Overview
This project leverages real-time COVID-19 data fetched from the disease.sh API to visualize global trends, including infection rates, recovery trajectories, and geographical impact. Using JavaScript, Leaflet.js, and GeoJSON, the project builds an interactive dashboard and live maps, providing up-to-date epidemiological insights.
Objectives
- Fetch real-time COVID-19 data globally via the disease.sh API
- Build an interactive world map showing live infection hotspots and recovery distribution
- Plot live daily trends for confirmed cases, deaths, and recoveries by country/region
- Enable user filtering by date range and country to see dynamic data changes
- Provide insights into pandemic progression and regional differences using live data
COVID-19 Cases by Country (WHO Style)
Loading global map…
Loading India map…
India COVID‑19 (WHO)
Updated weekly from WHO global table
Total Cases: —
New (last 7 days): —
Total Deaths: —
New Deaths (7 days): —
WHO Region Color Codes
The global map uses WHO‑style region colors (mapped from continent data; India is assigned to South‑East Asia).
- Africa
- Americas
- Europe
- South‑East Asia
- Western Pacific
- Eastern Mediterranean
- Other/Unknown
Search Country Data
Cases: —
Deaths: —
Recovered: —
COVID‑19 Trends
A flat placeholder line is shown until a country is selected.
Data Sources
| Source | Description |
|---|---|
| WHO Global Table CSV | Official weekly data used for India |
| disease.sh | Global country data & historical time series |
WHO CSV: https://covid19.who.int/WHO-COVID-19-global-table-data.csv
Methods & Tools
- Data Retrieval: Accessed WHO or COVID19 API, parsed JSON into Pandas, cleaned missing/inconsistent values.
- Data Wrangling: Aggregated case data, calculated rates, merged with GeoJSON country coordinates.
- Mapping (Folium): Built choropleth maps and circle marker layers with popups.
- Visualization (Plotly): Created interactive time series plots, bar charts, and optional animations.
Example Insights
- India, USA, and Brazil exhibited consistent surges aligned with policy delays.
- Recovery rates rose significantly post-July 2021 with mass vaccination campaigns.
- African nations showed underreporting patterns — visualized as data sparsity.
- Reinfection waves (Delta, Omicron) visualized in animated strain-period plots.
Tools Used for Interactive Live Data Map
| Tool | Purpose |
|---|---|
| JavaScript | Fetch live API data and build interactive visualizations |
| Leaflet.js | Interactive maps with markers, popups, and layers |
| disease.sh API | Real-time global COVID-19 data |
| GeoJSON | Country coordinates and shapes for mapping |
| HTML & CSS | Page structure, styling, and responsive layout |
| Optional Libraries (Chart.js / Plotly) | Interactive charts linked with map data |
Tools We can use for Static Map
| Tool | Purpose |
|---|---|
| Python | Data processing and visualization |
| Pandas | Data cleaning and manipulation |
| Plotly | Interactive graphs and plots |
| Folium | Geospatial mapping |
| GeoJSON | Geolocation mapping |
| Jupyter Notebook | Interactive development |
Applications
- Public health communication to display global pandemic impact
- Support for policy decision-making and resource allocation
- Educational tool for understanding epidemiological data
- Research support in real-time COVID surveillance and modeling