This repository contains the data, analysis scripts, and figures for the research paper:
"Epidemiology of the 2026 Measles Outbreak in Bangladesh: A Descriptive Analysis of National Surveillance Data with Vaccine Coverage Assessment"
Khalilur Rahman Ridoy Khan — East West University, Dhaka, Bangladesh
| Metric | Value |
|---|---|
| Reporting period | 2 April – 2 June 2026 (62 days) |
| Total suspected cases | 73,362 |
| Total confirmed cases | 9,136 |
| Confirmation rate | 12.5% |
| Suspected deaths | 504 |
| Confirmed deaths | 90 |
| Case fatality rate (confirmed) | 0.99% |
| Peak daily suspected cases | 1,503 (10 May 2026) |
| Doubling time (early phase) | 6.1 days |
| National vaccination coverage (MR Campaign 2026) | 102% |
All data is sourced from publicly available daily press release PDFs published by the Directorate General of Health Services (DGHS), Bangladesh:
- URL: https://dghs.gov.bd/pages/press-releases/
- Data collected: 2 April 2026 to 2 June 2026
- PDF host: Oracle Cloud Storage (linked from DGHS press release pages)
- No patient-level or identifiable data is used — all data is aggregated at national and division level
bangladesh-measles-2026/
├── data/
│ ├── measles_national_summary.csv # 62-day daily national data
│ ├── measles_division_breakdown.csv # Division-level daily data (8 divisions)
│ ├── table1_summary_stats.csv # Table 1: National summary statistics
│ ├── table2_division_stats.csv # Table 2: Division-level burden
│ ├── table3_dynamics_summary.csv # Table 3: Outbreak dynamics
│ ├── table3_dynamics_weekly.csv # Weekly breakdown
│ └── table_vaccination_division.csv # MR Campaign 2026 coverage by division
├── scripts/
│ ├── dghs_measles_full.py # Web scraper (collects data from DGHS)
│ ├── fix_deaths.py # Patches deaths columns from PDFs
│ ├── 01_epidemic_curve.py # Figure 1: Epidemic curve
│ ├── 02_cumulative_trajectory.py # Figure 2 + Table 1
│ ├── 03_division_analysis.py # Figure 3 + Table 2
│ ├── 04_vaccination_vs_cases.py # Figure 4
│ └── 05_outbreak_dynamics.py # Table 3 + Figure S1
├── figures/
│ ├── fig1_epidemic_curve.png
│ ├── fig2_cumulative_trajectory.png
│ ├── fig3_division_burden.png
│ ├── fig4_vaccination_vs_incidence.png
│ └── figS1_weekly_dynamics.png
└── paper/ # Manuscript files (Word/PDF)
# 1. Install dependencies
pip install requests beautifulsoup4 pdfplumber pandas matplotlib seaborn scipy openpyxl
# 2. Collect data (re-scrapes all press releases)
python scripts/dghs_measles_full.py
# 3. Fix deaths columns
python scripts/fix_deaths.py
# 4. Generate all figures and tables
python scripts/01_epidemic_curve.py
python scripts/02_cumulative_trajectory.py
python scripts/03_division_analysis.py
python scripts/04_vaccination_vs_cases.py
python scripts/05_outbreak_dynamics.pyDivision population estimates from the Bangladesh Population and Housing Census 2022 (Bangladesh Bureau of Statistics):
| Division | Population |
|---|---|
| Dhaka | 36,054,418 |
| Chattogram | 28,423,019 |
| Rajshahi | 18,484,858 |
| Khulna | 15,563,000 |
| Rangpur | 15,665,000 |
| Mymensingh | 11,370,000 |
| Sylhet | 10,009,239 |
| Barishal | 8,325,666 |
Data: Public domain (Government of Bangladesh, DGHS)
Code: MIT License
Paper: CC BY 4.0
If you use this data or code, please cite:
Ridoy Khan KR. Epidemiology of the 2026 Measles Outbreak in Bangladesh: A Descriptive Analysis of National Surveillance Data with Vaccine Coverage Assessment. Zenodo [Preprint]. 2026. doi: 10.5281/zenodo.20569837
Preprint URL: https://doi.org/10.5281/zenodo.20569837