ArticleBMJ open2023
Estimation of non-health gross domestic product (NHGDP) loss due to COVID-19 deaths in West Bengal, India.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Productivity Losses due to Health Problems Arising from COVID-19 Pandemic: A Systematic Review of Population-Level Studies Worldwide.Applied health economics and health policy · 2025Pooled it
- Paid and unpaid productivity losses across 28 European countries due to excess deaths and COVID-19 deaths from 2020 to 2023.The European journal of health economics : HEPAC : health economics in prevention and care · 2026Article
- Estimation of non-health gross domestic product (NHGDP) loss due to COVID-19 deaths in West Bengal, India.BMJ open · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe 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.
settingVarious 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).
results21 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.
conclusionsResults 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.