Analysis and nding the correlation of air quality parameters on the spread and deceased case of COVID-19 patients in India

Recent covid-19 pandemic state across the globe has brought some issues to be considered obviously for better sustainability of human society and economy. In this article a comprehensive study based on the air quality parameters has been represented in view the recent covid-19 situation in India. India being the second largest populated country in the world and having a very high population density is a vital region for controlling and observing the spread and recovery of covid-19 patients. It has been observed that the spread as well as recovery rate in India is far better than many other countries in the world. A noteworthy observation has been extracted in this study from the correlation between three Covid-19 parameters (total conrmed, active and deceased cases) and air quality index comprising of six air quality parameters (PM 2.5, PM 10, NO 2 , SO 2 , CO, and Ozone) of 25 highly Covid-19 affected Indian cities. Spearman rank correlation and Kendall correlation tests were used to understand the correlation between the Covid-19 variables with air quality variables. Both the statistical correlation test revealed that particulate matters like PM 2.5, PM 10, and overall air quality have signicantly strong correlation with the Covid-19 spread and death cases in 25 cities of India. However, the PM 2.5 is found to be the most signicant air quality parameter for Covid-19 spread and death cases in India. It indicates that the western part of India contains more risk zones as compared to the north-eastern and eastern part of the country. The high natural vegetation, less industrial areas of the northeast India with better air quality nds higher recovery rate. Similarly the high natural vegetation of the Himalayan zones are also comparatively having better air quality and experiencing better control of covid-19 cases.


Introduction
The entire world is recently passing through a very critical pandemic situation. Within four months as on April 2020, the world has lost more than 230,000 people and about 3,250,000 people affected. The gures are still increasingacross the globe. Many countries are severely affected. It has therefore become necessary to extract out and obtain the information of all relevant parameters like atmospheric pollution (Fattorini et  in India is far better and much under control. Thus it creates a space for studies to analyze and nd the factors appeared in favor of better control, and obtaining the correlation of those factors. This has therefore become necessary to obtain the knowledge of signi cant factors, that would becomeuseful for the human society considering the future of the coming days in world, and to manage its economic state towards a better direction. In the present time the spread, recovery and mortality rate of Covid-19 patients can be assumed to be broadly dependent onfour factors like (a) societal and human behavioral factor(b) treatment and health infrastructure. (c) local environmental factors and (d) individuals health immunity power. Out of these four factors the rst factor controls the spread of the virus in the society. The other factors are mainly related with the recovery and mortality rates. The second factor in India is not too satisfactory. Still India is in a comparatively better position indicates somewhat related with long term environmental effects over the individuals health and immunity power. Being inspired with this we have undertaken an objective to obtain a correlation of environmental parameters with the spread of the covid-19 cases within India.
According to the report of the World Health Organization (WHO), around 4.2 million deaths per year occur due to air pollution and more than 90% of the world's population lives in areas where the air quality is unsafe. In the study conducted by IQAir, AirVisual and Greenpeace, India is found to have seven of the worst 10 cities having the worst air quality in the world. Prolonged exposure to unhealthy air causes various lung ailments that explicitly spell danger in human beings. As severe respiratory problems are known to be related with air quality of individuals living site (Sharma et  Hence, in this study, the correlation between Covid-19 spread, death cases and air quality index comprising of six air quality parameters (PM 2.5, PM 10, NO 2 , SO 2 , CO, Ozone) of 25 highly affected Indian cities have been analyzed and the most signi cant air quality parameters linked with Covid-19 were also evaluated. This study indicates that there is a signi cant correlation between the spread and recovery of Covid-19 patients with the air quality parameters.

Methodology Of Study
This objective of the study is mostlyto nd the correlation between the air quality and Covid-19 pandemic in India. Therefore the methodology of this study is established on air quality and Covid-19 data collection and analysis, and it is detailed in the following sections.

Selection of region of study
This study has been conducted on different areas of India. The population distribution in India has a wide spectrum. As the spread of virus is highly related with the density of population and socioeconomic activities, it is rational to focus on the cities of the country with comparatively high population density.
Twenty ve different cities located at various parts of the country have been identi ed and selected for this study. The Fig.1 shows the places of population density distribution in India (Census report of Government of India).

Data sources and collection scheme
Data has been collected from two different types of sources, rst one is the data source related to the spread of Covid-19, and mortality, and the other is the data source of air quality index at different affected areas. The Covid-19 data of different places of India were collected from the website of Ministry of Health and Family welfare, Government of India (Ministry of Health and Family welfare, Government of India). The period of data collection was from 30 th January 2020 to 5 th May 2020. Among 28 states of India, several cities of the states like Maharashtra, Gujarat, Delhi, Rajasthan, Madhya Pradesh, Tamil Nadu, Uttar Pradesh, Telengana, West Bengal, Karnataka, and Punjub are designated as hotspot for Covid-19 in India. Based on the above, 25 major cities,which are also hotspot of Covid-19 have been considered in this study. The list of 25 considered cities along with their Covid-19 patient details are mentioned in Table 1. Covid-19 data which have been included in this research are total con rmed, active, and deceased cases for each city as on 5 th May 2020. The 25 number cities were selected based on two criteria, (i) cities with high infection rate of Covid-19 cases, and (ii) availability of su cient air quality index (AQI) data for those cities. The air quality index (AQI)data of the considered cities were collected from the web portal of the  Table 2. This is clear from the table that higher the pollutant AQI value, poorer is the air quality. Based on the concentration of any particular air pollutant, subsequent standards and possible health problems, a sub-index is determined for each of these air pollutants.
Subsequently the most awful sub-index indicates the overall AQI. Detailed methodology for calculation of pollutant AQI and overall AQI under the National Air Quality Index (IND-AIQ) can be obtained from the report of National Air Quality Index, Control of urban pollution series, CUPS/82/2014-15.

Correlation between air quality and Covid-19 cases
On observing and comparing the Fig.1 and Fig.2 one can easily realize that the spread of Covid-19 is not only and signi cantly associated with the population density in India. That is also a reason, which has driven us to consider the matter of prevailing air quality with Covid-19 spread in different places of India. Initially the Spearman and Kendallcorrelation coe cients between total covid-19 cases with seven AQI values for 25 cities are determined. The obtained coe cientvalues and the signi cance of each correlation coe cient value (with 95% con dence level and two tail test) are shown in Table 3 Fig. 4. Su ciently good agreement between total con rmed Covid-19 cases and PM 2.5 AQI can be observed in most of the considered location, resulting to highest correlation between them.   Fig.6 for most of the considered cities in India.
Hence it can be concluded that PM 2.5 is the most critical air quality parameter affecting Covid-19 spread (total con rmed and actives cases) as well as deceased cases in different locations of India as depicted in Fig. 7

Con ict of Interest Statement
On behalf of all authors, the corresponding author states that there is no con ict of interest.