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?:abstract
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About 83% of laboratory-confirmed Middle East respiratory syndrome coronavirus (MERS-CoV) cases have emerged from Saudi Arabia, which has the highest overall mortality rate worldwide This retrospective study assesses the impact of spatial/patient characteristics for 14-and 45-day MERS-CoV mortality using 2012-2019 data reported across Saudi regions and provinces The Kaplan-Meier estimator was employed to estimate MERS-CoV survival rates, Cox proportional-hazards (CPH) models were applied to estimate hazard ratios (HRs) for 14-and 45-day mortality predictors, and univariate local spatial autocorrelation and multivariate spatial clustering analyses were used to assess the spatial correlation The 14-day, 45-day and overall mortality rates (with estimated survival rates) were 25 52% (70 20%), 32 35% (57 70%) and 37 30% (56 50%), respectively, with no significant rate variations between Saudi regions and provinces Nationally, the CPH multivariate model identified that being elderly (age >= 61), being a non-healthcare worker (non-HCW), and having an underlying comorbidity were significantly related to 14-day mortality (HR = 2 10, 10 12 and 4 11, respectively;p = 61 and non-HCWs), Riyadh (comorbidity) and Madinah (age 41-60) Coming from Makkah (HR = 1 30 and 1 27) or Qassim province (HR = 1 77 and 1 70) was independently related to higher 14-and 45-day mortality, respectively MERS-CoV patient survival could be improved by implementing appropriate interventions for the elderly, those with comorbidities and non-HCW patients
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