Transmission scenarios for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and how to tell them apart

Abstract

Detection of human cases of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection internationally is a global public health concern. Rigorous risk assessment is particularly challenging in a context where surveillance may be subject to under-ascertainment and a selection bias towards more severe cases. We would like to assess whether the virus is capable of causing widespread human epidemics, and whether self-sustaining transmission is already under way. Here we review possible transmission scenarios for MERS-CoV and their implications for risk assessment and control. We discuss how existing data, future investigations and analyses may help in reducing uncertainty and refining the public health risk assessment and present analytical approaches that allow robust assessment of epidemiological characteristics, even from partial and biased surveillance data. Finally, we urge that adequate data be collected on future cases to permit rigorous assessment of the transmission characteristics and severity of MERS-CoV, and the public health threat it may pose. Going beyond minimal case reporting, open international collaboration, under the guidance of the World Health Organization and the International Health Regulations, will impact on how this potential epidemic unfolds and prospects for control.

Figure 1

Two illustrative scenarios for transmission of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) A. Few human-to-human infection events have occurred and observed clusters have arisen from separate spill-over events (i.e. introductions from the animal reservoir into human populations). B. Many undetected human-to human transmission events have occurred and the epidemic is already self-sustaining.

Figure 2

Probability that the epidemic of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection has become self-sustaining in humans after n introductions from the reservoir if R>1 R: reproduction number. This probability depends not only on R but also on the presence of super- spreading events (SSE) (without SSE: plain line; with SSE; dotted line). Values R=3 and R=1.2 were selected for illustrative purposes.

Figure 3

Upper bound for the reproduction number R as a function of the number of introductions from the reservoir that failed to generate self-sustaining epidemics