关键词: COVID-19 income inequality machine learning negative binomial regression refugees

Mesh : Humans COVID-19 Socioeconomic Factors Pandemics Refugees Income

来  源:   DOI:10.1080/19371918.2024.2318372

Abstract:
Refugees are more vulnerable to COVID-19 due to factors such as low standard of living, accommodation in crowded households, difficulty in receiving health care due to high treatment costs in some countries, and inability to access public health and social services. The increasing income inequalities, anxiety about providing minimum living conditions, and fear of being unemployed compel refugees to continue their jobs, and this affects the number of cases and case-related deaths. The aim of the study is to analyze the impact of refugees and income inequality on COVID-19 cases and deaths in 95 countries for the year 2021 using Poisson regression, Negative Binomial Regression, and Machine Learning methods. According to the estimation results, refugees and income inequalities increase both COVID-19 cases and deaths. On the other hand, the impact of income inequality on COVID-19 cases and deaths is stronger than on refugees.
摘要:
由于生活水平低等因素,难民更容易受到COVID-19的影响,在拥挤的家庭住宿,由于一些国家的高治疗费用,难以获得医疗保健,以及无法获得公共卫生和社会服务。收入不平等加剧,对提供最低生活条件的焦虑,对失业的恐惧迫使难民继续他们的工作,这会影响病例数和与病例相关的死亡。该研究的目的是使用泊松回归分析2021年95个国家的难民和收入不平等对COVID-19病例和死亡的影响,负二项回归,和机器学习方法。根据估算结果,难民和收入不平等增加了COVID-19病例和死亡人数。另一方面,收入不平等对COVID-19病例和死亡的影响比对难民的影响更强。
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