4. The impact of the COVID-19 pandemic on mortality and life expectancy

The understanding and modelling of longevity is central to the ability of the providers of lifetime retirement income to ensure that they will be able to continue to make retirement income payments. Mortality assumptions are the basis on which retirement income calculations are made, and their accuracy is crucial to ensure the solvency of providers and their resilience to face longevity risk.

The COVID-19 pandemic has been one of the largest shocks to longevity in recent history. Mortality was not only impacted directly by the virus, but also indirectly from the measures that governments imposed to combat the virus and the broader economic and social consequences that those have had. The immediate death toll from the virus itself was significant, but people also suffered indirect consequences of the pandemic, such as the impact to healthcare access and the effects that lockdown measures had on personal well-being and behaviour as well as on the economy. Hospitals that were overwhelmed with COVID patients may not have been able to provide needed care for individuals with other illnesses, while the fear of catching COVID-19 may have also led individuals not to seek needed medical care at all. Lockdown measures took a toll on personal well-being, with negative consequences manifesting themselves through substance abuse, declines in mental health, and violence. Nevertheless, it also resulted in some behavioural changes that were positive for mortality, such as less driving and better hygiene. The broader economic consequences of lockdowns are intertwined with both healthcare and well-being, and could also have an impact on mortality in the near term. In the long-term the impact on mortality is much more uncertain. There could be additional impacts on mortality for those who have been exposed to the virus, or potentially negative consequences on mortality linked to the shifting social and political trends emerging in the wake of the pandemic.

Understanding the broad impact of the COVID-19 pandemic on mortality is important to be able assess the impact of COVID-19 on the value of pension and annuity liabilities and to inform the setting of mortality assumptions for both current mortality and future mortality improvements. It will also provide lessons for managing and responding to the impact of similar events in the future.

This chapter looks at the wide-ranging impacts that COVID-19 has had already on mortality, focusing on the peak years of the pandemic in 2020 and 2021, and the effects that we may continue to observe going forward. The first section investigates the short-term impact of the pandemic on mortality. It looks at the direct impact of the COVID-19 virus on mortality and how the impact has varied across different groups of the population. It also considers the indirect effects of responses to the pandemic, in particular relating to healthcare, lockdown measures imposed by governments, and the overall economic fallout. The second section discusses the potential implications for mortality in the longer term. It considers the possible long-term consequences on mortality from the virus itself. It also discusses the potential indirect effects that could be felt from social and political shifts. The chapter concludes with a discussion of the implications that these impacts have for setting mortality assumptions used in the context of asset-backed pension systems.

The official count of COVID-19 deaths globally over the peak years of the pandemic of 2020 and 2021 totalled around 5.5 million lives lost (The Economist, 2022[1]).1,2 However, this figure does not accurately reflect the total number of lives that the pandemic took during that time. The official count includes only the deaths where the individual tested positive for the virus, or in some countries where the individual demonstrated a probable infection, yet the deaths of many more individuals who were never tested or suspected of being infected can likely be attributed to COVID-19. In addition, this figure ignores the indirect impact that the pandemic has had on mortality, due for example to reduced access to healthcare or the negative consequences that lockdown measures had on well-being.

To capture the real death toll of the pandemic, a more useful figure is the level of excess mortality experienced. Excess mortality measures the level of mortality experienced compared to what otherwise would have been expected, with expectations normally based on the average experience over recent years. As this figure accounts for all deaths experienced during the pandemic, it captures both the deaths directly related to the virus as well as the indirect effects the pandemic has had on mortality. While many of these indirect effects have likely resulted in additional deaths, there has also been some positive impact, such as the reduction of traffic accidents and improved hygiene, which would serve to offset the total mortality cost of COVID-19.

On a global scale, excess mortality figures present a significantly grimmer picture of the lives lost from COVID-19 than the official numbers indicate. One estimate puts global excess deaths at 19.2 million in 2020 and 2021, more than three times the level of officially reported COVID deaths (The Economist, 2022[1]).3 Few countries were spared. Figure ‎4.1 shows the average percentage of weekly excess deaths and the maximum weekly excess deaths experienced in OECD countries over the period from January 2020 to December 2021, or the latest available data. The average excess mortality across OECD jurisdictions over the period was just under 10%, with the average maximum excess during any week at 62.5%.4 Nevertheless, several countries managed to keep excess deaths during the pandemic to a minimum. New Zealand and Australia experienced fewer deaths on average during the pandemic than expected in normal times due to their zero-COVID policies, and Japan, Iceland, Korea, Denmark, Luxembourg, and Norway managed to keep average excess deaths under 1.5%. The relative severity of the pandemic waves differs across countries, with some like Spain experiencing significant spikes, while in others such as Israel the peak in mortality was more moderate. At the right end of the figure, the heavy death toll of the pandemic can be observed in Latin America, particularly in Colombia and Mexico where the average weekly excess mortality exceeded 35%, and the worst wave caused excess mortality of over 160% in Mexico.

The excess mortality experienced over 2020 led to a significant reduction in period life expectancy in most jurisdictions. Figure ‎4.2 shows the change in period life expectancy at age 60 in 2020 compared to 2019 in selected jurisdictions. The results are broadly consistent with the observed total excess mortality, with all jurisdictions shown experiencing a decline in life expectancy except Norway, Iceland, and Denmark, who all experienced very low levels of total excess mortality. In most jurisdictions, males suffered a larger drop in period life expectancy than females, in line with observations that men had a higher mortality risk from COVID-19. Polish males observed the largest decline in period life expectancy in 2020, losing 1.5 years for men, followed by US males and Spaniards of both genders for whom the observed decrease was over 1.4 years.

Nevertheless, these estimates do not take into account future trends in mortality, and only capture the impact that COVID-19 had on mortality during a single year. The impact on cohort life expectancies – accounting for mortality improvements and a return to ‘normal’ levels of mortality – would be substantially smaller, even insignificant. For example, Figure ‎4.2 shows that period life expectancy for Dutch males aged 60 fell by 9.24 months (0.77 years). However, assuming that excess mortality continues only through 2020-2022, the impact on cohort life expectancy is only 15 days (0.5 months).5

Within countries, different age groups did not experience the same relative magnitude of excess mortality. The differences observed across age groups may provide an indication as to what extent indirect effects may have had a disproportionate effect on some age groups. For example, the youngest age group may have experienced a net reduction in mortality because of fewer deaths caused by traffic accidents. Other age groups may have modified their behaviour more, such as by being stricter with social distancing. Additional explanations for observed differences across age groups could be differences in access to health care or testing. Figure ‎4.3 shows the excess mortality experienced during the pandemic by age group. Those aged 15-64 experienced negative excess deaths in several countries, indicating that positive indirect effects on mortality may have outweighed the negative impact of the COVID-19 virus. Surprisingly, those aged 85 and over did not experience the highest excess mortality in any jurisdiction, and in some countries such as the United States experienced substantially lower excess mortality than other age groups. In the United States, those aged 15-24 actually experienced the highest levels of excess mortality (Leavitt, 2021[4]). The age group 75-84 was the most severely impacted in half of the jurisdictions shown. The relative impact for different age groups has also changed over time. In the United Kingdom, for example, excess deaths for ages 45-64 were somewhat higher in 2021 compared to 2020 (Continuous Mortality Investigation, 2021[5]).

It is not easy to distinguish between the deaths caused directly by the COVID-19 virus, and those resulting from the indirect effects of the pandemic. The gap between the COVID deaths officially reported and the observed excess mortality can provide some indication of the indirect cost of lives, as shown in Figure ‎4.4. Countries on the right side of the figure experienced higher excess mortality than officially reported COVID deaths. While this could indicate that some of the indirect effects of the pandemic have had a negative effect on mortality, this would also capture any of deaths that were from COVID-19 but not reported as such. On the left side of the figure, several countries experienced lower total excess deaths than the number of COVID deaths officially reported. This would capture deaths that were classified as being due to COVID-19 because of a recent positive test result, but were actually due to other causes. This could also indicate that indirect impacts such as behavioural changes may have had a positive impact on mortality.

Another way to understand the direct and indirect impact of COVID-19 on mortality is to look at the decomposition of the change in life expectancy from 2019 to 2020. Figure ‎4.5 shows the decomposition of this change in life expectancy at birth (contrary to Figure ‎4.2 that shows life expectancy at age 60) between the direct impact of COVID-19 and the impact from other causes. Chileans experienced the largest reduction in life expectancy attributed directly to COVID-19, whereas those from the United States experienced the largest total reduction in life expectancy. Other causes of mortality actually had a positive impact on life expectancy in Chile, particularly for females.

Nevertheless, average figures may hide that indirect effects may still have had a net negative impact for many groups of the population, even if they were positive overall. Disadvantaged groups who have experienced higher mortality from COVID-19 have also experienced higher excess mortality during the pandemic from other causes. One study in the United States estimates that 17% of excess deaths were attributable to causes other than COVID-19, and this figure was substantially higher for counties having lower socioeconomic levels, poorer health, and a larger Black population (Stokes et al., 2021[7]).

While official statistics for COVID-19 deaths may not provide an accurate estimate of the total impact it has had on mortality, they do provide important insights regarding relative mortality risk for various groups of the population. The following section describes these differences and their potential drivers.

The mortality risk from COVID-19 seems to generally follow a similar pattern to the mortality risk from all causes, so those at higher risk of dying during regular times are also at higher risk of dying from COVID-19. As with baseline mortality, the mortality risk from COVID-19 differs substantially across ages, genders, baseline health, socioeconomic status, and ethnicity.

The mortality risk from COVID-19 increases exponentially with age, similarly to the normal mortality pattern observed across ages. The Gompertz model, which is commonly used to define mortality rates across ages and assumes that mortality increases exponentially with age, provides an adequate fit for the mortality from COVID-19. Indeed, the pattern of the mortality risk from COVID-19 has followed a similar pattern as that for other causes of death related to ageing, including pneumonia and influenza. However, the relative mortality risk for adults from COVID-19 has been much higher, at between 2.8 to 8.2 times higher than pneumonia and influenza (Sasson, 2021[8]).

Given the exponential pattern of mortality risk across ages, the age structure of a population is clearly a determinant in the overall mortality for COVID-19 experienced in any given jurisdiction. However, the starting point of mortality also matters. Older people are at higher relative risk in high-income countries, who have lower baseline mortality at adult ages, than in low and middle-income countries. This is because high-income countries have experienced more significant longevity gains at younger to middle ages, so the mortality curve for high-income countries is much steeper (see Figure ‎4.6 for an illustration). This means that individuals ‘age’ more quickly than in low and middle-income countries where the mortality curve is flatter. As such, the mortality risk from COVID-19 increases on average by 12.6 percent with each year of age in high-income countries, compared to only 7.1 percent in low and middle-income countries (Demombynes, 2020[9]). Younger individuals in the latter countries are therefore at higher relative risk of dying from COVID-19.

Males have been at a higher risk of dying from COVID-19 than females on average. Males have represented slightly less than half of confirmed positive cases – though they have been also less likely to get tested – but have made up a higher proportion of confirmed deaths (The Sex, Gender, and COVID-19 Project, 2021[10]). Figure ‎4.7 shows that this is generally true in a sample of 30 OECD countries where sex-disaggregated data is available. While men represent on average 48.3% of confirmed COVID-19 cases in the sample, weighted by the number of cases, they make up 55% of the deaths (The Sex, Gender, and COVID-19 Project, 2021[10]).

Nevertheless, the differences between genders in mortality risk from COVID-19 are largely in line with differences in baseline mortality. One global study concluded that males are nearly 40% more likely to die of COVID-19 than females, and nearly three times more likely to require intensive care, even though there is no difference between genders with respect to the proportion of confirmed positive cases of COVID-19 (Peckham et al., 2020[11]). A study on European data estimated the increased risk of males to range from 11% to 54% (Ahrenfeldt et al., 2020[12]). Another estimate based on a review of existing studies, however, puts the relative risk to males higher at 86% (Biswas et al., 2020[13]). Nevertheless, these observations are mostly in line with the generally observed increased risk of mortality of males. To put this into perspective, males in the United States between the ages 55 and 80 have a higher risk of mortality than females between around 35% and 70%.6 Differences between genders by age also demonstrate a pattern consistent with baseline mortality, tending to increase until ages in the 60s and decreasing thereafter (Ahrenfeldt et al., 2020[12]).

There are some exceptions, however, with a handful of countries experiencing a higher case fatality rate for females. In India, for example, the case fatality rate at the end of September 2020, was 3.3% for women compared to 2.9% for men. Nepal, Slovenia, and Vietnam have also demonstrated higher case fatality rates for females. Nevertheless, it is difficult to determine whether these are the true differences in mortality or whether they may be caused by biases in reporting, testing or access to healthcare (Dehingia and Raj, 2021[14]).

Having an underlying comorbidity significantly increases the mortality risk of COVID-19. Kidney disease is among the most deadly, increasing the risk of death by nearly five times. Other comorbidities identified as significant risk factors include, in order of descending risk, cardiovascular disease (~3x), respiratory disease (2-3x), diabetes (~2x), hypertension (~2x), dementia (~2x), cancer (~2x), and liver disease (1.5x) (Biswas et al., 2020[13]; Cho, Yoon and Lee, 2021[15]).

Indeed, the vast majority of people who have died from COVID-19 have had at least one comorbidity, and multiple comorbidities are common. Among those who died of COVID-19 in Canada, for example, 90% had at least one other underlying condition, nearly two-thirds had at least two comorbidities and nearly half had three or more (Statistics Canada, 2021[16]). One study on a care home in Sweden showed that deaths during the first wave of the pandemic were mainly the frailest of the population having multiple comorbidities, with 92% of deaths having three or more comorbidities (Nilsson, Andersson and Sjödahl, 2021[17]).

Death among the population under 65 with no comorbidities has remained rare. Less than 3.6% of COVID-19 fatalities under age 65 in France, Italy, the Netherlands, Sweden, Georgia (USA), and New York City (USA) had no comorbidities, though Mexico presents an exception to this with nearly 18% of those dying under 65 having no comorbidity (Ioannidis, Axfors and Contopoulos-Ioannidis, 2020[18]). However, this could at least partially driven by lower levels or reporting or diagnosis of comorbidities in Mexico.

Frail populations are clearly more at risk of dying from COVID-19. This leads to the somewhat counterintuitive observation that countries having better health care systems also have higher COVID-19 death rates. This is because in these countries people are more likely to survive life-threatening events such as heart attacks and strokes, making the overall population frailer on average. One study found that for every 1% increase in the size of a country’s population surviving heart conditions or stroke, the death rate from COVID increased by 19% (Botly et al., 2020[19]).

That frailer populations are more at risk supports the hypothesis that many of the deaths from COVID-19 are accelerated deaths that may well have occurred in the short-term regardless. This phenomenon has been observed in past pandemics as well. Following the Spanish Flu of 1918-1919, the gap in life expectancy between males and females significantly decreased. This is likely because many of those dying during that pandemic also had tuberculosis. Indeed, tuberculosis rates dropped in the years following the Spanish Flu, and disproportionately so for males (Noymer and Garenne, 2000[20]).

There is mixed evidence as to whether more disadvantaged groups have been at higher risk of dying from COVID-19. The link between socioeconomic status and COVID-19 mortality risk varies from one country to the next, therefore local context seems to play an important role in the difference in outcomes.

Higher levels of deprivation have been associated with higher COVID-19 mortality in several jurisdictions. In England, a one percentage point increase in the proportion of the population experiencing income deprivation was found to lead to a 2% increase in COVID-19 mortality rates (Rose et al., 2020[21]). In Scotland as well, mortality rates were two times higher for those from the most deprived areas, controlling for age and sex (Lone et al., 2021[22]). A strong gradient of excess mortality and socioeconomic status was also found in Santiago, Chile (Mena et al., 2021[23]).

Nevertheless, other studies have not shown a conclusive link between socioeconomic status and COVID-19 mortality. In Germany, one study found no evidence of a link between poverty and COVID-19 mortality during the first wave of the pandemic (Ettensperger, 2021[24]). In Wisconsin, USA, poverty was found to be associated with higher rates of admission to the Intensive Care Unit, but not higher rates of death (Muñoz-Price et al., 2020[25]). Supporting these results, a study using US Census data did not show income or poverty to be a significant factor in predicting mortality (McLaren, 2020[26]).

The drivers of these disparities and the potential increased mortality risk for lower socioeconomic groups vary across countries. A common explanation put forward is that lower socioeconomic groups have a higher incidence of comorbidities that increase the mortality risk from COVID-19. In the United States, those with either lower education or lower incomes have higher rates of every medical risk factor (Wiemers et al., 2020[27]). In Chile, people living in lower socioeconomic areas are more likely to be overweight and live in crowded conditions (Mena et al., 2021[23]). However, in England, the higher mortality risk for more deprived groups was not significantly explained by medical risk factors (Williamson et al., 2020[28]).

Access to medical care and health services is another potential driver of observed differences. In Chile, lower socioeconomic neighbourhoods experienced more testing delays (Mena et al., 2021[23]).

Higher rates of infection may also play a role. Lower socioeconomic groups may be more likely to have occupations that do not allow for teleworking, increasing their risk of infection. In Chile, lockdown measures were less effective at reducing people’s mobility in more disadvantaged areas (Mena et al., 2021[23]). Lower socioeconomic groups in Korea were also shown to be at higher risk of contracting COVID-19, particularly for those over the age of 60 (Oh, Choi and Song, 2021[29]).

Large disparities of mortality rates due to COVID-19 across ethnic groups have been observed in some jurisdictions. In the United States, Black, Hispanic, and Native populations have been at least twice as likely to die of COVID-19 compared to the White population (Center for Disease Control and Prevention, 2021[30]). This led to a reduction in life expectancy in 2020 for Blacks and Hispanics that was two to three times greater than for Whites (Woolf, Masters and Aron, 2021[31]). In England, the Black male population’s mortality risk was 3.7 times that of the White population during the first wave of the pandemic, and nearly all ethnic minorities were at higher risk of death than Whites. During the second wave, the mortality risk for the Bangladeshi population increased substantially to 4-5 times that of the White population (Office for National Statistics, 2021[32]).

The higher risk to ethnic minorities is clear, though factors other than ethnicity are likely driving these results. One study in Louisiana confirmed that while Blacks had a much higher rate of hospitalisation and deaths than Whites, race itself was not an explanatory factor in the conditional survivor probability when controlling for other factors (Price-Haywood et al., 2020[33]).

There are several explanations put forward to explain observed differences across ethnic groups, including that they tend to be from more disadvantaged backgrounds, have higher rates of comorbidities, or have higher rates of infection. However, there is not strong evidence supporting the explanation that these populations tend to more often be from lower socioeconomic backgrounds. One study in England showed that only a small part of the excess risk could be attributed to higher levels of deprivation (Williamson et al., 2020[28]). Another study in Wisconsin, USA found no strong relationship between socioeconomic status and race (Muñoz-Price et al., 2020[25]). An analysis using US Census data also found no evidence that income, poverty rates, or educational differences were driving the racial disparities for Black and Native populations, though education did seem to be a factor for differences observed for the Hispanic and Asian populations (McLaren, 2020[26]).

That minority populations suffer from higher rates of comorbidities seems to be a more plausible explanation for their increased mortality risk. In the United States, Blacks have a higher prevalence of most of the COVID-19 risk factors than Whites (Wiemers et al., 2020[27]). In one study in Louisiana, USA, Black patients had a higher prevalence of obesity, diabetes, hypertension, and chronic kidney disease (Price-Haywood et al., 2020[33]). In contrast, another study in England showed that a higher prevalence of medical problems did not fully explain observed disparities (Williamson et al., 2020[28]).

Higher infection rates may be another explanatory factor for observed ethnic disparities. In the Wisconsin study, Blacks were more likely to test positive for COVID-19, even when controlling for demographics, health and geography (Muñoz-Price et al., 2020[25]). Another study linked the increased risk to the use of public transportation and to the prevalence of heath support workers in the population (e.g. home aids, nursing assistants), in line with the theory of increased exposure leading to higher rates of infection (McLaren, 2020[26]).

The indirect consequences of the COVID-19 pandemic on mortality have potentially been large. The gap between officially reported COVID-19 deaths and the number of excess deaths presented in Figure ‎4.4 and Figure ‎4.5 provided some indication of the magnitude of this impact. This section aims to better understand the drivers of excess deaths not directly related to the COVID-19 virus itself. Drivers identified include reduced healthcare access, the impact of lockdown measures on well-being and behaviour, and the broader economic impact that the response to the pandemic had.

The COVID-19 pandemic caused significant disruptions to health services, including essential and emergency care that could have led to excess mortality from health problems other than COVID-19. A survey by the World Health Organization (WHO) found that 94% of the 135 responding countries experienced some disruption to essential health services, and over a third of the countries experienced disruptions to over half of their services. This included potentially lifesaving emergency, critical and operative interventions, which were disrupted in 20% of the countries. Over 40% of countries had disruptions to mental, neurological and substance abuse services, and a third experienced disruptions related to pre- and post-natal care. While less impacted, 26% of high-income countries still experienced disruptions (World Health Organization, 2021[34]).

Disruptions to health services, in particularly urgent care services, likely led to an increase in mortality for those unable to obtain needed treatment. One survey in the United States indicated that 1-2% of individuals surveyed were not able to access needed urgent care in the prior two months specifically because of the pandemic (Center for Disease Control and Prevention, 2021[35]). Deaths from Alzheimer’s and heart disease significantly increased in the United States during the peaks of the pandemic (Woolf et al., 2021[36]). The United Kingdom estimated that 6 000 of the excess non-COVID-19 deaths in March and April 2020 were due to changes in emergency care, compared to 42 000 deaths attributed directly to COVID-19. Another 10 000 are estimated to have died as a result of changes to adult social care, including early discharge, lack of emergency health care, and changes in the quality of care (Office for National Statistics, 2020[37]).

Avoidance of health care facilities because of a fear of being infected also likely played a significant role in the increased deaths among those not receiving needed care. In Northern Italy, emergency visits and hospitalisations decreased across all age groups and all types of diagnoses shortly after the first confirmed COVID-19 case in Italy. However, out-of-hospital mortality from neoplasms, cardiovascular and endocrine diseases significantly increased during lockdown, indicating that these individuals were not seeking needed care at the hospital (Santi et al., 2021[38]). Similarly, in Denmark, non-COVID-19 hospital admissions decreased by 30% after the first lockdown, and by 22% following the second lockdown after trends had returned to baseline levels. Despite this, mortality rates for non-COVID-19 diseases increased by over 20% during the lockdowns, and mortality rates from respiratory diseases, cancer, pneumonia, and sepsis remained higher over the entire period (Bodilsen et al., 2021[39]). In England and Wales, deaths from ischaemic heart disease, asthma, and diabetes increased, despite a reduction of these deaths in hospitals, indicating that many of these deaths were due to not receiving care (Kraindler, Barclay and Tallack, 2020[40]).

Disadvantaged groups of the population were in many cases more likely to experience reduced access to health care services. In Europe, a strong socioeconomic gradient was observed by socioeconomic status and previous health conditions for those experiencing foregone, postponed, or unavailable care, meaning that those who were more economically vulnerable and in poor health had less access to the health system (Börsch-Supan, 2021[41]). In the United States, the proportion of individuals not having access to urgent care because of the pandemic was negatively correlated with education level (Center for Disease Control and Prevention, 2021[35]). In addition, Black, Hispanic, and disabled populations were more likely to avoid urgent or emergency care during the first wave of the pandemic (Czeisler et al., 2020[42]). Hospital restrictions also seem to have been unbalanced in some cases, with sites caring more for Black populations being more impacted by lockdown measures. In a study on US patients with prostate cancer, prostatectomies decreased by over 90% for Blacks compared to only 17% for Whites, a difference not explained by the clinical parameters such as risk factors and age. While surgical treatments were restricted during lockdowns to prioritize those needing emergency care, some sites experienced increased surgical volume while those treating a higher proportion of Black patients paused surgeries completely (Vince, 2021[43]).

Capacity constraints and diminished resources could also put developing countries at increased mortality risk, especially children. Vaccination programmes against diseases other than COVID-19 in particular have been significantly disrupted. As of April 2021, vaccination programmes in 50 countries were still postponed, meaning that 228 million people faced an additional risk of contracting life threatening diseases such as measles, polio, and yellow fever (WHO, 2021[44]). Missed vaccinations may also reduce herd immunity, presenting a larger risk to these populations as a whole. This is not without precedent. During the Ebola outbreak in 2014, vaccinations for infants under one year fell by 75%, vaccinations for measles fell by 20%, and around half of the children in the three most affected countries did not receive all of their routine vaccinations (Elston et al., 2017[45]).

Past experience has shown that the unavailability of healthcare or the reluctance to seek healthcare during health crises can be particularly detrimental to pregnant women and children, especially in developing countries. At the height of the Ebola outbreak in 2014 in Sierra Leone, maternal mortality increased by 170%, and still births increased by 40%. Over that year, reduced access to routine health services increased maternal and child mortality by 22% and 25%, respectively, with preventable and treatable infectious diseases being a major contributor to the latter (Elston et al., 2017[45]). Applying this experience to the COVID-19 pandemic, one theoretical model estimated that child mortality could increase by up to 45%, and maternal mortality by up to 39%, in low-income and middle-income countries. 60% of the increase in maternal deaths were due to reduced access to key childbirth interventions, while 40% of the increase in child deaths were due to reduced access to treatments for pneumonia, sepsis, and diarrhea (Roberton et al., 2020[46]).

The strict lockdown measures that many governments implemented during the peak waves of the COVID-19 pandemic had a significant toll on the mental health and well-being of the populations impacted. In the United Kingdom, the proportion of adults experiencing some form of depression in early 2021 doubled from pre-pandemic levels, with young adults and women more impacted (Office of National Statistics, 2021[47]). Similarly, the proportion of adults having symptoms of anxiety or depression increased by 5 percentage points over the period from August 2020 to February 2021, with young adults being particularly impacted (Vahratian et al., 2021[48]). Such declines in wellbeing can lead to potentially fatal detrimental behaviour linked to substance abuse or even suicide. Declines in well-being at home may also pose a threat to those in abusive relationships. On the positive side, in some jurisdictions social distancing may have reduced the number of homicides during lockdown periods, reduced traffic fatalities, and reduced fatalities from other contagious diseases such as seasonal influenza.

The boredom and reductions in well-being that accompanied lockdown measures exacerbated existing negative trends with respect to substance abuse and fatalities from drug overdoses. In the United States, deaths from drug overdoses increased by 29% in 2020 compared to 2019. That amounted to 93 000 people, or to put this into perspective, about 25% of the number of deaths due directly to COVID-19 (OSF Healthcare, 2021[49]). In 2020, more than twice the number of people in San Francisco, California died of overdoses than of COVID-19 (The Economist, 2021[50]). Ontario, Canada experienced an increase of 75% in deaths from opioid overdoses in 2020 compared to 2019, with an 82% increase for the 25 to 44 age group (Gomes et al., 2021[51]). Alcohol-related deaths also increased substantially in Canada in 2020, increasing by more than 20% for those under the age of 65, and by nearly 50% for those under the age of 45 (Statistics Canada, 2021[52]).

The alarming increase in overdoses has been directly linked with the lockdown orders imposed in certain areas. Weekly median death rates from overdoses in San Francisco, California increased by 50% following the shelter in place order (Appa et al., 2021[53]). Overdose deaths in Ohio, USA increased by over 70% within two months following the declaration of a national emergency before decreasing again by August 2020. The largest increase was for ages under 25, whose death rates more than doubled compared to 2018-2019, and ages over 65 where the increase was just under 90% (Currie et al., 2021[54]).

However, the impact of lockdowns on substance abuse varies across countries. While the data is less conclusive, some evidence indicates that drug use declined during the strict lockdown periods in Europe, largely due to disruptions in the supply chain and less opportunity to use. Overdose deaths seem to have been lower in Italy and Portugal. However, they may have been higher in Finland, and they increased in Spain once lockdown restrictions eased. Other worrisome trends indicate that there could be an increase in problems linked to substance abuse in the coming years. Cocaine shipments seem to have increased substantially in Europe, and the product has also become more potent (UNODC, 2021[55]).

While depression and anxiety rose during the pandemic, this did not seem to lead to an immediate increase in suicide mortality in most countries. In one study of 21 high- and upper-middle-income countries, no significant increase in suicides was observed through the end of July, 2020 (Pirkis et al., 2021[56]). Suicides even declined in some jurisdictions, such as the United States where suicides in 2020 were 6% lower than in 2019 (Ahmad and Anderson, 2021[57]). One explanation for this could be that significant efforts were put into offering support to those at risk, in recognition of the impact that lockdown could have on mental health. Another, observed in previous epidemics, is the feeling of community and everyone going through hard times together. The economic assistance that many governments provided in high-income countries could have also mitigated any increase in the short term (John et al., 2020[58]).

Indeed, there is some evidence that the impact of the pandemic on suicide rates could still be observed going forward. Japan, Puerto Rico and Vienna, Austria all showed signs of an increase in suicides following the initial wave (Pirkis et al., 2021[56]). Following an initial decline of 14% in Japan during the first five months of the pandemic, suicides increased by 16% during the second wave, particularly for females and adolescents (Tanaka and Okamoto, 2021[59]). In Peru, the downward trend in suicides seemed to reverse in the post-lockdown period (Calderon-Anyosa and Kaufman, 2021[60]).

In addition, suicide rates may have increased for certain groups of the population. There were some signs that child suicide rates increased in the United Kingdom during the first lockdown period (Odd et al., 2021[61]). During the first wave of the pandemic, suicides among the Black population in Maryland, USA appeared to have doubled compared to previous years, while among the White population suicides nearly halved (Bray et al., 2021[62]). In the United States, emergency room visits due to suicide attempts by adolescent girls increased by 51% in early 2021 compared to 2019, while rising only by 4% for boys (U. S. Surgeon General, 2021[63]).

Lockdown measures may have increased violence against women, as those in abusive relationships became trapped at home with their abusers. Data early in the pandemic showed a worrying increase in the reports of domestic violence and calls to emergency and helplines, with observed increases between 25% to 33% in Argentina, Cyprus, France and Singapore (UN Women, 2020[64]).7 In Peru, calls to helplines for domestic violence increased by 48% (Calderon-Anyosa and Kaufman, 2021[60]). In South Africa, gender-based violence cases increased by 37% during the first week of lockdown in April 2020 (Warah, 2021[65]).

This increase in domestic violence has not necessarily translated into increased femicides, however. Femicides have decreased slightly in Mexico after remaining constant during the lockdown period, and have also decreased in Argentina, France, Peru, and Portugal, though in the latter the number of attempted femicides has not decreased (Hoehn-Velasco, Silverio-Murillo and de la Miyar, 2021[66]; Statistica, 2021[67]; Le Monde, 2021[68]; Calderon-Anyosa and Kaufman, 2021[60]; OMA-UMAR, 2020[69]).

Nevertheless, femicides have increased in some jurisdictions, and for others there are signs that an increase is yet to come. Femicide rates nearly doubled in the United Kingdom during the first weeks of the pandemic (Guerra Lund, Manica and Mânica, 2020[70]). A significant increase was also observed in Quebec, Canada (Laou, 2021[71]). Femicides followed a steady increasing trend between March and August, 2020 in Colombia (Statistica, 2021[67]). In Peru, over 900 women, of which two-thirds were children, were reported missing during the three and a half months of lockdown, and many missing person reports later end up being femicides (Charrier, 2020[72]). In addition, a significant portion of femicides occur at the moment of separation from the partner, whereas women were not able to leave during lockdown periods (Shiloh Vidon, 2021[73]). Lockdown measures may also have reduced the opportunity for femicide. In Peru, for example, bodies are most frequently found outside of the home (Casana-Jara, 2020[74]). It may therefore be the case that femicides could increase in the months following lockdowns.

While lockdown measures had a significant positive influence on crime rates, which experienced sharp reductions, homicide rates seem to have been less impacted. While overall crime reduced by 37% in European cities, the reduction was lowest for homicides, which went down by only 14% (Nivette et al., 2021[75]). Homicides in Mexico did not experience a big change, even though other types of crime reduced during lockdown before returning to pre-pandemic levels (Balmori de la Miyar, Hoehn-Velasco and Silverio-Murillo, 2021[76]). Other areas in Latin America experienced a more significant drop, with homicides reducing by 24%, 29% and 76% in large cities in Brazil, Colombia and Peru, respectively, though in Peru rates started to pick back up following the lockdown period (Nivette et al., 2021[75]) (Calderon-Anyosa and Kaufman, 2021[60]). Despite a significant drop in crime in large cities in the United States during lockdown orders, homicides actually increased in the summer of 2020 (Abrams, 2021[77]).

Lockdown measures led to a significant drop in traffic, though this did not always translate into a reduction in traffic fatalities. Nevertheless, many countries did experience a substantial drop in traffic deaths. Peru experienced a larger drop in fatalities related to traffic accidents than the reduction in suicides and homicides (Calderon-Anyosa and Kaufman, 2021[60]). Stay-at-home orders in March and April, 2020, reduced traffic deaths in Türkiye by 72% (Oguzoglu, 2020[78]). Across Europe, traffic fatalities decreased by 17% on average, although fatalities actually increased in Finland, Ireland, Latvia, Estonia, Luxembourg, Switzerland, and Iceland (European Commission, 2021[79]). Only a slight decrease was observed in Japan, and fatalities increased in certain prefectures such as in Tokyo (Tauchi, 2021[80]).

Globally, the change in traffic fatalities was not proportional with the change in traffic. In April 2020 the International Transport Forum found a decrease in road deaths by only a third, even though traffic was halved (ITF, 2020[81]). Other jurisdictions experienced an increase in traffic fatalities, despite less driving. In Ontario, Canada, traffic fatalities increased by 22% despite a reduction in accidents of 26% (The Canadian Press, 2021[82]). In the United States, traffic deaths increased by 7.2% compared to 2019 despite a 13.2% decrease in miles driven (NHTSA, 2021[83]). The increase in fatalities in both jurisdictions was attributed to an increase in reckless driving practices.

Improved hygiene and social distancing measures, including the use of masks, have not only helped in preventing the spread of COVID-19, but have also led to a significant reduction in the transmission of contagious diseases, in particular seasonal influenza. In normal years, seasonal influenza is a significant cause of mortality globally, with around 300 to 500 thousand deaths each year associated with influenza (Paget et al., 2019[84]). During the 2020-2021 influenza season, samples testing positive for influenza fell to practically zero in the WHO European Region (the European Influenza Surveillance Network, 2021[85]). It has also reached historical lows in the United States, Australia, Chile, and South Africa during 2020 (Olsen et al., 2020[86]).

While fewer people certainly lost their lives to influenza, the net benefits are less clear. The elderly more susceptible to seasonal influenza would be also more at risk for COVID-19. In addition, the absence of the seasonal influenza epidemic could lead to a reduction in herd immunity, leading to more severe and longer epidemics in coming flu seasons (Sanz-Muñoz et al., 2021[87]).

Economic cycles can have an impact on mortality because of changes in employment situations, daily behaviour and habits, and public spending. During the first year of the pandemic, many governments provided economic aid that shielded people from the full impact of the economic fallout resulting from lockdown requirements and business closures. However, the effects of any enduring unemployment and cuts to public spending may continue to be felt in the near to medium term, which could have possible ramifications on mortality. Countries providing less economic aid during the crisis likely already felt some of these effects. Additionally, negative effects on mortality can persist for years following a recession (Doerr and Hofmann, 2020[88]).

Many of the potential impacts on mortality from difficult economic environments are similar to the indirect effects on mortality already discussed in the context of COVID-19, although the drivers and dynamics of these impacts are subtly different so are worth discussing separately. Access to healthcare can be impacted through a reduction in public spending, as opposed to capacity constraints and fear of infection. As with lockdowns, increased unemployment can change daily habits and behaviours, and have important impacts on well-being, but without the accompanying social restrictions. As with COVID-19, disadvantaged populations tend to be more negatively impacted, as they are more likely to experience a loss of income from unemployment that will impact access to food and healthcare, with particularly harmful consequences for the young and the elderly.

Counterintuitively, recessions have actually been shown to be beneficial for mortality in many developed economies, and in the United States in particular. One widely cited study of the period 1972-1991 finds evidence that mortality increases in periods of higher growth, which the author attributes to higher rates of smoking and obesity, less physical activity and a poorer diet. In contrast, during periods of unemployment, people have more time to dedicate to their health. A reduction in accidents also significantly contributes to reduced mortality in recessions – as was also expected during COVID lockdowns – that primarily impacts young to middle ages. Overall, the study finds that a single percentage point increases in state unemployment rates reduce mortality by 2% (Rhum, 2000[89]). Reductions in mortality from accidents during recessions, particularly for younger men, have also been observed in Australia, France, Greece, Korea (Brüning and Thuilliez, 2019[90]; Laliotis, Ioannidis and Stavropoulou, 2016[91]; Kim et al., 2003[92]).

Suicides, however, are an important exception to the pattern of pro-cyclicality of mortality with the economy. The same study demonstrating the pro-cyclicality of mortality in the United States finds that suicides rise by 1.3% for each percentage point rise in unemployment (Rhum, 2000[89]). Increased suicides during economic crises have also been observed in Greece, Hong Kong (China), Japan, and Korea (Laliotis, Ioannidis and Stavropoulou, 2016[91]; Chang et al., 2009[93]). In one longitudinal study in Sweden, unemployment increased the risk of death for the working age population by nearly 50%, controlling for other characteristics such as health (Gerdtham and Johannesson, 2003[94]). Across Europe, a one percentage point increase in unemployment corresponds to a 1% increase in suicides for the working age population, but there is no impact on those over the age of 65 (Breuer, 2014[95]). Contrary to some increases observed during the COVID-19 pandemic, however, suicides during periods of high unemployment tend to affect men the most. This could imply that suicide patterns during COVID lockdowns may be more linked to the social situation imposed by lockdowns rather than economic hardship per se.

The pattern of pro-cyclicality of mortality in developed countries seems to be reversing more recently. An extension of the US study to 2010 showed that mortality has become more disconnected from macroeconomic conditions. The author attributes this mainly to recent negative trends in drug overdoses, which was also observed during the COVID lockdowns. While mental health has always been counter-cyclical, access to drugs is now easier so these troubles are more frequently fatal (Ruhm, 2015[96]). Mortality has also gone from being pro-cyclical to counter-cyclical in France, where mortality no longer decreases when unemployment increases (Brüning and Thuilliez, 2019[90]). While some pro-cyclical drivers of mortality were observed in Greece following the 2008 financial crisis – such as fewer respiratory infections, reduced smoking, and increased physical activity – mortality improvements still slowed during this period (Filippidis et al., 2017[97]; Laliotis, Ioannidis and Stavropoulou, 2016[91]). Another notable observation occurred in Australia, where the introduction of universal healthcare eliminated pro-cyclical mortality for female infants (Atalay et al., 2021[98]). Pro-cyclical mortality among infants in developed countries has been attributed in part to mothers having more time available to attend to self-care and the health of their baby (Dehejia and Lleras-Muney, 2004[99]).

Taking a more global perspective, mortality is predominantly counter-cyclical, particularly in the developing world. In one study of 180 countries, mortality increased by 4% during years where GDP declined, and this increase lasted up to ten years following the recession. This result is driven mainly by emerging and developing economies, as the effect is often not significant in advanced economies (Doerr and Hofmann, 2020[88]). The negative effects of recession in developing countries are particularly detrimental to children. A 1% decrease in GDP per capita translates into 0.24-0.4 more deaths per 1 000 children in developing countries, and there is a larger impact on girls (Baird, Friedman and Schady, 2011[100]).

The loss of income is one factor driving increased mortality during recessions, particularly for poorer households who may then struggle to obtain enough food to feed their family or pay for needed medical care. In France, the negative impact of recessions on mortality is higher for more disadvantaged groups such as migrants and those with lower education (Brüning and Thuilliez, 2019[90]). In Mexico, an increase in elderly mortality following the 1995 crisis was associated with an increase in women entering the labour force. While this could be a result of women then being less able to care for elderly relatives, there is more evidence that this was a result of the drop in income that forced women to look for work (Cutler et al., 2000[101]). Similarly in France, increased unemployment is associated with increased mortality among the age group 65-74, particularly for men (Brüning and Thuilliez, 2019[90]).

Access to healthcare is another major contributor to excess mortality during recessions, even in more developed countries, and especially among the elderly. In Mexico, mortality for ages 70-79 increased by 1% during the 1995 crisis, driven by non-communicable diseases such as cardiovascular disease and chronic respiratory disease (Cutler et al., 2000[101]). Following the 2008 financial crisis in Greece, where healthcare expenditure decreased by 25%, mortality for ages over 65 increased mainly due to circulatory and digestive diseases (Filippidis et al., 2017[97]; Laliotis, Ioannidis and Stavropoulou, 2016[91]). Adverse events during medical treatments also increased, highlighting the importance of the quality of healthcare (Laliotis, Ioannidis and Stavropoulou, 2016[91]). In Spain, during this same period of high austerity, winter mortality increased for ages over 60, particularly for males (Benmarhnia et al., 2014[102]).

While the short-term impacts of COVID-19 on mortality continue to emerge, we can expect most of these impacts to be temporary as the drivers of excess mortality subside. Nevertheless, COVID-19 could also have some effects on mortality that could emerge over time. The COVID-19 virus itself may have a long-term impact on health or immunity. The pandemic situation may also have exacerbated political and societal trends that could have long-term implications for future trends in life expectancy.

COVID-19 may have long-term health implications that could increase the mortality risk of survivors. Many people who contracted and survived COVID-19 have experienced symptoms for weeks or even months, even if their initial symptoms were mild to moderate, a situation which has now commonly become known as “Long COVID”. While studies may be biased towards hospitalised patients, one review of current literature estimates that 56% of confirmed COVID-19 cases experience symptoms beyond 12 weeks, and that 10% of these were not able to return to work (Domingo et al., 2021[103]). A broader and ongoing study in the United Kingdom indicates that up to 12% of infected individuals report to have symptoms lasting beyond 12 weeks, and up to 18% for those having symptomatic acute infections (Office for National Statistics, 2021[104]). Nevertheless, long-term medical problems reported are not necessarily the same symptoms as for the acute infection, and can include respiratory issues, neurological problems, gastrointestinal disorders, cardiovascular disorders, and a higher risk of having mental health issues (Al-Aly, Xie and Bowe, 2021[105]).

There is evidence that COVID-19 can cause lasting damage to the kidneys, lungs, heart, and brain, which could potentially lead to increased mortality risk. Severe illness from COVID-19 can lead to a long-term reduction in kidney function, and even patients experiencing moderate illness were shown to be at increased risk of death over the next six months (Bowe et al., 2021[106]). In another study, a third of a sample of hospitalised patients experienced lung tissue death (Marshall, 2020[107]). Heart injury has been in a quarter of hospitalised patients, and 60% of patients having recovered from COVID-19 had lasting heart inflammation (Giustino et al., 2020[108]; Puntmann et al., 2020[109]). There is also evidence that COVID-19 blocks blood flow to the brain (Hirunpattarasilp et al., 2021[110]). Long-term health impacts of these clinical observations could include kidney or heart failure, chronic respiratory problems, strokes, or even an increased risk of Parkinson’s and Alzheimer’s disease (Mayo Clinic, 2021[111]).

Evidence of longer-term complications can be found in patients recovering from the related diseases of severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS). Abnormalities in lung functioning, reduced exercise capacity, and psychological problems are common in survivors of SARS and MERS even 12 months after they have been discharged from the hospital (Ahmed et al., 2020[112]). After 15 years, 4.6% of SARS patients still had visible scarring on their lungs, and 38% had diminished lung functioning (Zhang et al., 2018[113]).

Studies on the Spanish Flu of 1918 have shown that there may be lasting health impacts to individuals exposed to viruses around birth. Children born in Sweden in 1919 are estimated to have had three months shorter life expectancy than proximate cohorts. The 1919 cohort ultimately had worse health and socioeconomic outcomes in old age, and males exposed to the virus during the second trimester experienced higher rates of heart disease and cancer (Helgertz and Bengtsson, 2019[114]). Similarly, in the United States, cohorts exposed in late gestation and at birth experienced 8-9% higher mortality from all causes, translating into at least seven months lower life expectancy at age 70 compared to surrounding cohorts. Those born during the peaks of the pandemic had higher mortality in particular from respiratory and cardiovascular disease, but also fewer cancer deaths (Myrskylä, Mehta and Chang, 2013[115]). These outcomes could mean that the 2020-2022 cohorts born during the COVID-19 pandemic could experience specific patterns of future mortality improvements and lower life expectancies compared to surrounding cohorts.

There is also evidence that any immunity acquired during a flu pandemic can affect future immune responses to other viruses, especially immunity acquired in childhood. One recent and plausible explanation put forward for the high fatality rate for young adults during the Spanish flu is the concept of antigenic imprinting, where the body’s antibody response is significantly influenced by the influenza strains exposed to in childhood. The ages experiencing the highest fatality during the Spanish flu would have been young children during the H3N8 Russian influenza in 1889-1890. The Spanish flu was caused by another type of influenza strain, the H1N1 strain. The antigenic imprinting theory proposes that the immune response of this cohort was dominated by antibodies responding to the earlier strain, and therefore not effective against the H1N1 strain (Gagnon et al., 2013[116]). This theory could also explain differences in the prevalence of infection from different flu strains for cohorts born before and after the Hong Kong flu of 1968 (Woo, 2019[117]).

Immune responses to coronaviruses may also be influenced by past exposure, which can have implications for future immunity. One study found that while the antibodies found in patients who had recovered from SARS were not effective against COVID-19 by themselves, these patients had a very strong immune response to the Pfizer vaccine, even after just one dose. The antibodies they developed were also effective against a broader range of coronavirus variants, which was not the case for others vaccinated for COVID-19 (Tan et al., 2021[118]). Other researchers have speculated that there may be some level of protection offered from T cells developed in response to other types of coronavirus, which seem to also be more effective than antibodies against different variants (Redd et al., 2021[119]; Tarke et al., 2021[120]; Geers et al., 2021[121]; Doshi, 2020[122]). Nevertheless, more research is needed to investigate the implications of the immune response to different strains of coronavirus.

Populations in democratic countries generally have higher life expectancies. Countries scoring at least 0.7 on the Liberal Democracy Index all had life expectancies over 74, while those countries having life expectancies under 60 all score below 0.5 on the Index (Figure ‎4.8).

Indeed, democracy seems to matter more than economic measures for measures of health of a population. Democracy is more strongly associated with higher life expectancy than a country’s GNP, level of inequality, and public expenditure (Franco, Álvarez-Dardet and Ruiz, 2004[124]). Democratic experience also explains more of the variation in mortality from cardiovascular disease, transport injury, cancer, cirrhosis, and other non-communicable diseases than GDP does (Bollyky et al., 2019[125]).

Political shifts have led to significant changes in life expectancy in the past. Life expectancies in the Central and Eastern European and Baltic countries started improving in the 1990s following the collapse of the Soviet Union, after years of stagnation and even decreases in life expectancy. Following the German reunification of 1990, the life expectancy of East Germans rapidly caught up to that of West Germans. One estimate is that East German men and women would have had 5.7 years and 4 years lower life expectancy, respectively, if reunification had not occurred (Vogt, 2013[126]).

Over recent decades there have been trends in the opposite direction, indicating some reversal in trends towards democracy, even in established democracies. Since 2005, the number of countries classified as “Free” by Freedom House has gone from 89 to 82, while the number of “Not Free” countries has increased by 9 over the same period. The “Democracy Gap”, or the number of countries whose aggregate Freedom score declined compared to those where it has increased, has been negative over the last 15 years and reached its highest level over that period in 2020 (Repucci and Slipowitz, 2021[127]). At an international level, some researchers have observed a decline in overt efforts to promote democracy, which has contributed to an increased willingness by some governments in developing democracies to violently oppose pro-democracy demonstrations and political opponents (Hyde, 2020[128]). Societal preferences have also moved away from democratic values in some areas. For example, in 2018, for the first time less than half of Latin Americans expressed full support for democracy, and nearly a third expressed indifference between a democratic or authoritarian regime, twice the proportion expressing an indifference two decades ago (UNDP, 2020[129]).

The COVID-19 pandemic exacerbated these trends. From January to August 2020, measures assessing the condition of human rights and democracy decreased in 80 out of 192 countries, or over 40% of the countries assessed, with struggling democracies and highly repressive states being the most impacted (Repucci and Slipowitz, 2020[130]). There is also evidence that the pandemic may have influenced public preferences for democracy, at least in the short term. At the beginning of the pandemic, Spaniards expressed higher preferences for strong leadership, technocracy, and authoritarian government, as well as more willingness to give up individual freedoms (Amat et al., 2020[131]).

Nevertheless, COVID-19 is unlikely to have an enduring negative impact on established democracies. To the contrary, public opinion may push these countries to place more weight on public health issues and the opinions of experts (Rapeli and Saikkonen, 2020[132]). However, social media has still facilitated the spread of misinformation that reinforces some groups’ beliefs in the effectiveness of unproven treatments or the dangers of vaccination against COVID-19. This type of polarisation is likely to endure.

COVID-19 has had a significant impact on mortality and life expectancy in the short term, but the impact on mortality assumptions used in the context of asset-backed pensions should be much lower. Many of the mortality shocks will be temporary, and mortality rates can be expected to return to their prior trajectories. Longer-term impacts are significantly less certain, however, thereby increasing the potential risk that experience will deviate from best estimate assumptions. This calls for the ongoing monitoring of longevity experience. Impacts will also vary widely from one country to the next, depending on factors such as the level of development, baseline health, and conditions during lockdown. These differences will need to be considered when assessing the impact of the COVID-19 pandemic on mortality assumptions.

The immediate impact of the COVID-19 virus itself will be a temporary shock to mortality. The evidence shows that across ages and genders, the shock to mortality seems to have been broadly parallel to the baseline curve. That is, the pattern of mortality across ages and genders was similar to a normal year, albeit at a higher level. Once the pandemic subsides, mortality rates should return to their baseline levels. This was the case following the Spanish Flu pandemic of 1918-1919. Figure ‎4.9 shows that life expectancy returned to its previous trend within three to four years, even exceeding the level observed prior to the pandemic.

Indeed, the frailest of the population are more likely to have died during the COVID-19 pandemic, and we can expect the survivors to be relatively stronger on average, resulting in lower mortality in the years following the peak of the outbreak. Many of the deaths due to COVID-19 may have been accelerated deaths that would have occurred anyway over the next several years. This is supported by evidence that the specific groups experiencing higher mortality were also the ones having a higher mortality risk generally, in particular those with higher rates of comorbidities. This selection effect will likely be short-lived, however, with mortality levels returning to their previous trajectory within a few years, as they did following the Spanish Flu pandemic of 1918-1919 (Figure ‎4.9).

Nevertheless, the impact of COVID-19 on mortality will likely still be felt over the coming year or two, as new variants emerge that may be more contagious or able to evade vaccines. Indeed, elevated excess mortality continues, at least in cycles, in many jurisdictions. Nevertheless, while variants of the virus continue to infect even vaccinated individuals, increased immunity has led to lower rates of health complications and deaths.

Viruses causing past pandemics have eventually become endemic, as more people become exposed to the virus and it mutates and becomes less fatal, even if it manages to at least partially evade immunity (Callaway, 2021[134]) (Branswell, 2021[135]). If COVID-19 follows this trend as expected, the virus should eventually become endemic and continue to circulate among the population, likely causing milder symptoms like a seasonal cold, as with the other four coronavirus strains that currently circulate endemically among the human population. Nevertheless, while it is sure that the pandemic will eventually dissipate and large excess mortality levels will subside, uncertainty remains around the virulence of future variants and how long this process will take.

The impact of reduced healthcare access is also likely to be largely temporary. Disruptions to service should lessen as increased COVID-19 vaccination rates improve hospital capacity to care for other patients. Reductions in infections should also help assuage people’s fear to seek needed medical attention, and healthcare provision will likely return to its normal levels. Nevertheless, delayed diagnosis of serious illness, such as cancer, may increase mortality in the short term to the extent that early preventative measures were not taken. In addition, high levels of stress and burnout among medical staff could present a challenge to maintaining the same levels of healthcare, as many individuals could exit the profession.

Lockdown measures have also been lifted, though some of the impacts that these will have on mortality may still emerge over the next year or two. Homicides and traffic accidents are likely to quickly return to their previous levels with the lifting of lockdown restrictions, though a spike in femicides may yet occur as women may be more likely to try to leave abusive relationships. Lingering mental health issues from the lockdown situation may endure in the short term, potentially increasing suicide rates, particularly if the widespread awareness and support offered during lockdown is eased during the post-lockdown period. While lockdown exacerbated the existing trends in drug overdoses in some cases, the change in trends generally seemed to be linked directly to lockdown. Nevertheless, the increasing trend in overdoses can certainly be expected to continue barring major changes in the facility to access drugs, and may even accelerate. The reduction in herd immunity from seasonal influenza will likely mean that the flu epidemics of the coming years will be more severe, and potentially have a larger impact on mortality than recent epidemics. Thus, any short-term gains from reduced influenza deaths are likely to be neutralised, or even net out to be negative.

Enduring impacts of the economic shock may have a more lasting impact on mortality in the medium term, particularly in developing countries. Disadvantaged households are likely to be more negatively impacted, and elderly mortality could increase even in advanced economies if unemployment remains high and there are cuts to public spending on healthcare. Any positive effects on mortality of the working age population from higher unemployment, such as reduced traffic accidents, are likely to be outweighed by the negative trends in substance abuse and potentially increased suicides.

Longer-term health impacts of the COVID-19 virus cannot be known in advance, and will only emerge in the decades to come. Ultimately, a cohort effect may emerge in the data for survivors or for those born during the COVID-19 pandemic. Disadvantaged populations that experienced higher infection rates could be more impacted. These trends will need to be monitored over time.

Political shifts will also need to be monitored, though there does not seem to be an immediate threat to mortality from changing political actions and public preferences for established democracies. There may nevertheless be a negative shift in the long-term trend in life expectancy for newer or less stable democracies if the current trends with respect to the support for democracy continue.

Overall, COVID-19 is likely to have a negligible impact on the mortality assumptions used in the context of asset backed pension arrangements. In most cases, mortality and life expectancy are likely to return to their previous trends within a year or two, with COVID-19 representing a temporary – albeit large – negative shock.

In assessing the impact of the COVID-19 pandemic on mortality assumptions, it is important to consider the purpose of these assumptions within the context of the asset-backed pension system. Here, best estimate mortality assumptions are needed to estimate how long pensioners can expect to receive their retirement income with the goal to ensure that there will be sufficient assets to finance that income over their remaining lifetime. As such, it is important that these assumptions reflect the best estimate life expectancy of current and future pensioners who have survived the pandemic. Nevertheless, significant uncertainty around the potential longer-term effects that COVID-19 will have on longevity remains, and the assessment and management of longevity risk will need to account for this uncertainty.

Historical mortality experience is frequently used as a basis on which to establish mortality assumptions for both current mortality and future mortality improvements. In selecting which historical data to use to calibrate the assumptions, it is necessary to consider whether the mortality experience during the period selected will be reflective of the current and future mortality of the population to which they will apply. When there have been anomalous shocks to mortality or clear changes in historical trends, judgement is needed to determine whether that data should be included in any calibration of mortality assumptions.

Current mortality assumptions are usually based on recent mortality data of a population that is expected to be representative of the population to whom the assumptions will apply. To reduce random volatility and increase the robustness of the assumptions, a span of several years (e.g. the last three to five years of data) is normally used.

In the context of the COVID-19 pandemic, the mortality experience from the years 2020-2021 should be adjusted or excluded from any calibration of current mortality assumptions, as their inclusion would significantly increase the calculated level of mortality.8 Given that the main impacts of the virus and indirect effects of the pandemic such as reduced access to health care have likely already been realised, this experience should not be relevant for estimating the mortality of those who survived this period. Nevertheless, somewhat higher excess mortality has also continued into 2022, which could justify an adjustment to this year’s assumed level of mortality to be higher than otherwise expected.

Going forward, basing current best estimate mortality assumptions on the average mortality excluding the shock from the pandemic seems reasonable. Additional adjustments could potentially be made based on any available measures or indices indicating changes in overall health or vulnerability for the currently surviving population relative to levels prior to 2020.

The calibration of future mortality improvement assumptions normally relies upon a much longer period of historical experience, as these assumptions intend to capture the long-term trajectory that mortality will follow. As such, the period over which these trends are based should be reflective of the trends expected to influence mortality going forward.

Here again, the mortality experience of the year 2020-2021 is a clear disruption to the long-term trend, and should normally be disregarded for the purpose of calibrating future mortality improvement assumptions. Nevertheless, future expectations regarding how the pandemic will affect mortality trends in the medium to long term can still inform modelling choices, and in particular whether mortality improvements could slow.

While mortality should return to its prior trajectory over the next few years, it will likely be rather volatile in the near term and long-term uncertainty in the trend remains. Mortality rates may initially decrease beyond what their prior trend implied, as the surviving population is likely to be stronger and healthier on average (see Figure ‎4.10 for an illustration). This decrease could potentially be partially offset, however, by higher mortality from the indirect effects of the pandemic – such as health care interruptions and more severe flu seasons – that should gradually subside.

The economic environment may have an additional impact on mortality over the medium term. In particular, if the higher public debt levels in advanced economies result in cuts to public healthcare spending, this could result in lower improvements to elderly mortality.

Nevertheless, in the longer term, the length of the historical period over which mortality improvement assumptions are calibrated should capture the expected trend in mortality going forward. Short-term volatility will be smoothed out and the effect of economic cycles on mortality captured, meaning that assumptions should be an appropriate best estimate on average.

The potential long-term effects of the COVID-19 virus on mortality remain highly uncertain and cannot yet be reflected in best estimate mortality assumptions. Assumptions will need to be regularly monitored and updated to adjust to any continued excess mortality in the short term. It will also be important that risk assessments reflect and account for the increased uncertainty in the long term. Stress testing of the assumptions can help to ensure that the potential impact of higher long-term mortality is understood and accounted for in the risk management strategy.

The expected volatility of mortality experience in the near term also highlights the need to be prudent with respect to any gains realised from a reduction in liability value resulting from the higher realised mortality during the COVID-19 pandemic. While reserves will no longer be needed to finance the pensions of those who died during the pandemic, there is a meaningful risk of underestimating the mortality of survivors in the near term, so some of these reserves may be need to be retained to cover the remaining liabilities rather than fully realised as profit. Mortality assumptions will need to be monitored to make sure they continue to be in line with observed experience and future expectations to ensure that reserves remain adequate.

The COVID-19 pandemic will eventually come to an end, and the mortality assumptions used in the context of asset-backed pension arrangements must reflect the best estimate view of what is most likely to happen going forward. At this point in time, the most likely scenario seems to be that mortality levels will return to their previous trajectory. While there remains significant uncertainty as to the long-term impact that the pandemic will have on mortality, how to deal with this uncertainty has not changed. Indeed, this is the nature of managing longevity risk.


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← 1. As of January 14, 2022.

← 2. This compares to 8.9 million deaths from ischaemic heart disease in 2019, the world’s biggest cause of death (World Health Organisation, 2020[137]).

← 3. As of January 14, 2022.

← 4. Simple average across countries and weeks.

← 5. Calculations based on male mortality with improvements from the AG2020 mortality table, assuming excess mortality of 8.7% in 2020, 10.4% in 2021 (the actual average weekly excess mortality observed each year in the Netherlands), and 5% in 2022.

← 6. Based on the 2019 general population life tables from the Human Mortality Database

← 7. Note by Türkiye: The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Türkiye recognizes the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Türkiye shall preserve its position concerning the “Cyprus” issue

← 8. The potential magnitude of this difference is shown in Figure ‎4.2.

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