A decision-making framework for supporting an equitable global vaccine distribution under humanitarian perspectives
针对疫苗民族主义导致的不公平分配问题，提出了一个包含多毒株流行病模型和公平约束分配模型的数据驱动框架，模拟显示公平分配能加速终结疫情，且高收入国家的优势是暂时的。
This paper is motivated by the occurrence of vaccine nationalism in the setting of pandemics. Certain high-income countries (HICs) aggressively accumulated vaccinations while showing little concern for the vaccination challenges faced by low- and middle- income countries. This disparity fosters the proliferation and mutation of viruses, thus risking the global population’s health and welfare. Hence, we create a data-driven framework to tackle this humanitarian problem by facilitating the provision of vaccines. The framework comprises of two models: a network model named multi-strain Susceptible-Vaccinated-Infected-Removed-Susceptible and a vaccine distribution model with equitable constraints. The latter also encompasses the diverse uncertainty associated with vaccination hesitancy in different countries, in order to avoid potential wastage of resources. The vaccine distribution from our framework is based on greedy thought, thus enabling decision-makers to actively engage in the real-time vaccine allocation process. When the suggested framework is applied to the scenario of the COVID-19 pandemic, the simulation results indicate that fair distributions could accelerate the end of the pandemic. Additional scenarios, such as equitable levels and traveling intensity, are also examined in the sensitivity analysis. The progression of the epidemic under vaccine nationalism is moreover simulated to highlight its harmfulness and validate the efficacy of our framework. We demonstrate that the inequitable advantage experienced by HICs is temporary, as HICs are bound to suffer from virus variants in due course when vaccinations become less efficacious against them.