Executive Summary

This report analyzes the Ebola outbreak data from Sierra Leone in 2014, providing key insights into the timing, demographics, and geographic distribution of cases.

Data Overview

The dataset contains 200 total cases, with 200 cases having onset dates, 196 cases with age information, and 200 cases with sex information.

Key Findings

1. First Case Reported

The first Ebola case was reported on May 18, 2014 in the Kailahun district.

2. Age Group with Most Cases (End of June 2014)

As of the end of June 2014, the 30-39 age group had the most cases with 43 reported cases.

3. Median Age of Affected Individuals

The median age of those affected was 35 years, with ages ranging from 1.8 to 80 years.

4. Gender Distribution

There were 114 cases in women (57%) and 86 cases in men (43%). Women had more cases, with a difference of 28 cases.

5. District with Most Reported Cases

The district with the most reported cases was Kailahun with 155 cases.

Visualizations

Timeline of Cases

Age Distribution by Gender

District Case Distribution

Summary Tables

Age Group Distribution (End of June 2014)

## **Age Group Distribution (End of June 2014):**
## 
## - ** 30-39 :**  43  cases
## - ** 40-49 :**  38  cases
## - ** 20-29 :**  37  cases
## - ** 10-19 :**  29  cases
## - ** 0-9 :**  21  cases
## - ** 50-59 :**  16  cases
## - ** 60-69 :**  9  cases
## - ** 70-79 :**  3  cases

District Case Summary

## **District Case Summary:**
## 
## - ** Kailahun :**  155  cases
## - ** Kenema :**  34  cases
## - ** Western Urban :**  4  cases
## - ** Bo :**  2  cases
## - ** Kono :**  2  cases
## - ** Port Loko :**  2  cases
## - ** Kambia :**  1  cases

Conclusion

This analysis reveals that the Ebola outbreak in Sierra Leone in 2014 affected individuals across all age groups, with the 30-39 age group being most impacted. The outbreak showed a slight gender disparity, with women being more affected. Geographically, Kailahun was the hardest-hit district, highlighting the need for targeted intervention strategies.

The data provides valuable insights for understanding the demographic patterns of the outbreak and can inform future public health responses to similar epidemics.