Causal Inference in Disease Spread across a Heterogeneous Social System

TL;DR

This paper introduces the Latent Influence Point Process model to uncover causal mechanisms and feedback dynamics in disease spread, using 15 years of dengue data in Queensland to reveal complex diffusion behaviors.

Contribution

The paper presents a novel model that captures macro-level internal dynamics and causal relationships in disease diffusion, integrating human mobility and feedback effects.

Findings

Global diffusion drives outbreaks more than local factors.

Reflexivity varies between regions, affecting outbreak dynamics.

Model uncovers probabilistic causal links in disease transmission.

Abstract

Diffusion processes are governed by external triggers and internal dynamics in complex systems. Timely and cost-effective control of infectious disease spread critically relies on uncovering the underlying diffusion mechanisms, which is challenging due to invisible causality between events and their time-evolving intensity. We infer causal relationships between infections and quantify the reflexivity of a meta-population, the level of feedback on event occurrences by its internal dynamics (likelihood of a regional outbreak triggered by previous cases). These are enabled by our new proposed model, the Latent Influence Point Process (LIPP) which models disease spread by incorporating macro-level internal dynamics of meta-populations based on human mobility. We analyse 15-year dengue cases in Queensland, Australia. From our causal inference, outbreaks are more likely driven by statewide global diffusion over time, leading to complex behavior of disease spread. In terms of reflexivity, precursory growth and symmetric decline in populous regions is attributed to slow but persistent feedback on preceding outbreaks via inter-group dynamics, while abrupt growth but sharp decline in peripheral areas is led by rapid but inconstant feedback via intra-group dynamics. Our proposed model reveals probabilistic causal relationships between discrete events based on intra- and inter-group dynamics and also covers direct and indirect diffusion processes (contact-based and vector-borne disease transmissions).