Authors: Erez Hatna*, New York University, Sharon K. Greene , New York City Department of Health and Mental Hygiene , Vasudha Reddy, New York City Department of Health and Mental Hygiene , Katelynn Devinney, New York City Department of Health and Mental Hygiene, Beth Nivin, New York City Department of Health and Mental Hygiene , Alyssa Masor, New York City Department of Health and Mental Hygiene
Topics: Geography and Urban Health, Spatial Analysis & Modeling
Keywords: Agent-based model, simulation, Shigellosis
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Truman, Marriott, Mezzanine Level
Presentation File: No File Uploaded
Large outbreaks of Shigella sonnei among children in the ultra-Orthodox Jewish community in Brooklyn, New York have occurred every 3–5 years since at least the mid-1980s. As of December 2017, the most recent outbreak was in 2014–15, with ~300 reported cases and presumably many more unreported cases. The shigellosis burden within this community is related to the large number and density of young children and insufficient handwashing practices. Transmission is highest in daycare and pre-school settings, with secondary transmission within households. We sought to better understand the mechanisms driving these recurrent outbreaks to learn how to optimally target interventions. The study population was defined as <12 year-olds residing in 50 census tracts in Brooklyn where >18% of the population speaks Yiddish or Hebrew at home, per the American Community Survey 2011–2015. This definition closely corresponded to census tracts with >1 diagnosed case during the 2014–15 shigellosis outbreak. Using NetLogo, we developed an agent-based model of shigellosis transmission among children in this community and used these data to parameterize the model. Simulated children were assigned an initial susceptible, infectious, or immune status and interacted and moved between their home and daycare or school. We assumed a low constant rate of shigellosis importations from external ultra-Orthodox communities. We observed the modeled pattern of infection arising over time, calibrating to the observed case count as reported to the New York City Health Department.