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Determining Significant Factors Affecting Vaccine Demand and Factor Relationships Using Fuzzy DEMATEL Method

机译:用模糊拆模法确定影响疫苗需求和因子关系的重要因素

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Even though deadly effects of outbreaks such as SARS, H1N1, EBOLA and COVID-19 took the attention of the community, generating 100% vaccination uptake from people who are expected to be affected by such outbreaks is almost impossible. Hence, determining the actual vaccine demand for typical viruses and reaching this population are becoming important issues to prevent from spreading such viruses like wildfire. Many countries have been forecasting vaccine demand according to birth rates. However, factors such as district-level per capita income, literacy rate, urbanization, and some other factors should also be considered for more accurate forecasts. There is another factor affecting countries' vaccine demand; some of the vaccines that WHO recommends are included in the national immunization programs, while others are only recommended. Thus, this study first aims to explore the most significant factors that affect the demand of vaccines that are not included in national immunization campaigns then to present the cause and effect relationships among the factors using the fuzzy DEMATEL method to provide insights to managers for better vaccine demand forecast and to increase vaccine uptake. According to the analysis results, immunization related beliefs is the most important factor among others included in this research.
机译:尽管爆发如SARS,H1N1,埃博拉和Covid-19所关注的爆发的致命影响,但是从预计受这些爆发的影响的人产生100%的疫苗接种,几乎是不可能的。因此,确定对典型病毒的实际疫苗需求并达到该人群正在成为预防野火等病毒的重要问题。根据出生率,许多国家一直在预测疫苗需求。然而,也应考虑为每个人均收入,识字率,城市化和其他一些因素等因素进行准确的预测。还有另一个影响国家疫苗需求的因素;一些建议的疫苗被列入国家免疫计划,而其他疫苗则仅推荐。因此,这项研究首先旨在探讨影响国家免疫活动中不包括在国家免疫活动中的疫苗需求的最重要因素,然后呈现使用模糊Dematel方法的因素之间的原因和效应关系,为管理者提供更好的疫苗需求预测和增加疫苗摄取。根据分析结果,免疫相关信念是本研究中其他人的最重要因素。

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