Analysis of Language Translations of State Governments' Coronavirus Disease 2019 Vaccine Websites.

Introduction: During the coronavirus disease 2019 (COVID-19) vaccination campaign, non-English-communicating individuals have faced inequities in access to resources for vaccine education and uptake. We characterized the language translation status of states' COVID-19 vaccine websites to inform discussion on the sufficiency of translated information and strategies for expanding the availability of multilingual vaccine information. Methods: We identified the primary COVID-19 vaccine website for all 50 states, the District of Columbia, and the federal government ("jurisdictions") and determined the languages into which information about obtaining the vaccine (access) and vaccine safety and efficacy had been translated, as of October 2021. We compared these findings with data from the American Community Survey to determine how many individuals had these online resources available in their primary language. Results: Only 56% of jurisdictions provided professionally translated information about COVID-19 vaccine safety and efficacy, and only 50% provided professionally translated information about how to register for or obtain the COVID-19 vaccine, in at least one language. Consequently, ∼26 million Americans may not have accurate vaccine safety and efficacy information available, and ∼29 million Americans may not have vaccine access information available, from their jurisdiction in their primary language. Furthermore, translated information often was limited in scope and/or number of languages provided. Conclusion: Translation of COVID-19 vaccine information on state government websites currently is insufficient to meet the needs of non-English-communicating populations. This analysis can inform discussions about resource needs and operational considerations for adequate provision of multilingual, critical health information.

Web Accessibility and beyond in eGovernment Does Web Accessibility ensure accessibility to Administration s websites?

The undeniable progress in Web Accessibility can be contrasted with the scant impact on its application to the real Web world. This problem is especially serious when the Web is the only way to obtain specific services. In some countries, fundamental procedures such as interaction with Administration, health services, or banks, can exclusively be accessed through the Web. This issue became even more evident during the COVID-19 pandemic, when a significant sector of the population that does not have access to the Internet experienced important barriers to manage their situation. In addition to the technical problems, the digital and gender divide, which have a decisive effect on accessibility and condition the exercise of civil rights, are often disregarded by Web Accessibility studies. In this talk we will present our work on the accessibility of Administration's websites and, in addition, we will discuss the need of considering non-Technological accessibility barriers to find ways to alleviate them. © 2022 Owner/Author.

A language-matching model to improve equity and efficiency of COVID-19 contact tracing.

Contact tracing is a pillar of COVID-19 response, but language access and equity have posed major obstacles. COVID-19 has disproportionately affected minority communities with many non-English-speaking members. Language discordance can increase processing times and hamper the trust building necessary for effective contact tracing. We demonstrate how matching predicted patient language with contact tracer language can enhance contact tracing. First, we show how to use machine learning to combine information from sparse laboratory reports with richer census data to predict the language of an incoming case. Second, we embed this method in the highly demanding environment of actual contact tracing with high volumes of cases in Santa Clara County, CA. Third, we evaluate this language-matching intervention in a randomized controlled trial. We show that this low-touch intervention results in 1) significant time savings, shortening the time from opening of cases to completion of the initial interview by nearly 14 h and increasing same-day completion by 12%, and 2) improved engagement, reducing the refusal to interview by 4%. These findings have important implications for reducing social disparities in COVID-19; improving equity in healthcare access; and, more broadly, leveling language differences in public services.

Understanding and Addressing Latinx COVID-19 Disparities in Washington State.

The COVID-19 pandemic has exposed, and intensified, health inequities faced by Latinx in the United States. Washington was one of the first U.S. states to report cases of COVID-19. Public health surveillance shows that 31% of Washington cases are Latinx, despite being only 13% of the state population. Unjust policies related to immigration, labor, housing, transportation, and education have contributed to both past and existing inequities. Approximately 20% of Latinx are uninsured, leading to delays in testing and medical care for COVID-19, and early reports indicated critical shortages in professional interpreters and multilingual telehealth options. Washington State is taking action to address some of these inequities. Applying a health equity framework, we describe key factors contributing to COVID-19-related health inequities among Latinx populations, and how Washington State has aimed to address these inequities. We draw on these experiences to make recommendations for other Latinx communities experiencing COVID-19 disparities.