An Accurate Mathematical Epidemiological Model (SEQIJRDS) to Recommend Public Health Interventions Related to COVID-19 in Sri Lanka.

Abstract COVID-19 has been causing negative impacts on various sectors in Sri Lanka as a result of the public health interventions that government had to implement in order to reduce the spreading of the disease. Equivalent work carried out in this context is outdated and close to ideal models. This research is carried out in a crucial time which the daily deaths are rapidly increasing which arise the requirement for an accurate and practical model to predict the mortality in order to take decisions regarding public health interventions. This paper presents a mathematical epidemiological model called SEQIJRDS to predict on COVID-19. The model has been validated for the COVID 19 pandemic in Sri Lanka. The results show that the model outstands many of the state-of-the-art SEIR epidemiological models such as Imperial, IHME once properly parameterized. At the end; this work recommends public health interventions at this crucial time to save people's lives based on the predictions of the proposed model. Specifically, 3 recommendations called minimal, sub-optimal and optimal recommendations are provided for public health interventions.