West Nile Virus Exposure in Gezira State, Sudan: An ELISA-Based Study

 Corresponding author: Sarah Esadig Elagib Eltahier Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. West Nile Virus Exposure in Gezira State, Sudan: An ELISA-Based Study Sara Elsadig Elagib Eltahir *, Abd El Rahman Aldaw Mohammed and Omer Hassan Mohamed Faculty of Medical Laboratory Sciences, University of Gezira, Sudan. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 280-286 Publication history: Received on 14 September 2025; revised on 22 October 2025; accepted on 25 October 2025 Article DOI: https://doi.org/10.30574/gscbps.2025.33.1.0407 Abstract West Nile Virus (WNV) is a mosquito-borne flavivirus responsible for West Nile fever. Although most infections are asymptomatic or mild, fewer than 1% progress to West Nile neuroinvasive disease (WNND), which has an estimated fatality rate of 10% (Petersen et al., 2013). This cross-sectional study assessed WNV exposure among 400 residents of Gezira State, Sudan (2019–2022). Blood samples were collected and analyzed for WNV-specific IgG and IgM antibodies using ELISA, while RT-PCR was performed on IgG-positive samples to detect active viral RNA. Overall, 62.3% (249/400) of participants were positive for WNV-IgG antibodies, indicating past exposure, whereas all samples were negative for WNV-IgM antibodies, suggesting the absence of recent infection. No significant correlations were observed between common risk factors and IgG positivity (P > 0.05), except for neck stiffness, which showed a significant association (P < 0.05). The high prevalence of WNV-IgG antibodies, coupled with the absence of IgM positivity, highlights widespread prior exposure and a lack of current infection in the population. These findings underscore the need for sustained surveillance and public health initiatives focusing on mosquito control and community awareness to prevent future WNV outbreaks. Keywords: West Nile Virus; Igg Seroprevalence; Sudan; ELISA; Vector-Borne Disease 1. Introduction West Nile Virus (WNV) is a globally distributed mosquito-borne flavivirus that primarily causes asymptomatic or mild infections, collectively termed West Nile fever (WNF). Severe neurological complications, including meningitis and encephalitis, occur in less than 1% of cases and are associated with a mortality rate of approximately 10% (Petersen et al., 2013). The virus was first isolated in Uganda in 1937 (Smith burn et al., 1940) and later spread to North America in 1999 (CDC, 2017; WHO, 2011). Since then, outbreaks have been reported across Europe, Africa, Asia, Australia, and the Americas. In the United States, seasonal outbreaks typically peak in late summer (CDC, 2017). Approximately 80% of WNV infections are asymptomatic, 20% result in WNF, and fewer than 1% develop neuroinvasive disease characterized by neck stiffness, confusion, or seizures (Campbell et al., 2002; CDC, 2017). Transmission occurs mainly through bites from infected Culex mosquitoes, which acquire WNV after feeding on viremic birds. Rare transmission routes include blood transfusion, organ transplantation, and vertical transmission from mother to child (WHO, 2011; CDC, 2019). Elderly individuals and those with comorbidities are at greater risk of severe outcomes. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 280-286 281 Historically, early epidemics were characterized by febrile illness with rash and lymphadenopathy (Marberg et al., 1956; Hayes, 1989), while more recent outbreaks in Romania (1996), Russia (1999), the United States (1999), and Israel (2000) have been dominated by neurological symptoms (Tsai et al., 1998; Platonov et al., 2001; Chowers et al., 2001). Culex mosquitoes are abundant in Sudan, particularly in Gezira State, suggesting a potentially high WNV transmission risk. However, limited epidemiological data exist, as most previous studies have focused on specific populations such as blood donors (Ahmed et al., 2011). This study aimed to determine the seroprevalence of WNV antibodies and associated risk factors among residents of Gezira State using ELISA-based detection of IgM and IgG. 2. Materials and Methods 2.1. Study Design and Population A cross-sectional, laboratory-based study was conducted in Gezira State, Sudan, between February and December 2022. Both symptomatic and asymptomatic individuals were recruited according to predefined inclusion and exclusion criteria. 2.2. Sample Collection and Processing Five milliliters of venous blood were collected aseptically from each participant—2 mL in EDTA tubes (for plasma) and 3 mL in plain tubes (for serum). Plasma was separated immediately, while serum was obtained after clotting by centrifugation at 3000 rpm for 5 minutes. Samples were stored at −20°C until analysis. 2.3. Sample Size A total of 400 participants were enrolled, exceeding the minimum calculated sample size of 384 to ensure representativeness. 2.4. Serological Testing WNV-specific IgM and IgG antibodies were detected using EUROIMMUN ELISA kits following manufacturer instructions. Samples with a ratio ≥1.1 were considered positive, 0.8–1.1 borderline, and <0.8 negative. 2.5. Data Collection and Statistical Analysis Demographic and clinical data were collected using structured questionnaires. Statistical analysis was performed with SPSS (version 22) using chi-square and logistic regression tests. A p-value <0.05 was considered statistically significant. 2.6. Ethical Considerations Ethical approval was obtained from the Faculty of Medical Laboratory Sciences, University of Gezira, and the Gezira State Ministry of Health. Informed consent was obtained from all participants, and confidentiality was maintained throughout the study. 3. Results 3.1. Seroprevalence of WNV Among 400 participants, 62.3% (249) tested positive for WNV-IgG, while 37.8% (151) were negative. All samples were negative for WNV-IgM, although 12 yielded borderline results. 3.2. Symptomatology Commonly reported symptoms included headache (16.3%), flu-like symptoms (13.8%), and fever (13.5%). Less frequent symptoms were vomiting (6.8%), rash (5.5%), and neck stiffness (2.5%). 3.3. Medical History Most participants (95.3%) reported no chronic diseases, and 98.8% had no history of blood transfusion or organ transplantation. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 280-286 282 3.4. Association Analyses No significant associations were found between WNV-IgG positivity and most symptoms (P > 0.05), except for neck stiffness (P = 0.005). Logistic regression revealed significant associations between IgG positivity and gender (female, OR = 1.82), educational level (OR = 1.42), marital status (OR = 0.33), and neck stiffness (OR = 0.08). 4. Discussion The high WNV-IgG seroprevalence (62.3%) observed in Gezira State indicates widespread past exposure, consistent with previous Sudanese studies reporting rates between 60% and 75% (Ahmed et al., 2011; Mohammed et al., 2019). The absence of IgM positivity confirms the lack of ongoing transmission during the study period. No significant associations were detected between IgG positivity and most symptoms, which supports the typically asymptomatic course of WNV infection (Campbell et al., 2002). The observed correlation with neck stiffness aligns with reports linking neuroinvasive manifestations to prior exposure (Sejvar et al., 2003). Environmental and ecological factors, including mosquito abundance and climatic conditions, likely play a major role in sustaining WNV circulation in Gezira State. Limited laboratory capacity and low public awareness further hinder early detection and control. Strengthening surveillance and incorporating WNV screening into blood donation programs are therefore critical (WHO, 2011; CDC, 2019). Figure 1 Symptoms distribution of the study population Figure 2 The medical background of the study population GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 280-286 283 Table 1 The characteristics and patterns of WNV IgG and IgM antibodies in the study population WNV antibodies (n=400) Frequency Percent IgG antibodies Negative 151 37.7 Positive 249 62.3 Borderline 0 0.0 IgM antibodies Negative 388 97.0 Positive 0 0.0 Borderline 12 3.0 Table 2 The distribution of symptoms among the study population Symptoms (n=400) No Yes Frequency Percent Frequency Percent Fever 346 86.5 54 13.5 Vomiting 373 93.3 27 6.8 Rash 378 94.5 22 5.5 Headache 335 83.8 65 16.3 Neck stiffness 390 97.5 10 2.5 Flue like 345 86.3 55 13.8 Table 3 The medical background of the study population Medical History (n=400) No Yes Frequency Percent Frequency Percent Chronic disease 381 95.3 19 4.8 Blood transfusion 395 98.8 5 1.3 Organ transplantation 400 100.0 0 0.0 Table 4 Correlation between WNV-IgG antibodies and clinical symptoms WNV-IgG antibodies Chi-Square P. value Negative (n=151) Positive (n=249) n % N % Fever No (n=346) 136 90.1% 210 84.3% 2.642 0.104 Yes (n=54) 15 9.9% 39 15.7% Vomiting No (n=373) 139 92.1% 234 94.0% 0.552 0.457 Yes (n=27) 12 7.9% 15 6.0% Rash No (n=378) 146 96.7% 232 93.2% 2.236 0.135 GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 280-286 284 Yes (n=22) 5 3.3% 17 6.8% Headache No (n=335) 128 84.8% 207 83.1% 0.185 0.667 Yes (n=65) 23 15.2% 42 16.9% Neck stiffness No (n=390) 143 94.7% 247 99.2% 7.791 0.005* Yes (n=10) 8 5.3% 2 0.8% Flue like No (n=345) 134 88.7% 211 84.7% 1.270 0.260 Yes (n=55) 17 11.3% 38 15.3% *. significant at the 0.05 level Table 5 Correlation between WNV-IgM antibodies and clinical symptoms WNV-IgM antibodies Chi-Square P. value Negative (n=388) Borderline (n=12) n % n % Fever No (n=346) 335 86.3% 11 91.7% 0.283 0.595 Yes (n=54) 53 13.7% 1 8.3% Vomiting No (n=373) 361 93.0% 12 100.0% 0.895 0.344 Yes (n=27) 27 7.0% 0 0.0% Rash No (n=378) 367 94.6% 11 91.7% 0.191 0.662 Yes (n=22) 21 5.4% 1 8.3% Headache No (n=335) 323 83.2% 12 100.0% 2.400 0.121 Yes (n=65) 65 16.8% 0 0.0% Neck stiffness No (n=390) 378 97.4% 12 100.0% 0.317 0.573 Yes (n=10) 10 2.6% 0 0.0% Flue like No (n=345) 334 86.1% 11 91.7% 0.306 0.580 Yes (n=55) 54 13.9% 1 8.3% Table 6 Correlation between WNV-IgG antibodies and medical history WNV-IgG antibodies Chi-Square P. value Negative (n=151) Positive (n=249) n % n % Chronic disease No (n=381) 143 94.7% 238 95.6% 0.161 0.688 Yes (n=19) 8 5.3% 11 4.4% Blood transfusion No (n=395) 151 100.0% 244 98.0% 3.071 0.080 Yes (n=5) 0 0.0% 5 2.0% GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 280-286 285 Table 7 Correlation between WNV-IgM antibodies and medical history WNV-IgM antibodies Chi-Square P. value Negative (n=388) Borderline (n=12) n % n % Chronic disease No (n=381) 369 95.1% 12 100.0% 0.617 0.432 Yes (n=19) 19 4.9% 0 0.0% Blood transfusion No (n=395) 383 98.7% 12 100.0% 0.157 0.692 Yes (n= 5) 5 1.3% 0 0.0% Table 8 Logistic regression analysis of factors associated with WNV-IgG seropositivity Factors P. value Odds ratio 95% confidence interval Lower Upper Fever 0.278 1.527 0.711 3.283 Vomiting 0.140 0.499 0.198 1.256 Rash 0.628 1.355 0.397 4.632 Headache 0.846 1.071 0.534 2.151 Neck stiffness 0.006* 0.082 0.014 0.486 Flue like 0.314 1.466 0.696 3.087 Chronic disease 0.365 1.818 0.499 6.630 Blood transfusion 0.999 0.000 0.000 . *. significant at the 0.05 level Table 9 Logistic regression analysis of factors associated with WNV-IgM seropositivity Factors P. value Odds ratio 95% confidence interval Lower Upper Fever 0.806 0.731 0.060 8.841 Vomiting 0.998 0.000 0.000 . Rash 0.295 4.088 0.293 56.939 Headache 0.997 0.000 0.000 . Neck stiffness 0.999 0.000 0.000 . Flue like 0.960 0.939 0.084 10.498 Chronic disease 0.998 0.000 0.000 . Blood transfusion 0.999 0.000 0.000 . 5. Conclusion This study demonstrates a high prevalence of WNV-IgG antibodies among residents of Gezira State, reflecting extensive past exposure but no current infection. These findings highlight the urgent need for enhanced vector surveillance, mosquito control programs, and integration of WNV diagnostics into national health strategies. Increasing public and healthcare awareness is vital to reduce misdiagnosis and morbidity associated with WNV in Sudan. GSC Biological and Pharmaceutical Sciences, 2025, 33(01), 280-286 286 Compliance with ethical standards Disclosure of conflict of interest No conflict of interest to be disclosed. Statement of ethical approval Ethical approval attached. References [1] Ahmed, A., Elduma, A.H., Magboul, B., Fahal, A. and Khair, O.M. 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