Objectives We examined national temporal trends, laboratory-confirmation performance, and climate associations in Lassa fever surveillance in Nigeria from 2020 to 2025, and assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on surveillance metrics. Methods: We analyzed 307 consecutive weeks of national Lassa fever surveillance data using an ecological study design. Primary outcomes included confirmed-case counts, case fatality rate (CFR), and laboratory-confirmation rate (LCR). Temporal trends were evaluated using regression models, climate associations using correlation and negative binomial regression analyses, and the impact of COVID-19 using interrupted time-series analysis. Results: Overall, 47,029 suspected cases, 6,288 confirmed cases, and 975 deaths were reported. The mean LCR was 11.2% (standard deviation, 7.2%), declining from 18.4% in 2020 to 9.9% in 2025 (p <0.001). The overall CFR was 15.5%, with no significant downward trend over time. Confirmed cases were inversely associated with weekly rainfall (rs=−0.589, p <0.0001) and positively associated with mean temperature (rs=0.462, p<0.0001). Peak season incidence was 5.3-fold higher than that during off-peak periods. The COVID-19 lockdown period was associated with an immediate reduction in confirmed cases without a corresponding reduction in suspected cases. Conclusion: Lassa fever surveillance in Nigeria from 2020 to 2025 was characterized by a declining LCR, persistently elevated CFR, and a climate-linked seasonal pattern of increasing intensity, findings that are consistent with, but do not definitively establish, systemic underascertainment. CFR trends may partly reflect case-mix variation and detection bias. Because of the ecological study design, causal inferences cannot be drawn. These findings underscore the need for resilient, climate-informed, One Health surveillance systems.
Objectives This study aimed to examine the prevalence and pattern of adverse events following childhood immunization and the responses of mothers in Ile-Ife, South West Nigeria.
Methods This descriptive cross-sectional study was conducted among 422 mothers of children aged 0 to 24 months attending any of the 3 leading immunization clinics in Ile-Ife, Nigeria. The respondents were selected using the multi-stage sampling technique. Data were collected using a pretested structured interviewer-administered questionnaire and analyzed using IBM SPSS ver. 26.0. The chi-square test was used to test associations, while binary logistic regression was used to determine the predictors of mothers’ responses to adverse events following immunization (AEFIs). A p-value of <0.05 was considered statistically significant.
Results The mean age of the respondents was 29.99±5.74 years. About 38% of the children had experienced an AEFI. Most mothers believed that the pentavalent vaccine was the most common cause of AEFIs (67.5%). Fever (88.0%) and pain and swelling (76.0%) were the most common AEFIs. More than half of the mothers (53.7%) administered home treatment following an AEFI. Younger mothers (odds ratio [OR], 2.43; 95% confidence interval [CI], 1.20–5.01), mothers who delivered their children at a healthcare facility (OR, 3.24; 95% CI, 1.08–9.69), and mothers who were knowledgeable about reporting AEFIs (OR, 2.53; 95% CI, 1.04–7.70) were most likely to respond appropriately to AEFIs.
Conclusion The proportion of mothers who responded poorly to AEFIs experienced by their children was significant. Therefore, strategies should be implemented to improve mothers’ knowledge about AEFIs to improve their responses.
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A comprehensive evaluation of the AEFI surveillance system in Ethiopia: An insight from a national study Admas Abera, Behailu Hawulte, Tesfaye Gobena, Lemma Demissie Regassa, Saba Hailu, Ahmed Mohammed, Berhanu Fikadie Endehabtu, Mulumebet Abera Wordofa, Keneni Gutema Negeri, Girma Taye, Michael Tarekegn, Binyam Tilahun, Mesoud Mohammed, Naod Wondirad, Kibro Journal of Global Health Economics and Policy.2026;[Epub] CrossRef
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Advancing Immunization in Africa: Overcoming Challenges to Achieve the 2030 Global Immunization Targets Olalekan Okesanya, Gbolahan Olatunji, Noah Olaleke, Mba Mercy, Ayodele Ilesanmi, Hassan Kayode, Emery Manirambona, Mohamed Ahmed, Bonaventure Ukoaka, Don Lucero-Prisno III Adolescent Health, Medicine and Therapeutics.2024; Volume 15: 83. CrossRef
Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The COVID-19 incidence and mortality rates are low in Nigeria compared to global trends. This research mapped the evolution of SARS-CoV-2 circulating in Nigeria and globally to determine whether the Nigerian isolates are genetically distinct from strains circulating in regions of the world with a high disease burden. Methods: Bayesian phylogenetics using BEAST 2.0, genetic similarity analyses, and genomewide mutational analyses were used to characterize the strains of SARS-CoV-2 isolated in Nigeria. Results: SARS-CoV-2 strains isolated in Nigeria showed multiple lineages and possible introductions from Europe and Asia. Phylogenetic clustering and sequence similarity analyses demonstrated that Nigerian isolates were not genetically distinct from strains isolated in other parts of the globe. Mutational analysis demonstrated that the D614G mutation in the spike protein, the P323L mutation in open reading frame 1b (and more specifically in NSP12), and the R203K/ G204R mutation pair in the nucleocapsid protein were most prevalent in the Nigerian isolates. Conclusion: The SARS-CoV-2 strains in Nigeria were neither phylogenetically nor genetically distinct from virus strains circulating in other countries of the world. Thus, differences in SARS-CoV-2 genomes are not a plausible explanation for the attenuated COVID-19 outcomes in Nigeria.
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Objectives The study aimed to examine health workers’ perceptions of the coronavirus disease 2019 (COVID-19) vaccine in Nigeria and their willingness to receive the vaccine when it becomes available.
Methods This multi-center cross-sectional study used non-probability convenience sampling to enroll 1,470 hospital workers aged 18 and above from 4 specialized hospitals. A structured and validated self-administered questionnaire was used for data collection. Data entry and analysis were conducted using IBM SPSS ver. 22.0.
Results The mean age of respondents was 40±6 years. Only 53.5% of the health workers had positive perceptions of the COVID-19 vaccine, and only slightly more than half (55.5%) were willing to receive vaccination. Predictors of willingness to receive the COVID-19 vaccine included having a positive perception of the vaccine (adjusted odds ratio [AOR], 4.55; 95% confidence interval [CI], 3.50−5.69), perceiving a risk of contracting COVID-19 (AOR, 1.50; 95% CI, 1.25–3.98), having received tertiary education (AOR, 3.50; 95% CI, 1.40−6.86), and being a clinical health worker (AOR, 1.25; 95% CI, 1.01−1.68).
Conclusion Perceptions of the COVID-19 vaccine and willingness to receive the vaccine were sub-optimal among this group. Educational interventions to improve health workers' perceptions and attitudes toward the COVID-19 vaccine are needed.
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Objectives
This study aims to create a mathematical model to better understand the spread of Ebola, the mathematical dynamics of the disease, and preventative behaviors. Methods
An epidemiological model is created with a system of nonlinear differential equations, and the model examines the disease transmission dynamics with isolation through stability analysis. All parameters are approximated, and results are also exploited by simulations. Sensitivity analysis is used to discuss the effect of intervention strategies. Results
The system has only one equilibrium point, which is the disease-free state (<i>S</i>,<i>L</i>,<i>I</i>,<i>R</i>,<i>D</i>) = (<i>N</i>,0,0,0,0). If traditional burials of Ebola victims are allowed, the possible end state is never stable. Provided that safe burial practices with no traditional rituals are followed, the endemic-free state is stable if the basic reproductive number, <i>R</i><sub>0</sub>, is less than 1. Model behaviors correspond to empirical facts. The model simulation agrees with the data of the Nigeria outbreak in 2004: 12 recoveries, eight deaths, Ebola free in about 3 months, and an <i>R</i><sub>0</sub> value of about 2.6 initially, which signifies swift spread of the infection. The best way to reduce <i>R</i><sub>0</sub> is achieving the speedy net effect of intervention strategies. One day's delay in full compliance with building rings around the virus with isolation, close observation, and clear education may double the number of infected cases. Conclusion
The model can predict the total number of infected cases, number of deaths, and duration of outbreaks among others. The model can be used to better understand the spread of Ebola, educate about prophylactic behaviors, and develop strategies that alter environment to achieve a disease-free state. A future work is to incorporate vaccination in the model when the vaccines are developed and the effects of vaccines are known better.
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Data Fitting and Scenario Analysis of Vaccination in the 2014 Ebola Outbreak in Liberia
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Effect of sexual transmission on the West Africa Ebola outbreak in 2014: a mathematical modelling study Dongmei Luo, Rongjiong Zheng, Duolao Wang, Xueliang Zhang, Yi Yin, Kai Wang, Weiming Wang Scientific Reports.2019;[Epub] CrossRef
Mathematical modeling of contact tracing as a control strategy of Ebola virus disease T. Berge, A. J. Ouemba Tassé, H. M. Tenkam, J. Lubuma International Journal of Biomathematics.2018; 11(07): 1850093. CrossRef
Challenges of Designing and Implementing High Consequence Infectious Disease Response Joan M. King, Chetan Tiwari, Armin R. Mikler, Martin O’Neill Disaster Medicine and Public Health Preparedness.2018; 12(5): 563. CrossRef
The potential impact of a prophylactic vaccine for Ebola in Sierra Leone Erin N. Bodine, Connor Cook, Mikayla Shorten Mathematical Biosciences and Engineering.2017; 15(2): 337. CrossRef
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