A mechanistic framework linking within-host pathogen progression to vector-mediated transmission under climate forcing

Abstract

Climate-driven disease forecasts typically assess whether environmental conditions favor pathogen growth, yet epidemic spread depends critically on how physiological processes within infected hosts shape transmission over time. This distinction is particularly consequential for vector-borne plant diseases, where vectors acquire infection from hosts whose pathogen load, symptom severity, and recovery are themselves temperature-dependent. Here, we develop a mechanistic epidemic framework that couples temperature-driven within-host pathogen dynamics to vector-mediated transmission. Infected hosts progress through ordered infection stages with stage-specific infectiousness, while transitions among stages--both progression and regression--are governed by thermal effects on pathogen accumulation and decay. We parameterize the model using experimental data for Pierces disease of grapevine, caused by Xylella fastidiosa, and analyze epidemic invasion under constant, seasonal, stochastic, and empirical temperature regimes. We show that temperature affects invasion not only by altering pathogen growth rates but also by reshaping the time hosts spend in transmissible infection stages. This generates a slow-growth paradox: temperatures that maximize within-host pathogen growth need not maximize epidemic spread, because rapid progression shortens the effective transmission window, whereas mildly suboptimal temperatures can prolong infectiousness and sustain larger epidemics. Conversely, cold conditions can suppress invasion by either halting progression or inducing regression and recovery. Analytical expressions for the basic reproduction number under constant and seasonal forcing capture these mechanisms and predict final epidemic size across diverse climatic regimes. Short-term temperature variability has its strongest effects near thermal thresholds, and empirical temperature series from invaded regions generate markedly different epidemic trajectories despite similar invasion suitability. These results show that ignoring the coupling between within-host physiology and transmission can qualitatively mislead predictions of plant disease dynamics under climate change, misidentifying the thermal regimes that pose the greatest epidemic risk.