Research press release


Nature Physics

Sending sick staff home won’t stop disease spread


流行時に、感染した教師や医療従事者などの重要な役割を持つ人々を、系統的に健康な後任者に代えるという方策は、感染した労働者は働くことができず、他者に病気をうつすリスクがあるという明快な論理に従っている。しかし、疾病が広がるダイナミクスを理解するための標準的なモデルは、こうした健康な後任者が、後任となる以前よりも危険な状況にさらされるという事実を組み込むことができない。Samuel Scarpinoたちは、このリスクの増大を明確にエンコードしてネットワークモデルに組み込み、関係的交換と名付けたこの交代策によって、流行のピークに達した病気が流行の開始時の予測よりも速いスピードで伝播しうることを示した。


During an epidemic, replacing infected key individuals with healthy ones may actually spread the disease more rapidly through a community, due to the underlying structure of the social network, suggests a paper published online this week in Nature Physics. The study combines modelling with empirical data analysis to explain epidemic patterns in influenza outbreaks at a state and national level in the United States.

The policy of systematically replacing key individuals - such as teachers and health-care workers - that become infected during an epidemic with healthy substitutes follows clear logic: infected workers are incapacitated, and run the risk of infecting others. However, standard models for understanding the dynamics of a spreading disease fail to incorporate the fact that these healthy substitutes are being introduced into a more dangerous situation than they were in previously. By specifically encoding this increased risk into a network model, Samuel Scarpino and colleagues show that this policy of replacement - named relational exchange - can cause a disease at its peak to transmit at a rate faster than would be expected at the onset of the outbreak.

The authors test their model on data for influenza and dengue. Both diseases are subject to seasonal effects, but dengue, unlike influenza, features a delay between transmission and behaviour, and is expected to be less susceptible to the impact of relational exchange. The authors show their model is consistent with data for 17 influenza outbreaks in the United States at a national level, 25 years of influenza data at a state level, and 19 years of dengue virus data from Puerto Rico. The findings are expected to better inform public health decision-making during outbreaks.

doi: 10.1038/nphys3832


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