Causality Network of Infectious Disease Revealed With Causal Decomposition

Abstract

Causal inference in the field of infectious disease attempts to gain insight into the potential causal nature of an association between risk factors and diseases. Simulated causality inference experiments have shown preliminary promise in improving understanding of the transmission of infectious diseases but still lack sufficient quantitative causal inference studies based on real-world data. Here, we investigate the causal interactions between three different infectious diseases and related factors, us-ing causal decomposition analysis, to characterize the na-ture of infectious disease transmission. We show that the complex interactions between infectious disease and hu-man behavior have a quantifiable impact on transmission efficiency of infectious diseases. Our findings, by shedding light on the underlying transmission mechanism of infec-tious diseases, suggest that causal inference analysis is a promising approach to determine epidemiological interventions.