Contribution to Omdena Sudan Chapter's Analyzing Healthcare Accessibility project.
# Analyzing Healthcare Accessibility in Sudan
My contribution to Omdena Sudan Chapter's Analyzing Healthcare Accessibility project.
## Challenge Background
The increase of infectious diseases in Sudan, coupled with the complex environmental and socio-economic factors, hold significant challenges to the existing healthsystem. Traditional disease surveillance methods often rely on retrospective data analysis, which may be insufficient for responding to emerging outbreaks. A robust forecasting system can provide early warnings, enabling timely interventions and resource allocation.
This project aims to develop a disease forecasting model using machine learning techniques and deploy it as a user-friendly web application. By leveraging historical data, real-time information, and ML algorithms, this system will enable accurate prediction of disease impact, empowering healthcare professionals and officials to make informed decisions.
## The Problem
The conflict areas, displacement and resource constraints have severely impacted healthcare access. Many facilities are under-resourced and understaffed, leaving critical gaps in addressing medical conditions. Alongside patients of chronic conditions such as diabetes and hypertension, the region faces threats of frequent outbreaks of infectious diseases like malaria, cholera, poisoning and pneumonia. Each area and topic requires tailored solutions in order to address such health challenges. Disease management and prediction using ML techniques work as aiding tools for medical professionals and provide a machine-aided solution.
More info here