Household bubbles and COVID-19 transmission: insights from percolation theory
Household bubbles and COVID-19 transmission: insights from percolation theory
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家庭泡沫和 COVID-19 传播：渗透理论的见解
DOI：
10.1101/2020.12.16.20248311
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Danon L
中科院分区：
文献类型：
--
作者：
Danon L
背景在为遏制COVID-19传播而实行社交距离的时代，冒泡是指两个或两个以上的家庭结合在一起，形成一个排他性的更大群体。泡沫对COVID-19传播的影响是具有挑战性的量化，因为涉及复杂的社会结构。MethodsWe开发了一个网络描述的家庭在英国，使用配置模型连接家庭。我们通过将不同规模的家庭结合在一起，探讨了泡沫情景的影响。对于每一个冒泡的场景，我们计算了渗流阈值，也就是说，每个人需要连接的数量，一个巨大的组件形成，数字和理论。我们相关的渗流阈值的家庭reproductionnumber.ResultsWe发现，冒泡的情况下，单人家庭与另一个家庭加入网络连接和传输潜力的影响最小。普遍存在的所有家庭都形成泡沫的场景，很可能导致难以控制的广泛传播。合理的情况下，可变的吸收和异构的泡沫大小的影响，可以减轻与减少数量的接触外的house.ConclusionsBubbling的家庭来在一个更大的风险传输，但在某些情况下，风险可以是温和的，可以平衡的其他行为的变化。
BackgroundIn the era of social distancing to curb the spread of COVID-19, bubbling is the combining of two or more households to create an exclusive larger group. The impact of bubbling on COVID-19 transmission is challenging to quantify because of the complex social structures involved.MethodsWe developed a network description of households in the UK, using the configuration model to link households. We explored the impact of bubbling scenarios by joining together households of various sizes. For each bubbling scenario, we calculated the percolation threshold, that is, the number of connections per individual required for a giant component to form, numerically and theoretically. We related the percolation threshold to the household reproduction number.ResultsWe find that bubbling scenarios in which single-person households join with another household has a minimal impact on network connectivity and transmission potential. Ubiquitous scenarios where all households form a bubble are likely to lead to extensive transmission that is hard to control. The impact of plausible scenarios, with variable uptake and heterogeneous bubble sizes, can be mitigated with reduced numbers of contacts outside the household.ConclusionsBubbling of households comes at an increased risk of transmission, however under certain circumstances risks can be modest and could be balanced by other changes in behaviours.
影响因子：
4.3
作者：
Ball, Frank;Sirl, David;Trapman, Pieter
通讯作者：
Trapman, Pieter
影响因子：
--
作者：
Leng T;White C;Hilton J;Kucharski A;Pellis L;Stage H;Davies NG;Centre for Mathematical Modelling of Infectious Disease 2019 nCoV Working Group;Keeling MJ;Flasche S
通讯作者：
Flasche S