Patrick Heuveline - UCLA
“I Heard We Had the Best Mortality Rate” Some Old and a New Mortality Indicator for COVID-19 Analyses
Date: 09/03/2020 (Thu)
Time: 3:30pm- 5:00pm
Location: ZOOM: https://duke.zoom.us/j/96311970245
Organizer: Giovanna Merli
Meeting Schedule: Login or email the organizer to schedule a meeting.
1:00pm - Meeting with Students (please enter your name: Claire Le Barbenchon, Allison Stolte,)
1:45pm - Giovanna Merli
2:15pm - Marcos Rangel
2:45pm - Christina Kamis and Jessie West
3:30pm - Seminar Presentation (3:30pm to 5:00pm)
Additional Comments: Expressing the significance of COVID-19 in a relatable metric is important because public awareness is critical to participation, on which mitigating policies depend. Mortality indicators are among the most salient measures of the impact of COVID-19. Following well-established practices in demography, several CoViD-19 mortality indicators can be derived from the cumulative number of CoViD-19 deaths. The first indicator is an occurrence-exposure rate comparable to the Crude Death Rate. Unstandardized, it may not be appropriate for comparisons between populations that have very different age compositions, but it allows for a direct comparison between CoViD-19 and all causes mortality over periods of any length. The second measure is an indirectly standardized rate which appears to perform quite like a directly standardized rate but without requiring a breakdown of CoViD-19 deaths by age and sex. While age-standardized death rates have excellent properties for tracking the pandemic, those are expressed in underwhelming metrics: deaths per 1,000 or fraction thereof. With extant life tables, reductions in 2020 life expectancies can be estimated. Declines in life expectancies are intuitive indicators, but they are unsuitable for fine-grained tracking of a fast-moving epidemic because their estimation requires an assumption of unchanged future mortality. To avoid making any assumption about future mortality, I introduce a Mean Unfulfilled Lifespan (MUL), defined as the average difference between the actual and otherwise expected ages at death in a recent death cohort. For fine-grained tracking of the pandemic across small areas or over short periods of time, MUL values can be quickly approximated. To illustrate I estimate that using a seven-day rolling window, the MUL peaked at 7.32 years in Lombardy, 8.96 years in Madrid, and 8.93 years in New York, but reached 12.86 years for the entire month of April in Guayas (Ecuador).