Modeling Reflexivity of Social Systems in Disease Spread

TL;DR

This paper introduces the LIPP model to quantify social system reflexivity in disease spread, revealing how external and internal influences drive dengue outbreaks and regional diffusion patterns.

Contribution

The study presents a novel Latent Influence Point Process model that captures external heterogeneity and internal dynamics in social systems for disease diffusion analysis.

Findings

External influences trigger abrupt disease outbreaks.

Internal dynamics relate to steady growth in outbreaks.

Regional diffusion patterns reflect synchronous reflexivity.

Abstract

Diffusion processes in a social system are governed by external triggers and internal excitations via interactions between individuals over social networks. Underlying mechanisms are crucial to understand emergent phenomena in the real world and accordingly establish effective strategies. However, it is challenging to reveal the dynamics of a target diffusion process due to invisible causality between events and their time-evolving intensity. In this study, we propose the Latent Influence Point Process model (LIPP) by incorporating external heterogeneity and internal dynamics of meta-populations based on human mobility. Our proposed model quantifies the reflexivity of a social system, which is the level of feedback on event occurrences by its internal dynamics. As an exemplary case study, we investigate dengue outbreaks in Queensland, Australia during the last 15 years. We find that abrupt and steady growth of disease outbreaks relate to exogenous and endogenous influences respectively. Similar diffusion trends between regions reflect synchronous reflexivity of a regional social system, likely driven by human mobility.