Abstract
OBJECTIVES
Recent reports suggest that Schistosoma infection may increase the risk of acquiring human immunodeficiency virus (HIV). We used data from a large cross-sectional study to investigate whether Schistosoma mansoni infection is associated with increased HIV prevalence.
METHODS
We conducted a household survey of residents in island fishing communities in Mukono district, Uganda, between October 2012 and July 2013. HIV status was assessed using rapid test kits. Kato-Katz (KK) stool tests and urine-circulating cathodic antigen (CCA) were used to test for Schistosoma infection. Multivariable logistic regression, allowing for the survey design, was used to investigate the association between S. mansoni infection and HIV infection.
RESULTS
Data from 1412 participants aged 13 years and older were analysed (mean age 30.3 years, 45% female). The prevalence of HIV was 17.3%. Using the stool Kato-Katz technique on a single sample, S. mansoni infection was detected in 57.2% (719/1257) of participants; urine CCA was positive in 73.8% (478/650) of those tested. S. mansoni infection was not associated with HIV infection. [KK (aOR = 1.04; 95% CI: 0.74–1.47, P = 0.81), CCA (aOR = 1.53; 95% CI: 0.78–3.00, P = 0.19)]. The median S. mansoni egg count per gram was lower in the HIV-positive participants (P = 0.005).
CONCLUSIONS
These results add to the evidence that S. mansoni has little effect on HIV transmission, but may influence egg excretion.
Keywords: Schistosoma mansoni, schistosomiasis, Bilharzia, HIV
Introduction
Sub-Saharan Africa is home to more than 90% of the world’s schistosomiasis cases [1] and more than 68% of people infected with human immunodeficiency virus type 1 (HIV-1) [2]. Schistosoma haematobium causes urogenital schistosomiasis and poses a risk for HIV acquisition through the urogenital lesions [3–5]. However, Schistosoma mansoni rarely causes genital lesions and there is still no consensus about its impact on HIV-1 acquisition, with variable findings on the association between the two infections reported [6–13].
In vitro studies have shown that patients with active schistosomiasis displayed higher cell surface densities of chemokine receptors CCR5 and CXCR4, making the cells more susceptible to HIV than those from helminth-free individuals [14]. Schistosoma mansoni has been shown to increase susceptibility to simian–human immunodeficiency virus (SHIV) infection in rhesus macaques after mucosal challenge by CCR5 tropic (R5) SHIV [15], and the presence of S. mansoni in rhesus macaques resulted in higher T-helper (Th) 2 cell numbers and SHIV replication [16]. In humans, a study in rural Tanzanian villages near Lake Victoria found that S. mansoni infection predicted HIV infection among reproductive age women [13].
We present findings from a study conducted among island fishing communities in Lake Victoria, Uganda. Low levels of sanitation and regular contact with water from Lake Victoria (a water body highly infested with Biomphalaria, the intermediate snail host of S. mansoni) lead to a high prevalence of S. mansoni in these communities. The prevalence of HIV infection is also higher than the national average among these communities, and they may play a key role in the spread of HIV and in the maintenance of the HIV infection levels in the general population [17, 18].
The main objective of this study was to determine whether there is an association between S. mansoni infection and HIV-1 infection in the fishing communities of Lake Victoria. A causal association between these two infections would be of huge public health importance in terms of prevention and treatment strategies for both diseases in these communities.
Methods
Study area and design
This was a cross-sectional household survey conducted in 26 fishing villages in Koome Islands, Lake Victoria, Mukono district, Uganda. The survey was carried out as the baseline for an ongoing cluster randomised trial which aims to investigate the impact of anthelminthic treatment on allergy-related diseases (The Lake Victoria Island Intervention Study on Worms and Allergy-related Diseases, ISRCTN 47196031). The protocol for this trial has been described [19].
Study procedures
For each village, existing household registers were checked and updated for use as the sampling frame for the survey. An equal number of households was then selected from each village by simple random sampling. Household members of all ages (defined as those who sleep in the same house and share meals) were included in the survey.
A questionnaire collecting data on social, demographic and family characteristics was completed for every household member. Data collected included gender, age, occupation, household assets, source of water for domestic use, exposure to the lake, the type of footwear worn and history of having ever received anthelminthic treatment (including praziquantel, which is effective against schistosomiasis). Voluntary HIV counselling (pre- and post-test) and testing was provided by trained and experienced counsellors through collaboration with the Makerere University Joint AIDS Programme’s ‘REACH-U’ project which had the mandate for voluntary counselling and testing in Mukono District at the time of the survey.
Stool samples were requested from all participants and midstream urine samples from a subgroup of participants (during the latter part of the survey) to test for S. mansoni infection. Both stool and urine samples were analysed immediately in the field.
Kato-Katz analysis of a single stool sample with duplicate slides was performed by experienced technicians, to identify and quantify S. mansoni infection [20]. Infection intensity was categorised using WHO cut-offs as light [1–99 eggs per gram (epg)], moderate (100–399 epg) or heavy (≥400 epg) [21].
The urine-circulating cathodic antigen (CCA) cassette test (Rapid Medical Diagnostics, Pretoria, South Africa) was used to detect the parasite antigen CCA which is present in all Schistosoma species [22]. The major portion of CCA released by the adult live parasite is secreted in urine. A positive CCA test result on a midstream urine specimen indicates an active Schistosoma infection. The procedure for the test conformed to the manufacturer’s instructions. All reagents were equilibrated to ambient temperature before commencing the assay. For each sample, one drop of urine was transferred by pipette to the circular well of the test cassette. The sample was allowed to absorb entirely into the specimen pad within the circular well and one drop of buffer added. The results were read exactly 20 min after adding the buffer to the test cassette. Any result read outside 25 min was considered invalid and the test repeated. All ‘trace’ or ‘weakly reactive’ readings were reported as positive.
HIV antibody testing was performed using Determine (Abbott Laboratories, Abbott Japan, Ltd., Tokyo, Japan), Stat-Pak (Chembio Diagnostic Systems, Inc., Medford, USA) and Uni-Gold HIV (Trinity Biotech, Bray, Ireland) test kits as per the manufacturers’ specifications and the Uganda national HIV testing algorithm [23].
Ethics
The study was approved by the Uganda Virus Research Institute Research and Ethics Committee, the Uganda National Council of Science and Technology and the Ethics Committee of the London School of Hygiene and Tropical Medicine. Permission to include each household was obtained from the household head (or from another adult if the household head was absent). Written informed consent was obtained from all adult household members and from parents or guardians on behalf of children. Written informed assent was also obtained from children aged 8 years and above. Individuals found to be HIV positive were referred for care to the subcounty health centre (where antiretroviral therapy is available) or to relevant mainland health services. All participants were offered treatment with praziquantel and albendazole as part of the community-wide anthelminthic intervention programme.
Statistical analysis
Data were entered using Microsoft Access (Microsoft Corporation, Redmond, WA, USA) and analysed using STATA version 13 (Stata Corporation, College Station, TX, USA). To allow for the survey design (clustering by village, and variable village size which meant the design was non-self-weighting), we used STATA survey commands to calculate linearised standard errors and apply village-level weights to the analysis.
The analysis had three aims: firstly, to identify individual and household-level characteristics associated with HIV infection; secondly, to identify characteristics associated with S. mansoni infection (as ascertained from stool samples using Kato-Katz analysis); and finally to assess the association between S. mansoni and HIV infections.
Children younger than 13 years were excluded from the analysis because they were unlikely to have acquired HIV infection by sexual transmission.
Variables considered as possible risk factors for both HIV and S. mansoni were sex, age, occupation, tribe, number of household members, asset score, type of wall, type of roof, smoking, fuel used for cooking, source of washing/drinking water, frequency of going in the lake, footwear when outside the house and history of treatment for worms. The asset score variable was generated by adding the number of assets owned by a household from a list comprising fishing boat, car, motorbike, bicycle, television, radio, mobile phone and bed. For the assessment of characteristics associated with HIV and S. mansoni infection, univariable logistic regression was used to assess crude associations between each potential risk factor and each of the two outcomes. Variables that showed evidence of crude association, or for which there was prior evidence of an association in the literature, were further investigated using multivariable logistic regression. Odds ratios (OR), 95% confidence intervals (CI) and adjusted Wald test P-values were calculated for each characteristic.
The association between S. mansoni and HIV infection was investigated using multivariable logistic regression. S. mansoni status as ascertained from stool using Kato-Katz, S. mansoni status as ascertained from urine using CCA and S. mansoni infection intensity (from Kato-Katz) were each separately considered as exposures for this analysis. Models were adjusted for variables showing any evidence of association with both HIV and S. mansoni infections (sex, age, occupation, asset score and history of ever having received anthelminthic treatment).
Results
Participant characteristics
We enrolled 2316 participants (1268 males, 1048 females). Stool and urine samples were obtained from 1996 and 917 participants, respectively. A total of 1867 participants were tested for HIV. Of these, 455 were children under 13 – of whom only five (all under 4) were HIV positive. Data analysis for the association between HIV and S. mansoni infection was restricted to the 1412 participants who were aged 13 years and older and who had information on HIV status.
The mean age of the participants was 30.3 years (SD, 9.5). Forty-two per cent (42.0%; 593/1412) of the participants were female. The prevalence of HIV infection was 17.3% (244/1412). Based on Kato-Katz analysis of a single stool sample, 57.2% (719/1257) had S. mansoni infection. Among the subgroup of 650 participants for whom urine CCA results were available, this test was positive in 73.5% (478/650). Ninety-two per cent of the participants mentioned the lake as their main source of water for domestic use. Mosquito control measures ranged from nets [34.8%; (492/1412)], or use of spray or coil (18.0%; 254/1412), to no control measures (47.2%; 666/1412). Regarding building materials, only 10.3% (145/1412) of the households used iron sheets to roof their houses (most used thatch with plastic sheeting) and only 10.0% (141/1412) of the households had a toilet.
Factors associated with HIV infection
As shown in Table 1, the prevalence of HIV infection increased with age (P = 0.001). Being aged 30 years or above was associated with a sixfold higher HIV prevalence. There was evidence of an association between occupation and HIV, with those working in shops, saloons, bars or restaurants having the highest HIV prevalence. Analysing asset score as a continuous variable showed some evidence of an inverse association with HIV (aOR = 0.89; 95% CI: 0.79–1.01, P = 0.072). In the univariable analysis, having ever received treatment for worms (with the type of treatment not specified) showed an inverse association with HIV (aOR = 0.74; 95% CI: 0.56–0.99; P = 0.040), but the strength of this association diminished after adjusting for potential confounders.
Table 1.
Factors associated with HIV infection
| Risk factor |
†HIV positive Proportion (%) |
Crude odds ratio‡ (95% CI) |
P-value§ (trend) | Adjusted odds ratio‡ (95% CI) | P-value§ (trend) |
|---|---|---|---|---|---|
| Sex | |||||
| Female | 113/593 (19.1) | 1 | 0.216 | 1 | 0.077 |
| Male | 131/819 (16.0) | 0.84 (0.63–1.12) | 0.72 (0.50–1.04) | ||
| Age group | |||||
| 13–19 | 5/143 (3.5) | 1 | 0.021 (<0.001) | 1 | 0.030 (0.001) |
| 20–29 | 83/591 (14.0) | 3.92 (1.36–11.30) | 3.40 (0.98–11.77) | ||
| 30–39 | 100/433 (23.1) | 7.56 (2.07–27.59) | 6.61 (1.56–28.13) | ||
| 40+ | 56/241 (23.2) | 7.59 (2.25–25.61) | 7.41 (1.80–30.55) | ||
| Occupation | |||||
| Housewife | 15/106 (14.2) | 1 | 0.091 | 1 | 0.009 |
| Fishing | 126/727 (17.3) | 1.41 (0.77–2.57) | 1.38 (0.67–2.83) | ||
| Shops, saloons | 24/105 (22.9) | 1.87 (0.76–4.58) | 2.16 (0.88–5.29) | ||
| Bars, restaurants | 27/129 (20.9) | 1.42 (0.65–3.08) | 1.46 (0.63–3.38) | ||
| Agriculture/charcoal | 44/233 (18.9) | 1.72 (0.84–3.52) | 1.38 (0.57–3.36) | ||
| Other | 7/98 (7.1) | 0.54 (0.17–1.70) | 0.86 (0.22–3.38) | ||
| Asset score | 0.88 (0.78–0.99) | 0.043 | 0.89 (0.79–1.01) | 0.072 | |
| Have you ever been treated for worms? | |||||
| No | 107/541 (19.8) | 1 | 0.040 | 1 | 0.17 |
| Yes | 132/851 (15.5) | 0.74 (0.56–0.99) | 0.83 (0.63–1.09) | ||
CI, confidence interval.
HIV is the acronym for human immunodeficiency virus.
Odds ratios estimated using logistic regression models with linearised standard errors and weighting to allow for the survey design; adjusted odds ratio (aOR) estimated from multivariable logistic regression models that included sex, age, occupation, asset score (generated by adding number of assets that household owns) and prior treatment for worms.
P-values are from the Wald test adjusted for the survey design.
Factors associated with S. mansoni infection
Being male was associated with a 2.6-fold greater odds of S. mansoni infection (Table 2), while increasing age showed an inverse association with S. mansoni infection (trend test P-value = 0.005). The odds of S. mansoni infection were highest among fishermen and among those with frequent lake exposure. The following showed evidence of association with lower odds of S. mansoni infection: use of water from a spring (as opposed to the lake); wearing sandals or closed shoes (as opposed to no shoes); and having ever received anthelminthic treatment.
Table 2.
Factors associated with Schistosoma mansoni infection
| Risk factor |
S. mansoni positive Proportion (%) |
Crude odds ratio† (95% CI) |
P-value‡ (trend) | Adjusted odds ratio† (95% CI) |
P-value‡ (trend) |
|---|---|---|---|---|---|
| Gender | |||||
| Female | 216/537 (40.7) | 1 | <0.001 | 1 | <0.001 |
| Male | 503/720 (68.7) | 3.26 (2.39–4.45) | 2.62 (1.88–3.65) | ||
| Age group | |||||
| 13–19 | 78/120 (65.7) | 1 | 0.48 (0.14) | 1 | 0.056 (0.007) |
| 20–29 | 311/523 (59.2) | 0.75 (0.39–1.44) | 0.58 (0.36–0.95) | ||
| 30–39 | 206/383 (53.8) | 0.60 (0.28–1.30) | 0.38 (0.19–0.78) | ||
| 40+ | 123/227 (53.1) | 0.59 (0.25–1.40) | 0.31 (0.14–0.68) | ||
| Occupation | |||||
| Housewife | 38/97 (39.2) | 1 | 0.001 | 1 | 0.059 |
| Fishing | 440/642 (68.5) | 3.24 (1.92–5.45) | 1.85 (1.00–3.44) | ||
| Shops, saloons | 41/95 (43.2) | 1.30 (0.65–2.59) | 0.96 (0.43–2.13) | ||
| Bars, restaurants | 38/117 (32.5) | 0.63 (0.35–1.15) | 0.62 (0.33–1.17) | ||
| Agriculture/charcoal | 107/209 (51.2) | 1.72 (0.93–3.16) | 1.01 (0.47–2.18) | ||
| Other | 47/86 (33.3) | 1.24 (0.60–2.57) | 0.64 (0.27–1.52) | ||
| Asset score | 0.94 (0.88–1.01) | 0.11 | 1.05 (0.95–1.15) | 0.31 | |
| Anybody smoking in house | |||||
| No | 493/891 (55.0) | 1 | 0.022 | 1 | 0.83 |
| Yes | 226/366 (62.2) | 1.35 (1.05–1.75) | 0.98 (0.81–1.18) | ||
| Cooking with charcoal | |||||
| No | 118/189 (67.7) | 1 | 0.044 | 1 | 0.41 |
| Yes | 601/1068 (55.3) | 0.60 (0.36–0.98) | 0.80 (0.45–1.39) | ||
| Source of water for domestic use | |||||
| Lake | 671/1257 (57.8) | 1 | 0.086 | 1 | 0.058 |
| Spring | 3/16 (16.8) | 0.15 (0.03–0.66) | 0.17 (0.04–0.78) | ||
| Well | 5/9 (55.5) | 0.91 (0.28–2.94) | 0.44 (0.14–1.43) | ||
| Communal tap | 40/74 (57.2) | 0.98 (0.63–1.52) | 1.10 (0.48–2.52) | ||
| How often do you go in the lake? | |||||
| Every day | 530/907 (58.4) | 1 | <0.001 (0.009) | 1 | 0.005 (0.43) |
| Almost every day | 135/206 (65.5) | 1.45 (1.02–2.06) | 1.66 (1.01–2.74) | ||
| Weekly | 35/74 (47.3) | 0.58 (0.27–1.23) | 0.82 (0.33–2.02) | ||
| Less frequently | 14/63 (22.2) | 0.20 (0.11–0.38) | 0.39 (0.15–1.01) | ||
| When you are outside the house, what do you normally wear on your feet? | |||||
| Nothing | 30/43 (75.0) | 1 | 0.062 | 1 | 0.004 |
| Sandals | 644/1146 (55.8) | 0.42 (0.19–0.93) | 0.29 (0.15–0.57) | ||
| Closed shoes | 40/60 (65.7) | 0.64 (0.25–1.74) | 0.29 (0.11–0.76) | ||
| Have you ever been treated for worms? | |||||
| No | 306/472 (64.6) | 1 | 0.011 | 1 | 0.031 |
| Yes | 399/768 (52.0) | 0.61 (0.42–0.88) | 0.56 (0.34–0.94) | ||
CI, confidence interval.
Odds ratios estimated using logistic regression models with linearised standard errors and weighting to allow for the survey design; adjusted odds ratio (aOR) estimated from multivariable logistic regression models that included sex, age, occupation, asset score (generated by adding number of assets that household owns), tribe, smoking within the household, cooking with charcoal, footwear and prior treatment of worms.
P-values are from the Wald test adjusted for the survey design.
Association between S. mansoni and HIV
As shown in Table 3, no evidence of an association between S. mansoni infection and HIV infection was found in this population using the Kato-Katz method (aOR = 1.04; 95% CI: 0.74–1.47, P = 0.81) or using the urine CCA results (aOR = 1.53; 95% CI: 0.78–3.00, P = 0.19). Using S. mansoni egg counts in stool, there was no evidence of any association between HIV status and S. mansoni infection intensity.
Table 3.
Association between Schistosoma mansoni and HIV
| Risk factor |
†HIV positive Proportion (%) |
Crude odds ratio (95% CI) |
P-value (trend) | Adjusted odds ratio‡ (95% CI) |
P-value§ (trend) |
|---|---|---|---|---|---|
| S. mansoni (tested using stool KK) | |||||
| Not infected | 96/538 (17.8) | 1 | 0.78 | 1 | 0.81 |
| Infected | 116/719 (16.1) | 0.95 (0.68–1.33) | 1.04 (0.74–1.47) | ||
| S. mansoni intensity categories | |||||
| Uninfected | 96/538 (17.8) | 1 | 0.39 (0.22) | 1 | 0.65 (0.67) |
| Light (<100 epg) | 58/282 (20.6) | 1.27 (0.85–1.90) | 1.22 (0.87–1.70) | ||
| Moderate (100–399 epg) | 31/206 (15.0) | 0.88 (0.46–1.65) | 0.90 (0.42–1.90) | ||
| Heavy (≥400 epg) | 27/231 (11.7) | 0.68 (0.33–1.38) | 0.87 (0.39–1.91) | ||
| Schistosoma infection (tested using urine circulating cathodic antigen) | |||||
| Negative | 31/172 (18.0) | 1 | 0.15 | 1 | 0.19 |
| Positive | 99/478 (20.7) | 1.42 (0.87–2.31) | 1.53 (0.78–3.00) | ||
CI, confidence interval.
HIV is the acronym for human immunodeficiency virus.
Odds ratios estimated using logistic regression models with linearised standard errors and weighting to allow for the survey design; adjusted odds ratios (aORs) estimated from multivariable logistic regression models that included sex, age, occupation, asset score (generated by adding number of assets that household owns) and prior treatment for worms.
P-values are from the Wald test adjusted for the survey design.
There was no evidence of effect modification by gender (P-values for interaction = 0.27 and 0.22, based on Kato-Katz and urine CCA results, respectively). Thus, it was not necessary to separately analyse the association between S. mansoni and HIV for female and male participants.
HIV infection and S. mansoni egg count
Among participants with S. mansoni infections, the median S. mansoni eggs per gram for the HIV-positive participants (median = 102, IQR 36–321) was lower than that for the HIV negatives (median = 180, IQR 60–660), Wilcoxon rank sum test P-value = 0.005.
Discussion
This study found no evidence of an association between S. mansoni infection and HIV infection among island fishing communities of Lake Victoria, Uganda. Moreover, there was no evidence of an association between HIV and S. mansoni infection intensity. This result, from a cross-sectional study, accords with findings from a prospective incidence study also undertaken among island and lakeshore fishing communities [24].
An important limitation of this study is its cross-sectional design. In their incidence study among similar communities, Ssetaala et al. [24] showed that S. mansoni infection status, defined by measurement of circulating anodic antigen (CAA) in serum, was largely stable over a period of up to 18 months between enrolment and HIV seroconversion, but still, prevalent S. mansoni infection status assessed in a cross-sectional design cannot tell us, with confidence, the status at the time of HIV exposure.
The use of single stool samples to assess S. mansoni infection status lacks sensitivity [25] and will have resulted in misclassification (and hence underestimation of the size of any true association) in this study. Moreover, HIV infection is associated with reduced S. mansoni egg excretion [12], and indeed, egg counts were lower in HIV-infected and S. mansoni-infected participants in this study. This effect might obscure a positive association or lead to a spurious inverse association. However, this was mitigated by the use of urine CCA for S. mansoni diagnosis in a large subgroup: antigen levels in blood (and hence in urine) would be expected to be similar among HIV-positive and HIV-negative people infected with similar worm numbers [9]. Urine CCA assays cannot distinguish between S. haematobium and S. mansoni, but parasitological studies have found S. haematobium to be very uncommon in Uganda [26].
Earlier cross-sectional studies (reviewed by Brown and colleagues [27]) also tended to show little evidence of a positive association between S. mansoni infection and HIV prevalence. However, the analysis presented here was inspired by the more recent study, conducted in the Tanzanian sector of the Lake Victoria basin, which found a positive association between S. mansoni and HIV infection among women [13]. Our study was larger, included more S. mansoni and HIV-infected people, and included both men and women, but failed to confirm the Tanzanian results. Stratification by gender showed no effect modification in our study, making it unlikely that the focus on women in the Tanzanian study explains the different findings.
In vitro and animal studies suggest a link between S. mansoni and risk of HIV infection [14, 15]. One possibility that remains among human populations in highly helminth endemic communities is that immunological effects of helminth exposure persist when infections are treated or cleared [28]. If this is the case, then within-community comparisons, such as the study reported here, may fail to demonstrate an important helminth-induced effect, by contrast to the Tanzanian study whose catchment area extended further from the lake, offering participants from a more varied exposure background. Thus, with regard to S. mansoni, it would be of interest to compare immunological parameters thought to increase susceptibility (such as chemokine receptor expression and Th1/Th2 cellular profiles – as discussed above) between similar populations with and without S. mansoni exposure – such as lakeshore villages versus inland, rural villages. Unfortunately, such studies face the ‘Catch 22’ that important exposures other than schistosomiasis may well differ between such disparate communities and confound these between-community comparisons.
Having received anthelminthic treatment in the past was associated with a reduced risk of S. mansoni infection, as expected. What was unexpected was the reduced risk of HIV infection associated with anthelminthic treatment on univariate analysis. This association was weakened after adjustment for confounders but was of interest given the surprising observation in Ssetaala’s study of a similar, weak association between lack of praziquantel treatment and HIV incidence.
This study addresses one aspect of the ongoing discussion about the potential association between S. mansoni and HIV, namely the effect of S. mansoni infection on HIV transmission. It does not address another important aspect of the discussion, that is the potential impact of schistosomiasis on the progression of HIV infection to AIDS.
The analysis presented in this study utilised data from the baseline survey of the LaVIISWA trial. If HIV testing and viral load estimation are included in the final survey – after 3 years of intensive vs. standard anthelminthic intervention – LaVIISWA may have an opportunity to investigate the impact of such treatment on HIV prevalence and replication.
Conclusions
Together with the study by Ssetaala [24], our findings suggest that, within fishing communities, current S. mansoni infection is not an important risk factor for HIV infection. The possibility remains that intense exposure to S. mansoni infection contributes to the susceptibility of fishing communities at population level and that intervention to treat schistosomiasis may have benefits for HIV transmission in these communities. These possibilities need to be further explored.
Acknowledgements
We thank the Koome subcounty community members, and their local council leaders, beach management committee members and village health team members, for participating in this study. We thank the leadership of Mukono District, particularly the district health officer (Elly Tumushabe) and the councillor for Koome subcounty (Asuman Muwumuza), who are members of the Trial Steering Committee (TSC), for their support. We thank also the other members of the TSC: Heiner Grosskurth (chair), Edridah Tukahebwa, Narcis Kabatereine, Neil Pearce and Anatoli Kamali. We thank the Makerere University Joint AIDS Programme (MJAP) for providing voluntary counselling and HIV testing for community members, including study participants, in collaboration with our research programme. The study was funded by a Wellcome Trust Senior Fellowship held by Professor Elliott. The Wellcome Trust had no role in the design or conduct of the study, or in analysis or preparation of this manuscript.
Appendix I
Project leaders: Margaret Nampijja, Richard Sanya, Barbara Nerima. Statisticians and data managers: Emily Webb, Lawrence Muhangi, Beatrice Mirembe, Justin Okello, Jonathan Levin. Clinical officers: Milly Namutebi, Christopher Zziwa. Nurses: Esther Nakazibwe, Josephine Tumusiime, Carol Ninsiima, Grace Kamukama, Susan Amongin. Internal monitor: Mirriam Akello. Field workers: Robert Kizindo, Moses Sewankambo, Denis Nsubuga. Laboratory staff: Prossy Kabubi Nakawungu, Emmanuel Niwagaba, Gloria Oduru, Grace Kabami, Elson Abayo, Joyce Kabagenyi, Gyaviira Nkurunungi, Fred Muwonge, Dennison Kizito Stephen Cose. Boatman: David Abiriga. HIV counselling and testing: Victoria Nannozi, Bonaventure Mbaraga, Rebecca Musoke, Wambi George. Vector Control Programme staff: James Kaweesa, Edridah Tukahebwa. Principal investigator: Alison Elliott.
References
- 1.WHO . Schistosomiais Fact Sheet Number 115. Geneva; WHO: [updated February 2014; cited 2 December 2014]. 2014. Available from: http://www.who.int/mediacentre/factsheets/fs115/en/ [Google Scholar]
- 2.WHO/UNAIDS/UNICEF . Global HIV/AIDS Response: Epidemic Update and Health Sector Progress Towards Universal Access -Progress Report. Geneva, Switzerland; WHO/UNAIDS/UNICEF: 2011. [Google Scholar]
- 3.Downs JA, Mguta C, Kaatano GM, et al. Urogenital schistosomiasis in women of reproductive age in Tanzania’s Lake Victoria region. Am J Trop Med Hyg. 2011;84:364–369. doi: 10.4269/ajtmh.2011.10-0585. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kjetland EF, Ndhlovu PD, Gomo E, et al. Association between genital schistosomiasis and HIV in rural Zimbabwean women. AIDS. 2006;20:593–600. doi: 10.1097/01.aids.0000210614.45212.0a. [DOI] [PubMed] [Google Scholar]
- 5.Ndhlovu PD, Mduluza T, Kjetland EF, et al. Prevalence of urinary schistosomiasis and HIV in females living in a rural community of Zimbabwe: does age matter? Trans R Soc Trop Med Hyg. 2007;101:433–438. doi: 10.1016/j.trstmh.2006.08.008. [DOI] [PubMed] [Google Scholar]
- 6.Lawn SD, Karanja DM, Mwinzia P, et al. The effect of treatment of schistosomiasis on blood plasma HIV-1 RNA concentration in coinfected individuals. AIDS. 2000;14:2437–2443. doi: 10.1097/00002030-200011100-00004. [DOI] [PubMed] [Google Scholar]
- 7.Brown M, Mawa PA, Joseph S, et al. Treatment of Schistosoma mansoni infection increases helminth-specific type 2 cytokine responses and HIV-1 loads in coinfected Ugandan adults. J Infect Dis. 2005;191:1648–1657. doi: 10.1086/429668. [DOI] [PubMed] [Google Scholar]
- 8.Elliott AM, Mawa PA, Joseph S, et al. Associations between helminth infection and CD4+ T cell count, viral load and cytokine responses in HIV-1-infected Ugandan adults. Trans R Soc Trop Med Hyg. 2003;97:103–108. doi: 10.1016/s0035-9203(03)90040-x. [DOI] [PubMed] [Google Scholar]
- 9.Fontanet AL, Woldemichael T, Sahlu T, et al. Epidemiology of HIV and Schistosoma mansoni infections among sugar-estate residents in Ethiopia. Ann Trop Med Parasitol. 2000;94:145–155. [PubMed] [Google Scholar]
- 10.Ganley-Leal LM, Mwinzi PN, Cetre-Sossah CB, et al. Correlation between eosinophils and protection against reinfection with Schistosoma mansoni and the effect of human immunodeficiency virus type 1 coinfection in humans. Infect Immun. 2006;74:2169–2176. doi: 10.1128/IAI.74.4.2169-2176.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kallestrup P, Zinyama R, Gomo E, et al. Schistosomiasis and HIV-1 infection in rural Zimbabwe: implications of coinfection for excretion of eggs. J Infect Dis. 2005;191:1311–1320. doi: 10.1086/428907. [DOI] [PubMed] [Google Scholar]
- 12.Karanja DM, Colley DG, Nahlen BL, Ouma JH, Secor WE. Studies on schistosomiasis in western Kenya: I. Evidence for immune-facilitated excretion of schistosome eggs from patients with Schistosoma mansoni and human immunodeficiency virus coinfections. Am J Trop Med Hyg. 1997;56:515–521. doi: 10.4269/ajtmh.1997.56.515. [DOI] [PubMed] [Google Scholar]
- 13.Downs JA, van Dam GJ, Changalucha JM, et al. Association of Schistosomiasis and HIV infection in Tanzania. Am J Trop Med Hyg. 2012;87:868–873. doi: 10.4269/ajtmh.2012.12-0395. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Secor WE, Shah A, Mwinzi PM, Ndenga BA, Watta CO, Karanja DM. Increased density of human immunodeficiency virus type 1 coreceptors CCR5 and CXCR4 on the surfaces of CD4(+) T cells and monocytes of patients with Schistosoma mansoni infection. Infect Immun. 2003;71:6668–6671. doi: 10.1128/IAI.71.11.6668-6671.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Chenine AL, Shai-Kobiler E, Steele LN, et al. Acute Schistosoma mansoni infection increases susceptibility to systemic SHIV clade C infection in rhesus macaques after mucosal virus exposure. PLoS Negl Trop Dis. 2008;2:e265. doi: 10.1371/journal.pntd.0000265. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Chenine AL, Buckley KA, Li PL, et al. Schistosoma mansoni infection promotes SHIV clade C replication in rhesus macaques. AIDS. 2005;19:1793–1797. doi: 10.1097/01.aids.0000189857.51935.0b. [DOI] [PubMed] [Google Scholar]
- 17.Kissling E, Allison EH, Seeley JA, et al. Fisherfolk are among groups most at risk of HIV: cross-country analysis of prevalence and numbers infected. AIDS. 2005;19:1939–1946. doi: 10.1097/01.aids.0000191925.54679.94. [DOI] [PubMed] [Google Scholar]
- 18.Asiki G, Mpendo J, Abaasa A, et al. HIV and syphilis prevalence and associated risk factors among fishing communities of Lake Victoria, Uganda. Sex Transm Infect. 2011;87:511–515. doi: 10.1136/sti.2010.046805. [DOI] [PubMed] [Google Scholar]
- 19.Nampijja M, Webb EL, Kaweesa J, et al. The Lake Victoria island intervention study on worms and allergy-related diseases (LaVIISWA): study protocol for a randomised controlled trial. Trials. 2015;16:187. doi: 10.1186/s13063-015-0702-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Katz N, Chaves A, Pellegrino J. A simple device for quantitative stool thick-smear technique in Schistosomiasis mansoni. Rev Inst Med Trop Sao Paulo. 1972;14:397–400. [PubMed] [Google Scholar]
- 21.WHO . Prevention and Control of Schistosomiasis and Soil-transmitted Helminthiasis: Report of a WHO Expert Committee. World Health Organization; Geneva: 2002. [PubMed] [Google Scholar]
- 22.Colley DG, Binder S, Campbell C, et al. A five-country evaluation of a point-of-care circulating cathodic antigen urine assay for the prevalence of Schistosoma mansoni. Am J Trop Med Hyg. 2013;88:426–432. doi: 10.4269/ajtmh.12-0639. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Uganda. Ministry of Health . Uganda National Policy Guidelines for HIV Voluntary Counselling and Testing. Ministry of Health; Kampala: 2003. [Google Scholar]
- 24.Ssetaala A, Nakiyingi-Miiro J, Asiki G, et al. Schistosoma mansoni and HIV acquisition in fishing communities of Lake Victoria, Uganda: a nested case control study. Trop Med Int Health. 2015 doi: 10.1111/tmi.12531. doi:10.1111/tmi.12531. [Epub ahead of print] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Utzinger J, Booth M, N’Goran EK, Muller I, Tanner M, Lengeler C. Relative contribution of day-to-day and intra-specimen variation in faecal egg counts of Schistosoma mansoni before and after treatment with praziquantel. Parasitology. 2001 May;122(Pt 5):537–544. doi: 10.1017/s0031182001007752. [DOI] [PubMed] [Google Scholar]
- 26.Kabatereine NB, Brooker S, Tukahebwa EM, Kazibwe F, Onapa AW. Epidemiology and geography of Schistosoma mansoni in Uganda: implications for planning control. Trop Med Int Health. 2004;9:372–380. doi: 10.1046/j.1365-3156.2003.01176.x. [DOI] [PubMed] [Google Scholar]
- 27.Brown M, Mawa PA, Kaleebu P, Elliott AM. Helminths and HIV infection: epidemiological observations on immunological hypotheses. Parasite Immunol. 2006;28:613–623. doi: 10.1111/j.1365-3024.2006.00904.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Maizels RM, McSorley HJ, Smyth DJ. Helminths in the hygiene hypothesis: sooner or later? Clin Exp Immunol. 2014;177:38–46. doi: 10.1111/cei.12353. [DOI] [PMC free article] [PubMed] [Google Scholar]