摘要翻译：
在大流行病或流行病中，公共卫生当局需要迅速对大量个人进行检测，以确定治疗路线，并了解感染的传播情况，以计划遏制、缓解和未来的应对措施。然而，缺乏足够的检测试剂盒可能是一个瓶颈，特别是在新冠肺炎等未预料到的新疾病的情况下，那里的检测技术、制造能力、分销、人力技能和实验室可能无法获得或短缺。此外，标准聚合酶链反应检测的费用约为48美元，这对贫困患者和大多数ZF来说是望而却步的。我们通过提出一种测试方法来解决这个瓶颈，该方法将来自两个（或更多）患者的样本集中在一个测试中。关键的见解是，从汇集的样本中得出的单一阴性结果可能意味着所有单个患者的阴性感染。从而排除了对患者进行进一步测试的可能性。因此，该协议需要的测试要少得多。然而，这可能会导致假阴性的增加。我们的模拟显示，将两个潜在感染可能性为7%的患者的样本结合起来，意味着所需的检测试剂盒减少了36%，检测时间单位增加了14%。
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英文标题：
《Accelerated infection testing at scale: a proposal for inference with
  single test on multiple patients》
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作者：
Tarun Jain, Bijendra Nath Jain
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最新提交年份：
2020
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  In pandemics or epidemics, public health authorities need to rapidly test a large number of individuals, both to determine the line of treatment as well as to know the spread of infection to plan containment, mitigation and future responses. However, the lack of adequate testing kits could be a bottleneck, especially in the case of unanticipated new diseases, such as COVID-19, where the testing technology, manufacturing capability, distribution, human skills and laboratories might be unavailable or in short supply. In addition, the cost of the standard PCR test is approximately USD 48, which is prohibitive for poorer patients and most governments. We address this bottleneck by proposing a test methodology that pools the sample from two (or more) patients in a single test. The key insight is that a single negative result from a pooled sample likely implies negative infection of all the individual patients. and It thereby rules out further tests for the patients. This protocol, therefore, requires significantly fewer tests. This may, however, result in somewhat increased false negatives. Our simulations show that combining samples from two patients with 7% underlying likelihood of infection implies that 36% fewer test kits are required, with 14% additional units of time for testing.
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PDF链接：
https://arxiv.org/pdf/2003.13282