No abstract

No abstract

Dear Editor, As one of the largest countries in the world, Brazil has administered over 380 million doses of COVID-19 vaccines, which counts to approximately 67% of its population being considered fully vaccinated. 1 In late January 2021, the national immunization campaign started after an emergency authorization for two vaccines: Sinovac-CoronaVac (inactivated virus) and ChAdOx1 nCoV-19 (nonreplicant adenoviral vector). 2 The interim data release for the ChAdOx1 nCoV-19 demonstrated a 70.4% overall efficacy against SARS-CoV-2. 3 The claimed data of CoronaVac efficacy was around 50%. 4,5 According to the CDC USA-Centers for Disease Control, a vaccine breakthrough infection is defined as the detection of SARS-CoV-2 RNA The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Chatbots are often designed to mimic social roles attributed to humans. However, little is known about the impact on user's perceptions of using language that fails to conform to the associated social role. Our research draws on sociolinguistic theory to investigate how a chatbot's language choices can adhere to the expected social role the agent performs within a given context. In doing so, we seek to understand whether chatbots design should account for linguistic register. This research analyzes how register differences play a role in shaping the user's perception of the human-chatbot interaction. Ultimately, we want to determine whether register-specific language influences users' perceptions and experiences with chatbots. We produced parallel corpora of conversations in the tourism domain with similar content and varying register characteristics and evaluated users' preferences of chatbot's linguistic choices in terms of appropriateness, credibility, and user experience. Our results show that register characteristics are strong predictors of user's preferences, which points to the needs of designing chatbots with register-appropriate language to improve acceptance and users' perceptions of chatbot interactions.CCS Concepts: • Human-centered computing → Human computer interaction (HCI); Empirical studies in HCI; Natural language interfaces.

Background Health Care workers (HCW) are an important group affected by this pandemic and COVID-19 has presented substantial challenges for health professionals and health systems in many countries. The Brazilian vaccination plan implemented in October, so that third dose for HCW. However, the persistence of CoronaVac vaccine-induced immunity is unknown, and immunogenicity according to age cohorts may differ among individuals. Objective Evaluate the post vaccination immune humoral response and the relationship between post-vaccination seropositivity rates and demographic data among Healthcare Workers over 6 months after CoronaVac immunization. Methods A cross section study including Healthcare professionals vaccinated with CoronaVac for 6 months or more. The study was carried with the analysis of post-vaccination serological test to assess the levels of humoral response after vaccination. Results 329 participants were included. Among them, 76% were female. Overall, 18.5% were positive quantitative titles (IQR 42.87-125.5) and the negative group was 80%, quantitative titles (IQR 5.50-13.92). Conclusion It was possible to identify a group with positive quantitative titles in serological test for IgG antibody against the SARS-CoV-2. Further investigation is required to determine the durability of post-vaccination antibodies and how serological tests can be determine the ideal timing of vaccine booster doses.