National Agency for Food and Drug Administration and Control

BACKGROUND:The African meningitis belt remains prone to recurrent invasive meningococcal disease (IMD) outbreaks, mainly from serogroups C, W, and X. In 2024, Niger and Nigeria conducted the first large-scale, real-world use of the pentavalent meningococcal conjugate vaccine (MMCV), covering Neisseria meningitidis serogroups A, C, W, Y, and X. This study describes enhanced passive safety surveillance implemented during these campaigns. METHODS:Enhanced passive safety surveillance was conducted during MMCV campaigns in Niger (May-July 2024) and Nigeria (March-June 2024). Surveillance included systematic adverse event reporting, digital tools (MedSafety App® in Nigeria, ODK Collect® in Niger), integrated supervision and systematic data monitoring. Adverse Events Following Immunization (AEFI) were analyzed by demographics, seriousness, and System Organ Class (SOC). Disproportionality analysis was performed using VigiBase® and Vigilyze® to identify potential safety signals. FINDINGS:A total of 4,881,027 individuals were vaccinated (Niger: 2,697,934; Nigeria: 2,183,093). There were 1109 AEFI reports (reporting rate: 22.7 per 100,000 vaccinees), with 11 (0.99%) classified as serious, including one death. Most AEFIs were mild and occurred on the day of vaccination; the most frequent were pyrexia, injection site reactions, myalgia, arthralgia, and headache. The majority of AEFI reports were among children aged 2-12 years (61.9%), followed by adolescents (17.4%) and young adults (15.2%). INTERPRETATION:The introduction of MMCV in Niger and Nigeria confirmed a robust safety profile in real-world outbreak settings, with very low rates of serious adverse events and no new safety signals detected. Enhanced passive surveillance, supported by digital tools and integrated supervision, enabled timely and comprehensive AEFI reporting. The observed safety outcomes were consistent with clinical trial data and previous vaccine introductions, reinforcing the reliability and generalizability of MMCV's safety. Sustained investment in pharmacovigilance infrastructure and ongoing training for healthcare workers remain essential for effective vaccine safety monitoring.

Background The commercial food environment in urban Nigeria is driving a dual increase in diet-related non-communicable diseases (NCDs), particularly adult and early-onset childhood obesity, alongside severe dental caries. Beverage manufacturers are increasingly using front-of-pack nutrient comparative claims, such as "less sugar," alongside industry-led Guideline Daily Amount (GDA) panels to capture health-conscious demographics. While these labels are technically legal by achieving a relative 25% sugar reduction against outdated high-sugar baselines, this standard completely ignores the absolute sugar payload delivered by expanded 500ml and 600ml retail configurations. Objective To evaluate how commercial soft drinks in Nigeria carrying "less sugar" profiles (Coca-Cola, Pepsi, and 7-Up) align with or undermine the World Health Organization (WHO) guidelines for free sugar intake, and to model their direct contribution to the national burdens of obesity and dental caries. Methods A public health nutritional modeling and dietary intake assessment was conducted. The absolute free sugar masses for Coca-Cola (7.5 g/100ml), Pepsi (7.1 g/100ml), and 7-Up (6.9 g/100ml) were mapped across 500ml and 600ml bottles. These payloads were benchmarked against the WHO recommendation restricting free sugars to < 10% (strong recommendation) and < 5% (conditional recommendation) of daily energy intake for a standard 2,000 kcal/day adult profile (ceiling: 50 g/day) and a 1,500 kcal/day pediatric profile (ceiling: 37.5 g/day). Front-of-pack industry’s 250ml GDA baseline was mathematically evaluated against WHO absolute thresholds to expose the scale of risk under-reporting. Results The evaluated soft drinks deliver absolute sugar payloads ranging from 34.5 g to 37.5 g per 500ml container, and 41.4 g to 45.0 g per 600ml container. A single 600ml bottle of 7-Up (6.9 g/100ml)—the lowest concentration evaluated—delivers 41.4 g of absolute sugar, instantly exhausting 82.8% of an adult's and 110.4% of a child’s maximum daily allowance. For Coca-Cola, a single 600ml bottle delivers 45.0 g of sugar (90.0% of the adult and 120.0% of the pediatric daily limit). The industry’s GDA label asserting that a 250ml serving contains 19g of sugar or "21% GDA" relies on an unscientific 90g daily denominator. This under-reports obesity and dental risks by more than double, as 19g actually consumes 38.0% of an adult's and 50.7% of a child’s entire daily allowance. Conclusion Relative "less sugar" descriptors on large-volume containers mask dangerously large quantities of free sugars, creating a false sense of dietary safety that directly accelerates obesity and enamel demineralization across Nigerian demographics. The National Agency for Food and Drug Administration and Control (NAFDAC) must prohibit relative nutrient comparative claims on large-volume packaging and replace confusing GDA panels with mandatory front-of-pack black octagonal warning labels.

Background Nigeria has adopted comprehensive tobacco control legislation, including the National Tobacco Control Act (NTCA) 2015 and Tobacco Control Regulations 2019, yet continues to experience high tobacco-related morbidity and a substantial illicit cigarette market. Institutional fragmentation and weak enforcement capacity, compounded by evolving obligations under the WHO Framework Convention on Tobacco Control (FCTC) and the Protocol to Eliminate Illicit Trade in Tobacco Products, undermine effective implementation. Methods A desk-based qualitative policy and regulatory analysis was conducted using three complementary approaches: (1) comparative legal mapping of Nigeria's tobacco control framework against core WHO FCTC and Illicit Trade Protocol obligations; (2) thematic synthesis of WHO guidance, treaty decisions, and peer-reviewed evidence on institutional arrangements for tobacco regulation; and (3) an implementation-readiness assessment of the National Agency for Food and Drug Administration and Control (NAFDAC) across key capacity domains. Results The analysis identified five interrelated structural gaps: fragmented institutional authority; absence of a central product regulator; weak supply-chain and illicit trade control; inadequate protection from tobacco industry interference; and a regulatory vacuum for emerging nicotine products. Nigeria's current ministry-led configuration constrains compliance with WHO FCTC Articles 9, 10, 11, and 15, while NAFDAC already possesses significant laboratory, port-of-entry, and digital traceability capacity developed through pharmaceutical regulation. Conclusion Reconfiguring Nigeria's tobacco control architecture to assign NAFDAC a central technical regulatory mandate, while retaining health policy stewardship within the Federal Ministry of Health (FMoH), offers a legally feasible and context-appropriate pathway to strengthen enforcement, meet evolving treaty expectations, and reduce tobacco-related harms.

The rising burden of obesity and non-communicable diseases among young people has prompted global recommendations for healthier food environments, but evidence is limited across African universities. This study aims to assess the healthiness and spatial distribution of university food environments using in-store retail audits and outdoor food advertising assessments. Outdoor food advertisements were audited in two universities (excluding the University of Ibadan), while retail stores were assessed across three participating institutions within a 300-500 m radius of each campus. Data were collected using the INFORMAS protocol and the NEMS-S-MED in-store audit tool, respectively, alongside spatial analyses. A total of 76 food advertisements and 145 food retail stores were identified. Less than one-tenth (7.5%) of advertised products were healthy. Healthier foods in retail stores were predominantly characterised by moderately low (37.2%) and medium (31.7%) availability, while affordability was low (73.1%), resulting in over half being classified as having a low (51.7%) degree of healthiness. These differed significantly across institutions (p < 0.05), with the University of Nigeria, Nsukka (UNN) having a more diverse, spatially dispersed and healthier food environment. There is a need to restrict unhealthy food advertising and encourage vendors' procurement and the sale of healthier foods.

Disease surveillance is fundamental to public health, enabling timely outbreak detection, efficient resource allocation, and evidence-based policymaking. In Nigeria, the Integrated Disease Surveillance and Response (IDSR) framework, while structured, is hampered by inconsistent data quality, limited private sector participation, and infrastructural constraints. Machine Learning (ML), a powerful subset of Artificial Intelligence (AI), offers transformative potential through its capacity for predictive analytics, real-time data processing, and automated pattern recognition to enhance surveillance capabilities. Despite global advancements in ML for disease forecasting and syndromic surveillance, its adoption within Nigeria’s IDSR system lags considerably. This paper addresses this critical gap by investigating how ML can overcome Nigeria-specific barriers, such as fragmented data systems and rural connectivity deficits. We provide enhanced technical depth on ML methodologies, comparing supervised and unsupervised learning, and detailing relevant architectures, including Decision Trees, Recurrent Neural Networks (RNNs), and Convolutional Neural Networks (CNNs), suited for time-series epidemiological forecasting. We present a methodological illustration of malaria surveillance in Northern Nigeria using synthetic data, benchmarking five ML models (Linear Regression, Decision Tree, Random Forest, Gradient Boosting, and Support Vector Machine) under temporal validation, and employing SHapley Additive exPlanations (SHAP) for robust model interpretability. A sensitivity analysis further examines the stability of model performance under coefficient perturbations. A benchmarking analysis compares Nigeria’s ML adoption against Rwanda and Kenya. Finally, we propose a tiered strategic framework encompassing policy, infrastructure, and capacity-building recommendations, complemented by a cost-benefit perspective emphasizing potential Disability-Adjusted Life Years (DALYs) averted and significant economic returns, aiming to foster a more resilient and equitable public health system in Nigeria. Not applicable.