For total nucleic acid extraction from 100 mg of stools and fecal sludges (wet-weight), we followed a pre-treatment protocol validated for multiplex PCR (Text S3).^23,37,38 We proceeded with extraction following the manufacturer’s protocol for the QIAamp 96 Virus QIAcube HT Kit, which we automated on the QIAcube (Qiagen, Hilden, Germany). We included MS2 as an extraction control. To determine the solids content of fecal sludges, we adapted the oven drying method (Text S3).³⁹

Recent advances in multiplex PCR assays enable rapid and simultaneous detection of pathogens from a variety of samples types^23,37,40, providing a useful molecular method for pathogen surveillance. One such platform, the TaqMan array card (TAC), is a 384-well microfluidic card that can be customized using validated assays^40–42, and therefore is suited to detect a wide range of pathogens that may vary by setting²². We tested all samples using a custom TAC (ThermoFisher Scientific, Waltham, MA) that tested for 20 enteric pathogens, including ten bacteria, five viruses, three protozoa and two soil-transmitted helminths (STH) in duplicate (Text S4, Table S1, Table S2). We included a positive and negative control on each TAC (Text S4). We visually compared exponential curves and multicomponent plots with the positive control plots to validate positive amplification. Samples that exhibited positive amplification in either duplicate well before a quantification cycle (Cq) of 40 were considered positive (Table S3).

We collected stools from 95 children who ranged in age from 1–82 months (median = 37 months, mean = 39 months, SD = 21 months). In stools, we most often detected pathogenic bacteria (96%, [91/95]), followed by protozoa (68%, [65/95]), STHs (53%, [50/95]) and viruses (28%, [27/95]) (Table S4, Table S5). Out of 20 pathogens, we detected a mean of 3.9 pathogens per stool on average (mean=3.9 out of 20, median=4.0, range=0–9), which is similar to children living in other LMICs²². Adjusted for wealth score, compound population, and the type of onsite sanitation, we found stools from the oldest children (48–82 months) had no difference in the number of pathogenic bacteria (aPR = 1.3, 95% CI [0.87, 1.9]) or protozoa (aPR = 1.3 [0.66, 2.6]), but observed a lower number of viruses (aPR = 0.17 [0.05, 0.57]), and a greater number of helminths (aPR = 4.3 [1.8, 10]) compared to the youngest children (1–23 months) (Table 1). This sub-sample of 95 stools collected from children in the MapSan cohort yielded consistent estimates of prevalence with the MapSan trial baseline (n = 759)²³ conducted 24–36 months earlier: we detected all pathogens in each taxa in the same rank order except for Campylobacter and STEC, which were infrequently detected at MapSan baseline (8% and 2% prevalence, respectively)²³.

We collected 52 fecal sludge samples from pour-flush to septic tank sanitation systems and 43 from pit latrines. The mean number of people per compound was 15 (SD=7, median=13, range=4–38). In fecal sludges we commonly detected all types of pathogens (bacteria: 95%, [90/95], STHs: 95%, [90/95], viruses: 91%, [86/95], protozoa: 88%, [84/95]) and in high number (mean=7.9 out of 20, median=8.0, range=0–14). In addition, adjusted for wealth score, compound population, and fecal sludge solids content, we found septic tank systems were associated with a reduced number of bacterial pathogens (aPR = 0.66, 95% [0.50, 0.86]) compared to pit latrines (Table S6).

Among all stools and fecal sludges, the six most frequently detected bacterial pathogens were the same in both matrices and were detected in the same rank order (Table 2). We did not observe the same pattern for the viral pathogens, and the prevalence of all viruses was much greater in fecal sludges than in stools. We detected all three protozoan pathogens in the same order of prevalence in stools and fecal sludges. We detected Trichuris more frequently than Ascaris in stools but detected Ascaris more frequently than Trichuris in fecal sludges. Stratifying our analysis by sanitation type (pit latrines and septic tanks), the six most frequently detected bacteria were different for pit latrines and septic tanks, but for each type of infrastructure the six most frequently detected bacterial pathogens were still detected in the same rank order as matched stools (Table S7).

We detected every pathogen except Campylobacter more frequently in fecal sludges than in stools. Because we detected pathogens more frequently in sludges than in stools, the Jaccard similarity coefficients were highest among pathogens with the greatest prevalence in stool, lowest for pathogens with lowest prevalence in stools, and were zero for all bacterial pathogens detected in less than 10% of stools (Table 2). For bacteria, protozoa, and STHs matched detections in stools and fecal sludges tended to increase with increased prevalence in stool; in at least half of the instances, all viruses detected in stools were detected in matched fecal sludges (Table 2). Specifically, when EAEC, rotavirus A, Giardia duodenalis, Entamoeba hystolytica, and Ascaris lumbricoides were detected in a stool, they were also detected in the matched sludge at least 80% of the time. These observations suggest that, for these pathogens, sludge may be a useful proxy for prevalence of shedding among children in this setting.

The same rank order of bacterial and protozoan pathogens in fecal sludges from pit latrines and septic tanks compared with pathogens in stools provides evidence that fecal sludges may be a reliable endpoint for enteric pathogen surveillance in low-income urban settings for at least some pathogens. However, the Jaccard similarity coefficients for 18 of the 20 pathogens assessed were less than 50%, indicating infrequent co-detection of pathogens in matched stools and sludges. Accordingly, surveillance of onsite sanitation systems may better provide a community-level snapshot of circulating pathogens, while being a poor predictor of individual prevalence.

While substantial overlap in gut microbiota has been observed among household members in previous studies,^49,50 suggesting that gut pathogen carriage may be comparable among those sharing living spaces, stool samples from any individual may not be representative of pathogens shared by others. We compared single stool samples from children with fecal sludges from latrines serving an average of 15 people, including adults. Of the 20 pathogens assessed, the number of detections in fecal sludges (n = 7.9) was twice that of stools (n = 3.9), reflective of the fact that sludge represents a composite of multiple individuals’ feces. Indeed, the total number of detects would necessarily increase unless pathogens were evenly distributed across all individuals. Furthermore, some children’s stools may not have been deposited in latrines.⁵¹ These factors may explain why we did not observe high Jaccard similarity coefficients between fecal sludges and individual stools.

Variations in the detected order and prevalence between stools and sludges – especially among viral targets – suggests additional work is needed to interpret pathogen detection based on shedding rates in stool^52,53, fate and transport^53–55, biological and environmental factors^53–55, assay limits of detection, and potential differences in nucleic acid extraction kit efficiencies. Such factors may explain why we did not detect viruses and STHs in fecal sludge in the same rank order as in stool samples. Ascaris can persist longer in the environment than Trichuris⁵³ but MDA to treat helminthiasis is less effective for Trichuris than Ascaris.⁵⁶ Children enrolled in the MapSan trial received single-dose albendazole before the 24-month follow-up period, which may explain why we detected Trichuris more often in stools but Ascaris more often in sludges. While we detected bacterial pathogens in the same rank order in stools and sludges, environmental dynamics such as die-off and re-growth⁵⁷ could produce a different result in other settings. During viral gastroenteritis viruses are shed in high concentration (≤10¹⁰-10¹² per gram feces)^52,53 and viral infections were associated with symptomatic diarrhea in Maputo.¹¹ Watery diarrheal stools may result in greater spatial distribution inside a latrine compared to solid stools, and may explain why we often detected viruses in sludges despite a relatively lower prevalence in stools. As expected from a previous studies in Maputo²³ and Manhiça, Mozambique^22,58, we observed increasing age was associated with a reduced number of pathogenic viruses, and a greater number of pathogenic protozoa (though not after correcting for multiple comparisons) and STHs. As children age their mobility and consumption of food and drinking water increases, which increases infection risks. However, as children in LMICs begin walking on their own, their contact with other people may decrease, potentially decreasing their infection risk from viruses spread via person-to-person transmission⁵⁹. Considering sludges are a composite from individuals with a wider range of ages than the stools we measured, it is logical the rank order of viruses and STHs in sludges may not align with the rank order of stools from young children alone, since the pathogen shedding profile in infants and children may differ from others also contributing waste to the latrine. In addition, the difference in prevalence of the three pathogenic protozoa in stools was large and may have limited the potential for change in the rank order detection from stool to sludge.

As a cross-sectional study we were unable to assess the sensitivity of pathogen signals to changes in disease prevalence or incidence over time, though this is a logical next step for further research. Longitudinal studies of fecal sludges in LMICs are required to assess such changes over time, including utility in detecting disease outbreaks⁶⁰ and to assess if sludges are useful for health impact assessment in water, sanitation, and hygiene (WASH), vaccine, and MDA intervention trials. We observed the same rank order prevalence for bacterial and protozoan pathogens from both pit latrines and septic tanks, except we detected fewer bacterial pathogens in septic tank sludges, and the six most prevalent bacterial pathogens were different between the two systems. Stratification of data by onsite sanitation infrastructure type may provide helpful nuance to understanding circulating pathogens. This level of detail suggests that fecal sludge surveillance may offer greater insight into circulating pathogens at a finer spatial scale compared to dilute wastewater samples which may be more representative of an entire sewershed.

Future work is needed before fecal sludge surveillance can be scaled and used in LMICs. First, we collected one sample per sanitation system in a 50 mL centrifuge tube at a single point just below the surface of the solids. It is plausible the sludges we collected represented older feces than those at the solids surface and may offer a longer-term snapshot of community infections compared to wastewater. More work is needed to standardize sample collection techniques, which may include collecting and homogenizing a larger volume of sludge from each system. Second, quantitative work is needed to assess differences in pathogen concentration and nucleic acid recovery between stools and sludges and to reconcile potential differences in limits of detection. Such concentration data would be helpful for risk assessment modeling⁶¹, to assess the sensitivity of signals in sludges to the number of individuals contributing waste, and to monitor temporal changes. Third, decay experiments are needed to characterize pathogen persistence in fecal sludges, including for pathogen nucleic acids that would typical be detected via methods similar to those we used in this study. Finally, compared with PCR-based methods, metagenomics should be explored as it offers an unbiased approach to assess the microbial community in onsite sanitation systems, and may be desired for comparison with global wastewater surveillance efforts¹⁵. Applying these methods for tracking specific pathogens may be limited by comparatively high detection limits and a lack of capacity for analysis in high-burden settings, however.

The ability to capture the relative frequency of enteric pathogens in a community – without the logistical constraints and invasive nature of stool collection – offers the opportunity to rapidly gather novel and actionable information regarding community health. In urban settings with limited resources, surveillance of fecal sludges may be a cheap and scalable option to monitor emerging pathogens.¹¹ Applying the principles of wastewater-based surveillance to areas covered by onsite systems is promising, but future work is needed to standardize methods and better characterize and interpret observed pathogen signals. Advances in surveillance where data are limited may help develop and prioritize appropriate and effective strategies to reduce infection risk.