A data-driven metapopulation model for the Belgian COVID-19 epidemic: assessing the impact of lockdown and exit strategies.
A data-driven metapopulation model for the Belgian COVID-19 epidemic: assessing the impact of lockdown and exit strategies.
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DOI：
10.1186/s12879-021-06092-w
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发表时间：
2021-05-30
影响因子：
3.7
通讯作者：
Hens N
中科院分区：
文献类型：
--
作者：
Coletti P;Libin P;Petrof O;Willem L;Abrams S;Herzog SA;Faes C;Kuylen E;Wambua J;Beutels P;Hens N
为应对持续的COVID-19疫情，多个国家采取不同程度的社交距离措施。对于许多国家来说，在成功遏制了第一波之后，封锁措施逐渐取消。在比利时，这种救济从5月4日的第一阶段开始，在接下来的几周内进行了几个后续阶段。我们分析了根据比利时分阶段退出策略放宽严格封锁措施的预期影响。我们开发了一个随机的，数据知情的，元人口模型，占比利时的年龄结构人口的混合和流动性。该模型根据每日住院数据进行校准，能够在国家一级重现疫情。我们考虑解除封锁的不同情景，并以疫情前社会混合和流动性的相对减少来量化。我们通过与封锁期间和之后收集的社交联系数据进行比较来验证我们的假设。我们的模型能够成功描述比利时的COVID-19第一波疫情，并将休闲/其他活动期间的互动确定为退出策略的关键。事实上，我们发现，与重新开始休闲活动和重新开放工作场所相比，学校重新开放的影响较小。我们还评估了新（疑似）感染病例隔离的影响，发现它允许重新建立相对更多的社会互动，同时仍然确保疫情控制。没有观察到预测第二波住院的情景，这表明每个接触的感染概率相对于封锁前时期发生了变化。休闲活动中的接触被认为是最有影响力的，其次是专业接触和学校接触，分别为即将到来的第二波COVID-19。因此，定期重新评估人群中的社会接触对于适应可能影响流行病扩散的不断演变的行为变化至关重要。在线版本包含补充材料，可在（10.1186/s12879-021-06092-w）获得。
In response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree. For many countries, after successfully curbing the initial wave, lockdown measures were gradually lifted. In Belgium, such relief started on May 4th with phase 1, followed by several subsequent phases over the next few weeks. We analysed the expected impact of relaxing stringent lockdown measures taken according to the phased Belgian exit strategy. We developed a stochastic, data-informed, meta-population model that accounts for mixing and mobility of the age-structured population of Belgium. The model is calibrated to daily hospitalization data and is able to reproduce the outbreak at the national level. We consider different scenarios for relieving the lockdown, quantified in terms of relative reductions in pre-pandemic social mixing and mobility. We validate our assumptions by making comparisons with social contact data collected during and after the lockdown. Our model is able to successfully describe the initial wave of COVID-19 in Belgium and identifies interactions during leisure/other activities as pivotal in the exit strategy. Indeed, we find a smaller impact of school re-openings as compared to restarting leisure activities and re-openings of work places. We also assess the impact of case isolation of new (suspected) infections, and find that it allows re-establishing relatively more social interactions while still ensuring epidemic control. Scenarios predicting a second wave of hospitalizations were not observed, suggesting that the per-contact probability of infection has changed with respect to the pre-lockdown period. Contacts during leisure activities are found to be most influential, followed by professional contacts and school contacts, respectively, for an impending second wave of COVID-19. Regular re-assessment of social contacts in the population is therefore crucial to adjust to evolving behavioral changes that can affect epidemic diffusion. The online version contains supplementary material available at (10.1186/s12879-021-06092-w).
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影响因子：
3.8
作者：
Abrams S;Wambua J;Santermans E;Willem L;Kuylen E;Coletti P;Libin P;Faes C;Petrof O;Herzog SA;Beutels P;Hens N
通讯作者：
Hens N
影响因子：
19
作者：
Heavey, Laura;Casey, Geraldine;McDarby, Geraldine
通讯作者：
McDarby, Geraldine
影响因子：
3.5
作者：
Eubank, S.;Eckstrand, I;Barrett, C. L.
通讯作者：
Barrett, C. L.
影响因子：
9.3
作者：
Jarvis, Christopher I.;Van Zandvoort, Kevin;Edmunds, W. John
通讯作者：
Edmunds, W. John
影响因子：
4.6
作者：
Coletti P;Wambua J;Gimma A;Willem L;Vercruysse S;Vanhoutte B;Jarvis CI;Van Zandvoort K;Edmunds J;Beutels P;Hens N
通讯作者：
Hens N