Abstract
A mass-gathering is defined as a congregation of a relatively large number of people in a specific location for a specific purpose over a short duration of time. Managing Mass-Gathering Healthcare (MGH), especially in resource-constrained regions, is a key policy challenge. Planning and preparation for MGH require understanding the sources, and estimation of demand. We propose a spatio-temporal Poisson point process model for MGH demand estimation that considers the associated risk factors. We analyze admissions data from a multi-specialty hospital in Ujjain, India, spanning a period before, during, and after Kumbh Mela, one of the larger religious gatherings globally. The results show that the effect of mass-gathering on hospital admissions is heterogeneous across disease groups. We identify key socio-economic and healthcare infrastructural factors that are associated with MGH demand. We establish the external-validity of the results by demonstrating that mass-gatherings generally increase the spatial dependence across regions, particularly where availability of healthcare infrastructure is relatively low. Finally, we discuss policy insights for managing MGH.
Original language | English (US) |
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Pages (from-to) | 995-1017 |
Number of pages | 23 |
Journal | Naval Research Logistics |
Volume | 68 |
Issue number | 8 |
DOIs | |
State | Published - Dec 2021 |
Keywords
- Kumbh Mela
- healthcare
- hospital admissions
- infectious diseases
- mass-gathering
ASJC Scopus subject areas
- Modeling and Simulation
- Ocean Engineering
- Management Science and Operations Research