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dc.contributor.authorRutto, Erick K
dc.contributor.authorNyagol, Joshua
dc.contributor.authorOyugi, Julius
dc.contributor.authorNdege, Samson
dc.contributor.authorOnyango, Noel
dc.contributor.authorObala, Andrew
dc.contributor.authorSimiyu, Chrispinus J
dc.contributor.authorBoor, Gye
dc.contributor.authorCheriro, Winfrida C
dc.contributor.authorOtsyula, Barasa
dc.contributor.authorEstambale, Ben
dc.date.accessioned2015-08-07T15:17:46Z
dc.date.available2015-08-07T15:17:46Z
dc.date.issued2015-07-15
dc.identifier.citationBMC Research Notes. 2015 Jul 15;8(1):303
dc.identifier.urihttp://dx.doi.org/10.1186/s13104-015-1270-1
dc.identifier.urihttp://hdl.handle.net/11295/89661
dc.description.abstractAbstract Background Malaria and HIV infections are both highly prevalent in sub-Saharan Africa, with HIV-infected patients being at higher risk of acquiring malaria. HIV-1 infection is known to impair the immune response and may increase the incidence of clinical malaria. However, a positive association between HIV-1 and malaria parasitaemia is still evolving. Equally, the effect of malaria on HIV-1 disease stage has not been well established, but when fever and parasitemia are high, malaria may be associated with transient increases in HIV-1 viral load, and progression of HIV-1 asymptomatic disease phase to AIDS. Objective To determine the effects of HIV-1 infection on malaria parasitaemia among consented residents of Milo sub-location, Bungoma County in western Kenya. Study design Census study evaluating malaria parasitaemia in asymptomatic individuals with unknown HIV-1 status. Methods After ethical approvals from both Moi University and MTRH research ethics committees, data of 3,258 participants were retrieved from both Webuye health demographic surveillance system (WHDSS), and Academic Model Providing Access to Healthcare (AMPATH) in the year 2010. The current study was identifying only un-diagnosed HIV-1 individuals at the time the primary data was collected. The data was then analysed for significant statistical association for malaria parasitemia and HIV-1 infection, using SPSS version 19. Demographic characteristics such as age and sex were summarized as means and percentages, while relationship between malaria parasitaemia and HIV-1 (serostatus) was analyzed using Chi square. Results Age distribution for the 3,258 individuals ranged between 2 and 94 years, with a mean age of 26 years old. Females constituted 54.3%, while males were 45.8%. In terms of age distribution, 2–4 years old formed 15.1% of the study population, 5–9 years old were 8.8%, 10–14 years old were 8.6% while 15 years old and above were 67.5%. Of the 3,258 individuals whose data was eligible for analysis, 1.4% was newly diagnosed HIV-1 positive. Our findings showed a higher prevalence of malaria in children aged 2–10 years (73.4%), against the one reported in children in lake Victoria endemic region by the Kenya malaria indicator survey in the year 2010 (38.1%). There was no significant associations between the prevalence of asymptomatic malaria and HIV-1 status (p = 0.327). However, HIV-1/malaria co-infected individuals showed elevated mean malaria parasite density, compared to HIV-1 negative individuals, p = 0.002. Conclusion HIV-1 status was not found to have effect on malaria infection, but the mean malaria parsite density was significantly higher in HIV-1 positive than the HIV-1 negative population.
dc.titleEffects of HIV-1 infection on malaria parasitemia in milo sub-location, western Kenya
dc.typeJournal Article
dc.date.updated2015-08-07T15:17:46Z
dc.language.rfc3066en
dc.rights.holderRutto et al.


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