A Novel Proof of Concept Forecasting Model for Pandemics – A Case Study in New Zealand

Disasters possess the potential to disrupt daily life, while pandemics that have natural sources wield the capability to profoundly impact communities worldwide. It is imperative to formulate comprehensive plans and strategies to effectively manage and mitigate the impacts of pandemics. However, pandemics are complex and multifaceted disasters that require the capability to identify intricate patterns and trends. Machine learning (ML) techniques emerge as valuable tools with the development of strategies and policies that can aid in controlling and managing pandemics. This study aims to extend and develop a novel forecasting model by training the algorithm utilizing daily COVID-19 cases from the Ministry of Health in Aotearoa, New Zealand. The ultimate goal of this study is to provide decision-makers with better insights for enhanced policy development and strategy implementation. The study seeks to enhance the performance of the time-series forecasting model, concluding in optimal forecasting results. The findings highlight the beneficial application of this method on the model’s performance. The forecasting model developed in this study serves as a supplementary tool for authorities, enabling them to make well-informed choices and adopt more efficient strategies when confronted with upcoming challenges.