Community Perception about Air Pollution, Willingness to Pay and Awareness about Health Risks in Chandigarh, India

Air pollution is one of the major risk factors for mortality, as per the Global Burden of Diseases. Various natural and anthropogenic sources contribute to air pollution, which makes air quality worse. Community perceptions of air pollution are crucial in deciding how people will react and whether they will accept relevant policies. Therefore, people's awareness, behavior and perception must be known to engage communities in air pollution reduction. This study aimed to determine the levels and correlations between people's perceptions of pollution and health risk before COVID-19 and during the COVID-19 period in Chandigarh. The study was conducted following the interview schedule methodology using a standard questionnaire. Univariate and air pollution hotspot analysis was conducted to assess the correlation of variables and to evaluate the spatial variation in the perceived levels. The results revealed that 79.9% of respondents were worried about the city's air quality. It was observed that 39.2% of study participants perceived that automobile emissions were the primary source of air pollution. Association of sociodemographic factors with the awareness of air pollution, health effects, and people's attitudes was also assessed. The study observed a strong correlation between people's education status and their knowledge of air pollution during the COVID-19 period (p-value=0.064) and the pre-COVID period (p-value=0.035). On assessing the air quality perception and respondent's happiness as a place to live, participants' happiness was found to be strongly correlated with their neighborhood as a place to live with their opinion of the air quality (p-value=0.000). However, this correlation was insignificant during the COVID-19 period (p-value=0.192). Respondents perceived that exposure to air pollution is related to respiratory and chest problems. A linear relationship was observed between people's willingness to improve air quality and awareness, which shows a statistically significant association (0.076 and 0.001) during the COVID-19 and pre-COVID period. People's attitudes and actions towards air pollution suggested that people are willing to pay to mitigate air pollution to enhance environmental sustainability and quality of life.

Application of machine learning approaches to predict the impact of ambient air pollution on outpatient visits for acute respiratory infections

With a remarkable increase in industrialization among fast-developing countries, air pollution is rising at an alarming rate and has become a public health concern. The study aims to examine the effect of air pollution on patient's hospital visits for respiratory diseases, particularly Acute Respiratory Infections (ARI). Outpatient hospital visits, air pollution and meteorological parameters were collected from March 2018 to October 2021. Eight machine learning algorithms (Random Forest model, K-Nearest Neighbors regression model, Linear regression model, LASSO regression model, Decision Tree Regressor, Support Vector Regression, X.G. Boost and Deep Neural Network with 5-layers) were applied for the analysis of daily air pollutants and outpatient visits for ARI. The evaluation was done by using 5-cross-fold confirmations. The data was randomly divided into test and training data sets at a scale of 1:2, respectively. Results show that among the studied eight machine learning models, the Random Forest model has given the best performance with R2 = 0.606, 0.608 without lag and 1-day lag respectively on ARI patients and R2 = 0.872, 0.871 without lag and 1-day lag respectively on total patients. All eight models did not perform well with the lag effect on the ARI patient dataset but performed better on the total patient dataset. Thus, the study did not find any significant association between ARI patients and ambient air pollution due to the intermittent availability of data during the COVID-19 period. This study gives insight into developing machine learning programs for risk prediction that can be used to predict analytics for several other diseases apart from ARI, such as heart disease and other respiratory diseases.

COVID-19 pandemic: What can we learn for better air quality and human health?

The COVID-19 lockdown resulted in improved air quality in many cities across the world. With the objective of what could be the new learning from the COVID-19 pandemic and subsequent lockdowns for better air quality and human health, a critical synthesis of the available evidence concerning air pollution reduction, the population at risk and natural versus anthropogenic emissions was conducted. Can the new societal norms adopted during pandemics, such as the use of face cover, awareness regarding respiratory hand hygiene, and physical distancing, help in reducing disease burden in the future? The use of masks will be more socially acceptable during the high air pollution episodes in lower and middle-income countries, which could help to reduce air pollution exposure. Although post-pandemic, some air pollution reduction strategies may be affected, such as car-pooling and the use of mass transit systems for commuting to avoid exposure to airborne infections like coronavirus. However, promoting non-motorized modes of transportation such as cycling and walking within cities as currently being enabled in Europe and other countries could overshadow such losses. This demand focus on increasing walkability in a town for all ages and populations, including for a differently-abled community. The study highlighted that for better health and sustainability there. is also a need to promote other measures such as work-from-home, technological infrastructure, the extension of smart cities, and the use of information technology.

COVID-19 pandemic and sudden rise in crop residue burning in India: issues and prospects for sustainable crop residue management.

The seasonal burning of crop residue significantly affects the environment, leading to poor air quality over Indo-Gangetic Plain (IGP) in India. Hence, there have been significant efforts to minimize crop residue burning through policy, innovations, and awareness measures. However, an abrupt increase in paddy residue burning was observed over IGP during 2020. Hence, the study explores the factors leading to this sharp rise. The business as usual trends analysis revealed that paddy crop residue burning activities increased significantly (60%) in 2020 compared to the previous year. The massive increase in crop residue burning consequently seems to be linked with the COVID-19 pandemic, which affected the farmer's income, including the poor compliance by the regulatory authorities. The study also highlights the issues and prospects for sustainable crop residue management and explores the solutions to minimize crop residue burning. There are few crops in India that have guaranteed minimum sale price and are also subsidized. These provisions encourage farmers to grow those particular crops, resulting in the generation of large amounts of crop residue from these specific crops. There have been several efforts by the Indian government, including based on recent court intervention. Still, there is no respite from burning activities and the occurrence of Delhi winter smog every year. Hence, the study emphasizes a need to adopt integrated approaches having in situ eco-friendly solutions, which enhances the farmer's income and focuses on employability, capacity building, awareness generation, and in situ economically viable solutions.

Five probable factors responsible for the COVID-associated mucormycosis outbreak in India.

The second wave of COVID-19 due to the delta variant (B.1.617.2) led to a rapid rise in total coronavirus and COVID-associated mucormycosis cases reported from India. Hence, our study explored the possible causes of a rapid upsurge in COVID-associated mucormycosis, which has accounted for over 70% of global cases. Factors associated with the increase in mucormycosis cases in COVID-19 patients include diabetes mellitus, steroid overdose, high iron levels, and immunosuppression, combined with other possible factors, such as unhygienic conditions, prolonged hospitalization, use of ventilators, and leaky humidifiers in oxygen cylinders. These create an ideal environment for contracting mucormycosis. However, these cases could be reduced by disseminating simple preventive measures and creating awareness among the medical society and general public of this rare and deadly contagion of COVID-associated mucormycosis. The identification of early symptoms will also help to restrict the spread of lethal fungal diseases. Furthermore, a collaborative team of surgeons, ophthalmologists, physicians, and otolaryngologists would be required in the hospital wards to accelerate surgeries on severely impacted patients.

Does airborne pollen influence COVID-19 outbreak?

The fast spread of SARS-CoV-2 presented a worldwide challenge to public health, economy, and educational system, affecting wellbeing of human society. With high transmission rates, there are increasing evidences of COVID-19 spread via bioaerosols from an infected person. The current review was conducted to examine airborne pollen impact on COVID-19 transmission and to identify the major gaps for post-pandemic research. The study used all key terms to identify revenant literature and observation were collated for the current research. Based on existing literature, there is a potential association between pollen bioaerosols and COVID-19. There are few studies focusing the impact of airborne pollen on SARS-CoV-2, which could be useful to advance future research. Allergic rhinitis and asthma patients were found to have pre-modified immune activation, which could help to provide protection against COVID-19. However, does airborne pollen acts as a potent carrier for SARS-CoV-2 transport, dispersal and its proliferation still require multidisciplinary research. Further, a clear conclusion cannot be drawn due to limited evidence and hence more research is needed to show how pollen bioaerosols could affect virus survivals. The small but growing literature review focuses on searching for every possible answer to provide additional security layers to overcome near future corona-like infectious diseases.

Impact of COVID-19 lockdown on ambient air quality in megacities of India and implication for air pollution control strategies.

The impact of restrictions during various phases of COVID-19 lockdown on daily mean PM2.5 concentration in five Indian megacities (New Delhi, Chennai, Kolkata, Mumbai, and Hyderabad) was studied. The impact was studied for pre-lockdown (1st Mar-24th Mar 2020), lockdown (25th Mar-31st May 2020), and unlocking (1st Jun-31st Aug 2020) phases. The lockdown period comprises 4 lockdown phases with distinct measures, whereas the unlocking period had 3 phases. PM2.5 concentration reduced significantly in all megacities and met the national standards during the lockdown period. The maximum reduction in PM2.5 level was observed in Kolkata (62%), followed by Mumbai (49%), Chennai (34%), and New Delhi (26%) during the lockdown period. Comparatively, Hyderabad exhibited a smaller reduction in PM2.5 concentration, i.e., 10%. The average PM2.5 levels during the lockdown in the peak hour (i.e., 07:00-11:00 h) in New Delhi, Chennai, Kolkata, Mumbai, and Hyderabad decreased by 21.3%, 48.5%, 63.4%, 56.4%, and 23.8%, respectively, compared to those before lockdown period. During the unlocking period, except for Chennai, all megacities showed a reduction in average PM2.5 levels compared to concentrations in the lockdown period, but these reductions were mainly linked with monsoon rains in India. The current study provided an opportunity to study air pollution in the absence of major anthropogenic activities and during limited activities in monsoon season having an ecological design. The study reports a new baseline of PM2.5, except for monsoon, and explores this knowledge to plan future air pollution reduction strategies. The study also discusses how this new learning of knowledge could strengthen air pollution control policies for better air quality and sustainability.Graphical abstract.

Impact of COVID-19 lockdown on air quality in Chandigarh, India: Understanding the emission sources during controlled anthropogenic activities.

The variation in ambient air quality during COVID-19 lockdown was studied in Chandigarh, located in the Indo-Gangetic plain of India. Total 14 air pollutants, including particulate matter (PM10, PM2.5), trace gases (NO2, NO, NOx, SO2, O3, NH3, CO) and VOC's (benzene, toluene, o-xylene, m,p-xylene, ethylbenzene) were examined along with meteorological parameters. The study duration was divided into four parts, i.e., a) 21 days of before lockdown b) 21 days of the first phase of lockdown c) 19 days of the second phase of lockdown d) 14 days of the third phase of lockdown. The results showed significant reductions during the first and second phases for all pollutants. However, concentrations increased during the third phase. The concentrations of SO2, O3, and m,p-xylene kept on increasing throughout the study period, except for benzene, which continuously decreased. The percentage decrease in the concentrations during consecutive periods of lockdown were 28.8%, 23.4% and 1.1% for PM2.5 and 36.8%, 22.8% and 2.4% for PM10 respectively. The Principal Component Analysis (PCA) and characteristic ratios identified vehicular pollution as a primary source during different phases of lockdown. During the lockdown, residential sources showed a significant adverse impact on the air quality of the city. Regional atmospheric transfer of pollutants from coal-burning and stubble burning were identified as secondary sources of air pollution. The findings of the study offer the potential to plan air pollution reduction strategies in the extreme pollution episodes such as during crop residue burning period over Indo-Gangetic plain.

Rapid preparation of hand sanitizer using WHO formulation in hospital settings during restricted supply due to COVID-19 pandemic

Good hand hygiene practices include cleaning of hands either by handwash or by hand rub. In healthcare settings, it is not easy to wash hands with soap after seeing each patient and is time-consuming as doctors are already working overtime. Hence, in hospital settings, it is also recommended to use alcohol-based hand sanitizers that can rapidly kill microorganisms, which spread various contagious diseases. Amidst the COVID-19 outbreak, the demand for essential commodities such as hand sanitizer, masks, etc., increased and hampered the hospital supplies. To address the shortage and limited supply of hand sanitizers to the various medical and paramedical departments of a tertiary hospital, the Department of Community Medicine and School of Public Health in coordination with the Pharmacology and Medical Microbiology Department prepared hands sanitizers following the World Health Organization (WHO) guidelines. The paper discusses the procedure that was followed for the preparation of hand sanitizer to meet the institutional demand and motivate others in similar settings to address the issue of restricted supply during the COVID-19 pandemic.

Impact of the COVID-19 pandemic on clean fuel programmes in India and ensuring sustainability for household energy needs.

Clean cooking energy strategies are critical for reducing air pollution, improving health, and achieving related Sustainable Development Goals. The recent COVID-19 lockdowns may impact the transition towards clean cooking fuels. The nationwide lockdown is likely to affect key factors such as energy access, income, transportation, etc., that play a role in decisions influencing household fuel use. The rural population already bears the burden of poverty and may not be able to afford and access clean cooking fuels during the lockdown. They are thus vulnerable to reversion to their traditional cooking methods using solid biomass fuels. The household air pollution caused due to the use of polluting fuels increases their susceptibility to non-communicable diseases, and thus may intensify the risk and severity of COVID-19 infection. Hence, there is an urgent need to expand sustainable energy solutions worldwide. The present study applies the DPSIR modeling framework to establish a set of comprehensive indicators for addressing the transition towards clean cooking fuels during the COVID-19 pandemic. The study also provides insights on various strategies adopted in India in response to the COVID-19 pandemic for maintaining continuity of delivering benefits under a clean cookstove program. The study offers future directions to ensure the transition towards cleaner fuels and sustainability.

COVID-19 lockdown and its impact on tropospheric NO2 concentrations over India using satellite-based data.

The World Health Organization has declared the COVID-19 pandemic a global public health emergency. Many countries of the world, including India, closed their borders and imposed a nationwide lockdown. In India, the lockdown was declared on March 24 for 21 days (March 25-April 14, 2020) and was later extended until May 3, 2020. During the lockdown, all major anthropogenic activities, which contribute to atmospheric pollution (such as industries, vehicles, and businesses), were restricted. The current study examines the impact of the lockdown on tropospheric NO2 concentrations. Satellite-based ozone monitoring instrument sensor data were analyzed in order to investigate the variations in tropospheric NO2 concentrations. The results showed that from March 1 to 21, 2020, the average tropospheric NO2 concentration was 214.4 ×1013 molecule cm-2 over India, and it subsequently decreased by 12.1% over the next four weeks. An increase of 0.8% in tropospheric NO2 concentrations was observed for the same period in 2019 and hence, the reduced tropospheric NO2 concentrations can be attributed to restricted anthropogenic activities during the lockdown. In the absence of significant activities, the contribution of various sources was estimated, and the emissions from biomass burning were identified as a major source of tropospheric NO2 during the lockdown. The findings of this study provide an opportunity to understand the mechanism of tropospheric NO2 emissions over India, in order to improve air quality modeling and management strategies.

Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India.

Lockdown measures to contain COVID-19 pandemic has resulted in a considerable change in air pollution worldwide. We estimate the temporal and diurnal changes of the six criteria air pollutants, including particulate matter (PM2.5 and PM10) and gaseous pollutants (NO2, O3, CO, and SO2) during lockdown (25th March - 3rd May 2020) across regions of India using the observations from 134 real-time monitoring sites of Central Pollution Control Board (CPCB). Significant reduction in PM2.5, PM10, NO2, and CO has been found in all the regions during the lockdown. SO2 showed mixed behavior, with a slight increase at some sites but a comparatively significant decrease at other locations. O3 also showed a mixed variation with a mild increase in IGP and a decrease in the South. The absolute decrease in PM2.5, PM10, and NO2 was observed during peak morning traffic hours (08-10 Hrs) and late evening (20-24 Hrs), but the percentage reduction is almost constant throughout the day. A significant decrease in day-time O3 has been found over Indo Gangetic plain (IGP) and central India, whereas night-time O3 has increased over IGP due to less O3 loss. The most significant reduction (∼40-60%) was found in PM2.5 and PM10. The highest decrease in PM was found for the north-west and IGP followed by South and central regions. A considerable reduction (∼30-70%) in NO2 was found except for a few sites in the central region. A similar pattern was observed for CO having a ∼20-40% reduction. The reduction observed for PM2.5, PM10, NO2, and enhancement in O3 was proportional to the population density. Delhi's air quality has improved with a significant reduction in primary pollutants, however, an increase in O3 was observed. The changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations.

Higher body mass index is an important risk factor in COVID-19 patients: a systematic review and meta-analysis.

Globally, both obesity and underweight are severe health risks for various diseases. The current study systematically examined the emerging evidence to identify an association between body mass index (BMI) and COVID-19 disease outcome. Online literature databases (e.g., Google Scholar, PubMed, MEDLINE, EMBASE, Scopus, Medrixv and BioRixv) were screened following standard search strategy having the appropriate keyword such as "Obesity", "Underweight", "BMI", "Body Mass Index", "2019-nCov", "COVID-19, "novel coronavirus", "coronavirus disease". Studies published till 20th April 2020 were included without language restriction. These studies include case reports, case series, cohort, and any other which reported BMI, overweight/obesity or underweight, and its complication with COVID-19 disease. This study observed COVID-19 infection among BMI < 25 kg/m2 with prevalence of 0.60 (95%CI: 0.34-0.86, I2 = - 76.77) as compared to the 0.34 (95%CI: 0.23-0.44, I2 = 53.45% heterogeneity) having BMI > 25 kg/m2. The results of the current study show that BMI plays a significant role in COVID-19 severity in all age groups, especially the older individuals. A panel of doctors and nursing staff should review COVID-19 patients with higher BMI with other co-morbidities (diabetes and hypertension), and they should be given increased vigilance, priority in testing, and treatment to control the associated co-morbidities. Further, the COVID-19 patients whose illness entered 7-10 days, age > 50 years, and elevated CRP levels should be given additional medical considerations. Our finding showed that the population and patients with high BMI have moderate to high risk of medical complications with COVID-19, and hence, their health status should be monitored more frequently including monitoring of blood pressure and blood glucose.

Higher Body Mass Index is an Important Risk factor in COVID-19 patients: A Systematic Review (preprint)

Background: Globally, both obesity and underweight are severe health risks for various diseases. The current study systematically examines the emerging evidence to identify an association between Body Mass Index (BMI) and COVID-19 disease outcome. Methods: Online literature databases (e.g., Google Scholar, PubMed, MEDLINE, EMBASE, Scopus, Medrixv and BioRixv) were screened following standard search strategy having the appropriate keyword such as Obesity, Underweight, BMI, Body Mass Index, 2019-nCov, COVID-19, novel coronavirus, coronavirus disease. Studies published till 20th April 2020 were included without language restriction. These studies include case reports, case series, cohort, and any other which reported BMI, overweight/obesity or underweight, and its complication with COVID-19 disease. Findings: Obesity plays a significant part in the pathogenesis of COVID-19 patients, though the role of BMI in the COVID-19 pandemic must not be ignored. Interpretation: Consequences of inflammation of adipose tissue has been reported as a leading cause of insulin resistance and hypertension due to metabolic dysfunction. The results of the current study show that BMI plays a significant role in COVID-19 severity in all ages, especially the elderly population. A panel should review COVID-19 patients with higher BMI and other co-morbidities, and they should be given increased vigilance, testing priority, and therapy. Further, the COVID-19 patients whose illness entered 7-10 days, age >50 yrs, and elevated CRP levels should have additional medical considerations. Recommendation: Population and patients with high BMI have moderate to high risk of medical complications with COVID-19, and hence their health status should be monitored more frequently. Keywords: Age, BMI, COVID-19, Obesity.