M-SDT: A modelling framework for dengue transmission, forecasting, and intervention strategies in Ahmedabad Municipal Corporation

TL;DR

This paper introduces M-SDT, a data-driven compartmental model for dengue transmission in Ahmedabad, enabling detailed forecasts, uncertainty quantification, and evaluation of targeted intervention strategies across different city zones.

Contribution

The study develops and calibrates a novel mechanistic seasonal dengue transmission model incorporating spatial heterogeneity and evaluates intervention strategies with uncertainty analysis.

Findings

Persistent hotspots identified across zones.

Residual spraying can reduce incidence by over 80%.

Mosquito-to-human ratio influences outbreak potential and control responsiveness.

Abstract

Dengue fever poses a persistent public health challenge in rapidly urbanizing Indian cities such as Ahmedabad, where spatial heterogeneity and seasonal variability complicate forecasting and control. In this study, we develop a data-driven compartmental framework to simulate transmission dynamics, generate forecasts, and evaluate intervention strategies across the Ahmedabad Municipal Corporation (AMC). We employ a Mechanistic Seasonal Dengue Transmission (M-SDT) model that incorporates symptomatic and asymptomatic infections. We calibrated the proposed model using zone-wise dengue case data during 2020--2024. Parameter uncertainty is rigorously quantified using a bootstrap sampling framework with negative binomial noise. The calibrated model reveals pronounced spatial heterogeneity across AMC zones, with persistent hotspots and distinct transmission regimes. Forecasts for 2026--2028 indicate continued endemic circulation with moderate inter-annual variability. Sensitivity analysis identifies the mosquito biting rate and vector mortality as dominant drivers of long-term disease burden, highlighting the central role of vector ecology in shaping epidemic outcomes. Evaluating seasonal vector control strategies shows a notable difference in operation; periodic fogging has a cumulative effect over the years, while sustained residual spraying can quickly curb outbreaks and decrease incidence by over 80%. The zone-wise analysis reveals that the mosquito-to-human ratio governs not only the baseline outbreak potential but also each zone's responsiveness to control strategies. Overall, the M-SDT modelling framework enables reconstruction of unobserved dynamics, rigorous uncertainty quantification, and evaluation of targeted, zone-specific interventions, underscoring the importance of integrating fine-scale surveillance data with mechanistic modelling for adaptive urban dengue control.