Analyzing COVID-19 Vaccination Sentiments in Nigerian Cyberspace: Insights from a Manually Annotated Twitter Dataset (preprint)

Numerous successes have been achieved in combating the COVID-19 pandemic, initially using various precautionary measures like lockdowns, social distancing, and the use of face masks. More recently, various vaccinations have been developed to aid in the prevention or reduction of the severity of the COVID-19 infection. Despite the effectiveness of the precautionary measures and the vaccines, there are several controversies that are massively shared on social media platforms like Twitter. In this paper, we explore the use of state-of-the-art transformer-based language models to study people's acceptance of vaccines in Nigeria. We developed a novel dataset by crawling multi-lingual tweets using relevant hashtags and keywords. Our analysis and visualizations revealed that most tweets expressed neutral sentiments about COVID-19 vaccines, with some individuals expressing positive views, and there was no strong preference for specific vaccine types, although Moderna received slightly more positive sentiment. We also found out that fine-tuning a pre-trained LLM with an appropriate dataset can yield competitive results, even if the LLM was not initially pre-trained on the specific language of that dataset.

Association between neighborhood overcrowdedness, multigenerational households, and COVID-19 in New York City

IMPACT: Patients living in overcrowded zip codes were at increased risk of contracting severe COVID-19 after controlling for confounding disease and socioeconomic factors OBJECTIVES/GOALS: This study sought to examine whether residences in over-crowded zip codes with higher reported over-crowding represented an independent risk factor for severe COVID-19 infection, defined by presentation to an emergency department. METHODS/STUDY POPULATION: In this zip code tabulated area (ZCTA)-level analysis, we used NYC Department of Health disease surveillance data in March 2020 merged with data from the CDC and ACS to model suspected COVID-19 case rates by zip code over-crowdedness (households with greater than 1 occupant per room, in quartiles). We defined suspected COVID-19 cases as emergency department reported cases of pneumonia and influenza-like illness. Our final model employed a multivariate Poisson regression models with controls for known COVID-19 clinical (prevalence of obesity, coronary artery disease, and smoking) and related socioeconomic risk factors (percentage below federal poverty line, median income by zip-code, percentage White, and proportion of multigenerational households) after accounting for multicollinearity. RESULTS/ANTICIPATED RESULTS: Our analysis examined 39,923 suspected COVID-19 cases across 173 ZCTAs in NYC between March 1 and March 30 2020. We found that, after adjusted analysis, for every quartile increase in defined over-crowdedness, case rates increased by 32.8% (95% CI: 22.7%% to 34.0%, P < 0.001). DISCUSSION/SIGNIFICANCE OF FINDINGS: Over-crowdedness by zip code may be an independent risk factor for severe COVID-19. Social distancing measures such as school closures that increase house-bound populations may inadvertently worsen the risk of COVID-19 contraction in this setting.

Racial and Neighborhood-Level Disparities in COVID-19 Incidence among Patients on Hemodialysis in New York City.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected socially disadvantaged populations. Whether disparities in COVID-19 incidence related to race/ethnicity and socioeconomic factors exist in the hemodialysis population is unknown. METHODS: Our study involved patients receiving in-center hemodialysis in New York City. We used a validated index of neighborhood social vulnerability, the Social Vulnerability Index (SVI), which comprises 15 census tract-level indicators organized into four themes: socioeconomic status, household composition and disability, minority status and language, and housing type and transportation. We examined the association of race/ethnicity and the SVI with symptomatic COVID-19 between March 1, 2020 and August 3, 2020. COVID-19 cases were ascertained using PCR testing. We performed multivariable logistic regression to adjust for demographics, individual-level social factors, dialysis-related medical history, and dialysis facility factors. RESULTS: Of the 1378 patients on hemodialysis in the study, 247 (17.9%) developed symptomatic COVID-19. In adjusted analyses, non-Hispanic Black and Hispanic patients had significantly increased odds of COVID-19 compared with non-Hispanic White patients. Census tract-level overall SVI, modeled continuously or in quintiles, was not associated with COVID-19 in unadjusted or adjusted analyses. Among non-Hispanic White patients, the socioeconomic status SVI theme, the minority status and language SVI theme, and housing crowding were significantly associated with COVID-19 in unadjusted analyses. CONCLUSIONS: Among patients on hemodialysis in New York City, there were substantial racial/ethnic disparities in COVID-19 incidence not explained by neighborhood-level social vulnerability. Neighborhood-level socioeconomic status, minority status and language, and housing crowding were positively associated with acquiring COVID-19 among non-Hispanic Whites. Our findings suggest that socially vulnerable patients on dialysis face disparate COVID-19-related exposures, requiring targeted risk-mitigation strategies.

Impact of COVID-19 on vulnerable patients with rheumatic disease: results of a worldwide survey.

OBJECTIVE: There is emerging evidence that COVID-19 disproportionately affects people from racial/ethnic minority and low socioeconomic status (SES) groups. Many physicians across the globe are changing practice patterns in response to the COVID-19 pandemic. We sought to examine the practice changes among rheumatologists and what they perceive the impact to be on their most vulnerable patients. METHODS: We administered an online survey to a convenience sample of rheumatologists worldwide during the initial height of the pandemic (between 8 April and 4 May 2020) via social media and group emails. We surveyed rheumatologists about their opinions regarding patients from low SES and racial/ethnic minority groups in the context of the COVID-19 pandemic. Mainly, what their specific concerns were, including the challenges of medication access; and about specific social factors (health literacy, poverty, food insecurity, access to telehealth video) that may be complicating the management of rheumatologic conditions during this time. RESULTS: 548 rheumatologists responded from 64 countries and shared concerns of food insecurity, low health literacy, poverty and factors that preclude social distancing such as working and dense housing conditions among their patients. Although 82% of rheumatologists had switched to telehealth video, 17% of respondents estimated that about a quarter of their patients did not have access to telehealth video, especially those from below the poverty line. The majority of respondents believed these vulnerable patients, from racial/ethnic minorities and from low SES groups, would do worse, in terms of morbidity and mortality, during the pandemic. CONCLUSION: In this sample of rheumatologists from 64 countries, there is a clear shift in practice to telehealth video consultations and widespread concern for socially and economically vulnerable patients with rheumatic disease.

Hydroxychloroquine and Chloroquine in COVID-19: A Survey of Prescription Patterns Among Rheumatologists.

OBJECTIVE: With hydroxychloroquine (HCQ) and chloroquine (CQ) emerging as potential therapies for coronavirus disease 2019 (COVID-19), shortages have been reported. We aimed to understand how rheumatologists, one of the most common prescribers of HCQ/CQ, prescribed these medications to manage COVID-19 and to understand if their patients are affected by shortages. METHODS: Between April 8 and April 27, 2020, an online survey was distributed to a convenience sample of rheumatologists who practice medicine in a diverse range of settings globally, resulting in 506 responses. Adjusted Poisson regression models were calculated. RESULTS: Only 6% of respondents prescribed HCQ/CQ for COVID-19 prophylaxis, and only 12% for outpatient treatment of COVID-19. Compared to the United States, the likelihood of prescribing HCQ/CQ for prophylaxis was higher in India (adjusted risk ratio [aRR], 6.7; 95% confidence interval [CI], 2.7-16.8; p < 0.001). Further, compared to the United States and those with 1 to 5 years of experience, rheumatologists in Europe (aRR, 2.9; 95% CI, 1.6-5.3; p < 0.001) and those with 10+ years of experience (11-20 years: aRR, 2.5; 95% CI, 1.2-5.3; p = 0.015; 21+ years: aRR = 3.3; 95% CI, 1.4-7.4; p = 0.004) had a higher likelihood of prescribing HCQ/CQ for outpatient treatment. Of note, 71% of all rheumatologists reported that their patients were directly affected by HCQ/CQ shortages. CONCLUSION: The results suggest that only a small percentage of rheumatologists are prescribing HCQ/CQ for prophylaxis or outpatient treatment of COVID-19. Medication shortages experienced by large numbers of autoimmune disease patients are concerning and should play a role in decisions, especially given poor efficacy data for HCQ/CQ in COVID-19.