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Health policy
Original research
Estimation of non-health gross domestic product (NHGDP) loss due to COVID-19 deaths in West Bengal, India
  1. Paramita Bhattacharya1,
  2. Denny John2,
  3. Nirmalaya Mukherjee1,
  4. Narassima MS3,
  5. Jaideep Menon4,
  6. Amitava Banerjee5
  1. 1Centre for Public Health Research, Manbhum Ananda Ashram Nityananda Trust, Kolkata, West Bengal, India
  2. 2Faculty of Life and Allied Health Sciences, MS Ramaiah University of Applied Sciences, Bengaluru, Karnataka, India
  3. 3Great Lakes Institute of Management, Manamai Village, Tamilnadu, India
  4. 4Department of Cardiology, Amrita Institute of Medical Sciences & Research Centre, Kochi, Kerala, India
  5. 5Institute of Health Informatics, University College London, London, UK
  1. Correspondence to Dr Denny John; djohn1976{at}gmail.com

Abstract

Objectives The state of West Bengal witnessed a significant surge of COVID-19 in all three waves. However, there is a gap in understanding the economic loss associated with COVID-19. This study estimates future non-health gross domestic product (NHGDP) losses associated with COVID-19 deaths in West Bengal, India.

Setting Various open domains were used to gather data on COVID-19 deaths in West Bengal and the aforementioned estimates.

Primary and secondary outcome measures The NHGDP losses were evaluated using the cost-of-illness approach. Future NHGDP losses were discounted at 3%. Excess death estimates by the WHO and Global Burden of Disease (GBD) were used. Sensitivity analysis was carried out by varying discount rates and average age of death (AAD).

Results 21 532 deaths in West Bengal from 17 March 2020 to 31 December 2022 decreased the future NHGDP by $0.92 billion. Nearly 90% of loss was due to deaths occurring in the age group of 30 years and above. Majority of the NHGDP loss was borne by the 46–60 years age group. NHGDP loss/death was $55,171; however, the average loss/death declined with rise in age. Based on the GBD and WHO excess death estimates, the NHGDP loss increased to $9.38 billion and $9.42 billion, respectively. When the lower age interval is considered as AAD, the NHGDP loss increased to $1.3 billion. At 5% and 10% discount rates, the losses reduced to $0.767 billion and $0.549 billion, respectively.

Conclusions Results from the study suggest that COVID-19 contributed to a major economic loss in West Bengal. The mortality and morbidity caused by COVID-19, the substantial economic costs at individual and population levels in West Bengal, and probably across India and other countries, is another economic argument for better infection control strategies across the globe to minimise the impact of COVID-19.

  • COVID-19
  • Economics
  • HEALTH ECONOMICS

Data availability statement

Data are available in a public, open access repository. All data that is incorporated into the article is available from the references mentioned. Raw data has been uploaded in the following link: https://datadryad.org/stash/share/XP_Zo452CqM-HYuLnhZHBjreokOm9A-h_Z7CEadGYuo.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2023-072559

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    Strengths and limitations of this study

    • This study evaluates the NHGDP losses associated with COVID-19 deaths in West Bengal.

    • This study also evaluates the NHGDP losses after considering the excess death estimates given by GBD and WHO.

    • Sensitivity analysis was carried out by varying discount rates and AAD.

    • This study did not consider the costs associated with illness and recovery.

    • Per capita GDP does not capture the inequality in the distribution of resources among people and households.

    Introduction

    With the COVID-19 pandemic, economies worldwide have faced several challenges in the form of the collapse of public health systems, employment, food availability and accessibility. The socioeconomic disruption caused by the pandemic is manifesting itself in the form of extreme poverty.1 The direct impact of the pandemic has been observed across various forms such as decline in domestic consumption, savings and investment. The indirect effects are on future business activity, and decline in tourism and business travel. Additional effects include spillover effects on other sectors and economies through trade and production linkages, and demand-side and supply-side disruptions. The effects on health are in the form of increased infections and mortality as well as shifts in healthcare spending.2

    India witnessed difficult times with recurrent waves of infection creating new challenges for policymakers.1 Until January 2022, India recorded 39 799 202 infections with 490 462 total deaths. In terms of infection, India is among the top three in the world after USA and France.3 Higher infection rates are associated with an increased burden on healthcare systems.4 The pandemic has created far-reaching consequences in the form of indirect effects due to morbidity and mortality.5 Social, economic and demographic variables play an important role in designing interventions, especially in low- and middle-income countries (LMICs) such as India where there exist wide differences across socioeconomic strata.5 Quantifying the economic impact would have an important bearing on the policy decisions in similar regions in India and other developing countries which have witnessed significant health impacts across all three waves of the pandemic.6 7

    Governance was observed to play an important role in both health and economic outcomes in managing COVID-19.8 In India, the economic impact of COVID-19 was more persistent in the states with lower per capita GDP (PCGDP) and with weaker healthcare infrastructure.9 Patients with chronic conditions, particularly among poor, rural and marginalised sections, experienced difficulties in accessing healthcare and were severely affected both socially and financially by the pandemic.9 A study based in Kerala found that majority of the burden was contributed by years of life lost (YLL), and losses due to years of potential productive life lost were reduced due to the incidence of COVID infection. The cost of productivity lost for individuals aged 40–49 years was found to be highest in the Kerala-based study.10

    With regard to the health effects of the pandemic, it is well-known that not only the underlying mortality risk and diseases but also the socioeconomic factors are important in determining outcomes (including mortality from COVID-19). This makes it important to analyse the economic impact of non-health components of gross domestic product (GDP), a dimension which has not been explored much in studies from India. Measuring the economic impact of non-health components of GDP is the point of interest in our study is the indirect impact of mortality on non-health consumption expenditures.11 It is further contended by Chisholm et al, “…the quantity of interest cannot be GDP, because medical care and health expenses actually form part of GDP; instead … a more appropriate quantification of interest would be the impact of disease or injury on the non-health components of GDP”.12 The need to look at non-health components of GDP is consistent with the WHO guidelines for quantifying the economic impact of a disease or an injury.13

    West Bengal is the sixth largest state and the second most densely populated state in India contributing to 8% of the country’s total population.14 The state was one of the most affected regions in the country across all the three waves of COVID-19 infection.6 7 All these factors make West Bengal an important study area, both geographically and demographically, to examine the impact of COVID-19.14 15 This paper estimates the future NHGDP losses associated with COVID-19 deaths in the state of West Bengal, India. The future NHGDP loss has been computed using state-level available figures of associated deaths, and the excess death figures reported by Global Burden of Disease (GBD) and the WHO.

    Methodology

    A cost-of-illness model was used to estimate the NHGDP losses attributable to COVID-19-related deaths in West Bengal, India. GDP measures the monetary value of all final goods and services, that is, those that are bought by the final user and produced in a country in a given period, and takes into account of all the outputs generated within the borders of a country. GDP includes non-market production, such as defence or education services, provided by the government.16 The mechanisms through which deaths impact macroeconomic output include increased health expenditure, losses in labour and productivity and reduced investment in human and physical capital formation.

    The present study employs a macroeconomic societal outlook, and the scope is limited to economic losses (GDP), in particular the impact of COVID-19 deaths on non-health components of GDP in the state of West Bengal. Economic losses in terms of non-health gross domestic product (NHGDP) were estimated among, six age group brackets viz. 0–15, 16–30, 31–45, 46–60 and 61–75, and among mlales and females to facilitate comparisons. The formulas mentioned below were used for computation:

    where ‘i’ represents ‘n’ age–gender cohorts; Di=deaths at the given age and gender; DYLLi=discounted years of life lost; NHGDPPC=non-health GDP per capita.

    Embedded Image

    NHGDPPC = GDPPC-PCHE

    GDPPC=GDP per capita

    PCHE=per capita health expenditure

    r=discounted rate for value of life.17

    YLLi=LE–AAD

    where YLLi = undiscounted years of life lost

    LE=life expectancy

    AAD=average age of death.

    The population data, COVID-19 deaths data (from 17 March 2020 to 31 December 2022), life expectancy (LE) data, per capita GDP (PCGDP) data and per capita health expenditure (PCHE) data of the state were gathered from openly available data sources.18–22 The study used midpoint age as the age of death for all the age group brackets, and considered the legal minimum age for working, that is, 15 years.23

    Scenario analysis was conducted to accommodate excess deaths estimates from WHO and GBD for effects on the overall total NHGDP loss estimate using similar proportion of deaths between age groups, and males and females for India are similar to West Bengal.

    Sensitivity analysis was conducted to determine the effect of age on the overall total NHGDP loss estimate. The model was re-estimated assuming an average age at death to be the starting age of each age group bracket. Based on existing literature, the discounted rate of interest to measure the value of life was taken as 2.9%.17 Sensitivity analysis of NHGDP loss was also computed using 5% and 10% of discounted rates of interest.

    The estimates in INR were converted to $ Purchasing Power Parity (PPP) using Organisation for Economic Co-operation and Development (OECD) estimates for the year 2020.24 People aged more than 75 years were excluded from the analysis as the LE of West Bengal is 72 years.

    Details of the input parameters used in the study are described in table 1.

    View this table:
    Table 1

    Input parameters for the study

    Validation

    The data on COVID-19 were compiled from official bulletins, reports and newspaper articles.19 25–28 Data on LE, PCGDP and PCHE were collected from central and state government published reports.18 21 22 NHGDP losses were computed based on the works by Kirigia et al.29 30 Discounting of value of life was based on values reported by Shanmugam.17 The methodology and results are written in accordance to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklist (online supplemental file 1).31

    Patient and public involvement

    The analysis employed in the study used secondary data and did not involve the public and/or patients directly in any of the phases including plan, design or reporting.

    Raw data has been uploaded in the following link: https://datadryad.org/stash/share/XP_Zo452CqM-HYuLnhZHBjreokOm9A-h_Z7CEadGYuo.32

    Results

    In West Bengal, due to COVID-19, the NHGDP loss amounts to $0.92 billion, with approximately 60% of NHGDP loss due to deaths among men (table 2). The major proportion of NHGDP loss is borne by the middle age group of 46–60 years. The NHGDP loss associated with each death is estimated to be $55,171. There is an age-wise continuous decline in NHGDP loss/death on one side and an increasing percentage of NHGDP loss until the 46–60 years age group that falls steeply thereafter in the 61–75 years age group (figure 1). NHGDP loss/death is higher for females than for males across all age groups.

    View this table:
    Table 2

    NHGDP loss in West Bengal

    Figure 1
    Figure 1

    Value of NHGDP loss/death and percentage of NHGDP loss by age. NHGDP, non-health gross domestic product; PPP, Purchasing Power Parity.

    Scenario analysis

    The NHGDP losses were also estimated using the excess death measures provided by GBD and WHO.25 27 28 33 In these analyses, the calculation is based on the assumption that the proportion of excess COVID deaths in India remains similar across age and gender in West Bengal. The calculated NHGDP losses amount to $9.38 billion and $9.42 billion based on the GBD and WHO estimates, respectively (table 3). NHGDP loss/death is higher for females compared with males across all age groups.

    View this table:
    Table 3

    NHGDP loss in West Bengal due to excess deaths

    Sensitivity analysis

    Table 3 shows that the NHGDP loss increases to $1.3 billion when assumed average age of death (AAD) to be starting age of each age group range (table 4).

    View this table:
    Table 4

    Sensitivity analysis

    View this table:
    Table 5

    Sensitivity analysis using discount values of 5 and 10%, respectively

    Discussion

    Key findings of this study

    The findings of this study reflect that the NHGDP loss in West Bengal is substantially high at $0.92 billion, and the NHGDP loss attributable to the 46–60 age group to be the highest. Majority (60%) of the NHGDP loss is found to be borne by males. NHGDP loss/death is higher for females compared with males across all age groups. This higher estimate could be due to higher LE experienced by females in West Bengal.18

    Estimation of excess deaths across 74 countries including 31 LMICs has been conducted by GBD, and the estimated mortality figures reflect a significantly higher number of deaths than reported.26 As per WHO projections, there could be over 4 million excess deaths in India.27–29 34 Both these estimates are found to be more than 10 times the reported figures for the state of West Bengal.27 28 35 Various published articles based on civil registration system support these estimates,33 but the Government of India has objected to the approach employed to compute the excess deaths due to the associated risk of bias.29 The generated estimates may involve some degree of bias; therefore, the fact that there are excess deaths during the tenure needs to be seriously investigated. Given this background, the estimates for NHGDP loss have been computed considering the excess deaths to be 10 times the actual numbers. The NHGDP loss estimates amount to $9.38 billion and $9.42 billion, respectively, based on the GBD and WHO estimates.

    In our analysis, the NHGDP loss computed using AAD was found to vary with the age of death. To take account of this factor, a sensitivity analysis was carried out by considering the lower age of the interval as the AAD. NHGDP loss showed an increase from $0.92 billion to $1.2 billion.

    The NHGDP loss also varies depending on the discounting rate. Previous calculation from India considered a discount rate of 2.9%.17 For our sensitivity analysis, this was changed to 5% and 10%, and the NHGDP loss showed a decline to $0.767 billion and $0.549 billion, respectively.

    There is a paucity of literature which accounts for the NHGDP loss associated with COVID-19 deaths. While similar studies have been conducted in other countries,30 35 there is only one study based in India which looks into the NHGDP loss; and, this study considered data only until 12 August 12 2020.36 This study uses a discount rate of 4% which is different from the discount rate used in our study. Further, the study did not consider NHGDP loss of males and females separately as the analysis was considered at all-India level. Moreover, two major peaks of COVID-19, September 2020 and April 2021, which had been the most devastating in terms of loss of life in West Bengal, are also considered in our study.37 The present study is much more comprehensive with scenario analysis using excess deaths predicted by GBD and WHO and sensitivity analysis, which are standard requirements for such models.26 28 29 34

    This study also accounts for the NHGDP losses separately for males and females. It is important to highlight the NHGDP losses borne by males and females separately as otherwise the huge economic loss borne by the untimely deaths of females would remain invisible. Losses on account of female deaths remain unaccounted in GDP calculations due to the underestimation of the roles females play in domestic and family care providing activities in households.38

    The findings of this study are corroborated by the findings of a study from China which demonstrates the effect of COVID-19 beyond the healthcare system and identifies that the potential productivity losses caused by a pandemic may by far exceed the healthcare cost.39 The huge losses in one single state, that is, West Bengal, in India give us a picture of the potential overall loss incurred in the country. Our estimates of NHGDP loss in West Bengal justifies the redirection of resources from other sectors of the economy to strengthen healthcare systems.35 Other studies have also identified the extent of the impact of COVID-19 on the world economy and its importance to institute future policies to protect society.40 41

    What is already known on this topic

    The COVID-19 pandemic has impacted economies worldwide by disrupting the socioeconomic fabric of the societies, and has manifested in terms of increased risk of extreme poverty and undernourishment levels.1 The pandemic has far-fetched consequences in terms of its indirect effects due to morbidity and mortality.2 Economic burden associated with COVID-19 has been estimated across various countries around the globe, such as Africa,42 China,39 India,10 Iran,43 Russia,44 Spain,45 Switzerland,46 USA47 and Vienna.48 As per US estimates, GDP loss associated with COVID-19 would amount to a cumulative US$1.4 trillion by 2030.47 In China, the estimated healthcare and societal costs associated with COVID-19 amounted to ¥4.26 billion.35 Economic burden associated with inpatient cases of COVID-19 alone amounted to $1.4 billion in Iran.43 The socioeconomic burden of COVID-19 in the Russian Federation amounted to approximately $71.1 billion, that is, 4% of their GDP.43 The existing studies indicate the huge economic burden imposed by the pandemic. Fiscal value or NHGDP loss has been estimated by very few countries. The fiscal value or NHGDP loss in China amounts to Int$924 million35 while that in India amounts to Int$815 million.36

    What this study adds

    This study adds to the existing limited literature on NHGDP loss attributable to COVID-19. This study substantiates the existing study based on the West Bengal state in India since it takes into consideration two most devastating peaks (in terms of loss of life) of COVID-19, one in September 2020 and another in April 2021, which had not been considered in the previous study.36 Further, the previous study based in India did not consider the attributable losses separately for males and females, a dimension addressed by this study.39 This study has also conducted sensitivity analysis by varying the AAD and considering the impact of excess deaths predicted by GBD and WHO.

    For accessibility and usability, we have created a free web-based, user-friendly tool, https://covidnonhealthgdp.cphr-mant.org, where users can enter data from their respective countries for calculating the NHGDP loss for their region. The ‘calculate’ function provides results, and ‘table’ function can be used to view final results table. Users can also download a pdf report using the ‘Download Report’ function.

    Limitations

    This study did not consider the costs associated with illness and recovery, that is, absence from work and costs associated with the treatment. PCGDP does not capture the inequality in the distribution of resources among people and households, and implies that the average income per capita might remain unchanged but the distribution of income might change. This has considerable implications at the household level.16 Further, GDP only captures economic activities associated with market transactions and does not take into consideration the valuation of domestic activities.16 For example, the value of labour of a woman who chooses to stay at home to conduct household chores and raise children is not accounted for in GDP estimations.16 GDP also does not account for the cost of production and consumption externalities such as pollution, climate change and the cost of consuming abusive substances (like smoking and alcohol).16 This study also did not account for the psychological pain associated with the death of one’s near and dear ones due to COVID-19.

    Conclusion

    This paper tried to contribute to the literature on the economic burden of COVID-19 deaths in West Bengal. The NHGDP loss (computed using state-level reported death figures) accounts for 0.2% of the state domestic product (SDP) of West Bengal. If the excess deaths reported by WHO and GBD are considered, then the NHGDP loss is found to be equivalent to 1.8% of the SDP of West Bengal. The loss is found to vary with the AAD and the discounting rate of interest. The NHGDP loss is significant especially for a state like West Bengal where one-fifth of the population lives below the poverty line.48

    The evidence from this paper substantiates the argument for the requirement of improved health infrastructure and greater allocation of funds to address the basic public health demands. The findings of this study re-establishes that health and economy are inseparably interlinked, probing the health and financial sectors of the economies to reconsider the laid down priorities to ensure sustainable improvements in population health, preparedness and economic performance.

    Data availability statement

    Data are available in a public, open access repository. All data that is incorporated into the article is available from the references mentioned. Raw data has been uploaded in the following link: https://datadryad.org/stash/share/XP_Zo452CqM-HYuLnhZHBjreokOm9A-h_Z7CEadGYuo.

    Ethics statements

    Patient consent for publication

    Ethics approval

    Not applicable.

    Acknowledgments

    The authors acknowledge the inputs provided by Dr Geetha Menon, Senior Scientist, ICMR-NIMS, New Delhi, India, for improving the manuscript.

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    Footnotes

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    • Contributors The conception and design of the study, or acquisition of data, or analysis and interpretation of data—PB, DJ, NM, NMS. Drafting the article or revising it critically for important intellectual content—DJ, PB, NM. Final approval of the version to be submitted—JM, AB, DJ, NM, NMS. DJ is the responsible for the overall content as the guarantor.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

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