Malaria an opportunistic infection in HIV/AIDS patients? – A Nigerian experience

Background HIV and malaria interact at the level of the host’s susceptibility to infection, but little is known about the effect of HIV on malaria infection in Nigeria. Objective This study estimated the prevalence of malaria parasitaemia and its relationship with HIV immunodeficiency. Methods This cross-sectional study was conducted in two hospitals in Abuja, Nigeria between October 2012 and March 2013 among 600 respondents, comprising 200 HIV-negative controls, 200 HIV-positive patients on antiretroviral therapy (ART), and 200 HIV-positive patients not on ART. Malaria parasites, malaria density and absolute CD4 counts were carried out on all three groups. Participants with CD4 counts below 350 cells/mm3 were considered immunocompromised and likely to develop opportunistic infections. Results Most study participants were aged 21–40 years (65.2%). The mean CD4 counts of HIV-positive patients not on ART (300 ± 211 cells/mm3) and those on ART (354 cells/mm3) were significantly lower than among controls (834 cells/mm3) (p < 0.001). Malaria prevalence was not statistically different between the controls (44.5%), patients on ART (40.5%), and those not on ART (39.5%) (p = 0.562). Compared to 7% immunodeficiency among controls, 56% of patients on ART and 65.5% of those not on ART had a CD4 count < 350 cells/mm3 (p < 0.001). The prevalence of malaria parasitaemia among immunodeficient individuals (42.4%) was similar to prevalence among those with CD4 counts > 350 cells/mm3 (40.8%; p = 0.695). Conclusion These findings suggest that malaria parasitaemia is not an opportunistic infection among HIV-positive individuals in Nigeria.


Introduction
With about 14% of the world's population, sub-Saharan Africa is home to roughly 67% of all people living with HIV/AIDS. 1,2 On the other hand, the World Health Organization estimates that sub-Saharan Africa accounts for more than 90% of the worldwide burden of malaria. 3 As a result, any interaction between the two infections is expected to have a considerable impact on health in the region, particularly in countries like Nigeria, which now has the largest malaria burden in sub-Saharan Africa and ranks first among African countries affected by HIV/AIDS. 3 Opportunistic infections occur more frequently and with greater severity in individuals with compromised immune systems, such as those positive for HIV. 4 Opportunistic infections are less prevalent today than during the early stages of HIV and AIDS, owing to improved medications that reduce HIV viral load and strengthen the immune system. 5 However, many people living with HIV continue to develop opportunistic infections, because they are unaware of their HIV status, are not on treatment, or their treatment does not keep their viral load low enough for their immune system to fight infections. 6 The possible repercussions and public health impact of HIV and malaria's geographical overlap have been identified and explored in recent years. 5,7,8 The two diseases interact at the level of the host's susceptibility to infection. HIV infection increases the probability of clinical and severe malaria, while Plasmodium falciparum infection increases HIV viral load. 8,9 Additionally, dual infection has been found to contribute to the spread of both illnesses in sub-Saharan Africa, raising concerns about treating coinfected patients and the possibility of therapeutic interactions. 10 Because of the significant geographic and social overlap between people infected with HIV and malaria, complex interactions at the individual and group levels are possible. 11 Notably, any http://www.ajlmonline.org Open Access relationship between the two infections has the potential to have considerable public health implications due to their respective frequencies. 12 HIV infection may exacerbate malaria's burden by increasing susceptibility to infection or impairing antimalarial medications' preventative and therapeutic efficiency, as both are immune-mediated. 13 However, early 1990s investigations failed to reveal substantial interactions between malaria and HIV in coinfected children and adults who had acquired semiimmunity to malaria, probably due to research design problems and a lack of information about immunosuppression. 14 In the early 2000s, it was shown that HIV infection has a clinical effect on malaria infection and disease and that this effect appears to be reliant on the dynamics of malaria transmission and the degree of HIV-associated immunosuppression. 15,16 HIV-positive individuals who have not acquired immunity to malaria exhibit a significant increase in the severity of infection, in contrast to those who have naturally acquired immunity to malaria, for whom HIV infection is associated with just a mild rise in clinical disease. 17 Malaria has been identified as a risk factor for concurrent HIV infection at the population level in the recent past. 13 Studies have addressed the prevalence of asymptomatic malaria, 18,19 association between clinical malaria and immunosuppression among HIV-positive patients. 20 and effects of malaria infection on HIV-positive individuals in Nigeria, 4,18,19,21,22 but information on malaria as an opportunistic infection in HIV-positive individuals is scanty. As such, this study sought to estimate the prevalence of malaria parasitaemia and its relationship with HIV immunodeficiency among HIV-positive patients in Abuja, Nigeria.

Ethical considerations
This study received approval from the Federal Capital Territory Health Research Ethics Committee (FHREC) with approval number FHREC/2012/11/34/05-11-12 The study protocol was made clear to the participants, and their informed consent was obtained, both orally and in written forms, before recruiting them to the study. Information that could be traced to any of the respondents was not collected. Data obtained from the participants were treated confidentially and for research purposes only. HIV-negative individuals served as controls for the study.

Study design
Only HIV-positive and HIV-negative patients attending the two hospitals were included in the study; those who did not attend these hospitals were excluded.

Data collection
After consent was given and before being enrolled into the study, HIV tests were done for the control patients to determine that they were truly HIV-negative and for the HIV-positive patients not on ART to confirm they were truly HIV-positive.
HIV tests were not conducted on HIV-positive patients on ART, because we confirmed their status from the treatment case files retrieved from the hospitals. All participants were tested for the presence and density of malaria parasites and for CD4 count to assess their immune status. Age and gender were collected from patients' medical records.

Experimental procedures Collection of blood samples for HIV test
A 5 mL blood sample was collected into an ethylenediaminetetraacetic acid tube by the staff of the laboratory departments at both hospitals for all three tests: HIV test, malaria parasite examination and CD4 count.
Samples that could not be tested immediately were stored in a refrigerator at 2 °C -6 °C and tested within 48 h. Blood samples were tested at the same facility in which they were collected and were not transported to another facility.

Malaria parasite examination
One or two drops of venous blood were spread on a clean, dry slide to make a thick blood film. The film was allowed to air dry, and the slide was then fixed in 100% alcohol for approximately 30 min. The slide was then flooded with a fresh solution of 10% Giemsa stain (Merck KGaA, Darmstadt, Germany), freshly prepared in distilled water. The stain was allowed to remain for approximately 30 min. After 30 min, the slide was rinsed in tap water and allowed to air dry thoroughly. When the thick film was completely dried, a drop of oil immersion was applied to an area of the film which appeared mauve coloured (usually around the edges).
The oil was spread to cover about 10 mm in diameter to allow the film to be examined first at low magnification (Olympus microscope, New York Microscope Company, Hicksville, New York, United States). The area that was well stained but not too thick was selected. A 100X objective lens was used to examine malaria parasites and malaria pigments. At least 100 high power microscope fields were examined for parasites. The approximate numbers of parasites (trophozoites, schizonts and gametocytes) and whether malaria pigment was present in the white cells were reported, with the result being graded as either + (mild or moderate parasitaemia), ++ (severe parasitaemia) or +++ (very severe parasitaemia). When no malaria parasites were seen, the sample was reported as 'none seen'. 24

Estimating malaria parasites numbers (density)
A drop of immersion oil was placed on the stained slide and viewed under a 100× objective lens. Two hundred (200) leucocytes were counted while noting the number of malaria parasites (trophozoites and schizonts) present during the count. The number of parasites per microlitre was calculated using the formula: Where N = number of parasites counted; T = Assumed total white blood cell (leucocyte) count (usually 8000) in cells/μL, and L = Number of Leucocytes counted. 24

Estimation of CD4
The flow cytometer (Sysmex Partec's CyFlow™ Counter System, Sysmex, Kobe, Japan) was prepared for analysis, and the operating software was prepared for measurement. The sample tube was filled with prepared sample suspension (20 μL of CyFlow™ CD4 PE antibody plus 20 μL thoroughly mixed whole blood). The mixture was allowed to incubate in the dark for 15 min, mixing the sample every 5 min during incubation. Then 800 μL of CD4 buffer was added and mixed gently. The tube was filled not to more than 2/3 of its volume. The sample was inserted onto the sample port until a 'click' sound was heard. The sample was fully mounted within one second. The measurement (acquisition) started automatically; the operating software indicated the Prerun, Run and Count Status. In the Prerun phase, cells were quickly transported to the flow cuvette's analysis position; they were analysed and classified into histograms on real-time display in the run phase and counted for a given volume (in a cubic millilitre of blood) in the final stage. After the count phase, the acquisition finished automatically. The button end was clicked to complete the acquisition manually, or the sample tube was removed from the sample port. After each day run, 1.6 mL of cleaning fluid and 1.6 mL of sheath fluid were used for cleaning. 25

Data analysis
Data were collected and cleaned in Microsoft Excel (Microsoft Corp., Redmond, Washington, United States) before they were exported to IBM-SPSS Statistics for Windows (Version 25.0., released 2017; IBM, Armonk, New York, United States) for analysis. In the analyses, HIV-positive participants were categorised as being on ART or not on ART according to their self-reported status at the time of recruitment. Participants were categorised as immunodeficient if they had a CD4 count of less than 350 cells/mm 3 and were HIV-positive. The Chisquare test was used to compare malaria and immune suppression proportions in the study groups. Analysis of Variance was used to compare the mean CD4 counts in the study groups, using a 95% confidence level, and a p-value of less than 0.05 was considered significant.

Results
Most study participants were aged 21-40 years (65.2%) (  The prevalence of malaria parasitaemia among immunodeficient individuals was 42.4%, which was not significantly different (p = 0.695) from the 40.8% among those with a CD4 count of 350 cells/mm 3 and above (Table 3).
Most malaria cases across all groups were found within the group aged 21-40 years, including 52.8% of controls, 79.0% of HIV patients on ART, 75.9% of HIV-positive patients not on ART and 77.5% of all HIV-positive patients (p = 0.001) (Table 4)

Discussion
The mean CD4 count among our study controls was 834 cells/ mm 3 ; it was 354 cells/mm 3 among HIV-positive patients on ART, and 300 cells/mm 3 among HIV-positive patients not on ART, which shows that those HIV-positive patients not on ART were immunodeficient. Several studies have supported this finding, reporting how a CD4 count of less than 350 cells/ mm 3 makes a patient immunodeficient, elevating their chances of being susceptible to different diseases. 20,26 A study conducted in India reported that a lower CD4 count increases the chance of infection among HIV-positive children below the age of 14 years. 27 They found the prevalence of opportunistic infections in 90.91% of the HIV-positive patients with a CD4 count of less than 200 cells/mm 3 , 21.21% among those with a CD4 count between 200 and 349 cells/mm 3 , and 23.81% among those with a CD4 count of 350 cells/mm 3 -499 cells/mm 3 , while patients with CD4 counts < 500 cells/ mm 3 had the least amount of infection (11.43%). 27 This finding may also explain why HIV clients not on ART with a CD4 count of less than 350 cells/mm 3 had a higher percentage of immunodeficiency.
However, with a lowered immunity (lower mean CD4 count) among HIV-positive patients on ART and those not on ART, one would ordinarily expect a higher prevalence of malaria parasitaemia in these groups, but this was not the case in our study. The study found that malaria prevalence was higher among controls and HIV-positive patients on ART, which might be explained by various factors, including the number of respondents in each group. Additionally, genotype may play a role, as it has previously been reported that individuals with AA genotype are more susceptible to malaria. 28 This claim was further substantiated by stating that malaria parasites do not thrive in individuals with sickle cell trait, since haemoglobin 'S' is known to inhibit the growth and reproduction of malaria parasites, which may explain the finding of a higher percentage of controls have the AA genotype. 28 ART may also potentially impact an individual's vulnerability, as studies have shown that it is less effective against the asexual ring stages of P. falciparum in the blood. 29,30    The prevalence of parasitaemia was not significantly higher among the group that was both HIV-positive and immunodeficient than in the negative group, which shows malaria is not an opportunistic infection in HIV-positive individuals. The study also found that most respondents who tested positive for malaria in all groups were between 21 and 40 years. A study conducted in Southwest Ethiopia also reported that malaria was more prevalent among HIVpositive individuals within a similar age range (25-34 years). 31 Studies in Jos, Nigeria, 4 Europe, 6 and Beira, Mozambique 22 have similarly reported that the prevalence of parasitaemia among HIV patients is usually among this age group. On the other hand, studies conducted on the mainland of Tanzania 32 and in Nankoma, Uganda 33 dispute this finding, indicating that the occurrence is typically highest among those under the age of 20, while another in Cross River State, Nigeria discovered that age has no bearing on this. 18

Limitations
Abuja is the central area of study, which may not fully represent Nigeria. Notwithstanding, the findings of the study are relevant to the Nigeria situation since the study areas is the capital city of Nigeria where people from different geopolitical regions reside.

Conclusion
This study reported immunodeficiency as a CD4 count of less than 350 cells/mm 3 . However, this did not have a statistically significant influence on the presence of malaria parasites in the blood of HIV-positive individuals. HIV-positive patients on ART and controls still recorded high rates of malaria. Therefore, these findings suggest that malaria parasitaemia is not an opportunistic infection among HIV-positive patients in Abuja, nor is malaria parasitaemia more common in HIV infection in Nigeria.