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In 2021, over 500,000 neonates in India died, accounting for 19% of the global total. Even though neonatal mortality is in decline and now stands at 19.4 per 1,000, it remains well above the SDG target of 12 per 1000. In this seminar, the Jamie Perin introduces a Bayesian multinomial model for estimating cause-specific neonatal mortality trends by state (2000-2021) and discusses heterogeneity in levels and causes.

Speaker

, Johns Hopkins University, Bloomberg School of Public Health 

Jamie Perin received her PhD in Biostatistics from the University of North Carolina at Chapel Hill in 2009. She then joined the Department of International Health at Johns Hopkins Bloomberg School of Public Health as an assistant scientist. Since joining International Health, she has enjoyed collaborating with a diverse group of researchers on issues relating to infectious diseases, child health, and child mortality, part of which she has worked on cause-specific child mortality and verbal autopsy for over ten years.  She also maintains an interest in purely statistical pursuits, including longitudinal and incomplete data, semi-parametric models, categorical data, clustered data, survival analysis, multiple imputation, and incomplete data.