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

在人口稠密的城市环境中，天然气、电力和供水网络等实体基础设施系统是居家庇护政策的关键推动因素，有助于减缓COVID-19疫情的传播。然而，从基础设施的角度来看，这些政策导致天然气、电力和水的消费主要转向住宅区而不是商业区，这可能会面临对基础设施服务的不寻常需求，可能导致停电和无法（或能力有限）为受保护的人口群体提供服务。即使不考虑COVID-19疫情的影响，此类停电也会造成社会无法接受的死亡人数。例如，仅在医疗保险的美国人中，居住在家中的电力依赖者的估计数量为685，000（2012年），其中大约五分之一容易受到即使是短暂的3 - 4小时停电的影响。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情况，并向基础设施运营商和城市规划者提供有效策略，以减轻公共卫生风险。在这些分析中，项目团队将特别关注弱势人群的需求，本提案的主要技术目标是弥合基础设施和疫情模型之间的现有差距，以了解不同疫情情景下基础设施服务需求的变化。为此，我们将首先在基础设施模型中内化健康流行病的影响。流行病模型将包括易感-传染-易感（SIS）和易感-传染-传染-传播（SIR）模型，这使得有可能合理地模拟流感和流行性感冒（SIS）以及麻疹、腮腺炎、风疹（SIR）等传染病的传播。第二，我们的研究团队将利用纽约市COVID-19疫情的真实数据以及天然气、电力、交通和供水系统的模型，在不同的疫情情景下进行基础设施脆弱性分析，这些情景将被适当设计，以代表COVID-19疫情的潜在轨迹（例如，"钟"形，当爆发达到峰值然后逐渐衰减时，或者"W"形，当爆发可以具有多个峰值时）。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，以充分捕捉这些资源在疫情期间由于非典型和转移使用而加速磨损的情况。该奖项反映了NSF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.