Check out this link for the current implementation in Streamlit: https://share.streamlit.io/egronskaya/measles/src/measles_analyser.py
The purpose of this project is to analyze measles data across the world. Our objective is twofold:
- to investigate the correlation between measles incidence and the vaccination rate
- to establish the effect of national income on measles vaccination rate
- Inferential Statistics
- Data Visualization
- Python
- Streamlit
- Pandas, jupyter
- HTML
- Plotly
- Geojson
Measles is a highly contagious acute viral respiratory illness accompanied by high fever, cough, coryza, conjunctivitis, and fatigue. Infants, pregnant women, and immunocompromised individuals are at increased risk of severe infection. This measles study is conducted on data collected from World Health Organization, Unicef, and Data World Bank.
Our hypothesis states:
- after the introduction of measles vaccination in 1963, the incidence rate of measles has decreased, however, this decrease is not proportional
- national income has been affecting the vaccination rate in non-linear way
We analyze the global measles incidence and vaccination rate data with plotly express choropleth map to demonstrate the evolution of the measles infection cases from 1980-2020. To explore nation-wide relationships between the measles immunization and vaccination rates, we implement line plots. The influence of the national income on vaccination rate is visualized with a scatter plot and a bar plot to observe how to correlation has been changing since 1980.
The main obstacles are caused by incomplete vaccination rate data provided by different nations. Additionally, the vaccination rates are directly affected by economic changes, healthcare access disparities, and vaccination scepticism. In parallel with the pertussis (1943), polio (1955), measles (1963), mumps (1967) and rubella (1971) vaccine rollout, the anti-vaccination movement gained traction altering the vaccination rates henceforth.
- Clone this repo (for help see this tutorial).
- Raw Data is being kept here within this repo.
- Data processing/transformation scripts are being kept here
- Follow setup instructions