@article{Article_52,

title = {Identifying Long-Term Optimal Vaccination Strategies for Mitigating a Pandemic: a Computational Modeling approach using COVID-19 data in Sri Lanka},

journal = {Communications in Combinatorics, Cryptography & Computer Science},

volume = {2023},

issue = {1},

issn = { 2783-5456 },

year = {2022},

url = {http://cccs.sgh.ac.ir/Articles/2023/issue 1/1-4-DentifyingLongTermOptimalVaccination.pdf},

author = {K.K.W.H. Erandi and A.C. Mahasinghe and N.C. Ganegoda and S.S.N. Perera and and S. Jayasinghe},

keywords = {Optimal control, Pandemic, Vaccination, Epidemic Models.},

abstract = {Infectious diseases with pandemic potential are having a devastating impact on global health and socioeconomic activities. A major and a primary strategy to control such pandemics that is used globally is the process of vaccination. However, the primary vaccination becomes less effective after several months for most infectious diseases. Therefore, for several years, repeated booster doses are necessary to enhance the immune response. The government policy of vaccine administration and public response to the vaccination procedure varies from country to country, depending on the incidence of the infected population, vaccine availability and types, age--related health risks, and prioritization by population density or mobility patterns. In this study, we propose an optimal control model for regional vaccination allocation based on age distribution and mobility patterns, with the goal of achieving a trade--off between vaccination costs and the economic burden caused by the infected population. We use a compartmental model to capture the transmission dynamics, write an optimal control equation and examine the validity using computer simulations generated for COVID-19 related data in Sri Lanka.}

};