Methodological Issues in Using the Upper Age Limit
It is noteworthy that in all of the case studies presented in this study, a similar pattern was observed—the person-year lost in the older age groups was not considered in calculating PYLL in some of the upper age limits such as 70 years and 75 years. For example, the person-year lost at age group 70–79 was not considered in the calculation of PYLL when the upper age limits of 70 and 75 were used, but it was not the case when age 80 was used as the upper limit. This was true in the case of Italy, Germany, and New York State. Although the reported age-groups were slightly different in the US compared to the other populations in the study, the pattern remained the same. In the US, the person-year lost in the older ages, such as in age-group 65–74 years, was nullified at the upper limit of age 70 but not so in the other two upper age limits of 75 and 80. These issues of calculating PYLL are important to consider because COVID-19 deaths occurred most commonly in the older age groups [2
Of the three age limits used in this study, choosing a cut-off age of 70 is obsolete based on the current state of life expectancy in most populations [18
]. Our data showed that the use of age 80 as the upper limit for PYLL calculations is probably more reasonable when the other two groups, ages 70 years and 75 years were compared. For example, deaths at ages 70 years and above had no additional contributions toward the calculation of PYLL at the upper limits of ages 70 and 75. While deaths due to COVID-19 were highest in the age group 70 years and above, as is consistent with other studies [2
], a complete elimination of the person-year loss in the older population may not provide a valid picture of the total PYLL in the context of this pandemic. The imprecise estimation of PYLLs and disability-adjusted life years (DALYs) are especially significant because these metrics are often used to determine resource allocation and health policy decision-making [22
]. The rationale for using age 80 was based on the current life expectancy at birth in most of the developed countries [18
]. However, as life expectancy increases, a further study may be justifiable, using another upper age limit (such as 85 or more) in the future. In addition to using age 80 as the upper limit in the context of developed countries, a standardized rate is recommended for cross-country comparisons [10
]. This research project will set new paradigms in the quantification of premature deaths in terms of person-years lost.
In a recent study [26
], Kirigia and Muthuri (2020) reported the economic impact of deaths due to COVID-19 in China. The total deaths in China was 2595, as of 24 February 2020. The total fiscal value of the COVID-19 deaths in that country was Int$
(International dollars) 924,346,795. The average fiscal value per death was Int$
356,203. If we want to translate the US deaths due to COVID-19 in terms of economic loss, that figure would be enormous.
The lack of consistency in age breakdown [21
] and reporting of age-specific death rates instead of the number of deaths by age [22
] are identified as important methodological issues. Due to these issues, the data of China, Spain, and France could not be used in the analyses. However, the primary goal of this study is to evaluate whether PYLL can be used as an indicator of societal loss in the case of a major pandemic. That goal was met. Still, it would have been more convincing if we could have shown the application of the parameter using more country-level data. The case of New York State [23
], however, offered at least another population where PYLL was applicable to assessing the societal loss. We advocate that a similar study should be done in other populations to assess a greater picture of the loss due to the COVID-19 pandemic and also to show the consistencies. Furthermore, for developing countries where life expectancies are lower than developed countries, studies are needed to determine a reasonable cut-off point of the upper age limit.
The criticisms that pertain to PYLL calculations have been adequately addressed in this research: (1) the use of different age weightings for PYLL at different ages has been minimized in this study, (2) the discounting mechanism of PYLL, by assigning a new upper age limit based on the current life expectancy-value, is adjusted, and (3) the use of PYLL in an epidemic situation has been established.
Limitations. One important limitation of this study was that the pandemic is still ongoing, and new data are being generated on a daily basis. The current mortality data in this study may not reflect the latest data and the exact gravity of the problem of the pandemic. The calculated PYLL rates are an underestimation of the real figures because of the rising number of deaths due to the pandemic. Another challenge in standardization was the lack of information about the age-specific population in the reference population. However, using the reference population as the denominator was shown to be a better alternative when comparing the rates across countries.
Policy Implications. Based on the current figure of life expectancy at birth in most developed countries, an upper limit age of 80 years is more realistic. A different age limit should be used when PYLL is measured for developing countries. Alternatively, the exact figure for life expectancy in each country may be used as the age limit. In that case, the comparability of data across countries could be an issue. More country-specific data are needed on the COVID-19 pandemic for international comparison of health system performances amongst countries and more accurate assessment of premature life lost due to the pandemic. A follow-up study would be useful for the aftermath of premature life lost once the pandemic is over. When addressing the issue of societal loss in general, several other factors in this analysis, which were not accounted for due to the scope of this study, could be considered in selecting populations. In future studies, perhaps differences in urban versus rural, healthcare outcomes, total healthcare system capacity/burden, and other population health measures such as obesity and chronic diseases could be investigated.