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segunshow/Outbreak-of-Diseases-in-Nigeria

Domain:

healthcare

Record type:

dataset
Creator:
seg
Host:
This project provides a comprehensive data analysis of disease outbreaks in Nigeria across various states, genders, and age groups. The aim is to uncover insights into disease patterns, identify the most affected demographics, and provide recommendations for targeted public health responses. ### Project Objective To analyze patterns in disease outbreaks across Nigerian states by exploring key metrics such as: Disease type and prevalence Gender and age group distribution Trends over time Survival status of patients This helps inform public health policy, resource allocation, and preventive strategies for government and health agencies. ### Tools Used Microsoft Excel Pivot Tables & Charts Dashboard Creation Data Cleaning & Structuring Exploratory Data Analysis (EDA) ### Dashboard Insights #### State-Level Impact Niger State had the highest outbreak, followed by Ondo, Kano, Bayelsa, and Imo. Disease outbreaks are not region-specific — affecting both Northern and Southern states. #### Disease Prevalence Top 3 diseases reported: Cholera (28,589 cases), Diarrhea (28,550), and Rubella Mars (28,539). Waterborne diseases are a major public health concern. Diseases like Marburg Virus and Viral Hemorrhagic Fever hint at zoonotic threats tied to environmental hygiene and wildlife contact. #### Gender & Age Group Females were more affected (147,272) than males (137,212), possibly due to societal or healthcare access factors. The 1–20 age group is the most affected (93,865 cases), followed by 21–40 years (70,934), suggesting increased exposure in youth due to environmental or immunity factors. #### Trends Over the Years Disease cases fluctuated, peaking in 2013 (28,745 cases) and 2016 (28,638). Indicates periodic outbreaks, potentially influenced by seasonal changes, natural disasters, or health system readiness. #### Patient Survival Analysis Nearly equal number of deaths (142,289) and recoveries (142,195). High mortality may reflect late detection, inadequ …

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