A Comparative Epidemiological Study on the Incidence of Dengue and Chikungunya IgM Antibodies in Ile-Ife and its Environs

Background: Dengue and Chikungunya remain under-recognized illnesses in Nigeria, which are are often misdiagnosed as malaria due to similar symptoms and lack of routine arboviral testing. This study investigated the prevalence of dengue and chikungunya among apparently healthy and febrile individuals presenting to selected healthcare facilities in Ile-Ife and its environs, Osun State, Nigeria.
Methods: A cross-sectional study was conducted among 164 consenting participants attending healthcare facilities across rural, peri-urban, and urban communities in three Local Government Areas (LGAs) in Ile-Ife. Venous blood samples were collected and screened for DENV IgM and CHIKV IgM using appropriate rapid diagnostic test kits. Necessary data to support the study were obtained from the participants using structured questionnaires.
Results: Dengue IgM was detected in 7.3% (12/164) while Chikungunya IgM was 0.6% (1/164) of the participants, with dengue cases distributed across all the three LGAs. Highest Dengue IgM was detected in the age group 11-20 and 21-30 (3%, 5/164). Both Dengue IgM and Chikungunya IgM are predominant in female with 11 (6.7%) for dengue and 1 (0.6%) for chikungunya. No individual was co-infected.
Conclusion: This study establishes recent dengue and chikungunya viruses exposure and a higher incidence of dengue in Ile-Ife. Both being RNA viruses calls for molecular analysis to know more about the adaptation strategies of the viruses. Strengthening differential diagnosis, improving community awareness, and enhancing vector control interventions are essential to improve case detection and reduce misdiagnosis.

Dengue, Chikungunya, IgM, Antibodies

1. Abuelmaali SA, Jamaluddin JAF, Noaman K, Allam M, Abushama HM, Elnaiem DE, et al. (2021). Distribution and Genetic Diversity of Aedes aegypti Subspecies across the Sahelian Belt in Sudan. Pathogens;10(1):78. doi: 10.3390/pathogens10010078 [Google Scholar] [Crossref]

2. Abushouk, A. I., Negida, A., and Ahmed, H. (2016). An updated review of Zika virus. Journal of Clinical Virology, 84, 53–58. [Google Scholar] [Crossref]

3. Adesina, O. A, Japhet, M. O and Omilabu, S. A. (2017). Detection of chikungunya and west nile viruses in febrile patients in Ile-Ife Osun State, Nigeria using real time reverse transcription-polymerase chain reaction (RT-PCR). African Journal of Microbiology Research, 11(28): 1136-1141 [Google Scholar] [Crossref]

4. Adesina, O. A., and Adeniji, J. A. (2016). Incidence of dengue virus in febrile episodes in Ile-Ife, Nigeria. African Journal of Infectious Diseases, 10, 21–24. [Google Scholar] [Crossref]

5. Animasaun, O. S., Shaibu, J. O., Akomolafe, B. K., Animasaun, O. P., Niyang, P. M., Olugbade, O. T., Akinyode, A. O., Omisakin, I. A., Adeogun, A. O., and Audu, R. A. (2025). Enhancing surveillance for dengue fever on Oyo state, Nigeria - a one-health approach. One health outlook, 7(1), 5. [Google Scholar] [Crossref]

6. Azuonwu, O., Adebayo-Olajide T.C., Dimkpa, O Emmanuella, (2024), Serological Investigation of Chikungunya Virus Antibody among Malaria-Suspected Febrile Patients in Some Healthcare Facilities in Rivers State, Clinical Trials and Clinical Research,3(5); DOI:10.31579/2834-5126/077 [Google Scholar] [Crossref]

7. Baba, M. M., Logue, C. H., Oderinde, B., Abdulmaleek, H., Williams, J., Marcello, A., D’Agaro, P., and Hewson, R. (2012). Arbovirus co-infections in suspected febrile malaria and typhoid patients: A worrisome situation in Nigeria. Journal of Antivirals and Antiretrovirals, 4(S1), 1948–5964. [Google Scholar] [Crossref]

8. Baharia, R. K., Pradhan, S., Kumar, V., and Modi, B. (2025). Molecular diagnostics for mosquito-borne viral diseases: Challenges and emerging concepts. In Medical Virology: From Pathogenesis to Disease Control (pp. 253–268). [Google Scholar] [Crossref]

9. Gebremariam, T. T., Schallig, H. D. F. H., Kurmane, Z. M., and Danquah, J. B. (2023). Increasing prevalence of malaria and acute dengue virus coinfection in Africa: A meta-analysis and meta-regression of cross-sectional studies. Malaria Journal, 22(1) [Google Scholar] [Crossref]

10. Kolawole O., Seriki A.A., Irekeola A.A., Ogah J. (2018). The Neglect and Fast Spread of Some Arboviruses:A Note for Healthcare Providers in Nigeria. Diseases.;6:99. doi: 10.3390/diseases6040099. [Google Scholar] [Crossref]

11. Linda, O. E., Violet Chimere, E., & George, O. C. (2021). Determination of Dengue Virus IgM Seroprevalence, Malaria Parasitaemia and Some Haematological Parameters of HIV Infected Individuals in Awka, Nigeria. Journal of Advances in Microbiology, 21(12),17–29. [Google Scholar] [Crossref]

12. https://doi.org/10.9734/jamb/2021/v21i1230410 [Google Scholar] [Crossref]

13. Muhammad , B., Babatunde , M. I., Musa , U. A., Bindawa, A. T., Johnny , J., Aliyu , M. H., … Makeri , M. S. (2023). Serological Evidence of Chikungunya Infection in Kaltungo, Gombe State, Nigeria. Journal of Advances in Microbiology, 23(10), 11–20. [Google Scholar] [Crossref]

14. https://doi.org/10.9734/jamb/2023/v23i10752 [Google Scholar] [Crossref]

15. Nigeria Centre for Disease Control and Prevention (NCDC) (2025). Protecting public health during flood season: NCDC issues nationwide alert on cholera, yellow and dengue fever https://ncdc.gov.ng/news/529/protecting-public-health-during-flood-season%3A-ncdc-issues--nationwide-alert-on-cholera%2C-yellow-and-dengue-fever [Google Scholar] [Crossref]

16. Ogwuche, J., Chang, C. A., Ige, O., Sagay, A. S., Chaplin, B., Kahansim, M. L., Paul, M., Elujoba, M., Imade, G., Kweashi, G., Dai, Y. C., Hsieh, S. C., Wang, W. K., Hamel, D. J., and Kanki, P. J. (2023). Arbovirus surveillance in pregnant women in north-central Nigeria, 2019-2022. Journal of clinical virology: the official publication of the Pan American Society for Clinical Virology, 169, 105616. [Google Scholar] [Crossref]

17. Okoror, L. E, Osanyinlusi S. A., Ukhureigbe O.M and Udenze, D. O.(2019). Prevalence of Dengue Virus Antibody among Residents of a Rural Community in Southwestern, Nigeria. Nigerian Journal of Microbiology, 33(1): 4512 - 4517 [Google Scholar] [Crossref]

18. Otu, A. A., Udoh, U. A., Ita, O. I., Hicks, J. P., Egbe, W. O., Walley, J. (2019) A cross-sectional survey on the seroprevalence of dengue fever in febrile patients attending health facilities in Cross River State, Nigeria. Plos One 14(4): e0215143. [Google Scholar] [Crossref]

19. Sharma P, Pavitra K, Shettigar S.. (2022). Trends in dengue virus infection with seasonal variation at a tertiary care centre, Mangaluru: a retrospective study. IP Intl J Med Microbiol Trop Dis. ;8:294–17. doi: 10.18231/j.ijmmtd.2022.057 [Google Scholar] [Crossref]

20. Wang, S., Liu, Y., Wang, Y., Zhou, L., & Liu, J. (2026). Global and regional burden of chikungunya from 2004 to 2024: a worldwide observational study. Journal of global health, 16, 04055. https://doi.org/10.7189/jogh.16.04055 [Google Scholar] [Crossref]

21. World Health Organization (2024). Dengue - Global situation. Retrieved from [Google Scholar] [Crossref]

22. https://www.who.int/emergencies/disease-outbreak-news/item/2024- [Google Scholar] [Crossref]

23. World Health Organization. (2025). https://www.who.int/news-room/fact-sheets/detail/chikungunya. Accessed on March 4, 2026 [Google Scholar] [Crossref]

24. World Health Organization. (2024). Weekly epidemiological record, 2024, vol. 99, 18 [full issue]. World Health Organization. https://iris.who.int/handle/10665/376641 [Google Scholar] [Crossref]

25. World Health Organization. Dengue and Severe Dengue: Fact Sheet. WHO, 2025. [Google Scholar] [Crossref]

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