MIGUEL ÁNGEL
LUQUE FERNÁNDEZ

I received my Ph.D. in Preventive Medicine (Epidemiology) and Public Health, awarded Summa Cum Laude, from the University of Granada (UGR, Spain) and the ULB (Universite Libre de Bruxelles, Belgium). Also, I hold a Bachelor's in Maths and Stats from the Open University, UK, an MSc in Biostatistics from the University of Newcastle, Australia, an MSc in Epidemiology from ULB, and a Master's in Public Health from the UGR. After the completion of my Ph.D. in 2010, I moved to the Center for Infectious Disease Epidemiology and Research (University of Cape Town) as a postdoctoral fellow for two years. Afterward, I moved to the Harvard School of Public Health (Department of Epidemiology), where I specialized in epidemiologic methods from 2012 to 2015. I have also been trained as an Epidemic Intelligence Officer (EIS), and I worked as a field epidemiologist for several years in different African countries with Médecins Sans Frontières and GOARN-WHO during the Cholera epidemic in Haiti, in 2010. In Europe, I worked as an epidemiologist for the local government of the city of Brussels identifying socio-demographic and economic determinants of health inequalities. My research interests lie principally, but not exclusively in the field of epidemiologic methods aiming to assess determinants of social inequalities in population health outcomes and comparative effectiveness research with a specific interest in longitudinal analysis, causal inference, repeated measures, and translational epidemiology. Example web application to understand colliders: https://watzile.shinyapps.io/EpiCollider At UCT, I used marginal structural models applied to large longitudinal data from Khayelitsha (HIV-Cohort) to assess the effectiveness of an observational, nonrandomized intervention. At Harvard, I used fixed effects methods in the context of the analysis of the components of the variance and within siblings' design (observational cross-over) to evaluate the effect of a small fetoplacental ratio at birth on the risk of delivering a small gestational age infant. Recently, using multilevel analysis, I studied the contextual effect of regional unemployment on stillbirth by geographical regions in Spain as a complement to previous studies where I evaluated the multiplicative effect of maternal education and ethnicity on the risk of delivering a stillborn. Currently, I am studying the impact of socioeconomic inequities on cancer outcomes in Spain and evaluating the best framework to extract cancer patients' comorbidity information from population-based administrative records: https://desocanes.netlify.app/ Also, I am developing in collaboration with colleagues from the ICON-LSHTM Group data-adaptive methods for model selection and evaluation based on cross-validation techniques (cvAUROC) and applying advanced causal inference methods such as cross-validated targeted maximum likelihood estimation (TMLE) to study cancer outcomes. Recently, I developed the implementation of TMLE for Stata statistical software users, named ELTMLE, and divulgated it at the Stata Users Group Meeting in London and Spain: https://github.com/migariane/eltmle Together with collaborators from the ICON Group, we proposed a structural framework for population-based cancer epidemiology and evaluated the performance of double-robust estimators for binary exposure in cancer mortality. Using Montecarlo experiments, I have demonstrated that TMLE and Croos-validated TMLE show better bias-variance trade-offs, more precise estimates, and appropriate 95% confidence interval coverage than its competitors, supporting the use of the data-adaptive model selection strategies based on machine-learning algorithms. My research projects: https://maluque.netlify.app/