Control of epidemics via social partnership adjustment

TL;DR

This paper compares two epidemic control strategies—reducing contact with infected individuals versus increasing contacts among susceptibles—using a stochastic interaction model, finding that the latter is more robust and effective under various conditions.

Contribution

It provides a comparative analysis of two social partnership adjustment strategies for epidemic control using a novel stochastic interaction model.

Findings

Reducing contact with infected individuals is sensitive to infection intensity and interaction rates.

Increasing contacts among susceptibles is more robust and consistently effective.

Analytical results align with simulation outcomes, validating the model.

Abstract

Epidemic control is of great importance for human society. Adjusting interacting partners is an effective individualized control strategy. Intuitively, it is done either by shortening the interaction time between susceptible and infected individuals or by increasing the opportunities for contact between susceptible individuals. Here, we provide a comparative study on these two control strategies by establishing an epidemic model with non-uniform stochastic interactions. It seems that the two strategies should be similar, since shortening the interaction time between susceptible and infected individuals somehow increases the chances for contact between susceptible individuals. However, analytical results indicate that the effectiveness of the former strategy sensitively depends on the infectious intensity and the combinations of different interaction rates, whereas the latter one is quite robust and efficient. Simulations are shown in comparison with our analytical predictions. Our work may shed light on the strategic choice of disease control.