Diego Bassani

Diego Bassani is an Associate Professor of Epidemiology at the Dalla Lana School of Public Health and the Department of Pediatrics at the University of Toronto. He is a Senior Scientist at the Research Institute at The Hospital for Sick Children, and the Director of the International Program Evaluation Unit at the Centre for Global Child Health. His research focuses on large-scale studies in the area of maternal and child health, including multi-country analyses of national surveys. Dr. Bassani has conducted important research on child growth and development, the causes and distribution of child deaths, coverage of health interventions, identification of risk factors for child mortality, program evaluation, and large-scale field trials in maternal and child health in multiple countries.

After gathering extensive experience in collecting and analyzing population health data in low- and middle-income countries, Dr. Bassani has decided to revisit the focus of his research program, to address major barriers in population health measurement, namely the timeliness and accuracy of data.

To achieve this, he plans to take an interdisciplinary approach that integrates knowledge and methods from network science and epidemiology, paving the way to a novel transdisciplinary network-based population health research program. Dr. Bassani is currently working with network scientists toward the development of novel methodological approaches to survey design, sampling, and data collection. These novel methods use a large set of multi-country standardized national surveys to expose the underlying complex network structure of populations, traditionally treated as unstructured collections of individuals in epidemiological studies.

By reconstructing unobserved networks of populations, Dr. Bassani aims to re-examine a broad range of health dynamics. He is particularly interested in using influential network nodes identified through these reconstructions to develop novel network-based sampling designs and inferential methods for large-scale surveys. These methods would allow for more frequent data collection, early detection of emerging diseases and risks, and timely response to changes in disease patterns, all critical to evidence-based decision-making.