Bibliographic citations
Samaniego, A., (2024). Simulación e impacto de estrategias de vacunación en el distrito de Lima utilizando herramientas de analítica y modelamiento matemático [Pontificia Universidad Católica del Perú]. http://hdl.handle.net/20.500.12404/27578
Samaniego, A., Simulación e impacto de estrategias de vacunación en el distrito de Lima utilizando herramientas de analítica y modelamiento matemático []. PE: Pontificia Universidad Católica del Perú; 2024. http://hdl.handle.net/20.500.12404/27578
@mastersthesis{renati/535229,
title = "Simulación e impacto de estrategias de vacunación en el distrito de Lima utilizando herramientas de analítica y modelamiento matemático",
author = "Samaniego Osorio, Alvaro Danilo",
publisher = "Pontificia Universidad Católica del Perú",
year = "2024"
}
The global crisis caused by COVID19 has highlighted the importance of strategic management of epidemic detection and control to minimize the number of infected and to reduce the number of infected with severe complications and subsequent death. The global response went by three pathways: (1) containment (2) mass vaccination and (3) reinforcement of health institutions. Therefore, the objective of this research is to represent the dynamics of the COVID19 epidemic as a linear programming model that allows the evaluation of different policies based on some combinations of the three aforementioned pathways. In the first chapter, the theoretical framework and the mathematical tools used such as linear programming and geographic information systems will be detailed, as well as the description of an epidemic and/or pandemic and its key indicators. In the second chapter, two case studies will be presented, in which modeling or partial differential equation techniques have been applied to define vaccination st rategies in United States and Australia. In the third chapter, there will be a brief diagnosis of the current situation seen as the temporal evolution of the stages of COVID19 in Peru including main indicators, as well as the country's response to this pandemic with the acquisition of vaccines and the installation of vaccination centers. In the fourth chapter, the mathematical model is conceptualized based on an adaptation of the SIR compartmental model under different assumptions that do not affect the linearization of the problem. The model, the code used, the results of the model and a sensitivity analysis with respect to the critical parameters will be presented. In the fifth chapter, the main conclusions driven from the model and its results will be presented, as well as its applicability to other epidemics and future scopes that could use this research work as a primary source.
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