Whispers of the Outbreak: Modeling Hidden Cholera Transmission in Informal Settlements

Davide Rinaldi¹, Eleni Kosta², Yun Zhao³

Abstract

Background:
Cholera outbreaks in informal settlements are often under-reported due to limited surveillance infrastructure, stigma, and delayed health-seeking behaviors. Traditional surveillance systems fail to capture these "silent" transmission zones, leading to underestimated risk and delayed interventions.

Objective:
To develop and validate a predictive model for identifying hidden cholera transmission clusters in urban informal settlements using syndromic, spatial, and environmental data.

Methods:
A retrospective cohort analysis was conducted using health and environmental data from 47 informal settlements in Dhaka, Bangladesh and Nairobi, Kenya, collected between January 2020 and June 2023. Reported diarrhea cases, rainfall, latrine proximity, population density, and mobile clinic reports were integrated into a spatial-temporal Bayesian model. Hidden transmission was inferred by comparing observed vs. expected case distributions and validating with stool sample positivity rates.

Results:
The model identified 26 high-probability hidden clusters where case reporting was below 30% of predicted burden. Incorporating environmental variables improved the model’s AUC from 0.71 to 0.88. Areas within 150 meters of open drainage and high foot traffic were 3.2× more likely to host hidden clusters (OR: 3.2, 95% CI: 2.1–5.0, p < 0.001). Community-based stool testing confirmed Vibrio cholerae in 17 of 26 flagged clusters.

Conclusion:
Silent cholera transmission in informal settlements can be effectively modeled using combined syndromic and spatial predictors. This approach reveals outbreak dynamics overlooked by routine surveillance and supports early, targeted intervention. Integrating such models into city-level health dashboards could revolutionize outbreak prediction in vulnerable communities.