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adeliepl/ntd-analysis

Domain:

healthcare

Record type:

dataset
Creator:
ade
Host:
Neglected Tropical Diseases (NTDs) affect over 1 billion people worldwide. This project analyzes WHO data from 2010-2021 to uncover trends, disparities, and insights into the battle against NTDs in the Africa region. # The Battle Against Neglected Tropical Diseases (NTDs) in the WHO Africa Region (2010-2021) ## Overview Neglected Tropical Diseases (NTDs) affect over **1 billion people** worldwide, disproportionately impacting the most vulnerable populations. This project analyzes **WHO data from 2010-2021** to uncover trends, disparities, and insights into the battle against NTDs in the Africa region. ## Dataset - **Source:** World Health Organization (WHO) - **Period Covered:** 2010 - 2021 - **Key Variables:** - `Location`: Country or region - `Period`: Year - `FactValueNumeric`: Number of reported NTD cases ## Methodology This project follows a structured data analysis approach: 1. **Data Cleaning & Preprocessing:** - Handling missing values and duplicates. - Converting necessary columns to numerical format. 2. **Exploratory Data Analysis (EDA):** - Statistical analysis to understand key trends in NTD cases. - Identifying extreme values, central tendencies, and distributions. 3. **Geographic Disparity Analysis:** - Identifying top and bottom countries based on NTD prevalence. - Visualizing case distribution across regions. 4. **Visualization:** - Line graphs for NTD trends over time. - Bar charts ranking countries by case counts. ## Key Findings - The **NTD case range** varies drastically, highlighting disparities across regions.. - A **gradual decline in NTD cases** in recent years suggests the impact of healthcare interventions. - Stark **geographic disparities** highlight the need for targeted strategies in highly affected regions. - The integration of key WHO events into trend analysis provides insights into major policy impacts.. ## How to Run the Analysis ### Prerequisites Ensure you have Python and the following libraries installed: ```bash pip install pandas numpy matplotlib seaborn ``` ### Running the Script 1. Clone the repository: ```bash git clone github.com ``` 2. Navigate to the project directory: ```bash cd ntd …