There are no equal opportunity infectors: Epidemiological modelers must rethink our approach to inequality in infection risk.
There are no equal opportunity infectors: Epidemiological modelers must rethink our approach to inequality in infection risk.
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DOI：
10.1371/journal.pcbi.1009795
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发表时间：
2022-03
影响因子：
4.3
通讯作者：
Malosh R
中科院分区：
文献类型：
--
作者：
Zelner J;Masters NB;Naraharisetti R;Mojola SA;Chowkwanyun M;Malosh R
数学模型在全球流行病防范和疫情应对中发挥了关键作用：帮助规划疾病负担、医院能力，并为非药物干预措施提供信息。这些模型在2019冠状病毒病大流行中发挥了关键作用，传播模型以及由此产生的模型指导了全球、国家和地方对SARS-CoV-2的应对。然而，这些模型在很大程度上没有考虑到导致社会经济、种族和地理健康差异的社会和结构因素。在这篇文章中，我们提出并试图澄清与传染病建模研究和实践中这一重要差距有关的几个问题：为什么新发感染的流行病学模型通常忽略了不同健康结果的已知结构驱动因素？一个主要关注感染公平性总体结果的框架产生了什么后果？在大流行期间，应该做些什么来制定一种更全面的基于模型的决策方法？在这篇综述中，我们评估了排除新发感染的传染病模型中差异驱动因素的潜在历史和政治解释，这些新发感染通常被描述为“机会均等的感染者”，尽管有充分的证据表明相反。我们着眼于其他疾病系统（艾滋病毒、性传播感染）的例子，并成功地将社会不平等纳入急性感染传播模型，作为如何将社会联系、环境和结构因素纳入连贯、严格和可解释的建模框架的蓝图。最后，我们概述了指导新发感染建模的原则，这些原则代表了感染不平等的原因是中心而不是外围机制。
Mathematical models have come to play a key role in global pandemic preparedness and outbreak response: helping to plan for disease burden, hospital capacity, and inform nonpharmaceutical interventions. Such models have played a pivotal role in the COVID-19 pandemic, with transmission models—and, by consequence, modelers—guiding global, national, and local responses to SARS-CoV-2. However, these models have largely not accounted for the social and structural factors, which lead to socioeconomic, racial, and geographic health disparities. In this piece, we raise and attempt to clarify several questions relating to this important gap in the research and practice of infectious disease modeling: Why do epidemiologic models of emerging infections typically ignore known structural drivers of disparate health outcomes? What have been the consequences of a framework focused primarily on aggregate outcomes on infection equity? What should be done to develop a more holistic approach to modeling-based decision-making during pandemics? In this review, we evaluate potential historical and political explanations for the exclusion of drivers of disparity in infectious disease models for emerging infections, which have often been characterized as “equal opportunity infectors” despite ample evidence to the contrary. We look to examples from other disease systems (HIV, STIs) and successes in including social inequity in models of acute infection transmission as a blueprint for how social connections, environmental, and structural factors can be integrated into a coherent, rigorous, and interpretable modeling framework. We conclude by outlining principles to guide modeling of emerging infections in ways that represent the causes of inequity in infection as central rather than peripheral mechanisms.
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影响因子：
4.2
作者：
Clemenzi-Allen, Angelo;Geng, Elvin;Gandhi, Monica
通讯作者：
Gandhi, Monica
影响因子：
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Hatzenbuehler, Mark L.;Phelan, Jo C.;Link, Bruce G.
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Link, Bruce G.
DOI：
10.1016/j.socscimed.2020.113554
发表时间：
2021-01
期刊：
Social science & medicine (1982)
影响因子：
--
作者：
Clouston SAP;Natale G;Link BG
通讯作者：
Link BG
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Clouston, Sean A. P.;Rubin, Marcie S.;Link, Bruce G.
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