让生病员工回家或加速流行病传播
科学网 · 2016/08/15
美国圣菲研究所的一个研究小组根据历史数据和实验模型的分析发现,在流行病爆发时撤下被感染的员工,换上健康替补的做法,实际上可能会加快疾病在社区中的传播。


该研究颠覆了人们的传统认识,有望对现有公共卫生决策产生积极影响。相关论文在线发表于《自然—物理学》杂志网站上。

由于被感染者丧失了工作能力,还有感染他人的风险,在流行病爆发时,撤下被感染人员换上健康者,符合逻辑也在现实中被广泛采用。但人们没有注意到的是,这些健康的替补人员同时也进入了比先前更危险的环境。理解疾病传播动态的标准模型不能忽略这一重要因素。

在新的研究中,圣菲研究所的塞缪尔·斯卡皮诺和他的同事特意将这一风险因素纳入了网络模型,结果发现,这种撤换策略可能会导致流行病在巅峰时期的传播速度快于爆发初始时的预期。研究人员称,他们的模型与美国17次国家级流感爆发和25年的州级流感数据,以及波多黎各19年的登革热病毒数据相符。

而后,他们用流感和登革热数据对模型进行了校验,结果显示,两种疾病都受季节效应影响。但与流感不同的是,登革热在传播和行为上存在延迟,因此受这种替换策略的影响更小。

研究人员表示,这项研究结合了模型与实证数据分析,对美国全国及州级流感爆发的流行规律进行了解释,有望改进现有的公共卫生决策。

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  • The effect of a prudent adaptive behaviour on disease transmission

    The spread of disease can be slowed by certain aspects of real-world social networks, such as clustering1, 2 and community structure3, and of human behaviour, including social distancing4 and increased hygiene5, many of which have already been studied. Here, we consider a model in which individuals with essential societal roles—be they teachers, first responders or health-care workers—fall ill, and are replaced with healthy individuals. We refer to this process as relational exchange, and incorporate it into a dynamic network model to demonstrate that replacing individuals can accelerate disease transmission. We find that the effects of this process are trivial in the context of a standard mass-action model, but dramatic when considering network structure, featuring accelerating spread, discontinuous transitions and hysteresis loops. This result highlights the inability of mass-action models to account for many behavioural processes. Using empirical data, we find that this mechanism parsimoniously explains observed patterns across 17 influenza outbreaks in the USA at a national level, 25 years of influenza data at the state level, and 19 years of dengue virus data from Puerto Rico. We anticipate that our findings will advance the emerging field of disease forecasting and better inform public health decision making during outbreaks.

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