Optimal strategies to protect a sub-population at risk due to an established epidemic

Optimal strategies to protect a sub-population at risk due to an established epidemic
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保护因既定流行病而面临风险的亚人群的最佳策略

DOI:
10.1101/2021.09.10.459742
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发表时间:
2021
期刊:
--
影响因子:
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通讯作者:
Bussell E
Bussell E
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文献类型:
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作者:
Bussell E

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流行病尤其可能威胁到某些亚群体。例如,对于严重急性呼吸综合征冠状病毒2(SARS-CoV-2),老年人往往优先受到保护。对于植物和动物疾病,某些亚种群可以推动缓解,因为它们在生态、经济、社会文化或政治方面的价值更高。在这里,我们使用最优控制理论来确定策略,以最佳地保护一个“高价值”的亚群时,有一个有限的预算和流行病学的不确定性。我们使用的保护红杉国家公园在加州面临的大规模持续全州范围内流行的橡树猝死(引起疫霉ramorum)作为案例研究。我们关注的是,控制是否应该完全集中在国家公园本身,或者在周围的“缓冲区”治疗日益增长的流行病是否可以更有利可图。我们发现,根据感染率和正在进行的流行病的规模,集中控制高价值地区往往是最佳的。但是,只有当当地疫情增长时,优先级才能从缓冲区切换到高值区。我们的特点是任何开关的时间取决于流行病学和逻辑参数,并测试鲁棒性,由于不完善的先验知识,这些因素的系统性误指定。
Epidemics can particularly threaten certain sub-populations. For example, for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the elderly are often preferentially protected. For diseases of plants and animals, certain sub-populations can drive mitigation because they are intrinsically more valuable for ecological, economic, socio-cultural or political reasons. Here, we use optimal control theory to identify strategies to optimally protect a ‘high-value’ sub-population when there is a limited budget and epidemiological uncertainty. We use protection of the Redwood National Park in California in the face of the large ongoing state-wide epidemic of sudden oak death (caused byPhytophthora ramorum) as a case study. We concentrate on whether control should be focused entirely within the National Park itself, or whether treatment of the growing epidemic in the surrounding ‘buffer region’ can instead be more profitable. We find that, depending on rates of infection and the size of the ongoing epidemic, focusing control on the high-value region is often optimal. However, priority should sometimes switch from the buffer region to the high-value region only as the local outbreak grows. We characterize how the timing of any switch depends on epidemiological and logistic parameters, and test robustness to systematic misspecification of these factors due to imperfect prior knowledge.
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