Erez Hatna
Erez Hatna
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Clinical Associate Professor of Epidemiology
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Professional overview
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Dr. Erez Hatna works in the fields of geoinformatics, spatial analysis, agent-based modeling, and studies urban dynamics, residential segregation, scaling laws of urban systems, and infectious disease modeling.
Dr. Hatna studies ethnic and economic residential patterns of cities using agent-based computational models of relocating households. The models simulate the formation of residential patterns as an outcome of relocation decisions of households. Dr. Hatna also studies the statistical regularities of urban systems and urban scaling. His research focuses on how the choice of urban boundaries influences the scaling relationships.
At NYU, Dr. Hatna is part of the Agent-based Modeling Lab, which works with large-scale epidemic models and cognitively plausible agents in order to produce a transformative synthesis for global public health modeling. Previously, he has conducted research at Wageningen University, University College London, and Johns Hopkins University.
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Education
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PhD, Geography, Tel Aviv University, Tel Aviv, IsraelMA, Geography, Tel Aviv University, Tel Aviv, Israel
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Areas of research and study
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Agent-Based ModelingEpidemiologyGeographic Information Science (GIS)Geospatial MethodsInfectious DiseasesMathematical and Computational ModelingModeling Social and Behavioral DynamicsUrban Informatics
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Publications
Publications
An agent-based model to assess possible interventions for large shigellosis outbreaks
Simulating the Simultaneous Impact of Medication for Opioid Use Disorder and Naloxone on Opioid Overdose Death in Eight New York Counties
AbstractCerdá, M., Hamilton, A. D., Hyder, A., Rutherford, C., Bobashev, G., Epstein, J. M., Hatna, E., Krawczyk, N., El-Bassel, N., Feaster, D. J., & Keyes, K. M. (n.d.).Publication year
2024Journal title
EpidemiologyVolume
35Issue
3Page(s)
418-429AbstractBackground: The United States is in the midst of an opioid overdose epidemic; 28.3 per 100,000 people died of opioid overdose in 2020. Simulation models can help understand and address this complex, dynamic, and nonlinear social phenomenon. Using the HEALing Communities Study, aimed at reducing opioid overdoses, and an agent-based model, Simulation of Community-Level Overdose Prevention Strategy, we simulated increases in buprenorphine initiation and retention and naloxone distribution aimed at reducing overdose deaths by 40% in New York Counties. Methods: Our simulations covered 2020-2022. The eight counties contrasted urban or rural and high and low baseline rates of opioid use disorder treatment. The model calibrated agent characteristics for opioid use and use disorder, treatments and treatment access, and fatal and nonfatal overdose. Modeled interventions included increased buprenorphine initiation and retention, and naloxone distribution. We predicted a decrease in the rate of fatal opioid overdose 1 year after intervention, given various modeled intervention scenarios. Results: Counties required unique combinations of modeled interventions to achieve a 40% reduction in overdose deaths. Assuming a 200% increase in naloxone from current levels, high baseline treatment counties achieved a 40% reduction in overdose deaths with a simultaneous 150% increase in buprenorphine initiation. In comparison, low baseline treatment counties required 250-300% increases in buprenorphine initiation coupled with 200-1000% increases in naloxone, depending on the county. Conclusions: Results demonstrate the need for tailored county-level interventions to increase service utilization and reduce overdose deaths, as the modeled impact of interventions depended on the county's experience with past and current interventions.The role of analytical models and their circulation in urban studies and policy
Coresidency of Immigrant Groups in a Diverse Inner-City Neighborhood of Whitechapel, London
Generating Mixed Patterns of Residential Segregation: An Evolutionary Approach
AbstractGunaratne, C., Hatna, E., Epstein, J. M., & Garibay, I. (n.d.).Publication year
2023Journal title
JASSSVolume
26Issue
2AbstractThe Schelling model of residential segregation has demonstrated that even the slightest preference for neighbors of the same race can be amplified into community-wide segregation. However, these models are unable to simulate mixed, coexisting patterns of segregation and integration, which have been seen to exist in cities. Using evolutionary model discovery we demonstrate how including social factors beyond racial bias when modeling relocation behavior enables the emergence of strongly mixed patterns. Our results indicate that the emergence of mixed patterns is better explained by multiple factors influencing the decision to relocate; the most important being the interaction of nonlinear, rapidly diminishing racial bias with a recent, historical tendency to move. Additionally, preference for less isolated neighborhoods or preference for neighborhoods with longer residing neighbors may produce weaker mixed patterns. This work highlights the importance of exploring the influence of multiple hypothesized factors of decision making, and their interactions, within agent rules, when studying emergent outcomes generated by agent-based models of complex social systems.Special Section on "Inverse Generative Social Science": Guest Editors’ Statement
AbstractEpstein, J. M., Garibay, I., Hatna, E., Koehler, M., & Rand, W. (n.d.).Publication year
2023Journal title
JASSSVolume
26Issue
2AbstractThis is a guest editors’ statement accompanying the publication of a special issue on "Inverse Generative Social Science", published in volume 26, issue 2, 2023 of JASSS-Journal of Artificial Societies and Social Simulation".Privacy and contact tracing efficacy
AbstractBenthall, S., Hatna, E., Epstein, J. M., & Strandburg, K. J. (n.d.).Publication year
2022Journal title
Journal of the Royal Society InterfaceVolume
19Issue
194AbstractAs the COVID-19 pandemic emerged, public health authorities and software designers considered the possibility that smartphones could be used for contact tracing to control disease spread. Smartphone-based contact tracing was attractive in part because it promised to allow the tracing of contacts that might not be reported using traditional contact tracing methods. Comprehensive contact tracing raises distinctive privacy concerns, however, that have not been previously explored. Contacts outside of an individual's ordinary social network are more likely to be privacy-sensitive, making fear that such contacts will be disclosed a potential disincentive to adoption of smartphone contact tracing. Here, we modify the standard SEIR infectious disease transmission model to incorporate contact tracing and perform a series of simulations aimed at studying the importance of tracing socially distant (and potentially privacy-sensitive) contacts. We find that, for a simple model network, ensuring that distant contacts are traced is surprisingly unimportant as long as contact tracing adoption is sufficiently high. These results suggest that policy-makers designing contact tracing systems should be willing to trade off comprehensiveness for more widespread adoption.Triple contagion: A two-fears epidemic model
AbstractEpstein, J. M., Hatna, E., & Crodelle, J. (n.d.).Publication year
2021Journal title
Journal of the Royal Society InterfaceVolume
18Issue
181AbstractWe present a differential equations model in which contagious disease transmission is affected by contagious fear of the disease and contagious fear of the control, in this case vaccine. The three contagions are coupled. The two fears evolve and interact in ways that shape distancing behaviour, vaccine uptake, and their relaxation. These behavioural dynamics in turn can amplify or suppress disease transmission, which feeds back to affect behaviour. The model reveals several coupled contagion mechanisms for multiple epidemic waves. Methodologically, the paper advances infectious disease modelling by including human behavioural adaptation, drawing on the neuroscience of fear learning, extinction and transmission.Evidence for localization and urbanization economies in urban scaling
Defining urban clusters to detect agglomeration economies
AbstractCottineau, C., Finance, O., Hatna, E., Arcaute, E., & Batty, M. (n.d.).Publication year
2019Journal title
Environment and Planning B: Urban Analytics and City ScienceVolume
46Issue
9Page(s)
1611-1626AbstractAgglomeration economies are a persistent subject of debate in regional science and city planning. Their definition turns on whether or not larger cities are more efficient than smaller ones. Here, we complement existing discussions on agglomeration economies by providing a sensitivity analysis of estimated externalities to the definitions of urban agglomeration. We regress wages versus population and jobs over thousands of different definitions of cities in France, based on an algorithmic aggregation of spatial units. We also search for evidence of larger inequalities in larger cities. This paper therefore focuses on the spatial and economic complexity of the mechanisms defining agglomeration within and between cities.Diverse cities or the systematic paradox of Urban Scaling Laws
Cities and regions in Britain through hierarchical percolation
Defining urban agglomerations to detect agglomeration economies
Regions and cities in Britain through hierarchical percolation
Combining segregation and integration: Schelling model dynamics for heterogeneous population
Constructing cities, deconstructing scaling laws
On the problem of boundaries and scaling for urban street networks
Paradoxical Interpretations of Urban Scaling Laws
Combining segregation and integration: Schelling model dynamics for heterogeneous population
Influence of provider and urgent care density across different socioeconomic strata on outpatient antibiotic prescribing in the USA
Assessing spatial uncertainties of land allocation using a scenario approach and sensitivity analysis: A study for land use in Europe
City boundaries and the universality of scaling laws
Hatna, E., & Al., . (n.d.).Publication year
2013Journal title
arXivLong-term changes in the configuration of agriculture and natural areas around cities in the Netherlands (1900-1990)
AbstractHatna, E., & Bakker, M. M. (n.d.). In Modeling of Land-use and Ecological Dynamics (1–).Publication year
2013Page(s)
37-49AbstractCities' influence on the spatial configuration of land in their proximity has presumably changed during the last century as agriculture, cities, and transportation evolved. Investigation of these changes has been limited due to the limited availability of historical maps in digital form. In this chapter, we employ a set of digitized historical land-cover maps in order to compare the spatial distribution of cropland, pasture, and nature surrounding cities in the Netherlands for three time periods: 1900, 1960 and 1990. Our findings suggest that the land cover around cities was relatively stable during these time periods. However, we discovered that, near the perimeter of cities, in 1900, we could discern a clear trend of higher fractions of cropland. These tendencies weakened by the middle of the century and almost completely ceased by 1990.The schelling model of ethnic residential dynamics: Beyond the integrated - segregated dichotomy of patterns
Abandonment and Expansion of Arable Land in Europe