Pandey Bhartendu, Gu Jianyu, Ramaswami Anu
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540 USA.
National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401 USA.
NPJ Urban Sustain. 2022;2(1):26. doi: 10.1038/s42949-022-00071-z. Epub 2022 Oct 28.
Understanding spatial determinants, i.e., social, infrastructural, and environmental features of a place, which shape infectious disease is critically important for public health. We present an exploration of the spatial determinants of reported COVID-19 incidence across India's 641 urban and rural districts, comparing two waves (2020-2021). Three key results emerge using three COVID-19 incidence metrics: cumulative incidence proportion (aggregate risk), cumulative temporal incidence rate, and severity ratio. First, in the same district, characteristics of COVID-19 incidences are similar across waves, with the second wave over four times more severe than the first. Second, after controlling for state-level effects, urbanization (urban population share), living standards, and population age emerge as positive determinants of both risk and rates across waves. Third, keeping all else constant, lower shares of workers working from home correlate with greater infection risk during the second wave. While much attention has focused on intra-urban disease spread, our findings suggest that understanding spatial determinants human settlements is also important for managing current and future pandemics.
了解空间决定因素,即塑造传染病的一个地方的社会、基础设施和环境特征,对公共卫生至关重要。我们对印度641个城乡地区报告的新冠疫情发病率的空间决定因素进行了探索,比较了两个时期(2020 - 2021年)。使用三个新冠疫情发病率指标得出了三个关键结果:累计发病率比例(总体风险)、累计时间发病率和严重程度比。首先,在同一地区,不同时期新冠疫情发病率的特征相似,第二波疫情的严重程度是第一波的四倍多。其次,在控制了邦一级的影响因素后,城市化(城市人口占比)、生活水平和人口年龄成为不同时期风险和发病率的正向决定因素。第三,在其他条件不变的情况下,居家办公的员工比例较低与第二波疫情期间更高的感染风险相关。虽然很多注意力都集中在城市内部的疾病传播上,但我们的研究结果表明,了解人类住区的空间决定因素对于管理当前和未来的疫情也很重要。