Pritchard Alexander J, Silk Matthew J, Carrignon Simon, Bentley R Alexander, Fefferman Nina H
NIMBioS, National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, USA.
Centre for Ecology and Conservation, University of Exeter Penryn Campus, UK.
Infect Dis Model. 2022 Apr 6;7(2):106-116. doi: 10.1016/j.idm.2022.04.001. eCollection 2022 Jun.
Reporting of epidemiological data requires coordinated action by numerous agencies, across a multitude of logistical steps. Using collated and reported information to inform direct interventions can be challenging due to associated delays. Mitigation can, however, occur indirectly through the public generation of concern, which facilitates adherence to protective behaviors. We utilized a coupled-dynamic multiplex network model with a communication- and disease-layer to examine how variation in reporting delay and testing probability are likely to impact adherence to protective behaviors, such as reducing physical contact. Individual concern mediated adherence and was informed by new- or active-case reporting, at the population- or community-level. Individuals received information from the communication layer: direct connections that were sick or adherent to protective behaviors increased their concern, but absence of illness eroded concern. Models revealed that the relative benefit of timely reporting and a high probability of testing was contingent on how much information was already obtained. With low rates of testing, increasing testing probability was of greater mitigating value. With high rates of testing, maximizing timeliness was of greater value. Population-level reporting provided advanced warning of disease risk from nearby communities; but we explore the relative costs and benefits of delays due to scale against the assumption that people may prioritize community-level information. Our findings emphasize the interaction of testing accuracy and reporting timeliness for the indirect mitigation of disease in a complex social system.
报告流行病学数据需要众多机构在众多后勤步骤上采取协调行动。由于相关延迟，利用整理和报告的信息为直接干预提供依据可能具有挑战性。然而，缓解可以通过公众产生的关注间接发生，这有助于人们遵守保护行为。我们使用了一个具有通信层和疾病层的耦合动态多重网络模型，来研究报告延迟和检测概率的变化如何可能影响对保护行为的遵守，例如减少身体接触。个人关注介导了遵守行为，并受到人群或社区层面新病例或现患病例报告的影响。个体从通信层获取信息：生病或遵守保护行为的直接联系会增加他们的关注，但没有疾病则会削弱关注。模型显示，及时报告和高检测概率的相对益处取决于已经获得的信息量。在检测率较低时，提高检测概率具有更大的缓解价值。在检测率较高时，最大限度地提高及时性具有更大的价值。人群层面的报告提供了附近社区疾病风险的预警；但我们探讨了由于规模导致的延迟的相对成本和收益，与人们可能优先考虑社区层面信息的假设相对照。我们的研究结果强调了在复杂社会系统中检测准确性和报告及时性对疾病间接缓解的相互作用。
