Epidemiological Characterisation of the Record 2023 Dengue Epidemic in Bangladesh: An 8-Year National Surveillance Analysis (2018–2025)
Khalilur Rahman Ridoy Khan (Corresponding Author)
Independent Researcher, Dhaka, Bangladesh
📧 khalilurrahmanridoykhan@gmail.com
🐙 @khalilurrrahmanridoykhan
Watan Rahman
Institute of Science and Technology, Dhaka, Bangladesh
This repository contains all data, analysis scripts, figures, and the manuscript for a study characterising the 2023 record dengue epidemic in Bangladesh using 8 years of national hospital surveillance data (2018–2025).
| Metric | Value |
|---|---|
| 2023 admitted cases (record) | 321,017 |
| National incidence 2023 | 189.6 per 100,000 |
| Fold increase from 2018 baseline | 31.6× |
| COVID-19 lockdown case reduction (2020) | 97.5% |
| Monsoon burden (Jun–Oct, 2023) | 83.2% of annual cases |
| Peak week 2023 | W38 — 20,244 cases |
| Post-2023 new baseline (2024–2025) | ~102,000/year |
| Highest per-capita division | Barishal (10.01/100,000) |
All data were extracted from the DGHS HEOC Dengue Dynamic Dashboard:
🔗 https://dashboard.dghs.gov.bd/pages/heoc_dengue_v1.php
This is a publicly accessible government dashboard maintained by the Directorate General of Health Services (DGHS), Government of Bangladesh. No login or authentication is required. Data accessed: June 2026.
Data represents admitted (hospitalised) dengue cases — not total community infections.
bangladesh-dengue-2018-2025/
│
├── data/
│ └── raw/
│ ├── dengue_annual_national.csv # Annual cases 2018–2026
│ ├── dengue_monthly_national.csv # Monthly cases 2023–2025
│ ├── dengue_weekly_national.csv # Weekly cases 2023–2025
│ ├── dengue_daily_2026.csv # Daily cases Jan–Jun 2026
│ ├── dengue_division_2026.csv # Division cases + deaths 2026 YTD
│ ├── dengue_weekly_division_2026.csv # Weekly by division 2026
│ └── dengue_scrape_log.txt # Scrape log
│
├── analysis/
│ ├── 01_annual_trend.py # Fig 1: Annual trend bar chart
│ ├── 02_epidemic_curve.py # Fig 2: Weekly epidemic curves
│ ├── 03_seasonal_pattern.py # Fig 3: Monthly heatmap + seasonal index
│ ├── 04_division_analysis.py # Fig 4: Division incidence + weekly trends
│ └── 05_summary_stats.py # Table 5: Key stats for manuscript
│
├── figures/
│ ├── fig1_annual_trend.png
│ ├── fig2_epidemic_curve.png
│ ├── fig3_seasonal_pattern.png
│ ├── fig4_division_analysis.png
│ ├── table1_annual_summary.csv
│ ├── table2_weekly_peaks.csv
│ ├── table3_seasonal_index.csv
│ ├── table4_division_incidence.csv
│ └── table5_key_stats.csv
│
├── scrape_dengue_dashboard.py # Data collection script
├── write_manuscript.py # Generates Word manuscript
├── Bangladesh_Dengue_Manuscript.docx # Full manuscript (Word)
├── README.md
└── LICENSE
python3 -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txtThe repository includes a snapshot of the source data. Reproduce every figure and summary table with:
make reproducemake dataSaves 6 CSV files to data/raw/.
python analysis/01_annual_trend.py
python analysis/02_epidemic_curve.py
python analysis/03_seasonal_pattern.py
python analysis/04_division_analysis.py
python analysis/05_summary_stats.pySaves figures and tables to figures/.
make manuscriptSaves Bangladesh_Dengue_Manuscript.docx.
| Column | Description |
|---|---|
| year | Calendar year (2018–2026) |
| dengue_cases | Annual admitted dengue cases |
| Column | Description |
|---|---|
| year | Calendar year |
| month | Month name |
| month_num | Month number (1–12) |
| dengue_cases | Monthly admitted dengue cases |
| Column | Description |
|---|---|
| year | 2026 |
| division | Administrative division name |
| dengue_cases_cumulative | Cumulative admitted cases (Jan–Jun 2026) |
| dengue_deaths_cumulative | Cumulative deaths (Jan–Jun 2026) |
If you use this data or code, please cite:
Khan KRR, Rahman W. Epidemiological Characterisation of the Record 2023 Dengue Epidemic in Bangladesh: An 8-Year National Surveillance Analysis (2018–2025). medRxiv [Preprint]. 2026. doi: [to be added after submission]
Data source citation:
DGHS Bangladesh. HEOC Dengue Dynamic Dashboard. Directorate General of Health Services, Government of Bangladesh. Available at: https://dashboard.dghs.gov.bd/pages/heoc_dengue_v1.php. Accessed June 2026.
This study used publicly available, aggregated surveillance data published by DGHS Bangladesh. No individual patient data were accessed. IRB review was not required.
This repository is licensed under the MIT License. Data originally sourced from DGHS Bangladesh (public government data).