John Pesavento’s research while affiliated with Thomas Jefferson School of Law and other places

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Publications (1)


Figure 2: Heatmaps of the top 100 POIs for two selected topics with topic count í µí±˜ = 50 (left: topic 37, right: topic 43)
Figure 4: Disease Spread Simulation Results with Various Model Parameterization
Figure 5: Disease Spread Simulation Results after Prescribing Interventions 7.3 Effect of Policy Interventions A variety of experiments are implemented to test the impact of various public health interventions on the spread of COVID-19 and the subsequent effect on the epidemic curve.
POI Distributions of Latent Mobility Topics
Experiment settings (Default parameters in bold)
Data-driven mobility models for COVID-19 simulation
  • Conference Paper
  • Full-text available

November 2020

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126 Reads

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25 Citations

John Pesavento

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Andy Chen

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Rayan Yu

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[...]

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Andreas Züfle
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Citations (1)


... Agent-based models (ABMs) are commonly used to simulate the spread of infectious diseases between individuals, including COVID-19 virus [1][2][3][4], influenza [5,6], and the chickenpox virus [7,8]. Unlike traditional compartmental models that use differential equations to predict the proportion of the population that is Susceptible, Infectious, and Recovered at each time step (e.g., SIR, or other variants of such models), ABMs use a bottom-up approach that simulates the behaviors, interactions, and subsequent transmission of disease between individual "agents" within their environment [9,10]. ...

Reference:

Synthetic population generation with public health characteristics for spatial agent-based models
Data-driven mobility models for COVID-19 simulation