Table 4.
Characteristics of reviewed COVID-19 dashboards
| Study # | Platform | Dashboard users | Public accessibility | Update frequency | Data analysis | Goal | Interactive | Presentation | Features | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Web | Mobile | Desktop | Informative | Supportive | ||||||||
| S1 | ✓ | ✕ | ✕ |
- GP - AR |
✓ | Real-time | MS | ✓ | ✕ | ✓ |
- Map - Chart - Trend |
- Comparison over time - Reporting - Plots downloadable |
| S2 | ✓ | ✕ | ✕ | - GP | ✓ | Real-time | SA | ✓ | ✕ | ✕ | List mode | |
| S3 | ✕ | ✓ | ✕ | - GP | ✓ | Daily | - Algorithm developed by authors for classifying countries/regions into four quadrants in GSM - MS | ✓ | ✕ | ✕ |
- Map - Trend |
|
| S4 | ✓ | ✕ | ✕ | - GP | ✓ | Daily | ML | ✓ | ✕ | ✓ |
- Map - Chart |
- The most prevalent factual information among Twitter users in any user-selected USA geographic region - COVID-19 chatbot |
| S5 | ✓ | ✕ | ✕ |
- GP - PM |
✓ | Daily | SA | ✓ | Generation of structured data for decision-making at government level | ✓ |
- Map - Chart |
|
| S6 | ✓ | ✕ | ✕ | - HP | ✕ | Irregular | SA | ✕ |
Highlighting of the patients less likely to require intubation - Color-coded system (yellow, amber, red) to highlight patients with extremes of respiratory dysfunction. |
✓ | - Table | |
| S7 | ✓ | ✕ | ✕ | - GP | ✓ | Daily | SA | ✓ | ✕ | ✕ |
- Chart - Table |
- User accounts (normal user, admin user) - Data sent via email to users |
| S8 | ✓ | ✕ | ✕ | - GP | ✓ | >1 day | MS | ✓ | ✓ | ✕ | N/S | |
| S9 | ✓ | ✕ | ✕ | - GP | ✓ | Daily | SA | ✓ | ✕ | ✓ | - Trend | |
| S10 | ✓ | ✕ | ✕ | - GP | ✓ | Real-time | SA | ✓ | ✕ | ✓ |
- Map - Trend |
- Rankings of worst-affected areas - Plots downloadable |
| S11 | ✓ | ✕ | ✕ |
- GP - AR - PM |
✓ | Real-time | SA | ✓ | Estimation of confirmed cases, active cases, new cases, and deaths | ✓ | - Color map - Chart - Table |
- Zooming - Filtering - Categorizing - Visualizing multiple time series - Details-on-demand - SQL-like query tool - Filter text box - Navigating through data table - Interactive queries for analytics - Semantic textual similarity - User query dataset - Drills down to different levels of data |
| S12 | ✕ | ✓ | ✓ |
- GP - HP |
✕ | Real-time | SA | ✓ | Visual display of COVID-19 patient information for physicians | ✓ | - Color graphic symbols | |
| S13 | ✓ | ✕ | ✕ |
- GP - AR - PM |
✓ | Real-time | MS | ✓ | Projection regarding future trend of cases and deaths worldwide | ✓ |
- Geographic chart - Color map - Chart |
|
| S14 | ✓ | ✕ | ✕ |
- GP - AR - PM |
✓ | Real-time | SA | ✕ | Investigating of impact of racial disparities on both cases and deaths due to COVID-19 | N/S | - Chart | |
| S15 | ✕ | ✕ | ✓ | - HP | ✕ | Real-time | Calculation of COVID-19 severity score for each patient based on predefined algorithm that included clinical parameters, age, lab results, and comorbidities | ✓ | ✕ | ✓ |
- Color-coding schema - Chart - Table |
drill down |
| S16 | ✓ | ✕ | ✕ |
- GP - PM |
✓ | Daily | Binomial statistical model | ✓ | Estimation of risk of individuals contracting COVID-19 | ✓ |
- Cartogram - Static map - Interactive map - Chart |
|
| S17 | ✓ | ✕ | ✕ |
- GP - PM |
✓ | Daily | SA | ✓ | ✕ | ✕ | - Chart | |
| S18 | ✓ | ✕ | ✕ |
- GP - AR |
✓ | Daily | Poisson prospective space-time scan statistic | ✓ | ✕ | ✓ |
- Bivariate choropleth map - Bubble map |
- Pan and zoom tools - Time slider - Animation - Popup boxes |
| S19 | ✓ | ✕ | ✕ | - AR | ✓ | Real-time | Bayesian spatio-temporal model Poisson Knorr–Held model | ✓ |
- Estimation of confirmed cases, active cases, new cases and deaths - Display of impact of stay-at-home variable according to data on confirmed cases, active cases, new cases, and deaths |
✓ |
- Color map - Black and white map - Chart |
|
| S20 | ✓ | ✕ | ✕ |
- GP - PM |
✓ | Real-time | SA | ✓ | ✕ | ✓ |
- Color map - Chart |
- Spatial-time indicators - Multi-temporal and multi-scale information |
| S21 | ✓ | ✕ | ✕ |
- GP - PM |
✓ | Daily | - Time-series forecasting model to understand prevalence of COVID-19 based on the Holt-Winters (HW) seasonal method - Multiple linear regression (MLR) method - Machine learning techniques | ✓ | Analysis of global and regional job and stock markets, and model to predict their future trend by considering state of COVID-19 outbreak | ✓ |
- Color map - Chart |
|
| S22 | ✓ | ✕ | ✕ |
- GP - PM |
✓ | Real-time | Auto regression using Seasonal AutoRegressive Integrated Moving Average with exogenous regressors (SARIMAX) | ✓ | Forecasting of trends and patterns of outbreak, and complications of COVID-19 pandemic | ✓ |
- World heat map - Bubble map - Chart - Trend - Table |
- Data entry component - Text input - Radio button - Play/pause - Sliders component - Drop-down component - Interactive graphs - Global trend display - Canada trend display |
| S23 | ✓ | ✕ | ✕ |
- GP - AR - PM |
✓ | Real-time | SA | ✓ | Forecast of trends, patterns of outbreak, and complications of corona pandemic | ✓ |
- Color map - Chart - Table |
- Dynamic visualized data - Drill down to county-level data - Subpopulation selection - Filtering - Radio button |
| S24 | ✓ | ✕ | ✕ |
- GP - AR |
✓ | Real-time | SA | ✓ | ✕ | ✓ |
- Color map - Chart |
- Zooming - Categorizing - Generation of dynamic graphics - Animation display to play, pause, and restart options |
| S25 | ✓ | ✕ | ✕ |
- GP - AR |
✓ | Real-time | SA | ✓ | ✕ | ✓ |
- Color map - Chart |
- Drill down to different levels of data - Subpopulation selection |
| S26 | ✓ | ✕ | ✕ |
- GP - PM |
✓ | Daily | SA | ✓ | ✕ | ✕ |
- Chart - Table |
|
N/S, not specified; SA, simple analysis (e.g., calculating counts, average, median, aggregate of data, etc.); MS, mathematical/statistical models; ML, machine learning techniques; GP, general public; HP, healthcare professionals; PM, policy-makers, public authorities, managers; AR, analysts, academics, researchers; GSM, Global System for Mobile Communications; USA, United States of America; SQL, Structured Query Language