Epidemiology of Malaria in Bauchi North, Bauchi State Nigeria: Prevalence and Determinants of the Infection
DOI:
https://doi.org/10.56919/usci.2541.025Keywords:
Malaria prevalence, Risk factors, Bauchi North, Socioeconomic impact, Environmental determinantsAbstract
Study’s Excerpt:
• The study assessed malaria prevalence and risk factors in Bauchi North, Bauchi State, Nigeria.
• Microscopy detected the parasite, while structured questionnaires identified infection determinants.
• Results showed a high malaria burden with variations by age and socioeconomic status.
• Findings highlight the need for public health interventions targeting high-risk, vulnerable groups.
• Findings can guide policymakers in malaria treatment, control, and prevention efforts.
Full Abstract:
Malaria remains a leading public health concern globally, particularly in sub-Saharan Africa, with Nigeria bearing a significant burden of the disease. This cross-sectional study aimed to assess malaria prevalence and associated risk factors among patients attending healthcare facilities in Bauchi North, Bauchi State, Nigeria. A total of 300 patients suspected of having malaria were enrolled, and blood samples were analyzed using microscopy of thick blood film stained with Giemsa’s stain. The presence of gametocytes, trophozoites, or schizonts, which stained dark blue, indicated positive results. Structured questionnaires were administered to collect demographic and risk factor data. The overall prevalence of malaria was 40%, with higher prevalence rates among females (27%) compared to males (13%) and among adults aged 25–64 years (24%). Rural residents (29.67%), individuals from low-income families (20.67%), and those exposed to poor housing and environmental conditions exhibited higher prevalence rates. The key risk factors assessed included residence of the patients, use of a net, and socioeconomic status, among which a history of fever within two weeks prior to the study (p = 0.006) was the only statistically significant risk factor associated with malaria at p < 0.05. Logistic regression analysis confirmed fever history as the primary predictor of malaria (COR = 0.438, 95% CI = 0.242–0.792). These findings highlighted the need for targeted malaria control interventions focusing on high-risk groups and environmental management. Strengthened public health campaigns are essential to improve awareness of the danger of malaria, its modes of transmission, infection agents, and preventive measures in underserved areas.
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