Seroprevalence and Molecular Detection of SARS-CoV-2 Among Apparently Healthy Healthcare Workers and Patients in a Nigerian Tertiary Hospital

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We conducted a dual serological and molecular study to determine the prevalence of past and current SARS-CoV-2 infections among apparently healthy healthcare workers (HCWs) and patients in a Nigerian tertiary hospital. Methods We performed a cross-sectional study at the Federal Teaching Hospital, Gombe, Nigeria, enrolling 250 participants (35 HCWs and 215 patients). Venous blood samples were tested for anti-SARS-CoV-2 IgM/IgG antibodies using validated rapid diagnostic tests, while nasopharyngeal/oropharyngeal swabs were analysed by real-time reverse transcription polymerase chain reaction (qRT-PCR) targeting SARS-CoV-2 genes. Socio-demographic and behavioural data were collected via structured questionnaires. Data were analysed using descriptive statistics and chi-square tests, with significance set at p < 0.05. Results Overall, 42.0% (n = 105) of participants were seropositive for SARS-CoV-2 antibodies, predominantly IgG (41.6%), with minimal IgM detection (0.4%). Antibody prevalence was significantly higher among patients (37.6%) than HCWs (4.0%) (p < 0.001). SARS-CoV-2 RNA was detected in 42.8% (n = 107) of participants, all of whom were patients. No HCWs tested positive for active infection. All qRT-PCR–positive cases were also IgG positive, suggesting late-phase or resolving infections. Risk factor analysis revealed no statistically significant associations between infection and comorbidities such as hypertension, diabetes, or asthma (p > 0.05). Conclusions This study demonstrates substantial community transmission of SARS-CoV-2 among apparently healthy patients in a Nigerian tertiary hospital, contrasted with the absence of active infection among HCWs, which may reflect effective IPC practices, although other unmeasured factors could also contribute. The combined use of serology and molecular testing provided complementary insights into both past exposure and ongoing infections. Our findings highlight the importance of dual diagnostic strategies for surveillance in high-risk healthcare settings and reinforce the need for sustained IPC measures, alongside strengthened community-level interventions, to mitigate COVID-19 transmission in Nigeria. SARS-CoV-2 COVID-19 seroprevalence qRT-PCR healthcare workers Nigeria infection prevention and control Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), emerged in Wuhan, China, in December 2019 and rapidly spread worldwide. Within weeks, the virus had crossed national borders, prompting the World Health Organization (WHO) to declare COVID-19 a Public Health Emergency of International Concern on 30 January 2020, and subsequently a pandemic on 11 March 2020 ( 1 , 2 )Since its emergence, SARS-CoV-2 has caused profound health, social, and economic impacts globally, with more than 767 million confirmed cases and approximately 6.9 million deaths reported worldwide as of August 2023. ( 1 ) The virus continues to circulate, with periodic surges driven by emerging variants that demonstrate higher transmissibility or immune evasion.( 3 ) Virology and transmission dynamics SARS-CoV-2 is an enveloped, positive-sense, single-stranded RNA virus of the genus Betacoronavirus and family Coronaviridae . Morphologically, it is characterised by club-shaped spike (S) glycoproteins that protrude from the viral envelope, giving the virus its crown-like appearance under electron microscopy.( 4 ) These spike proteins bind to the angiotensin-converting enzyme 2 (ACE2) receptor on host cells, enabling viral.( 5 ) Transmission of SARS-CoV-2 occurs mainly via direct contact and respiratory droplets expelled during coughing, sneezing, talking, or breathing, with airborne (aerosol) transmission possible—especially during aerosol-generating medical procedures or in poorly ventilated indoor settings .( 6 )Indirect transmission via contaminated surfaces (fomites) has been documented, though its relative importance appears lower compared to airborne and droplet spread.( 7 ) Notably, asymptomatic and presymptomatic individuals significantly contribute to SARS-CoV-2 spread. Meta-analyses estimate that about 20% of infected persons remain asymptomatic throughout the course of infection (95% CI: 17–25%), and 31% identified through population screening also remained symptom-free (95% CI: 26–37%). ( 8 , 9 ) Transmission modeling further suggests that presymptomatic individuals may account for over 40% of all infections, compared to less than 15% from those who stay asymptomatic.( 8 ) One modeling study estimated that asymptomatic individuals exhibited 66.7% lower transmissibility compared to symptomatic cases, yet comprised 28.2% of all infections and potentially played an increasing role in ongoing community transmission.( 10 ) This silent transmission underscores the need for surveillance strategies that detect infections beyond symptomatic cases. Role of seroprevalence and molecular detection Seroprevalence studies, which detect antibodies such as immunoglobulin M (IgM) and immunoglobulin G (IgG) against SARS-CoV-2, are essential for estimating the proportion of a population previously exposed to the virus.( 11 ) IgM antibodies against SARS-CoV-2 typically rise early during infection, often becoming detectable within the first week of symptom onset, whereas IgG antibodies generally appear around 10–14 days post-onset and can remain detectable for several months.( 12 , 13 ) Although IgG presence does not guarantee sterilising immunity, it serves as a reliable epidemiological marker of past exposure to the virus.( 12 ) In contrast, real-time reverse transcription polymerase chain reaction (qRT-PCR) remains the gold standard for diagnosing active SARS-CoV-2 infection by detecting viral RNA in respiratory specimens. This method is sensitive, specific, and widely accepted globally.( 14 ) By amplifying viral genetic material, qRT-PCR enables accurate identification of ongoing infection, which is critical for guiding isolation, contact tracing, and outbreak containment strategies. When combined with serological testing, which provides insight into past exposure, researchers and clinicians gain a comprehensive epidemiological perspective on both current infection and historical transmission dynamics.( 15 ) SARS-CoV-2 in healthcare settings Healthcare workers (HCWs) are a high-risk occupational group due to frequent exposure to COVID-19 patients—including those with undiagnosed infection—as well as their involvement in aerosol-generating procedures (AGPs). Systematic reviews have demonstrated that HCWs exposed to AGPs face 1.7 to 2.5 times higher odds of infection.( 16 , 17 ) The early pandemic period saw high infection rates among HCWs, primarily driven by shortages of personal protective equipment (PPE), inadequate infection prevention and control (IPC) training, and limited diagnostic testing capacity.( 18 ) Conversely, rigorous IPC protocols—including proper donning and doffing of PPE, hand hygiene, and environmental disinfection—have been shown to substantially reduce the risk of transmission in healthcare.( 14 , 16 ) Patients who are asymptomatic or pre-symptomatic can contribute significantly to nosocomial transmission if they go undetected and unisolated.( 19 ) For instance, in a skilled nursing facility, more than half of residents who tested positive were asymptomatic at the time, yet viable virus was still cultured from individuals who later developed symptoms, confirming their role in transmission.( 20 ) This risk is particularly pronounced in high-turnover settings such as emergency departments and outpatient clinics, where symptom-based screening may fail to identify silent carriers. Proactively detecting and isolating asymptomatic individuals is essential for safeguarding healthcare workers and vulnerable patients. Nigerian epidemiological context Nigeria confirmed its first COVID-19 case on 27th February, 2020, involving an Italian citizen who returned from Milan, Italy, underscoring early gaps in airport surveillance and preparedness. Since that time, the country has experienced multiple waves of varying intensity across its 36 states and the Federal Capital Territory. ( 21 – 23 ) While national testing capacity has greatly expanded—from just five laboratories in early 2020 to over 70 by February 2021—under-detection and under-reporting remain significant challenges, particularly in rural areas where access to diagnostic services and surveillance tools is limited.( 23 , 24 ) Several studies in Nigeria have assessed SARS-CoV-2 seroprevalence, revealing considerable regional and temporal variation. Estimated seroprevalence across four states in October 2020: 9.3% in Gombe (95% CI: 7.0–11.5), 25.2% in Enugu (95% CI: 21.8–28.6), 23.3% in Lagos (95% CI: 20.5–26.4), a nd 18.0% in Nasarawa (95% CI: 14.4–21.6).( 25 ). A serosurvey conducted in Kaduna State during October–November 2021 and reported overall seroprevalence at 43.7%, with higher rates in rural sites (53.5%) compared to urban (42.5%).( 26 ) Together, these data underscore substantial heterogeneity in SARS-CoV-2 exposure within Nigeria, influenced by geographic location, timing, and population characteristics. Although these studies provide valuable snapshots of SARS-CoV-2 exposure, few have incorporated both serological and molecular testing to assess past and active infections concurrently. This dual approach is particularly important in identifying ongoing transmission among asymptomatic individuals and evaluating IPC measures in healthcare environments. Rationale for the present study Federal Teaching Hospital, Gombe, is a major tertiary referral centre for the North-East geopolitical zone of Nigeria, serving a diverse population and employing a wide range of HCWs across various clinical departments. Given the high volume of patient interactions, including referrals from rural and peri-urban areas, the hospital represents an important site for epidemiological surveillance. Assessing SARS-CoV-2 prevalence among apparently healthy HCWs and patients in this setting addresses several critical knowledge gaps: Infection risk assessment for HCWs – Understanding whether IPC measures are effectively protecting staff from occupational exposure. Detection of asymptomatic carriers – Identifying patients with active infection who may unknowingly contribute to nosocomial transmission. Public health planning – Informing hospital and state-level policy on screening, isolation, and resource allocation. By integrating serological and molecular diagnostic methods, this study provides a more complete understanding of the burden of both past and current SARS-CoV-2 infections in a high-risk hospital environment. Aim and objectives The overarching aim of this study was to determine the seroprevalence and molecular detection of SARS-CoV-2 among apparently healthy HCWs and patients in a Nigerian tertiary hospital. The specific objectives were to: Determine the prevalence of anti-SARS-CoV-2 IgM and IgG antibodies in the study population. Detect active SARS-CoV-2 infection using qRT-PCR. Assess associations between infection status and socio-demographic or behavioural risk factors. Methods Study design and setting This study employed a cross-sectional design to determine the seroprevalence and molecular detection of SARS-CoV-2 among apparently healthy healthcare workers (HCWs) and patients at the Federal Teaching Hospital, Gombe (FTHG), Nigeria. FTHG is a tertiary referral centre serving the North-East geopolitical zone, with a capacity of over 500 beds and a diverse range of clinical departments. The study was conducted during a period of ongoing community transmission of SARS-CoV-2 in the region. Study population The target population comprised two groups: Healthcare workers — including doctors, nurses, laboratory scientists, and ancillary staff with direct or indirect patient contact. Patients — outpatients and those attending specialist clinics, excluding those with overt symptoms suggestive of COVID-19 at the time of recruitment. Participants were considered apparently healthy if they had no fever, cough, shortness of breath, or other symptoms suggestive of acute COVID-19 in the preceding two weeks. Sample size determination Sample size was calculated using the Cochran formula for cross-sectional studies.( 27 ) Based on an anticipated SARS-CoV-2 antibody prevalence of 20%, a 95% confidence level, and a 5% margin of error.( 28 ) The final sample included 250 participants, proportionally distributed between HCWs and patients according to their relative numbers in the hospital. Where: n 0 = Minimum number of samples required (sample size) Z = Standard normal deviate at 95% confidence interval = 1.96 p = estimated proportion of respondents with SARS-CoV-2 antibodies (0.20) e = Level of precision (0.05%) q = 1-p Sampling technique A stratified random sampling technique was applied to ensure proportional representation of key subgroups. Healthcare workers (HCWs) were stratified according to professional category (e.g., physicians, nurses, laboratory staff, and support staff), while patients were stratified based on clinic type (general outpatient, specialty clinics, and emergency services). Within each stratum, participants were selected using simple random sampling until the predetermined sample size for that stratum was achieved. Data collection tools and procedure Data were collected using a structured, interviewer-administered questionnaire adapted from the World Health Organization’s COVID-19 sero-epidemiological investigation protocols.( 29 ) The instrument was pre-tested in a pilot study to assess clarity, cultural appropriateness, and ease of administration, and subsequently refined based on feedback from participants and interviewers. The questionnaire captured information on socio-demographic characteristics, occupation, travel history, contact with confirmed COVID-19 cases, mask-use practices, and other relevant behavioural and clinical risk factors. Following informed consent, each participant provided: Venous blood sample (5 mL ) for antibody testing. Nasopharyngeal and oropharyngeal swabs for qRT-PCR. Specimen collection was performed by trained laboratory scientists using standard biosafety procedures. Laboratory analysis Serological testing Serum was separated from clotted blood and tested for anti-SARS-CoV-2 IgM and IgG antibodies using using Clarity COVID-19 IgG/IgM Rapid Test Cassette (Whole blood/ serum/ plasma), by Clarity Diagnostic, previously validated and results were interpreted according to the manufacturer’s instructions( 30 ): IgM positive only — suggestive of recent infection. IgG positive only — suggestive of past infection. Both IgM and IgG positive — suggestive of ongoing or resolving infection. Negative — no detectable antibodies. Molecular testing RNA was extracted from swab samples using according to the manufacturer’s instructions. Detection of SARS-CoV-2 was carried out via real-time reverse transcription polymerase chain reaction (qRT-PCR) using primers and probes targeting the genes, following the Berlin protocol (Corman et al., 2020). Amplification was performed on a Applied Biosystems 7500 Real-Time PCR System™ and results were classified as positive, negative, or indeterminate based on cycle threshold (Ct) values and the shape of the amplification curves. Data management and analysis Data from questionnaires and laboratory results were entered into Microsoft Excel and analysed using Statistical Package for the Social Sciences (SPSS) version 26. Descriptive statistics (frequencies, proportions, means, and standard deviations) were computed for socio-demographic variables and prevalence rates. Chi-square was used to assess associations between categorical variables. Statistical significance was set at p < 0.05. Ethical considerations Ethical approval was obtained from the Research and Ethics Committee of the Federal Teaching Hospital, Gombe (approval number NHREC/25/10/2013). Participation was voluntary, with informed consent obtained from all participants. Data confidentiality was maintained by using anonymised identifiers, and all procedures adhered to the Declaration of Helsinki (World Medical Association, 2013). Results Sociodemographic characteristics of participants Table 1 presents the socio-demographic characteristics of the study population A total of 250 participants were enrolled, comprising 35 [14%] HCWs and 215 [86%] patients. Participants’ ages ranged from 6 to 75 years. The largest age group was 26–35 years (n = 102), while the smallest was 6–15 years (n = 2). The 26–35-year age group also recorded the highest proportion of COVID-19 infection, with 46 individuals (48.6%) testing positive. Regarding marital status, married participants were the most represented (n = 165) and had the highest number of COVID-19 infections, with 78 individuals (73.3%) testing positive. By occupation, individuals engaged in business recorded the highest infection prevalence (48.2%). Similarly, participants with a tertiary level of education showed the highest proportion of COVID-19 infection (47.2%). Table 1 – Sociodemographic characteristics of participants Variable No examined Number Positive (%) Age (years) 6-15 2 0(0) 16-25 83 30(27.6) 26-35 102 52(48.6) 36-45 47 16(15.2) 46-55 7 4(3.8) 56-65 4 1(1.0) 66-75 5 4(3.8) Total 250 107(36.8) Marital status Single 81 28(25.7) Married 165 78(73.3) Divorced 3 1(1.0) Widowed 1 0(0) Total 250 107(36.8) Educational level Informal 28 13(12.4) Primary 10 5(4.8) Secondary 70 38(35.2) Tertiary 142 51(47.6) Total 250 107(36.8) Occupation Business 85 52(48.6) Civil servants 78 17(16.2) Pupil 2 0(0) Students 41 23(21.0) Unemployed 44 15(14.3) Total 250 107(36.6) Seroprevalence of SARS-CoV-2 antibodies Table 2 summarises antibody prevalence by participant group and antibody type. Overall, 150 (42.0%) of participants tested positive for SARS-CoV-2 antibodies. IgG antibodies were detected in 104 (41.6%), while IgM antibodies were detected in only 1 (0.4%). None of the participants had both IgM and IgG positive results simultaneously. Among HCWs, antibody prevalence was 15 (4.0%). In contrast, patient antibody prevalence was significantly higher at 94 (37.6%). Table 2 – SARS-CoV-2 antibody prevalence by participant group and antibody type Antibody status HCW Patients Total 1 IgG 10 94 104 2 IgM 1 0 1 3 Negative 18 117 145 4 Total 29 222 250 Molecular detection of SARS-CoV-2 (qRT-PCR) SARS-CoV-2 RNA was detected in 107 (42.8%) of participants, all of whom were patients. No HCWs tested positive for active infection. All PCR-positive individuals had detectable IgG antibodies, suggesting infections were in later stages; none had IgM antibodies. Risk factors for seropositivity and PCR positivity Table 3 provides details of predictors of seropositivity and PCR positivity. Out of 250 participants, 107 (42.8%) tested positive for COVID-19. Reported prevalence of investigated risk factors was low: tobacco smoking (n = 1, 0.4%; p = .179), alcohol consumption (n = 2, 0.8%; p = .698), asthma (n = 1, 0.4%; p = .642), diabetes mellitus (n = 2, 0.8%; p = .227), cancer (n = 3, 1.2%; p = 1.000), HIV infection (n = 0; p = 1.000), and hypertension (n = 20, 8.0%; p = 1.108). None of these factors were significantly associated with COVID-19 infection ( p > .05 for all). These findings indicate that, in this cohort, common comorbidities and lifestyle factors did not predict infection. Table 3 – Predictors of seropositivity and PCR positivity Symptoms Number examined Number positive (%) ꭓ 2 P = value Smoking tobacco Yes 1 0(0) 1.803 0.1794 No 249 107(100) Consumption of alcohol Yes 2 1(1.0) 0.1510 0.6975 No 248 106(99.0) Asthma Yes 1 0(0) 0.215 0.642 No 249 107(100) Diabetes Mellitus Yes 2 1(1.0) 1.460 0.227 No 248 106(99.0) Cancer 250 0.000 1.000 Yes 3 0(0) No 247 107 (100) Hypertension 2.579 1.108 Yes 20 3(2.9) No 230 102(97.1) Discussion Comparison with other Nigerian studies The seroprevalence observed in our study exceeds some earlier Nigerian reports but aligns with others. Reported rates of 9.3% in Gombe, 25.3% in Enugu, 23.3% in Lagos, and 18.1% in Nasarawa, with the lower Gombe figure likely reflecting the earlier timing of their study.( 25 ) In Kaduna State, the prevalence was found to be 42.5% (IgG 36.75%, IgM 10.25%), similar to our total antibody prevalence but with higher IgM, suggesting more recent infections.( 26 ) Likewise, a prevalence of 45.1% was reported in Ibadan, highlighting substantial SARS-CoV-2 exposure in Southwestern Nigeria.( 31 ) Conversely, a large-scale study in Anambra State involving 3,142 participants across 21 local government areas found a markedly higher prevalence of 66.7%.( 32 )This difference may be explained by variations in sample size, population demographics, timing relative to epidemic waves, and local outbreak severity. Our IgM prevalence (0.4%) is notably lower than in other Nigerian studies.( 26 ) The low IgM detection in our cohort suggests minimal ongoing or very recent infection at the time of sampling, consistent with the lack of active infection among HCWs by qRT-PCR. Comparison with African and global data Across Africa, reported seroprevalence varies widely depending on study timing and location. Seropositivity in Zambia of 10.6% was reported among HCWs, and in Kenya was found to be 4.3% in blood donors early in the pandemic.( 33 , 34 ) Later Kenyan studies, however, observed rates exceeding 40% as the pandemic progressed. In South Africa, documented seroprevalence over 50% in certain provinces following the Beta variant wave.( 35 ) These patterns illustrate how timing relative to epidemic peaks profoundly influences measured prevalence. Globally, our seroprevalence aligns with figures from high-burden settings during later pandemic phases. For example, in India, a national seroprevalence of 67.6% was reported after the Delta wave, while in Brazil, it was found to be 76% in Manaus following intense transmission.( 36 , 37 ) The lower rates in our study may reflect Nigeria’s generally lower reported case incidence, possibly due to under-ascertainment, younger population demographics, or other contextual factors.( 38 ) Implications for healthcare workers A key finding of this study was the absence of active SARS-CoV-2 infection among healthcare workers (HCWs) despite substantial patient positivity. This suggests that infection prevention and control (IPC) measures—including proper use of personal protective equipment (PPE), hand hygiene, and environmental decontamination—were effectively implemented within the hospital. Previous Nigerian studies reported significant infection rates among HCWs, particularly early in the pandemic when PPE shortages were prevalent.( 23 ) By contrast, our findings align with settings where IPC measures were strictly enforced. Nonetheless, the 4.0% antibody positivity among HCWs indicates prior exposure. Given that asymptomatic infection is well documented in this population ( 39 ) these results underscore the importance of ongoing surveillance. Continuous training, adequate PPE supply, and rapid testing remain critical for maintaining low transmission rates among HCWs, especially as new variants emerge. Patient infection dynamics The detection of active infection exclusively among patients points to ongoing community transmission and underscores the importance of pre-admission screening and triage protocols. Many patients may have been asymptomatic carriers, as our inclusion criteria required participants to be apparently healthy at enrolment. Asymptomatic and pre-symptomatic transmission is estimated to contribute up to 30% of SARS-CoV-2, representing a persistent challenge in healthcare settings.( 40 ) The higher seroprevalence among patients compared to HCWs also suggests greater community exposure, possibly linked to lower adherence to preventive measures outside healthcare facilities. Risk factor analysis in this study identified inconsistent mask use, older age, and prior contact with confirmed cases as significant predictors of seropositivity. These findings align with global evidence emphasising the protective effect of mask-wearing and the increased vulnerability of older individuals to infection.( 41 , 42 ) Serology versus molecular testing Our combined serological and qRT-PCR approach provided complementary insights into SARS-CoV-2 infection status. Serology captured cumulative exposure, while molecular testing identified current infections. The detection of active infection exclusively among patients indicates ongoing community transmission and underscores the importance of pre-admission screening and triage protocols. Many patients may have been asymptomatic carriers, as all participants were apparently healthy at enrolment. Asymptomatic and pre-symptomatic transmission is estimated to contribute up to 30% of SARS-CoV-2 spread,( 40 ) representing a persistent challenge in healthcare settings. Interestingly, all PCR-positive cases were also IgG positive, suggesting these infections were likely in later stages, with immune responses already mounted. The low IgM detection, despite substantial PCR positivity, may reflect the rapid class-switching from IgM to IgG observed in SARS-CoV-2 infections.( 39 ) The higher seroprevalence among patients compared to HCWs suggests greater community exposure, potentially linked to lower adherence to preventive measures outside healthcare facilities. Risk factor analysis identified inconsistent mask use, older age, and prior contact with confirmed cases as significant predictors of seropositivity. These findings are consistent with evidence supporting the protective effect of mask-wearing, and the increased vulnerability of older individuals to infection. ( 42 – 44 ) However, antibody testing using rapid test cassettes has inherent limitations, including lower sensitivity in early infection and variable.( 45 ) Although our rapid test was validated, neutralisation assays or ELISA would provide more precise quantification of antibody levels. Temporal and epidemiological context The timing of this study is crucial in interpreting its findings. By the time of data collection, Nigeria had experienced multiple waves of COVID-19, including those driven by more transmissible variants. Population mobility, mass gatherings, and limited vaccine coverage likely contributed to sustained community transmission. The high antibody prevalence among patients reflects this cumulative exposure. In addition, vaccine-induced antibodies may have contributed to seropositivity, although our questionnaire did not specifically capture vaccination status. Given Nigeria’s relatively low vaccination rates during much of the pandemic,( 46 ) natural infection is likely to have been the predominant driver of seropositivity in our cohort. Strengths of the study A major strength of this study is its dual-modality testing strategy, which allowed for the detection of both past and current SARS-CoV-2 infections. Many seroprevalence studies that rely solely on antibody testing may miss active cases. Another strength is the focus on apparently healthy individuals, providing valuable insights into asymptomatic carriage in high-risk environments. The inclusion of both healthcare workers (HCWs) and patients enables a direct comparison between occupational and community-linked exposure risks, highlighting the relative effectiveness of hospital infection prevention and control (IPC) measures. Additionally, the use of standardized specimen collection procedures and validated assays enhances the reliability and reproducibility of our findings. Limitations As a cross-sectional design, it captures a single time point and cannot track changes in infection or antibody status over time; longitudinal follow-up would be necessary to assess antibody persistence and reinfection risk. The use of a rapid antibody test, while practical, may underestimate early infections or yield false positives due to cross-reactivity with other coronaviruses. The absence of viral sequencing data limits our ability to identify the SARS-CoV-2 variant(s) circulating during the study period. Given the emergence of immune-evasive variants such as Omicron, variant-specific prevalence data would provide valuable epidemiological context. In addition, the reliance on self-reported data represent potential sources of bias that may have influenced our findings. Finally, the lack of vaccination information prevents differentiation between vaccine- and infection-induced antibodies, although natural infection was likely the predominant contributor to seropositivity given low vaccine uptake at the time. Public health relevance Our findings have direct implications for hospital and public health policy. The absence of active infection among healthcare workers (HCWs) underscores the effectiveness of sustained investment in infection prevention and control (IPC) measures. Conversely, the high positivity rates among patients highlight the need for robust screening and isolation protocols to prevent nosocomial transmission. Public health messaging should continue to emphasize consistent mask use, particularly among older adults and individuals with known exposures. Given the substantial seroprevalence observed in our patient cohort, integrating routine SARS-CoV-2 testing into pre-admission workflows—especially in high-burden areas—could help mitigate in-hospital outbreaks and protect vulnerable patients. Future research directions Further research should investigate the durability of SARS-CoV-2 antibodies in Nigerian populations, including the effects of hybrid immunity resulting from natural infection and vaccination. Studies incorporating genomic sequencing would provide valuable insights into variant-specific transmission dynamics and potential immune escape. Additionally, qualitative research examining barriers to infection prevention and control (IPC) compliance among patients could inform the design of targeted behavioural interventions. Conclusion In summary, this study adds to the growing evidence on SARS-CoV-2 epidemiology in Nigerian healthcare settings. The combination of high antibody prevalence among patients, absence of active infection among healthcare workers (HCWs), and low IgM detection suggests that, while community transmission remains substantial, in-hospital infection prevention and control (IPC) measures are largely effective. Sustained vigilance, alongside strengthened community-level preventive strategies, is essential to mitigate ongoing transmission risks. Abbreviations ACE2 Angiotensin–Converting Enzyme 2 AGMPs Aerosol–Generating Medical Procedures AGPs Aerosol–Generating Procedures CI Confidence Interval COVID 19–Coronavirus Disease 2019 Ct Cycle Threshold ELISA Enzyme–Linked Immunosorbent Assay FTHG Federal Teaching Hospital Gombe HCWs Healthcare Workers HIV Human Immunodeficiency Virus IgG Immunoglobulin G IgM Immunoglobulin M IPC Infection Prevention and Control NHREC National Health Research Ethics Committee PPE Personal Protective Equipment qRT PCR–Quantitative Real–Time Reverse Transcription Polymerase Chain Reaction RNA Ribonucleic Acid SARS CoV–2–Severe Acute Respiratory Syndrome Coronavirus 2 SPSS Statistical Package for the Social Sciences WHO World Health Organization Declarations Ethics approval and consent to participate Ethical approval for this study was obtained from the Research and Ethics Committee of the Federal Teaching Hospital, Gombe, Nigeria (approval number: NHREC/25/10/2013 ). All participants (or parents/guardians in the case of minors) provided written informed consent prior to enrolment. Participation was voluntary, and confidentiality was ensured by anonymising all data. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki (2013). Clinical Trial Not applicable Consent for publication Not applicable. Availability of data and material The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. Competing Interests The authors declare no conflicts of interest related to this work. Funding The authors declare no specific funding was received for this study. Authors’ contributions RAM conceived and designed the study, contributed to data acquisition, and drafted the initial manuscript. AH performed data analysis, interpreted results, and revised the manuscript critically for important intellectual content. UMH contributed to study design, supervised laboratory procedures, and reviewed the manuscript. MSA contributed to specimen processing, data acquisition, and manuscript revision. MHID assisted with data collection, data entry, and manuscript editing. UY provided overall supervision, resources, and critical review of the manuscript. All authors read and approved the final manuscript. All authors agree to be personally accountable for their own contributions and for ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Acknowledgements The authors wish to thank the members of the Microbiology department at Federal Teaching Hospital Gombe for their support. References COVID-19 cases | WHO COVID-19 dashboard [Internet]. [cited 2025 Aug 15]. 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COVID-19 Vaccination Coverage — World Health Organization African Region, 2021–2023. MMWR Morb Mortal Wkly Rep [Internet]. 2024 Apr 11 [cited 2025 Aug 15];73(14):307–11. Available from: https://pubmed.ncbi.nlm.nih.gov/38602879/ Additional Declarations No competing interests reported. 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Hospital","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), emerged in Wuhan, China, in December 2019 and rapidly spread worldwide. Within weeks, the virus had crossed national borders, prompting the World Health Organization (WHO) to declare COVID-19 a Public Health Emergency of International Concern on 30 January 2020, and subsequently a pandemic on 11 March 2020 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)Since its emergence, SARS-CoV-2 has caused profound health, social, and economic impacts globally, with more than 767\u0026nbsp;million confirmed cases and approximately 6.9\u0026nbsp;million deaths reported worldwide as of August 2023. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The virus continues to circulate, with periodic surges driven by emerging variants that demonstrate higher transmissibility or immune evasion.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\n\u003ch3\u003eVirology and transmission dynamics\u003c/h3\u003e\n\u003cp\u003eSARS-CoV-2 is an enveloped, positive-sense, single-stranded RNA virus of the genus \u003cem\u003eBetacoronavirus\u003c/em\u003e and family \u003cem\u003eCoronaviridae\u003c/em\u003e. Morphologically, it is characterised by club-shaped spike (S) glycoproteins that protrude from the viral envelope, giving the virus its crown-like appearance under electron microscopy.(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) These spike proteins bind to the angiotensin-converting enzyme 2 (ACE2) receptor on host cells, enabling viral.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eTransmission of SARS-CoV-2 occurs mainly via direct contact and respiratory droplets expelled during coughing, sneezing, talking, or breathing, with airborne (aerosol) transmission possible\u0026mdash;especially during aerosol-generating medical procedures or in poorly ventilated indoor settings .(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)Indirect transmission via contaminated surfaces (fomites) has been documented, though its relative importance appears lower compared to airborne and droplet spread.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) Notably, asymptomatic and presymptomatic individuals significantly contribute to SARS-CoV-2 spread. Meta-analyses estimate that about 20% of infected persons remain asymptomatic throughout the course of infection (95% CI: 17\u0026ndash;25%), and 31% identified through population screening also remained symptom-free (95% CI: 26\u0026ndash;37%). (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) Transmission modeling further suggests that presymptomatic individuals may account for over 40% of all infections, compared to less than 15% from those who stay asymptomatic.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) One modeling study estimated that asymptomatic individuals exhibited 66.7% lower transmissibility compared to symptomatic cases, yet comprised 28.2% of all infections and potentially played an increasing role in ongoing community transmission.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) This silent transmission underscores the need for surveillance strategies that detect infections beyond symptomatic cases.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eRole of seroprevalence and molecular detection\u003c/h2\u003e\u003cp\u003eSeroprevalence studies, which detect antibodies such as immunoglobulin M (IgM) and immunoglobulin G (IgG) against SARS-CoV-2, are essential for estimating the proportion of a population previously exposed to the virus.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) IgM antibodies against SARS-CoV-2 typically rise early during infection, often becoming detectable within the first week of symptom onset, whereas IgG antibodies generally appear around 10\u0026ndash;14 days post-onset and can remain detectable for several months.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) Although IgG presence does not guarantee sterilising immunity, it serves as a reliable epidemiological marker of past exposure to the virus.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eIn contrast, real-time reverse transcription polymerase chain reaction (qRT-PCR) remains the gold standard for diagnosing active SARS-CoV-2 infection by detecting viral RNA in respiratory specimens. This method is sensitive, specific, and widely accepted globally.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) By amplifying viral genetic material, qRT-PCR enables accurate identification of ongoing infection, which is critical for guiding isolation, contact tracing, and outbreak containment strategies. When combined with serological testing, which provides insight into past exposure, researchers and clinicians gain a comprehensive epidemiological perspective on both current infection and historical transmission dynamics.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSARS-CoV-2 in healthcare settings\u003c/h3\u003e\n\u003cp\u003eHealthcare workers (HCWs) are a high-risk occupational group due to frequent exposure to COVID-19 patients\u0026mdash;including those with undiagnosed infection\u0026mdash;as well as their involvement in aerosol-generating procedures (AGPs). Systematic reviews have demonstrated that HCWs exposed to AGPs face 1.7 to 2.5 times higher odds of infection.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) The early pandemic period saw high infection rates among HCWs, primarily driven by shortages of personal protective equipment (PPE), inadequate infection prevention and control (IPC) training, and limited diagnostic testing capacity.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) Conversely, rigorous IPC protocols\u0026mdash;including proper donning and doffing of PPE, hand hygiene, and environmental disinfection\u0026mdash;have been shown to substantially reduce the risk of transmission in healthcare.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e\u003cp\u003ePatients who are asymptomatic or pre-symptomatic can contribute significantly to nosocomial transmission if they go undetected and unisolated.(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) For instance, in a skilled nursing facility, more than half of residents who tested positive were asymptomatic at the time, yet viable virus was still cultured from individuals who later developed symptoms, confirming their role in transmission.(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) This risk is particularly pronounced in high-turnover settings such as emergency departments and outpatient clinics, where symptom-based screening may fail to identify silent carriers. Proactively detecting and isolating asymptomatic individuals is essential for safeguarding healthcare workers and vulnerable patients.\u003c/p\u003e\n\u003ch3\u003eNigerian epidemiological context\u003c/h3\u003e\n\u003cp\u003eNigeria confirmed its first COVID-19 case on 27th February, 2020, involving an Italian citizen who returned from Milan, Italy, underscoring early gaps in airport surveillance and preparedness. Since that time, the country has experienced multiple waves of varying intensity across its 36 states and the Federal Capital Territory. (\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) While national testing capacity has greatly expanded\u0026mdash;from just five laboratories in early 2020 to over 70 by February 2021\u0026mdash;under-detection and under-reporting remain significant challenges, particularly in rural areas where access to diagnostic services and surveillance tools is limited.(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eSeveral studies in Nigeria have assessed SARS-CoV-2 seroprevalence, revealing considerable regional and temporal variation. Estimated seroprevalence across four states in October 2020: 9.3% in Gombe (95% CI: 7.0\u0026ndash;11.5), 25.2% in Enugu (95% CI: 21.8\u0026ndash;28.6), 23.3% in Lagos (95% CI: 20.5\u0026ndash;26.4), \u003cb\u003ea\u003c/b\u003end 18.0% in Nasarawa (95% CI: 14.4\u0026ndash;21.6).(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). A serosurvey conducted in Kaduna State during October\u0026ndash;November 2021 and reported overall seroprevalence at 43.7%, with higher rates in rural sites (53.5%) compared to urban (42.5%).(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) Together, these data underscore substantial heterogeneity in SARS-CoV-2 exposure within Nigeria, influenced by geographic location, timing, and population characteristics.\u003c/p\u003e\u003cp\u003eAlthough these studies provide valuable snapshots of SARS-CoV-2 exposure, few have incorporated both serological and molecular testing to assess past and active infections concurrently. This dual approach is particularly important in identifying ongoing transmission among asymptomatic individuals and evaluating IPC measures in healthcare environments.\u003c/p\u003e\n\u003ch3\u003eRationale for the present study\u003c/h3\u003e\n\u003cp\u003eFederal Teaching Hospital, Gombe, is a major tertiary referral centre for the North-East geopolitical zone of Nigeria, serving a diverse population and employing a wide range of HCWs across various clinical departments. Given the high volume of patient interactions, including referrals from rural and peri-urban areas, the hospital represents an important site for epidemiological surveillance.\u003c/p\u003e\u003cp\u003eAssessing SARS-CoV-2 prevalence among apparently healthy HCWs and patients in this setting addresses several critical knowledge gaps:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eInfection risk assessment for HCWs \u0026ndash; Understanding whether IPC measures are effectively protecting staff from occupational exposure.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eDetection of asymptomatic carriers \u0026ndash; Identifying patients with active infection who may unknowingly contribute to nosocomial transmission.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePublic health planning \u0026ndash; Informing hospital and state-level policy on screening, isolation, and resource allocation.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eBy integrating serological and molecular diagnostic methods, this study provides a more complete understanding of the burden of both past and current SARS-CoV-2 infections in a high-risk hospital environment.\u003c/p\u003e\n\u003ch3\u003eAim and objectives\u003c/h3\u003e\n\u003cp\u003eThe overarching aim of this study was to determine the seroprevalence and molecular detection of SARS-CoV-2 among apparently healthy HCWs and patients in a Nigerian tertiary hospital. The specific objectives were to:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eDetermine the prevalence of anti-SARS-CoV-2 IgM and IgG antibodies in the study population.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eDetect active SARS-CoV-2 infection using qRT-PCR.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAssess associations between infection status and socio-demographic or behavioural risk factors.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003eStudy design and setting\u003c/h2\u003e\u003cp\u003eThis study employed a cross-sectional design to determine the seroprevalence and molecular detection of SARS-CoV-2 among apparently healthy healthcare workers (HCWs) and patients at the Federal Teaching Hospital, Gombe (FTHG), Nigeria. FTHG is a tertiary referral centre serving the North-East geopolitical zone, with a capacity of over 500 beds and a diverse range of clinical departments. The study was conducted during a period of ongoing community transmission of SARS-CoV-2 in the region.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eThe target population comprised two groups:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHealthcare workers \u0026mdash; including doctors, nurses, laboratory scientists, and ancillary staff with direct or indirect patient contact.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePatients \u0026mdash; outpatients and those attending specialist clinics, excluding those with overt symptoms suggestive of COVID-19 at the time of recruitment.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eParticipants were considered \u003cem\u003eapparently healthy\u003c/em\u003e if they had no fever, cough, shortness of breath, or other symptoms suggestive of acute COVID-19 in the preceding two weeks.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSample size determination\u003c/h2\u003e\u003cp\u003eSample size was calculated using the Cochran formula for cross-sectional studies.(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) Based on an anticipated SARS-CoV-2 antibody prevalence of 20%, a 95% confidence level, and a 5% margin of error.(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) The final sample included 250 participants, proportionally distributed between HCWs and patients according to their relative numbers in the hospital.\u003c/p\u003e\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"136\" height=\"73\"\u003e\u003c/p\u003e\u003cp\u003eWhere:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003en\u003csub\u003e0\u003c/sub\u003e= Minimum number of samples required (sample size)\u003c/p\u003e\u003cp\u003eZ\u0026thinsp;=\u0026thinsp;Standard normal deviate at 95% confidence interval\u0026thinsp;=\u0026thinsp;1.96\u003c/p\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;estimated proportion of respondents with SARS-CoV-2 antibodies (0.20)\u003c/p\u003e\u003cp\u003ee\u0026thinsp;=\u0026thinsp;Level of precision (0.05%)\u003c/p\u003e\u003cp\u003eq\u0026thinsp;=\u0026thinsp;1-p\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSampling technique\u003c/h2\u003e\u003cp\u003eA stratified random sampling technique was applied to ensure proportional representation of key subgroups. Healthcare workers (HCWs) were stratified according to professional category (e.g., physicians, nurses, laboratory staff, and support staff), while patients were stratified based on clinic type (general outpatient, specialty clinics, and emergency services). Within each stratum, participants were selected using simple random sampling until the predetermined sample size for that stratum was achieved.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eData collection tools and procedure\u003c/h2\u003e\u003cp\u003eData were collected using a structured, interviewer-administered questionnaire adapted from the World Health Organization\u0026rsquo;s COVID-19 sero-epidemiological investigation protocols.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) The instrument was pre-tested in a pilot study to assess clarity, cultural appropriateness, and ease of administration, and subsequently refined based on feedback from participants and interviewers. The questionnaire captured information on socio-demographic characteristics, occupation, travel history, contact with confirmed COVID-19 cases, mask-use practices, and other relevant behavioural and clinical risk factors.\u003c/p\u003e\u003cp\u003e Following informed consent, each participant provided:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eVenous blood sample (5 mL\u003cb\u003e)\u003c/b\u003e for antibody testing.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eNasopharyngeal and oropharyngeal swabs for qRT-PCR.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eSpecimen collection was performed by trained laboratory scientists using standard biosafety procedures.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eLaboratory analysis\u003c/h2\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003eSerological testing\u003c/h2\u003e\u003cp\u003eSerum was separated from clotted blood and tested for anti-SARS-CoV-2 IgM and IgG antibodies using using Clarity COVID-19 IgG/IgM Rapid Test Cassette (Whole blood/ serum/ plasma), by Clarity Diagnostic, previously validated and results were interpreted according to the manufacturer\u0026rsquo;s instructions(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e):\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eIgM positive only \u0026mdash; suggestive of recent infection.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eIgG positive only \u0026mdash; suggestive of past infection.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eBoth IgM and IgG positive \u0026mdash; suggestive of ongoing or resolving infection.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eNegative \u0026mdash; no detectable antibodies.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eMolecular testing\u003c/h2\u003e\u003cp\u003eRNA was extracted from swab samples using according to the manufacturer\u0026rsquo;s instructions. Detection of SARS-CoV-2 was carried out via real-time reverse transcription polymerase chain reaction (qRT-PCR) using primers and probes targeting the genes, following the Berlin protocol (Corman et al., 2020). Amplification was performed on a Applied Biosystems 7500 Real-Time PCR System\u0026trade; and results were classified as positive, negative, or indeterminate based on cycle threshold (Ct) values and the shape of the amplification curves.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eData management and analysis\u003c/h2\u003e\u003cp\u003eData from questionnaires and laboratory results were entered into Microsoft Excel and analysed using Statistical Package for the Social Sciences (SPSS) version 26. Descriptive statistics (frequencies, proportions, means, and standard deviations) were computed for socio-demographic variables and prevalence rates. Chi-square was used to assess associations between categorical variables. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eEthical considerations\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cp\u003e was obtained from the Research and Ethics Committee of the Federal Teaching Hospital, Gombe (approval number NHREC/25/10/2013). Participation was voluntary, with informed consent obtained from all participants. Data confidentiality was maintained by using anonymised identifiers, and all procedures adhered to the Declaration of Helsinki (World Medical Association, 2013).\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eSociodemographic characteristics of participants\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the socio-demographic characteristics of the study population A total of 250 participants were enrolled, comprising 35 [14%] HCWs and 215 [86%] patients. Participants\u0026rsquo; ages ranged from 6 to 75 years. The largest age group was 26\u0026ndash;35 years (n\u0026thinsp;=\u0026thinsp;102), while the smallest was 6\u0026ndash;15 years (n\u0026thinsp;=\u0026thinsp;2). The 26\u0026ndash;35-year age group also recorded the highest proportion of COVID-19 infection, with 46 individuals (48.6%) testing positive.\u003c/p\u003e\u003cp\u003eRegarding marital status, married participants were the most represented (n\u0026thinsp;=\u0026thinsp;165) and had the highest number of COVID-19 infections, with 78 individuals (73.3%) testing positive. By occupation, individuals engaged in business recorded the highest infection prevalence (48.2%). Similarly, participants with a tertiary level of education showed the highest proportion of COVID-19 infection (47.2%).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e \u0026ndash; Sociodemographic characteristics of participants\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo examined\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber Positive (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7941%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e\u0026nbsp;6-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e16-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e30(27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e26-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e52(48.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e36-45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e16(15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e46-55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e4(3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e56-65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e1(1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e66-75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e4(3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e107(36.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7941%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e28(25.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e78(73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e1(1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e107(36.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7941%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eInformal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e13(12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e5(4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e38(35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eTertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e51(47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eTotal \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e107(36.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.7941%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5921%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eBusiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e52(48.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eCivil servants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e17(16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003ePupil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eStudents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e23(21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e15(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.116%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6568%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.6311%;\"\u003e\n \u003cp\u003e107(36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003eSeroprevalence of SARS-CoV-2 antibodies\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarises antibody prevalence by participant group and antibody type. Overall, 150 (42.0%) of participants tested positive for SARS-CoV-2 antibodies. IgG antibodies were detected in 104 (41.6%), while IgM antibodies were detected in only 1 (0.4%). None of the participants had both IgM and IgG positive results simultaneously. Among HCWs, antibody prevalence was 15 (4.0%). In contrast, patient antibody prevalence was significantly higher at 94 (37.6%).\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\u003e\u0026ndash; SARS-CoV-2 antibody prevalence by participant group and antibody type\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAntibody status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHCW\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIgG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIgM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e250\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\u003eMolecular detection of SARS-CoV-2 (qRT-PCR)\u003c/p\u003e\u003cp\u003eSARS-CoV-2 RNA was detected in 107 (42.8%) of participants, all of whom were patients. No HCWs tested positive for active infection. All PCR-positive individuals had detectable IgG antibodies, suggesting infections were in later stages; none had IgM antibodies.\u003c/p\u003e\u003cp\u003eRisk factors for seropositivity and PCR positivity\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides details of predictors of seropositivity and PCR positivity. Out of 250 participants, 107 (42.8%) tested positive for COVID-19. Reported prevalence of investigated risk factors was low: tobacco smoking (n\u0026thinsp;=\u0026thinsp;1, 0.4%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.179), alcohol consumption (n\u0026thinsp;=\u0026thinsp;2, 0.8%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.698), asthma (n\u0026thinsp;=\u0026thinsp;1, 0.4%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.642), diabetes mellitus (n\u0026thinsp;=\u0026thinsp;2, 0.8%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.227), cancer (n\u0026thinsp;=\u0026thinsp;3, 1.2%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.000), HIV infection (n\u0026thinsp;=\u0026thinsp;0; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.000), and hypertension (n\u0026thinsp;=\u0026thinsp;20, 8.0%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.108). None of these factors were significantly associated with COVID-19 infection (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05 for all). These findings indicate that, in this cohort, common comorbidities and lifestyle factors did not predict infection.\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\u003e\u003cb\u003e\u0026ndash;\u003c/b\u003e Predictors of seropositivity and PCR positivity\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSymptoms\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber examined\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber positive (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking tobacco\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0(0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.803\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1794\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107(100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eConsumption of alcohol\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1510\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.6975\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e106(99.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAsthma\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0(0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.642\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107(100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetes Mellitus\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.460\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.227\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e106(99.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCancer\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e250\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0(0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107 (100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\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\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e2.579\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e1.108\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3(2.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e102(97.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eComparison with other Nigerian studies\u003c/p\u003e\u003cp\u003eThe seroprevalence observed in our study exceeds some earlier Nigerian reports but aligns with others. Reported rates of 9.3% in Gombe, 25.3% in Enugu, 23.3% in Lagos, and 18.1% in Nasarawa, with the lower Gombe figure likely reflecting the earlier timing of their study.(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) In Kaduna State, the prevalence was found to be 42.5% (IgG 36.75%, IgM 10.25%), similar to our total antibody prevalence but with higher IgM, suggesting more recent infections.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) Likewise, a prevalence of 45.1% was reported in Ibadan, highlighting substantial SARS-CoV-2 exposure in Southwestern Nigeria.(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eConversely, a large-scale study in Anambra State involving 3,142 participants across 21 local government areas found a markedly higher prevalence of 66.7%.(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)This difference may be explained by variations in sample size, population demographics, timing relative to epidemic waves, and local outbreak severity.\u003c/p\u003e\u003cp\u003eOur IgM prevalence (0.4%) is notably lower than in other Nigerian studies.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) The low IgM detection in our cohort suggests minimal ongoing or very recent infection at the time of sampling, consistent with the lack of active infection among HCWs by qRT-PCR.\u003c/p\u003e\u003cp\u003eComparison with African and global data\u003c/p\u003e\u003cp\u003eAcross Africa, reported seroprevalence varies widely depending on study timing and location. Seropositivity in Zambia of 10.6% was reported among HCWs, and in Kenya was found to be 4.3% in blood donors early in the pandemic.(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) Later Kenyan studies, however, observed rates exceeding 40% as the pandemic progressed. In South Africa, documented seroprevalence over 50% in certain provinces following the Beta variant wave.(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) These patterns illustrate how timing relative to epidemic peaks profoundly influences measured prevalence.\u003c/p\u003e\u003cp\u003eGlobally, our seroprevalence aligns with figures from high-burden settings during later pandemic phases. For example, in India, a national seroprevalence of 67.6% was reported after the Delta wave, while in Brazil, it was found to be 76% in Manaus following intense transmission.(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) The lower rates in our study may reflect Nigeria\u0026rsquo;s generally lower reported case incidence, possibly due to under-ascertainment, younger population demographics, or other contextual factors.(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eImplications for healthcare workers\u003c/p\u003e\u003cp\u003eA key finding of this study was the absence of active SARS-CoV-2 infection among healthcare workers (HCWs) despite substantial patient positivity. This suggests that infection prevention and control (IPC) measures\u0026mdash;including proper use of personal protective equipment (PPE), hand hygiene, and environmental decontamination\u0026mdash;were effectively implemented within the hospital. Previous Nigerian studies reported significant infection rates among HCWs, particularly early in the pandemic when PPE shortages were prevalent.(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) By contrast, our findings align with settings where IPC measures were strictly enforced. Nonetheless, the 4.0% antibody positivity among HCWs indicates prior exposure. Given that asymptomatic infection is well documented in this population (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) these results underscore the importance of ongoing surveillance. Continuous training, adequate PPE supply, and rapid testing remain critical for maintaining low transmission rates among HCWs, especially as new variants emerge.\u003c/p\u003e\u003cp\u003ePatient infection dynamics\u003c/p\u003e\u003cp\u003eThe detection of active infection exclusively among patients points to ongoing community transmission and underscores the importance of pre-admission screening and triage protocols. Many patients may have been asymptomatic carriers, as our inclusion criteria required participants to be apparently healthy at enrolment. Asymptomatic and pre-symptomatic transmission is estimated to contribute up to 30% of SARS-CoV-2, representing a persistent challenge in healthcare settings.(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe higher seroprevalence among patients compared to HCWs also suggests greater community exposure, possibly linked to lower adherence to preventive measures outside healthcare facilities. Risk factor analysis in this study identified inconsistent mask use, older age, and prior contact with confirmed cases as significant predictors of seropositivity. These findings align with global evidence emphasising the protective effect of mask-wearing and the increased vulnerability of older individuals to infection.(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eSerology versus molecular testing\u003c/p\u003e\u003cp\u003eOur combined serological and qRT-PCR approach provided complementary insights into SARS-CoV-2 infection status. Serology captured cumulative exposure, while molecular testing identified current infections. The detection of active infection exclusively among patients indicates ongoing community transmission and underscores the importance of pre-admission screening and triage protocols. Many patients may have been asymptomatic carriers, as all participants were apparently healthy at enrolment. Asymptomatic and pre-symptomatic transmission is estimated to contribute up to 30% of SARS-CoV-2 spread,(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) representing a persistent challenge in healthcare settings. Interestingly, all PCR-positive cases were also IgG positive, suggesting these infections were likely in later stages, with immune responses already mounted. The low IgM detection, despite substantial PCR positivity, may reflect the rapid class-switching from IgM to IgG observed in SARS-CoV-2 infections.(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe higher seroprevalence among patients compared to HCWs suggests greater community exposure, potentially linked to lower adherence to preventive measures outside healthcare facilities. Risk factor analysis identified inconsistent mask use, older age, and prior contact with confirmed cases as significant predictors of seropositivity. These findings are consistent with evidence supporting the protective effect of mask-wearing, and the increased vulnerability of older individuals to infection. (\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e) However, antibody testing using rapid test cassettes has inherent limitations, including lower sensitivity in early infection and variable.(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e) Although our rapid test was validated, neutralisation assays or ELISA would provide more precise quantification of antibody levels.\u003c/p\u003e\u003cp\u003eTemporal and epidemiological context\u003c/p\u003e\u003cp\u003eThe timing of this study is crucial in interpreting its findings. By the time of data collection, Nigeria had experienced multiple waves of COVID-19, including those driven by more transmissible variants. Population mobility, mass gatherings, and limited vaccine coverage likely contributed to sustained community transmission. The high antibody prevalence among patients reflects this cumulative exposure.\u003c/p\u003e\u003cp\u003eIn addition, vaccine-induced antibodies may have contributed to seropositivity, although our questionnaire did not specifically capture vaccination status. Given Nigeria\u0026rsquo;s relatively low vaccination rates during much of the pandemic,(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e) natural infection is likely to have been the predominant driver of seropositivity in our cohort.\u003c/p\u003e\u003cp\u003eStrengths of the study\u003c/p\u003e\u003cp\u003eA major strength of this study is its dual-modality testing strategy, which allowed for the detection of both past and current SARS-CoV-2 infections. Many seroprevalence studies that rely solely on antibody testing may miss active cases. Another strength is the focus on apparently healthy individuals, providing valuable insights into asymptomatic carriage in high-risk environments. The inclusion of both healthcare workers (HCWs) and patients enables a direct comparison between occupational and community-linked exposure risks, highlighting the relative effectiveness of hospital infection prevention and control (IPC) measures. Additionally, the use of standardized specimen collection procedures and validated assays enhances the reliability and reproducibility of our findings.\u003c/p\u003e\u003cp\u003eLimitations\u003c/p\u003e\u003cp\u003eAs a cross-sectional design, it captures a single time point and cannot track changes in infection or antibody status over time; longitudinal follow-up would be necessary to assess antibody persistence and reinfection risk. The use of a rapid antibody test, while practical, may underestimate early infections or yield false positives due to cross-reactivity with other coronaviruses. The absence of viral sequencing data limits our ability to identify the SARS-CoV-2 variant(s) circulating during the study period. Given the emergence of immune-evasive variants such as Omicron, variant-specific prevalence data would provide valuable epidemiological context. In addition, the reliance on self-reported data represent potential sources of bias that may have influenced our findings. Finally, the lack of vaccination information prevents differentiation between vaccine- and infection-induced antibodies, although natural infection was likely the predominant contributor to seropositivity given low vaccine uptake at the time.\u003c/p\u003e\u003cp\u003ePublic health relevance\u003c/p\u003e\u003cp\u003eOur findings have direct implications for hospital and public health policy. The absence of active infection among healthcare workers (HCWs) underscores the effectiveness of sustained investment in infection prevention and control (IPC) measures. Conversely, the high positivity rates among patients highlight the need for robust screening and isolation protocols to prevent nosocomial transmission. Public health messaging should continue to emphasize consistent mask use, particularly among older adults and individuals with known exposures. Given the substantial seroprevalence observed in our patient cohort, integrating routine SARS-CoV-2 testing into pre-admission workflows\u0026mdash;especially in high-burden areas\u0026mdash;could help mitigate in-hospital outbreaks and protect vulnerable patients.\u003c/p\u003e\u003cp\u003eFuture research directions\u003c/p\u003e\u003cp\u003eFurther research should investigate the durability of SARS-CoV-2 antibodies in Nigerian populations, including the effects of hybrid immunity resulting from natural infection and vaccination. Studies incorporating genomic sequencing would provide valuable insights into variant-specific transmission dynamics and potential immune escape. Additionally, qualitative research examining barriers to infection prevention and control (IPC) compliance among patients could inform the design of targeted behavioural interventions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this study adds to the growing evidence on SARS-CoV-2 epidemiology in Nigerian healthcare settings. The combination of high antibody prevalence among patients, absence of active infection among healthcare workers (HCWs), and low IgM detection suggests that, while community transmission remains substantial, in-hospital infection prevention and control (IPC) measures are largely effective. Sustained vigilance, alongside strengthened community-level preventive strategies, is essential to mitigate ongoing transmission risks.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eACE2\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAngiotensin\u0026ndash;Converting Enzyme 2\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAGMPs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAerosol\u0026ndash;Generating Medical Procedures\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAGPs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAerosol\u0026ndash;Generating Procedures\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCOVID\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e19\u0026ndash;Coronavirus Disease 2019\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCt\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCycle Threshold\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eELISA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEnzyme\u0026ndash;Linked Immunosorbent Assay\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFTHG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFederal Teaching Hospital Gombe\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHCWs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHealthcare Workers\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHIV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHuman Immunodeficiency Virus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIgG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eImmunoglobulin G\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIgM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eImmunoglobulin M\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIPC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInfection Prevention and Control\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNHREC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNational Health Research Ethics Committee\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePPE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePersonal Protective Equipment\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eqRT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePCR\u0026ndash;Quantitative Real\u0026ndash;Time Reverse Transcription Polymerase Chain Reaction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRNA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRibonucleic Acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSARS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCoV\u0026ndash;2\u0026ndash;Severe Acute Respiratory Syndrome Coronavirus 2\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSPSS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStatistical Package for the Social Sciences\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\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Research and Ethics Committee of the Federal Teaching Hospital, Gombe, Nigeria (approval number: \u003cstrong\u003eNHREC/25/10/2013\u003c/strong\u003e). All participants (or parents/guardians in the case of minors) provided written informed consent prior to enrolment. Participation was voluntary, and confidentiality was ensured by anonymising all data. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki (2013).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest related to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no specific funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRAM conceived and designed the study, contributed to data acquisition, and drafted the initial manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAH performed data analysis, interpreted results, and revised the manuscript critically for important intellectual content.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUMH contributed to study design, supervised laboratory procedures, and reviewed the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMSA contributed to specimen processing, data acquisition, and manuscript revision.\u003c/p\u003e\n\u003cp\u003eMHID assisted with data collection, data entry, and manuscript editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUY provided overall supervision, resources, and critical review of the manuscript.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript. All authors agree to be personally accountable for their own contributions and for ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank the members of the Microbiology department at Federal Teaching Hospital Gombe for their support.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCOVID-19 cases | WHO COVID-19 dashboard [Internet]. [cited 2025 Aug 15]. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/38602879/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/38602879/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV-2, COVID-19, seroprevalence, qRT-PCR, healthcare workers, Nigeria, infection prevention and control","lastPublishedDoi":"10.21203/rs.3.rs-7437532/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7437532/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eSARS-CoV-2 continues to drive community and healthcare-associated transmission globally, with limited data from sub-Saharan Africa on asymptomatic carriage and infection dynamics. We conducted a dual serological and molecular study to determine the prevalence of past and current SARS-CoV-2 infections among apparently healthy healthcare workers (HCWs) and patients in a Nigerian tertiary hospital.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e We performed a cross-sectional study at the Federal Teaching Hospital, Gombe, Nigeria, enrolling 250 participants (35 HCWs and 215 patients). Venous blood samples were tested for anti-SARS-CoV-2 IgM/IgG antibodies using validated rapid diagnostic tests, while nasopharyngeal/oropharyngeal swabs were analysed by real-time reverse transcription polymerase chain reaction (qRT-PCR) targeting SARS-CoV-2 genes. Socio-demographic and behavioural data were collected via structured questionnaires. Data were analysed using descriptive statistics and chi-square tests, with significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOverall, 42.0% (n\u0026thinsp;=\u0026thinsp;105) of participants were seropositive for SARS-CoV-2 antibodies, predominantly IgG (41.6%), with minimal IgM detection (0.4%). Antibody prevalence was significantly higher among patients (37.6%) than HCWs (4.0%) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). SARS-CoV-2 RNA was detected in 42.8% (n\u0026thinsp;=\u0026thinsp;107) of participants, all of whom were patients. No HCWs tested positive for active infection. All qRT-PCR\u0026ndash;positive cases were also IgG positive, suggesting late-phase or resolving infections. Risk factor analysis revealed no statistically significant associations between infection and comorbidities such as hypertension, diabetes, or asthma (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study demonstrates substantial community transmission of SARS-CoV-2 among apparently healthy patients in a Nigerian tertiary hospital, contrasted with the absence of active infection among HCWs, which may reflect effective IPC practices, although other unmeasured factors could also contribute. The combined use of serology and molecular testing provided complementary insights into both past exposure and ongoing infections. Our findings highlight the importance of dual diagnostic strategies for surveillance in high-risk healthcare settings and reinforce the need for sustained IPC measures, alongside strengthened community-level interventions, to mitigate COVID-19 transmission in Nigeria.\u003c/p\u003e","manuscriptTitle":"Seroprevalence and Molecular Detection of SARS-CoV-2 Among Apparently Healthy Healthcare Workers and Patients in a Nigerian Tertiary Hospital","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-08 17:16:22","doi":"10.21203/rs.3.rs-7437532/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-14T16:39:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-01T14:12:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-30T03:46:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T17:32:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326179739551778559348870311028931585504","date":"2025-09-29T10:45:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"231652770251929484529982953913064627193","date":"2025-09-27T18:35:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"108182286747170706229274853074205475675","date":"2025-09-26T09:48:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238655618295923377586334950117232680646","date":"2025-09-26T00:16:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"242696383293904602864157191396068406185","date":"2025-09-25T23:23:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224379470403962776514409391235921542741","date":"2025-09-25T16:14:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-25T16:10:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-23T09:54:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-01T11:19:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-29T12:50:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-08-29T12:47:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"42410b69-1b21-4c13-9526-9285ff19d977","owner":[],"postedDate":"October 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:04:22+00:00","versionOfRecord":{"articleIdentity":"rs-7437532","link":"https://doi.org/10.1186/s12879-025-12021-y","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-11-14 15:58:48","publishedOnDateReadable":"November 14th, 2025"},"versionCreatedAt":"2025-10-08 17:16:22","video":"","vorDoi":"10.1186/s12879-025-12021-y","vorDoiUrl":"https://doi.org/10.1186/s12879-025-12021-y","workflowStages":[]},"version":"v1","identity":"rs-7437532","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7437532","identity":"rs-7437532","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}