Environmental Health Practitioner
Africa Centre for Disease Control and Prevention Addis Ababa, Ethiopia
Abstract:
Title: Trends, Burden and Predictors of Yellow Fever cases in Nigeria: A Retrospective Analysis of National Surveillance Data, January 2022 – 2nd November 2025
Background: Yellow fever (YF) remains a significant public health threat, with Africa accounting for approximately 90% of global cases and an estimated 30,000 deaths annually. In Nigeria, YF reemerged in 2017 after two decades without major outbreaks and has since caused recurrent epidemics. This study assessed the trends, burden, and predictors of YF in Nigeria.
Methods: We conducted a retrospective analysis of national YF surveillance data collected between 1st January 2022 and 2nd November 2025 across all 36 states and the Federal Capital Territory (FCT). Standard national case definitions for suspected, probable, and confirmed YF cases were applied. Data were cleaned, and variables with substantial missing data were classified as “Unknown.” The outcome variable was laboratory-confirmed YF, while independent variables included age, sex, vaccination status, state-level burden, and clinical symptoms. Descriptive analyses and multivariable logistic regression were performed to identify predictors of infection. Adjusted odds ratios (aORs) with 95% confidence intervals (CI) were calculated at a significance level of p<0.05.
Results: Of 10,906 suspected cases, 9,417 (86.4%) were tested, and 148 (1.6%) were confirmed across 33 states and the FCT. Confirmed cases increased from 35 in 2022 to 45 in 2024, then declined to 31 in 2025. Ondo State recorded the highest cumulative burden (20 cases). The Southwest, South-south, Southeast, and Northeast regions accounted for most confirmed cases. Median age was 20.5 years (IQR: 6.4–35.8), and 56.1% were female. Individuals aged ≥41 years had higher odds of infection (aOR=1.65; 95% CI: 1.00–2.68), while residence in low-burden states was protective (aOR=0.39; 95% CI: 0.28–0.55). Discordant results were observed, including 61.8% PRNT positivity among IgM-negative samples and incomplete confirmatory testing among IgMpositive cases. PRNT positivity among IGM negatives highlights public health implications, including underestimating yellow fever transmission, delayed outbreak detection, case misclassification, and surveillance gaps, which can affect risk assessment, vaccination, and response planning when IGM testing alone is relied on.
Conclusion and recommendations: Yellow fever's continued spread in Nigeria indicates immunity gaps, low vaccination coverage, and ongoing transmission in vulnerable communities. This underscores the need to strengthen immunization, improve surveillance and diagnostics, and enhance early outbreak detection. Integrated vector control, community engagement, and a One Health approach are crucial for better prevention and control of the virus.
Keywords: Disease outbreak; Yellow Fever; Logistic model; Public Health Surveillance, Nigeria
Biography:
I am a health professional with 8 years of experience in the public health sector. Currently, I serve as an Environmental Health Practitioner for the Ministry of Health and Social Services in Namibia. I hold a Master's degree in Public Health Science from the University of South Wales and a Bachelor's degree in Environmental Health Science from the now University of Science and Technology in Namibia. Additionally, I possess certificates in Public Health Entomology and Leadership Management in Global Health, and am an Africa Epidemic Service Fellow with Africa CDC.
