Addressing drug demand uncertainty in a pandemic outbreak

Syahrir, I.; Suparno, Vanany I.

This investigation is based on the application of Susceptible-Exposed-Infectious-Recovered (SEIR) model to simulate the number of diseases spread in a region, along with a historical approach of epidemic outbreak cases. Dengue fever pandemic outbreak is used to apply the proposed model for drug demand uncertainty in a pandemic. The aim of this research is to predict the number of drugs needed in a hospital for the treatment of dengue fever cases during the epidemic outbreak. The SEIR model is used to simulate the number of dengue fever patients in a hospital atGresik district, East Java in Indonesia. This analysis was carried out in a comparative way with the other forecasting methods. The result showed that the simulation’s result is different from other forecasting methods, depending on the context in which it is used, such as the disease type and the area of epidemic under study. In the future research, the proposed model is could applied in Malaria, COVID-19 pandemic, and another in order to ensuring the applicability of proposed model.