Elucidating Infectious Causes of Fever of Unknown Origin: A Laboratory-Based Observational Study of Patients with Suspected Ebola Virus Disease, Guinea, 2014

This study investigated the causes of fever of unknown origin (FUO) in 550 Guinean patients who initially tested negative for Ebola virus during the 2014 outbreak.

This repository contains data and analysis files from our study investigating infectious causes of fever of unknown origin (FUO) in 550 Guinean patients during the 2014 Ebola outbreak:

-Appendix_I_ONT_Pipeline_Results.xlsx Complete 16S sequencing data including quality metrics, BLAST alignment results, and taxonomic assignments for bacterial identification.
-Appendix_II_FUO_Guinea_Clinical_Data.xlsx: Complete dataset including patient demographics, symptoms, pathogen detection results, and clinical parameters.
-Appendix_III_Statistical_Analysis_Report.zip: Jamovi project file containing all statistical analyses, enabling reproducibility and further exploration of the data and statistical report detailing associations between cohort variables, parasitemia, coinfections, and symptoms. Includes all statistical tests, significance values, and visualizations.

Key findings include:

Major Results:
- Identified infectious causes in 52.3% of patients through molecular and serological testing
- Main pathogens found:
- Plasmodium (35.6%, predominantly P. falciparum)
- Pathogenic bacteria (18.4%), including Salmonella and Klebsiella
- Hemorrhagic fever viruses (5.8%), including previously missed Ebola cases

Notable Findings:
1. Missed Diagnoses:
- 28 previously undetected Ebola cases (5.1%)
- Demonstrates compromise in diagnostic capabilities during outbreaks

2. Antimicrobial Resistance:
- 60% of samples showed resistance to first-line antibiotics
- High prevalence of resistance genes against aminoglycosides, beta-lactams, tetracyclines

3. Coinfections:
- 20% of infected patients had multiple pathogens
- Most common: Malaria with sepsis-causing bacteria
- Similar rates in adults (12.1%) and children (12.5%)

Data Collection/Methods:
- Blood samples from March-December 2014
- Analysis through PCR, serological tests, and high-throughput sequencing
- Patient demographics: median age 29 years, 63% male
- Most patients from Western Guinea regions

Interpretation:
1. Clinical Impact:
- Demonstrates need for comprehensive testing beyond single pathogens
- Supports empirical antimalarial and antibiotic therapy in resource-limited settings
- Highlights importance of monitoring antibiotic resistance

2. Public Health Implications:
- Shows necessity of strengthening laboratory capacity in sub-Saharan Africa
- Emphasizes need for syndromic testing during outbreaks
- Suggests value of point-of-care diagnostics for multiple pathogens

The data provides actionable insights for improving diagnostic approaches and treatment guidelines in resource-limited settings during disease outbreaks.