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Spatiotemporal Clustering of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Incidence in Saudi Arabia,

Khalid Al-Ahmadi1, Sabah Alahmadi2, Ali Al-Zahrani3

  • 1King Abdulaziz City for Science and Technology, P.O. Box 6086, Riyadh 11442, Saudi Arabia.

International Journal of Environmental Research and Public Health
|July 18, 2019
PubMed

Insights

This study investigated Middle East respiratory syndrome coronavirus (MERS-CoV) clusters in Saudi Arabia. High-risk MERS-CoV infection periods and locations were identified, aiding disease control efforts.

Area of Science:

  • Epidemiology
  • Infectious Diseases
  • Public Health

Background:

  • Middle East respiratory syndrome coronavirus (MERS-CoV) poses a significant global health threat.
  • Saudi Arabia accounts for 83% of global MERS-CoV cases, yet its spatiotemporal clustering remains understudied.

Purpose of the Study:

  • To analyze the spatiotemporal patterns and clusters of MERS-CoV incidence in Saudi Arabia.
  • To identify high-risk periods and geographical areas for MERS-CoV infection.

Main Methods:

  • Utilized Kulldorff's spatial scan statistics for temporal, seasonal, spatial, and spatiotemporal cluster analysis.
  • Analyzed laboratory-confirmed MERS-CoV cases reported in Saudi Arabia from June 2012 to March 2019.

Main Results:

  • A significant temporal MERS-CoV cluster occurred from April 5 to May 24, 2014.
  • Spring, particularly April and May, showed significant seasonal clusters; Wadi Addawasir was a high-risk spatial cluster.
  • High-risk annual spatiotemporal clusters were found in Riyadh province (2014-2016), and monthly clusters included Jeddah, Makkah, and Taif, especially April-May 2014.

Conclusions:

  • Significant spatiotemporal clusters of MERS-CoV incidence were identified in Saudi Arabia.
  • Findings are crucial for developing targeted MERS-CoV control strategies.
  • This research provides a basis for investigating environmental risk factors linked to MERS-CoV clusters.
Keywords:
GISMiddle East respiratory syndromeSaudi Arabiacoronavirusepidemiologyoutbreakspatiotemporal cluster

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