Temporal dynamics of Middle East respiratory syndrome coronavirus in the Arabian Peninsula, 2012-2017

Temporal dynamics of Middle East respiratory syndrome coronavirus in the Arabian Peninsula, 2012-2017

Middle East respiratory syndrome coronavirus (MERS-CoV) remains a notable disease and poses a significant threat to global public health. The Arabian Peninsula is considered a major global epicentre for the disease and the virus has crossed regional and continental boundaries since 2012. In this stu...

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Bibliographic Details
Published in:Epidemiology and infection Vol. 147; pp. 1 - e21
Main Authors: Alkhamis, M A, Fernández-Fontelo, A, VanderWaal, K, Abuhadida, S, Puig, P, Alba-Casals, A
Format: Journal Article
Language:English
Published: England Cambridge University Press 01-01-2019
Subjects:
Analytical methods
Autoregressive models
Coronaviridae
Coronaviruses
Disease control
Disease prevention
Epidemics
Epidemiology
Health risks
Health surveillance
Human populations
Infections
Infectious diseases
Original Paper
Outbreaks
Pandemics
Populations
Public health
Respiratory diseases
Seasonal variations
Statistical analysis
Time dependence
Time series
Viruses
Zoonoses
Middle East
Saudi Arabia
Arabian Peninsula
South Korea
Qatar
United Arab Emirates
Riyadh Saudi Arabia
Oman
MERS-CoV
time-dependent reproductive number
surveillance
ARIMA modelling
seasonality
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Summary:Middle East respiratory syndrome coronavirus (MERS-CoV) remains a notable disease and poses a significant threat to global public health. The Arabian Peninsula is considered a major global epicentre for the disease and the virus has crossed regional and continental boundaries since 2012. In this study, we focused on exploring the temporal dynamics of MERS-CoV in human populations in the Arabian Peninsula between 2012 and 2017, using publicly available data on case counts and combining two analytical methods. Disease progression was assessed by quantifying the time-dependent reproductive number (TD-Rs), while case series temporal pattern was modelled using the AutoRegressive Integrated Moving Average (ARIMA). We accounted for geographical variability between three major affected regions in Saudi Arabia including Eastern Province, Riyadh and Makkah. In Saudi Arabia, the epidemic size was large with TD-Rs >1, indicating significant spread until 2017. In both Makkah and Riyadh regions, the epidemic progression reached its peak in April 2014 (TD-Rs > 7), during the highest incidence period of MERS-CoV cases. In Eastern Province, one unique super-spreading event (TD-R > 10) was identified in May 2013, which comprised of the most notable cases of human-to-human transmission. Best-fitting ARIMA model inferred statistically significant biannual seasonality in Riyadh region, a region characterised by heavy seasonal camel-related activities. However, no statistical evidence of seasonality was identified in Eastern Province and Makkah. Instead, both areas were marked by an endemic pattern of cases with sporadic outbreaks. Our study suggested new insights into the epidemiology of the virus, including inferences about epidemic progression and evidence for seasonality. Despite the inherent limitations of the available data, our conclusions provide further guidance to currently implement risk-based surveillance in high-risk populations and, subsequently, improve related interventions strategies against the epidemic at country and regional levels.
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ISSN:0950-2688
1469-4409
DOI:10.1017/S0950268818002728