In this post we estimate an “equal-risk” projection of COVID-19 mortality within life settlements using the geographic overlap of COVID-19 deaths with life settlement insureds.  By comparing this equal-risk rate to observed data, we estimate a net mortality risk factor of 6-12x for the life settlements population.  This is on par with a simple age-weighted projection of mortality and suggests socio-economic advantages may have a weaker protective effect than expected.

The life settlements population has a mixed geographic overlap with COVID-19 mortality rates.  Many life settlement insureds live in the New York metropolitan area, which has experienced the highest COVID-19 mortality rates to-date.  However, many life settlement insureds live in areas less impacted by the pandemic, like south Florida and southern California.

Figure 1. COVID-19 Crude Mortality Rate by County, Updated 5/13/2020 Interactive

Source: New York Times

We computed an “equal-risk” life settlements COVID-19 mortality estimate, which assumes that life settlement insureds experience the same mortality risk as the average citizen in their county of residence.  We expect the true mortality rate of life settlements to be much higher than this estimate (see, e.g., our posts on age and comorbidity impacts in life settlements).  Instead, the value of the equal-risk estimate is that it provides the baseline for an empirical test of the realized net impact of risk factors like age, comorbidities, and socio-economics on COVID-19 outcomes within life settlements.  By comparing the equal-risk estimate to observed excess deaths in life settlements, we can compute a net mortality risk factor for the population taken as a whole.

Actual mortality data shows the first indications of a rise in mortality caused by the pandemic.  We examined this year’s observed deaths through April 4th for excess mortality – i.e. actual deaths above what would be expected under “normal” circumstances, which are likely caused directly or indirectly by the pandemic.  Due to reporting delay, data after April 4th was deemed incomplete.  The weeks ending March 28th and April 4th will likely also be adjusted up as more data comes in.

Since data for the week ending April 4th is likely incomplete, we estimated excess mortality by comparing the total number of deaths in the week to both the previous week and the maximum year-to-date.  Using this approach, excess mortality in the week ending April 4th was an estimated 29%-83% or 26-52 deaths.  The equal-risk expected excess deaths for the same week was 4.3.

Figure 2. 2020 Life Settlements Mortalities and Equal-Risk Expected

Taking the ratio of raw to expected excess deaths, we estimate a total risk factor for the life settlements population of 6-12x.  This is a crude – we believe, conservative – estimate.  It suggests, however, that socio-economic advantages may have a weaker protective effect than expected.  This is because actual mortality data implies a risk factor similar to our 9-10x age-based estimate.

We will post an updated analysis when further mortality data comes in that will refine these estimates and clarify the realized mortality impact that the pandemic is having on the life settlements population.

[1] Longevity Holdings is the parent company of PBI Research Services, ITM21st, Fasano Associates, and Life Insurance Trust Company.