenomenon which has become known as spatial confounding. We also show that coefficients from spatial models with a certain form of homoscedasticity can be interpreted simply as intervention effects. The standard intrinsic conditional autoregression (ICAR) model does not have this property, but we use a normalized version which does. In order to

quantify the proximity of individuals in the intervention arm we use Tukey’s half space depth. We fit the models in a Bayesian framework using integrated nested Laplace approximations (INLA), and illustrate the methodology using data from a pair-matched CRT done in Venezuela against the mosquito Aedes aegypti, which is a vector of dengue and Zika.