Abstract
Introduction
Globally, malaria in pregnancy is a public health challenge. Malaria and HIV are among the two most important diseases contributing to the global health burden of our time. HIV positive pregnant women are at increased risk of all the adverse outcomes of malaria in pregnancy.
Objective
The objective of this study was to compare malaria parasitaemia between HIV positive and HIV negative pregnant women attending antenatal clinics offering Preventing Maternal to Child Transmission (PMTCT) services in Enugu metropolis, south-eastern Nigeria.
Methods
A descriptive cross sectional study was conducted among 200 HIV positive and 200 HIV negative pregnant women attending antenatal clinics in Enugu. Two out of five hospitals that provide PMTCT services were selected through balloting. Finger pricked blood samples were collected and thick blood films were examined for malaria parasite using giemsa expert microscopy. A structured interviewer administered questionnaire was used for data collection. Data was analysed using SPSS version 22.
Results
The HIV positive pregnant women (152) (76%) and HIV negative women (137) (68.5%) studied were mostly in the age range of 25–34 years. Mean gestational age of HIV positive and HIV negative participants were 23.4±10.7 and 23.2±10.1 weeks respectively (P=0.001). The prevalence of malaria infection among HIV positive pregnant mothers was 81% (162/200) and 75% (150/200) among HIV negative pregnant women (P < 0.001). The HIV positive mothers had more moderate parasitaemia (86/200: 53.1%) compared to 43/200: 28.7% in HIV negative mothers (P<0.001). Even though more HIV positive mothers (54.5%) used insecticide treated nets ITNs during pregnancy compared to 41.5% in HIV negative mothers, moderate malaria parasitaemia was higher in HIV positive mothers. HIV positive nulliparous pregnant women had the highest rate of malaria parasitaemia (32/36: 88.9%).
Conclusion
Moderate malaria parasitaemia was higher among HIV positive pregnant women. All malaria preventive strategies should be intensified in pregnancy as ITNs provided little protection.
Keywords: Malaria parasitaemia, HIV, pregnant women, Enugu, Nigeria
Introduction
Malaria in pregnancy, especially among HIV positive pregnant mothers, is a major cause of morbidity and mortality in sub-Saharan Africa. Malaria infection during pregnancy is indeed a major public health challenge in tropical and subtropical regions throughout the world1. Studies have established that malaria and HIV are among the two most important diseases contributing to the global health burden of our time and, together, they cause more than 4 million deaths every year2,3. Nearly 40% of the world's population lives in infected regions4. Every year, approximately 50 million women become pregnant in malaria endemic regions.5 Approximately 1 million are estimated to be infected with both malaria and HIV which are preventable, and responsible for serious maternal and neonatal morbidity5. Malaria transmission is intense and occurs all year round in Nigeria6. It has been shown that at least 3 million pregnancies occur among women in malarious areas of Africa, most of whom reside in areas of relatively stable malaria transmission6. A good number of HIV infected individuals live in regions with different levels of malaria transmission7. Several studies have reported that malaria is a major public health problem affecting 300–500 million people annually8,9. It is also a major cause of maternal and infant morbidity and mortality in sub-Saharan Africa10,11.
Much work has been done to show the relationship between malaria and HIV in pregnancy. Some studies among pregnant women in Sub-Saharan Africa have provided evidence of an important public health problem arising from the interaction of HIV and malaria. A study in Ibadan, south western Nigeria, revealed that HIV positive pregnant women had higher malaria parasite levels than those not infected with HIV12. This result was confirmed by another study in Abakaliki, south-eastern Nigeria13. In addition, data from Malawi suggested that infants exposed to both placental malaria and maternal HIV infection have a 3–8 fold increased risk for post neonatal death higher than infants born to mothers with either infection alone14.
Some economists have estimated that the Gross Domestic Product (GDP) of African governments is reduced by $12 billion annually as a result of malaria infection2. It has also been estimated that up to 132 billion naira is spent each year on malaria treatment in Nigeria11. Although over-a-century of work to control or eradicate malaria has been done, more work needs to be done to examine the effects and public health implications of malaria and HIV in pregnancy15. In malaria endemic areas, including Enugu State, malaria may account for up to 15% of maternal anaemia and 5–14% of Low Birth weight (LBW)16. Anaemia due to malaria causes up to 10,000 maternal deaths each year16. Available data indicates that Enugu State has very high maternal mortality with figures ranging from 772 to 998 per 100,00017,18. This is almost thrice the figure (286/100,000) reported for the entire southeast zone, and almost double the 545/100,000 national averages for the seven years period preceding the 2008 National Demographic and Health Survey19.
At present, maternal mortality ratio in Enugu State approximates close to the national ratio of 1,000 maternal deaths per 100,000 live births19. Malaria and anaemia in pregnancy, amongst other causes, have been seriously associated with this high rate of maternal deaths19. Several studies have documented evidence that HIV impairs malaria immunity among pregnant women, because pregnant women infected with HIV demonstrate more frequent and higher density parasitaemia than pregnant women not infected with HIV20–23. The aim of this research was to compare malaria parasitaemia between HIV positive and HIV negative pregnant women attending antenatal clinics offering PMTCT services in Enugu metropolis, south-eastern Nigeria.
Materials And Methods
Study area
Enugu State is one of the six states in the south eastern part of Nigeria. It shares boundaries with Anambra, Abia, Kogi, Benue and Ebonyi States. The 2006 census recorded its population as 1,596,042 males and 1,671,795 females24. Enugu State has rich agricultural land because of its location within the tropical forest and savannah belts.
Study design and sampling technique
A simple random sampling technique, balloting, was used to select two from the five hospitals with maternal health services that offered PMTCT services in Enugu metropolis. The sample constituted 400 pregnant women that were consecutively selected during their registration exercise (booking) from the antenatal register. There were 200 HIV positive and 200 HIV negative pregnant women who were selected and those who consented were recruited for the study. Sample size was calculated using a formula for calculating sample size from a finite population using a previous prevalence of malaria infection in HIV positive pregnant women12. Any woman that did not give consent was replaced with the next consenting woman.
Specimen collection and data collection
Finger pricked blood samples were collected and thick blood films were made. The films were examined for malaria parasite using Giemsa expert microscopy. The socio-demographic data of respondents were collected using a structured interviewer administered questionnaire. HIV status was determined from the blood test results retrieved from the respondent's folders.
Data analysis
Data collected was analysed using SPSS version 17 (SPSS Inc, Chicago, Illinois, USA). Relationship of various variables and Chi-square was used to determine significance at p<0.05. Mild parasitaemia refers to levels of 1–999 mp/ml, moderate refers to 1000–9999 mp/ml, and high refers to >10,000 mp/ml. The parameters considered in the analysis included age, gestational age, parity and gravidity.
Ethical approval
Ethical approval was obtained from the Health Research Ethics Committees of the University of Nigeria Teaching Hospital and Annunciation Specialist Hospital, Enugu. Informed written consent was obtained from the participants.
Results
Socio-demographic characteristics of the study population
Table 1 shows the age range of HIV positive pregnant women and negative women who were enrolled for the study. Above half (106) (53%) had secondary education and 64 (32%) had tertiary education amongst the HIV positive women, whereas 92 (46%) and 74 (37.0%) had tertiary and secondary education, respectively, among the HIV negative women. Majority of the respondents were married, 188 (94%) and 190 (95%) for HIV positive and HIV negative mothers respectively. Occupations included trading (103) (51.5%) and civil service (34) (17%). Among the HIV positive respondents, 18% (36/200) were primigravidae, 38% (76/200) were secundigravidae and 44% (88/200) were multigravidae. Some of the mothers (23%) (46/200) were in their first trimester, 37% (74/200) in the second trimesters, while the remaining 40.5% (80/200) were in their last trimester. The parity revealed that 18% (36/200) of the HIV positive women were nullipara (had no children at the time of pregnancy), 31% (62/200) had one child and majority of them, 51% (102/200), had given birth to two or more children (multipara). In the HIV negative population, 20.5%, 40% and 39.5% were in the first, second and third trimester respectively. Primigravidae constituted 12%, secundigravidae were 32% and multigravidae constituted 56% of the mothers. Concerning parity, 33.5%, 23.0% and 43.5% were nullipara, primipara and multipara respectively.
Table 1.
Socio-demographic characteristics of HIV positive and HIV negative work participants
| Variables | Categories | HIV Positive | HIV Negative | ||
| N | % | N | % | ||
| Age Group (Years) |
15–19 | 0 | 0 | 2 | 1.0 |
| 20–24 | 14 | 7.0 | 26 | 13.0 | |
| 25–29 | 66 | 33.0 | 74 | 37.0 | |
| 30–34 | 86 | 43.0 | 63 | 31.5 | |
| 35–39 | 26 | 13.0 | 25 | 12.5 | |
| 40–44 | 8 | 4.0 | 10 | 5.0 | |
| Education Level |
None | 4 | 2.0 | 3 | 1.5 |
| Primary | 26 | 13.0 | 31 | 15.5 | |
| Secondary | 106 | 53.0 | 74 | 37.0 | |
| Tertiary | 64 | 32.0 | 92 | 46.0 | |
| Marital Status |
Single | 2 | 1.0 | 2 | 1.0 |
| Married | 188 | 94.0 | 190 | 95.0 | |
| Widowed | 10 | 5.0 | 8 | 4.0 | |
| Occupation | Civil servants | 34 | 17.0 | 41 | 20.5 |
| Teachers | 18 | 9.0 | 5 | 2.5 | |
| Traders | 103 | 51.5 | 71 | 35.5 | |
| Health workers | 13 | 6.5 | 16 | 8.0 | |
| House wives | 21 | 10.5 | 3 | 1.5 | |
| Others | 11 | 5.5 | 61 | 30.5 | |
| Trimester | 1st | 46 | 23.0 | 41 | 20.5 |
| 2nd | 74 | 37.0 | 80 | 40.0 | |
| 3rd | 80 | 40.5 | 79 | 39.5 | |
| Gravidity | Primigravidae | 36 | 18.0 | 24 | 12.0 |
| Secundigravidae | 76 | 38.0 | 64 | 32.0 | |
| Multigravidae | 88 | 44.0 | 102 | 56.0 | |
| Parity | Nullipara | 36 | 18.0 | 67 | 33.5 |
| Primipara | 62 | 31.0 | 46 | 23.0 | |
| Multipara | 102 | 51.0 | 87 | 43.5 | |
Gestational age and CD4 counts of the study population
Table 2 shows that the mean gestational age was 23.4±10.7 weeks for HIV positive women and 23.2±10.1 weeks for HIV negative pregnant women. Among the HIV positive women 64 (32%) had CD4 levels of ≤250 cells/mm3 and 136 (68%) of the pregnant women had CD4 levels ≥250 cells/mm3.
Table 2.
Relationship of some variables with HIV positive and negative participants
| Variables | HIV Positive =200 | HIV Negative N=200 | P-value |
| Age(years) Mean ± Sd | 37±6.1 | 35.6±5.4 | 0.001 |
| Gestational age in months | 5.4±2.48 | 5.38±2.34 | 0.001 |
| PCV (%) mean± SD | 35.34±3.78 | 28±3.2 | 0.005 |
| CD4 Levels | |||
| ≤250 cells/mm3 | 64 (32.0%) | N/A | |
| >250 cells/mm3 | 136(68.0%) | N/A | |
| Total | 200 | 200 |
Malaria parasitaemia in the study population
Figure 1 shows that the prevalence of malaria infection for HIV positive pregnant women was 81% (162/200) and 75% (150/200) for HIV negative pregnant women. Table 3 shows that out of the 162 HIV positive pregnant women with parasitaemia, 76/162 (46.9%) had mild (1–999/uL) infection, 86/162 (53.1%) had moderate (1000–9999/uL) malaria infection and none of the women had high malaria parasitaemia. Among the HIV negative women, 107/150 (71.3%) had mild parasitaemia, 43/150(28.7%) had moderate and 50/150 (25%) no parasites seen and none had severe parasitaemia. There was a highly significant difference in degree of parasitaemia between HIV positive and HIV negative women.
Figure 1.
Prevalence of Malaria infection in HIV positive and HIV negative pregnant women
Table 3.
Malaria Parasitaemia among HIV Positive and HIV Negative participants
| Malaria Parasite (MP) | HIV Positive n % | HIV Negativen % | P-Value | ||
| Not seen | 38 | 19.0 | 50 | 25.0 | P<0.001 |
| Mild (1–999) | 76 | 46.9 | 107 | 71.3 | |
| Moderate (1000–9999) |
86 | 53.1 | 43 | 28.7 | |
| High | 0 | 0 | 0 | 0 | |
Relationship between malaria prevalence and gravidity, trimester and parity
Table 4 shows that among HIV positive pregnant women, the multigravidae were found to have the highest malaria prevalence with 76/88 (86.4%); while the primigravidae had the least malaria prevalence, 22/36 (61.1%). Women in their third trimester were mostly affected (79/80:98.8%) while those in their first trimester had the least prevalence (26/46:56.5%). The distribution of malaria among different parity groups showed that nullipara (32/36: 88.9%) were more affected than the multipara (46/102: 45.1%).
Table 4.
Relationship between factors and prevalence of malaria among HIV positive participants
| Category | Variables | No Examined N |
No Malaria Seen |
Mild Infection | Moderate Infection |
Total Malaria Prevalence |
P-Value | ||||
| N | % | N | % | N | % | N | % | ||||
| Trimester | 1st | 46 | 20(43.5) | 16(61.5 | 10(38.5) | 26(56.5%) | |||||
| 2nd | 74 | 17(22.9) | 25(43.9) | 32(56.1) | 57(77.0%) | <0.0001 | |||||
| 3rd | 80 | 1(1.3) | 45(57.0) | 34(43.0) | 79(98.8%) | ||||||
| Parity | Nullipara | 36 | 4 | 11.2 | 16 | 44.4 | 16 | 44.4 | 32 | 88.8 | < 0.0001 |
| Primipara | 62 | 12 | 19.4 | 29 | 46.8 | 21 | 33.8 | 50 | 80.6 | ||
| Multipara | 102 | 56 | 54.9 | 20 | 19.6 | 26 | 25.5 | 46 | 45.1 | ||
| Gravidity | Primigravidae | 36 | 14 | 38.9 | 14 | 38.9 | 8 | 22.2 | 22 | 61.1 | < 0.05 |
| Secundigravidae | 76 | 12 | 15.8 | 36 | 47.4 | 28 | 36.8 | 64 | 84.0 | ||
| Multigravidae | 88 | 12 | 13.6 | 36 | 40.9 | 40 | 45.5 | 76 | 86.4 | ||
| CD4 Count | ≤250 Cells/mm3 | 64 | 16 | 25.0 | 24 | 37.5 | 24 | 37.5 | 48 | 75.0 | < 0.0001 |
| >250 cells/mm3 | 136 | 22 | 16.2 | 60 | 44.1 | 54 | 39.7 | 114 | 83.8 | ||
| Age grp(years) | 15–19 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | <0.005 |
| 20–24 | 14 | 4 | 28.6 | 4 | 28.6 | 6 | 42.8 | 10 | 71.4 | ||
| 25–29 | 66 | 16 | 24.2 | 32 | 48.5 | 18 | 27.3 | 50 | 75.8 | ||
| 30–34 | 86 | 10 | 11.6 | 34 | 39.5 | 42 | 48.9 | 76 | 88.4 | ||
| 35–39 | 26 | 4 | 15.4 | 12 | 46.2 | 10 | 38.4 | 22 | 84.6 | ||
| 40–44 | 8 | 4 | 50.0 | 4 | 50.0 | 0 | 0 | 5 | 62.5 | ||
| Educational Level |
None | 4 | 0 | 0 | 2 | 50.0 | 2 | 50.0 | 4 | 100 | <0.0001 |
| Primary | 26 | 6 | 23.0 | 10 | 38.5 | 10 | 38.5 | 20 | 76.9 | ||
| Secondary | 106 | 28 | 26.4 | 50 | 47.2 | 28 | 26.4 | 78 | 73.6 | ||
| Tertiary | 64 | 4 | 6.3 | 24 | 37.5 | 36 | 56.2 | 60 | 93.8 | ||
In their HIV negative counterparts (Table 5), multigravidae had the least malaria parasitaemia (66/92: 71.7%) with the primigravidae and secundigravidae following closely with 38/49: 77.6% and 46/59:78% respectively. HIV negative women in their first trimester had the highest malaria parasitaemia with 35/41:85% Tables 4 and 5 show that the distribution of malaria among HIV positive pregnant women was higher at all levels compared to HIV negative pregnant women. Malaria prevalence was higher among HIV positive pregnant women that were Secundigravidae (84.0%) and Multigravidae (86.4%) compared to HIV negative women (78.0%) and 71.1% at the same gravid levels respectively. The prevalence among the primigravidae that were HIV negative was 77.6% compared with the HIV positive group at the same gravida level (61.1%). More of the HIV negative women had mild infection compared to HIV positive pregnant women. The difference in the distribution of malaria among the two groups was statistically significant (P<0.05). The highest malaria prevalence among HIV infected pregnant women occurred between the ages of 30 – 34years (88.4%), while the least occurred between the age of 15 to 19 years. The differences in the result of this distribution was statistically significant (P<0.05). Few women with no formal education (4) participated among the HIV positive mothers and scored the highest malaria prevalence (100%) and the least malaria prevalence was found among those with secondary and primary education. Pregnant women with tertiary education recorded high malaria prevalence for both HIV positive and HIV negative group (93.8% and 82.6% respectively), with HIV positive pregnant women having more. The trimester related prevalence result of HIV positive pregnant women compared to HIV negative women shows that HIV positive women had the highest level of malaria prevalence at all trimester levels (78.3%, 77.0% and 86.3%) compared to HIV negative women (85.4%, 71.3%, 73.4%). The difference in the distribution of malaria among the two groups was statistically significant (P<0.05). The parity related prevalence result of HIV positive pregnant women compared to HIV negative women shows that HIV positive women had the highest level of malaria prevalence at all parity levels (nullipara (88.9%), primipara (80.4%_ and multipara(81.0%) compared to HIV negative mothers (nullipara (71.6%), primipara (76.1%) and multipara (77.0%). Among HIV positive pregnant women, the nullipara groups had the highest malaria prevalence (88.9%) whereas among the HIV negative groups, the multipara had the highest malaria prevalence rate of (77%). The difference in the distribution of malaria among the two groups was statistically significant (P<0.05). Table 6 shows that both HIV positive and negative mothers that use ITNs had lower levels of parasetaemia (75.5% and 73.6%) compared to those that did not use ITNs (89.4% and 89.4%). This was found to be statistically significant (P<0.05).
Table 5.
Relationship of factors and Prevalence of Malaria among HIV Negative participants
| Category | Variables | No Examined N |
No Malaria Seen |
Mild Infection | Moderate Infection |
Total Malaria Prevalence |
P-Value | ||||
| N | % | N | % | N | % | N | % | ||||
| Parity | Nulipara | 67 | 19 | 41.3 | 33 | 71.7 | 15 | 32.6 | 48 | 71.6 | <0.0001 |
| Primipara | 46 | 11 | 16.4 | 26 | 38.8 | 9 | 13.4 | 35 | 76.1 | ||
| Multipara | 87 | 20 | 23.0 | 50 | 57.5 | 17 | 19.5 | 67 | 77.0 | ||
| Gravidity | Primigravidae | 49 | 11 | 22.4 | 27 | 71.1 | 11 | 28.9 | 38 | 77.6 | |
| Secungravidae | 59 | 13 | 22.0 | 29 | 63.0 | 17 | 37.0 | 46 | 78.0 | ||
| Multigravidae | 92 | 26 | 28.3 | 51 | 77.3 | 15 | 22.7 | 66 | 71.7 | ||
| Age grp(Yrs) | 15–19 | 2 | 0 | 0.0 | 0 | 0.0 | 2 | 100.0 | 2 | 100.0 | |
| 20–24 | 26 | 5 | 19.2 | 13 | 61.9 | 8 | 38.1 | 21 | 80.8 | ||
| 25–29 | 74 | 25 | 33.8 | 40 | 81.6 | 9 | 18.4 | 49 | 66.2 | ||
| 30–34 | 63 | 12 | 19.0 | 35 | 68.6 | 16 | 31.4 | 51 | 81.0 | ||
| 35–39 | 25 | 3 | 12.0 | 14 | 63.6 | 8 | 36.4 | 22 | 88.0 | ||
| 40–44 | 10 | 5 | 50.0 | 5 | 100. | 0 | 0.0 | 5 | 50.0 | ||
| Educational Level |
None | 0 | 0 | 0 | 0 | 0 | |||||
| Primary | 34 | 14 | 45.2 | 14 | 41.2 | 6 | 35.3 | 17 | 54.8 | ||
| Secondary | 74 | 20. | 27.0 | 38 | 70.4 | 16 | 29.6 | 54 | 73.0 | ||
| Tertiary | 92 | 16 | 17.4 | 55 | 72.4 | 21 | 27.6 | 6 | 82.6 | ||
Table 6.
Use of ITNs and parasitaemia among HIV positive and negative participants
| ITN use | ITN non-use | |||
| HIV status | Frequency (%) | Frequency (%) | X2 | P value |
| Positive | 80 (75.5) | 84 (89.4) | 6.512 | 0.016 |
| Negative | 78 (73.6) | 84 (89.4) | 8.058 | 0.006 |
Discussion
Malaria parasitaemia was mostly mild to moderate in both HIV positive and HIV negative pregnant mothers. This prevalence agrees with results of a study Olusi and Abe where prevalence of malaria in pregnant women was found to be 96.92%, with majority (93.17%) infected with low parasitaemia25. Similarly, Cameroon recorded high malaria prevalence of 86.5%.26 This prevalence differs from findings in a previous study in Enugu that documented only 49.83% of HIV positive pregnant women with malaria27. Our study revealed a statistically significant difference concerning distribution of malaria parasitaemia density among HIV positive pregnant mothers and their HIV negative counterparts (P<0.05). Some studies have reported that HIV and AIDS causes immunosuppression thereby reducing the overall immune response to malaria parasitaemia, thus increasing the frequency of clinical attacks of malaria28. This agrees with previous studies carried out in southeastern and southwestern Nigeria where susceptibility to malaria among HIV positive mothers was higher than HIV negative mothers29. In this study, the HIV negative pregnant mothers had more mild malaria infection than HIV positive mothers. However, moderate malaria infection was more in HIV positive mothers. The result of these differences in malaria density was statistically significant (P<0.05). No high malaria prevalence was recorded among both HIV positive and HIV negative mothers (i.e. Parasite Density = 10,000/uL). However, a recent study in rural areas of southeast Nigeria reported cases of high malaria prevalence in contrast to this study26. A possible factor could be that the national guideline recommends cotrimoxazole for HIV positive pregnant mothers and intermittent preventive therapy (IPTp) for HIV negative pregnant mothers which has been documented to avert severe malaria attacks among pregnant mothers30. Some studies have generally reported HIV as a major risk factor for malaria transmission in pregnancy, and have also reported HIV in pregnancy as a double burden for high malaria parasitaemic density in pregnancy due to immmunosuppression28. There was a statistically significant difference (P<0.05) between the HIV positive and negative mothers that used ITNs for the prevention of malaria. More HIV positive mothers used ITNs compared with the HIV negative mothers even though the HIV positive mothers had a higher prevalence of malaria infection. Those women that used ITNs were less infected than those who did not. This difference could probably be due to the pre-existing health condition that influenced better health practices.
The age related distribution of malaria parasitaemia showed that malaria prevalence was higher in women of age group 40–44 years and least prevalent among the 25–29 age range group in the HIV positive pregnant mothers. Our study found that the age group of 15–19 years among the HIV negative mothers had 100% malaria prevalence. Education should have a positive influence on malaria prevention substantiated by the fact that a previous study revealed that participants who satisfactorily responded to the questions about malaria transmission and prevention were less affected by malaria as compared to those who had a poor knowledge31. Surprisingly, pregnant mothers with tertiary education recorded high malaria prevalence for both HIV positive and negative mothers in this study. In addition, this study observed that the illiterate pregnant women had the highest rate of malaria probably because they were more exposed to malaria parasite due to bad environmental condition and their lifestyles31. The parity related prevalence showed that HIV positive mothers who had not given birth before (nullipara) had the highest malaria prevalence while the pregnant mothers with two children and above (multipara) had the least malaria prevalence. At all parity levels, malaria prevalence was higher among HIV positive mothers compared to HIV negative mothers where the multipara group had the highest prevalence. This is consistent with findings from another study by Rogerson et al, where significant differences were seen among parity groups32. In our study, the multigravidae had the highest malaria prevalence while primigravidae had the least malaria prevalence among HIV positive mothers. On the other hand, among the HIV negative pregnant mothers, primigravidae had the highest malaria prevalence, (77.6%). This is consistent with a study that showed that among the HIV negative mothers, the primigravidae are more susceptible to high malaria prevalence33. The drug related malaria distribution showed that majority of the HIV positive pregnant mothers, 128(64%), did not take antimalaria therapy which can also be strongly linked to the reason for high malaria prevalence in this study. One of the most important factors for these observed differences in malaria parasitaemia among HIV positive and negative patients could be explained by the fact that HIV pregnant mothers have a compromised immunity due to low CD4 level. The immunosuppression caused by HIV virus leads to high malaria prevalence as has been documented34. From this study, it was obvious that women who used ITNs were less infected than women who did not. Studies have strongly supported and concluded on the fact that ITNs coverage was related to malaria control, has significantly reduced malaria and was associated with a malaria risk-protective effect28.
Limitations of the study
The limitation of this study includes the fact that populations not visiting a hospital were not included in the study.
Conclusion
In this study, moderate malaria parasitaemia was commoner among HIV positive pregnant mothers than among HIV negative andITNs provided little protection against malaria in pregnancy among HIV positive pregnant mothers. It is therefore recommended that all malaria preventive strategies should be intensified in pregnancy especially among HIV positive women.
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