Optimal control and policy review for realistic simulated epidemics.

<p>Rows (a) and (b) represent epidemics simulated under a COVID-like generation time and basic reproduction number with 7 and 14 days policy review periods, respectively. Rows (c) and (d) represent epidemics simulated under Ebola-like parameters with 7 and 14 days policy review periods, respec...

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Bibliographic Details
Main Author:	Sandor Beregi (22177739) (author)
Other Authors:	Kris V. Parag (4540165) (author)
Published:	2025
Subjects:	Medicine Neuroscience Biotechnology Immunology Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> deciding stochastic epidemic projections recent studies propose overload healthcare capacities optimises npi decisions flatten epidemic peaks dampen endemic oscillations controlling infectious diseases infectious disease epidemiology extremely delayed reporting reduced npi costs prompting mistimed npis predictive control algorithm reporting delays disease growth control spread trigger npis substantial costs relax non predetermined times optimal algorithms novel model misinform decision jointly minimise insensitive strategies general framework different stringency central challenge algorithm provides
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Optimal control and policy review for realistic simulated epidemics.

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