Guidance on the use of complex systems models for economic evaluations of public health interventions
To help health economic modelers respond to demands for greater use of complex systems
models in public health. To propose identifiable features of such models and support …
models in public health. To propose identifiable features of such models and support …
A tale of three recent pandemics: influenza, HIV and SARS-CoV-2
Emerging infectious diseases are one of the main threats to public health, with the potential
to cause a pandemic when the infectious agent manages to spread globally. The first major …
to cause a pandemic when the infectious agent manages to spread globally. The first major …
[HTML][HTML] Agent-based modeling of COVID-19 outbreaks for New York state and UK: Parameter identification algorithm
O Krivorotko, M Sosnovskaia, I Vashchenko… - Infectious Disease …, 2022 - Elsevier
This paper uses Covasim, an agent-based model (ABM) of COVID-19, to evaluate and
scenarios of epidemic spread in New York State (USA) and the UK. Epidemiological …
scenarios of epidemic spread in New York State (USA) and the UK. Epidemiological …
Calibration and validation of the colorectal cancer and adenoma incidence and mortality (CRC-AIM) microsimulation model using deep neural networks
Objectives Machine learning (ML)–based emulators improve the calibration of decision-
analytical models, but their performance in complex microsimulation models is yet to be …
analytical models, but their performance in complex microsimulation models is yet to be …
Emulator-based Bayesian optimization for efficient multi-objective calibration of an individual-based model of malaria
Individual-based models have become important tools in the global battle against infectious
diseases, yet model complexity can make calibration to biological and epidemiological data …
diseases, yet model complexity can make calibration to biological and epidemiological data …
Einns: epidemiologically-informed neural networks
We introduce EINNs, a framework crafted for epidemic forecasting that builds upon the
theoretical grounds provided by mechanistic models as well as the data-driven expressibility …
theoretical grounds provided by mechanistic models as well as the data-driven expressibility …
[HTML][HTML] A model learning framework for inferring the dynamics of transmission rate depending on exogenous variables for epidemic forecasts
In this work, we aim to formalize a novel scientific machine learning framework to reconstruct
the hidden dynamics of the transmission rate, whose inaccurate extrapolation can …
the hidden dynamics of the transmission rate, whose inaccurate extrapolation can …
Likelihood-based methods improve parameter estimation in opinion dynamics models
We show that a maximum likelihood approach for parameter estimation in agent-based
models (ABMs) of opinion dynamics outperforms the typical simulation-based approach …
models (ABMs) of opinion dynamics outperforms the typical simulation-based approach …
Agent-based mathematical model of COVID-19 spread in Novosibirsk region: Identifiability, optimization and forecasting
O Krivorotko, M Sosnovskaia… - Journal of Inverse and Ill …, 2023 - degruyter.com
The problem of identification of unknown epidemiological parameters (contagiosity, the
initial number of infected individuals, probability of being tested) of an agent-based model of …
initial number of infected individuals, probability of being tested) of an agent-based model of …
Real-time infectious disease modeling to inform emergency public health decision making
Infectious disease transmission is a nonlinear process with complex, sometimes unintuitive
dynamics. Modeling can transform information about a disease process and its parameters …
dynamics. Modeling can transform information about a disease process and its parameters …