Forgotten but not gone in rural South Africa: Urinary schistosomiasis and implications for chronic kidney disease screening in endemic countries

Background: Urinary schistosomiasis caused by infection with Schistosoma haematobium ( S. haematobium) remains endemic in Africa and is associated with haematuria and albuminuria/proteinuria. Kidney Disease Improving Global Outcomes clinical guidelines recommend evaluating proteinuria/albuminuria and glomerular filtration rate for chronic kidney disease (CKD) diagnosis. The guidelines are informed by population data outside of Africa but have been adopted in many African countries with little validation. Our study aimed to characterise the burden of urinary schistosomiasis in rural South Africa (SA) and evaluate its relationship with markers of kidney dysfunction with implications for CKD screening. Methods: In this population-based cohort study, we recruited 2021 adults aged 20 – 79 years in the Mpumalanga Province, SA. Sociodemographic data were recorded, urinalysis performed, and serum creatinine and urine albumin and creatinine measured. Kidney dysfunction was defined as an estimated glomerular filtration rate (eGFR) <60ml/min/1.73m 2 and/or urine albumin-creatinine ratio >3.0mg/mmol. S . haematobium infection was determined by urine microscopy. Multivariable analyses were performed to determine relationships between S. haematobium and markers of kidney dysfunction. Results: Data were available for 1226 of 2021 participants. 717 (58.5%) were female and the median age was 35 years (IQR 27 – 47). Prevalence of kidney dysfunction and S. haematobium was 20.2% and 5.1% respectively. S. haematobium was strongly associated with kidney dysfunction (OR 8.66; 95% CI 4.10 – 18.3) and related to albuminuria alone (OR 8.69; 95% CI 4.11 – 18.8), with no evidence of an association with eGFR <90ml/min/1.73m 2 (OR 0.43; 95% CI 0.05 – 3.59). Discussion: The strong association between urinary schistosomiasis and albuminuria requires careful consideration when screening for CKD. Screening for, and treatment of, schistosomiasis should be a routine part of initial work-up for CKD in S. haematobium endemic areas. Urinary schistosomiasis, a neglected tropical disease, remains a public health concern in the Mpumulanga province of SA.

dysfunction was defined as an estimated glomerular filtration rate (eGFR) <60ml/min/1.73m 2 and/or urine albumin-creatinine ratio >3.0mg/mmol.S. haematobium infection was determined by urine microscopy.Multivariable analyses were performed to determine relationships between S. haematobium and markers of kidney dysfunction.Results: Data were available for 1226 of 2021 participants.717 (58.5%) were female and the median age was 35 years (IQR 27 -47).Prevalence of kidney dysfunction and S. haematobium was 20.2% and 5.1% respectively.S. haematobium was strongly associated with kidney dysfunction (OR 8.66; 95% CI 4.10 -18.3) and related to albuminuria alone (OR 8.69; 95% CI 4.11 -18.8), with no evidence of an association with eGFR <90ml/min/1.73m 2 (OR 0.43; 95% CI 0.05 -3.59).Discussion: The strong association between urinary schistosomiasis and albuminuria requires careful consideration when screening for CKD.Screening for, and treatment of, schistosomiasis should be a routine part of initial work-up for CKD in S. haematobium endemic areas.Urinary schistosomiasis, a neglected tropical disease, remains a public health concern in the Mpumulanga province of SA.

Introduction
Schistosomiasis persists in deprived communities, ranking low on national and global health agendas despite evidence that prevention and control are one of the "best buys" in global public health for neglected tropical diseases 1 .Globally, an estimated 90% of schistosomiasis cases occur in Africa 2 .In South Africa, 25 million people are at risk of infection, with 5 million (of which half are children) already infected 3 .Endemic areas in South Africa report most infections due to Schistosoma haematobium (S. haematobium) with the highest national prevalence in Limpopo and Mpumalanga provinces 4 .Human infection occurs through direct contact with infected freshwater.Contributing factors for infection are pervasive water insecurity, increasing exposure to contaminated freshwater sources, and the absence of implemented programs for the monitoring, evaluation, preventive chemotherapy and vector management 4 .
The lifecycle of S. haematobium begins with the shedding of eggs from the urine of infected hosts.Eggs hatch in optimal freshwater conditions, releasing miracidia which penetrate snails (intermediate host), and infected snails release larvae which penetrate human skin (definitive host) migrating through several tissues before lodging in the venous plexus of the bladder 5 .Clinical manifestations depend on the host immune response, which may be cell-or immune-complex-mediated.A hallmark of the cell-mediated response is the "granuloma", which can occur anywhere along the genitourinary tract and evolves from acute cellular inflammation (terminal hematuria, dysuria, frequency) to parenchymal-mesenchymal transformation dominated by fibrosis and calcification (may be asymptomatic).Fibrosis can result in strictures of the ureter, ureterovesical junction, or urethra, predisposing to urinary obstruction and reflux.Untreated chronic infection increases the risk of squamous cell carcinoma of the urinary tract.Renal disease may arise from chronic pyelonephritis or obstructive nephropathy [6][7][8] .There are a small number of case reports of S. haematobium-associated glomerular disease [9][10][11] .
As non-communicable disease (NCD) prevalence rises in Africa, the nexus between persistent infectious disease burdens (endemic, seasonal, and others) and NCDs is relevant and remains understudied 12 .Data are scarce on the effect of S. haematobium infection on estimated glomerular filtration rate (eGFR), but its associations with leukocyturia, hematuria, and proteinuria/ albuminuria are well documented, with some evidence of reversal following treatment with praziquantel 6,13,14 .The Kidney Disease Improving Global Outcomes (KDIGO) guidelines for chronic kidney disease (CKD) diagnosis define CKD as (i) eGFR <60 ml/min/1.73m 2 , and/or (ii) markers of kidney damage -most commonly albuminuria and urine sediment abnormalities, that persist for at least three months 15 .While the guidelines acknowledge a different context may require variations in practice, there is little guidance to inform CKD screening in schistosomiasis-endemic countries.Our study aimed to characterise the burden of urinary schistosomiasis in rural South Africa and evaluate how S. haematobium infection might impact markers of kidney damage used for diagnosing CKD.

Study design, participants and study area
The African Research on Kidney Disease (ARK) Study aimed to determine CKD prevalence and identify associated risk factors in rural South Africa (SA) 16

Data collection and definitions
Demographic and lifestyle data, anthropometric measurements, and blood and urine specimens were collected by locally trained field workers and study nurses.Sex was defined based on participants self-reporting as male or female.Blood and urine samples were stored at 4-8°C until transported to the research laboratory where they were processed and stored at -80°C prior to shipping to the Central Laboratory Services in Johannesburg for testing.For urinary schistosomiasis screening, a 10-milliliter aliquot of urine was filtered through a nucleopore membrane, and the filter examined for eggs by a trained microscopist, using a BS200 Biological Microscope at x10 magnification.Urine samples were examined within 48 hours of receipt of the specimen from the field.A selection of samples underwent a second microscopy read by co-author XGO at the study site for internal quality control and shipped to the National Health Laboratory Services in Johannesburg for external quality control.Serum creatinine was measured using an isotope dilution mass spectrometry (IDMS) traceable Jaffe method.eGFR (ml/min/1.73m 2 ) was calculated using the 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation without adjusting for African American ethnicity 18 .Urine albumin concentration was measured with immunoturbidimetry, and urine creatinine concentration measured with Jaffe's kinetic method.From these measurements a urine albumin to creatinine ratio (ACR) was calculated (mg/mmol).Kidney dysfunction was defined as a single screen composite outcome of eGFR <60 ml/min/1.73m 2 and/or urine ACR >3.0 mg/mmol.Urinalysis was carried out on fresh urine specimens at the time of collection using Roche Combur 10 urine dipsticks.Urine protein levels were recorded on a scale of 0 to 3+, and urine blood levels on a scale of 0 to 4+.HIV status was either self-reported or based on a rapid antigen test on whole blood.For each participant, the highest level of education and a household assets-based score to assess socioeconomic status were received from the Agincourt HDSS 19 .Data were collected on water, sanitation, and hygiene (WASH) variables: Household water source, frequency of availability of drinking water and distance to the main household water supply in meters.Freshwater exposure was determined at village level.Each village's proximity to freshwater was mapped using local cartography 20 in conjunction with Google mapping software 21 .Villages were grouped into three categories based on the distance of their central point to a freshwater source such as a lake or river: <1 kilometer (km), 1 -2 km and >2 km.

Statistical analysis
Categorical data are presented as absolute numbers and percentages, and continuous data as means and standard deviations (SD), or medians and interquartile ranges (IQR) depending on their distribution.We conducted a complete case analysis of participants with available data for schistosomiasis, eGFR and ACR.Schistosomiasis infection was recorded as a binary variable; present or absent.Continuous variables eGFR and ACR were recoded as binary: eGFR <60 ml/min/1.73m 2 defining a reduced eGFR, and ACR >3.0 mg/mmol defining albuminuria.Kidney dysfunction was subsequently defined as a binary variable -present or absent -based on the composite outcome of an eGFR <60 ml/min/1.73m 2 and/or urine ACR >3.0 mg/mmol.Schistosomiasis point prevalence was calculated as the percentage of the study population with positive urine microscopy for schistosomiasis eggs.Univariable analyses of the crude relationship between covariates and (i) schistosomiasis and (ii) kidney dysfunction were conducted using the chi-squared test.
Age and sex were included as a priori variables in the logistic regression model for the association between S. haematobium and kidney dysfunction.Additional confounders to be entered into the fully adjusted logistic regression model were determined using a directional acyclic graph 22 .A likelihood ratio test (LRT) was conducted for the association between S. haematobium and kidney dysfunction for the fully adjusted logistic regression model.Clustering of schistosomiasis and kidney dysfunction were controlled for by logistic regression with random effects.The p-value for rho (p<0.001) and values for quadratic approximation (all <0.001) were calculated and provided statistical evidence for the assumption of intra-cluster correlation by village 23 .Sensitivity analyses were pre-determined to assess for the association of S. haematobium with individual indicators of kidney dysfunction (albuminuria, reduced eGFR, haematuria) with odds ratios (OR) calculated using a logistic regression model and the LRT to calculate p-values for these associations.For those excluded from the analyses due to missing data, evidence for a systematic difference between included and excluded participants was assessed using cross-tabulation and the chi-squared test.
Finally, we calculated sensitivity, specificity, and predictive values for the presence of haematuria, detected by urine dipstick, as a screening tool for schistosomiasis when compared to the gold standard diagnostic test of detection of schistosomiasis eggs by urine microscopy.Absolute numbers were entered into a 2 × 2 table, grouping urine dipstick results into true positive (TP), false positive (FP), false negative (FN) and true negative (TN).Results in each cell of the table were then used in the following equations to obtain percentage values: Sensitivity=[TP/(TP+FN)]×100; Specificity=[TN/(TN+FP)]×100; Positive predictive value=[TP/(TP+FP)]×100; Negative predictive value=[TN/(FN+TN)]×100 24 .Confidence intervals for sensitivity and specificity were calculated using Clopper-Pearson and the log method used to calculate confidence intervals for positive and negative predictive values 25 .
All data were captured using electronic case report forms and uploaded onto a secure password-protected online database REDCap 26 .Data was analysed in Stata version 16 (StataCorp LLC, College Station, TX).

Results
Overall, 2021 of 2759 (73.3%) participants were enrolled into the study.Reasons for non-inclusion are shown in Figure 1.Of those enrolled, 1226 (60.7%) contributed data to this analysis.Remaining participants were excluded due to missing data on schistosomiasis because of microscope malfunction (n=790) and missing data for albuminuria (n=5).
With multivariable analysis (Figure 2), the adjusted odds ratio for the association between S. haematobium infection and kidney dysfunction was 8.66 (95% CI 4.10 -18.3).Because analysis of eGFR <60 mL/min/1.73m 2 as an outcome variable was not possible due to insufficient data, we used eGFR <90 mL/min/1.73m 2 with no evidence of association with S. haematobium infection (OR 0.43; 95% CI 0.05 -3.59).We conducted sensitivity analyses comparing those included in the analysis to those excluded because of missing data.There were no differences in respect to age and sex, however there was a difference in the prevalence of kidney dysfunction, which was higher for those included in the analysis (20.2% versus 2.3%).
Table 2 shows calculated sensitivity, specificity, and predictive values of haematuria on urine dipstick as a screening tool for S. haematobium infection.

Discussion
In this population-based study of adults residing in rural Mpumalanga Province, South Africa, we found that S. haematobium remains endemic, with men twice as likely to have evidence of infection than women.Kidney dysfunction was detected in one in five participants, and S. haematobium infection was strongly associated with (moderate) albuminuria and urine dipstick hematuria, but not with reduced eGFR.In endemic areas, where access to the gold standard diagnostic urine microscopy is unavailable, urine dipstick can be a useful screening tool for S. haematobium.The high NPV found in our study supports this approach and is helpful for ruling out those who don't need investigation or treatment.In the absence of access to additional diagnostic testing, a single dose of praziquantel in those who present with hematuria is recommended in endemic areas in South Africa.One caveat to this recommendation is the need to "exclude glomerulonephritis", Total with available data: occupation n = 1184; haematuria n=1225; HIV status n=1153; water supply n=1112; water availability n=1112; distance to water supply n=509.All other variables n=1226.cOR crude odds ratio; 95% CI 95% confidence interval; eGFR estimated glomerular filtration rate calculated using the Chronic Kidney Disease-Epidemiology Collaboration equation without African American ethnicity factor; ACR albumin creatinine ratio; HIV human immunodeficiency virus.
a calculated from MHodds chi-squared test; b calculated from two sample t-test; c unable to calculate cOR due to data sparsity, d defined as eGFR <60 ml/min/1.73m 2 and/or ACR>3 mg/mmol which is impractical given the paucity of specialist nephrology services 27 .Our estimated prevalence of kidney dysfunction was higher than that of previous studies for sub-Saharan Africa 18,28 , almost solely based a higher prevalence of albuminuria.Despite the strong association between schistosomiasis and kidney dysfunction, there is limited prior evidence for a direct causal relationship between S. haematobium and intrinsic kidney disease.Future studies are needed to understand causal mechanisms for albuminuria in this group.Aside from S. haematobium, other important causes of albuminuria to consider include HIV, tuberculosis and NCDs, of which hypertension is most common and with diabetes on the rise.
The WHO-recommended core strategic intervention of preventative chemotherapy in South Africa aims to eliminate schistosomiasis as a public health problem 3 .Despite this recommendation, there are no current public health programs targeting schistosomiasis elimination in South Africa.Our calculated prevalence for schistosomiasis in the adult population of 5.1%, alongside a recent prevalence study in both adults and children of more than 30% 4 , supports the need for targeted public health interventions in the Mpumulanga region.The Neglected Topical Diseases Sustainable Development Goals highlight preventive chemotherapy with praziquantel, access to safer water, sanitation and hygiene, and vector control as public health priorities in the control of schistosomiasis 1 .Additionally, the detection of haematuria and/ or proteinuria on urine dipstick should prompt investigation and individual case management of schistosomiasis infection given the strong associations with S. haematobium demonstrated by our study.Further studies are necessary to investigate causal mechanisms for albuminuria (the most common abnormality) in those with S. haematobium infection that will inform future guidelines for management in endemic countries, many of whom are in Africa and likely to remain resource-limited.

Strengths and limitations
This is the first study from South Africa to assess the association of endemic S. haematobium infection with markers of kidney dysfunction, and one of a few studies from the Mpumalanga province that has performed population screening.There are however limitations, including the absence of screening for those younger than 20 years which is likely to underestimate prevalent infection; exclusion of 795 participants because of missing data with a higher prevalence of kidney dysfunction in those included in the final analysis, reducing generalizability of the study; and the use of a single urine microscopy result to diagnose schistosomiasis compared to the gold standard three separate samples for microscopy 29 with a possible underestimate in point prevalence.Any misclassification of schistosomiasis infection is likely to be non-differential which biases effect estimates towards the null.Our results for sensitivity, specificity, PPV and NPV of dipstick haematuria for S. haematobium infection should also be viewed in light of this possible underestimation.

Conclusions
S. haematobium infection is endemic in South Africa and strongly associated with hematuria and moderate albuminuria as markers of kidney dysfunction used for diagnosing CKD.

Extended data
WIReDSpace: Dataset From: Forgotten but not gone in rural South Africa: Urinary schistosomiasis and implications for chronic kidney disease screening in endemic countries, https://doi.org/10.54223/uniwitwatersrand-10539-33712 30is project contains the following extended data: -

Peter Makaula
Research for Health Environment and Development, Mangochi, Malawi Forgotten but not gone in rural South Africa: Urinary schistosomiasis and implications for chronic kidney disease screening in endemic countries Craik A, Gondwe M, Mayindi N, Chipungu S, Khoza B, Gómez-Olivé X, Tollman S, Frean J et al.
Please provide a constructive assessment of the study, detailing your thoughts and recommendations for the author.Also, please state if there are any aspects of the study you have not been able to assess.
Thank you for the opportunity to review this paper.The authors should be commended for writing this paper on an important topic to validate association of non-communicable diseases and neglected tropical diseases to foster understanding the issues for policy formulation in developing countries.While the authors have done a good job in putting together this paper, there are some areas that will need to be revised to improve the general quality of the manuscript.Below are some comments for their consideration: Title -the wording gives a contradictory impression that the study is about rural South Africa, while at the same time referring to other endemic countries.The title and extrapolations should be confined to South Africa considering several limitations of the study also acknowledged by the authors in the Discussion section.

1.
Abstract, Methods -the second sentence needs to be revised so many "and" used.2.

Abstract, Results
-indicate percentage of those whose data were available and merge the first two sentences into one.

3.
Abstract, Discussion -this should be renamed "Discussion and conclusion" or just "Conclusion".

4.
Introduction -the authors write "The lifecycle of S. haematobium begins with the shedding of eggs from the urine of infected hosts."Please specify infected definitive human hosts to differentiate it from intermediate snail hosts mentioned later in the write up.

5.
Methods, Study design and participants -this subsection needs to be revised.While the 6.
subtitle mentions design, "population-based cohort study" have been mentioned only in Abstract -methods and Discussion but no such information is included in this subsection.Later, information unrelated to the subtitle about study area and ethical approvals are included.Consider introducing own subsections for 'participants selection process'; 'study area'; 'ethical considerations' etc.
Methods, Data collection and definitions -similarly to the above observation, this subsection has mainly reported on data collection, but no definitions are included as alluded in the subtitle.The definitions are appearing in the next subsection "Statistical analysis".

7.
Results -Figure 1, it is not clear what authors mean by "ARK Study: on-participants N = 738" is indicated as excluded in the flow diagram.The reasons for non-inclusion shown in this panel should be first described in Results section before referring the reader to Figure 1.Also consider moving Figure 1 and its associated text to Methods, where the selection process of participants is described.

8.
Results -the presentation of the Results could benefit from subsections such as "Sociodemographic characteristics of the study participants"; "Association of Schistosoma haematobium by demographic and clinical characteristics" etc. to make it easier for a reader to follow.

9.
Discussion -the limitations of the study should come at the end after findings of the study are discussed (before recommendations for future research.

Conclusion -authors should consider rewriting "S. haematobium infection is endemic [in some parts of] South
Africa" as they reported that it is only mostly found in Limpopo and Mpumalanga provinces.

11.
Conclusion -authors should highlight key conclusions from the study.Remove the part that reads "Further studies are necessary to investigate causal mechanisms for albuminuria (the most common abnormality) in those with S. haematobium infection that will inform future guidelines for management in endemic countries, many of whom are in Africa and likely to remain resource limited" from to the Discussion section. 12.

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility?

Olusola Ojurongbe
Ladoke Akintola University of Technology, Osogbo, Nigeria Craik et al. presented the study of urinary schistosomiasis and its implications for chronic kidney disease.Understanding the implications of urinary schistosomiasis for chronic kidney disease is crucial, and the presented work provides valuable data and results for further analysis.The study seems to be well-designed and presented, but the authors will need to clarify these observations.
Excluding a whole lot of 790 samples because of the microscope malfunction is not a welcome development.This large chunk of data would have significantly contributed to the study outcome.Why can't the authors preserve these samples and re-analyze them? 1.
The author should clarify this statement "Because analysis of eGFR <60 mL/min/1.73m2as an outcome variable was not possible due to insufficient data".Was the eGFR not conducted on the 790 individuals without schistosomiasis results due to microscope malfunction?2.
In Table 2 table the author presented the Creatinine (μmol/L) as Mean (SD), whereas the heading of the table says n (%).This is a bit confusing.The author should correct it appropriately.

3.
The author listed several limitations in the study, including using single urine microscopy to diagnose schistosomiasis, which I believe has a significant impact on the outcome of this study.In addition, the inability of the authors to administer PZQ to schistosomiasis-positive participants and analyze their post-treatment sample is an additional limitation.This would have helped to see if the observed CKD in those positive was due to schistosomiasis or other factors not investigated.The authors should comment on this.

Is the work clearly and accurately presented and does it cite the current literature? Yes
Is the study design appropriate and is the work technically sound?Yes

Are sufficient details of methods and analysis provided to allow replication by others? Yes
If applicable, is the statistical analysis and its interpretation appropriate?Yes Are all the source data underlying the results available to ensure full reproducibility?Yes Are the conclusions drawn adequately supported by the results?

Figure 1 .
Figure 1.Flow diagram depicting sample selection, participant recruitment, and urinary schistosomiasis screening strategy.

Figure 2 .
Figure 2. Comparison of the primary logistic regression model for the association with Schistosoma haematobium and kidney dysfunction with results from sensitivity analyses of the association of individual markers of kidney dysfunction.
https://doi.org/10.21956/wellcomeopenres.20680.r61833© 2023 Ojurongbe O.This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
. The study took place from November 2017 to September 2018 and included a population-based sample (N=2759) of adults aged 20-79 years from the Agincourt Health and Socio-Demographic Surveillance System (HDSS) site in rural Bushbuckridge, Mpumalanga Province 17 .Institutional review board approval was obtained from the University of Witwatersrand (clearance number M170583) with additional approval for this sub-study from the London School of Hygiene and Tropical Medicine MSc Research and Ethics Committee (reference number 22152).Written informed consent was obtained from individual participants prior to enrolment.

expertise to confirm that it is of an acceptable scientific standard. Version 1
This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.