A stochastic model for COVID-19 spread and the effects of Alert Level 4 in Aotearoa New Zealand
A stochastic model for COVID-19 spread and the effects of Alert Level 4 in Aotearoa New Zealand
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COVID-19 传播的随机模型以及新西兰 Aotearoa 4 级警报的影响
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
N. Steyn
中科院分区：
文献类型：
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作者：
M. Plank;Rachelle N. Binny;S. Hendy;Audrey Lustig;A. James;N. Steyn
虽然病例数量仍然很低，但全人口控制方法加上有效的追踪、检测和病例隔离，为新西兰提供了遏制和消除新冠肺炎的机会。我们使用一个随机模型来研究新西兰新冠肺炎的遏制和消除情景，因为新西兰正在考虑退出为期四周的强有力的4级人口控制措施。特别是，我们考虑了其病例隔离行动的有效性如何影响解除这些强有力的全人口控制的结果。该模型为新西兰设定了参数，并使用当前病例数据进行了初始化，尽管我们没有利用有关病例地理分布的信息，该模型也没有按年龄或合并疾病进行分层。我们发现，只要保持强有力的全人口控制，快速追踪和病例隔离(即维持与新西兰反应初期相当的速度的行动)就可以导致遏制或消除。只要保持强有力的4级人群控制，缓慢的病例隔离就可以导致遏制(但不是消除)。然而，我们发现，在四周后放松强有力的全人群控制最有可能导致进一步暴发，尽管通过快速病例隔离、追踪、检测或其他方式可以减缓疫情的增长速度。我们发现，只有在病例隔离与维持超过四周的强有力的全人群控制相结合的情况下，才有可能消除疫情。这一模型的进一步版本将包括年龄结构的人口，以及考虑地理分散和联系网络结构的影响、区域遏制的可能性以及区域间旅行限制的可能性，以及对高危社区和基本工作人员的潜在伤害。
While case numbers remain low, population-wide control methods combined with efficient tracing, testing, and case isolation, offer the opportunity for New Zealand to contain and eliminate COVID-19. We use a stochastic model to investigate containment and elimination scenarios for COVID-19 in New Zealand, as the country considers the exit from its four week period of strong Level 4 population-wide control measures. In particular we consider how the effectiveness of its case isolation operations influence the outcome of lifting these strong population-wide controls. The model is parameterised for New Zealand and is initialised using current case data, although we do not make use of information concerning the geographic dispersion of cases and the model is not stratified for age or co-morbidities. We find that fast tracing and case isolation (i.e. operations that are sustained at rates comparable to that at the early stages of New Zealand's response) can lead to containment or elimination, as long as strong population-wide controls remain in place. Slow case isolation can lead to containment (but not elimination) as long as strong Level 4 population-wide controls remain in place. However, we find that relaxing strong population-wide controls after four weeks will most likely lead to a further outbreak, although the speed of growth of this outbreak can be reduced by fast case isolation, by tracing, testing, or otherwise. We find that elimination is only likely if case isolation is combined with strong population-wide controls that are maintained for longer than four weeks. Further versions of this model will include an age-structured population as well as considering the effects of geographic dispersion and contact network structure, the possibility of regional containment combined with inter-regional travel restrictions, and the potential for harm to at risk communities and essential workers.