Prediction of Influenza Transmission in Mass Gathering: A Systematic Review

Abstract

Introduction:

The annual Hajj pilgrimage in Mecca, Saudi Arabia, uniquely attracts over 3 million participants from more than 180 countries, who gather for several days. Although Saudi authorities have effectively managed these vast numbers, the risk of epidemics poses a continuous challenge. An early warning system capable of forecasting epidemic outbreaks could significantly enhance preparedness and containment efforts. This review aims to assess the existing literature on influenza prediction models, focusing on their application to the Hajj pilgrimage setting.

Methods:

We collected data on influenza's infectivity, the susceptibility and immunity levels among Hajj pilgrims from health authorities, and contact rates and patterns from previous surveys. Crowd modeling techniques were employed to simulate the pilgrims' movements in terms of time and location. A close contact was defined as any individual within a 2-meter radius of an infected person, with further categorizations based on the pilgrims' countries of origin and ages to reflect the impact on transmission patterns.

Results:

The compilation of epidemiological parameters and crowd movement simulations offers a foundation for predicting the spread of the influenza virus among Hajj pilgrims. These models consider various factors, including contact rates and pilgrim demographics, to forecast potential outbreaks.

Conclusion:

Effective prediction models for influenza transmission during the Hajj can guide and enhance preventive measures. By understanding the dynamics of pilgrim interactions and the disease's infectivity, health authorities can better prepare for and potentially mitigate the impact of epidemics.