The discounted value of human lives lost due to COVID-19 in France

Ethical statement

The study relied totally upon the analysis of secondary data contained in the International Monetary Fund (IMF), WHO, Worldometer, and Santé Publique France databases that are freely available to the public. Therefore, ethical clearance was not required.

Study location

This investigation of the value of human life was conducted on the cumulative number of persons who died of COVID-19 by 14 September 2020 in France. The study was a cross-sectional study. All the 30,916 COVID-19 people reported to have died from COVID-19 as of 14 September 2020 in France were included in the study.

Human capital approach model

This study applied the human capital approach (HCA), initially suggested by Adam Smith in 1776²³, to estimate the monetary value of human life. The Organisation for Economic Co-operation and Development²⁴ defines human capital as “The knowledge, skills, competencies and attributes (including stock of health) embodied in individuals that facilitate [the] creation of personal, social and economic wellbeing” (p.18).

Death from COVID-19 (or any other disease or injury) extinguishes the potential of a person to tap into one’s stock of human capital either for personal development and enjoyment of leisure or to enhance societal cultural and socioeconomic wellbeing. A person’s capacity for personal development, enjoyment of life (or flourishing)²⁵, loving, religious practice, and performing expected societal roles ends upon death. It is also true that death halts individuals’ spending on the consumption of goods and services, investments, government services (including payment of fees and taxes), and imports permanently. In other words, death terminates an individual’s potential contribution to the creation of national output or GDP. Following the death of a human being at any stage of life, society losses not only the statistical person’s contribution to GDP but also other intangible contributions, e.g. child’s joy to parents, love to family and friends, companionship, fellowship, comradeship, sharing of knowledge (written or tacit) and social values.

Weisbrod²⁶ suggested measuring lost human capital as a result of premature death from any cause in terms of the deceased person’s discounted future earnings net of their consumption²⁶. In line with our past research^13–21, the current study uses net GDP per capita (i.e. GDP per capita of France minus current health expenditure per person) to value human lives lost due to COVID-19 in France.

The TDVHL in France (TDVHL_FRANCE) due to COVID-19 is the sum of DVHL among persons aged 0–14 years, 15–44 years, 45–64 years, 65–74 years, and 75 years and over^13–21. Formally^13–21:

Where: DVHL_i is the discounted value of human lives lost due to COVID-19 in i^th age group; i=1 is age 0–14 years, i=2 is age 15–44 years, i=3 is age 45–64 years, i=4 is age 65–74 years, and i=5 is age 75 years and over; ${\displaystyle {\sum }_{i=1}^{i=5}}$ is the sum of the discounted values of human lives lost in age groups denoted by number 1 to 5.

The DVHL_i in each of the five age groups was calculated using the following formula^13–21:

Where: ${\displaystyle {\sum }_{t=\mathrm{n}}^{t=1}}$ is the sum from the first year of life lost (t=1) to the last years of life lost (t=n); Y₁ is the GDP per capita of France; Y₂ is the current health expenditure per person in France; Y₃ is the average life expectancy at birth in France; Y₄ is the average life expectancy at the onset of death in the i^th age group; Y₅ is the total number of COVID-19 deaths in France as of 14 September 2020; Y₆ is the proportion of total COVID-19 deaths borne by those in the i^th age group. The baseline for the analysis is 2020.

Data and data sources

The data analysed in this paper and the sources are contained in Table 3.

Data analysis

The human capital model was analysed using Excel 2016 software (Microsoft, New York). The study reported in this paper replicates steps that were developed and applied in our recent valuation of human life studies related to COVID-19^{13–15,17–21}.

Step 1: Estimation of net GDP per capita (NGDPC) as the difference between per capita GDP (PCGDP) and current health expenditure per capita (CHEPC) for France. Thus, NGDPC = PCGDP – CHEPC = (Int$41637.729 – Int$5011.20068359) = Int$36,626.53.

Step 2: Estimation of the undiscounted years of life lost (UYLL) from COVID-19 in France between December 2019 and 14 September 2020.

(a) Calculation of average ages of onset of death (AAOD) from COVID-19 for each of the five age groups. This entailed taking simple averages for each age group, e.g. for AAOD for 0–14 age group = (0+14)/2 = 7 years.

(b) Calculation of YLL by one person who died of COVID-19 in the age group as the difference between national average life expectancy for France and the AAOD for the specific age group. For example, YLL by a person dead in the age group 0–14 years = national average life expectancy for France (83.13 years) minus AAOD for the group (7 years) = 76.13 years. Thus, the YLL for one person who died in each of the five age groups was obtained similarly (see Table 4).

(c) Total UYLL in each age group = UYLL per deceased person in age group multiplied by the number of persons who died in an age group. For example, total UYLL in 0-14 age group = 76 years’ x 4.5974025974026 persons dead = 349.40 undiscounted YLL.

Step 3: Discounting of the years of life lost (DYLL).

(a) A discount rate of 3% was chosen because it has been used in our previous COVID-19 related economic studies^13–21, the economic evaluation of public health problems in Africa³⁰, the World Health Report 2000³¹, the burden of disease³², and the World Bank Disease Control Priorities study³³.

(b) Calculation of the discount factors applying the discount factor formula: $\left(\frac{1}{{\left(1+r\right)}^t}\right)$. The discount factor for first YLL = $\left(\frac{1}{{\left(1+0.03\right)}^1}\right)$ = 0.970873786407767; discount factor for second YLL = $\left(\frac{1}{{\left(1+0.03\right)}^2}\right)$ = 0.942595909133754; discount factor for third YLL = $\left(\frac{1}{{\left(1+0.03\right)}^3}\right)$ = 0.91514165935316; …, discount factor for the final YLL (which is 76.13 years for 0–14 years) = $\left(\frac{1}{{\left(1+0.03\right)}^{76.13}}\right)$ = 0.105772050189903.

(c) Calculation of DYLL per deceased person in age group. DYLL in year 1 = discount factor in year one x UYLL in year one = 0.970873786407767 × 1 = 0.970873786407767. DYLL in year 2 = discount factor in year two × UYLL per person in year two = 0.942595909133754 × 1 = 0.942595909133754. DYLL in year 3 = discount factor in year three × UYLL per person in year three = 0.91514165935316 × 1 = 0.91514165935316. DYLL in the last YLL (e.g. 76^th year for 0–14 years) = discount factor in 76^th year × UYLL per person in 76^th year = 0.105772050189903 × 1 = 0.105772050189903.

(d) Estimation of total DYLL per deceased person in age group is equivalent to the sum of discount factors from year one to the last year of life.

(e) Total DYLL in each age group = DYLL per deceased person in age group multiplied by number of persons who died in age group. Therefore: UYLL in 0–14 age group = 29.80759833 × 4.597402597 = 137.04 discounted YLL (see Table 5).

Step 4: Estimation of the total number of COVID-19 deaths in age group (COVID-19D_j) equals the total number of COVID-19 deaths in France (TCOVID-19D) multiplied by the proportion (PROP) for that age group. For example, number of COVID-19 deaths in age group 0–14 years = TCOVID-19D × PROP = 30,916 × 0.000148706 = 4.597402597. The number of COVID-19 for each age group are in Table 6.

Step 5: Estimation of the discounted economic value of human lives lost due to COVID-19 in each age j^th group = NGDPC × DYLL_j × COVID-19D_j. For instance, DVHL for age group 0-14 = Int$36,626.53 × 29.80759833 × 4.5974025974026 =Int$5,019,209.

Step 6: Calculation of the share of TDVHL accruing to the 13 regions and five territories of France²⁹ through multiplication of the TDVHL by proportion of COVID-19 deaths sustained by specific region and territory.

Step 7: A one-way sensitivity analysis was performed to evaluate the effect of changes in discount rate and the average life expectancy on the estimated TDVHL. This entailed recalculating the HCA model with (a) 5% and 10% discount rates^13–21 and (b) the world average life expectancy of 73.2 years and the world highest average life expectancy of 88.17 years, i.e. the average life expectancy of Hong Kong women⁴. The model was reanalysed while holding all other parameters constant.

Findings from the HCA model: assuming a national life expectancy of 83.13 years and a 3% discount rate

Table 7 depicts the distribution by age group of the TDVHL of the 30,916 human lives lost due to COVID-19 in France by 14 September 2020.

The human lives lost to COVID-19 had a TDVHL of Int$10,492,290,194, and an average value of Int$339,381 per human life lost. Out of the TDVHL, 0.05% was borne by persons aged 0–14 years, 3.13% by 15–44 years, 21.48% by 45–64 years, 21.87% by 65–74 years, and 53.47% by 75 years and above. Around 46.48% of the TDVHL accrued to persons aged 15 and 74 years. The average TDVHL decreases with increase in age of the deceased, e.g. the average TDVHL for 0–14-year-olds is three-fold that of 75-year-olds and above.

Distribution of the total discounted value of human life by regions and territories. Figure 1 depicts the share of TDVHL across the 13 regions and five territories of France.

Figure 1. Regional and territorial distribution of the discounted value of human lives lost from COVID-19 in France as of 14 September 2020 (Int$).

About 80.3% of the TDVHL accrued to only five regions of France, i.e. Auvergne-Rhône-Alpes, Bourgogne-Franche-Comté, Grand Est, Hauts-de-France, and Ile-de-France. Grand Est, Hauts-de-France, and Ile-de-France regions alone accounted for 66.18% of the TDVHL. The territories combined made up less than 1% of TDVHL.

Findings from the HCA model: assuming 5% and 10% discount rates holding national life expectancy and other parameters constant

Table 8 presents the effects of the application of 5% and 10% discount rates on the TDVHL due to COVID-19 in France.

Rerun of the HCA model, alternately, with discount rates of 5% and 10% resulted in decreased TDVHL by Int$1,304,764,602 (12.4%) and Int$3,506,938,312 (33%), respectively. The average values per human life lost declined by Int$42,204 and Int$113,434 in turn.

Findings from the HCA model: assuming the world and world's highest average life expectancies

Table 9 displays the impact on the TDVHL of substituting the national life expectancy with the world and world's highest average life expectancies.

Replacement of the national life expectancy of 83.13 years with the world average life expectancy of 73.2 years in the HCA model led to decreases in the total and average TDVHL of Int$7,750,187,267 (73.87%) and Int$250,685, respectively. Contrastingly, application of the world’s highest life expectancy of 88.17 years augmented total and average TDVHL by Int$3,744,263,463 (35.7%) and Int$121,111

Recap of key findings

Contrasting of study findings with those from other countries

The sensitivity analysis revealed that growth in discount rate triggers contraction in the TDVHL, and an upsurge in average life expectancy amplifies the TDVHL. The two findings are consistent with those of our previous studies conducted in Brazil¹⁴, Canada¹⁵, China¹⁶, Germany¹⁷, Iran¹³, Spain¹⁸, Turkey¹⁹, the United Kingdom (UK)²⁰, and the United States of America (USA)²¹.

The China¹⁶ and Spain¹⁸ average values of Int$356,203 and Int$470,798 per human life loss associated with COVID-19 were 4.96% and 38.72% higher than the French average of Int$339,381. On the other hand, the French average economic value per human life of Int$339,381 was higher than those of Brazil of Int$99,629¹⁴, Canada of Int$231,217¹⁵, Germany of Int$132,960¹⁷, Iran of Int$165,187¹³, Turkey of Int$228,514¹⁹, the UK of Int$225,104²⁰, and the USA of Int$292,889²¹ by 70.64%, 31.87%, 60.82%, 51.33%, 32.67%, 33.67%, and 13.70%, in that order. Our previous studies have attributed the differences to variations in underlying population age distributions, the YLL, the GDP per capita, and the per capita health spending^{13–15,17–21}.

Practical implications of the study findings

Evidence on the economic value of human lives losses associated with COVID-19 may be useful to the Ministry of Public Health when advocating within the Government of France for sustaining or increasing investments into the national health system, disease surveillance and response system (including IHR core capacities), and other systems (e.g. water and sanitation) that tackle social determinants of health in the pursuit of the United Nations Sustainable Development Goal 3 to “Ensure healthy lives and promote well-being for all at all ages” and Goal 6 to “Ensure availability and sustainable management of water and sanitation for all” (p.14)³⁴. Of course, the economic evidence reported in this paper is meant to complement the International Bill of Human Rights obliging the Government of France to assure every citizen’s realization of the right to life (Article 3) and to “..a standard of living adequate for the health and well-being of himself and of his family, including food, clothing, housing and medical care and necessary social services… (Article 25)” (p.76)³⁵.

Suggestions for further economic studies

Limitations of the study

First, HCA has been criticized for valuing non-market contributions to society at zero dollars³⁷. For instance, traditional HCA values YLL among children below 14 years³⁸, retired (62 years and above)³⁸, homemakers (not employed outside the home), unemployed, and severely handicapped. In order to avoid discrimination against these vulnerable groups, which goes against the 1948 United Nations Universal Declaration of Human Rights³⁵ and the Constitution of the World Health Organization³⁹, YLL at all the age groups were valued at equal net GDP per capita.

Second, the current study did not compare the costs and benefits of a raft of alternative preventive community-level interventions implemented by the French Government and citizens to limit transmission of COVID-19, e.g. bans on gatherings of more than 100 people, all religious gatherings, all travel, ships carrying more than 100 passengers, and embalming; closure of most public establishments, all schools and institutions of higher learning; and mandatory mask-wearing in public places⁴⁰. It was also outside the scope of the current study to appraise the costs and benefits of various options for diagnosis of COVID-19, contact tracing, quarantine, and management of persons who test positive for COVID-19 .

Finally, Stiglitz, Sen and Fitoussi⁴¹ have criticized GDP for not measuring economic wellbeing (or quality of life), ignoring income inequalities, and disregarding environmental damage caused by production processes.