Chronic disease patients have fewer social contacts: A pilot survey with implications for transmission dynamics

IF 8.8 3区 医学 Q1 Medicine
J. Vanderlocht , S. Møgelmose , K. Van Kerckhove , P. Beutels , N. Hens
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引用次数: 0

Abstract

Non-communicable diseases (NCD) are the most important cause of death in the world. The socio-economic costs associated with NCDs makes it imperative to prevent and control them in the 21st century. The severe toll that the COVID-19 pandemic has taken worldwide is an unfortunate illustration of our limited insight into the infectious risk for the global population. Co-incidence between NCD and infection offers an underexplored opportunity to design preventive policies. In a pilot survey, we observed that the NCD population displays a substantial reduction in their social contacting behavior as compared to the general population. This indicates that existing mathematical models based on contact surveys in the general population are not applicable to the NCD population and that the risk of acquiring an infection following a contact is probably underestimated. Our demonstration of reduced social mixing in several chronic conditions, raises the question to what extent the social mixing is influenced by the burden of disease. We advocate the design of disease-specific contact surveys to address how the burden of disease associates with social contact behavior and the risk of infection. The SARS-CoV-2 pandemic offers an unprecedented opportunity to gain insight into the importance of infection in the NCD population and to find ways to improve healthcare procedures.

慢性病患者的社会接触较少:一项试点调查对传播动态的影响
非传染性疾病(NCD)是世界上最重要的死亡原因。与非传染性疾病相关的社会经济成本使得预防和控制非传染性疾病成为 21 世纪的当务之急。COVID-19 大流行在全球造成的严重损失不幸说明了我们对全球人口感染风险的洞察力有限。非传染性疾病和感染之间的并发症为设计预防政策提供了一个尚未充分开发的机会。在一项试点调查中,我们观察到,与普通人群相比,非传染性疾病人群的社会接触行为大幅减少。这表明,基于普通人群接触调查的现有数学模型并不适用于非传染性疾病人群,而且接触后感染的风险很可能被低估了。我们对几种慢性疾病的社会混合程度降低的证明,提出了社会混合程度在多大程度上受疾病负担影响的问题。我们主张设计针对特定疾病的接触调查,以解决疾病负担如何与社会接触行为和感染风险相关联的问题。SARS-CoV-2 大流行提供了一个前所未有的机会,让我们可以深入了解感染在非传染性疾病人群中的重要性,并找到改善医疗保健程序的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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