RESUMEN
The world witnessed the emergence of a deadly virus in December 2019, later named COVID-19. The virus was found to be highly contagious, and so people across the world were highly prone to be affected by the virus. Being a virus-borne disease, developing a vaccine was one of the most promising remedies. Thus, research organizations across the globe started working on developing the vaccine. However, it was later found by many researchers that a large number of people were hesitant to receive the vaccine. This paper aims to study the acceptance and hesitancy levels of people in India and compares them with the acceptance and hesitancy levels of people from the UK, the USA, and the rest of the world by analyzing their tweets on Twitter. For this study, 2,98,452 tweets were fetched from January 2020 to March 2022 from Twitter, and 1,84,720 tweets from 1,22,960 unique users were selected based on their country of origin. Machine learning based Sentiment analysis is then used to evaluate and analyze the tweets. The paper also proposes an NLP-based algorithm to perform opinion mining on Twitter data. The study found the public sentiment of the Indian population to be 63% positive, 28% neutral, and 9% negative. While the worldwide sentiment distribution is 45% positive, 34% neutral, and 21% negative, the USA has 42% positive, 34% neutral, and 23% negative and the UK has 50% positive, 29% neutral, and 21% negative. Also, sentiment analysis for individual vaccines in Indian context resulted in "Covaxin" with the highest positive sentiment at 43% followed by "Covishield" at 36%. The outcome of this work yields an insight into the public perception of the COVID-19 vaccine and thus can be used to formulate policies for existing and future vaccine campaigns. This study becomes more relevant as it is the consolidated opinion of Indian people, which is versatile in nature.
RESUMEN
Sex and gender matter to health outcomes, but despite repeated commitments to sex-disaggregate data in health policies and programmes, a persistent and substantial absence of such data remains especially in lower-income countries. This represents a missed opportunity for monitoring and identifying gender-responsive, evidence-informed solutions to address a key driver of the pandemic. In this paper we review the availability of national sex-disaggregated surveillance data on COVID-19 and examine trends on the testing-to-outcome pathway. We further analyse the availability of data according to the economic status of the country and investigate the determinants of sex differences, including the national gender inequality status (according to a global index) in each country. Results are drawn from 18 months of global data collection from over 200 countries. We find differences in COVID-19 prevention behaviours and illness outcomes by sex, with lower uptake of vaccination and testing plus an elevated risk of severe disease and death among men. Supporting and maintaining the collection, collation, interpretation and presentation of sex-disaggregated data requires commitment and resources at subnational, national and global levels, but provides an opportunity for identifying and taking gender-responsive action on health inequities. As a first step the global health community should recognise, value and support the importance of sex-disaggregated data for identifying and tackling an inequitable pandemic.
RESUMEN
Sex and gender matter to health outcomes, but despite repeated commitments to sex-disaggregate data in health policies and programmes, a persistent and substantial absence of such data remains especially in lower-income countries. This represents a missed opportunity for monitoring and identifying gender-responsive, evidence-informed solutions to address a key driver of the pandemic. In this paper we review the availability of national sex-disaggregated surveillance data on COVID-19 and examine trends on the testing-to-outcome pathway. We further analyse the availability of data according to the economic status of the country and investigate the determinants of sex differences, including the national gender inequality status (according to a global index) in each country. Results are drawn from 18 months of global data collection from over 200 countries. We find differences in COVID-19 prevention behaviours and illness outcomes by sex, with lower uptake of vaccination and testing plus an elevated risk of severe disease and death among men. Supporting and maintaining the collection, collation, interpretation and presentation of sex-disaggregated data requires commitment and resources at subnational, national and global levels, but provides an opportunity for identifying and taking gender-responsive action on health inequities. As a first step the global health community should recognise, value and support the importance of sex-disaggregated data for identifying and tackling an inequitable pandemic.