Spreading dynamics of infectious diseases on structured society with daily cycles

TL;DR

This paper models infectious disease spread in structured societies with daily cycles, revealing how societal modularity and initial infection points influence epidemic dynamics, and proposing design principles for mitigation.

Contribution

It introduces an artificial society model with daily cycles and analyzes how societal structure affects infection spread, highlighting modularity as a key factor.

Findings

High modularity slows infection spread.

Long-distance commuting accelerates infection.

Initial infection location impacts spread speed.

Abstract

We are facing a common serious issue, infectious diseases, and trying to suppress the spreading of infection. We need less contact with each other to decrease the chance of infection, but this means loss of economic activity, as well. This tradeoff is inevitable in our society, because we still need direct communication and commuting, so far. The focus of our paper is the structure of society, on which we have direct contacts. We study on spreading process with artificial sosiety model, where each agent has daily cycle and go office and back home, every day. At the same time, infection spreads along SIR model. We show both slow infection and short commuting can be realized with some structures and vice versa. The most effective factor for such features is modularity of society. In highly modular society, agents live around the destined office, but agents commute long way to their office and can be infected fast, in not modular society. The first infection point is one more factor for the features. If the first infection takes place around the office, infection spreads slower. On the contrary, if the first one takes place far away from the office, infection can be fast. We show a design principle, high modularity and sparsely distributed offices, for good society and discuss on possible solutions in real society, where we live in.