Transmission Dynamics and Control of COVID-19: A Mathematical Modelling Study

We look at the SQIRP mathematical model for new coronavirus transmission in Bangladesh and India in this study. The basic reproduction number of the SQIRP system is designed using the next cohort matrix process. The SQIRP system has asymptotically stable locally at an infection-free equilibrium point when the basic reproduction number is not more than unity and unsteady when the value is greater than unity. The SQIRP system is found to go through a backward bifurcation, which is a novel perspective for Coronavirus infection transmission. The infection-free equilibrium and endemic equilibrium are shown to be asymptotically stable globally using the Lyapunov function hypothesis and the invariance principle of Lasalle. A SQIRP system with backward bifurcation is explored using stochastic analysis. The ecological stochasticity in the appearance of white noise best describes the system's value. To verify the results, more numerical simulations are run © 2023 L&H Scientific Publishing, LLC. All rights reserved

Analysis of Fuzzy Dynamics of SEIR COVID-19 Disease Model

The objective of this article is to build an SEIR epidemic system for episode COVID-19 (novel crown) with fuzzy numbers. Mathematical models might assist with investigating the transmission elements, forecast and control of Covid-19. The fuzziness in the infection rate, increased death owing to COVID-19, and recovery rate from COVID-19 were all deemed fuzzy sets, and their member functions were used as fuzzy parameters in the SEIR system. The age lattice technique is used in the SEIR system to calculate the fuzzy basic reproduction number and the system’s stability at infection-free and endemic equilibrium points. Computer simulations are provided to comprehend the subtleties of the proposed SEIR COVID-19 model. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

On modelling growing menace of household emissions under COVID-19 in Indian metros.

While local anthropogenic emission sources contribute largely to deteriorate metro air quality, long range transport can also play a significant role in influencing levels of pollutants, particularly carbon monoxide (CO) that has a relatively long life span. A nationwide lockdown of two months imposed across India amid COVID-19 led to a dramatic decline in major sources of emissions except for household, mainly from cooking. This initially led to declined levels of CO in two of the largest megacities of India, Delhi and Mumbai under stable weather conditions, followed by a distinctly different variability under the influence of prevailing mesoscale circulation. We hereby trace the sources of CO from local emissions to transport pathways and interpret the observed variability in CO using the interactive WRF-Chem model and back trajectory analysis. For this purpose, COVID-19 emission inventory of CO has been estimated. Model results indicate a significant contribution from externally generated CO in Delhi from surrounding regions and an unusual peak on 17th May amid lockdown due to long range transport from the source region of biofuel emissions in central India. However, the oceanic winds played a larger role in keeping CO levels in check in a coastal megacity Mumbai which otherwise has high CO emissions from household sources due to a larger share of urban slums. Keeping track of evolving carbon-intensive pathways can help inform government responses to the COVID-19 pandemic to prioritize controls of emissions sources.

COVID-19 lockdown and air quality of SAFAR-India metro cities

A drastic decline in the sources of emissions of pollutants under COVID-19 induced lockdown resulted in an unprecedented trends in most hazardous pollutants PM2.5, PM10 and NO2 in India. To realize the impact of lockdown in the concentrations of PM2.5, PM10 and NO2, we compared the trend of lockdown period (20nd March to 15th April) with several (3–7) years of past data in four Indian mega cities (Delhi, Pune, Mumbai, and Ahmedabad) of different micro-climate and geography. The significant reduction in the concentrations of NO2 in the ranges of ~60–65% is noticed in four megacities within the lockdown period when compared with the averaged data of past years. However, relatively low reduction in PM2.5 (~25–50%) and PM10 (~36–50%) is observed and city to city variation is found to be significant. The prevailing secondary aerosol formation and enhancement of any natural source of emissions could be some factors preventing PM2.5 levels to go down significantly. Under near negligible fossil fuel emission, contrary to the expectation, an increase in the ratio as compared to normal scenario is observed in Delhi on some days whereas on some selected days, PM2.5/PM10 ratio is found to decline significantly.

Towards baseline air pollution under COVID-19: implication for chronic health and policy research for Delhi, India

The Megacity of Delhi, home to 19 million inhabitants, is infamous for its poor air quality mainly due to anthropogenic emissions. While the COVID-19 pandemic is a health emergency, lockdown due to it saw an unprecedented decline in emission sources of pollutants by ~85%-90% in Delhi, resulting in sharp decline in the concentration of majority of pollutants. Here we report the experimental estimate of baseline level that is defined as the minimum level reached after lockdown under consistent fair weather condi-tion of major criteria pollutants. This may be consi-dered as an indicator of the background levels to which the population is chronically exposed. The con-sequences of such chronic air pollution exposure are excess respiratory and cardiovascular morbidity and mortality which are reported to be more serious than severe pollution episodes by epidemiologists. As the lockdown which was imposed on 24 March 2020, was extended during April and May, we present the pre-vailing ambient pollution levels and compare them with the baseline levels. Results are based on India’s largest monitoring network of 34 stations in Delhi. The findings are critical for policymakers to fine-tune ambient air quality standards and regulations leading to the development of effective risk management poli-cies and control strategies. © 2020. All rights reserved.

COVID-19 and environmental -weather markers: Unfolding baseline levels and veracity of linkages in tropical India.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is rapidly spreading across the globe due to its contagion nature. We hereby report the baseline permanent levels of two most toxic air pollutants in top ranked mega cities of India. This could be made possible for the first time due to the unprecedented COVID-19 lockdown emission scenario. The study also unfolds the association of COVID-19 with different environmental and weather markers. Although there are numerous confounding factors for the pandemic, we find a strong association of COVID-19 mortality with baseline PM2.5 levels (80% correlation) to which the population is chronically exposed and may be considered as one of the critical factors. The COVID-19 morbidity is found to be moderately anti-correlated with maximum temperature during the pandemic period (-56%). Findings although preliminary but provide a first line of information for epidemiologists and may be useful for the development of effective health risk management policies.