Trichy is in the South of India on the banks of the Cauvery River in Tamil Nadu State (Rohilla et al., 2015). The city covers an area of 167.23 km² and is subdivided into 65 wards, in four zones. It has a tropical climate and has no major change in temperature between summer and winter (Rohilla et al., 2015). The population of the city was calculated to be 1,104,710 with an estimated household size of four (Safi, 2019).

The changes in the SSC both in the service delivery and the enabling environment from 2015 to 2019 were analyzed through reviews of secondary data, interviews of key informants with the city stakeholders, and observations (Safi, 2019). The data collection was guided by the SFD manual (SFD-PI, 2018a). It took approximately 2 months to collect the data, with the aid of a local organization that acted as a gatekeeper to the sanitation community.

The 2019 SFDG for the city was developed based on the data collected (SFD-PI, 2018a). A new SFDG for 2015 was developed as the design of the SFDG had changed; this was to enable easier visual comparison. The original SFDG (Rohilla et al., 2015) was updated in collaboration with the authors as it was known that it did not capture all the onsite sanitation systems in Trichy. Trend Graphs were also developed from the SFDG data, to assess their use when comparing data visually (Martinez, 2016).

The CSDAs of 2015 and 2019 for Trichy were developed as per the CWIS CSDA Guideline (Blackett and Hawkins, 2020). The CSDA for 2015 was developed using the SFD Report data (Rohilla et al., 2015) and key informant interviews (Safi, 2019). For the 2019 CSDA, data collection was guided by the SDF Manual (SFD-PI, 2018a). Details of the data collected can be found in Safi (2019). The initial CSDAs were developed by the researcher. These were then validated in consultation with sanitation stakeholders and experts in Trichy, as documented in Safi (2019). Citywide CSDAs were developed for each year to assess their use when comparing the data visually (Safi, 2019).

The SFDG shows the status of service delivery in the form of percentage population (SFD-PI, 2018a). The sensitivity of the SFDG is 1% of the population (SFD-PI, 2018a). The CSDA is more complex as each pillar is divided into three indicators (Figure 3), and then each indicator is subdivided into one to four sub-indicators which are scored 0, 0.5, or 1 (Blackett and Hawkins, 2020). Scoring is based on the existence, appropriateness, acknowledgment and implementation of each sub-indicator, e.g., 0 = not available/inappropriate, 0.5 = appropriate but not widely known, 1.0 = widely known and acknowledged, available and fully implemented (Blackett and Hawkins, 2020). The sub-indicator scores are then averaged to give the indicator score (Blackett and Hawkins, 2020). The indicator scores are then classified as either poor (red) 0–0.4, improving (yellow) 0.5–0.7, or satisfactory (green) 0.8–1.0 (Figure 3). The sensitivity of the tools is related to their original aim, so the ability of each tool to capture change needs to be assessed.

The SFDGs for 2015 and 2019 can be found in Figures 2A,B. In Figure 2A, it can be seen that 41% of the population were using onsite sanitation and 59% offsite sanitation (Rohilla, et al., 2015), and this remained the same in 2019 (Figure 2B).

The most noticeable change when comparing Figures 2A,B was the 8% increase (from 66% to 74%) in safely managed excreta across the city, caused mainly by the elimination of direct discharge to open drains and reduction in open defecation. This can be attributed to the following changes across the SSC:

1) Containment (6%): This improvement was due to the construction of new individual and community/public toilets, upgrading of existing unsanitary toilets, conducting information, education, and communication activities (Table 1, Interventions 1, 3, 2, and 10).

Only Interventions 8 and 9 in Table 1 were not captured in the SFDGs, as they had not been fully implemented. The visual comparison of the two SFDGs (Figures 2A,B) took skill, time, and was tedious, as some changes were not easily seen. Therefore, Trend Graphs were developed as in Martinez (2016) (Figure 2C). These graphs captured the individual impact of interventions of the service delivery as in the original SFDGs. Trend Graphs (Figure 2C) more clearly show the overall change in each of the components of the sanitation service chain. The data are not disaggregated between onsite and offsite, but as the tools are being explored to monitor citywide sanitation, this level of detail is not required.

The SFDGs and Trend Graphs only captured change at the level of ±1% population, for Trichy in 2019. This equates to 11,047 population or 2,761 households. The magnitude of the change is dependent on the scale of the intervention in relation to the population of the city, e.g., in Trichy an additional 3,080 new sewer connections, serving an approximate population of 12,320, (Table 1, Intervention 4), is approximately a 1% improvement in the safe containment in 2019. Therefore, the magnitude of any interventions needed to keep pace with population growth. The effect of population growth was noted to be a major factor when using these tools to model future sanitation scenarios, as little impact was seen with many of the proposed interventions (Martinez, 2016). These units are thought to be appropriate for citywide monitoring as it ensures services are keeping pace with population growth.

The offsite and onsite CSDAs were developed for the years 2015 and 2019 (Figures 3A,B) and were compared separately with the documented changes (Table 1).

Containment changed from 0.7 (improving) to 1.0 (satisfactory) in offsite sanitation (WC, house connection), whereas it changed from 0.7 (improving) to 0.8 (satisfactory) for onsite sanitation (toilet, pit, or septic tank) (Figures 3A,B). Emptying and transport in offsite sanitation (sewerage) changed from 0.8 to 1.0 (remained satisfactory), while in onsite, they changed from 0.3 (poor) to 0.7 (improving). For treatment and reuse, in onsite and offsite sanitation, the rating did not change as it gained the highest rating, 1.0 (satisfactory) in 2015, and it remained at this level. For onsite sanitation, these changes were linked to Interventions 11 and 13 (Table 1) and general improvement in sanitation can be attributed to the implementation of Intervention 12, Table 1.

For containment, offsite sanitation changed from 0.3 (poor) to 0.8 (satisfactory) and, for onsite sanitation, from 0.3 (poor) to 1.0 (Figures 3A,B). The remaining two steps of the SSC in both systems changed to 0.8 (satisfactory) from 0.5 (improving) in offsite and 0.3 (poor) in onsite. These changes are linked to Interventions 14 and 15, but mainly 17, as this included the budget, (Table 1).

This indicator remained at 0.5 (improving) for both offsite and onsite for containment, and emptying and transport (Figures 3A,B). The policy, planning, and budgetary arrangements before 2015 include some aspects of inclusion; hence, the initial scores were 0.5. Although CWIS was being implemented in Trichy in 2019, it was only at the planning stage and had not yet been implemented, so no change was captured in the CSDA for this indicator as no changes had occurred.

For all parts of the offsite, SSC changed to 0.7 (satisfactory), from 0.5 (improving) or 0.3 (poor) (Figures 3A,B). For onsite sanitation, containment changed from 0.5 (improving) to 1.0 (satisfactory), emptying and transport changed from 0.2 to 0.3 (remaining poor), while treatment and reuse changed from 0.3 (poor) to 0.8 (satisfactory). These changes were linked to Interventions 15 and 17 (Table 1). As no significant public funds were assigned for transport and emptying in these interventions, these scores increased only slightly. The CSDAs only capture public funding, so although 20 new vacuum tankers were purchased by private operators, this was not captured.

The score increased in all parts of the offsite SSC from 0.7 (improving) to 0.8 (satisfactory) (Figures 3A,B). While in onsite sanitation, the scores for containment, and emptying and transport increased from 0.3 (poor) to 0.5 (improving), and for treatment and reuse, the scores changed from 0.7 (improving) to 0.8 (satisfactory). These slight improvements were linked to the implementation of outreach activities (Intervention 10, Table 1).

Remained at 0.5 (improving) from 2015 to 2019 in both the offsite and onsite for containment, and emptying and transport (Figures 3A,B). Delivery before 2015 includes some aspects of inclusion; hence, the initial score was 0.5. Although CWIS was being implemented in Trichy in 2019, it was only at the planning stage and had not yet been implemented, so no change was captured in the CSDA for this indicator as it has not occurred.

For offsite sanitation, the score remained the same: 0.7 (improving) across the SSC (Figures 3A,B). This is the same for onsite sanitation for emptying and transport, treatment, and reuse, except the score for containment, remained 0.5. Although Intervention 13 (Table 1) was implemented by the municipality, it was not fully enforced, so no improvement was shown on the CSDA for onsite sanitation. As the new guidelines and rules for containment (Intervention 16, Table 1) were reiterations of previous rules and guidelines, no improvement was shown on the CSDA.

The scores remained the same: 0.5 (improving) for offsite sanitation and 0.4 (poor) for onsite from 2015 to 2019 (Figures 3A,B). No new interventions relating to these sub-indicators could be found; the scores remained the same.

The scores remained 0.5 (improving) for containment, and emptying and transport in both onsite and offsite (Figures 3A,B). Sustaining before 2015 includes some aspects of inclusion; hence, the initial score was 0.5. Although CWIS was being implemented in Trichy in 2019, it was only at the planning stage and had not yet been implemented, so no change was captured in the CSDA for this indicator as it has not occurred.

Not all interventions on Table 1 were captured in the CSDA, due to the scoring of the sub-indicators being related to the appropriateness, level of acknowledgment, or implementation, rather than the existence of an intervention. The scoring system and its sensitivity were deemed appropriate for monitoring changes at a citywide level, as it was able to capture changes that occurred over the 4 years. Increasing the levels in scoring criteria would add additional complexity to the tool and make it harder to score, as differences between the categories would be reduced. As the CSDA only covers the public sector, this means any improvement due to the private sector such as investments were not captured. This may lead to sections of SSC on the CSDA being rated lower than they are in reality. As there is no indication of the percentage population using each type of sanitation system, the most dominant type of sanitation within the city cannot be identified. Therefore, they must be used in conjunction with an SFDG (Figures 2A,B), which contains these data. Another option is to develop a Citywide CSDA for each year by weighting the CSDA indicator scores for offsite and onsite sanitation by the percentage of the population using each type of sanitation (Safi, 2019). This CSDA then reflects the enabling environment at a citywide level for a given year (Figure 3C) and makes the comparison of the changes easier to analyze.

In general, onsite sanitation scored lower than offsite sanitation across all pillars in both 2015 and 2019 (Figures 3A,B), and 41% of the population used this type of sanitation system in both years. This is reflected in the lowering of the Citywide CSDA indicator scores (Figure 3C) compared with the score for offsite sanitation in each year. The sanitation situation in Trichy was unusual, as the percentage of the population using onsite and offsite was almost equally split (Figures 2A,B). In a study of sanitation in 39 low- and middle-income cities, similar sanitation was only found in five cities (Peal et al., 2020). Although this situation seems to be more common in India, 27% of the cities in India in this study had similar sanitation situations (Peal et al., 2020). If there was a more dominant sanitation type, the Citywide CSDA would reflect this and may hide the sanitation needs of the marginalized as they may be using a different sanitation system compared with the majority of the population. As all three pillars in the CSDAs (Figures 3A–C) have an inclusion indicator, this should capture inequalities in the sanitation focus of a city, but this needs to be evaluated further. As CSDAs and Citywide CSDAs have not been widely used, the authors recommend further piloting of these tools for monitoring purposes, paying special attention to their ability to capture inclusion. A further development would be to trial change CSDAs (Safi, 2019), which capture the change in the enabling environment on one CSDA.

Although piloting of these tools to monitor changes in citywide sanitation was deemed to be successful, several limitations or challenges were noted. Extensive data is required for both the development of the SFDGs and CSDAs. Trichy was purposively chosen for this study as data on sanitation were readily available and accessible [an initial SFDG already existed (Rohilla et al., 2015), a citywide sanitation plan was available (TCC, 2018), and it has adopted a CWIS approach (Safi, 2019)], this may not be the case in other cities. Even with these data being available, the data collection period took 2 months; in cities where less data are available, it may take longer, although it should be noted that the researcher was not from the sanitation sector in Trichy, so the data collection period stated could be an overestimation of the time required. In most cities, there is a general lack of data on sanitation, which means that some assumptions will need to be made. Guidance on these assumptions is given in the manuals of the tools (SFD-PI, 2018a; Blackett and Hawkins, 2020). All assumptions made were validated in consultation with sanitation stakeholders and experts in Trichy before the final CSDAs and SFDGs were developed (Safi, 2019). The biases of the sanitation stakeholders and experts need to be considered in this process, as there may be political reasons for them wanting the current sanitation situation to be seen as being worse or better than it is. These biases can be and were minimized by consulting with a broad range of sanitation experts and stakeholders from different organizations within a city. The final outputs of these tools could be seen as being subjective, due to the methods and assumptions that are required. This is because both tools were designed for advocacy and therefore not designed to be accurate or precise (SFD-PI, 2018a; Blackett and Hawkins, 2020). This subjectivity is and was minimized by validating the outputs of these tools with a wide range of sanitation stakeholders and experts. The analysis and comparison of the output of the tools were done by visual comparisons without guidance, and it was noted to be time consuming and tedious. Additionally, this could be seen as being subjective. Guidance for these comparisons could be developed, or software could be produced to aid this process. This software could generate a short report or graphic noting the positive and negative changes in sanitation at a citywide level. Although some of these data were in the public domain, some of the data required could be seen as being sensitive, e.g., performance of sewage treatment plant; hence, the results could also be deemed as being sensitive, as cities may not want to highlight slippages in sanitation coverage, which could be linked to the units used, e.g., the city may be increasing sanitation coverage in terms of numbers, but not keeping up with population growth. Most of the limitations in terms of subjectivity and biases discussed can be overcome or minimized by consulting and working with a wider range of sanitation stakeholders and experts, meaning that this is not a standalone process, and it should be done in conjunction with the sanitation community. This can be difficult to do if there is a lack of political buy-in or an undeveloped sanitation sector in a city. In these cities, the tools could be used to monitor changes in sanitation, but the lack of data, assumptions, and potential biases should be acknowledged. Undertaking this process may even stimulate political buy-in and the development of the sanitation sector in these cities.