At the end of February 2020, Peru started the first cases of pneumonia associated with coronavirus (COVID-19), they were reported in Lima, Peru (Rodriguez-Morales et al., 2020). Therefore, the first week on March started with 72 infected people, the government published new law for a national crisis by COVID-19 pandemic (Vizcarra et al., 2020), with a quarantine in each city of Peru. Our analysis has considered March and April 2020, for air quality measurement and infections in Lima, the data collected on 6 meteorological stations with CO (carbon monoxide), NO₂ (nitrogen oxide), O₃ (ozone), SO₂ (sulfur dioxide), PM₁₀ and PM_2.5 (particle matter with diameter aerodynamic less than 2.5 and 10 m respectively). As a result, the average of these concentrations and the hospital information is recollected per hour. This analysis is executed during the quarantine an important correlation is discovered in the zone with highest infection by COVID-19, NO₂ and PM₁₀, even though in a reduction of air pollution in Lima. In this paper, we proposed a classification model by Reduced-Space Gaussian Process Regression for air pollution and infections; with technological and environmental dynamics and global change associated COVID-19. An evaluation of zones in Lima city, results have demonstrated influence of industrial influence in air pollution and infections by COVID-19 before and after quarantine during the last 28 days since the first infection in Peru; the problems relating to data management were validated with a successful classification and cluster analysis for future works in COVID-19 influence by environmental conditions.

2020 年 2 月底，秘鲁开始出现第一例与冠状病毒 (COVID-19) 相关的肺炎病例，这些病例是在秘鲁利马报道的（Rodriguez-Morales 等，2020）。因此，从 3 月第一周就有 72 名感染者开始，政府针对 COVID-19 大流行的国家危机发布了新法律（Vizcarra 等，2020），并在秘鲁每个城市进行隔离。我们的分析考虑了2020年3月和4月利马的空气质量测量和感染情况，在6个气象站收集的数据包括CO（一氧化碳）、NO ₂（氮氧化物）、O ₃（臭氧）、SO ₂（二氧化硫） )、PM ₁₀和 PM _2.5（空气动力直径分别小于 2.5 和 10 m 的颗粒物）。因此，每小时都会收集这些浓度的平均值和医院信息。这项分析是在隔离期间执行的，尽管利马的空气污染有所减少，但在 COVID-19、NO ₂和 PM _{10感染最高的地区发现了重要的相关性。}在本文中，我们提出了一种针对空气污染和感染的降空间高斯过程回归分类模型；与 COVID-19 相关的技术和环境动态以及全球变化。对利马市各区域的评估结果显示，自秘鲁首次感染以来的过去 28 天内，工业对空气污染和隔离前后的 COVID-19 感染产生了影响；通过成功的分类和聚类分析，验证了与数据管理相关的问题，以供未来研究 COVID-19 受环境条件影响的工作使用。