Using neural networks to calibrate agent based models enables improved regional evidence for vaccine strategy and policy-Reference-Cited by-同舟云学术

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Using neural networks to calibrate agent based models enables improved regional evidence for vaccine strategy and policy

Published:2023-11 Issue:48 Volume:41 Page:7067-7071
ISSN:0264-410X
Container-title:Vaccine
language:en
Short-container-title:Vaccine

Author:

Chopra Ayush,Rodriguez Alexander,Prakash B. Aditya,Raskar Ramesh,Kingsley Thomas

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Infectious Diseases,Public Health, Environmental and Occupational Health,General Veterinary,General Immunology and Microbiology,Molecular Medicine

Reference11 articles.

1. Differentiable agent-based epidemiology;Chopra;Adaptive Agents Multi-agent Systems (AAMAS),2023

2. Chopra A, Raskar R, Subramanian J, et al. DeepABM: scalable and efficient agent-based simulations via geometric learning frameworks - a case study for Covid-19 spread and interventions. In: 2021 Winter simulation conference (WSC); 2021. p. 1. doi: 10.1109/WSC52266.2021.9715507.

3. CDC. COVID data tracker. Centers for Disease Control and Prevention. Published March 28, 2020. Accessed March 30, 2023. https://covid.cdc.gov/covid-data-tracker.

4. Global impact of the first year of COVID-19 vaccination: a mathematical modelling study;Watson;Lancet Infect Dis,2022

5. Development and dissemination of infectious disease dynamic transmission models during the COVID-19 pandemic: what can we learn from other pathogens and how can we move forward?;Becker;Lancet Digit Health,2021

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