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Unraveling the drivers of MERS-CoV transmission
Simon Cauchemez1, Pierre Nouvellet2, Anne Cori2
1Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, 75015 Paris, France; Centre National de la Recherche Scientifique, Unité de Recherche Associée 3012, 75015 Paris, France; Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France;
Abstract:
With more than 1,700 laboratory-confirmed infections, Middle East respiratory syndrome coronavirus (MERS-CoV) remains a significant threat for public health. However, the lack of detailed data on modes of transmission from the animal reservoir and between humans means that the drivers of MERS-CoV epidemics remain poorly characterized. Here, we develop a statistical framework to provide a comprehensive analysis of the transmission patterns underlying the 681 MERS-CoV cases detected in the Kingdom of Saudi Arabia (KSA) between January 2013 and July 2014. We assess how infections from the animal reservoir, the different levels of mixing, and heterogeneities in transmission have contributed to the buildup of MERS-CoV epidemics in KSA. We estimate that 12% [95% credible interval (CI): 9%, 15%] of cases were infected from the reservoir, the rest via human-to-human transmission in clusters (60%; CI: 57%, 63%), within (23%; CI: 20%, 27%), or between (5%; CI: 2%, 8%) regions. The reproduction number at the start of a cluster was 0.45 (CI: 0.33, 0.58) on average, but with large SD (0.53; CI: 0.35, 0.78). It was >1 in 12% (CI: 6%, 18%) of clusters but fell by approximately one-half (47% CI: 34%, 63%) its original value after 10 cases on average. The ongoing exposure of humans to MERS-CoV from the reservoir is of major concern, given the continued risk of substantial outbreaks in health care systems. The approach we present allows the study of infectious disease transmission when data linking cases to each other remain limited and uncertain.
Insights
Middle East respiratory syndrome coronavirus (MERS-CoV) outbreaks are driven by both animal-to-human transmission and human-to-human spread. Understanding these transmission patterns is crucial for public health, especially with ongoing reservoir exposure risks.
Area of Science:
- Epidemiology
- Infectious Disease Dynamics
- Statistical Modeling
Background:
- Middle East respiratory syndrome coronavirus (MERS-CoV) poses a significant public health threat with over 1,700 confirmed infections.
- Limited data on transmission routes from animal reservoirs and between humans hinders understanding of MERS-CoV epidemic drivers.
Purpose of the Study:
- To statistically analyze MERS-CoV transmission patterns in Saudi Arabia (2013-2014).
- To quantify the contributions of animal reservoir, human mixing, and transmission heterogeneity to MERS-CoV epidemics.
- To assess the dynamics of MERS-CoV transmission clusters.
Main Methods:
- Development of a statistical framework for analyzing transmission patterns.
- Comprehensive analysis of 681 MERS-CoV cases in Saudi Arabia.
- Estimation of transmission sources (reservoir vs. human-to-human) and spatial spread.
Main Results:
- Approximately 12% of cases originated from the animal reservoir; the remainder were human-to-human transmissions.
- Human-to-human transmission occurred in clusters (60%), within regions (23%), and between regions (5%).
- The average reproduction number at cluster onset was 0.45, decreasing significantly as clusters grew; 12% of clusters had a reproduction number >1.
Conclusions:
- Ongoing human exposure to MERS-CoV from the animal reservoir is a major concern, posing risks for healthcare-associated outbreaks.
- The statistical approach is valuable for studying infectious disease transmission with limited case-linking data.
- Effective control strategies must address both zoonotic spillover and human-to-human transmission dynamics.
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