Spatial variability of Middle East respiratory syndrome coronavirus survival rates and mortality hazard in Saudi Arabia, 2012–2019

• DOI: 10.7717/peerj.9783
• Publication Date: 2020-08-12T07:43:57Z
• Authors: Khalid Hussain Al...; Mohammed Hussain ...; Ali Saeed Al-Zahrani; Maged Gomaa Hemida
• Keywords: Univariate

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 impact spatial/patient characteristics for 14-and 45-day MERS-CoV using 2012–2019 data reported across regions and provinces. The Kaplan–Meier estimator was employed to estimate survival rates, Cox proportional-hazards (CPH) models were applied hazard ratios (HRs) predictors, univariate local spatial autocorrelation multivariate clustering analyses used assess correlation. 14-day, rates (with estimated rates) 25.52% (70.20%), 32.35% (57.70%) 37.30% (56.50%), respectively, with no significant variations between Nationally, CPH model identified that being elderly (age ≥ 61), a non-healthcare worker (non-HCW), having an underlying comorbidity significantly related 14-day (HR = 2.10, 10.12 4.11, respectively; p < 0.0001). similar risk factors but additional factor: patients aged 41–60 1.44; Risk those in national observed Central, West Riyadh, Makkah, Eastern, Madinah Qassim provinces varying HRs. Spatial clusters based on ( r 2 0.85–0.97): Riyadh (Cluster 1), Makkah 2), other north south country 3). HRs varied spatially by province. For mortality, found 61 non-HCWs), (comorbidity) 41–60). Coming 1.30 1.27) or province 1.77 1.70) independently higher respectively. patient could be improved implementing appropriate interventions elderly, comorbidities non-HCW patients.