Effect of 2021 assembly election in India on COVID-19 transmission

Systematic literature review of postponed elections during COVID-19: Campaigns, regulations, and budgets

The postponement of elections during the COVID-19 pandemic reflects a decline in global democracy. The policy of postponing elections due to health concerns, regulatory changes, and economic crises lacks empirical evidence. Several studies suggest that holding elections in countries that proceed with them does not significantly impact the spread of COVID-19. The acceleration of COVID-19 transmission is not limited to countries holding elections; it affects all countries, including those postponing them. Moreover, countries that continue to hold elections have turned this challenge into a COVID-19 mitigation strategy. This study aimed to analyze the findings of original research on election execution during the COVID-19 pandemic, focusing on campaign activities, regulatory changes, and election budgeting. It employed systematic literature review using 12 articles from the Web of Science and Scopus databases. The results show that conducting elections during the COVID-19 pandemic does not contribute to the spread of the virus. This is evident through the adoption of blended campaign strategies by the candidates. Election committees have adjusted voting procedures, including increasing the number of polling stations, tightly scheduling voter arrivals, and visiting red zone lockdown areas to prevent mass mobilization. The increase in election budgets during an economic crisis is not solely for the elections themselves but also for reinforcing health protocols. This research recommends a reconsideration of election postponements and advocates for conducting elections during the COVID-19 pandemic to uphold democracy. Furthermore, future research should explore the social and political implications, as well as the long-term consequences for democracy, which result from the implementation of soft campaign strategies and voting system modifications on a global scale, all in the pursuit of preserving democracy.

Impact of air pollutants on COVID-19 transmission: a study over different metropolitan cities in India

India is affected strongly by the Coronavirus and within a short period, it becomes the second-highest country based on the infected case. Earlier, there was an indication of the impact of pollution on COVID-19 transmission from a few studies with early COVID-19 data. The study of the effect of pollution on COVID-19 in Indian metropolitan cities is ideal due to the high level of pollution and COVID-19 transmission in these cities. We study the impact of different air pollutants on the spread of coronavirus in different cities in India. A correlation is studied with daily confirmed COVID-19 cases with a daily mean of ozone, particle matter (PM) in size ≤ 10 μ m, carbon monoxide, sulfur dioxide, and nitrogen dioxide of different cities. It is found that particulate matter concentration decreases during the nationwide lockdown period and the air quality index improves for different Indian regions. A correlation between the daily confirmed cases with particulate matter (PM2.5 and PM10 both) is observed. The air quality index also shows a positive correlation with the daily confirmed cases for most of the metropolitan Indian cities. The correlation study also indicates that different air pollutants may have a role in the spread of the virus.

Impact of climate on COVID-19 transmission: A study over Indian states

Coronavirus Disease-2019 (COVID-19) started in Wuhan province of China in November 2019 and within a short time, it was declared as a worldwide pandemic by World Health Organisation due to the very fast worldwide spread of the virus. There are a few studies that look for the correlation with infected individuals and different environmental parameters using early data of COVID-19 but there is no study so far that deals with the variation of effective reproduction number and environmental factors. Effective reproduction number is the driving parameter of the spread of a pandemic and it is important to study the effect of various environmental factors on effective reproduction number to understand the effect of those factors on the spread of the virus. We have used time-dependent models to investigate the variation of different time-dependent driving parameters of COVID-19 like effective reproduction number and contact rate using data from India as a test case. India is a large population country that is highly affected due to the COVID-19 pandemic and has a wide span of different temperature and humidity regions and is ideal for such study. We have studied the impact of temperature and humidity on the spread of the virus of different Indian states using time-dependent epidemiological models SIRD, and SEIRD for a long time scale. We have used a linear regression method to look for any dependency between the effective reproduction number with the relative humidity, absolute humidity, and temperature. The effective reproduction number shows a negative correlation with both relative and absolute humidity for most of the Indian states, which are statistically significant. This implies that relative and absolute humidity may have an important role in the variation of effective reproduction number. Most of the states (six out of ten) show a positive correlation while two (out of ten) show a negative correlation between effective reproduction number and average air temperature for both SIRD and SEIRD models.