Michael A.L. Hayashi, PhD, MPH
- Clinical Assistant Professor
Michael Hayashi is a computational epidemiologist and modeler. He is currently a Clinical Assistant Professor in the Department of Epidemiology. He received his MPH and PhD in Epidemiology from the University of Michigan.
- PhD, Epidemiological Science, University of Michigan, 2016
- MPH, Epidemiology, University of Michigan, 2013
- BA, Political Science, University of Rochester, 2011
Michael uses systems science methods to address a range of public health topics. His research uses mathematical and computational tools to understand the mechanisms of disease transmission with a focus on the interaction between human behavior and disease processes.
Current projects include modeling the impact of water and sanitation interventions on respiratory disease outbreaks and understanding the transmission of respiratory and gastrointestinal diseases in child care settings. Michael is also actively interested in the development and application of computational methods for public health research and practice.
Shared water facilities and risk of COVID-19 in resource-poor settings: a transmission modelling study, MAL Hayashi, S Boerger, K Zou, S Simon, M Freeman, JNS EisenbergPLOS Water (In Press)
The Statewide Economic Impact of Child Care-Associated Viral Acute Gastroenteritis Infections, MAL Hayashi, JNS Eisenberg, ET Martin, AN HashikawaJournal of the Pediatric Infectious Diseases Society 10 (8), 847-855
Risk for fomite-mediated transmission of SARS-CoV-2 in child daycares, schools, nursing homes, and offices, Alicia NM Kraay, Michael AL Hayashi, David M Berendes, Julia S Sobolik, Juan S Leon, Benjamin A Lopman, Emerging infectious diseases 27 (4), 1229
Antimicrobial Bacteria and Viruses Detected Through Systematic Sampling in the Childcare Environment, Khalil Chedid, Michael AL Hayashi, Peter DeJonge, Olivia Yancey, Elliane Siebert, Amy Getz, Joseph Eisenberg, Andrew Hashikawa, Emily MartinInfection Control and Hospital Epidemiology 41 (S1), s461-s461
Linking decision theory and quantitative microbial risk assessment: tradeoffs between compliance and efficacy for waterborne disease interventions, MAL Hayashi, MC Eisenberg, JNS Eisenberg, Risk Analysis 39 (10), 2214-2226