COLLABORATIVE MAPPING AS A METHODOLOGY FOR IDENTIFYING COMMUNITY PERCEPTIONS ON BASIC SANITATION NEEDS AND INTERVENTIONS FOR LEPTOSPIROSIS IN SALVADOR, BRAZIL

This study demonstrates that collaborative mapping with residents of two peripheral communities in Salvador, Brazil, effectively identified specific local sanitation needs and intervention priorities—particularly regarding sewage and waste management near local rivers—that are essential for preventing leptospirosis, revealing a negative correlation between perceived intervention needs and predicted disease seropositivity.

The Gist

Imagine a city as a giant, complex machine. Sometimes, parts of that machine start to rust and break down, making people sick. In the city of Salvador, Brazil, two neighborhoods on the edge of town (called "peripheral communities") were struggling with a specific kind of rust: leptospirosis. This is a disease spread by rats and dirty water, often caused by poor sanitation.

For a long time, the people in charge of fixing the city (the government and scientists) looked at maps to decide where to send help. But these maps were like old, blurry photographs—they missed the details of the messy, real-life streets where people actually lived. They didn't show the puddles, the clogged drains, or the piles of trash that the residents saw every day.

The Big Idea: Let the Locals Draw the Map
Instead of just looking at the blurry photo, the researchers decided to hand the crayons to the residents. They used a method called "Collaborative Mapping."

Think of it like this: If you want to know the best route through a forest, you don't ask a satellite; you ask the hiker who walks there every day. The researchers gathered 213 neighbors and said, "Show us where the problems are. Draw them on the map."

What the Neighbors Drew
When the residents drew their map, they didn't just point to one thing. They highlighted two main "villains":

1. The Sewage System: It was like a clogged artery in the body. People wanted pipes fixed, sewers cleaned, and open rivers covered up so dirty water wouldn't splash on them.
2. The Trash: They pointed to squares and streets where garbage was piling up, acting like a magnet for rats.

Interestingly, the residents knew exactly what they needed. Some wanted new pipes built (construction), while others just wanted the existing pipes cleaned out (maintenance). They were very specific about where the work needed to happen, usually clustering around the local river that ran through their neighborhoods.

The Surprise Twist
Here is where the story gets fascinating. The researchers also used science to predict where the disease risk was highest. They built a "risk model" (like a weather forecast for sickness) based on soil, distance to roads, and other data.

They expected the residents' drawings to match the scientists' predictions perfectly. They thought, "If the model says this spot is dangerous, the people will say, 'Fix this spot!'"

But they didn't match.
The scientists' model showed "hotspots" of danger in some areas, but the residents didn't mark those spots as their top priority. Instead, the residents were focused on the river.

Why? Because while the scientists were looking at invisible bacteria risks, the residents were dealing with the visible reality: the bad smell, the mosquitoes, the flooding, and the trash floating in the water. To them, the river wasn't just a risk factor; it was a daily nuisance that made life hard. They were fighting the immediate fire, while the scientists were worried about the smoldering embers.

The Lesson
This study teaches us a valuable lesson about fixing broken systems: You can't just fix what you see on a map; you have to fix what people feel in their bones.

If the government builds a fancy new pipe in a spot the scientists picked, but ignores the trash pile the residents are pointing at, the rats will still be there, and the disease will still spread.

The Takeaway
To stop diseases like leptospirosis, we need a team effort. We need the scientists' data and the neighbors' crayons. We need to listen to the people living in the "rusty" parts of the machine. When we combine the high-tech risk models with the low-tech, real-life wisdom of the community, we can build solutions that actually work, keep people healthy, and make the whole city machine run smoother.

In short: Don't just map the problem; map the people.

Technical Summary

1. Problem Statement

Leptospirosis, a neglected zoonotic disease caused by Leptospira bacteria, disproportionately affects populations in low-and middle-income countries (LMICs), particularly in peripheral urban communities with precarious sanitation and infrastructure. While spatial mapping is a standard tool for analyzing health risks, traditional methods often render these vulnerable communities "invisible" or fail to incorporate local knowledge.

• The Gap: Existing official maps often lack updated data on hard-to-reach areas and do not encourage community participation. Consequently, sanitation interventions are frequently implemented without aligning with the specific needs and perceptions of residents, leading to ineffective outcomes and a lack of sustainability.
• The Objective: To utilize collaborative mapping to identify the perceived basic sanitation needs of residents in two peripheral communities in Salvador, Brazil, map the spatial distribution of these needs, and analyze their relationship with the objective risk of leptospirosis infection.

2. Methodology

The study employed a cross-sectional design integrating participatory research methods with epidemiological modeling.

• Study Setting: Two peripheral neighborhoods in Salvador, Brazil: Nova Sussuarana (NS) and Jardim Santo Inácio/Mata Escura (JSI/ME). These areas are characterized by low-income populations, high rates of self-declared Black ethnicity, and significant sanitation deficits.
• Participants: A census sample of 213 self-declared heads-of-households (107 in NS, 106 in JSI/ME) who had previously participated in a serological survey.
• Data Collection (Collaborative Mapping):
  • Training: Community researchers and residents underwent training on collaborative mapping concepts, territorial reading, and the use of web-mapping tools (Vicon Saga) and GIS (QGIS).
  • Fieldwork: Residents used printed maps to mark locations of sanitation needs. They identified specific components (sewage, water supply, urban cleaning, drainage) and suggested intervention types (implementation, maintenance, removal, integrated action).
  • Validation: Data was categorized through thematic analysis and validated by a basic sanitation specialist.
• Serological Data: Leptospirosis exposure was determined via the Microscopic Agglutination Test (MAT), the gold standard, using a panel of prevalent serovars. Seropositivity was defined as a titer $\ge$ 1:50.
• Statistical Analysis:
  • Risk Modeling: A binomial Generalized Additive Model (GAM) was used to predict leptospirosis seropositivity probabilities across the study areas. Covariates included household distance to pruning rubbish piles, soil land cover percentage (within a 20m buffer), age, gender, and study area.
  • Correlation Analysis: A Poisson regression model assessed the relationship between the predicted probability of seropositivity (objective risk) and the density of perceived intervention needs (subjective perception) across a 5-meter grid.

3. Key Contributions

• Methodological Innovation: The study demonstrates the efficacy of collaborative mapping as a tool for co-producing spatial data in marginalized communities, bridging the gap between official data and local reality.
• Community-Centric Diagnosis: It shifts the focus from top-down risk assessment to a bottom-up approach where residents define the problems and propose solutions, specifically identifying the "invisible" needs of peripheral urban areas.
• Integration of Qualitative and Quantitative Data: The research uniquely correlates subjective community perceptions of sanitation needs with objective serological risk models, providing a nuanced view of health determinants.

4. Key Results

A. Perceived Sanitation Needs

• Primary Needs: Sewage was the most critical perceived need in both communities (87.1% in NS; 84.9% in JSI/ME), followed by urban cleaning and solid waste management (25.9% in NS; 32.6% in JSI/ME).
• Intervention Types:
  • NS: Residents prioritized integrated actions (cleaning + sealing/piping) and new construction of sanitary sewage networks.
  • JSI/ME: Residents focused on sewage sealing, piping, and maintenance (cleaning).
• Spatial Distribution: Perceived intervention needs were heavily clustered around the local river in both communities, which residents viewed as an open sewer due to pollution and lack of infrastructure.

B. Seroprevalence and Risk Modeling

• Seroprevalence: Baseline unadjusted seroprevalence was 9.0% in NS and 8.0% in JSI/ME.
• Risk Hotspots: The predictive model identified "hotspots" of leptospirosis risk, with probabilities reaching up to 49.9% in NS and 44.3% in JSI/ME. These hotspots were not always aligned with the areas where residents perceived the highest need for intervention.

C. Correlation Between Perception and Risk

• Negative Correlation: A significant negative correlation was found between predicted leptospirosis seropositivity and the density of perceived intervention needs in most categories.
  • In NS, higher predicted risk correlated with lower density of perceived needs for sewage, urban cleaning, and drainage.
  • In JSI/ME, higher predicted risk correlated with lower density of perceived sewage needs but a slight increase in perceived urban cleaning needs.
• Interpretation: Residents did not identify the specific "hotspots" predicted by the biological model. Instead, their concerns were driven by immediate environmental nuisances (odors, flooding, trash accumulation) around the river, rather than the abstract risk of infection in specific peri-domiciliary zones.

D. Demographic Insights

• Gender: Women reported higher densities of perceived needs than men, though the relationship between perception and risk did not vary by gender.
• Serostatus: Seropositive individuals in NS only identified sewage needs, whereas seronegative individuals reported a broader range of needs.

5. Significance and Implications

• Policy Relevance: The findings highlight a disconnect between scientific risk models and community priorities. Effective public health interventions must align with local perceptions to ensure community buy-in and sustainability.
• Sanitation Strategy: The study argues for integrated basic sanitation interventions that combine sewage management, solid waste removal, and river remediation. It suggests that "sealing" polluted rivers (a common practice in wealthier areas) may be necessary in these contexts to prevent direct contact with contaminated water, even if ecological restoration is the ideal long-term goal.
• Participatory Governance: The research supports the institutionalization of collaborative mapping in municipal health strategies (e.g., Brazil's National Secretariat of Peripheries) to ensure that sanitation policies are socially appropriate and address the actual vulnerabilities of peripheral communities.
• Disease Prevention: By addressing the specific sanitation gaps identified by residents (particularly around rivers and waste accumulation), interventions can more effectively reduce the environmental determinants of leptospirosis and other zoonotic diseases.

Conclusion: The prevention of leptospirosis in peripheral urban communities requires moving beyond purely technical risk modeling. It demands integrated sanitation interventions that are co-designed with residents, addressing both the objective biological risks and the subjective, lived experiences of environmental degradation.