Statistical modeling approach for PM10 prediction before and during confinement by COVID-19 in South Lima, Perú.

A total of 188,859 meteorological-PM[Formula: see text] data validated before (2019) and during the COVID-19 pandemic (2020) were used. In order to predict PM[Formula: see text] in two districts of South Lima in Peru, hourly, daily, monthly and seasonal variations of the data were analyzed. Principal Component Analysis (PCA) and linear/nonlinear modeling were applied. The results showed the highest annual average PM[Formula: see text] for San Juan de Miraflores (SJM) (PM[Formula: see text]-SJM: 78.7 [Formula: see text]g/m[Formula: see text]) and the lowest in Santiago de Surco (SS) (PM[Formula: see text]-SS: 40.2 [Formula: see text]g/m[Formula: see text]). The PCA showed the influence of relative humidity (RH)-atmospheric pressure (AP)-temperature (T)/dew point (DP)-wind speed (WS)-wind direction (WD) combinations. Cool months with higher humidity and atmospheric instability decreased PM[Formula: see text] values in SJM and warm months increased it, favored by thermal inversion (TI). Dust resuspension, vehicular transport and stationary sources contributed more PM[Formula: see text] at peak times in the morning and evening. The Multiple linear regression (MLR) showed the best correlation (r = 0.6166), followed by the three-dimensional model LogAP-LogWD-LogPM[Formula: see text] (r = 0.5753); the RMSE-MLR (12.92) exceeded that found in the 3D models (RMSE [Formula: see text]) and the NSE-MLR criterion (0.3804) was acceptable. PM[Formula: see text] prediction was modeled using the algorithmic approach in any scenario to optimize urban management decisions in times of pandemic.

Association between air pollution in Lima and the high incidence of COVID-19: findings from a post hoc analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) originated in the People's Republic of China in December 2019. Thereafter, a global logarithmic expansion of cases occurred. Some countries have a higher rate of infections despite the early implementation of quarantine. Air pollution might be related to high susceptibility to the virus and associated case fatality rates (deaths/cases*100). Lima, Peru, has the second highest incidence of COVID-19 in Latin America and also has one the highest levels of air pollution in the region. METHODS: This study investigated the association of levels of PM2.5 exposure in previous years (2010-2016) in 24 districts of Lima with cases, deaths and case fatality rates for COVID-19. Multiple linear regression was used to evaluate this association controlled by age, sex, population density and number of food markets per district. The study period was from March 6 to June 12, 2020. RESULTS: There were 128,700 cases in Lima and 2382 deaths due to COVID-19. The case fatality rate was 1.93%. Previous exposure to PM2.5 (2010-2016) was associated with the number of COVID-19- cases (ß = 0.07; 95% CI: 0.034-0.107) and deaths (ß = 0.0014; 95% CI: 0.0006-0.0.0023) but not with the case fatality rate. CONCLUSIONS: After adjusting for age, sex and number of food markets, the higher rates of COVID-19 in Metropolitan Lima are attributable to the increased PM2.5 exposure in the previous years, among other reasons. Reduction in air pollution from a long-term perspective and social distancing are needed to prevent the spread of virus outbreaks.

Association Between Air Pollution in Lima and the High Incidence of COVID-19: Findings from a Post Hoc Analysis.

BACKGROUND: Corona virus disease (COVID-19) originated in China in December 2019. Thereafter, a global logarithmic expansion of the cases has occurred. Some countries have a higher rate of infections despite of early implementation of quarantine. Air pollution could be related to the high susceptibility to SARS-CoV-2 and the associated case-fatality rates (deaths/cases*100). Lima, Peru has the second highest incidence of COVID-19 in Latin America and it is also one of the cities with highest levels of air pollution in the Region. METHODS: This study investigated the association of the levels of PM2.5 exposure in the previous years (2010-2016) in 24 districts of Lima with the cases, deaths and case-fatality rates of COVID-19. RESULTS: Until June 12, 2020, there were 6,308 deaths and 220,749 SARS-CoV-2 positive cases in Peru. In Lima, the total number of COVID-19 deaths in all metropolitan areas was 2,382. The case-fatality rate at the national level was 2.58% and 1.93% in Lima. Higher PM2.5 levels are associated with higher number of cases and deaths of COVID-19. The case-fatality rate (Deaths/cases*100) did not increase with the increase in PM2.5 levels. A higher number of food markets was associated with higher incidence and mortality of COVID-19 (p < 0.01 for both); these associations persisted when cases (r = 0.49; p < 0.01) and deaths (r = 0.58; p < 0.01) were adjusted by the population density. The association of PM2.5 with cases of COVID-19 was maintained after controlling analysis by age, sex and number of food markers. CONCLUSIONS: the higher rates of COVID-19 in Metropolitan Lima is attributable, among others, to the increased PM2.5 exposure in the previous years after adjusting for age, sex and number of food markets. Reduction of air pollution since a long term perspective, and social distancing are needed to prevent spreads of virus outbreak.