Understanding Sars-COV-2 Mortality: IMPACT of Population and Mobility Metrics
Author(s)
Shah S1, Ray B2, Holy C3, Sakthivel M1, Elangovanraaj N1, Krishnan D4, Gupta S5, Trivedi P1, Devulapally M1, Mohapatra A1, Coplan P6
1Mu Sigma, Bangalore, KA, India, 2Mu Sigma, Bangalore , India, 3Johnson & Johnson, Somerville, MA, USA, 4Mu-Sigma, Bangalore, India, 5Mu Sigma, Bangalore, India, 6Johnson & Johnson, New Brunswick, NJ, USA
Presentation Documents
OBJECTIVES: Published mortality rates from SARS-CoV-2 infections have varied significantly due to differences in testing and disease tracking rates across countries. The impact of population density, family size, mobility and government actions on mortality due to SARS-CoV-2 infections is not well understood. METHODS: This is a retrospective data analysis using the Worldwide WHO situation reports along with population density information and family size information (from Worldometer.com), government response data (7 policies: school closure (SC), workplace closure (WC), public event cancellation (PEC), restriction on gatherings (RG), public transport closure (PTC), stay-at-home (SAH), internal movement restrictions (IMR) - Oxford University) and mobility reports (Apple) to estimate variables associated with COVID-19 mortality from countries with complete information. Poisson regression models were developed to evaluate associations between mortality counts and variables mentioned herein. A 42-day lag was applied to mobility and government response metrics to evaluate the impact thereof on mortality. RESULTS: Nine countries were included in the analysis (Australia, Belgium, Chile, Italy, Peru, Saudi Arabia, Spain, UK, USA). The highest quartile of government response index had the greatest protective effect on mortality (incidence proportion ratio (IPR): 0.05 (95% confidence interval (CI): 0.01-0.32). There was no consistent association impact between walking, driving or transit mobility metric. Government actions with significant protective effect were PTC (IPR: 0.46 (0.28-0.75)) and PEC (IPR: 0.65 (0.47-0.91)). All other government actions did not show a statistically significant association with mortality. CONCLUSIONS: Our study identified population metrics and government actions potentially associated with mortality, across multiple geographies. Further research on key confounders (such as mask wearing) is required to evaluate further actions to mitigate the mortality from COVID-19.
Conference/Value in Health Info
2020-11, ISPOR Europe 2020, Milan, Italy
Value in Health, Volume 23, Issue S2 (December 2020)
Code
PIN115
Topic
Epidemiology & Public Health
Topic Subcategory
Public Health, Safety & Pharmacoepidemiology
Disease
Infectious Disease (non-vaccine)