Ebola Virus in Democratic Republic of Congo Cost Peer Reviewed Articles

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• Published: 03 September 2019

The monetary value of man lives lost through Ebola virus disease in the Democratic Republic of Congo in 2019

• Rose Nabi Deborah Karimi Muthuri² &
• Newton Gitonga Muthuriⁱⁱⁱ

BMC Public Wellness book 19, Article number:1218 (2019) Cite this article

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Abstract

Groundwork

Betwixt 8 May 2018 and 27 May 2019, cumulatively there were 1286 deaths from Ebola Virus Disease (EVD) in the Democratic Commonwealth of Congo (DRC). The objective of this written report was to estimate the monetary value of human lives lost through EVD in DRC.

Methods

Human being capital arroyo was applied to monetarily value years of life lost due to premature deaths from EVD. The future losses were discounted to their present values at 3% discount charge per unit. The model was reanalysed using v and x% discount rates. The analysis was washed alternately using the average life expectancies for DRC, the world, and the Japanese females to assess the effect on the budgetary value of years of life lost (MVYLL).

Results

The 1286 deaths resulted in a full MVYLL of Int$17,761,539 assuming iii% discount charge per unit and DRC life expectancy of 60.5 years. The average budgetary value per EVD death was of Int$13,801. Almost 44.7 and 48.6% of the total MVYLL was borne past children aged below 9 years and adults aged between 15 years and 59 years, respectively.

Re-estimation of the algorithm with average life expectancies of the world (both sexes) and Japanese females, holding discount charge per unit constant at 3%, increased the MVYLL past Int$ 3,667,085 (twenty.six%) and Int$ 7,508,498 (42.iii%), respectively. The application of disbelieve rates of 5 and ten%, holding life expectancy constant at 60.5 years, reduced the MVYLL by Int$ four,252,785 (− 23.9%) and Int$ 9,658,195 (− 54.four%) respectively.

Conclusion

The EVD outbreak in DRC led to a considerable MVYLL. There is an urgent need for DRC regime and development partners to disburse adequate resources to strengthen the national health organization and other systems that address social determinants of health to end recurrence of EVD outbreaks.

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Background

The Democratic Congo-brazzaville (DRC) is situated in Central Africa [ane]. It is divided into 26 administrative provinces and has a population of 97.879 meg persons. The land had a full gross domestic production (GDP) of US$ 48.458 billion and a per capita Gdp of Usa$ 495.ane (equivalent to Int$ 791.nineteen) in 2019 [two].

In 2017 DRC had a low man development alphabetize (HDI) of 0.457 and inequality-adjusted HDI of 0.319; life expectancy of threescore.v years; and 6.8 hateful years of schooling [3]. Information technology had an overall multidimensional poverty alphabetize of 0.378. The low standard of living contributes 56.two%, wellness 25% and education xviii.9% to overall multidimensional poverty. Approximately, 57 meg of the population live in multidimensional poverty.

The Ministry of Health in DRC notified Earth Health Arrangement (WHO) of confirmed cases of ongoing Ebola Virus Disease (EVD) outbreak in the provinces of North Kivu and Ituri on viii May 2018 [iv]. Equally of 27 May 2019, the cumulative number of EVD cases was 1926. In that location were 1286 EVD-related deaths between 8 May 2018 and 27 May 2019; of which 91.viii and 8.2% occurred in N-Kivu and Ituri provinces, respectively [5] (See Boosted file 1).

The recurrent EVD epidemics could be attributed partially to underinvestment in the national health organization and other systems that address social determinants of wellness [6]. For instance, the current health expenditure (CHE) per capita was The states$21 in 2016; which was beneath the Usa$74 to US$ 198 total cost per person needed to accomplish health system targets for the attainment of SDG3 [seven]. It was made upward of domestic general government health expenditure (GGHE-D) per capita of United states$3; domestic private health expenditure (PVT-D) per capita of United states$9; and external health expenditure (EXT) per capita of US$nine. The DRC out-of-pocket expenditure (OOPS) per capita of Us$eight was 88.9% of PVT-D and 38.1% of CHE [8]. According to the WHO Earth Health Report 2010 [nine], when OOPs are in a higher place fifteen–twenty% of CHE, the incidence of fiscal catastrophe and impoverishment increases substantially.

The DRC universal wellness coverage (UHC) service index was xl% in 2015 [6]; implying essential wellness services coverage gap of 60%. The tracer indicators of the essential wellness services include reproduction, maternal, newborn and child health (family unit planning, pregnancy and delivery care, kid immunization and treatment); infectious diseases (TB handling, HIV treatment, malaria prevention, water and sanitation); noncommunicable diseases (handling of cardiovascular diseases, management of diabetes, cervical cancer screening, tobacco control); and services capacity and access (infirmary access, health worker density, essential medicines and health security) [6]. There is a need for sustained evidence-based advocacy for the DRC government, private sector, and external partners to increase their investments in the building of resilient national health organization to attain universal coverage of essential health services.

Some of the testify needed for advancement is the monetary value of lives lost from a affliction such as EVD. A few studies have estimated the economic brunt of EVD. For example, Bartsch, Gorham and Lee estimated the cost of an EVD case in Guinea, Liberia and Sierra Leone [10]. Kirigia et al estimated the hereafter productivity losses associated with EVD deaths in Guinea, Republic of liberia, Mali, Nigeria and Sierra Leone [xi]. Kastelic et al estimated the socio-economic impacts of Ebola in Sierra Leone [12]. Bowles et al estimated the extent to which economical action declined and jobs disappeared in Liberia during the outbreak [thirteen]. Thomas, Smith and Ferreira provided an update of the macro-economic bear upon of Ebola on sub-Saharan Africa in 2015 [14]. In that location is a dearth of similar economic evidence on the EVD epidemic in DRC.

Thus, the aim of this study is to contribute towards bridging that cognition gap. The specific objective was to estimate the monetary value of human lives lost from EVD in DRC.

Methods

Human capital arroyo framework

This study employed human upper-case letter approach (HCA) to monetarily value potential years of life lost (PYLL) due to premature bloodshed caused by the EVD in the DRC between 8 May 2018 and 27 May 2019. Culyer [xv] defines human being capital equally the stock of homo skills (adamant by basic power, educational attainment and health status) embodied in an individual; which is measured equally the nowadays value of expected earnings over a period of time [15].

Death extinguishes expected flow of productive capability in time to come years. Bold per capita GDP is a proxy of private person's rate of remuneration, the productivity forgone by society considering of premature mortality from EVD is the sum of the discounted stream of potential earnings that could accept accrued over the potential years of life lost (PYLL) [xvi]. According to Gardner and Sanborn [17]. PYLL is a measure of the average time a person would have lived had (south)he not died prematurely, i.east. DRC life expectancy at decease minus age group's average age at death.

Thus, potential economic losses to order were estimated using PYLL, a cut-off point at the DRC life expectancy at birth of 60.5 years, 3% discount rate, number of EVD deaths at various age groups, and non-wellness per capita GDP (per capita GDP minus total current wellness expenditure). Only the PYLL above the DRC minimum working age for admission to piece of work of 15 years was monetarily valued for age groups ane–4 years, 5–9 years and 10–14 years [xviii].

The analytical framework formulated below was adapted from the frameworks applied in estimating the indirect costs of maternal deaths in 2010 [19], maternal deaths in 2013 [xx], kid mortality [21], neglected tropical diseases deaths [22], tuberculosis [23] and not-communicable illness deaths [24] in the WHO African Region, and Ebola Virus Disease in W Africa [11]. As recommended first by Weisbrod [25], and subsequently, past WHO [26] we deducted electric current health expenditure from gross productivity to obtain net productivity.

The monetary value of potential PYLL lost (MVYLL) due to EVD deaths in DRC is the sum of the potential non-health Gross domestic product lost among those aged ane–4 (MVYLL _1 − iv), those aged five–9 (MVYLL _v − 9), those anile ten–fourteen (MVYLL _x − 14), those aged xv–19 (MVYLL _{15 − xix}), those aged 20–24 (MVYLL _{twenty − 24}), those aged 25–29 (MVYLL _{25 − 29}), those anile 30–34 (MVYLL _{thirty − 34}), those aged 35–39 (MVYLL _{35 − 39}), those anile 40–44 (MVYLL _{xl − 44}), those aged 45–49 (MVYLL _{45 − 49}), those aged 50–54 (MVYLL _l − 54), those aged 55–59 (MVYLL _{55 − 59}), those aged 60–64 (MVYLL _{threescore − 64}), those aged 65–69 (MVYLL _{65 − 69}), those aged 70–74 (MVYLL _{70 − 74}), those aged 75–79 (MVYLL _{75 − 79}), those anile fourscore–84 (MVYLL _{80 − 84}), those aged 85–89 (MVYLL _{85 − 89}), those anile 90–94 (MVYLL _{90 − 94}), and those aged 95 years and higher up (MVYLL _≥95).

The MVYLL amongst persons of a specific age group is the product of the total discounted years of life lost, per capita not-health GDP in purchasing power parity (NHGPC_Int$) and the total number of EVD deaths (EVDD) for age group [11, xix,twenty,21,22,23,24]. The DRC'south discounted full non-health GDP loss attributable to EVD deaths (MVYLL_DRC) was estimated using the eqs. (1) and (2) below [11] (meet Additional file 2 for details).

$$ {MVYLL}_{DRC}=\left({MVYLL}_{1-iv}+{MVYLL}_{v-9}+{MVYLL}_{x-14}+{MVYLL}_{15-19}+{MVYLL}_{20-24}+{MVYLL}_{25-29}+\dots +{MVYLL}_{\ge 95}\correct) $$

(1)

$$ {\displaystyle \brainstorm{array}{c}{MVYLL}_i=\sum \limits_{t=1}^n\left\{\left[1/{\left(ane+r\right)}^t\right]\times \left[{NHGPC}_{Int\$}\right]\times \left[{EVDD}_i\right]\right\}=\\ {}\left\{\left[1/{\left(1+r\right)}^i\correct]\times \left[{NHGPC}_{Int\$}\correct]\times \left[{EVDD}_i\right]\right\}+\\ {}\left\{\left[one/{\left(one+r\right)}^2\right]\times \left[{NHGPC}_{Int\$}\right]\times \left[{EVDD}_i\right]\right\}+\dots +\\ {}\left\{\left[1/{\left(1+r\right)}^n\right]\times \left[{NHGPC}_{Int\$}\right]\times \left[{EVDD}_i\right]\correct\}\end{assortment}} $$

(2)

Where: 1/(1 +r) ^t is the discount factor that converts futurity GDP losses into today's dollars; r is an involvement rate that measures the opportunity cost of lost earnings, i.e. 3% in this report; \( \sum \limits_{t=one}^n \) is the summation from yr t to n; t is the first year of life lost, and due north is the final year of the total number of years of life lost per EVD death within an age group, which is obtained by subtracting the age groups average age at death (GAAD) for EVD-related causes from the DRC average life expectancy at birth; NHGPC _Int$ is per capita not-health Gross domestic product in purchasing power parity (PPP), which is obtained by subtracting per capita current wellness expenditure (PCCHE) from GDP per capita (GDPPC _Int$ ); EVDD _i is the number of EVD deaths occurring in age grouping i, where i = 1 represent to the age grouping ane–4 years, i = ii to the historic period group five–nine years, i = iii to the age group 10–14 years, i = four to the age group 15–19 years, i = 5 to the historic period grouping 20–24 years, i = 6 to the historic period group 25–29 years, i = vii to the age group 30–34 years, i = 8 to the age group 35–39 years, i = 9 to the age grouping 40–44 years, i = ten to the age group 45–49 years, i = 11 to the age group 54–54 years, i = 12 to the historic period group of 55–59 years, i = thirteen to the age group lx–64 years, i = 13 to the age group 65–69 years, i = 14 to the age group 70–74 years, i = 15 to the age group lxx–74 years, i = xvi to the age group 75–79 years, i = 17 to the age group 80–84 years, i = 18 to the age group 85–89 years, i = xix to the historic period group 90–94 years, and i = 20 to the age grouping 95 years and higher up in DRC. The base year to which Gross domestic product losses occurring in hereafter years were discounted is 2019. The average budgetary value per EVD decease was obtained by dividing MVYLL_DRC past the total number of EVD deaths.

Sensitivity analysis

Sensitivity analysis is a procedure of assessing the robustness of monetary valuation of years of life lost by considering the effects of doubt [fifteen, 27]. In this report, there was uncertainty about the life expectancy at birth and discount rate used. Thus, the algorithm was estimated bold DRC life expectancy of 60.5 years, the global average life expectancy of 72 years, and Nihon female life expectancy of 87 years (the longest in the world) [6]. The algorithm was also re-estimated bold disbelieve rates of three, 5 and 10%. The results can exist accounted robust if the conclusions remain unchanged [28, 29].

Data sources

The 1286 EVD-related deaths that occurred betwixt 8 May 2018 and 27 May 2019 were obtained from the DRC Ministry of Health [5]. The distribution of EVD deaths by each of the 20 historic period groups was estimated using data from the Institute for Wellness Metrics and Evaluation (IHME) global burden of affliction report 2017 database [30]. The DRC life expectancy at nascence, Japan female person life expectancy, and global average life expectancy were obtained from World Wellness Statistics 2019 [6]. The current health expenditure per capita of 34 International Dollars (Int$) or Purchasing Power Parity was obtained from the WHO Global Wellness Expenditure Database [viii]. The Gdp of Int$791.19 per capita for DRC in 2019 was gotten from IMF World Outlook database [ii]. The equations were estimated using Excel Software, Microsoft Corporation, New York.

Data analysis

The economic model was estimated in 8 steps using Excel Software (Microsoft Corporation, New York):

• Footstep 1: Development of analysis algorithm on Excel software

The equations developed in the HCA analytical framework in a higher place were built into a spreadsheet.

• Step 2: Extraction of EVD mortality data

The data on the full number of EVD deaths between 8 May 2018 and 27 May 2019 was extracted from the DRC Ministry building of Health website [5].

• Step iii: Distribution of EVD deaths from step 2 across the xx historic period groups

The number of EVD deaths by each of the 20 age groups was obtained by multiplying total number of EVD deaths [5] and relevant proportion [thirty] (See Boosted file 3). For example, the since the full number of EVD deaths was 1286 and the proportion for age group ane–4 years was 0.22857, the number of deaths in age group 1–four years equals 1286 multiplied by 0.22857, i.e. 294.

• Step 4: Interpretation of undiscounted potential productive years of life lost

The DRC life expectancy at birth of 60.five years, global boilerplate life expectancy of 72 years, and Nippon female person life expectancy of 87.ane years (i.due east. the highest in the world) were obtained from Annex 1 (role 1) of the World Wellness Statistics 2019 report [6]. Assuming DRC life expectancy of threescore.5 years [half dozen], the i^th age group undiscounted potential years of life lost (PYLL) from EVD equals average life expectancy at nascency for DRC minus the average age at death for i^thursday age group, where i = one,2,iii,…,20. For example, the PYLL for a expiry in age group 15–19 equals 43.five years, i.e. [threescore.5 – ((15 + 19)/2)]. The undiscounted PYLL for the 20 age groups are contained in Additional file 4.

The undiscounted PYLLs in Boosted file v were calculated, in a similar manner, assuming the earth and the Japan female life expectancies. The PYLL cannot exist negative. Thus, for historic period groups with average age at death greater than DRC life average life expectancy of threescore.5 years, their PYLL are assumed to be equal to zero [31].

• Step v: Discounting of potentially productive YLL

The potentially productive YLLs estimated in Step iv were discounted at a charge per unit (r) of 3% using the post-obit formula: i/(ane + r)^t, i.e. the discount cistron formula. For instance, the get-go twelvemonth of life lost would be discounted as follows: [1 × 1/(1 + 0.03)^ane = 0.97087. The discounted (or present value) for the second YLL would be [1 x [i/(1 + 0.03)^two] = 0.942596; for third YLL would be [i x [1/(1 + 0.03)³] = 0.915142; and for the due north^th YLL (due east.one thousand. for a premature expiry in age group 15–19) would be [i x [1/(1 + 0.03)^43.5] = 0.276427. Thus, present value of the full years of life lost (PVYLL_i) from one death in a given i^th age group equals the sum of the discount factors multiplied by each undiscounted YLL, i.e.

$$ {PVYLL}_i=\sum \limits_{t=i}^{t=n}{YLL}_i\times \left[\frac{1}{{\left(1+r\correct)}^n}\correct]. $$

The meanings of t, n and r are as defined earlier under eq. (two). Additional file six contains the discounted PYLL from EVD, for all the 20 age groups, assuming DRC life expectancy and iii% discount charge per unit. The discounted potentially productive YLLs in Additional file 7 were calculated, in a similar fashion, bold the world and the Nippon female life expectancies and a 3% discount rate.

• Step 6: Estimation of non-wellness GDP per capita (NHGPC _Int$ )

The data on Gross domestic product per capita of Int$791.19 was obtained from the International monetary fund World Outlook Database [ii]; and current wellness expenditure per capita of Int$34 from WHO Global Health Expenditure Database [eight]. The NHGPC_Int$ was the difference betwixt Gdp per capita and current health expenditure per capita for DRC, i.e. Int$791.19 – Int$34 = Int$757.19 per person.

• Step 7: Calculation of MVYLL per age group

The algorithm developed in Step one was estimated bold the DRC life expectancy at birth and 3% discount rate. The data on number of deaths by historic period group in Additional file 3; discounted potential years of life lost from EVD bold DRC life expectancy in Boosted file 6; and non-wellness Gross domestic product per capita for DRC were used in adding of MVYLL for each historic period group.

For example, MVYLL for i–four years' age grouping was the product of non-health Gross domestic product per capita (Int$757.19), discounted years of life lost per expiry in the age grouping (25.02470783) and number of EVD deaths in the historic period grouping (294). Therefore, MVYLL_1–4 = 757.19 × 25.02470783 × 294 = Int$ 5,570,847. The MVYLL for the other historic period groups was calculated in a like manner.

• Step 8: Conduct of sensitivity assay

  • Footstep 8.1: Sensitivity to discount rate

Equations (i) to (twenty) were re-estimated with 5% (see Additional file 8) and x% (encounter Boosted file nine) disbelieve rates to measure the sensitivity of the budgetary value of years of life lost. For case, at the DRC life expectancy and 5% disbelieve charge per unit, the MVYLL_ane–4 = 757.19 × 17.98101571 × 294 = Int$4,002,823. At the earth life expectancy and 5% discount rate, the MVYLL_1–4 = 757.19 × eighteen.8195417 × 294 = Int$4,189,491. At the Japanese Female life expectancy and 5% disbelieve charge per unit, the MVYLL_ane–4 = 757.19 × 19.43217937 × 294 = Int$ 4,325,872.

At the DRC life expectancy and 10% discount rate, the MVYLL_1–4 = 757.nineteen × 9.886618082 × 294 = Int$ 2,200,898. At the world life expectancy and x% discount rate, the MVYLL_1–4 = 757.19 × 9.96026033 × 294 = Int$two,217,292. At the Japanese Female life expectancy and 10% disbelieve rate, the MVYLL_1–4 = 757.xix × ix.990486639 × 294 = Int$two,224,021. The sensitivity analysis of MVYLL to changes in discount rates for the other age groups was calculated in the same way.

• Step 8.two: Sensitivity to life expectancy

In lodge to make up one's mind the impact of life expectancy on MVYLL estimates, the equations were re-estimated alternately assuming the world life expectancy of 72 years (Additional file 7) and the Japanese female life expectancy of 87 years (which is the highest in the world) (Additional file seven). At the world life expectancy of 72 years and 3% disbelieve rate, the MVYLL_one–iv = 757.19 × 27.33100549 × 294 = Int$ 6,084,261. At the Japanese Female life expectancy of 87 years and 3% discount rate, the MVYLL_one–four = 757.xix × 29.4806675 × 294 = Int$ six,562,805. The sensitivity analysis of MVYLL to changes in life expectancy for the other age groups was estimated in the same mode.

Results

Table ane provides a breakup of the monetary value of potential years of life lost from Ebola Virus Disease in DRC discounted at a iii% rate. The 1286 deaths resulted in total MVYLL of Int$17,761,539; Int$21,428,624; and Int$25,270,037 bold DRC life expectancy of threescore.5 years, the boilerplate global life expectancy of 72 years and Japan female life expectancy of 87 years, respectively. The boilerplate MVYLL bold DRC, global and Nippon female life expectancies was Int$13,801, Int$16,650 and Int$nineteen,635 per death, respectively.

Tabular array one Monetary value of years of life lost from Ebola Virus Disease in DRC discounted at 3% (2019 Int$ or PPP)

Full size table

Out of the Int$17,761,539, nigh 31.iv% occurred among one–four-year-old; 13.three% among v–9-year-old; half dozen.seven% amongst 10–14-twelvemonth-old; iv.7% among 15–xix-year-one-time; 3.7% amongst twenty–24-yr-old; iii.2% among 25–29-year-onetime; 2.9% amongst 30–34-year-sometime; 27.ix% among 35–39-twelvemonth-old; ii.3% among 40–44-year-old; 1.9% among 45–49-year-one-time; 1.4% among 50–54-year-onetime; and 0.6% amidst 55–59-yr-old. Thus, 48.half dozen% of the MVYLL occurred among adults aged between 15 years and 59 years; which is the most productive age bracket.

Use of the Japanese female life expectancy at nativity of 87 years, holding discount rate constant at iii%, increased the MVYLL by Int$ seven,508,498 (42.iii%). Utilization of the average global life expectancy at nascence of 72 years, holding discount rate constant at 3%, increased the MVYLL by Int$ iii,667,085 (20.6%).

Table ii presents an age-group break-down of MVYLL from EVD discounted at a 5% rate. The application of 5% disbelieve charge per unit holding life expectancy constant at 60.5 years, 72 years and 87 years reduced the MVYLL by Int$ 4,252,785 (− 23.94%), Int$ v,806,233 (− 27.ane%), and seven,737,915 (− xxx.vi%) respectively.

Table two Monetary value of years of life lost from Ebola Virus Disease in DRC discounted at 5% (2019 Int$ or PPP)

Full size table

Table three presents an age-grouping break-down of MVYLL from EVD discounted at a 10% charge per unit. The application of x% discount charge per unit belongings life expectancies constant at 60.5 years, 72 years and 87 years reduced the MVYLL by Int$ 9,658,195 (−54.4%), Int$ 12,537,911 (−58.5%), and Int$ 15,792,925 (−62.v%) respectively.

Tabular array 3 Monetary value of years of life lost from Ebola Virus Disease in DRC discounted at 10% (2019 Int$ or PPP)

Full size table

Word

This written report has estimated the monetary value of human being lives lost due to EVD outbreak between viii May 2018 and 27 May 2019 in DRC. The 1286 EVD-related deaths resulted in total MVYLL of Int$17,761,539; which translates to Int$13,801 per death. The chief drivers of MVYLL estimates were the life expectancy and discount rate used.

How does this MVYLL per EVD-related decease in DRC compare to similar studies conducted in the past in other African countries? Kirigia et al [eleven] estimated productivity loss per EVD decease to exist Int$ 17,473 for Guinea, Int$ xi,283 for Liberia, Int$ 25,126 for Mali, Int$ 47,364 for Nigeria and Int$ 14,633 for Sierra Leone. Thus, MVYLL per EVD expiry in DRC is lower than that of Guinea, Mali, Nigeria and Sierra Leone due to lower per capita GDP.

How does this MVYLL per EVD-related death compare to that of other diseases? Kirigia et al [19] estimated the African Region boilerplate k full non-health GDP loss to be Int$ thirty,203 per maternal death; and Int$ xvi,397 per maternal death in 2010 for low-income countries. Another study estimated the African Region low-income countries discounted value of future non-health Gdp loss due to maternal deaths in 2013 at Int$xix,822 per maternal death [20]. Kirigia and Muthuri [23] appraised the African Region average g total non-health GDP loss to be Int$66,872 per tuberculosis decease; and Int$21,513 per tuberculosis death in 2014 for depression-income countries. The expected future productivity loss per child death in the WHO African Region in 2013 was estimated to be Int$50,494; and Int$ 25,508 per child decease for low-income countries [21]. In 2015 the mean value of human life lost per NTD death in the African Continent was Int$ 37,489; and Int$ 37,489 per human life in low-income countries [22]. In 2012 the WHO African Region boilerplate grand total non-health GDP loss was Int$ 21,985 per NCD expiry; and Int$ 9096 per NCD expiry for low-income countries [24]. Therefore, the approximate of MVYLL per EVD expiry in DRC is lower than the indirect toll per maternal death, tuberculosis death, child death and NTD death in Africa. However, MVYLL per EVD death in DRC was larger than the indirect toll per NCD death in low-income countries in Africa. Given the virulent nature of EVD and its multi-sectoral negative consequences, concerted national, continental and global effort should be made to eradicate EVD in the DRC.

Limitations of the study

The study reported in this paper has iv master limitations. First, it omits the cost of productivity fourth dimension lost among those diagnosed with EVD just do not dice; health system costs, including vaccination, tracing cases, diagnostic tests, send of health workers and patients (suspected and bodily), plus building and operating treatment centres (including health workforce, medicines, medical devices); and intangible costs of pain, grief, mental anguish and social stigma to patients and family members [32]. In addition, this study does not include the negative bear on of fear and stigmatisation of EVD on various socioeconomic activities, east.g. aviation, teaching (schooling), mining, tourism (hospitality), etc. [33,34,35].

2nd, strictly applied the HCA would attach a zero monetary value on the years of life lost among the children below minimum working age of xv years; unemployed adults; total-fourth dimension homemakers; and retired people [xvi, 36]. Fifty-fifty though their contribution does not characteristic in GDP calculations, the final three categories of people make an of import non-monetized contribution to the guild, and thus, we valued their YLL at the net non-health Gross domestic product per capita for DRC. With regard to deaths amongst children, merely the YLL above the minimum working historic period of 15 years were valued.

Third, HCA is "..implicitly based upon the maximization of society'south present and future production" (p. 556) [36]. Maximization of economical product is not the merely reason for combatting EVD. There are other reasons such every bit restoring patients to health so that they can flourish, savor leisure, and realize their inalienable right to health [37]. In addition, society desires to combat EVD to reduce (or alleviate) fear and anxiety in the population, and pave way for unimpeded international flow of goods and people.

Quaternary, the HCA does not counterbalance the costs and benefits of alternative interventions into EVD [38, 39]. Thus, its results should not exist used as a basis for priority setting, simply primarily for advocacy for increased investments into the national health arrangement (including affliction surveillance system) and other systems that address the social determinants of health.

Conclusion

The ongoing EVD outbreak in the DRC has led to the noun monetary value of years of life lost. Therefore, in that location is urgent need for DRC authorities and development partners to disburse adequate resources to strengthen national health organisation (including disease surveillance system) and other systems that address social determinants of health (educational activity, water, sanitation, hygiene, cultural practices, physical security) to end recurrence of EVD outbreaks [40].

In addition, at that place is a necessity for conducting economical evaluations that identify, appraise and compare the costs and consequences associated with alternative preventive and treatment interventions for EVD. Unlike, the evidence presented in this paper which is primarily for apply in advocacy, economic evaluation prove would guide priority-setting, controlling and planning of prevention and control actions for combatting EVD.

Availability of data and materials

All data generated or analysed during this study are included in this published commodity and its supplementary information files.

Abbreviations

CHE:

Current health expenditure

DRC:

Democratic republic of the congo

EVD:

Ebola Virus Disease

EVDD_i :

Number of Ebola Virus Disease deaths per i^th age group

EXT:

External wellness expenditure

Gross domestic product:

Gross domestic product

GGHE-D:

Domestic general regime health expenditure

HCA:

Human being capital arroyo

IHME:

Plant of Health Metrics and Evaluation

IMF:

Imf

Int$:

International Dollars or Purchasing Ability Parity (PPP)

MVYLL:

Budgetary value of years of life lost

MVYLL_= > 95 :

Monetary value of potential years of life lost among those aged 95 years and in a higher place

MVYLL_10–xiv :

Budgetary value of potential years of life lost among those anile 10–14

MVYLL_1–4 :

Monetary value of potential years of life lost among those anile ane–iv

MVYLL_15–19 :

Monetary value of potential years of life lost amidst those aged 15–19

MVYLL_20–24 :

Budgetary value of potential years of life lost among those aged 20–24

MVYLL_25–29 :

Monetary value of potential years of life lost among those anile 25–29

MVYLL_30–34 :

Monetary value of potential years of life lost among those aged 30–34

MVYLL_35–39 :

Budgetary value of potential years of life lost amid those aged 35–39

MVYLL_{twoscore–44} :

Monetary value of potential years of life lost amidst those aged xl–44

MVYLL_45–49 :

Monetary value of potential years of life lost amidst those anile 45–49

MVYLL_50–54 :

Monetary value of potential years of life lost among those aged 50–54

MVYLL_55–59 :

Monetary value of potential years of life lost among those aged 55–59

MVYLL_5–ix :

Monetary value of potential years of life lost among those anile 5–ix

MVYLL_sixty–64 :

Monetary value of potential years of life lost among those aged threescore–64

MVYLL_65–69 :

Monetary value of potential years of life lost amongst those anile 65–69

MVYLL_lxx–74 :

Monetary value of potential years of life lost amid those anile 70–74

MVYLL_75–79 :

Budgetary value of potential years of life lost amongst those aged 75–79

MVYLL_80–84 :

Monetary value of potential years of life lost among those aged 80–84

MVYLL_85–89 :

Budgetary value of potential years of life lost among those aged 85–89

MVYLL_90–94 :

Monetary value of potential years of life lost among those aged 90–94

NCD:

Not-communicable disease

NHGPC_Int$ :

Per capita non-health GDP in purchasing power parity

NTD:

Neglected tropical illness

OOPS:

Out-of-pocket expenditure

PVT-D:

Domestic private health expenditure

PYLL:

Potential Years of Life Lost

r:

Interest rate that measures the opportunity toll of lost earnings

SDG3:

United nations Sustainable Development Goal

UHC:

Universal health coverage

United states of america$:

United States Dollar

WHO:

Globe Health Organization

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Acknowledgements

We owe profound gratitude to Jehovah Jireh for meeting all our needs during the entire process of the report reported in this paper. We are grateful to Lenity Hones ty Kainyu Nkanata for immense moral support. The views expressed in this paper are solely those of the authors and should not be attributed to institutions they are affiliated to.

Author information

Affiliations

1. African Sustainable Development Research Consortium (ASDRC), P.O. Box 6994 00100 GPO, Nairobi, Kenya

   Joses M. Kirigia

2. Faculty of Health Sciences, Academy of Pretoria, Pretoria, South Africa

   Rose Nabi Deborah Karimi Muthuri

3. School of Business, The states International Academy, Nairobi, Kenya

   Newton Gitonga Muthuri

Contributions

JMK and RDKM designed the report; downloaded the data on number of deaths from DRC Ministry of Health website, per capita Gdp from International monetary fund database, and current health expenditure per capita from WHO database; designed the economic model/algorithm on Excel software; and drafted the manuscript. NGM did the literature review and contributed in the drafting of give-and-take and conclusion sections. All the authors approved the terminal version of the newspaper.

Corresponding author

Correspondence to Joses M. Kirigia.

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Ethics approval and consent to participate

Not applicable. No ethical clearance was required because the study relied completely on analysis of secondary data publicly available in the DRC Ministry building of Health Website, WHO Global Health Expenditure database and IMF database.

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Not applicative.

Competing interests

The authors declare that they accept no competing interests.

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Additional files

Additional file 1:

Epidemiological situation of Ebola Virus Disease in DRC equally at 27 May 2019. (DOCX 12 kb)

Additional file 2:

Equations used to estimate the DRC's discounted total not-health Gdp loss attributable to EVD deaths (MVYLL_DRC). (DOCX 91 kb)

Boosted file 3:

Age distribution of EVD deaths in DRC. (DOCX 12 kb)

Boosted file 4

Undiscounted potential years of life lost from EVD assuming DRC life expectancy. (DOCX 12 kb)

Additional file v:

Undiscounted potential years of life lost from EVD assuming world's and Japanese Female life expectancies. (DOCX 13 kb)

Boosted file 6:

Discounted potential years of life lost from EVD assuming DRC life expectancy and 3% discount rate. (DOCX 12 kb)

Additional file seven:

Discounted potential years of life lost from EVD assuming globe'southward and Japan Female life expectancies and a three% disbelieve rate. (DOCX 13 kb)

Additional file 8:

Discounted potential years of life lost from EVD assuming the DRC, the world and Japanese female person life expectancies and a 5% discount charge per unit. (DOCX thirteen kb)

Boosted file 9:

Discounted potential years of life lost from EVD bold the DRC, the World and the Japan female life expectancies and a x% discount rate. (DOCX 13 kb)

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Kirigia, J.M., Muthuri, R.N.D.Chiliad. & Muthuri, Due north.G. The monetary value of human lives lost through Ebola virus disease in the Democratic Democracy of Congo in 2019. BMC Public Health 19, 1218 (2019). https://doi.org/x.1186/s12889-019-7542-2

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• Received: 08 July 2019

• Accepted: 25 August 2019

• Published: 03 September 2019

• DOI : https://doi.org/10.1186/s12889-019-7542-two

Keywords

• Ebola virus affliction (EVD) deaths
• Human capital
• Monetary value of life
• Years of life lost
• Gross domestic production
• Autonomous Republic of Congo (DRC)

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