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Effects of HIV-1 infection on malaria parasitemia in milo sub-location, western Kenya

Overview of attention for article published in BMC Research Notes, July 2015
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Title
Effects of HIV-1 infection on malaria parasitemia in milo sub-location, western Kenya
Published in
BMC Research Notes, July 2015
DOI 10.1186/s13104-015-1270-1
Pubmed ID
Authors

Erick Kipkoech Rutto, Joshua Nyagol, Julius Oyugi, Samson Ndege, Noel Onyango, Andrew Obala, Chrispinus J Simiyu, Gye Boor, Winfrida Chelangat Cheriro, Barasa Otsyula, Ben Estambale

Abstract

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. To determine the effects of HIV-1 infection on malaria parasitaemia among consented residents of Milo sub-location, Bungoma County in western Kenya. Census study evaluating malaria parasitaemia in asymptomatic individuals with unknown HIV-1 status. 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. 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. 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 20%
Student > Ph. D. Student 10 14%
Student > Bachelor 7 10%
Researcher 5 7%
Student > Postgraduate 5 7%
Other 12 17%
Unknown 18 25%
Readers by discipline Count As %
Medicine and Dentistry 27 38%
Nursing and Health Professions 6 8%
Agricultural and Biological Sciences 6 8%
Social Sciences 6 8%
Business, Management and Accounting 3 4%
Other 3 4%
Unknown 20 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 July 2015.
All research outputs
#20,283,046
of 22,817,213 outputs
Outputs from BMC Research Notes
#3,559
of 4,262 outputs
Outputs of similar age
#219,400
of 262,607 outputs
Outputs of similar age from BMC Research Notes
#75
of 96 outputs
Altmetric has tracked 22,817,213 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 262,607 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.