Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach

Abstract

The emergence of the novel 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 and importations in a set of European countries to assess the 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 under-ascertainment. Maximum likelihood estimates for the ME, considering outbreak data up to 31 August 2013, indicate the occurrence of a subcritical epidemic with a reproductive number R of 0.50 (95% confidence interval (CI): 0.30-0.77) associated with a daily rate of sporadic introductions psp of 0.28 (95% CI: 0.12-0.85). Infections in the ME appear to be mainly dominated by zoonotic/environmental transmissions, with possible under-ascertainment (ratio of estimated to observed (0.116) sporadic cases equal to 2.41, 95% CI: 1.03-7.32). No time evolution of the situation emerges. Analyses of flight passenger data from ME countries 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 under-ascertainment, and calls for alertness in high importation risk areas worldwide.