Optimal strategies for containing infectious disease spread in mass gatherings with crowd mobility

Abstract

The risk of infectious diseases is considerably high during Hajj rituals due to overcrowding. The general application of a framework that describes Hajj can be limited as the characteristics of mass gatherings differ from one site to another. Therefore, there is a call for studies that focus on each of the Hajj rituals independently. This study proposes an agent-based model that describes the spread of contagions in the Mena Region, calibrated against reported COVID-19 outbreak characteristics during Hajj. An optimization was performed to test nine scenarios in which diseases’ prevalence, regional diversity, mobility, and capacity were prioritized in different combinations. The results show that prevalence becomes unrealistic in the case of no constraints, whereas eight out of the nine fitted scenarios fall within or near the empirical ranges of both prevalence (3–15%) and R0 (1.4–3.1), signifying that the framework captures important epidemiological dynamics. The most cost-effective control is generated when all four factors are considered equally so high capacity and mobility are allowed, with infections kept in realistic bounds. When nationality groups vary according to vaccination properties and age distributions, limiting participants from high-risk regions illustrated a significant impact on suppressing the infection. Finally, the study also investigated the relationship between disease incubation time and the time people spend in a foreign area. Once the stay time exceeds the incubation time, the infection level and the peak of the infection undergo a sharp increase.

keywords: Agent-based model, Crowd mobility, Epidemiological modeling, Genetic algorithm, Hajj rituals, Men