Assessment of the MERS-CoV epidemic situation in the Middle East region

TL;DR

This study uses a spatial-transmission model with mobility data to assess the MERS-CoV epidemic in the Middle East, indicating a subcritical epidemic mainly driven by zoonotic transmissions and highlighting the importance of surveillance.

Contribution

It introduces an integrative maximum likelihood approach combining cluster and importation data to evaluate MERS-CoV transmission dynamics and underascertainment.

Findings

Subcritical epidemic with R=0.50

Estimated sporadic introductions at 0.28 per day

Indications of zoonotic transmission dominance

Abstract

The appearance of a novel coronavirus named Middle East (ME) Respiratory Syndrome Coronavirus (MERS-CoV) has raised global public health concerns regarding the current situation and its future evolution. Here we propose an integrative maximum likelihood analysis of both cluster data in the ME region and importations in Europe to assess transmission scenario and incidence of sporadic infections. Our approach is based on a spatial-transmission model integrating mobility data worldwide and allows for variations in the zoonotic/environmental transmission and underascertainment. Maximum likelihood estimates for the ME region indicate the occurrence of a subcritical epidemic (R=0.50, 95% confidence interval (CI) 0.30-0.77) associated with a 0.28 (95% CI 0.12-0.85) daily rate of sporadic introductions. Infections in the region appear to be mainly dominated by zoonotic/environmental transmissions, with possible underascertainment (95% CI of estimated to observed sporadic cases in the range 1.03-7.32). No time evolution of the situation emerges. Analyses of flight passenger data from the region indicate areas at high risk of importation. While dismissing an immediate threat for global health security, this analysis provides a baseline scenario for future reference and updates, suggests reinforced surveillance to limit underascertainment, and calls for increased alertness in high-risk areas worldwide.