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arXiv · 2512.03760

A decay-adjusted spatio-temporal model to account for the impact of mass drug administration on neglected tropical disease prevalence

Emanuele Giorgi·Claudio Fronterre·Peter J. Diggle
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Abstract

Prevalence surveys are routinely used to monitor the effectiveness of mass drug administration (MDA) programmes for controlling neglected tropical diseases (NTDs). We propose a decay-adjusted spatio-temporal (DAST) model that explicitly accounts for the time-varying impact of MDA on NTD prevalence, providing a flexible and interpretable framework for estimating intervention effects from sparse survey data. Using case studies on soil-transmitted helminths and lymphatic filariasis, we show that DAST offers a practical alternative to standard geostatistical models when the objective includes quantifying MDA impact and supporting short-term programmatic forecasting. We also discuss extensions and identifiability challenges, advocating for data-driven parsimony over complexity in settings where the available data are too sparse to support the estimation of highly parameterised models.

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Emanuele Giorgi, Claudio Fronterre, Peter J. Diggle. 2025-12-03. A decay-adjusted spatio-temporal model to account for the impact of mass drug administration on neglected tropical disease prevalence. https://doi.org/10.1093/jrsssa%2Fqnag100

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