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Keywords:

  • HIV ;
  • genital schistosomiasis;
  • sub-Saharan Africa;
  • Schistosoma haematobium ;
  • Schistosoma mansoni ;
  • regression analysis

Abstract

  1. Top of page
  2. AbstractSummary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Objective

Epidemiological studies have observed that genital schistosomiasis increases the risk of HIV infection in Africa. We analysed the correlation between Schistosoma haematobium prevalence and HIV prevalence across sub-Saharan African countries.

Design

Regression analysis of prevalence of HIV and S. haematobium across sub-Saharan African countries.

Methods

Using compiled country-level S. haematobium prevalence, HIV prevalence and other demographic and economic data from published sources, we applied univariate and multivariate regression models to assess the correlations between S. haematobium prevalence and HIV prevalence while controlling for risk factors associated with each infection.

Results

In 43 sub-Saharan African countries, the mean prevalence of S. haematobium was 22.4% [standard deviation (SD): 9.8%] and for HIV was 6.21% (SD: 5.71%). In multivariate analysis, adjusted for prevalence of male circumcision, years since a country's first HIV/AIDS diagnosis, geographical region and immunization coverage, each S. haematobium infection per 100 individuals was associated with a 2.9% (95% CI: 0.2–5.8%) relative increase in HIV prevalence. Shaematobium was not associated with Schistosoma mansoni, HSV-2, hepatitis C, malaria or syphilis.

Conclusions

Schistosoma haematobium prevalence was associated with HIV prevalence in sub-Saharan Africa. Controlling S. haematobium may be an effective means of reducing HIV transmission in sub-Saharan Africa.

Objectif

Des études épidémiologiques ont observé que la schistosomiase génitale augmente le risque d'infection par le VIH en Afrique. Nous avons analysé la corrélation entre la prévalence de S. haematobium et celle du VIH dans des pays d'Afrique subsaharienne.

Méthodes

En utilisant la prévalence compilée de S. haematobium à l’échelle du pays, celle du VIH et d'autres données démographiques et économiques provenant de sources publiées, nous avons appliqué des modèles de régression univariée et multivariée afin d’évaluer les corrélations entre la prévalence de S. haematobium et celle du VIH tout en ajustant les facteurs de risque associés à chaque infection.

Résultats

Dans 43 pays d'Afrique subsaharienne, la prévalence moyenne de S. haematobium était de 22,4% [déviation standard (DS): 9,8%] et pour le VIH, 6,21% (DS: 5,71%). Dans l'analyse multivariée, ajustée pour la prévalence de la circoncision masculine, l'année depuis le premier diagnostic du VIH/SIDA dans le pays, la région géographique et la couverture vaccinale, chaque infection par S. haematobium pour 100 individus a été associée à 2.9% (IC95%: 0,2-5,8%) d'augmentation relative de la prévalence du VIH. S. haematobium n’était pas associée à S. mansoni, au HSV-2, à l'hépatite C, au paludisme ni à la syphilis.

Conclusions

La prévalence de S. haematobium était associée à celle du VIH en Afrique subsaharienne. La lutte contre S. haematobium pourrait être un moyen efficace de réduire la transmission du VIH en Afrique subsaharienne.

Summary

Objetivo

En estudios epidemiológicos se ha observado que la esquistosomiaisis genital aumenta el riesgo de infección por VIH en África. Hemos analizado la correlación entre la prevalencia de S. haematobium y de VIH en países de África subsahariana.

Métodos

Utilizando prevalencias de S. haematobium, prevalencia de VIH, y otros datos demográficos y económicos de fuentes públicas recopiladas a nivel del país, hemos aplicado modelos de regresión univariada y multivariada para evaluar las correlaciones entre la prevalencia de S. haematobium y la prevalencia de VIH controlando para factores de riesgo asociados con cada infección.

Resultados

En 43 países del África subsahariana, la prevalencia media de S. haematobium era del 22.4% [desviación estándar (DS): 9.8%] y para VIH del 6.21% (DS: 5.71%). En un análisis multivariado, ajustado para la prevalencia de circuncisión masculina, los años desde el primer diagnóstico de VIH/SIDA en el pais, la región geográfica y la cobertura vacunal, cada infección por S. haematobium por cada 100 individuos estaba asociada con un aumento relativo del 2.9% (95% CI: 0.2–5.8%) en la prevalencia de VIH.

S. haematobium no estaba asociado con S. mansoni, HSV-2, Hepatitis C, malaria o sífilis.

Conclusiones

La prevalencia de S. haematobium estaba asociada con la prevalencia de VIH en África subsahariana. Controlar a S. haematobium podría ser una forma efectiva de reducir la transmisión del VIH en África subsahariana.


Introduction

  1. Top of page
  2. AbstractSummary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Schistosoma haematobium is highly prevalent in sub-Saharan Africa, with an estimated 112 million people infected (Chitsulo et al. 2000; van der Werf et al. 2003). In S. haematobium-endemic areas, up to 75% of infected individuals suffer from genital schistosomiasis (Renaud et al. 1989), acquired primarily during childhood (Mbabazi et al. 2011). Female genital schistosomiasis causes ulcerative lesions and inflammation on the cervix and vagina (Mbabazi et al. 2011), while male genital schistosomiasis is associated with both leukocytospermia and gross haematospermia (Leutscher et al. 2005). In both sexes, these conditions result in activation of the immune system which may facilitate HIV entry and binding to HIV-susceptible cells (Secor 2006; Kjetland et al. 2012). The biological plausibility of the association between female genital schistosomiasis and HIV infection, as well as the strong statistical associations between female genital schistosomiasis and HIV (Mbabazi et al. 2011; Kjetland et al. 2012), suggest that genital schistosomiasis is a risk factor for HIV (Stoever et al. 2009).

We sought to determine whether S. haematobium is correlated with HIV prevalence, across sub-Saharan African countries, while addressing multiple potential confounders. For comparison, we evaluated the relationship between HIV and Schistosoma mansoni, which is also highly prevalent in sub-Saharan Africa, but not known to cause urogenital ulcers (Gelfand & Ross 1953; van der Werf et al. 2003). Thus, we contribute a geographical perspective to the body of evidence regarding the association between S. haematobium and HIV by showing that S. haematobium is significantly correlated with HIV prevalence at the national level.

Methods

  1. Top of page
  2. AbstractSummary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We compiled country-specific S. haematobium and S. mansoni prevalence data on 43 sub-Saharan African countries (van der Werf et al. 2003) (Table 1) from both published and unpublished survey data (Brooker et al. 2000). We corroborated the data with different meta-analyses sources and WHO Global Schistosomiasis Atlas, using the most recent prevalence data when sources differed (Chitsulo et al. 2000; van der Werf et al. 2003; World Health Organization).

Table 1. Schistosoma haematobium, Schistosoma mansoni and HIV prevalence for the 43 sub-Saharan African countries (Chitsulo et al. 2000; van der Werf et al. 2003; Gillespie & Greener 2007; Piot et al. 2007)
CountryS. haematobium prevalence (%)S. mansoni prevalence (%)HIV prevalence (%)
Angola331.11.9
Benin173.61.2
Botswana63.125.3
Burkina Faso355.71.4
Burundi01.93.8
Cameroon855.4
Central African Republic32136.1
Chad215.63.5
Congo1203.6
Côte d'Ivoire2544.4
DR Congo21171.3
DR Sao Tome and Principe<1N/A1.5
Equatorial Guinea<1N/A4.0
Eritrea<1N/A0.9
Ethiopia16N/A1.4
Gabon2005.4
Gambia580.41.3
Ghana323.61.9
Guinea5131.4
Guinea-Bissau3002.4
Kenya15356.6
Liberia243.22.0
Madagascar111.30.2
Malawi341511.8
Mali2561.1
Mauritania230.40.7
Mauritius<1N/A1.0
Mozambique441811.3
Namibia422.915.0
Niger263.10.9
Nigeria316.33.6
RwandaN/A<13.0
Senegal101.30.8
Sierra Leone2711.81.6
Somalia38.7N/A0.5
South Africa180.418.1
Sudan17.810.20.7
Swaziland20N/A25.7
Tanzania30166.0
Togo1710.23.3
Uganda1186.3
Zambia184.613.8
Zimbabwe26417.2

Country-specific HIV prevalence data (% population aged 15–49) were obtained from the database of Joint United Nations Programme on HIV/AIDS (2010) (Table 1). Additional statistics included population structure, indicators of development, economic status, education, religion, reproductive health, health services and other infectious diseases obtained from the United Nations Development Programme, World Health Organization, United Nations Children's Fund and United Nations Statistics Division (Drain et al. 2004, 2006). We used the country-level prevalence of male circumcision as previously categorised as ‘low’ (<20%), ‘medium’ (20–80%) or ‘high’ (>80%) by Drain et al. (2006). Countries were categorised into four African regions (eastern, central, southern and western) according to the WHO classification, which is based on geographical differences in the trajectory of the HIV epidemic (Drain et al. 2004). This aggregation of data per geographical differences was performed because of the scarcity of countrywide data on schistosomiasis.

HIV prevalence was log-transformed to create a more normal distribution for use in the regression analysis. We weighted country-level data by the size of adult population of each country to avoid disproportionately representing data from less populous countries. We summarised S. haematobium and HIV prevalence by geographical region and used analysis of variance (anova) to compare the prevalence across African regions. The analysis was performed with one record per country, without cluster variable. All regression statistics were performed using a robust variance to account for unmeasured ecological and population differences. Robust variance is a conservative statistical measure that reduces the association between two variables. This is a more conservative approach for an ecological analysis.

We used univariate linear regression statistics to analyse the relationship between S. haematobium prevalence, HIV prevalence and other infectious and non-infectious variables. We constructed a multivariate model with HIV prevalence as the dependent variable. The multivariate model builds upon our previously published multivariate model, which started with 81 independent variables (Drain et al. 2004), and added S. haematobium, as it was our primary variable of interest. We then removed independent variables that were not statistically significant. All reported P-values were two-tailed. Stata, version 9.0, was used for statistical analyses (Stata Corp. 2004).

Results

  1. Top of page
  2. AbstractSummary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

The mean country-level S. haematobium prevalence was 22.4% [standard deviation (SD): 9.8%] among the 43 sub-Saharan Africa countries for which we had data (Table 2). Mean S. haematobium prevalence differed significantly by the four regions (= 0.03) and was highest among the 15 western African countries and lowest among the 13 eastern African countries. The mean country-level HIV adult prevalence was 6.21% (SD: 5.7%) among all 43 countries, but differed significantly by region (< 0.0001; Table 2). In univariate analysis, S. haematobium was not significantly associated with HIV prevalence (regression coefficient: 3.62; = 0.7).

Table 2. Schistosoma haematobium and HIV prevalence by geographical region within sub-Saharan Africa
Sub-Saharan African regionNo. of countriesS. haematobium prevalence per 100 peopleaHIV prevalence per 100 adultsb
Mean ± SDMean ± SD
  1. a

    = 0.037 using one-way analysis of variance between groups.

  2. b

    < 0.0001 using one-way analysis of variance between groups.

Eastern Africa1317.7 ± 9.64.69 ± 3.04
Central Africa820.5 ± 8.14.10 ± 1.79
Southern Africa723.7 ± 11.918.47 ± 1.78
Western Africa1527.7 ± 7.73.31 ± 1.62
Total4322.4 ± 9.86.21 ± 5.71

Among other infectious disease indicators, an increase in S. haematobium prevalence of 1 infection per 100 people was associated with a decrease of 0.15 infections per 100 people in hepatitis C in univariate analysis (= 0.03). S. haematobium was not significantly associated with cervical cancer incidence, tuberculosis, herpes simplex virus type 2, malaria or syphilis prevalence. S. haematobium was also not significantly associated with S. mansoni prevalence (regression coefficient: 0.0015; = 0.99).

In univariate regression analyses among non-infectious healthcare indicators, the number of S. haematobium infections per 100 individuals was positively correlated with infant mortality rate (0.12 infections per death per 1000 births, = 0.01), child mortality rate (0.06 infections per death per 1000 births, = 0.009) and number of midwives (0.25 infections per midwife per 100 000 population, < 0.0001). S. haematobium prevalence was negatively correlated with age of the HIV epidemic (−2.1 infections per year prior to 2000 in which first HIV or AIDS diagnosis occurred, = 0.04), male use of condoms with non-regular partners (−0.22 infections per percentage of men using condoms, = 0.02), breastfeeding (−0.10 infections per percentage of women exclusively breastfeeding for first 4 months, = 0.045), cigarette consumption (−0.007 infections per cigarette per year per adult, = 0.05) and access to essential medicines (−0.15 infections per percentage with access, = 0.01).

In multivariate analyses, significant independent correlates of HIV prevalence were the prevalence of S. haematobium, the male circumcision coverage, the age of the HIV epidemic, the geographical region and the percentage of the population immunized for diphtheria, tetanus and pertussis (DTP; Table 3). When controlling for the other predictors, each S. haematobium infection per 100 people was significantly associated with a 2.9% relative increase (95% CI: 0.2–5.8%; = 0.038) in HIV prevalence. In contrast, the prevalence of S. mansoni was not a significant predictor of HIV prevalence, either in univariate (regression coefficient: 0.0078; = 0.71) or multivariate analysis (regression coefficient: 0.017; = 0.33).

Table 3. Model of HIV: multivariate linear regression analysis of the Natural Log of HIV prevalence within sub-Saharan Africa
HIV log-prevalence as dependent variableaRegression coefficientP-value
  1. 1–4 (west, central, east, south) representing the level of HIV prevalence in each region. Given that the main focus on our analysis was the association between HIV and schistosomiasis prevalence over the all of sub-Saharan Africa, this transformation may only have a marginal, or no, effect on our results.

  2. a

    In the model, number of countries was 35 and R-squared was 0.66. Variables removed from the model due to non-significance included the following: percentage of females with non-regular sex partners, female age at first sexual intercourse, population younger than 25 years, female adult illiteracy rate, human development index rank and healthcare delivery (total spending on health per capita).

  3. b

    Male circumcision prevalence was categorised as low (<20%), intermediate (20–80%) or high (>80%).

  4. c

    For the sake of simplicity, geographical region was transformed into an ordinal variable with values from.

Schistosoma haematobium prevalence (%)0.029 (0.002 to 0.056)0.038
Male circumcision prevalence by categoryb−0.84 (−1.13 to −0.54)<0.001
Age of HIV epidemic (years)0.30 (0.19 to 0.40)<0.001
Geographical regions (west, central, east, south)c0.19 (0.04 to 0.34)0.012
Children fully immunized for diphtheria, tetanus and pertussis (%)−0.0077 (−0.014 to −0.0015)0.017

Discussion

  1. Top of page
  2. AbstractSummary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Here, we used regression models to assess the correlations between S. haematobium and HIV prevalence in sub-Saharan African countries. While controlling for specific HIV risk factors and for general healthcare indicators, we showed that HIV prevalence is positively correlated with S. haematobium, the primary cause of urogenital schistosomiasis, across 43 sub-Saharan African countries. Our results regarding prevalence at the national level agree with epidemiological studies that have reported strong statistical associations between female genital schistosomiasis and HIV (Kjetland et al. 2006; Downs et al. 2011).

There are many social, behavioural and biomedical risk factors that may influence the incidence of HIV and S. haematobium in sub-Saharan Africa (Todd et al. 2006; Chen et al. 2007; Gillespie & Greener 2007; Piot et al. 2007; Barnabas et al. 2011). Several studies have reported that sexual behaviours such as age at sexual debut, number of sexual partners, engaging in paid sex, condoms use and marital status are associated with an increased HIV incidence in sub-Saharan Africa (Todd et al. 2006; Chen et al. 2007). Biomedical factors such as sexually transmitted diseases (STDs), and medical male circumcision, as well as social factors such as migration, education, socio-economic status and population structure (urbanisation and demography), have also been associated with an increase in HIV incidence (Todd et al. 2006; Chen et al. 2007; Gillespie & Greener 2007; Piot et al. 2007; Alirol et al. 2011; Barnabas et al. 2011). On the other hand, urbanisation, education, poverty, sanitation, water supply and demography have been associated with an increase in S. haematobium prevalence in sub-Saharan Africa (Ugbomoiko et al. 2010; Alirol et al. 2011). These factors may confound the country-level relationship between S. haematobium and HIV prevalence in sub-Saharan Africa. Our study incorporates available data on many of the potential confounders, but is limited by the difficulty in obtaining national-level data on some of these variables across Africa.

In contrast to S. haematobium, the prevalence of S. mansoni was not a significant predictor of HIV prevalence, either in univariate or multivariate analysis, suggesting that the correlative factor between S. haematobium and HIV is the urogenital ulcerations caused specifically by S. haematobium (Secor 2006; Mbabazi et al. 2011). Although our analysis found that S. mansoni prevalence was not a significant predictor of HIV prevalence across sub-Saharan African countries, a recent cross-sectional study among rural Tanzanian women shows that infection with S. mansoni may be a risk factor for HIV acquisition (Downs et al. 2012). Therefore, S. mansoni may be a significant predicator of HIV prevalence at the rural African community level, but not necessarily at the national level.

Schistosoma haematobium is usually regarded as a rural and peri-urban disease (Alirol et al. 2011). However, it has established itself in urban areas across Africa (Ugbomoiko et al. 2010; Alirol et al. 2011), most probably through infected migrants (Alirol et al. 2011), with the presence of endemic foci in many large cities such as in Bamako, Mali, Dar-es-Salaam, Tanzania and Kampala, Uganda (Alirol et al. 2011). In contrast, HIV is often considered an urban infection, but there are also important and emerging foci of HIV epidemics in African rural communities (Serwadda et al. 1992; Oramasionwu et al. 2011). Schistosoma haematobium and HIV meet in migrating populations, travellers, commuting spouses and roadside rural and peri-urban communities (Serwadda et al. 1992; Alirol et al. 2011). In using averaged country-specific prevalence rather than community-specific prevalence, our analysis is likely to underestimate the strength of association between S. haematobium and HIV prevalence by overlooking the potential contribution of S. haematobium highly endemic communities to the spread of HIV within sub-Saharan African countries. An additional limitation of our study was the fact that HIV and S. haematobium prevalence data were not obtained at similar times. To reduce the potential effect of this time difference on the outcome of our analysis, we used the most recent country-specific S. haematobium prevalence data available from the published literature.

Country-level analysis such as this study does not disentangle individual- and population-level risks (Todd et al. 2006), requiring verification of results at the level of the individual. Prospective studies of HIV acquisition in people with genital schistosomiasis would be helpful. However, such studies will be complicated by the ethical imperative to treat schistosomiasis for prevention of the urinary tract consequences of infection, the burden of which is significant (Fenwick & Webster 2006; Stillwaggon 2012).

Schistosomiasis control programmes have been based on mass administration of praziquantel (Fenwick & Webster 2006). For the prevention of genital schistosomiasis to be effective, praziquantel administration should start from childhood, when exposure to schistosomiasis through water contact is highest and adaptive immunity is weakest (Fenwick & Webster 2006), as genital lesions do not necessarily regress with treatment (Kjetland et al. 2012). A prospective study to evaluate the effect of praziquantel treatment on HIV incidence has been proposed as a necessary step towards developing a new protocol to treat schistosomiasis for reducing HIV transmission (Stillwaggon 2012). In addition to praziquantel administration, sustainable interventions for schistosomiasis control should also include provision of clean water and sanitation (Spiegel et al. 2010).

HIV might increase the prevalence of genital schistosomiasis, but existing evidence does not support this as the cause of the correlation with S. haematobium. Genital schistosomiasis manifests prior to sexual debut, and the population prevalence does not rise with age, suggesting it predates HIV infection in co-infected individuals (Poggensee et al. 2000; Kjetland et al. 2005, 2012). Additionally, HIV infection has been associated with either decreased (N'Zoukoudi-N'Doundou et al. 1995; Mwanakasale et al. 2003) or unchanged (Kallestrup et al. 2005) shedding of S. haematobium eggs, indicating that the association between the diseases in not due to increased detection of schistosomiasis.

In summary, our results show that throughout sub-Saharan Africa, S. haematobium prevalence is associated with HIV prevalence. This finding supports the hypothesis that urogenital schistosomiasis is a risk factor for sexual transmission of HIV. Consequently, public health programmes to control S. haematobium may not only reduce morbidity due to schistosomiasis, but may also reduce HIV transmission in sub-Saharan Africa.

Acknowledgements

  1. Top of page
  2. AbstractSummary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

This research was funded by the Institute for Advanced Studies in Berlin and the Notsew Orm Sands Foundation and supported by the Ventura County Medical Center, affiliated with the David Geffen School of Medicine at UCLA.

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  2. AbstractSummary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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