Individual and network characteristic associated with hospital-acquired Middle East Respiratory Syndrome coronavirus

Abstract

Background: During outbreaks of infectious diseases, transmission of the pathogen can form networks of infected individuals connected either directly or indirectly.

Methods: Network centrality metrics were used to characterize hospital-acquired Middle East Respiratory Syndrome Coronavirus (HA-MERS) outbreaks in the Kingdom of Saudi Arabia between 2012 and 2016. Covariate-adjusted multivariable logistic regression models were applied to assess the effect of individual level risk factors and network level metrics associated with increase in length of hospital stay and risk of deaths from MERS.

Results: About 27% of MERS cases were hospital acquired during the study period. The median age of healthcare workers and hospitalized patients were 35 years and 63 years, respectively, Although HA-MERS were more connected, we found no significant difference in degree centrality metrics between HA-MERS and non-HA-MERS cases. Pre-existing medical conditions (adjusted Odds ratio (aOR)=2.43, 95% confidence interval: (CI) [1.11-5.33]) and hospitalized patients (aOR=29.99, 95% CI [1.80-48.65]) were the strongest risk predictors of death from MERS. The risk of death associated with 1-day increased length of stay was significantly higher for patients with comorbidities.

Conclusion: Our investigation also revealed that patients with an HA-MERS infection experienced a significantly longer hospital stay and were more likely to die from the disease. Healthcare worker should be reminded of their potential role as hubs for pathogens because of their proximity to and regular interaction with infected patients. On the other hand, this study has shown that while healthcare workers acted as epidemic attenuators, hospitalized patients played the role of an epidemic amplifier.

Keywords: Healthcare workers; Hospital-acquired infections; MERS; Network analysis.

Fig. 1

Distribution of weekly number of MERS cases by week of symptom onset and the number of HA-MERS in KSA. Wherever the date of onset is not available, the date hospitalized or date the disease is reported was used (whichever comes first).

Fig. 2

Visualization of MERS-CoV cases during the outbreak. Isolated cased were not included in the figure. The size of the node represents the degree centrality, increasing node sizes implies the more important the patient is.