Rapid urbanization has led to the expansion of informal settlements in many low- and middle-income countries (LMICs). Such settlements often have very limited sanitation infrastructure (UN-Habitat, 2016). Separation of human waste from human contact can prevent exposure to enteric pathogens that cause infection, diarrhea (Liu et al., 2016), and potentially long-term health effects such as environmental enteric dysfunction (EED) (Kosek and MAL-ED Network Investigators, 2017), linear growth deficits (Rogawski et al., 2018), impaired cognitive development (MAL-ED Network Investigators, 2018), and reduced oral vaccine immunogenicity (Parker et al., 2018). Children living in densely populated slum areas where fecal contamination is pervasive and sanitation infrastructure is limited may be at an increased risk of adverse health effects due to frequent exposure to enteric pathogens (Ezeh et al., 2017; Fink et al., 2014).

Household-level sewerage has demonstrated health benefits (Barreto et al., 2010; Barreto et al., 2007; Norman et al., 2010) and remains an important long-term goal for many urban settings despite limited evidence from controlled trials (Norman et al., 2010; Wolf et al., 2018). Such systems may not be feasible short-term solutions due to cost, space, and logistical constraints, challenges that have also impeded their evaluation via randomized trials (Norman et al., 2010). Further, in densely populated areas, there may not be space for household-level sanitation of any type. Shared sanitation is a subject of considerable debate but may represent the only near-term sanitation option in some settings (Evans et al., 2017; Heijnen et al., 2014; Tidwell et al., 2020). Yet, while shared, onsite systems may fill the growing need for safe sanitation in rapidly expanding urban areas in LMICs, to date, there has been little evidence of their health impacts in these settings. Recent large-scale, rigorous evaluations of onsite sanitation interventions and combined water, sanitation, and hygiene (WASH) interventions have demonstrated mixed effects on health (Clasen et al., 2014; Sanitation Hygiene Infant Nutrition Efficacy (SHINE) Trial Team et al., 2019; Luby et al., 2018; Null et al., 2018; Patil et al., 2014; Pickering et al., 2015) but all were conducted in rural areas with household-level interventions, and their findings may have limited generalizability to urban areas. A recent meta-analysis estimated that non-sewered interventions reduced the risk of self-reported diarrhea by 16% but did not estimate effects on objective health outcomes, such as enteric infection (Brown and Cumming, 2020), and could not stratify estimates by rural versus urban setting given the lack of evidence in urban areas (Wolf et al., 2018). To date, no controlled trials of urban onsite sanitation have been conducted despite over 740 million urban residents relying on such technologies (Berendes et al., 2017).

The Maputo Sanitation (MapSan) trial was the first controlled trial to evaluate an onsite, shared sanitation intervention in an urban setting and the first to use the prevalence of enteric infection, as detected by molecular methods, as the primary study outcome (Brown et al., 2015). The study was located in densely populated, low-income, informal neighborhoods of Maputo, Mozambique where the sanitary conditions are poor and disease burden high (Knee et al., 2018). As of 2017, only half of urban residents in Mozambique had access to at least basic sanitation infrastructure, 3% had access to sewerage, and 9% shared sanitation with multiple households, often in poor neighborhoods where space and resources are limited (UNICEF/WHO, 2019). We investigated whether an engineered, onsite, shared sanitation intervention could reduce enteric infection and diarrhea in young children living in these low-income, densely populated neighborhoods in Maputo, Mozambique.

The MapSan trial was a controlled before-and-after (CBA) trial designed to evaluate the impact of an onsite sanitation intervention on child health after 12 and 24 months of follow-up. The intervention consisted of pour-flush toilets to septic tanks with soakaway pits to discharge the liquid portion of the waste. A non-governmental organization (NGO) delivered the intervention to clusters of households known as compounds, replacing the existing poor-condition shared facilities. Control compounds did not receive the intervention and continued to use their poor-condition sanitation for the duration of the study. We assessed several measures of child health, including enteric infection measured via stool-based molecular methods, soil-transmitted helminth (STH) re-infection measured via Kato-Katz, and diarrhea measured via caregiver report in both intervention and control children during three phases: baseline (pre-intervention), 12-month follow-up, and 24-month follow-up. Children were eligible for baseline enrollment if they were less than 4 years old (1–48 months old). At follow-up, children were eligible for enrollment if they were less than 4 years old or if they would have been less than 4 years old during baseline.

We enrolled 987 children in 495 compounds during the baseline phase (February 2015 – February 2016) and collected stool samples (whole stool or diaper samples containing liquid diarrhea) from 765 children (78%) (Figure 1). During the 12-month follow-up phase (March 2016 – April 2017), we enrolled or revisited 939 children in 438 compounds and collected 805 stool samples (86%). During the 24-month follow-up phase (April 2017 – August 2018), we enrolled or revisited 1001 children in 408 compounds and collected stool samples from 922 (90%). To improve the success rate of stool sample collection during the 12- and 24-month follow-up visits, we collected rectal swabs from children who did not provide a whole stool sample after multiple collection attempts. The proportion of each type of sample (whole stool, diaper sample, and rectal swab) was similar between arms at each phase (Appendix 1—figure 1). Fewer than 5% of all samples were diapers and approximately 7% of 12-month samples and 25% of 24-month samples were rectal swabs (Appendix 1—table 1). The NGO delivered interventions to 15 control compounds after baseline and children in those compounds were censored at the time of intervention receipt (Figure 1). Children living in control compounds that independently upgraded their latrines were included in the main analyses. However, as inclusion of these control children may have diluted the intervention effect, they were excluded from sensitivity analyses designed to understand the impact of the intervention when compared with controls served by poor-condition sanitation throughout the study. Children in intervention and control compounds were enrolled at similar rates during each phase (Appendix 1—figure 2). Due to migration out of the compound, we collected longitudinal data from 62% of children (59% controls, 67% interventions) between baseline and 12-month and 51% of children (46% controls, 58% interventions) between baseline and 24-month.

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At baseline enrollment, intervention compounds had more residents, households, and on-premise water taps than controls, though the number of shared latrines was similar (Table 1). Animals were observed in over half of all compounds. Intervention and control households had similar wealth scores, though intervention households had more members and were more crowded while control households more often had walls made of sturdy materials. All households used a municipal water tap as their primary drinking water source with 78% reporting use of a tap on the compound grounds. At baseline, latrines used by intervention households more often had pedestals or slabs, drop-hole covers, and sturdy walls compared with controls. Consistent with previous estimates in urban Maputo (Satterthwaite et al., 2019), open defecation was rare in our study population with only one control household reporting open defecation at baseline. Baseline characteristics of intervention and control children were similar: the average age at enrollment was 23 months (SD = 13), 51% were female, and 32% were still breastfeeding (Table 1). The age distributions of intervention and control children were similar at baseline and both follow-up phases (Appendix 1—figure 3).

We used the Luminex Gastrointestinal Pathogen Panel (GPP), a qualitative multiplex molecular assay, to simultaneously test for 15 enteric pathogens in stool samples, including nine bacteria, three protozoa, and three viruses. We detected ≥1 bacterial or protozoan enteric infection, our pre-defined primary outcome, in 78% (591/753) of children with stools available at baseline. We measured our pre-defined secondary outcome, ≥1 STH re-infection, using the Kato-Katz microscope method and detected ≥1 STH in 45% (308/698) of stools at baseline. The prevalences of pre-defined outcomes, individual pathogens, and pathogen types were similar between the intervention and control arms at baseline (Table 2). The prevalence of most bacterial, protozoan, and STH infections increased with age while the prevalence of enteric viruses decreased with age (Appendix 1—table 2 and Appendix 1—figure 4).

The characteristics of children with repeated observations (including baseline) were similar to characteristics of children measured at baseline only (Appendix 1—table 3 and Appendix 1—table 4) and to characteristics of children measured at 12 month and/or 24 month only with the exception of age-related characteristics (Appendix 1—table 5 and Appendix 1—table 6). Over half of the children enrolled after baseline were born into study sites (336/622 [54%], Figure 1).

Our main analyses included observations from all eligible children enrolled at baseline (mean sampling age 664 days, SD = 393) and the 12-month (940 days, SD = 498) and 24-month (1137 days, SD = 603) follow-up visits (Table 2). We used a difference-in-difference (DID) analysis to estimate the intervention effect and adjust for baseline differences between intervention and control compounds. We present effect estimates from the DID analyses as prevalence ratios (ratio of ratios). To assess the validity of the parallel trend assumption, a key assumption of DID analyses, we ran ‘placebo tests’ by replacing outcomes with variables unrelated to the intervention, such as child age, respondent role, and presence of animals. Placebo tests showed no effect of the intervention on these variables, suggesting the parallel trend assumption was valid. We found no evidence that the intervention had an effect on the prevalence of any bacterial or protozoan infection (adjusted PR 1.04, 95% CI [0.94–1.15]), or any STH re-infection (1.11 [0.89–1.38]) 12 months after implementation (Table 2) despite household respondents reporting almost exclusive use of the intervention latrine (97%, 404/417). The prevalence of diarrhea remained fairly constant in both arms in all three phases with the exception of the 12-month measure in the control arm which was lower, resulting in a larger effect estimate with low precision (1.69 [0.89–3.21]).

The intervention had no meaningful effect at 12 months on the prevalence of infection with any of the three pathogen types measured by the GPP (bacterial, protozoan, viral), pathogen coinfection, or on any individual pathogen (Table 2). There was poor precision in the effect estimates for infrequently detected pathogens, evident from their wide confidence intervals. Therefore, some estimates suggestive of a large protective or detrimental effect (Campylobacter, C. difficile, E. coli O157, STEC, Norovirus GI/GII, Adenovirus 40/41) may have arisen by chance. While the National Deworming Campaign (NDC) provided albendazole to all compound members following baseline, during 12-month visitation only 58% of caregivers (56% control, 60% intervention) confirmed that their child was dewormed during these visits. A sensitivity analysis restricted to children confirmed to have been dewormed produced similar results to the main analysis (Appendix 1—table 7). By the 12-month visit, 19 control compounds (19/240 [8.0%]) had independently upgraded their facilities to pour-flush toilets. Results from sensitivity analyses excluding children living in control compounds with independently upgraded facilities were consistent with the main results (Appendix 1—table 8).

There was no evidence that the intervention had an effect on the prevalence of any bacterial or protozoan infection, any STH re-infection, or diarrhea after 24 months among all enrolled children (Table 2). We also found limited evidence of effect on the prevalence of any pathogen type or coinfection with ≥2 GPP pathogens 24 months after intervention. Results for several individual outcomes were suggestive of a protective (STEC, E. coli O157, Cryptosporidium, STH coinfection) or adverse (Campylobacter, C. difficile) effect, but evidence was weak as estimates were accompanied by wide confidence intervals and chance discoveries were possible given multiple comparisons. At the 24-month visits, caregivers confirmed baseline and/or 12-month deworming more frequently for intervention children (339/502 [68%]) than for control children (286/499 [57%]). Adjustment for deworming status or time since deworming had no impact on effect estimates (Appendix 1—table 7). Excluding children from control compounds which independently upgraded their facilities by the 24-month visit (35/211 compounds, [17%]) did not impact the results (Appendix 1—table 8).

Point estimates of effect and associated confidence intervals were largely similar in unadjusted and adjusted models with few exceptions (e.g. ETEC at 24 month) (Table 2). Multivariable models for GPP outcomes and STH outcomes were adjusted for covariates selected a priori (child age, sex, caregiver education, and household wealth index). No other variables met our inclusion criteria for multivariable models, which included being imbalanced between intervention and control at baseline and meaningfully changing 12-month effect estimates (>10% change in prevalence ratios) (Appendix 1—table 9). While the relationship between age and pathogen prevalence appeared to be non-linear for many pathogens (Appendix 1—figure 4), the inclusion of a higher order age term (age squared) did not meaningfully change effect estimates in the main or sub-group analyses (Appendix 1—table 10). Three measures of seasonality were considered for inclusion in multivariable models to adjust for any difference in seasonal distributions of data collection: (1) a binary variable defining the ‘rainy’ (November – April) and ‘dry’ seasons (May – October) in Maputo, (2) a measure of cumulative rainfall (mm) in the 30 days prior to data collection, and (3) sine and cosine terms representing dates of sample collection. While there was some imbalance between arms in data collected during the wet and dry seasons at baseline (Appendix 1—table 9), no measure of seasonality meaningfully changed effect estimates in the 12- and 24-month analyses and seasonality was excluded from final multivariable models (Appendix 1—table 9 and Appendix 1—table 11). For diarrhea, two variables in addition to variables selected a priori met our inclusion criteria and were included in adjusted models: presence of a latrine drop-hole cover at baseline and reported use of a water tap located within the compound grounds at baseline (Appendix 1—table 9). The magnitude of effect estimates were larger and confidence intervals wider for diarrhea in adjusted versus unadjusted models in the 12-month and 24-month analyses (Table 2).

In addition to the main analyses which included all enrolled children, we also performed two sub-group analyses. The first included children who were born after the intervention was implemented (or after baseline in control compounds) and present at the 12- and/or 24-month follow-up visit. This analysis allowed us to evaluate the impact of the intervention on young children who were never exposed to poor sanitation at baseline. The second sub-group analysis included only children with repeated measures at baseline and 12- and/or 24-month follow-up.

In sub-group analyses comparing children born into study compounds before the 24-month visit with children of similar ages at baseline (<2 years old), there was suggestive evidence that the intervention reduced the prevalence of infection with any STH by 49% (n = 522; adjusted prevalence ratio 0.51, [95% CI 0.27–0.95]), Trichuris by 76% (n = 522; 0.24, [0.10–0.60]), and Shigella by 51% (n = 630; 0.49, [0.28–0.85]) (Table 3). These effects were attenuated in sub-group analyses restricted to older children (>24 months) who were born before the intervention was implemented and present at the 24-month phase (Appendix 1—table 12). We did not observe intervention effects among children born into the study by the 12-month visit, but the sample size was small, resulting in high uncertainty in effect estimates (Appendix 1—table 13).

Longitudinal sub-group analyses explored the effect of the intervention on children with repeated measures at baseline and 12 month (for unadjusted analyses: n = 870 data points [435 children with repeat measures] for GPP outcomes, n = 572 [286] for Kato-Katz outcomes, and n = 1112 [556] for diarrhea) and at baseline and 24 month (n = 716 (358), n = 402 (201), n = 834 (417)). Effect estimates were consistent with results from the main analyses (Appendix 1—table 14 and Appendix 1—table 15) but less precise due to the reduced sample numbers.

We found no evidence that this urban, onsite shared sanitation intervention was protective against our pre-specified child health outcomes of enteric infection, STH re-infection, or diarrhea. We also found no strong evidence that the intervention affected prevalence of any individual pathogen, pathogen type, or coinfection with ≥2 enteric pathogens or STH. In exploratory sub-group analyses, we found suggestive evidence that the intervention reduced the prevalence of any STH, Trichuris, and Shigella infections among children born into the study by the 24-month follow-up visit. Studying children born into intervention sites after implementation allowed us to examine the effect of the intervention from birth through the first 2 years of life. These results suggest that the intervention delayed pathogen exposure and the accumulation of enteric infections during early childhood, but need to be treated with caution as this was an exploratory subgroup analysis.

The trial was neither designed nor powered to detect differences in sub-groups of children such as those born after the intervention was implemented, potentially limiting our ability to detect small effects in such analyses. Further, all exploratory sub-group analyses included multiple comparisons, increasing the likelihood of chance discoveries. However, the magnitude of the effect estimates for the outcomes of any STH, Trichuris, and Shigella observed among children born into the study by the 24-month visit, and the directional consistency of effect estimates among most other outcomes in this sub-group analysis, strengthens the plausibility of these findings.

There are several reasons we observed suggestive evidence of an effect for some outcomes among this sub-group of young children but not among older children or in the main analyses. Children’s exposures vary by age, particularly as they become mobile and begin independent exploration of their environment. It is possible that the intervention reduced exposure via pathways that are important for very young children but may represent just minor pathways of exposure among older children (Kwong et al., 2020). Additionally, young children may experience fewer exposures outside of the compound. Reductions in exposure and subsequent infection early in life may delay or prevent the development of environmental enteric dysfunction (EED), a subclinical condition that affects the structure and function of the gut and may increase susceptibility to future infection (Keusch et al., 2014; Prendergast and Kelly, 2016). Results from the EED sub-study of the WASH Benefits cluster randomized controlled trial (cRCT) in Bangladesh suggest that the intervention delayed but did not prevent the onset of EED (Lin et al., 2019). If this intervention similarly delayed the development of EED among children born into intervention sites, they may have been less susceptible to infection than children of a similar age at baseline. Finally, some pathogens, like Giardia and certain STH, can cause persistent infections that can remain active for months or years if not treated (Else et al., 2020; Rogawski et al., 2017). The intervention would have no effect on such infections, highlighting the potentially important role of protection from birth.

Notably, both Shigella and Trichuris are primarily anthroponotic, and infection was strongly age-dependent in this study population (Knee et al., 2018). These factors may help explain the differing intervention effects observed both among pathogens and age groups. The intervention was unlikely to limit exposure to animal feces, reducing the likelihood that it would impact the infection prevalence of zoonotic pathogens like Campylobacter or Giardia. The strong positive associations between age and prevalence for Shigella and Trichuris suggest that exposure increases with age. This supports the hypothesis that the intervention may have reduced the overall frequency or intensity of exposure enough to impact Shigella and Trichuris infection among young children but not older children.

Rapid urbanization is expanding informal settlements and out-pacing the expansion of sanitation services in many cities, widening the gap in sanitation access between the urban rich and poor (UNICEF/WHO, 2019). To our knowledge, MapSan was the first trial to estimate the health impact of an urban, onsite shared sanitation intervention and the first to use enteric infection as the primary trial outcome. Most of the urban sanitation literature published to date has evaluated the expansion of sewerage, an important and ambitious goal that is out of reach for many cities in the near-term (Norman et al., 2010). Access to sewerage is associated with a 30–60% reduction of diarrheal disease depending on starting conditions, and an approximately 30% reduction in enteric parasite detection, though most studies are observational and few controlled trials exist (Barreto et al., 2010; Norman et al., 2010; Wolf et al., 2018).

Most studies of onsite sanitation interventions have occurred in rural areas. Despite good evidence that onsite sanitation is associated with reductions in diarrheal disease (Freeman et al., 2017a; Wolf et al., 2018), several recent rural trials of basic sanitation and combined WASH interventions with good uptake and use reported mixed effects on child health outcomes including diarrhea, linear growth, and more recently, enteric infection (Ercumen et al., 2019; Grembi et al., 2020; Sanitation Hygiene Infant Nutrition Efficacy (SHINE) Trial Team et al., 2019; Lin et al., 2018; Luby et al., 2018; Null et al., 2018; Pickering et al., 2019; Rogawski McQuade et al., 2020a).

The Sanitation, Hygiene, Infant Nutrition Efficacy (SHINE) trial in rural Zimbabwe found no impact of a combined WASH intervention on diarrhea, growth, or the prevalence of a suite of enteric pathogens among children aged <12 months old but did report a small reduction in the number of parasitic pathogens detected (Sanitation Hygiene Infant Nutrition Efficacy (SHINE) Trial Team et al., 2019; Rogawski McQuade et al., 2020a).

While the WASH Benefits Bangladesh cRCT reported no effect of any WASH intervention on child growth, the sanitation, hygiene, and combined WASH study arms reduced the prevalence of diarrheal disease from 5.7% to 3.5% (Luby et al., 2018), accompanied by absolute reductions in Giardia prevalence of 6–9% among children aged 2–3 years in the same arms (Lin et al., 2018). The sanitation arm also reduced the prevalence of T. trichiura among children 2–3 years old (from 5.2% to 3.2%) but had no impact on A. lumbricoides or hookworm, the only other parasites detected frequently enough to estimate effects in that study (Ercumen et al., 2019). In a parallel analysis, only the water treatment and combined WASH interventions of the WASH Benefits Kenya cRCT reduced the prevalence of A. lumbricoides, suggesting that the reduction in the combined WASH arm may be attributable to the water treatment intervention (Pickering et al., 2019). The sanitation-only arm had no impact on any parasite measured, although T. trichiura was too infrequently detected to estimate effects (Pickering et al., 2019). An evaluation of a comprehensive suite of 34 enteric pathogens reported reduced prevalence and quantity of enteric viruses, but not bacteria or parasites, among children aged 14 months old in the combined WASH arms in the Bangladesh trial (Grembi et al., 2020). Together with our findings, these results suggest that sanitation and combined WASH interventions can reduce the prevalence of enteric infection in some settings but that effects may vary by pathogen, child age, intervention, and setting.

We previously published two baseline risk factor analyses to identify demographic, environmental, and WASH-related predictors of infection and environmental fecal contamination in our study setting prior to the intervention implementation (Holcomb et al., 2020; Knee et al., 2018). Age was an important predictor of infection, although the direction of its effect varied by pathogen type. Increasing age was associated with increased risk of bacterial and protozoan infections and decreased risk of viral infections (Knee et al., 2018). Other socio-demographic predictors of infection included breastfeeding, which was associated with a decreased risk of any infection (driven by its strong association with protozoan infection), and female sex which was associated with an increased risk of viral infection. Few sanitation-related or environmental variables were associated with infection at baseline and the magnitude of associations were often small. The presence of a latrine superstructure and drop-hole cover were associated with small reductions in risk of bacterial or protozoan infection, often only in unadjusted analyses, but other latrine features (e.g. presence of a cleanable slab) were not. The observation of feces or used diapers around the compound grounds was associated with increased risk of bacterial and protozoan infection but most other environmental and sanitary hazards were not (Knee et al., 2018).

Fecal contamination was common among all environmental reservoirs tested (water, soil, food preparation surfaces) at baseline. We detected one or more microbial markers of contamination in over 95% of environmental samples (Holcomb et al., 2020). E. coli was the most frequently detected and abundant marker of contamination among all sample types, and human-associated markers were most frequently detected in soil (59%) and stored drinking water (17%) samples. Measures of latrine quality that were associated with small reductions in infection risk (e.g. drop-hole covers, latrine superstructures) were not associated with decreased odds of fecal contamination in this setting. Overall, we found few consistent relationships between markers of fecal contamination and environmental, WASH-related, and demographic characteristics at baseline (Holcomb et al., 2020).

While these results suggest WASH-related and environmental risk factors may be poor determinants of child health in this setting, the lack of heterogeneity in WASH conditions at baseline, given the selection criterion that compounds must share sanitation in ‘poor condition,’ may have limited our ability to identify strong WASH-related predictors of infection or environmental fecal contamination. Results from a forthcoming companion study suggests the intervention had mixed effects on environmental fecal contamination. The intervention may have reduced the concentration of E. coli by an order of magnitude in soil collected from latrine entrances after 12 months; however, there was no effect on the prevalence or concentration of indicators of fecal contamination in any other environmental compartment sampled at that time (Holcomb et al., 2021). It is unlikely that the observed reductions in fecal contamination in soils alone would be sufficient to impact health outcomes in this setting. Other studies that have evaluated the impact of sanitation interventions on fecal contamination of the surrounding environment have found limited evidence of effect (Clasen et al., 2014; Ercumen et al., 2018a; Ercumen et al., 2018b; Fuhrmeister et al., 2020; Patil et al., 2014; Pickering et al., 2015; Sclar et al., 2016; Steinbaum et al., 2019).

In this setting, where fecal contamination was pervasive and burden of infection high, even considerable reductions in contamination and exposure may have been insufficient to realize measurable health gains as the intervention did not address all potential transmission pathways (Briscoe, 1984; Julian, 2016; Robb et al., 2017). For example, the intervention did not address child feces disposal practices or handwashing behaviors and it is unlikely that the intervention infrastructure would have changed these (Cochrane Infectious Diseases Group et al., 2019). Previous studies of sanitation interventions have found no reduction in hand contamination (Ercumen et al., 2018b), which has been associated with increased incident diarrheal disease in young children (Pickering et al., 2018). The intervention may not have reduced exposure via consumption of contaminated food – particularly foods contaminated prior to arrival in the compound – likely an important source of enteric pathogen transmission in some settings (Julian, 2016; Kwong et al., 2020). Children’s exposure to animal feces has been documented in rural, peri-urban, and urban settings and could be an important, unmitigated source of exposure to enteric pathogens in both intervention and control arms where animals were frequently observed (Delahoy et al., 2018; Kwong et al., 2020; Penakalapati et al., 2017). Observation of animals in compounds was examined as a potential confounder but did not change effect estimates.

The intervention was delivered at the compound level, not the community level, and was not designed to achieve any specified threshold of sanitation coverage in the study neighborhoods. Previous studies have suggested that achieving a certain level of community sanitation coverage may be necessary to reduce disease burdens (Barreto et al., 2007; Fuller and Eisenberg, 2016; Fuller et al., 2016; Harris et al., 2017; Jung et al., 2017; Spears et al., 2013; Wolf et al., 2018). For example, a study of a large-scale sewerage expansion in urban Brazil found that the intervention reduced diarrheal disease by 22%, with neighborhood coverage level being the single most important explanatory variable (Barreto et al., 2007). We did not measure neighborhood-level sanitation coverage, but previous estimates show that while coverage is high and open defecation is limited (1%), only 9% of sanitation systems are safely managed (Satterthwaite et al., 2019). Further, in the Nhlamankulu district where many of our study sites are located, the majority of households (56%) rely on private pit latrines, most of which are in poor condition (Devamani et al., 2014; Satterthwaite et al., 2019). Together with our results, this suggests that both the extent and quality of community coverage are likely important to reducing overall transmission. Sanitation coverage and quality may be especially important in urban areas given the proximity of compounds and the opportunity for person-to-person contact, neighborhood-level exposure, and for external sources of contamination (e.g. a neighbor’s flooded pit latrine) to influence compound-level exposures (Barreto et al., 2007). We did not measure neighborhood-level exposures, which may be important for young children in slum settings (Ezeh et al., 2017; Medgyesi et al., 2019), and their impact on our health outcomes is unclear. In addition to neighborhood-level exposures, the transience of the study population meant that trips to and from provinces outside of Maputo, where exposures were varied and unmeasured, were common.

It is unlikely that our findings are due to poor intervention fidelity or use, a challenge encountered in some trials of rural sanitation interventions (Clasen et al., 2014; Patil et al., 2014). The use of the intervention required minimal behavior change as compound members switched from using their existing latrine in poor condition, which was removed following construction of the intervention latrine, to using the new hygienic latrine. The results of a forthcoming process evaluation demonstrate that 96% of intervention latrines were well-maintained 2 or more years after construction, suggesting continued use by compound members (Bick, 2021). Further, only 3% of intervention compounds (8/270) had a secondary, non-intervention latrine in use after two or more years, indicating that members of most intervention compounds exclusively used the intervention latrines (Bick, 2021). It is possible that development in the study neighborhoods, including changes to sanitation facilities in control compounds, contributed to the limited effect of the intervention. However, results from sensitivity analyses that excluded control compounds with upgraded sanitation were consistent with results from the main analyses.

The two intervention designs we evaluated in this study – communal sanitation blocks and shared latrines – utilized the same basic sanitation technology but differed in the number of cabins and amenities available. While it is possible that this heterogeneity in design may have modified the effect of the intervention, this study was not powered to test this. Moreover, all intervention compounds were encouraged to independently upgrade their facilities by adding features like electricity and handwashing stations, or by connecting existing handwashing stations to the water supply, resulting in heterogeneity even within the two broad categories of intervention type.

While the NDC dewormed every study compound annually during the study period, it is possible that not all study participants received, or took, the medication and that the time between deworming and subsequent measurement of STH re-infection varied among children. Additionally, single-dose albendazole can have limited effectiveness against certain STH, notably Trichuris (Moser et al., 2017). Inadequate or ineffective deworming could have limited our ability to detect an effect on STH outcomes. Sensitivity analyses adjusting for caregiver-confirmed deworming and for estimated time between deworming and re-infection measurement produced similar results to the main analysis.

There are several important limitations of this study. As the intervention was pre-planned and not implemented by the study team, we could not randomize its allocation, increasing the risk of confounding. We assessed potential confounding variables at baseline and used a DID analysis, which accounts for baseline outcome measures, to limit the effect of unmeasured, residual confounding. While we attempted to enroll intervention and control compounds with comparable numbers of residents, the NGO which identified and implemented the intervention selected most of the largest eligible compounds for intervention. This resulted in intervention compounds having a slightly higher mean number of residents than control compounds (Table 1). Crowding has been identified as a risk factor for pathogen transmission and poor health outcomes in other studies (Halpenny et al., 2012; Rahman et al., 1985; Rogawski McQuade et al., 2020b), although we found limited evidence of this in our study population at baseline (Knee et al., 2018). Further, we assessed the number of compound residents as a potential confounder but found that it did not meaningfully change the DID estimates for our pre-defined outcomes (Appendix 1—table 9). We consider our analysis to be robust to small differences in study arms at baseline; however, we cannot exclude the possibility of residual confounding due to such differences, a limitation of non-randomized designs.

It was not possible to mask participants to their intervention status, and our measure of caregiver-reported diarrhea could be subject to respondent and recall biases. To reduce the risk of respondent bias, the MapSan field enumerator team and implementation team were different, and respondents were not informed explicitly that the MapSan team was evaluating the health effect of the intervention. To limit recall bias, we used a 7-day recall period (Arnold et al., 2013). Our other pre-specified outcomes were objective measures of pathogen infection and not subject to the same biases (Brown and Cumming, 2020).

Due to the greater than expected losses to follow-up in both study arms, we were not able to follow all children enrolled at baseline through time as expected, but we still achieved our target enrollment numbers due to migration and births into study compounds. We conducted the originally planned longitudinal analysis as a sub-group analysis. It also served as a sensitivity analysis to estimate the impact of migration on our effect estimates. Results from this sub-group analysis were largely similar to results of the main analysis which treated measures as repeated cross-sections, although the reduction in sample size led to wider confidence intervals (Appendix 1—table 14 and Appendix 1—table 15). Measures of outcomes and covariates in children with and without repeated measures were mostly similar, further limiting the likelihood that changes in the study population biased our results.

While molecular detection of enteric pathogens in stool is evidence of pathogen exposure, it is not necessarily evidence of active infection, making its clinical significance less clear (Brown and Cumming, 2020). We assumed pathogen detection by the GPP indicated infection because the assay’s limits of detection exceeded the median infectious dose of most pathogens. While the GPP detects many enteric pathogens recognized as important causes of childhood diarrhea in LMICs, (Liu et al., 2016) it does not detect all enteric pathogens of importance. Further, qualitative, cross-sectional analysis of stools does not provide information on the duration or intensity of infection or pathogen carriage. Quantitative results like those produced by multiplex quantitative PCR panels can be used to aid identification of etiologic agents of diarrhea, especially in cases of coinfection, and to differentiate between low-level enteric pathogen detection of unknown clinical relevance and higher concentration shedding which is more clearly associated with disease (Liu et al., 2014; Liu et al., 2016; Platts-Mills et al., 2013). Some studies have demonstrated overall good performance of the GPP but observed elevated false positive detection rates for the Salmonella targets (Duong et al., 2016; Kellner et al., 2019). For this reason we removed Salmonella results from our pre-specified outcome definition. Results from analyses including and excluding Salmonella were similar. In addition, some studies have observed reduced sensitivity or specificity for some GPP targets compared with qPCR-based methods, including norovirus, adenovirus, Campylobacter, Yersinia enterocolitica, ETEC, and Salmonella, although inconsistencies between studies exist and are likely due to differences in comparator assays or sample storage and processing (Chhabra et al., 2017; Deng et al., 2015; Duong et al., 2016; Huang et al., 2016; Zhan et al., 2020; Zhuo et al., 2017). Further, the lack of an adequate reference standard in most comparative studies complicates interpretation (Freeman et al., 2017b).

Our ability to detect an effect on our primary outcome, the prevalence of ≥1 bacterial or protozoan infection, may have been limited by (1) the extended duration of shedding of some pathogens following active infection; (2) the overall high burden of disease in our study population, particularly among older children; and (3) residual confounding by age given the strong observed relationship between age and infection status (particularly for protozoan pathogens), all of which may have biased our results toward the null. Further, the intervention may have impacted the concentration of pathogens shed (Grembi et al., 2020; Lin et al., 2019), but our binary outcome was not sensitive to such differences The qualitative nature of the GPP did not allow us to interrogate this question.

We analyzed a smaller number of stool samples for STH than for other enteric pathogens due to requirements of the Kato-Katz method used for STH detection. The Kato-Katz method can only be performed on whole, solid stool. Diarrheal samples and rectal swabs, the latter of which were introduced during the 12-month follow-up phase, were not eligible for STH analysis by Kato-Katz. Further, when limited stool material was collected, we prioritized the molecular analysis used for the primary outcome. While the smaller sample size available for the STH analyses may have reduced our ability to detect small effects, the proportions of whole stool, diarrheal diaper samples, and rectal swabs were similar between arms at each phase (Appendix 1—table 1). This limited the potential impact that sample type could have on our results.

While the Kato-Katz method performs similarly to other microscope-based and molecular methods for detection of moderate- to high-intensity infections, it may be less sensitive than molecular methods in detecting low-intensity infections (Benjamin-Chung et al., 2020; Cools et al., 2019). A recent study has also suggested reduced specificity of the Kato-Katz method for detection of low-intensity A. lumbricoides infections (Benjamin-Chung et al., 2020). In settings where low-intensity infections are common, or where STH may be targeted for elimination, methods with better diagnostic accuracy, like qPCR, may be considered.

We had limited ability to evaluate the impact of seasonality or weather-related trends on our effect estimates due to drought conditions during the 2015/2016 rainy season. We adjusted models for cumulative 30-day rainfall, a binary indicator of wet/dry season, and sine/cosine terms of sample collection date (Stolwijk et al., 1999) but excluded all seasonality terms from final multivariable models because they did not meaningfully change effect estimates.

Our results demonstrate that access to hygienic, shared onsite sanitation systems was not sufficient to reduce enteric infection or diarrhea in children aged 6 years or younger (≤4 at baseline) 12–24 months after implementation. Results from our sub-group analysis of children born into intervention sites showed a substantial reduction in the prevalence of any STH, Trichuris, and Shigella infection, suggesting that children may require protection from birth to reduce or delay infection burdens. Our results do not suggest that shared sanitation is inadvisable in this setting, as we did not compare against household-level sanitation improvements, nor do they account for the many non-health-related benefits associated with this intervention or upgraded sanitation generally (Caruso et al., 2018; Sclar et al., 2018; Shiras et al., 2018).

The need for effective sanitation solutions may be most urgent in densely populated, low-income, informal communities like our study setting where ubiquitous fecal contamination drives high infection burdens. Disease transmission in these settings may be driven by multiple interrelated pathways, complicated by frequent migration and the diversity of circulating pathogens, and therefore difficult to interrupt. While decades of research have demonstrated meaningful health gains following sanitation improvements, the results of this study and other rigorous trials of sanitation interventions suggest that the relationship between sanitation and health is complex, difficult to measure, and may not be generalizable across diverse settings and populations.

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files and code have been provided for all analyses and specifically for Figure 1 and Tables 1, 2, and 3. Additionally, we have archived all data and code at Open Science Framework (https://osf.io/me2tx, DOI 17605/OSF.IO/ME2TX).

1. 1. Brown J

   (2020) Open Science Framework

   ID me2tx. Effects of an urban sanitation intervention on childhood enteric infection and diarrhoea in Mozambique.

   https://osf.io/me2tx/