Vaccine Supply Forecasting and Optimization using Deterministic and Probabilistic Approaches

When the pandemic was at its peak, it was a quite difficult task for the government to schedule vaccine supply in various districts of a state. This task became further difficult when vaccines were required to be supplied to various Covid Vaccination Centers (CVCs) at a granular level. This is because there was no data regarding the trend being acquired at each CVC and the population distribution is non-uniform across the district. This led to the arousal of an ambiguous situation for a certain period and hence mismanagement. Now that we have sufficient data across each CVC, we can work on a time series analysis of vaccine requirements in which we can essentially forecast the number of administered doses and optimize the wastage at all atomic CVC levels. © 2023 IEEE.

A Power Supply Reliability Optimization Strategy of Shipboard Integrated Power System Equipped with Medical Load and Energy Storage System

The continuing COVID-19 pandemic around the world has raised concerns about public health security and posed a serious threat to the international shipping industry. Considering the fact that current epidemic may exist for a long time, it is necessary to set up independent epidemic prevention function zones on ships to deal with possible outbreaks. Due to the characteristics of high precision and low fault tolerance of medical devices and related equipment in epidemic prevention functional zones, they require more strict power supply quality and reliability, and may cause the deterioration of the power quality of the system. To solve this problem, the paper introduced a novel power management strategy for the shipboard medical system by power generation equipment switching process optimization, partitioning and grading of different types of loads to solve the power supply and distribution problems of the introduced ship epidemic prevention zone, and ensure a stable and reliable power supply of high-power medical equipment on the ship. © 2022 IEEE.

Vaccine Supply Optimization and Forecasting using Random Forest and ARIMA Models

In order to tackle the Corona Virus Disease, it took a considerable amount of time for the governments to come up with effective and efficient vaccines. After the vaccines were developed, the next challenge was to supply the vaccines to various designated centers based on demographics, population distribution, and other factors. The whole system for vaccine supply played a vital role during the COVID-19 pandemic. We also saw a lot of haphazard and mismanagement in some places especially when the cases per day surged high, as people weren't prepared for such a situation. Now that we have got enough data, we can use it to optimize the vaccine supply across various Covid Vaccination Centers and be prepared for any such circumstances in the future. In this paper, we have proposed a two-step approach where considering the past supply and wastage data we performed a classification task that indicates whether doses are to get wasted at a given center. If yes, we then perform demand forecasting based on the number of administered doses so that the wastage can be reduced, and supply can be optimized. © 2022 IEEE.