Post-lockdown changes of age-specific susceptibility and its correlation with adherence to social distancing measures.
Post-lockdown changes of age-specific susceptibility and its correlation with adherence to social distancing measures.
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DOI：
10.1038/s41598-022-08566-6
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发表时间：
2022-03-17
影响因子：
4.6
通讯作者：
Lopman BA
中科院分区：
文献类型：
--
作者：
Lau MSY;Liu C;Siegler AJ;Sullivan PS;Waller LA;Shioda K;Lopman BA
社会距离措施在减少整个社区传播方面是有效的，但关于它们如何影响更精细的规模动态，仍有许多未知之处。特别是，关于这些措施引起的接触模式和其他行为(包括坚持社交距离)的变化可能如何影响不同年龄段之间更精细的传播动态，目前尚不清楚。在本文中，我们建立了一个随机的年龄传播模型，系统地刻画了美国佐治亚州解除封锁前后年龄传播动力学的程度和变化。我们利用报告的年龄特定病例、血清阳性率和死亡率数据，进行贝叶斯(缺失)数据扩充模型推断。我们估计，在宣布避难所就地命令的大约一周内，总体人口水平的传播率降至41.2%，95%的可信区间为封锁前的水平[39%，43.8%]。虽然随后在解禁后有所上升，但仅在大约一个月后反弹至解禁前的62%[58%，67.2%]。我们还发现，在禁闭期间，感染的易感性随着年龄的增加而增加。具体来说，相对于年龄最大的年龄组(>； 65+)，最小年龄组(0-17岁)的易感性为0.13[0.09，0.18]，18-44岁的易感增加到0.53[0.49，0.59]，45-的易感增加到0.75[0.68，0.82]。更重要的是，我们的结果揭示了封锁解除后特定年龄的易感性(定义为在包含年龄相关行为因素的传染病接触期间感染的平均风险)的明显变化，这一趋势与报告的特定年龄对社会距离和预防措施的坚持程度基本一致。具体地说，较老的组(>； 45)(依从性最高)似乎具有最显著的敏感性降低(例如，锁定后的敏感度降至6+ 组解禁前估计的31.6%[29.3%，34%])。最后，我们发现不同年龄组的病例报告存在异质性，0-17岁组的病例报告异质性最低(9.7%[6.4%，19%])。我们的结果提供了对严格封锁措施的影响的更基本的了解，并提供了更好的证据，表明其他社会距离和预防措施可能在减少SARS-CoV-2传播方面有效。这些结果可能被用来指导在许多当前环境下(全球疫苗接种率低和新出现的变种)以及在未来新病原体的潜在暴发中更有效地实施这些措施。
Social distancing measures are effective in reducing overall community transmission but much remains unknown about how they have impacted finer-scale dynamics. In particular, much is unknown about how changes of contact patterns and other behaviors including adherence to social distancing, induced by these measures, may have impacted finer-scale transmission dynamics among different age groups. In this paper, we build a stochastic age-specific transmission model to systematically characterize the degree and variation of age-specific transmission dynamics, before and after lifting the lockdown in Georgia, USA. We perform Bayesian (missing-)data-augmentation model inference, leveraging reported age-specific case, seroprevalence and mortality data. We estimate that overall population-level transmissibility was reduced to 41.2% with 95% CI [39%, 43.8%] of the pre-lockdown level in about a week of the announcement of the shelter-in-place order. Although it subsequently increased after the lockdown was lifted, it only bounced back to 62% [58%, 67.2%] of the pre-lockdown level after about a month. We also find that during the lockdown susceptibility to infection increases with age. Specifically, relative to the oldest age group (> 65+), susceptibility for the youngest age group (0–17 years) is 0.13 [0.09, 0.18], and it increases to 0.53 [0.49, 0.59] for 18–44 and 0.75 [0.68, 0.82] for 45–64. More importantly, our results reveal clear changes of age-specific susceptibility (defined as average risk of getting infected during an infectious contact incorporating age-dependent behavioral factors) after the lockdown was lifted, with a trend largely consistent with reported age-specific adherence levels to social distancing and preventive measures. Specifically, the older groups (> 45) (with the highest levels of adherence) appear to have the most significant reductions of susceptibility (e.g., post-lockdown susceptibility reduced to 31.6% [29.3%, 34%] of the estimate before lifting the lockdown for the 6+ group). Finally, we find heterogeneity in case reporting among different age groups, with the lowest rate occurring among the 0–17 group (9.7% [6.4%, 19%]). Our results provide a more fundamental understanding of the impacts of stringent lockdown measures, and finer evidence that other social distancing and preventive measures may be effective in reducing SARS-CoV-2 transmission. These results may be exploited to guide more effective implementations of these measures in many current settings (with low vaccination rate globally and emerging variants) and in future potential outbreaks of novel pathogens.
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DOI：
10.1097/ede.0000000000001361
发表时间：
2021-07-01
期刊：
Epidemiology (Cambridge, Mass.)
影响因子：
--
作者：
Shioda K;Lau MSY;Kraay ANM;Nelson KN;Siegler AJ;Sullivan PS;Collins MH;Weitz JS;Lopman BA
通讯作者：
Lopman BA
影响因子：
5.6
作者：
Siegler, Aaron J.;Sullivan, Patrick S.;Bradley, Heather
通讯作者：
Bradley, Heather
DOI：
10.1073/pnas.2011802117
发表时间：
2020-09-08
影响因子：
11.1
作者：
Lau, Max S. Y.;Grenfell, Bryan;Lopman, Ben
通讯作者：
Lopman, Ben
影响因子：
8.8
作者：
Eikenberry, Steffen E.;Mancuso, Marina;Gumel, Abba B.
通讯作者：
Gumel, Abba B.
影响因子：
16.8
作者：
Lau, Max S. Y.;Becker, Alexander D.;Grenfell, Bryan T.
通讯作者：
Grenfell, Bryan T.