RESUMEN
Background: Several COVID-19 vaccination rollout strategies are implemented. Real-world data from the large-scale, government-mandated Central Vaccination Center (CVC), Thailand, could be used for comparing the breakthrough infection, across all available COVID-19 vaccination profiles. Methods: This prospective cohort study combined the vaccine profiles from the CVC registry with three nationally validated outcome datasets to assess the breakthrough COVID-19 infection, hospitalization, and death among Thais individuals who received at least one dose of the COVID-19 vaccine. The outcomes were analyzed by comparing vaccine profiles to investigate the shot effect and homologous effect. Findings: Of 2,407,315 Thais who had at least one dose of COVID-19 vaccine, 63,469 (2.75%) had breakthrough infection, 42,001 (1.79%) had been hospitalized, and 431 (0.02%) died. Per one vaccination shot added, there was an 18% risk reduction of breakthrough infection (adjusted hazard ratio [HR] 0.82, 95% confidence interval [CI] 0.80-0.82), a 25% risk reduction of hospitalization (HR 0.75, 95% CI 0.73-0.76), and a 96% risk reduction of mortality (HR 0.04, 95% CI 0.03-0.06). The heterologous two-shot vaccine profiles had a higher protective effect against infection, hospitalization, and mortality compared to the homologous counterparts. Interpretation: COVID-19 breakthrough infection, hospitalization, and death differ across vaccination profiles that had a different number of shots and types of vaccines. Funding: This study did not involve any funding.
RESUMEN
We propose the concept of teaching (and learning) unfamiliar visualizations by analogy, that is, demonstrating an unfamiliar visualization method by linking it to another more familiar one, where the in-betweens are designed to bridge the gap of these two visualizations and explain the difference in a gradual manner. As opposed to a textual description, our morphing explains an unfamiliar visualization through purely visual means. We demonstrate our idea by ways of four visualization pair examples: data table and parallel coordinates, scatterplot matrix and hyperbox, linear chart and spiral chart, and hierarchical pie chart and treemap. The analogy is commutative i.e. any member of the pair can be the unfamiliar visualization. A series of studies showed that this new paradigm can be an effective teaching tool. The participants could understand the unfamiliar visualization methods in all of the four pairs either fully or at least significantly better after they observed or interacted with the transitions from the familiar counterpart. The four examples suggest how helpful visualization pairings be identified and they will hopefully inspire other visualization morphings and associated transition strategies to be identified.
RESUMEN
High-dimensional data visualization has been attracting much attention. To fully test related software and algorithms, researchers require a diverse pool of data with known and desired features. Test data do not always provide this, or only partially. Here we propose the paradigm WYDIWYGS (What You Draw Is What You Get). Its embodiment, SketchPadND, is a tool that allows users to generate high-dimensional data in the same interface they also use for visualization. This provides for an immersive and direct data generation activity, and furthermore it also enables users to interactively edit and clean existing high-dimensional data from possible artifacts. SketchPadND offers two visualization paradigms, one based on parallel coordinates and the other based on a relatively new framework using an N-D polygon to navigate in high-dimensional space. The first interface allows users to draw arbitrary profiles of probability density functions along each dimension axis and sketch shapes for data density and connections between adjacent dimensions. The second interface embraces the idea of sculpting. Users can carve data at arbitrary orientations and refine them wherever necessary. This guarantees that the data generated is truly high-dimensional. We demonstrate our tool's usefulness in real data visualization scenarios.
