Using Twitter to Understand COVID-19 Vaccine-Related Ageism During the Pandemic.

BACKGROUND AND OBJECTIVES: During the rollout of coronavirus 2019 (COVID-19) vaccines, older adults in high-income countries were often prioritized for inoculation in efforts to reduce COVID-19-related mortality. However, this prioritization may have contributed to intergenerational tensions and ageism, particularly with the limited supply of COVID-19 vaccines. This study examines Twitter discourse to understand vaccine-related ageism during the COVID-19 pandemic to inform future vaccination policies and practices to reduce ageism. RESEARCH DESIGN AND METHODS: We collected 1,369 relevant tweets on Twitter using the Twint application in Python from December 8, 2020, to December 31, 2021. Tweets were analyzed using thematic analysis, and steps were taken to ensure rigor. RESULTS: Our research identified four main themes including (a) blame and hostility: "It's all their fault"; (b) incompetence and misinformation: "clueless boomer"; (c) ageist political slander; and (d) combatting ageism: advocacy and accessibility. DISCUSSION AND IMPLICATIONS: Our findings exposed issues of victim-blaming, hate speech, pejorative content, and ageist political slander that is deepening the divide of intergenerational conflict. Although a subset of tweets countered negative outcomes and demonstrated intergenerational solidarity, our findings suggest that ageism may have contributed to COVID-19 vaccine hesitancy among older adults. Consequently, urgent action is needed to counter vaccine misinformation, prohibit aggressive messaging, and promote intergenerational unity during the COVID-19 pandemic and beyond.

Social vulnerability indices: a scoping review.

BACKGROUND: Social vulnerability occurs when the disadvantage conveyed by poor social conditions determines the degree to which one's life and livelihood are at risk from a particular and identifiable event in health, nature, or society. A common way to estimate social vulnerability is through an index aggregating social factors. This scoping review broadly aimed to map the literature on social vulnerability indices. Our main objectives were to characterize social vulnerability indices, understand the composition of social vulnerability indices, and describe how these indices are utilized in the literature. METHODS: A scoping review was conducted in six electronic databases to identify original research, published in English, French, Dutch, Spanish or Portuguese, and which addressed the development or use of a social vulnerability index (SVI). Titles, abstracts, and full texts were screened and assessed for eligibility. Data were extracted on the indices and simple descriptive statistics and counts were used to produce a narrative summary. RESULTS: In total, 292 studies were included, of which 126 studies came from environmental, climate change or disaster planning fields of study and 156 studies were from the fields of health or medicine. The mean number of items per index was 19 (SD 10.5) and the most common source of data was from censuses. There were 122 distinct items in the composition of these indices, categorized into 29 domains. The top three domains included in the SVIs were: at risk populations (e.g., % older adults, children or dependents), education, and socioeconomic status. SVIs were used to predict outcomes in 47.9% of studies, and rate of Covid-19 infection or mortality was the most common outcome measured. CONCLUSIONS: We provide an overview of SVIs in the literature up to December 2021, providing a novel summary of commonly used variables for social vulnerability indices. We also demonstrate that SVIs are commonly used in several fields of research, especially since 2010. Whether in the field of disaster planning, environmental science or health sciences, the SVIs are composed of similar items and domains. SVIs can be used to predict diverse outcomes, with implications for future use as tools in interdisciplinary collaborations.