SEIMR/R-S/OPT. Epidemic Management Optimization Model, Control Policies, Vital Health Resources and Vaccination. Theory

Abstract

Make decision during an epidemic process implies enter in the dialectic of duality of goals: lives saved in the short term versus loss of quality of life of the population in the long term. The optimization models may be used to support epidemic management without entering the duality of goals do not try to compare economic impact with avoided deaths, concentrating the mathematical effort into avoid additional deaths over the minimum natural death due to the biological aspects of the epidemics, considering the real restrictions about economic budgets and logistics constraints. The pandemic is a natural process that follows known mathematical rules, which involve great uncertainty for being unknown, but humanity has developed great scientific (analytical) capacity to face complex natural processes, managing a pandemic like COVID-19 is perhaps the biggest challenge it must overcome. Tackling the pandemic by ignoring humanity's ability to model processes and find the "best" decision means that, despite acting with goodwill, policies that do not produce the greatest social well-being and that possibly generate more dead than the minimum possible and cause an economic impact that negatively affects quality of life by returning to levels 20 or more years ago, it affects strongly to countries in development way. SEIMR/R-S simulation epidemic model is the core of SEIMR/R-S/OPT, it considers the impact of modeling the population divided into sociodemographic segments based on age and economic stratum (other dimensions, for example: ethnics, gender, …). The added value by mathematical programming approach is to convert simulation models into optimization models enabling decision makers to determine optimal policies for public health management. SEIMR/R-S/OPT may determine optimal policies considering the socio-spatial distribution of the population. SEIMR/R-S/OPT was implemented in GAMS using OPTEX Expert Optimization System.