First Field Use of the Pentavalent Meningococcal Conjugate Vaccine (Men5CV) in Response to a Serogroup C Meningitis Outbreak: Evidence from Yobe State, Northeastern Nigeria

First Field Use of the Pentavalent Meningococcal Conjugate Vaccine (Men5CV) in Response to a Serogroup C Meningitis Outbreak: Evidence from Yobe State, Northeastern Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article First Field Use of the Pentavalent Meningococcal Conjugate Vaccine (Men5CV) in Response to a Serogroup C Meningitis Outbreak: Evidence from Yobe State, Northeastern Nigeria Baba Waru Goni, Hamidu Suleiman Kwairanga, Olugbenga Oguntunde, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8262447/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: In early 2024, an outbreak of meningococcal meningitis occurred in Yobe State, northeastern Nigeria, prompting an urgent public health response. This study analyzes the epidemiologic, clinical, and laboratory characteristics of the outbreak and evaluates the effect of the reactive Men5C vaccination campaign. Methods: A retrospective review of 2,948 suspected meningitis cases was conducted using line-listed surveillance data for the year 2024. Data included demographic variables, clinical presentation, laboratory results, and vaccination history. Descriptive statistics, bivariate analysis, and multivariable logistic regression were used to identify predictors of mortality. Results: Children and adolescents aged 1–19 years accounted for 84.8% of all cases. The overall case fatality ratio (CFR) was 3.6%, with the highest CFR observed among adults aged ≥ 40 years ( 5.6% ). Males had a significantly higher CFR than females ( 4.4% vs. 2.5%, p = 0.009 ) . Most deaths occurred among individuals who had no record for vaccination against Neisseria meningitidis serogroup A (59.0%). Logistic regression showed that male sex ( aOR = 1.74; 95% CI: 1.14–2.66; p = 0.011 ) and outpatient admission status ( aOR = 0.07; 95% CI: 0.01–0.54; p = 0.010 ) were significant predictors of mortality. Laboratory confirmation identified Neisseria meningitidis serogroup C in 93.8% of all positive cases. A reactive ring vaccination campaign using Men5CV deployed 585,035 doses and administered 579,004 cases across the three most affected local government areas, with vaccination coverage ranging from 45% to 104%. Conclusion: This outbreak was driven primarily by Neisseria meningitidis serogroup C, with adolescents and unvaccinated individuals disproportionately affected. The successful deployment of Men5CV demonstrates its feasibility in emergency settings and highlights the urgent need for preventive routine vaccination in Nigeria’s meningitis belt. Meningococcal Meningitis Neisseria meningitidis Serogroup C Men5CV Yobe State Northeast Nigeria Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Contributions to the Literature The study demonstrates how a new 5-in-1 meningitis vaccine (Men5CV) worked in real life during an outbreak in Nigeria. Provides first evidence that Men5CV can quickly stop disease spread and is safe for people. Highlights the need for routine vaccination and better outbreak response in hard-to-reach communities. Suggests practical steps for governments to prevent future meningitis epidemics. Background Globally, meningitis remains a persistent public health threat despite advances in vaccines and diagnostics. In 2019, an estimated 2.5 million people developed meningitis and approximately 240,000 died from the disease. 1 – 4 The burden falls disproportionately on sub-Saharan Africa’s “Meningitis Belt,” a region of 26 countries from Senegal to Ethiopia characterized by recurrent outbreaks during the dry season (typically December - June). 5 Devastating epidemics have historically occurred every few years; the 1996 West African epidemic alone resulted in over 250,000 cases and 25,000 deaths. 6 Before 2010, serogroup A N. meningitidis (NmA) was responsible for 80–85% of epidemic meningitis cases in this region. 7 Nigeria is one of the most affected countries within the Meningitis Belt and has experienced repeated large-scale outbreaks since the early 20th century. Major epidemics were recorded in 1996, 2003, 2009, and 2017, predominantly in northern states where climatic factors such as dust, low humidity, and high temperatures amplify transmission. 8 The 1996 outbreak in Nigeria alone caused more than 109,000 cases and nearly 12,000 deaths. 6 These recurrent epidemics highlight the vulnerability of the region and the need for robust, broad-spectrum meningitis control measures. A major shift in meningococcal epidemiology occurred after the introduction of MenAfriVac, a monovalent serogroup A conjugate vaccine, beginning in 2010. Nigeria introduced MenAfriVac through mass vaccination campaigns in 2013, targeting individuals aged 1–29 years, the group at highest risk of epidemic meningitis. The impact was remarkable as serogroup A meningococcal disease virtually disappeared in countries achieving high coverage. 8 – 11 By 2015, more than 220 million people across 15 African countries had been vaccinated, leading to the elimination of NmA epidemics and demonstrating strong herd immunity effects. 11 However, the decline of NmA created an ecological niche that was increasingly occupied by other serogroups. A growing body of evidence documents the emergence of serogroups C, W, X, and Y in various countries of the belt. 4 , 7 , 12 – 14 These trends exposed the limitations of monovalent and polysaccharide vaccines, which provide limited and short-lived protection against multiple serogroups and do not support long-term mucosal immunity or herd protection. In particular, serogroup X, although historically less common, remained a concern because no licensed vaccine targeted it prior to 2023. Serogroup C (NmC) emerged as a major threat in the mid-2010s. A novel NmC strain first detected in northern Nigeria in 2013 caused localized outbreaks in 2014–2016. 15 , 16 The strain then spread to Niger in 2015, triggering the largest global NmC epidemic on record with over 8,500 cases. 17 These events were followed by a large NmC epidemic in northwestern Nigeria in 2016–2017, during which more than 14,000 suspected cases were reported and approximately 80% of confirmed cases were due to NmC. 16 Reactive vaccination campaigns using serogroup C and ACWY vaccines helped curb transmission but underscored the urgent need for broader, more affordable, and more durable meningococcal vaccines. 9 , 18 Before 2023, available polyvalent conjugate meningococcal vaccines were limited. Quadrivalent ACWY vaccines offered broader protection but were costly and used mainly for reactive campaigns with restricted availability. 19 , 20 The absence of serogroup X coverage, combined with the rising relevance of non-A serogroups, created a strong rationale for a multivalent vaccine specifically designed for the African Meningitis Belt. To address these gaps, the Serum Institute of India and PATH developed a pentavalent conjugate vaccine - Men5CV, covering serogroups A, C, W, Y, and X. Clinical trials in Africa demonstrated strong immunogenicity across all five serogroups, including more than 97% seroconversion for serogroup X and high responses for A, C, W, and Y, alongside a favorable safety profile. 21 , 22 After 13 years of development, Men5CV was prequalified by the WHO in July 2023 and formally recommended in October 2023 for use in epidemic response and routine immunization strategies. 23 Men5CV is the first vaccine to offer protection against all major epidemic-causing meningococcal serogroups in a single shot. Its approval for the global emergency stockpile by the International Coordinating Group (ICG) in late 2023 further enabled its deployment during outbreaks. 24 Nigeria subsequently became the first country worldwide to deploy Men5CV in the context of an active epidemic. 25 Beginning in late 2023, a serogroup C meningococcal outbreak spread across seven northern states. By March 2024, a cumulative 1,742 suspected cases and 153 deaths had been reported across Adamawa, Bauchi, Gombe, Jigawa, Katsina, Yobe, and Zamfara states. 25 Yobe State, which had not experienced a major epidemic in over a decade, largely due to the success of MenAfriVac, confirmed its first NmC epidemic in early 2024. In response, Nigerian health authorities, with support from WHO and Gavi, launched a reactive Men5CV ring vaccination campaign in March 2024. Approximately one million individuals aged 1–29 years across affected states were targeted, with priority given to outbreak hotspots. 25 Despite the major global significance of Men5CV, no published field studies had evaluated its real-world performance, operational feasibility, or safety during an active epidemic at the time of this outbreak. Evidence on how Men5CV functions outside clinical trials, particularly in resource-limited, conflict-affected settings such as Yobe State, is essential for guiding future policy, improving outbreak response, and informing global strategies to eliminate meningitis epidemics. This study presents the first field-based evaluation of the 2024 NmC outbreak in Yobe State, northeast Nigeria, following the deployment of the pentavalent Men5CV vaccine. It describes outbreak characteristics, assesses vaccination coverage and safety, documents the operational processes surrounding the first-ever Men5CV campaign, and evaluates the implications for future epidemic preparedness and meningitis control across the African Meningitis Belt. Methods Study Design and Setting We conducted a descriptive observational study of the meningococcal meningitis outbreak that occurred in Yobe State, Nigeria, during the 2023–2024 dry season. This study utilized a retrospective analysis of surveillance data and administrative records from the vaccination campaign, applying descriptive epidemiological methods and ecological analysis to characterize disease trends and assess the impact of the reactive Men5CV vaccination response implemented during the outbreak. Yobe State is located in northeastern Nigeria and falls within the African Meningitis Belt (Fig. 1). It comprises 17 Local Government Areas (LGAs) with an estimated population of approximately 3.4 million in 2023. 26 The population is largely rural and agrarian, and the climate is arid to semi-arid with an extended dry season (October to May). Environmental conditions such as low humidity and Harmattan winds favour meningococcal transmission. Prior to 2024, Yobe had not experienced a large-scale meningitis outbreak since the national rollout of MenAfriVac in 2013, although isolated NmA cases were reported in 2017 in the state’s northwest during a regional epidemic. Health service delivery in Yobe includes primary health centers, State-level general and specialist hospitals, and a tertiary referral hospital in the state capital, Damaturu. In March 2024, the State Ministry of Health supported by the Nigeria Centre for Disease Control (NCDC), activated an Incident Management System and Emergency Operations Center (EOC) to coordinate outbreak response. Figure 1 about here Figure 1: Map showing the Africa Meningitis Belt and Yobe State, Nigeria, highlighting study LGAs and geographical boundaries The map shows the geographical context of the study area, highlighting Yobe State’s 17 Local Government Areas (LGAs) where meningitis surveillance and outbreak response activities were conducted during the 2024 outbreak. Source Plate A: US Center for Disease Control and Prevention) Case Definitions and Surveillance : We applied standard World Health Organization (WHO) definitions for meningococcal meningitis surveillance: 27 Suspected case : Any person with sudden onset of fever (≥ 38.5°C rectal or ≥ 38.0°C axillary) and neck stiffness or signs of meningeal irritation. In infants, a bulging fontanelle or lethargy could substitute for neck stiffness. Probable case : A suspected case with turbid/purulent cerebrospinal fluid (CSF), CSF leukocyte count > 10/µL, or positive Gram stain. In the context of a confirmed outbreak, clinically compatible cases without lumbar puncture were also considered probable due to epidemiologic linkage. Confirmed case : A suspected or probable case with laboratory confirmation of Neisseria meningitidis from CSF or blood by PCR, culture, or agglutination testing. Serogroup confirmation was based on PCR testing. Surveillance was enhanced during the outbreak. Health workers across all health facilities were sensitized to the case definitions and instructed to immediately notify the LGA Disease Surveillance and Notification Officer (DSNO) upon identifying any suspected case. Community-based surveillance networks, including polio informants, were mobilized to report suspicious febrile illnesses and deaths. A standardized national CSM case-based reporting form was used to line-list each case, capturing clinical features, demographics, vaccination status, and outcome. Line lists were submitted to the EOC daily. Laboratory Diagnosis CSF samples were collected aseptically at the point of care. Initial testing (Gram stain, cell count) was done at state-level laboratories when feasible. Samples were then transported under cold chain to the National Reference Laboratory (NRL) in Abuja. Real-time PCR Detection of Meningitis-Associated Bacteria Pathogens Real-time PCR (qPCR) assays were performed at the NRL using the QuantStudio 12K Flex platform, in accordance with standardized Nigeria Centre for Disease Control (NCDC) protocols aligned to the WHO Global invasive Vaccine-Preventable Disease (IB-VPD) surveillance guidelines. 28 – 30 DNA Extraction Genomic DNA was extracted from cerebrospinal fluid (CSF) using the QIAamp DNA Mini Kit (Qiagen), following the manufacturer’s protocol. 31 Extracts were aliquoted and stored at -20 0 C prior to amplification. qPCR Assay Each 20 µL reaction mixture was prepared using Perfecta qPCR ToughMix (QuantaBio), pathogen-specific primers and hydrolysis probes, PCR-grade water and 2 µL of template DNA. Reaction mixtures were assembled into 96-well plates under contamination-controlled conditions using a unidirectional workflow. Each run included pathogen-specific positive controls, no-template controls (NTCs) to monitor for contamination and internal amplification controls (e.g human RNaseP gene or synthetic inhibition control) to assess DNA extraction and PCR efficiency. Positive controls were sourced and validated in accordance with NCDC protocols aligned to WHO guidelines. Thermal cycling was performed under the following conditions: initial denaturation at 95°C for 10 minutes, followed by 40 amplification cycles at 95°C for 15 seconds and 60°C for 60 seconds. Pathogen Detection and Typing N. meningitidis : identification was based on amplification of the ctrA gene, with sero-grouping performed via detection of capsule biosynthesis genes: synA (serogroup A), siaD (serogroups B, C, Y, W), and mynB (serogroup X), using WHO-validated multiplex assays. 28 , 32 Streptococcus pneumoniae : The lytA gene was targeted for species confirmation. Optional serotyping of vaccine-related serotypes was conducted as needed. Haemophilus influenzae : Detection involved amplification of the bexA gene, with capsular typing based on type-specific primers targeting the cap locus (types a–f). Fluorescence Data Analysis Fluorescence data were analysed using QuantStudio software (v1.3, Applied Biosystems). A sample was considered positive if the cycle threshold (Ct) was < 36, based on WHO/CDC guidance. 29 Positive results were further validated by comparison with standard curves generated from known DNA concentrations. Outbreak Response and Men5CV Vaccination Campaign The outbreak response was led by the Yobe State EOC in collaboration with NCDC and WHO. Interventions included public awareness, free antibiotics, clinical kits, and reactive vaccination. The campaign deployed the pentavalent meningococcal conjugate vaccine (Men5CV) for the first time in a field outbreak setting. The ring vaccination strategy targeted high-risk LGAs based on case counts and WHO epidemic thresholds (> 10 cases/100,000 per week). Out of the seven LGAs that accounted for over 95% of reported cases (Potiskum, Nangere, Fune, Fika, Gulani, Damaturu, and Gujba), the top 3 were selected. These include Potiskum, Nangere and Fika. The campaign was implemented from 25–28 March 2024 (epidemiologic week 13). Target population was persons aged 1–30 years. Children less than 12 months were excluded due to age-specific vaccine indications. Vaccination was conducted via fixed, outreach, and mobile teams. Cold chain was maintained at 2–8°C using vaccine carriers. One 0.5 mL dose was administered intramuscularly. Paper tally sheets recorded vaccinations by age and location. Community sensitization included radio spots and engagement with traditional leaders. Vaccination Coverage Assessment Administrative coverage was calculated as doses administered divided by projected target population per LGA. Target populations were estimated from 2023 National Bureau of Statistics data. 26 Post-campaign rapid coverage assessments in select communities validated administrative data, although case-level vaccination status was not reliably documented. Data Sources We used four main data sources, Line list: The case-based line list served as the primary dataset for epidemiologic analysis. It included anonymized patient-level information such as age, sex, residence, symptom onset date, clinical features, outcome, and laboratory results, and was continuously updated by surveillance officers through June 2024. Daily surveillance call-ins: Each day, designated LGA focal persons reported aggregated case counts, deaths, and hospital resource use to the Emergency Operations Center via phone. These daily summaries provided near-real-time situational awareness and were used to validate and supplement the case-based line list. Vaccination records: Vaccination history was primarily assessed through patient-held immunization cards and caregiver recall. However, most patients lacked verifiable documentation, and reliance on verbal reporting was common. AEFI logs: Adverse events following immunization were reported using standardized forms completed by frontline health workers and monitored by the EOC’s immunization safety team. These logs documented both mild and serious events post-vaccination and supported post-campaign safety assessment. Data Analysis: All data analyses were conducted using Python (version 3.11), leveraging libraries such as pandas, numpy, and statsmodels. Incidence rates were calculated by dividing the number of confirmed or suspected meningitis cases in each Local Government Area (LGA) by the estimated LGA population for 2024, and expressed per 10,000 population. Case fatality rates (CFRs) were computed as the proportion of deaths among the total number of suspected cases, expressed as percentages. Categorical variables such as sex, age group, residence, vaccination status were summarized using frequencies and proportions. Bivariate associations between patient characteristics and mortality were assessed using Chi-square tests. Factors independently associated with death were explored using multivariate logistic regression, with adjusted odds ratios (AORs) and 95% confidence intervals (CIs) reported and statistical significance was defined as p < 0.05. For vaccination status, patients with unknown or undocumented MenAfriVac status were grouped with those reporting no prior MenA vaccination. None of the cases had evidence of receiving the full two-dose MenAfriVac schedule. Administrative vaccination data were compiled from tally sheets filled by immunization teams during the reactive Men5CV campaign. Target population estimates were drawn from microplans based on demographic projections (from 2006 population census), 26 enabling calculation of coverage at ward and LGA levels. Spatial analysis, including choropleth maps of incidence and CFRs, was conducted using ArcMap version 10.8.2, part of the ArcGIS Desktop suite (Esri, Redlands, CA, USA). Epidemic trends were visualized using temporal plots of weekly and monthly case counts. Adverse events following immunization (AEFI) were summarized using descriptive statistics. Ethical Considerations . This study was conducted as part of an emergency public health response to a meningitis outbreak in Yobe State, Nigeria. All data used in the study were fully anonymized prior to analysis, with no personal identifiers retained. The line-listing, vaccination records, and surveillance datasets were accessed with authorization from the Yobe State Ministry of Health, in accordance with national outbreak response protocols. Although the primary aim was outbreak control and not research, formal ethical approval for the use of the data for analysis and dissemination was obtained from the Yobe State Ministry of Health Ethical Review Committee (MOH/GEN/747/Vol.1). No individual-level consent was required as data were collected during routine surveillance and response activities in line with established national guidelines. Results Demographic Characteristics of Cases A total of 2,948 suspected meningococcal meningitis cases were reported during the outbreak period (Table 1 ). Demographic analysis revealed significant patterns across age, sex, vaccination status, residential location, and admission status. The mean age of cases was 13.7 ± 8.6 years. The outbreak disproportionately affected children and adolescents, with the 1–9 and 10–19 year age groups jointly accounting for 2,498 cases (84.8% of all infections). The 10–19 year cohort was the most affected, comprising 1,567 cases (53.2%) and 54 deaths (CFR = 3.4%), followed by children aged 1–9 years, accounting for 931 cases (31.6%) with a slightly higher CFR of 3.8%. Adults aged 20–40 years represented 379 cases (12.9%) and experienced a CFR of 3.2%, while individuals aged ≥ 40 years accounted for only 71 cases (2.4%) but had the highest case fatality ratio at 5.6%. Despite these differences, the association between age group and mortality was not statistically significant (χ² = 1.23; p = 0.75). There was a slight male predominance among the cases. Males accounted for 1,672 cases (56.7%). In contrast, females accounted for 1,276 cases (43.3%), giving a male-to-female ratio of approximately 1.3:1. Men also experienced a higher number and rate of death (73 deaths; CFR 4.4%) compared to females (32 deaths; CFR 2.5%), a statistically significant difference (X² = 6.74; p = 0.0094). The majority of individuals affected by this outbreak had no record of prior immunization against meningococcal serogroup A. Analysis of vaccination history based on patient records and immunization cards revealed that 99.3% of meningitis cases had either zero-dose (60.4%) or unknown (38.9%) MenA vaccine status, indicating unverifiable MenAfriVac status. Only 0.7% of cases had any history of MenAfriVac vaccination, and none had completed the full two-dose schedule. In terms of residential location, rural communities were more heavily impacted than urban centers. Overall, 1,989 cases (67.4%) were reported from rural areas compared to 959 cases (32.5%) in urban areas. Of the total 2948 patients, 105 died, and the majority (99%) of these deaths occurred among those who were admitted as inpatients (CFR = 4.0%), while only one death occurred among outpatients (CFR = 0.3%) (X² = 10.53; p = 0.0012). Table 1 Bivariate Analysis of Mortality by Demographic, Vaccination, and Location Characteristics among suspected Cerebrospinal Meningitis cases (n = 2948) Variable Alive (n, %) Dead (n, %) Total (n, %) CFR (%) Chi-square p-value Age group(Years) 1– 9 896 (31.5%) 35(33.3%) 931(31.6%) 3.8% 1.23 0.75 10–19 1,513 (53.2%) 54 (51.4%) 1,567 (53.2%) 3.4% 20–40 367 (12.9%) 12 (11.4%) 379 (12.9%) 3.2% ≥ 40 67 (2.4%) 4 (3.8%) 71 (2.4%) 5.6% Sex Male 1,599 (56.2%) 73(69.5%) 1,672 (56.7%) 4.4% 6.74 0.0094 Female 1,244 (43.8%) 32 (30.5%) 1,276 (43.3%) 2.5% Vaccination Status One dose 18(0.6) 2(1.9%) 20(0.7%) 10.0 2.45 0.294 None 1719 (60.5%) 62 (59.0%) 1781(60.4%) 3.5% Unknown 1106 (38.9%) 41 (39.0%) 1147(38.9%) 3.6% Admission status Inpatients 2512(88.4) 104(99.0 2616(88.7) 4.0 10.53 0.0012 Outpatient 331(11.7) 1(1.0) 331(11.3) 0.3 Location Rural 1926(67.7.1%) 63(60%) 1989 (67.4%) 3.2% 2.43 0.119 Urban 917 (32.3%) 42 (40%) 959 (32.5%) 4.4% A logistic regression analysis was conducted to identify factors independently associated with mortality among suspected meningitis cases (Table 2 ). Key predictors included sex, age group, residential location (urban vs rural), vaccination status, and admission status. Male sex was significantly associated with increased odds of death (adjusted odds ratio [AOR] = 1.74; 95% CI: 1.14–2.66; p = 0.011). Compared to children under 10 years (reference group), none of the older age groups were statistically significant predictors of mortality: age 10–19 years (AOR = 0.87; 95% CI: 0.56–1.36; p = 0.546), age 20–40 years (AOR = 0.91; 95% CI: 0.46–1.78; p = 0.780), and age ≥ 40 years (AOR = 1.56; 95% CI: 0.53–4.57; p = 0.419). Urban residence showed no significant association with death (AOR = 1.09; 95% CI: 0.72–1.66; p = 0.691). Additionally, receipt of one dose of MenAfriVac was not associated with increased odds of death (AOR = 0.42; 95% CI: 0.09–1.91; p = 0.260), nor was unknown vaccination status (AOR = 0.37; 95% CI: 0.08–1.74; p = 0.208). In contrast, being managed as an outpatient was significantly protective, with 93% lower odds of death compared to inpatients (AOR = 0.07; 95% CI: 0.01–0.54; p = 0.010). Table 2 Multivariate logistic regression of factors associated with death among suspected Cerebrospinal Meningitis cases in Yobe State, 2024 (n = 2,948) Variable AOR 95% CI p-value Age group (ref: 0–9 years) 10–19 years 0.87 0.56–1.36 0.546 20–39 years 0.91 0.46–1.78 0.780 ≥ 40 years 1.56 0.53–4.57 0.419 Sex (ref: Female) Male 1.74 1.14–2.66 0.011 Vaccination status (ref: 1 dose) None 0.42 0.09–1.91 0.260 Unknown 0.37 0.08–1.74 0.208 Residence (ref: Rural/Nomadic) Urban 1.09 0.72–1.66 0.691 Admission status (ref: Inpatient) Outpatient 0.07 0.01–0.54 0.010 Geographical and spatial Distribution of Cases The outbreak was geographically widespread but varied in intensity across the State. Of the state’s 17 LGAs, 12 (70.6%) reported suspected meningitis cases. Potiskum LGA, one of the more populous districts, recorded the highest number of cases (810; 27.5% of all cases). Other LGAs with high case counts included Fune (606; 20.6%), Fika (539; 18.3%), and Nangere (472; 16%). When adjusted for population, the incidence rates were highest in Nangere (31.7 per 100,000 population), followed by Potiskum (23.3/10,000), Fika (23.2/10,000) and Fune (11.9/10,000). These high-burden LGAs formed a contiguous belt in the south-central zone of the state. In contrast, Tarmuwa and Bade LGAs recorded fewer than 10 cases each, with incidence rates below 10 per 10,000. A map of LGA-level incidence rate is shown in Fig. 2A. Figure 2 about here Figure 2: Spatial distribution of cerebrospinal meningitis Incidence Rates(A) and Case Fatality Rates(CFR) by LGA, Yobe State, 2024 These maps show the spatial heterogeneity of the outbreak. Panel A reveals higher incidence rates concentrated in central and southern LGAs such as Potiskum and Fika. Panel B demonstrates that case fatality rates varied independently of incidence, with some LGAs reporting high CFRs despite lower case counts, underscoring the need for targeted support in those areas. Epidemic curve and Temporal Distribution The temporal epidemic curve (Fig. 3) reveals that cases surged rapidly to a peak in March 2024, when 1,159 cases (39.3% of the total) and 34 deaths were recorded (monthly CFR 2.9%). Thereafter, the outbreak subsided over the next three months: 755 cases were recorded in April, 283 in May and just 41 in June at which point no further deaths were reported. This sharp rise and gradual fall over a four-month interval indicate a single epidemic wave confined to the late dry-season months, as illustrated by the weekly trend in Fig. 3. Figure 3 about here Figure 3: Weekly epidemic curve of suspected meningitis cases in Yobe State, 2024 The epidemic curve illustrates the temporal progression of the outbreak. A rapid rise in cases was observed in late March, peaking in mid-April before declining. This pattern aligns with the timing of reactive vaccination and emergency response deployment. Clinical Outcomes and Case Fatality In total, 105 deaths occurred during the outbreak, giving an overall case fatality ratio (CFR) of 3.6% (Table 1 ). Males experienced a higher CFR (4.4%) compared to females (2.5%). Adults aged over 40 years had the highest age-specific CFR at 5.6%, despite forming the smallest fraction of total cases. In contrast, children aged 1–9 years had a CFR of 3.8%, while those aged 10–19 years had a CFR of 3.4%, and adults aged 20–40 years recorded a CFR of 3.2%. Most mortalities occurred among inpatients with a CFR of 4.0% compared to 0.3% among outpatients. Among the 20 individuals with a documented history of meningitis vaccination, two deaths were recorded (CFR = 10%), although this estimate is based on very small numbers. Bade LGA recorded only 4 cases and 1 mortality, translating to a LGA-specific CFR of 25%, whereas Potiskum had 17 mortalities among 780 cases (CFR = 2.2%). Most LGAs recorded CFRs ranging between 1% and 4% (Fig. 2B). Clinically, most suspected cases had the classic symptoms of meningitis (Table 3 ). Approximately 95.5% had documented fever at onset, and over 90.8% reported severe headache. Meningeal signs such as neck stiffness were commonly but not universally recorded, occurring in 78.7% of cases. In contrast, only 15.8% of cases had convulsions or altered consciousness. The most common symptom combination was fever, headache, neck stiffness, and abdominal pain (2,042 cases [69.3%]). In contrast, only 315 patients (10.7%) had a combination of all five major symptoms: fever, headache, neck stiffness, abdominal pain, and convulsions. Thus, the dominant clinical syndrome was a tetrad of fever, neck stiffness, headache, and abdominal pain, while seizures or altered consciousness were less common. Table 3 Frequency and percentage distribution of Clinical Symptoms among Cerebrospinal meningitis cases, Yobe State, 2024 Symptom(s) Number of Cases Percentage of Total Cases Fever 2815 95.5% Headache 2677 90.8% Neck stiffness 2321 78.7% Abdominal pain 2633 89.3% Convulsions or altered consciousness 467 15.8% Fever + Headache + Neck stiffness + Abdominal pain 2042 69.3% Fever + Headache + Neck stiffness + Abdominal pain + Convulsions 315 10.7% Laboratory confirmation of the etiologic agent was obtained in 423 (14.3%) of cases via cerebrospinal fluid (CSF); as is the case in low-resource settings during large outbreaks because of logistics and human resource constraints. Figure 4 shows that the majority (93.8%) of all confirmed positive cases were due to Neisseria meningitidis serogroup C (NmC) infections, corroborating the outbreak strain, while Haemophilus influenzae and Streptococcus Pneumoniae accounted for 4.9% and 0.9%, respectively. Figure 4 about here Figure 4: Laboratory Test Results Among Cerebrospinal Meningitis Cases, Yobe State, 2024 Among the confirmed positive cases, Neisseria meningitidis serogroup C (NmC) was the predominant pathogen, accounting for 93.8% of positives and representing just over half of all test results (52.7%). In contrast, Haemophilus influenzae and Streptococcus pneumoniae were detected in 4.9% and 0.9% of positive cases, corresponding to only 2.6% and 0.5% of all tested cases, respectively. Among the confirmed cases, 98.8% presented with fever, and a majority had headaches, while only 7% experienced convulsions. The most common symptom combination was fever, headache and abdominal pain (24.4%), while the least common was headache with neck stiffness alone. A comparison of clinically suspected vs. laboratory-confirmed cases yielded a Cohen’s kappa coefficient of + 0.423, indicating moderate agreement and supporting the validity of the clinical case definition used during the outbreak. Despite limited confirmation rate, the clinical characteristics of lab-confirmed cases closely matched the overall population. Vaccination Campaign Coverage, Uptake and Effect on Outbreak Trend The reactive ring vaccination commenced in late March 2024 in the most affected LGAs- Potiskum, Nangere, and Fika, targeting individuals aged 1–30 years, who constituted the majority of reported cases. The campaign reached a substantial proportion of the target population, though coverage varied across LGAs. A total of 600,825 doses of the newly introduced pentavalent meningococcal conjugate vaccine (Men5CV) were supplied for the reactive campaign conducted across three local government areas (LGAs) in Yobe State. Of these, 585,035 doses were deployed to the LGAs and 579,004 doses were administered, resulting in an overall deployment, utilization rate(of deployed doses) and vaccine wastage rate of 97.37%, 98.97% and 1.03% respectively. Based on administrative data, Fika LGA recorded 184,679 doses administered against a target population of 177,995 (103.8%). Potiskum LGA recorded 309,897 doses administered against a target population of 689,718 (44.9% coverage), while Nangere LGA recorded 84,428 doses administered out of a target of 186,563 (45.3% coverage) (Fig. 5A). Figure 5 about here Figure 5: Distribution of meningococcal vaccination(Men5CV) coverage among suspected cases by LGA, Yobe State, 2024 The bar charts illustrate the distribution and timing of the reactive meningococcal vaccination campaign in Yobe State. Panel A shows that Potiskum received the highest number of doses and vaccinated individuals, followed by Fika and Nangere. Panel B demonstrates that the mass vaccination campaign was implemented in late March, coinciding with the peak of reported cases. A notable and sustained decline in case numbers followed the rollout, suggesting a potential impact of the campaign in curbing further transmission. As illustrated in Fig. 5B, the temporal trends show that the vaccination rollout coincided with a decline in reported cases, suggesting possible early impact of the intervention. The incidence of meningitis declined sharply following the vaccination campaign. In April 2024 - the first full month after Men5C rollout - case count dropped to 755, (a 34.9% reduction from the March). The decline continued to 283 cases in May and 41 in June. By June, new infections represented only 3.5% of the March peak. Reported deaths also declined in parallel: from 34 in March to 18 in April, with no deaths in June. No resurgence of cases was observed following the intervention. Adverse Events Following Immunization (AEFI) Adverse events following immunization (AEFI) were monitored throughout the vaccination campaign. Of the 585,035 Men5C vaccine doses administered, 223 AEFI incidents were reported, representing an overall incidence rate of 0.04%. All reported AEFIs were mild and self-limiting. The most commonly reported symptoms were injection site pain or swelling (n = 80; 0.014%), headache (n = 60; 0.010%), low-grade fever (n = 50; 0.009%), and itching or rash (n = 20; 0.003%). No serious adverse events, such as anaphylaxis, seizures, or deaths were reported or attributed to the vaccine. Of the 223 AEFIs, 175 (78.5%) had complete documentation through the line listing system and were included in further analysis. Table 4 presents the distribution of these 175 AEFIs by age group, sex, local government area (LGA), and location type. The majority of cases occurred in children aged 1–4 years (n = 52; 29.7%) and 5–9 years (n = 50; 28.6%), followed by those aged 10–14 years (n = 40; 22.9%). Fewer cases were observed in the 15–19 (n = 18; 10.3%), 20–24 (n = 9; 5.1%), and 25–29 (n = 6; 3.4%) age groups, with no cases recorded among individuals aged 30 years and above. Males accounted for a slightly higher number of AEFI reports (n = 97; 55.4%) compared to females (n = 78; 44.6%). Geographically, the highest number of cases was reported in Fika LGA (n = 79; 45.1%), followed by Nangere (n = 71; 40.6%) and Potiskum (n = 25; 14.3%). When disaggregated by location type, the majority of AEFIs occurred in rural areas (n = 150; 85.7%), with urban locations accounting for the remaining 14.3% (n = 25). Table 4 Summary of Adverse Events Following Immunization (AEFI) by Age, Sex, LGA and Location, Yobe State, 2024 (n = 175) Variable AEFI % Age 1–4 52 29.7 5–9 50 28.6 10–14 40 22.9 15–19 18 10.3 20–24 9 5.1 25–29 6 3.4 30+ 0 0 Sex Male 97 55.4 Female 78 44.6 LGA Nangere 71 40.6 Fika 79 45.1 Potiskum 25 14.3 Location Rural 150 85.7 Urban 25 14.3 Discussion The 2024 meningococcal meningitis outbreak in Yobe State confirms a notable epidemiological shift in the circulating Neisseria meningitidis serogroups. Historically, serogroup A dominated large-scale epidemics across the African meningitis belt, including Nigeria. 3 However, current data indicate a transition towards serogroup C as the dominant strain, aligning with recent trends in northern Nigeria and West Africa following the widespread MenAfriVac deployment against serogroup A. 17,33 The emergence of serogroup C reinforces the need for broader multivalent vaccination strategies, such as Men5CV. 34 As in previous outbreaks, males were disproportionately affected. 35 , 36 This may reflect greater male exposure to risk factors, such as crowded markets, religious events, communal living, and inhalation exposures (e.g smoking, wood fire smoke exposure), which facilitate nasopharyngeal carriage and transmission 37 . 37 , 38 Higher male case-fatality may also stem from gender-related health-seeking differences, with evidence suggesting women seek care earlier. 39 The outbreak’s timing aligns with the typical late dry seasonal pattern observed across the region. 38,39 Hot, dry, and dusty conditions compromise nasopharyngeal mucosal immunity and facilitate transmission, whereas, rising humidity and rainfall reduce aerosolized dust and close contact spread, contributing to epidemic cessation. 40 , 41 In this outbreak, however, a sharp decline in cases began before the the rains, coinciding with the Men5CV vaccination campaign. While meningitis epidemics in the Sahel usually wane with the rains (May-June in Yobe), 36,40,41 the abrupt decline shortly after vaccine deployment suggests a likely intervention-driven effect. This is consistent with studies showing rapid declines in meningitis incidence and carriage following conjugate vaccination, 8,10 in contrast to the slower seasonal declines without vaccination. 42 Although causality cannot be proven, the strong temporal association supports the role of Men5CV in halting transmission. The age distribution showed expected susceptibility among children and young adults, corroborating findings from other meningococcal epidemics. 43 , 44 This may relate to higher contact rates and limited prior immunity. Older adults bore a lower disease burden but higher case fatality possibly due to immune senescence, comorbidities and delayed presentations. 20 , 45 Their exclusion from previous vaccination campaigns may also contribute. 7 , 46 These patterns highlight the need for age-tailored clinical vigilance and possible extension of vaccine coverage to at-risk older populations 7 , 47 As elsewhere in the meningitis belt 41 , 48 rural communities bore heavier burden, likely due to delayed outbreak detection, low vaccination coverage and environmental exposures. Contributing factors include overcrowding, poor nutrition, and wood smoke/dust exposures. 49 Yet urban centers like Potiskum were also affected, showing how population density and mobility sustain transmission. 3 , 41 Immunity gaps may persist in urban cohorts not reached by prior MenAfriVac campaigns or those aged out of routine programs. Conflict-related displacement likely exacerbated these vulnerabilities. The Boko Haram insurgency has displaced thousands into urban and peri-urban areas, 50,51 straining infrastructure, and facilitating disease spread. Seasonal nomadic migration may have also contributed to the spread. These rural-urban dynamics illustrate that meningitis outbreaks are not limited to remote settings but can thrive where socio-demographic risks converge. Variations in LGA case-fatality rate, including high mortality in low incidence areas, points to gaps in early detection and access to care. This underscores the need for surveillance strategies that prioritize not only high-incidence LGAs but also those with low case counts but high mortality. Nomadic populations were particularly vulnerable. Similar outbreaks in Nigeria have implicated nomadic movements and trade routes in meningitis spread. 41,48,52 Targeted approaches such as mobile vaccination teams and outreach in nomadic settlements are therefore essential. In this outbreak, the state Ministry of Health, with partner support, implemented a “ring vaccination” strategy using Men5CV, efficiently deploying limited vaccine resources to contain the epidemic. Vaccination coverage in Fika LGA exceeded 100%. This reflects limitations in population census-based projections and contextual factors. Fika experiences seasonal nomadic influx during the dry season because of its greener pastures compared to other parts of the state affected by Sahelian drought and desertification linked to climate change. WHO reports confirm seasonal normadic migration in northern Nigeria, with health services use along transit routes. 53 Fika also borders states concurrently affected by meningitis; cross-border vaccination of mobile groups has been well-documented in northern Nigeria, particularly when vaccine availability differs between adjoining states. 54 Finally, Fika was perceived as relatively safer than adjoining LGAs attracting people from less secure areas for vaccination. 55,56 Together, these factors explain why administered doses exceeded the estimated target population. Another key finding was the lack of documented MenAfriVac among most cases. While this may partly reflect poor record-keeping and recall bias, it highlights weaknesses in immunization systems, especially in conflict-affected areas and underscores the importance of strong routine immunization systems and accurate documentation, probably through digitization of the system. The use of a clinical case definition was both necessary and effective. Strong concordance with laboratory-confirmed cases suggests high sensitivity of syndromic diagnosis. 57–59 This highlights the importance of training frontline health workers to recognize meningitis symptoms and initiate prompt treatment, even while diagnostic capacity expands. A turning point in this outbreak was the deployment of the Men5CV, the first use of this vaccine in Nigeria and globally for outbreak control. The steep case decline following vaccination suggest effectiveness, 25,60 though causality cannot be established. This supports reactive vaccination as a critical tool to alter epidemic trajectories, even mid-outbreak. Men5CV broad serogroups coverage and favourable safety profile are promising, with most adverse effects minimal and self-limiting. Of 223 AEFI cases, only 175 had complete documentation, potentially under-representing some event types. Strengthening AEFI reporting is needed to improve safety monitoring during. Demographic differences in reporting likely reflect disparities in healthcare access and surveillance rather than safety concerns. Ongoing community engagement and transparent communication will be vital to sustain public trust. Yobe State’s experience provides early real-world evidence that Men5CV is both effective and safe for outbreak control. It supports recommendations for broader use across the meningitis belt, both reactively and via routine immunization. With strong surveillance and rapid response, the goal of eliminating epidemic meningitis by 2030 becomes more achievable. Continuous post-introduction monitoring will be essential to ensure sustained impact and public confidence. In summary, the Yobe outbreak underscores the emergence of serogroup C and demonstrates the potential of Men5CV to rapidly curb transmission, with a favorable safety profile. Strengthening surveillance, AEFI reporting, and targeted vaccination of high-risk groups will be critical for sustaining impact Conclusion The 2024 serogroup C meningococcal meningitis outbreak in Yobe State, Nigeria, followed patterns typical of epidemics in the African meningitis belt with the highest burden among children, young people, males and rural communities. The seasonal peak in the late dry season was consistent with regional trends, and strong concordance between clinical and laboratory diagnosis confirmed the appropriateness of case definition for rapid response. The reactive ring vaccination campaign with the novel Men5CV coincided with a marked decline in cases and deaths, demonstrating the potential of timely, targeted vaccination even amid an ongoing epidemic. These findings highlight the importance of vigilant surveillance, early diagnosis, and swift deployment of effective vaccines. The Yobe experience illustrates how new tools like Men5CV, integrated with established public health strategies, can advance the goal of eliminating meningitis epidemics in Africa. Public Health and Policy Implications Integrate Men5C into routine and seasonal vaccination strategies: Routine use of multivalent meningococcal conjugate vaccines, along with pre-dry-season mass vaccination campaigns, should be adopted to prevent outbreaks by reducing meningococcal carriage and building herd immunity. Prioritise targeted reactive vaccination during outbreaks: Rapid deployment of focused campaigns like ring vaccination should be used during outbreaks to optimise vaccine use and limit disease spread, especially in high-risk or hard-to-reach populations. Strengthen meningitis surveillance systems: Investments are needed to improve real-time case reporting, laboratory confirmation, and predictive tools such as climate data integration for early outbreak detection and tailored responses. Build capacity of the healthcare workforce: Continuous training in meningitis recognition, case management, and outbreak response will improve clinical outcomes and readiness for future epidemics. Engage communities and address misinformation: Culturally sensitive risk communication and community mobilisation can improve vaccine uptake, early treatment-seeking, and trust in public health interventions. Enhance preparedness and regional collaboration: Governments should invest in local vaccine production, diagnostics, and cross-border coordination to enable a faster, more cohesive regional response in line with the WHO’s Defeating Meningitis by 2030 strategy. Limitations This study has several important limitations. First, it was based on surveillance and line-list data collected during an emergency response, which may be subject to underreporting and missing information. Not all suspected meningitis cases could be laboratory confirmation due to overwhelming nature of the outbreak in a low-resource setting coupled with limited diagnostic capacity. Second, data on prior vaccination (especially receipt of the MenAfriVac serogroup A vaccine) were often incomplete or unreliable. Many patients did not know their vaccination status or lacked documentation. This made it difficult to accurately assess the role of pre-existing immunity, and it introduces potential misclassification and information bias in our analysis of risk factors. Third, as an observational outbreak report, our study can only infer associations rather than prove causation. For example, the decline in cases following the Men5C vaccination campaign is strongly suggestive of impact but could also be influenced by other coincident factors (such as the seasonal weather change). We did not have a comparison group or the ability to conduct analytical studies (e.g. vaccine effectiveness calculations) in the midst of the emergency. Despite these limitations, the study provides valuable insights into the epidemiology of a serogroup C meningococcal outbreak in a region that had not seen an epidemic in over a decade, and it offers practical lessons for improving outbreak response and prevention in similar environments. Abbreviations AEFI Adverse Events Following Immunization AOR Adjusted Odds Ratio CFR Case Fatality Rate CSF Cerebrospinal Fluid DSNO Disease Surveillance and Notification Officer EOC Emergency Operations Center IB VPD–Invasive Bacteria–Vaccine Preventable Diseases LGA Local Government Area Men5CV Meningococcal Serogroup A, C, W, Y, and X Conjugate Vaccine NCDC Nigeria Centre for Disease Control NmA Neisseria meningitidis serogroup A NmC Neisseria meningitidis serogroup C NRL National Reference Laboratory NTC No Template Control PCR Polymerase Chain Reaction qPCR Quantitative Polymerase Chain Reaction WHO World Health Organization Declarations Ethical approval and consent to participate: Ethical clearance for the secondary use of outbreak response data was granted by the Yobe State Ministry of Health Ethical Review Committee. Only anonymised surveillance and vaccination records were used, and no identifiable personal information was accessed. As the data were obtained during routine public health response activities, the requirement for individual informed consent was waived in accordance with national guidelines. Consent for publication: No individual person’s data, images, or identifying information are included in this manuscript. Therefore, consent for publication was not applicable. Data Availability: The raw datasets generated and analysed during the current study are publicly available in Zenodo (DOI: 10.5281/zenodo.15720689). Conflict of Interest: The authors declare that there is no conflict of interest Source of Funding: The study did not recive any specific grant from funding agenies in the public, commercial or not for profic sectors. The analysis was conducted as part of the routine public health responsibilities of the Yobe state Ministry of Health and collaborating partners Authors’ contributions: BWG and OO conceptualized the study and contributed to drafting and critical revisions. HSK performed data analysis and assisted in drafting and revising. MI coordinated data collection and field supervision. AB supported data collection and supervision. MBK contributed to data analysis and review. AA handled sample collection, laboratory analysis, and supervision; MOP assisted with sample analysis. MMB, HA, MLG, IMK, BB, HY, MBM, and IM reviewed the manuscript and provided critical input, with IM offering scientific mentorship. All authors read and approved the final manuscript. Acknowledgements: We would like to extend our special thanks and appreciation to the Yobe State Ministry of Health, the Department of Public Health, the Epidemiology Unit Yobe State Primary Health Care Board and the Africa Field Epidemiology Network (AFENET) Yobe State Field Office Damaturu, for the approval to use Cerebrospinal meningitis data for this study. 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Arq Neuropsiquiatr. 2016;74(11):875–80. Nissa S, Iftiyastuti B, Rizkita LD, Ihsana N, Selohandono A. The Relationship between the Classic Triad of Meningitis and Types of Meningitis. J La Medihealtico. 2024;5(4):848–56. Akaishi T, Kobayashi J, Abe M, Ishizawa K, Nakashima I, Aoki M, et al. Sensitivity and specificity of meningeal signs in patients with meningitis. J Gen Fam Med. 2019;20(5):193–8. World Health Organization (WHO). WHO combats cerebrospinal meningitis outbreak in Yobe State, Nigeria. 2024. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8262447","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581130452,"identity":"0beea72c-3b51-4df8-92ea-e0c7eeba91a0","order_by":0,"name":"Baba Waru Goni","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYBACAwYeBOfAByDBxk6KloMzQFqYSdHCDGYT0mLOfvbgZ56ae4nz3XsPHrb5tU2ej5mB8cPHHNxaLHvykqV5jhUnbjxzLuFwbt9twzZmBmbJmdvwOOxAjoF0DltC4sYZOQaHc3tuMwK1sDHz4tNy/o3x75x/UC2WPbftCWu5kWMmnduWkDhfAqiF4cftRIJaLGe8S7P+25dgvIHnjMHB3obbyW3MjM14/WLOn3v45oxvCbLz23uMP/z4c9t2fnvzwQ8f8WhBuPAAkGBsAzEZG4hQDwTyYHV/iFM8CkbBKBgFIwsAAA3RVfdRSUeKAAAAAElFTkSuQmCC","orcid":"","institution":"Yobe State University Teaching Hospital","correspondingAuthor":true,"prefix":"","firstName":"Baba","middleName":"Waru","lastName":"Goni","suffix":""},{"id":581130454,"identity":"738d6751-de7f-4547-ba96-789ca3ef06ea","order_by":1,"name":"Hamidu Suleiman Kwairanga","email":"","orcid":"","institution":"Gombe State University","correspondingAuthor":false,"prefix":"","firstName":"Hamidu","middleName":"Suleiman","lastName":"Kwairanga","suffix":""},{"id":581130456,"identity":"bf083247-2fd1-4b34-b8c3-2f5ecb5be2b4","order_by":2,"name":"Olugbenga Oguntunde","email":"","orcid":"","institution":"Yobe State University","correspondingAuthor":false,"prefix":"","firstName":"Olugbenga","middleName":"","lastName":"Oguntunde","suffix":""},{"id":581130458,"identity":"9fb8af6d-f819-4983-b3c5-5803ba95424d","order_by":3,"name":"Mohammed Isiaka","email":"","orcid":"","institution":"Yobe State Primary Healthcare Board Damaturu","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Isiaka","suffix":""},{"id":581130459,"identity":"b5cee520-2f62-4a3b-8e6d-57196f3c901d","order_by":4,"name":"Ahmad Ba’aba","email":"","orcid":"","institution":"Yobe State Field Office","correspondingAuthor":false,"prefix":"","firstName":"Ahmad","middleName":"","lastName":"Ba’aba","suffix":""},{"id":581130461,"identity":"93dcb28c-381b-4e7e-a732-0e235d4f3791","order_by":5,"name":"Musa Mohammed Baba","email":"","orcid":"","institution":"Yobe State University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Musa","middleName":"Mohammed","lastName":"Baba","suffix":""},{"id":581130462,"identity":"01bba9a5-7bcb-4c58-892a-70058eb1a004","order_by":6,"name":"Habu Abdul","email":"","orcid":"","institution":"Yobe State University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Habu","middleName":"","lastName":"Abdul","suffix":""},{"id":581130463,"identity":"0d2f91c7-a4c4-4891-9d30-ba4092ebef11","order_by":7,"name":"Muhammad Lawan Gana","email":"","orcid":"","institution":"Yobe State University","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Lawan","lastName":"Gana","suffix":""},{"id":581130464,"identity":"0a2cb6f4-6349-40ec-adb6-2ea5dcb6dfde","order_by":8,"name":"Ibrahim Musa Kida","email":"","orcid":"","institution":"University of Maiduguri","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"Musa","lastName":"Kida","suffix":""},{"id":581130465,"identity":"3dabf47c-82ec-4037-8c38-984c14dc0d1f","order_by":9,"name":"Bukar Bakki","email":"","orcid":"","institution":"University of Maiduguri","correspondingAuthor":false,"prefix":"","firstName":"Bukar","middleName":"","lastName":"Bakki","suffix":""},{"id":581130466,"identity":"1bfc4dd2-e10e-4a5c-aa8d-593bba0e0e46","order_by":10,"name":"Haruna Yusuph","email":"","orcid":"","institution":"University of Maiduguri","correspondingAuthor":false,"prefix":"","firstName":"Haruna","middleName":"","lastName":"Yusuph","suffix":""},{"id":581130467,"identity":"370e4908-031b-4b26-8486-fae81ace8b17","order_by":11,"name":"Modibbo Babagana-Kyari","email":"","orcid":"","institution":"Yobe State University","correspondingAuthor":false,"prefix":"","firstName":"Modibbo","middleName":"","lastName":"Babagana-Kyari","suffix":""},{"id":581130469,"identity":"f199df85-d43e-4f82-b920-81f8f06b8d9e","order_by":12,"name":"Abdullahi Ago","email":"","orcid":"","institution":"Yobe State Ministry of Health","correspondingAuthor":false,"prefix":"","firstName":"Abdullahi","middleName":"","lastName":"Ago","suffix":""},{"id":581130472,"identity":"79e7ced2-a899-460a-90be-d912df05dbb6","order_by":13,"name":"Michael Oladotun Popoola","email":"","orcid":"","institution":"10.\tBacteriology Unit, National Reference Laboratory (NRL), Nigeria Centre for Disease Control (NCDC) Abuja, Nigeria","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"Oladotun","lastName":"Popoola","suffix":""},{"id":581130473,"identity":"24eedd78-4b35-4664-8502-6b2692af0a3e","order_by":14,"name":"Mahmoud Bukar Maina","email":"","orcid":"","institution":"University of Sussex","correspondingAuthor":false,"prefix":"","firstName":"Mahmoud","middleName":"Bukar","lastName":"Maina","suffix":""},{"id":581130474,"identity":"c6f9e69c-26bc-43f6-a5cf-30acf22e4e98","order_by":15,"name":"Idris Mohammed","email":"","orcid":"","institution":"Gombe State University","correspondingAuthor":false,"prefix":"","firstName":"Idris","middleName":"","lastName":"Mohammed","suffix":""}],"badges":[],"createdAt":"2025-12-02 15:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8262447/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8262447/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101362478,"identity":"b8b12dd0-6f92-4ffe-9028-44aa2ea66d65","added_by":"auto","created_at":"2026-01-29 00:29:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1579458,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMap showing the Africa Meningitis Belt and Yobe State, Nigeria, highlighting study LGAs and geographical boundaries\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe map shows the geographical context of the study area, highlighting Yobe State’s 17 Local Government Areas (LGAs) where meningitis surveillance and outbreak response activities were conducted during the 2024 outbreak. \u003cem\u003eSource Plate A: US Center for Disease Control and Prevention)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8262447/v1/b7306667d2f5812dea83f9cc.png"},{"id":101362481,"identity":"242a1085-3181-4f82-8948-fdaa3f65c036","added_by":"auto","created_at":"2026-01-29 00:29:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1000520,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial distribution of cerebrospinal meningitis Incidence Rates(A) and Case Fatality Rates(CFR) by LGA, Yobe State, 2024\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese maps show the spatial heterogeneity of the outbreak. Panel A reveals higher incidence rates concentrated in central and southern LGAs such as Potiskum and Fika. Panel B demonstrates that case fatality rates varied independently of incidence, with some LGAs reporting high CFRs despite lower case counts, underscoring the need for targeted support in those areas.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8262447/v1/88b0605138e09d8842ce16bb.png"},{"id":101398122,"identity":"8681e5f2-a167-4bfa-8652-8954098c2ee6","added_by":"auto","created_at":"2026-01-29 09:39:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":442310,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWeekly epidemic curve of suspected meningitis cases in Yobe State, 2024\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe epidemic curve illustrates the temporal progression of the outbreak. A rapid rise in cases was observed in late March, peaking in mid-April before declining. This pattern aligns with the timing of reactive vaccination and emergency response deployment.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8262447/v1/5c88a8c23402c51248658e4d.png"},{"id":101362482,"identity":"9b4b01dd-f974-4476-a104-98b1311d5381","added_by":"auto","created_at":"2026-01-29 00:29:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":78128,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLaboratory Test Results Among Cerebrospinal Meningitis Cases, Yobe State, 2024\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the confirmed positive cases, Neisseria meningitidis serogroup C (NmC) was the predominant pathogen, accounting for 93.8% of positives and representing just over half of all test results (52.7%). In contrast, \u003cem\u003eHaemophilus influenzae\u003c/em\u003eand \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e were detected in 4.9% and 0.9% of positive cases, corresponding to only 2.6% and 0.5% of all tested cases, respectively.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8262447/v1/8036e2ae1dbe9dae13323be0.png"},{"id":101398559,"identity":"77a2cfc6-725d-4850-a6fd-a36dd1669140","added_by":"auto","created_at":"2026-01-29 09:42:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":443112,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of meningococcal vaccination(Men5CV) coverage among suspected cases by LGA, Yobe State, 2024\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe bar charts illustrate the distribution and timing of the reactive meningococcal vaccination campaign in Yobe State. Panel A shows that Potiskum received the highest number of doses and vaccinated individuals, followed by Fika and Nangere. Panel B demonstrates that the mass vaccination campaign was implemented in late March, coinciding with the peak of reported cases. A notable and sustained decline in case numbers followed the rollout, suggesting a potential impact of the campaign in curbing further transmission.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8262447/v1/117cec92c8bb68ac3d94b9c4.png"},{"id":109160481,"identity":"9be4580a-b6ad-46d9-ab25-20f78e6f339d","added_by":"auto","created_at":"2026-05-13 07:32:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3730363,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8262447/v1/1d7b792f-8d81-43f5-a809-96a336a95860.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"First Field Use of the Pentavalent Meningococcal Conjugate Vaccine (Men5CV) in Response to a Serogroup C Meningitis Outbreak: Evidence from Yobe State, Northeastern Nigeria","fulltext":[{"header":"Contributions to the Literature","content":"\u003cul\u003e\n \u003cli\u003eThe study demonstrates how a new 5-in-1 meningitis vaccine (Men5CV) worked in real life during an outbreak in Nigeria.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eProvides first evidence that Men5CV can quickly stop disease spread and is safe for people.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHighlights the need for routine vaccination and better outbreak response in hard-to-reach communities.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSuggests practical steps for governments to prevent future meningitis epidemics.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Background","content":"\u003cp\u003eGlobally, meningitis remains a persistent public health threat despite advances in vaccines and diagnostics. In 2019, an estimated 2.5\u0026nbsp;million people developed meningitis and approximately 240,000 died from the disease.\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The burden falls disproportionately on sub-Saharan Africa\u0026rsquo;s \u0026ldquo;Meningitis Belt,\u0026rdquo; a region of 26 countries from Senegal to Ethiopia characterized by recurrent outbreaks during the dry season (typically December - June).\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Devastating epidemics have historically occurred every few years; the 1996 West African epidemic alone resulted in over 250,000 cases and 25,000 deaths.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Before 2010, serogroup A \u003cem\u003eN. meningitidis\u003c/em\u003e (NmA) was responsible for 80\u0026ndash;85% of epidemic meningitis cases in this region.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eNigeria is one of the most affected countries within the Meningitis Belt and has experienced repeated large-scale outbreaks since the early 20th century. Major epidemics were recorded in 1996, 2003, 2009, and 2017, predominantly in northern states where climatic factors such as dust, low humidity, and high temperatures amplify transmission.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The 1996 outbreak in Nigeria alone caused more than 109,000 cases and nearly 12,000 deaths.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e These recurrent epidemics highlight the vulnerability of the region and the need for robust, broad-spectrum meningitis control measures.\u003c/p\u003e \u003cp\u003eA major shift in meningococcal epidemiology occurred after the introduction of MenAfriVac, a monovalent serogroup A conjugate vaccine, beginning in 2010. Nigeria introduced MenAfriVac through mass vaccination campaigns in 2013, targeting individuals aged 1\u0026ndash;29 years, the group at highest risk of epidemic meningitis. The impact was remarkable as serogroup A meningococcal disease virtually disappeared in countries achieving high coverage.\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e By 2015, more than 220\u0026nbsp;million people across 15 African countries had been vaccinated, leading to the elimination of NmA epidemics and demonstrating strong herd immunity effects.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHowever, the decline of NmA created an ecological niche that was increasingly occupied by other serogroups. A growing body of evidence documents the emergence of serogroups C, W, X, and Y in various countries of the belt.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e These trends exposed the limitations of monovalent and polysaccharide vaccines, which provide limited and short-lived protection against multiple serogroups and do not support long-term mucosal immunity or herd protection. In particular, serogroup X, although historically less common, remained a concern because no licensed vaccine targeted it prior to 2023.\u003c/p\u003e \u003cp\u003eSerogroup C (NmC) emerged as a major threat in the mid-2010s. A novel NmC strain first detected in northern Nigeria in 2013 caused localized outbreaks in 2014\u0026ndash;2016.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The strain then spread to Niger in 2015, triggering the largest global NmC epidemic on record with over 8,500 cases.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e These events were followed by a large NmC epidemic in northwestern Nigeria in 2016\u0026ndash;2017, during which more than 14,000 suspected cases were reported and approximately 80% of confirmed cases were due to NmC.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Reactive vaccination campaigns using serogroup C and ACWY vaccines helped curb transmission but underscored the urgent need for broader, more affordable, and more durable meningococcal vaccines.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eBefore 2023, available polyvalent conjugate meningococcal vaccines were limited. Quadrivalent ACWY vaccines offered broader protection but were costly and used mainly for reactive campaigns with restricted availability.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The absence of serogroup X coverage, combined with the rising relevance of non-A serogroups, created a strong rationale for a multivalent vaccine specifically designed for the African Meningitis Belt.\u003c/p\u003e \u003cp\u003eTo address these gaps, the Serum Institute of India and PATH developed a pentavalent conjugate vaccine - Men5CV, covering serogroups A, C, W, Y, and X. Clinical trials in Africa demonstrated strong immunogenicity across all five serogroups, including more than 97% seroconversion for serogroup X and high responses for A, C, W, and Y, alongside a favorable safety profile.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e After 13 years of development, Men5CV was prequalified by the WHO in July 2023 and formally recommended in October 2023 for use in epidemic response and routine immunization strategies.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Men5CV is the first vaccine to offer protection against all major epidemic-causing meningococcal serogroups in a single shot. Its approval for the global emergency stockpile by the International Coordinating Group (ICG) in late 2023 further enabled its deployment during outbreaks.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eNigeria subsequently became the first country worldwide to deploy Men5CV in the context of an active epidemic.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Beginning in late 2023, a serogroup C meningococcal outbreak spread across seven northern states. By March 2024, a cumulative 1,742 suspected cases and 153 deaths had been reported across Adamawa, Bauchi, Gombe, Jigawa, Katsina, Yobe, and Zamfara states.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Yobe State, which had not experienced a major epidemic in over a decade, largely due to the success of MenAfriVac, confirmed its first NmC epidemic in early 2024. In response, Nigerian health authorities, with support from WHO and Gavi, launched a reactive Men5CV ring vaccination campaign in March 2024. Approximately one million individuals aged 1\u0026ndash;29 years across affected states were targeted, with priority given to outbreak hotspots.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDespite the major global significance of Men5CV, no published field studies had evaluated its real-world performance, operational feasibility, or safety during an active epidemic at the time of this outbreak. Evidence on how Men5CV functions outside clinical trials, particularly in resource-limited, conflict-affected settings such as Yobe State, is essential for guiding future policy, improving outbreak response, and informing global strategies to eliminate meningitis epidemics.\u003c/p\u003e \u003cp\u003eThis study presents the first field-based evaluation of the 2024 NmC outbreak in Yobe State, northeast Nigeria, following the deployment of the pentavalent Men5CV vaccine. It describes outbreak characteristics, assesses vaccination coverage and safety, documents the operational processes surrounding the first-ever Men5CV campaign, and evaluates the implications for future epidemic preparedness and meningitis control across the African Meningitis Belt.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eWe conducted a descriptive observational study of the meningococcal meningitis outbreak that occurred in Yobe State, Nigeria, during the 2023\u0026ndash;2024 dry season. This study utilized a retrospective analysis of surveillance data and administrative records from the vaccination campaign, applying descriptive epidemiological methods and ecological analysis to characterize disease trends and assess the impact of the reactive Men5CV vaccination response implemented during the outbreak.\u003c/p\u003e \u003cp\u003eYobe State is located in northeastern Nigeria and falls within the African Meningitis Belt (Fig.\u0026nbsp;1). It comprises 17 Local Government Areas (LGAs) with an estimated population of approximately 3.4\u0026nbsp;million in 2023.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e The population is largely rural and agrarian, and the climate is arid to semi-arid with an extended dry season (October to May). Environmental conditions such as low humidity and Harmattan winds favour meningococcal transmission. Prior to 2024, Yobe had not experienced a large-scale meningitis outbreak since the national rollout of MenAfriVac in 2013, although isolated NmA cases were reported in 2017 in the state\u0026rsquo;s northwest during a regional epidemic. Health service delivery in Yobe includes primary health centers, State-level general and specialist hospitals, and a tertiary referral hospital in the state capital, Damaturu. In March 2024, the State Ministry of Health supported by the Nigeria Centre for Disease Control (NCDC), activated an Incident Management System and Emergency Operations Center (EOC) to coordinate outbreak response.\u003c/p\u003e \u003cp\u003eFigure 1 about here\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 1: Map showing the Africa Meningitis Belt and Yobe State, Nigeria, highlighting study LGAs and geographical boundaries\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe map shows the geographical context of the study area, highlighting Yobe State\u0026rsquo;s 17 Local Government Areas (LGAs) where meningitis surveillance and outbreak response activities were conducted during the 2024 outbreak. \u003cem\u003eSource Plate A: US Center for Disease Control and Prevention)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eCase Definitions and Surveillance\u003c/b\u003e: We applied standard World Health Organization (WHO) definitions for meningococcal meningitis surveillance:\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eSuspected case\u003c/em\u003e: Any person with sudden onset of fever (\u0026ge;\u0026thinsp;38.5\u0026deg;C rectal or \u0026ge;\u0026thinsp;38.0\u0026deg;C axillary) and neck stiffness or signs of meningeal irritation. In infants, a bulging fontanelle or lethargy could substitute for neck stiffness.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eProbable case\u003c/em\u003e: A suspected case with turbid/purulent cerebrospinal fluid (CSF), CSF leukocyte count\u0026thinsp;\u0026gt;\u0026thinsp;10/\u0026micro;L, or positive Gram stain. In the context of a confirmed outbreak, clinically compatible cases without lumbar puncture were also considered probable due to epidemiologic linkage.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eConfirmed case\u003c/em\u003e: A suspected or probable case with laboratory confirmation of \u003cem\u003eNeisseria meningitidis\u003c/em\u003e from CSF or blood by PCR, culture, or agglutination testing. Serogroup confirmation was based on PCR testing.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eSurveillance was enhanced during the outbreak. Health workers across all health facilities were sensitized to the case definitions and instructed to immediately notify the LGA Disease Surveillance and Notification Officer (DSNO) upon identifying any suspected case. Community-based surveillance networks, including polio informants, were mobilized to report suspicious febrile illnesses and deaths. A standardized national CSM case-based reporting form was used to line-list each case, capturing clinical features, demographics, vaccination status, and outcome. Line lists were submitted to the EOC daily.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLaboratory Diagnosis\u003c/strong\u003e \u003cp\u003eCSF samples were collected aseptically at the point of care. Initial testing (Gram stain, cell count) was done at state-level laboratories when feasible. Samples were then transported under cold chain to the National Reference Laboratory (NRL) in Abuja.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eReal-time PCR Detection of Meningitis-Associated Bacteria Pathogens\u003c/h3\u003e\n\u003cp\u003eReal-time PCR (qPCR) assays were performed at the NRL using the QuantStudio 12K Flex platform, in accordance with standardized Nigeria Centre for Disease Control (NCDC) protocols aligned to the WHO Global invasive Vaccine-Preventable Disease (IB-VPD) surveillance guidelines.\u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eDNA Extraction\u003c/h3\u003e\n\u003cp\u003eGenomic DNA was extracted from cerebrospinal fluid (CSF) using the QIAamp DNA Mini Kit (Qiagen), following the manufacturer\u0026rsquo;s protocol.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Extracts were aliquoted and stored at -20\u003csup\u003e0\u003c/sup\u003eC prior to amplification.\u003c/p\u003e\n\u003ch3\u003eqPCR Assay\u003c/h3\u003e\n\u003cp\u003eEach 20 \u0026micro;L reaction mixture was prepared using Perfecta qPCR ToughMix (QuantaBio), pathogen-specific primers and hydrolysis probes, PCR-grade water and 2 \u0026micro;L of template DNA. Reaction mixtures were assembled into 96-well plates under contamination-controlled conditions using a unidirectional workflow. Each run included pathogen-specific positive controls, no-template controls (NTCs) to monitor for contamination and internal amplification controls (e.g human RNaseP gene or synthetic inhibition control) to assess DNA extraction and PCR efficiency. Positive controls were sourced and validated in accordance with NCDC protocols aligned to WHO guidelines. Thermal cycling was performed under the following conditions: initial denaturation at 95\u0026deg;C for 10 minutes, followed by 40 amplification cycles at 95\u0026deg;C for 15 seconds and 60\u0026deg;C for 60 seconds.\u003c/p\u003e\n\u003ch3\u003ePathogen Detection and Typing\u003c/h3\u003e\n\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eN. meningitidis\u003c/em\u003e: identification was based on amplification of the \u003cem\u003ectrA\u003c/em\u003e gene, with sero-grouping performed via detection of capsule biosynthesis genes: \u003cem\u003esynA\u003c/em\u003e (serogroup A), \u003cem\u003esiaD\u003c/em\u003e (serogroups B, C, Y, W), and \u003cem\u003emynB\u003c/em\u003e(serogroup X), using WHO-validated multiplex assays.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e: The lytA gene was targeted for species confirmation. Optional serotyping of vaccine-related serotypes was conducted as needed.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eHaemophilus influenzae\u003c/em\u003e: Detection involved amplification of the bexA gene, with capsular typing based on type-specific primers targeting the cap locus (types a\u0026ndash;f).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFluorescence Data Analysis\u003c/h2\u003e \u003cp\u003eFluorescence data were analysed using QuantStudio software (v1.3, Applied Biosystems). A sample was considered positive if the cycle threshold (Ct) was \u0026lt;\u0026thinsp;36, based on WHO/CDC guidance.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Positive results were further validated by comparison with standard curves generated from known DNA concentrations.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eOutbreak Response and Men5CV Vaccination Campaign\u003c/strong\u003e \u003cp\u003eThe outbreak response was led by the Yobe State EOC in collaboration with NCDC and WHO. Interventions included public awareness, free antibiotics, clinical kits, and reactive vaccination. The campaign deployed the pentavalent meningococcal conjugate vaccine (Men5CV) for the first time in a field outbreak setting.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe ring vaccination strategy targeted high-risk LGAs based on case counts and WHO epidemic thresholds (\u0026gt;\u0026thinsp;10 cases/100,000 per week). Out of the seven LGAs that accounted for over 95% of reported cases (Potiskum, Nangere, Fune, Fika, Gulani, Damaturu, and Gujba), the top 3 were selected. These include Potiskum, Nangere and Fika. The campaign was implemented from 25\u0026ndash;28 March 2024 (epidemiologic week 13). Target population was persons aged 1\u0026ndash;30 years. Children less than 12 months were excluded due to age-specific vaccine indications.\u003c/p\u003e \u003cp\u003eVaccination was conducted via fixed, outreach, and mobile teams. Cold chain was maintained at 2\u0026ndash;8\u0026deg;C using vaccine carriers. One 0.5 mL dose was administered intramuscularly. Paper tally sheets recorded vaccinations by age and location. Community sensitization included radio spots and engagement with traditional leaders.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eVaccination Coverage Assessment\u003c/strong\u003e \u003cp\u003eAdministrative coverage was calculated as doses administered divided by projected target population per LGA. Target populations were estimated from 2023 National Bureau of Statistics data.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Post-campaign rapid coverage assessments in select communities validated administrative data, although case-level vaccination status was not reliably documented.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData Sources\u003c/strong\u003e \u003cp\u003eWe used four main data sources,\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLine list: The case-based line list served as the primary dataset for epidemiologic analysis. It included anonymized patient-level information such as age, sex, residence, symptom onset date, clinical features, outcome, and laboratory results, and was continuously updated by surveillance officers through June 2024.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDaily surveillance call-ins: Each day, designated LGA focal persons reported aggregated case counts, deaths, and hospital resource use to the Emergency Operations Center via phone. These daily summaries provided near-real-time situational awareness and were used to validate and supplement the case-based line list.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eVaccination records: Vaccination history was primarily assessed through patient-held immunization cards and caregiver recall. However, most patients lacked verifiable documentation, and reliance on verbal reporting was common.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAEFI logs: Adverse events following immunization were reported using standardized forms completed by frontline health workers and monitored by the EOC\u0026rsquo;s immunization safety team. These logs documented both mild and serious events post-vaccination and supported post-campaign safety assessment.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis:\u003c/h2\u003e \u003cp\u003eAll data analyses were conducted using Python (version 3.11), leveraging libraries such as pandas, numpy, and statsmodels. Incidence rates were calculated by dividing the number of confirmed or suspected meningitis cases in each Local Government Area (LGA) by the estimated LGA population for 2024, and expressed per 10,000 population. Case fatality rates (CFRs) were computed as the proportion of deaths among the total number of suspected cases, expressed as percentages.\u003c/p\u003e \u003cp\u003eCategorical variables such as sex, age group, residence, vaccination status were summarized using frequencies and proportions. Bivariate associations between patient characteristics and mortality were assessed using Chi-square tests. Factors independently associated with death were explored using multivariate logistic regression, with adjusted odds ratios (AORs) and 95% confidence intervals (CIs) reported and statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eFor vaccination status, patients with unknown or undocumented MenAfriVac status were grouped with those reporting no prior MenA vaccination. None of the cases had evidence of receiving the full two-dose MenAfriVac schedule. Administrative vaccination data were compiled from tally sheets filled by immunization teams during the reactive Men5CV campaign. Target population estimates were drawn from microplans based on demographic projections (from 2006 population census),\u003csup\u003e26\u003c/sup\u003e enabling calculation of coverage at ward and LGA levels.\u003c/p\u003e \u003cp\u003eSpatial analysis, including choropleth maps of incidence and CFRs, was conducted using ArcMap version 10.8.2, part of the ArcGIS Desktop suite (Esri, Redlands, CA, USA). Epidemic trends were visualized using temporal plots of weekly and monthly case counts. Adverse events following immunization (AEFI) were summarized using descriptive statistics.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEthical Considerations\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThis study was conducted as part of an emergency public health response to a meningitis outbreak in Yobe State, Nigeria. All data used in the study were fully anonymized prior to analysis, with no personal identifiers retained. The line-listing, vaccination records, and surveillance datasets were accessed with authorization from the Yobe State Ministry of Health, in accordance with national outbreak response protocols.\u003c/p\u003e \u003cp\u003eAlthough the primary aim was outbreak control and not research, formal ethical approval for the use of the data for analysis and dissemination was obtained from the Yobe State Ministry of Health Ethical Review Committee (MOH/GEN/747/Vol.1). No individual-level consent was required as data were collected during routine surveillance and response activities in line with established national guidelines.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDemographic Characteristics of Cases\u003c/h2\u003e \u003cp\u003eA total of 2,948 suspected meningococcal meningitis cases were reported during the outbreak period (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Demographic analysis revealed significant patterns across age, sex, vaccination status, residential location, and admission status. The mean age of cases was 13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6 years. The outbreak disproportionately affected children and adolescents, with the 1\u0026ndash;9 and 10\u0026ndash;19 year age groups jointly accounting for 2,498 cases (84.8% of all infections). The 10\u0026ndash;19 year cohort was the most affected, comprising 1,567 cases (53.2%) and 54 deaths (CFR\u0026thinsp;=\u0026thinsp;3.4%), followed by children aged 1\u0026ndash;9 years, accounting for 931 cases (31.6%) with a slightly higher CFR of 3.8%. Adults aged 20\u0026ndash;40 years represented 379 cases (12.9%) and experienced a CFR of 3.2%, while individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;40 years accounted for only 71 cases (2.4%) but had the highest case fatality ratio at 5.6%. Despite these differences, the association between age group and mortality was not statistically significant (χ\u0026sup2; = 1.23; p\u0026thinsp;=\u0026thinsp;0.75).\u003c/p\u003e \u003cp\u003eThere was a slight male predominance among the cases. Males accounted for 1,672 cases (56.7%). In contrast, females accounted for 1,276 cases (43.3%), giving a male-to-female ratio of approximately 1.3:1. Men also experienced a higher number and rate of death (73 deaths; CFR 4.4%) compared to females (32 deaths; CFR 2.5%), a statistically significant difference (X\u0026sup2; = 6.74; p\u0026thinsp;=\u0026thinsp;0.0094).\u003c/p\u003e \u003cp\u003eThe majority of individuals affected by this outbreak had no record of prior immunization against meningococcal serogroup A. Analysis of vaccination history based on patient records and immunization cards revealed that 99.3% of meningitis cases had either zero-dose (60.4%) or unknown (38.9%) MenA vaccine status, indicating unverifiable MenAfriVac status. Only 0.7% of cases had any history of MenAfriVac vaccination, and none had completed the full two-dose schedule.\u003c/p\u003e \u003cp\u003eIn terms of residential location, rural communities were more heavily impacted than urban centers. Overall, 1,989 cases (67.4%) were reported from rural areas compared to 959 cases (32.5%) in urban areas. Of the total 2948 patients, 105 died, and the majority (99%) of these deaths occurred among those who were admitted as inpatients (CFR\u0026thinsp;=\u0026thinsp;4.0%), while only one death occurred among outpatients (CFR\u0026thinsp;=\u0026thinsp;0.3%) (X\u0026sup2; = 10.53; p\u0026thinsp;=\u0026thinsp;0.0012).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate Analysis of Mortality by Demographic, Vaccination, and Location Characteristics among suspected Cerebrospinal Meningitis cases (n\u0026thinsp;=\u0026thinsp;2948)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003cp\u003e(n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDead\u003c/p\u003e \u003cp\u003e(n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCFR (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group(Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash; 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e896 (31.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e931(31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,513 (53.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (51.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,567 (53.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e367 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e379 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,599 (56.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73(69.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,672 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,244 (43.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (30.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,276 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccination Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne dose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20(0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1719 (60.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (59.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1781(60.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1106 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (39.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1147(38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInpatients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2512(88.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104(99.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2616(88.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e331(11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e331(11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1926(67.7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63(60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1989 (67.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e917 (32.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e959 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA logistic regression analysis was conducted to identify factors independently associated with mortality among suspected meningitis cases (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Key predictors included sex, age group, residential location (urban vs rural), vaccination status, and admission status. Male sex was significantly associated with increased odds of death (adjusted odds ratio [AOR]\u0026thinsp;=\u0026thinsp;1.74; 95% CI: 1.14\u0026ndash;2.66; p\u0026thinsp;=\u0026thinsp;0.011). Compared to children under 10 years (reference group), none of the older age groups were statistically significant predictors of mortality: age 10\u0026ndash;19 years (AOR\u0026thinsp;=\u0026thinsp;0.87; 95% CI: 0.56\u0026ndash;1.36; p\u0026thinsp;=\u0026thinsp;0.546), age 20\u0026ndash;40 years (AOR\u0026thinsp;=\u0026thinsp;0.91; 95% CI: 0.46\u0026ndash;1.78; p\u0026thinsp;=\u0026thinsp;0.780), and age\u0026thinsp;\u0026ge;\u0026thinsp;40 years (AOR\u0026thinsp;=\u0026thinsp;1.56; 95% CI: 0.53\u0026ndash;4.57; p\u0026thinsp;=\u0026thinsp;0.419). Urban residence showed no significant association with death (AOR\u0026thinsp;=\u0026thinsp;1.09; 95% CI: 0.72\u0026ndash;1.66; p\u0026thinsp;=\u0026thinsp;0.691). Additionally, receipt of one dose of MenAfriVac was not associated with increased odds of death (AOR\u0026thinsp;=\u0026thinsp;0.42; 95% CI: 0.09\u0026ndash;1.91; p\u0026thinsp;=\u0026thinsp;0.260), nor was unknown vaccination status (AOR\u0026thinsp;=\u0026thinsp;0.37; 95% CI: 0.08\u0026ndash;1.74; p\u0026thinsp;=\u0026thinsp;0.208). In contrast, being managed as an outpatient was significantly protective, with 93% lower odds of death compared to inpatients (AOR\u0026thinsp;=\u0026thinsp;0.07; 95% CI: 0.01\u0026ndash;0.54; p\u0026thinsp;=\u0026thinsp;0.010).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression of factors associated with death among suspected Cerebrospinal Meningitis cases in Yobe State, 2024 (n\u0026thinsp;=\u0026thinsp;2,948)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (ref: 0\u0026ndash;9 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;19 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u0026ndash;1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.46\u0026ndash;1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.780\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.53\u0026ndash;4.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (ref: Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.14\u0026ndash;2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccination status (ref: 1 dose)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u0026ndash;1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u0026ndash;1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence (ref: Rural/Nomadic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.72\u0026ndash;1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.691\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission status (ref: Inpatient)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u0026ndash;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGeographical and spatial Distribution of Cases\u003c/h2\u003e \u003cp\u003eThe outbreak was geographically widespread but varied in intensity across the State. Of the state\u0026rsquo;s 17 LGAs, 12 (70.6%) reported suspected meningitis cases. Potiskum LGA, one of the more populous districts, recorded the highest number of cases (810; 27.5% of all cases). Other LGAs with high case counts included Fune (606; 20.6%), Fika (539; 18.3%), and Nangere (472; 16%). When adjusted for population, the incidence rates were highest in Nangere (31.7 per 100,000 population), followed by Potiskum (23.3/10,000), Fika (23.2/10,000) and Fune (11.9/10,000). These high-burden LGAs formed a contiguous belt in the south-central zone of the state. In contrast, Tarmuwa and Bade LGAs recorded fewer than 10 cases each, with incidence rates below 10 per 10,000. A map of LGA-level incidence rate is shown in Fig.\u0026nbsp;2A.\u003c/p\u003e \u003cp\u003eFigure 2 about here\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2: Spatial distribution of cerebrospinal meningitis Incidence Rates(A) and Case Fatality Rates(CFR) by LGA, Yobe State, 2024\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThese maps show the spatial heterogeneity of the outbreak. Panel A reveals higher incidence rates concentrated in central and southern LGAs such as Potiskum and Fika. Panel B demonstrates that case fatality rates varied independently of incidence, with some LGAs reporting high CFRs despite lower case counts, underscoring the need for targeted support in those areas.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEpidemic curve and Temporal Distribution\u003c/h2\u003e \u003cp\u003eThe temporal epidemic curve (Fig.\u0026nbsp;3) reveals that cases surged rapidly to a peak in March 2024, when 1,159 cases (39.3% of the total) and 34 deaths were recorded (monthly CFR 2.9%). Thereafter, the outbreak subsided over the next three months: 755 cases were recorded in April, 283 in May and just 41 in June at which point no further deaths were reported. This sharp rise and gradual fall over a four-month interval indicate a single epidemic wave confined to the late dry-season months, as illustrated by the weekly trend in Fig.\u0026nbsp;3.\u003c/p\u003e \u003cp\u003eFigure 3 about here\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 3: Weekly epidemic curve of suspected meningitis cases in Yobe State, 2024\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe epidemic curve illustrates the temporal progression of the outbreak. A rapid rise in cases was observed in late March, peaking in mid-April before declining. This pattern aligns with the timing of reactive vaccination and emergency response deployment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eClinical Outcomes and Case Fatality\u003c/h2\u003e \u003cp\u003eIn total, 105 deaths occurred during the outbreak, giving an overall case fatality ratio (CFR) of 3.6% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Males experienced a higher CFR (4.4%) compared to females (2.5%). Adults aged over 40 years had the highest age-specific CFR at 5.6%, despite forming the smallest fraction of total cases. In contrast, children aged 1\u0026ndash;9 years had a CFR of 3.8%, while those aged 10\u0026ndash;19 years had a CFR of 3.4%, and adults aged 20\u0026ndash;40 years recorded a CFR of 3.2%. Most mortalities occurred among inpatients with a CFR of 4.0% compared to 0.3% among outpatients. Among the 20 individuals with a documented history of meningitis vaccination, two deaths were recorded (CFR\u0026thinsp;=\u0026thinsp;10%), although this estimate is based on very small numbers. Bade LGA recorded only 4 cases and 1 mortality, translating to a LGA-specific CFR of 25%, whereas Potiskum had 17 mortalities among 780 cases (CFR\u0026thinsp;=\u0026thinsp;2.2%). Most LGAs recorded CFRs ranging between 1% and 4% (Fig.\u0026nbsp;2B).\u003c/p\u003e \u003cp\u003eClinically, most suspected cases had the classic symptoms of meningitis (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Approximately 95.5% had documented fever at onset, and over 90.8% reported severe headache. Meningeal signs such as neck stiffness were commonly but not universally recorded, occurring in 78.7% of cases. In contrast, only 15.8% of cases had convulsions or altered consciousness.\u003c/p\u003e \u003cp\u003eThe most common symptom combination was fever, headache, neck stiffness, and abdominal pain (2,042 cases [69.3%]). In contrast, only 315 patients (10.7%) had a combination of all five major symptoms: fever, headache, neck stiffness, abdominal pain, and convulsions. Thus, the dominant clinical syndrome was a tetrad of fever, neck stiffness, headache, and abdominal pain, while seizures or altered consciousness were less common.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency and percentage distribution of Clinical Symptoms among Cerebrospinal meningitis cases, Yobe State, 2024\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptom(s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage of Total Cases\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeadache\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeck stiffness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbdominal pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConvulsions or altered consciousness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever\u0026thinsp;+\u0026thinsp;Headache\u0026thinsp;+\u0026thinsp;Neck stiffness\u0026thinsp;+\u0026thinsp;Abdominal pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever\u0026thinsp;+\u0026thinsp;Headache\u0026thinsp;+\u0026thinsp;Neck stiffness\u0026thinsp;+\u0026thinsp;Abdominal pain\u0026thinsp;+\u0026thinsp;Convulsions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLaboratory confirmation of the etiologic agent was obtained in 423 (14.3%) of cases via cerebrospinal fluid (CSF); as is the case in low-resource settings during large outbreaks because of logistics and human resource constraints. Figure\u0026nbsp;4 shows that the majority (93.8%) of all confirmed positive cases were due to \u003cem\u003eNeisseria meningitidis\u003c/em\u003e serogroup C (NmC) infections, corroborating the outbreak strain, while Haemophilus influenzae and Streptococcus Pneumoniae accounted for 4.9% and 0.9%, respectively.\u003c/p\u003e \u003cp\u003eFigure 4 about here\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 4: Laboratory Test Results Among Cerebrospinal Meningitis Cases, Yobe State, 2024\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAmong the confirmed positive cases, Neisseria meningitidis serogroup C (NmC) was the predominant pathogen, accounting for 93.8% of positives and representing just over half of all test results (52.7%). In contrast, \u003cem\u003eHaemophilus influenzae\u003c/em\u003e and \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e were detected in 4.9% and 0.9% of positive cases, corresponding to only 2.6% and 0.5% of all tested cases, respectively.\u003c/p\u003e \u003cp\u003eAmong the confirmed cases, 98.8% presented with fever, and a majority had headaches, while only 7% experienced convulsions. The most common symptom combination was fever, headache and abdominal pain (24.4%), while the least common was headache with neck stiffness alone. A comparison of clinically suspected vs. laboratory-confirmed cases yielded a Cohen\u0026rsquo;s kappa coefficient of +\u0026thinsp;0.423, indicating moderate agreement and supporting the validity of the clinical case definition used during the outbreak. Despite limited confirmation rate, the clinical characteristics of lab-confirmed cases closely matched the overall population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eVaccination Campaign Coverage, Uptake and Effect on Outbreak Trend\u003c/h2\u003e \u003cp\u003eThe reactive ring vaccination commenced in late March 2024 in the most affected LGAs- Potiskum, Nangere, and Fika, targeting individuals aged 1\u0026ndash;30 years, who constituted the majority of reported cases. The campaign reached a substantial proportion of the target population, though coverage varied across LGAs.\u003c/p\u003e \u003cp\u003eA total of 600,825 doses of the newly introduced pentavalent meningococcal conjugate vaccine (Men5CV) were supplied for the reactive campaign conducted across three local government areas (LGAs) in Yobe State. Of these, 585,035 doses were deployed to the LGAs and 579,004 doses were administered, resulting in an overall deployment, utilization rate(of deployed doses) and vaccine wastage rate of 97.37%, 98.97% and 1.03% respectively. Based on administrative data, Fika LGA recorded 184,679 doses administered against a target population of 177,995 (103.8%). Potiskum LGA recorded 309,897 doses administered against a target population of 689,718 (44.9% coverage), while Nangere LGA recorded 84,428 doses administered out of a target of 186,563 (45.3% coverage) (Fig.\u0026nbsp;5A).\u003c/p\u003e \u003cp\u003eFigure 5 about here\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 5: Distribution of meningococcal vaccination(Men5CV) coverage among suspected cases by LGA, Yobe State, 2024\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe bar charts illustrate the distribution and timing of the reactive meningococcal vaccination campaign in Yobe State. Panel A shows that Potiskum received the highest number of doses and vaccinated individuals, followed by Fika and Nangere. Panel B demonstrates that the mass vaccination campaign was implemented in late March, coinciding with the peak of reported cases. A notable and sustained decline in case numbers followed the rollout, suggesting a potential impact of the campaign in curbing further transmission.\u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;5B, the temporal trends show that the vaccination rollout coincided with a decline in reported cases, suggesting possible early impact of the intervention. The incidence of meningitis declined sharply following the vaccination campaign. In April 2024 - the first full month after Men5C rollout - case count dropped to 755, (a 34.9% reduction from the March). The decline continued to 283 cases in May and 41 in June. By June, new infections represented only 3.5% of the March peak. Reported deaths also declined in parallel: from 34 in March to 18 in April, with no deaths in June. No resurgence of cases was observed following the intervention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAdverse Events Following Immunization (AEFI)\u003c/h2\u003e \u003cp\u003eAdverse events following immunization (AEFI) were monitored throughout the vaccination campaign. Of the 585,035 Men5C vaccine doses administered, 223 AEFI incidents were reported, representing an overall incidence rate of 0.04%. All reported AEFIs were mild and self-limiting. The most commonly reported symptoms were injection site pain or swelling (n\u0026thinsp;=\u0026thinsp;80; 0.014%), headache (n\u0026thinsp;=\u0026thinsp;60; 0.010%), low-grade fever (n\u0026thinsp;=\u0026thinsp;50; 0.009%), and itching or rash (n\u0026thinsp;=\u0026thinsp;20; 0.003%). No serious adverse events, such as anaphylaxis, seizures, or deaths were reported or attributed to the vaccine. Of the 223 AEFIs, 175 (78.5%) had complete documentation through the line listing system and were included in further analysis.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the distribution of these 175 AEFIs by age group, sex, local government area (LGA), and location type. The majority of cases occurred in children aged 1\u0026ndash;4 years (n\u0026thinsp;=\u0026thinsp;52; 29.7%) and 5\u0026ndash;9 years (n\u0026thinsp;=\u0026thinsp;50; 28.6%), followed by those aged 10\u0026ndash;14 years (n\u0026thinsp;=\u0026thinsp;40; 22.9%). Fewer cases were observed in the 15\u0026ndash;19 (n\u0026thinsp;=\u0026thinsp;18; 10.3%), 20\u0026ndash;24 (n\u0026thinsp;=\u0026thinsp;9; 5.1%), and 25\u0026ndash;29 (n\u0026thinsp;=\u0026thinsp;6; 3.4%) age groups, with no cases recorded among individuals aged 30 years and above. Males accounted for a slightly higher number of AEFI reports (n\u0026thinsp;=\u0026thinsp;97; 55.4%) compared to females (n\u0026thinsp;=\u0026thinsp;78; 44.6%). Geographically, the highest number of cases was reported in Fika LGA (n\u0026thinsp;=\u0026thinsp;79; 45.1%), followed by Nangere (n\u0026thinsp;=\u0026thinsp;71; 40.6%) and Potiskum (n\u0026thinsp;=\u0026thinsp;25; 14.3%). When disaggregated by location type, the majority of AEFIs occurred in rural areas (n\u0026thinsp;=\u0026thinsp;150; 85.7%), with urban locations accounting for the remaining 14.3% (n\u0026thinsp;=\u0026thinsp;25).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Adverse Events Following Immunization (AEFI) by Age, Sex, LGA and Location, Yobe State, 2024 (n\u0026thinsp;=\u0026thinsp;175)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAEFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNangere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFika\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotiskum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe 2024 meningococcal meningitis outbreak in Yobe State confirms a notable epidemiological shift in the circulating \u003cem\u003eNeisseria meningitidis\u003c/em\u003e serogroups. Historically, serogroup A dominated large-scale epidemics across the African meningitis belt, including Nigeria.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e However, current data indicate a transition towards serogroup C as the dominant strain, aligning with recent trends in northern Nigeria and West Africa following the widespread MenAfriVac deployment against serogroup A.\u003csup\u003e17,33\u003c/sup\u003e The emergence of serogroup C reinforces the need for broader multivalent vaccination strategies, such as Men5CV.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAs in previous outbreaks, males were disproportionately affected.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e This may reflect greater male exposure to risk factors, such as crowded markets, religious events, communal living, and inhalation exposures (e.g smoking, wood fire smoke exposure), which facilitate nasopharyngeal carriage and transmission\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e Higher male case-fatality may also stem from gender-related health-seeking differences, with evidence suggesting women seek care earlier.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe outbreak\u0026rsquo;s timing aligns with the typical late dry seasonal pattern observed across the region. \u003csup\u003e38,39\u003c/sup\u003e Hot, dry, and dusty conditions compromise nasopharyngeal mucosal immunity and facilitate transmission, whereas, rising humidity and rainfall reduce aerosolized dust and close contact spread, contributing to epidemic cessation.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e In this outbreak, however, a sharp decline in cases began before the the rains, coinciding with the Men5CV vaccination campaign. While meningitis epidemics in the Sahel usually wane with the rains (May-June in Yobe),\u003csup\u003e36,40,41\u003c/sup\u003e the abrupt decline shortly after vaccine deployment suggests a likely intervention-driven effect. This is consistent with studies showing rapid declines in meningitis incidence and carriage following conjugate vaccination,\u003csup\u003e8,10\u003c/sup\u003e in contrast to the slower seasonal declines without vaccination.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Although causality cannot be proven, the strong temporal association supports the role of Men5CV in halting transmission.\u003c/p\u003e \u003cp\u003eThe age distribution showed expected susceptibility among children and young adults, corroborating findings from other meningococcal epidemics.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e This may relate to higher contact rates and limited prior immunity. Older adults bore a lower disease burden but higher case fatality possibly due to immune senescence, comorbidities and delayed presentations.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e Their exclusion from previous vaccination campaigns may also contribute.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e These patterns highlight the need for age-tailored clinical vigilance and possible extension of vaccine coverage to at-risk older populations\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAs elsewhere in the meningitis belt\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e rural communities bore heavier burden, likely due to delayed outbreak detection, low vaccination coverage and environmental exposures. Contributing factors include overcrowding, poor nutrition, and wood smoke/dust exposures.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e Yet urban centers like Potiskum were also affected, showing how population density and mobility sustain transmission.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Immunity gaps may persist in urban cohorts not reached by prior MenAfriVac campaigns or those aged out of routine programs.\u003c/p\u003e\u003cp\u003eConflict-related displacement likely exacerbated these vulnerabilities. The Boko Haram insurgency has displaced thousands into urban and peri-urban areas,\u003csup\u003e50,51\u003c/sup\u003e straining infrastructure, and facilitating disease spread. Seasonal nomadic migration may have also contributed to the spread. These rural-urban dynamics illustrate that meningitis outbreaks are not limited to remote settings but can thrive where socio-demographic risks converge.\u003c/p\u003e\n\u003cp\u003eVariations in LGA case-fatality rate, including high mortality in low incidence areas, points to gaps in early detection and access to care. This underscores the need for surveillance strategies that prioritize not only high-incidence LGAs but also those with low case counts but high mortality.\u003c/p\u003e\n\u003cp\u003eNomadic populations were particularly vulnerable. Similar outbreaks in Nigeria have implicated nomadic movements and trade routes in meningitis spread. \u003csup\u003e41,48,52\u0026nbsp;\u003c/sup\u003eTargeted approaches such as mobile vaccination teams and outreach in nomadic settlements are therefore essential. In this outbreak, the state Ministry of Health, with partner support, implemented a “ring vaccination” strategy using Men5CV, efficiently deploying limited vaccine resources to contain the epidemic.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVaccination coverage in Fika LGA exceeded 100%. This reflects limitations in population census-based projections and contextual factors. Fika experiences seasonal nomadic influx during the dry season because of its greener pastures compared to other parts of the state affected by Sahelian drought and desertification linked to climate change. WHO reports confirm seasonal normadic migration in northern Nigeria, with \u0026nbsp;health services use along transit routes.\u003csup\u003e53\u003c/sup\u003e Fika also borders states concurrently affected by meningitis; cross-border vaccination of mobile groups has been well-documented in northern Nigeria, particularly when vaccine availability differs between adjoining states.\u003csup\u003e54\u003c/sup\u003e Finally, Fika was perceived as relatively safer than adjoining LGAs attracting people from less secure areas for vaccination.\u003csup\u003e55,56\u003c/sup\u003e\u0026nbsp; Together, these factors explain why administered doses exceeded the estimated target population. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother key finding was the lack of documented MenAfriVac among most cases. While this may partly reflect poor record-keeping and recall bias, it highlights weaknesses in immunization systems, especially in conflict-affected areas and underscores the importance of strong routine immunization systems and accurate documentation, probably through digitization of the system.\u003c/p\u003e\n\u003cp\u003eThe use of a clinical case definition was both necessary and effective. Strong concordance with laboratory-confirmed cases suggests high sensitivity of syndromic diagnosis.\u003csup\u003e57–59\u003c/sup\u003e This highlights the importance of training frontline health workers to recognize meningitis symptoms and initiate prompt treatment, even while diagnostic capacity expands.\u003c/p\u003e\n\u003cp\u003eA turning point in this outbreak was the deployment of the Men5CV, the first use of this vaccine in Nigeria and globally for outbreak control. The steep case decline following vaccination suggest effectiveness,\u003csup\u003e25,60\u003c/sup\u003e though causality cannot be established. This supports reactive vaccination as a critical tool to alter epidemic trajectories, even mid-outbreak.\u003c/p\u003e\n\u003cp\u003eMen5CV broad serogroups coverage and favourable safety profile are promising, with most adverse effects\u0026nbsp;minimal and self-limiting. Of 223 AEFI cases, only 175 had complete documentation, potentially under-representing some event types. Strengthening AEFI reporting is needed to improve safety monitoring during. Demographic differences in reporting likely reflect disparities in healthcare access and surveillance rather than safety concerns. Ongoing community engagement and transparent communication will be vital to sustain public trust.\u003c/p\u003e\n\u003cp\u003eYobe State’s experience provides early real-world evidence that Men5CV is both effective and safe for outbreak control. It supports recommendations for broader use across the meningitis belt, both reactively and via routine immunization. With strong surveillance and rapid response, the goal of eliminating epidemic meningitis by 2030 becomes more achievable. Continuous post-introduction monitoring will be essential to ensure sustained impact and public confidence.\u003c/p\u003e\n\u003cp\u003eIn summary, the Yobe outbreak underscores the emergence of serogroup C and demonstrates the potential of Men5CV to rapidly curb transmission, with a favorable safety profile. Strengthening surveillance, AEFI reporting, and targeted vaccination of high-risk groups will be critical for sustaining impact\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe 2024 serogroup C meningococcal meningitis outbreak in Yobe State, Nigeria, followed patterns typical of epidemics in the African meningitis belt with the highest burden among children, young people, males and rural communities. The seasonal peak in the late dry season was consistent with regional trends, and strong concordance between clinical and laboratory diagnosis \u0026nbsp; confirmed the appropriateness of case definition for rapid response. The reactive ring vaccination campaign with the novel Men5CV coincided with a marked decline in cases and deaths, demonstrating the potential of timely, targeted vaccination even amid an ongoing epidemic. These findings highlight the importance of vigilant surveillance, early diagnosis, and swift deployment of effective vaccines. The Yobe experience illustrates how new tools like Men5CV, integrated with established public health strategies, can advance the goal of eliminating meningitis epidemics in Africa.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePublic Health and Policy Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eIntegrate Men5C into routine and seasonal vaccination strategies:\u003c/strong\u003e Routine use of multivalent meningococcal conjugate vaccines, along with pre-dry-season mass vaccination campaigns, should be adopted to prevent outbreaks by reducing meningococcal carriage and building herd immunity.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePrioritise targeted reactive vaccination during outbreaks:\u003c/strong\u003e Rapid deployment of focused campaigns like ring vaccination should be used during outbreaks to optimise vaccine use and limit disease spread, especially in high-risk or hard-to-reach populations.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eStrengthen meningitis surveillance systems:\u003c/strong\u003e Investments are needed to improve real-time case reporting, laboratory confirmation, and predictive tools such as climate data integration for early outbreak detection and tailored responses.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eBuild capacity of the healthcare workforce:\u003c/strong\u003e Continuous training in meningitis recognition, case management, and outbreak response will improve clinical outcomes and readiness for future epidemics.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eEngage communities and address misinformation:\u003c/strong\u003e Culturally sensitive risk communication and community mobilisation can improve vaccine uptake, early treatment-seeking, and trust in public health interventions.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eEnhance preparedness and regional collaboration:\u003c/strong\u003e Governments should invest in local vaccine production, diagnostics, and cross-border coordination to enable a faster, more cohesive regional response in line with the WHO’s Defeating Meningitis by 2030 strategy.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several important limitations. First, it was based on surveillance and line-list data collected during an emergency response, which may be subject to underreporting and missing information. Not all suspected meningitis cases could be laboratory confirmation due to overwhelming nature of the outbreak in a low-resource setting coupled with limited diagnostic capacity. Second, data on prior vaccination (especially receipt of the MenAfriVac serogroup A vaccine) were often incomplete or unreliable. Many patients did not know their vaccination status or lacked documentation. This made it difficult to accurately assess the role of pre-existing immunity, and it introduces potential misclassification and information bias in our analysis of risk factors. Third, as an observational outbreak report, our study can only infer associations rather than prove causation. For example, the decline in cases following the Men5C vaccination campaign is strongly suggestive of impact but could also be influenced by other coincident factors (such as the seasonal weather change). We did not have a comparison group or the ability to conduct analytical studies (e.g. vaccine effectiveness calculations) in the midst of the emergency. Despite these limitations, the study provides valuable insights into the epidemiology of a serogroup C meningococcal outbreak in a region that had not seen an epidemic in over a decade, and it offers practical lessons for improving outbreak response and prevention in similar environments.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAEFI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdverse Events Following Immunization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCFR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCase Fatality Rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCerebrospinal Fluid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDSNO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDisease Surveillance and Notification Officer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEOC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEmergency Operations Center\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVPD\u0026ndash;Invasive Bacteria\u0026ndash;Vaccine Preventable Diseases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLocal Government Area\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMen5CV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMeningococcal Serogroup A, C, W, Y, and X Conjugate Vaccine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCDC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNigeria Centre for Disease Control\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNmA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeisseria meningitidis serogroup A\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNmC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeisseria meningitidis serogroup C\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNRL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Reference Laboratory\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNTC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNo Template Control\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePolymerase Chain Reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eqPCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQuantitative Polymerase Chain Reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical approval and consent to participate:\u003c/p\u003e\n\u003cp\u003eEthical clearance for the secondary use of outbreak response data was granted by the Yobe State Ministry of Health Ethical Review Committee. Only anonymised surveillance and vaccination records were used, and no identifiable personal information was accessed. As the data were obtained during routine public health response activities, the requirement for individual informed consent was waived in accordance with national guidelines.\u003c/p\u003e\n\u003cp\u003eConsent for publication:\u003c/p\u003e\n\u003cp\u003eNo individual person\u0026rsquo;s data, images, or identifying information are included in this manuscript. Therefore, consent for publication was not applicable.\u003c/p\u003e\n\u003cp\u003eData Availability:\u003c/p\u003e\n\u003cp\u003eThe raw datasets generated and analysed during the current study are publicly available in Zenodo (DOI: 10.5281/zenodo.15720689).\u003c/p\u003e\n\u003cp\u003eConflict of Interest:\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no conflict of interest\u003c/p\u003e\n\u003cp\u003eSource of Funding:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study did not recive any specific grant from funding agenies in the public, commercial or not for profic sectors. The analysis was conducted as part of the routine public health responsibilities of the Yobe state Ministry of Health and collaborating partners\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions:\u003c/p\u003e\n\u003cp\u003eBWG and OO conceptualized the study and contributed to drafting and critical revisions. HSK performed data analysis and assisted in drafting and revising. MI coordinated data collection and field supervision. AB supported data collection and supervision. MBK contributed to data analysis and review. AA handled sample collection, laboratory analysis, and supervision; MOP assisted with sample analysis. MMB, HA, MLG, IMK, BB, HY, MBM, and IM reviewed the manuscript and provided critical input, with IM offering scientific mentorship. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe would like to extend our special thanks and appreciation to the Yobe State Ministry of Health, the Department of Public Health, the Epidemiology Unit Yobe State Primary Health Care Board and the Africa Field Epidemiology Network (AFENET) Yobe State Field Office Damaturu, for the approval to use Cerebrospinal meningitis data for this study. We are also grateful to Dr \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Umar Ahmad, Senior Technical Consultant for Pathogen Genomics, Africa CDC, for his valuable review of the draft manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCollaborators GBD. 2019 M. Global, regional, and national burden of meningitis, 1990\u0026ndash;2016. Lancet Neurology. 2018;17(12):1061\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchiess N, Groce NE, Dua T. The impact and burden of neurological sequelae following bacterial meningitis: a narrative review. Microorganisms [Internet]. 2021;9(5):900. 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Arq Neuropsiquiatr. 2016;74(11):875\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNissa S, Iftiyastuti B, Rizkita LD, Ihsana N, Selohandono A. The Relationship between the Classic Triad of Meningitis and Types of Meningitis. J La Medihealtico. 2024;5(4):848\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkaishi T, Kobayashi J, Abe M, Ishizawa K, Nakashima I, Aoki M, et al. Sensitivity and specificity of meningeal signs in patients with meningitis. J Gen Fam Med. 2019;20(5):193\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (WHO). WHO combats cerebrospinal meningitis outbreak in Yobe State, Nigeria. 2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Meningococcal Meningitis, Neisseria meningitidis Serogroup C, Men5CV, Yobe State, Northeast Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-8262447/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8262447/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eIn early 2024, an outbreak of meningococcal meningitis occurred in Yobe State, northeastern Nigeria, prompting an urgent public health response. This study analyzes the epidemiologic, clinical, and laboratory characteristics of the outbreak and evaluates the effect of the reactive Men5C vaccination campaign.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eA retrospective review of 2,948 suspected meningitis cases was conducted using line-listed surveillance data for the year 2024. Data included demographic variables, clinical presentation, laboratory results, and vaccination history. Descriptive statistics, bivariate analysis, and multivariable logistic regression were used to identify predictors of mortality.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eChildren and adolescents aged 1\u0026ndash;19 years accounted for 84.8% of all cases. The overall case fatality ratio (CFR) was 3.6%, with the highest CFR observed among adults aged\u0026thinsp;\u0026ge;\u0026thinsp;40 years \u003cb\u003e(\u003c/b\u003e5.6%\u003cb\u003e).\u003c/b\u003e Males had a significantly higher CFR than females \u003cb\u003e(\u003c/b\u003e4.4% vs. 2.5%, p\u0026thinsp;=\u0026thinsp;0.009\u003cb\u003e)\u003c/b\u003e. Most deaths occurred among individuals who had no record for vaccination against \u003cem\u003eNeisseria meningitidis\u003c/em\u003e serogroup A (59.0%). Logistic regression showed that male sex \u003cb\u003e(\u003c/b\u003eaOR\u0026thinsp;=\u0026thinsp;1.74; 95% CI: 1.14\u0026ndash;2.66; p\u0026thinsp;=\u0026thinsp;0.011\u003cb\u003e)\u003c/b\u003e and outpatient admission status \u003cb\u003e(\u003c/b\u003eaOR\u0026thinsp;=\u0026thinsp;0.07; 95% CI: 0.01\u0026ndash;0.54; p\u0026thinsp;=\u0026thinsp;0.010\u003cb\u003e)\u003c/b\u003e were significant predictors of mortality. Laboratory confirmation identified \u003cem\u003eNeisseria meningitidis\u003c/em\u003e serogroup C in 93.8% of all positive cases. A reactive ring vaccination campaign using Men5CV deployed 585,035 doses and administered 579,004 cases across the three most affected local government areas, with vaccination coverage ranging from 45% to 104%.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eThis outbreak was driven primarily by \u003cem\u003eNeisseria meningitidis\u003c/em\u003e serogroup C, with adolescents and unvaccinated individuals disproportionately affected. The successful deployment of Men5CV demonstrates its feasibility in emergency settings and highlights the urgent need for preventive routine vaccination in Nigeria\u0026rsquo;s meningitis belt.\u003c/p\u003e","manuscriptTitle":"First Field Use of the Pentavalent Meningococcal Conjugate Vaccine (Men5CV) in Response to a Serogroup C Meningitis Outbreak: Evidence from Yobe State, Northeastern Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 00:29:17","doi":"10.21203/rs.3.rs-8262447/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dede62d3-3958-42a6-bcb8-2366c3323561","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-13T07:17:38+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T07:30:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 00:29:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8262447","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8262447","identity":"rs-8262447","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}