RAPID: RETrofitting REsiliency AgainsT COVID-19! (RETREAT COVID-19!)

在人口密集的城市环境中，天然气、电力和供水网络等物质基础设施系统是帮助减缓COVID-19疫情传播的居家避难政策的关键推动因素。然而，从基础设施的角度来看，这些政策导致天然气、电力和水的消耗主要转向住宅而不是商业社区，这可能面临对基础设施服务的不同寻常的需求概况，可能导致中断和无法（或能力有限）为受庇护的人口群体服务。即使不考虑COVID-19疫情的影响，这种中断造成的死亡人数在社会上也是不可接受的。例如，仅在有医疗保险的美国人中，居住在家中依赖电力的估计人数为68.5万人（2012年），其中大约五分之一的人甚至容易受到3-4小时的短暂停电的影响。该提案的主要目标是利用来自纽约市的真实基础设施和公共卫生数据，分析不同疾病爆发情景下的基础设施运营，并为基础设施运营商和城市规划者提供有效的策略，以减轻公共卫生风险。在这些分析中，项目小组将特别注重脆弱人口群体的需要。本建议的主要技术目标是弥合目前基础设施和流行病模型之间的差距，以了解基础设施服务的需求在不同的爆发情景下如何变化。为此，我们将首先在基础设施模型中内部化卫生流行病的影响。流行病模型将包括易感-感染-易感（SIS）和易感-感染-恢复（SIR）模型，这使得合理地模拟流感和流感（SIS）以及麻疹、腮腺炎、风疹（SIR）等传染病的传播成为可能。其次，我们的研究团队将利用纽约市新冠肺炎疫情的真实数据和天然气、电力、交通和水系统的模型，在不同的疫情情景下进行基础设施脆弱性分析，并适当设计以代表新冠肺炎疫情的潜在轨迹(例如：“钟形”形状（当爆发达到峰值然后逐渐衰减时）或“W”形状（当爆发可以有多个峰值时）。我们将开发关键基础设施设备（水泵、气体压缩机、电力变压器）的停机模型，以便充分捕捉由于疫情期间非典型和转移使用而导致这些资源加速损耗的情况。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

In densely populated urban environments, such physical infrastructure systems as gas, electric power and water networks are critical enablers of shelter-at-home policies that help slow down the spread of the COVID-19 outbreak. However, from the infrastructure viewpoint, these policies cause a major shift of gas, electricity and water consumption to residential rather than commercial neighborhoods, which may face unusual demand profiles for infrastructure services, possibly leading to outages and inability (or limited ability) to serve sheltered population groups. Such outages take societally unacceptable death tolls, even without factoring in the effect of the COVID-19 outbreak. For example, only among medically insured Americans, the estimated number of electricity-dependent persons residing at home was 685,000 (2012), among whom roughly one fifth is vulnerable to even short 3-4 hour power outages. The main goal of this proposal is to analyze infrastructure operations under different scenarios of disease outbreaks, using real-life infrastructure and public health data from New York City, and inform infrastructure operators and urban planners on efficient strategies to mitigate public health risks. In these analyses, the project team will specially focus on needs of vulnerable population groups.The main technical objective of this proposal is to bridge the current gap between infrastructure and epidemic models to understand how the demand of infrastructure services change under different outbreak scenarios. To this end, we will first internalize the effects of health epidemics in infrastructure models. The epidemics model will include Susceptible-Infectious-Susceptible (SIS) and Susceptible-Infectious-Recovered (SIR) models, which make it possible to reasonably simulate the spread of infectious diseases as flu and influenza (SIS) and measles, mumps, rubella (SIR). Second, using real-life data on the COVID-19 outbreak in NYC and models of gas, electricity, transportation and water systems, our research team will carry out an infrastructure vulnerability analysis under different outbreak scenarios, which will be appropriately designed to represent potential trajectories of the COVID-19 outbreak (e.g. "bell" shape, when the outbreak peaks and then gradually decays or the "W" shape, when the outbreak can have multiple peaks). We will develop outage models of critical infrastructure equipment (water pumps, gas compressors, electric power transformers) in order to adequately capture accelerated wear-and-tear of these resources due to the atypical and shifted usage during the outbreaks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.