疫情暴发后的前100天：药物、行为和数字干预措施的相互作用——基于智能体建模的研究
First 100 days of pandemic; an interplay of pharmaceutical, behavioral and digital interventions -- A study using agent based modeling
AI总结：
本研究利用基于智能体模型模拟疫情前100天的干预组合，发现行为与数字干预可减轻药物负担，且检测追踪比疫苗接种更具成本效益。
摘要：
流行病，特别是最近的COVID-19疫情，对公共卫生和全球经济都产生了影响。因此，为了应对未来可能的疫情暴发，需要深入了解疾病传播动态和有效的应对策略。在本文中，我们强调了基于智能体模型（ABM）在捕捉复杂感染动态和理解干预措施影响方面的潜力。我们模拟了现实的药物、行为和数字干预措施，这些措施反映了现实世界政策采纳中的挑战，并建议将这些干预措施进行整体组合以应对疫情。利用这些模拟，我们基于华盛顿州国王县的真实社会人口和地理普查数据，研究了大规模人群中涌现行为的趋势。我们的分析揭示了疫情暴发后的前100天在决定疫情进程中的关键作用，强调了快速决策和高效政策制定的重要性。此外，我们指出，投资于行为和数字干预措施可以通过减少总感染人数和住院人数，以及推迟疫情高峰的到来，来减轻药物干预措施的负担。我们还推断，将相同数额的资金用于广泛的检测、接触者追踪和自我隔离，比将全部预算用于疫苗接种更具成本效益。
英文摘要：
Pandemics, notably the recent COVID-19 outbreak, have impacted both public health and the global economy. A profound understanding of disease progression and efficient response strategies is thus needed to prepare for potential future outbreaks. In this paper, we emphasize the potential of Agent-Based Models (ABM) in capturing complex infection dynamics and understanding the impact of interventions. We simulate realistic pharmaceutical, behavioral, and digital interventions that mirror challenges in real-world policy adoption and suggest a holistic combination of these interventions for pandemic response. Using these simulations, we study the trends of emergent behavior on a large-scale population based on real-world socio-demographic and geo-census data from Kings County in Washington. Our analysis reveals the pivotal role of the initial 100 days in dictating a pandemic's course, emphasizing the importance of quick decision-making and efficient policy development. Further, we highlight that investing in behavioral and digital interventions can reduce the burden on pharmaceutical interventions by reducing the total number of infections and hospitalizations, and by delaying the pandemic's peak. We also infer that allocating the same amount of dollars towards extensive testing with contact tracing and self-quarantine offers greater cost efficiency compared to spending the entire budget on vaccinations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
