Infectious diseases such as Influenza and Ebola pose a serious threat to everyone but certain demographics and cohorts face a higher risk of infection than others. This research provides a computational framework for studying health disparities among cohorts based on individual level features, such as age, gender, income, etc. We apply this framework to find health disparities among subpopulations in an influenza epidemic and evaluate vaccination prioritization strategies to achieve specific objectives. We explore the heterogeneities in individuals’ demographic and socioeconomic attributes as the potential cause of health disparities. An agent-based model is used to simulate an influenza epidemic over a synthetic social contact network of the Montgomery County in Southwest Virginia to identify infected cases which are then labeled with a specific clinical outcome by using a predefined probability distribution based on age and risk level. We divide the population into age and income based cohorts and measure the direct and indirect economic impact of vaccination for each cohort. Simulation-based results find strong health disparities across age and income groups. Various vaccine distribution strategies are considered and outcomes are measured through metrics such as death count, total number of infections, net return per capita, net return per dollar spent and net return per vaccinated person. The results, framework, and methodology developed here can assist public health policy makers in efficiently allocating limited pharmaceutical resources.

中文翻译：

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发现流感流行期间人群健康差异的框架。


流感和埃博拉等传染病对每个人都构成严重威胁，但某些人群和人群比其他人群面临更高的感染风险。这项研究提供了一个计算框架，用于根据个人水平特征（例如年龄、性别、收入等）研究人群之间的健康差异。我们应用该框架来查找流感流行中亚人群之间的健康差异，并评估疫苗接种优先策略，以实现特定目标目标。我们探讨个人人口和社会经济属性的异质性作为健康差异的潜在原因。基于代理的模型用于在弗吉尼亚州西南部蒙哥马利县的综合社交联系网络上模拟流感流行，以识别感染病例，然后使用基于年龄和风险水平的预定义概率分布来标记特定的临床结果。我们将人口分为基于年龄和收入的群体，并衡量疫苗接种对每个群体的直接和间接经济影响。基于模拟的结果发现，不同年龄和收入群体的健康状况存在巨大差异。考虑了各种疫苗分配策略，并通过死亡人数、感染总数、人均净回报、每美元支出的净回报和每个疫苗接种者的净回报等指标来衡量结果。这里开发的结果、框架和方法可以帮助公共卫生政策制定者有效地分配有限的制药资源。