All-cause excess mortality in the State of Gujarat, India, during the COVID-19 pandemic (March 2020-April 2021)

Acosta, Rolando J.; Patnaik, Biraj; Buckee, Caroline O.; Balsari, Satchit; Mahmud, Ayesha S.

doi:10.1101/2021.08.22.21262432

Cited by 7 publications

(17 citation statements)

References 15 publications

(9 reference statements)

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“…A total of 13 studies were included in the systematic review based on literature search. 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 Fig. 1 depicts the PRISMA chart for inclusion of the studies.…”

Section: Resultsmentioning

confidence: 99%

“…The majority of studies estimated excess deaths only at national level except three studies, which did it for Chennai (city), Gujrat and Bihar (states), respectively. 15 , 20 , 22 Table 1 shows the details of data sources used by various studies for counterfactual expected deaths during pandemic (counterfactual are those deaths which would have happened if there was no pandemic). Majority of the studies have used data from CRS for expected deaths.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

A systematic review of excess all-cause mortality estimation studies in India during COVID-19 pandemic

Yadav¹,

Ahmed

Dhumka

et al. 2023

Medical Journal Armed Forces India

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

A systematic review of excess all-cause mortality estimation studies in India during COVID-19 pandemic

Yadav¹,

Ahmed

Dhumka

et al. 2023

Medical Journal Armed Forces India

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“…But there is no convincing reason to believe the rest of the country was less hard hit than STAR12. Indeed, partial data [8,48,49] suggests that some of the absent states, such as Uttar Pradesh and Gujarat, have been very badly hit during the pandemic. The effects of these uncertainties are fairly easily quantified.…”

Section: Discussionmentioning

confidence: 99%

“…These disease surveillance systems are innovative in the context of India. However, it is widely recognized that reported cases generally capture a small fraction of total infections, and that deaths in these systems are undercounts [8][9][10]. All-cause mortality data, where available, has been used to understand the overall mortality impact of the pandemic [11,12].…”

Section: Introductionmentioning

confidence: 99%

Estimates of pandemic excess mortality in India based on civil registration data

Banaji

Gupta

2022

PLOS Glob Public Health

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The population health impacts of the COVID-19 pandemic are less well understood in low and middle-income countries, where mortality surveillance before the pandemic was patchy. Interpreting the limited all-cause mortality data available in India is challenging. We use existing data on all-cause mortality from civil registration systems of twelve Indian states comprising around 60% of the national population to understand the scale and timing of excess deaths in India during the COVID-19 pandemic. We carefully characterize the reasons why registration is incomplete and estimate the extent of coverage in the data. Comparing the pandemic period to 2019, we estimate excess mortality in twelve Indian states, and extrapolate our estimates to the rest of India. We explore sensitivity of the estimates to various assumptions. For the 12 states with available all-cause mortality data, we document an increase of 28% in deaths during April 2020–May 2021 relative to expectations from 2019. This level of increase in mortality, if it applies nationally, would imply 2.8–2.9 million excess deaths. More limited data from June 2021 increases national estimates of excess deaths during April 2020–June 2021 to 3.8 million. With more optimistic or pessimistic assumptions, excess deaths during this period could credibly lie between 2.8 million and 5.2 million. The scale of estimated excess deaths is broadly consistent with expectations based on seroprevalence and COVID-19 fatality rates observed internationally. Moreover, the timing of excess deaths and recorded COVID-19 deaths is similar–they rise and fall at the same time. The surveillance of pandemic mortality in India has been extremely poor, with 8–10 times as many excess deaths as officially recorded COVID-19 deaths. India is among the countries most severely impacted by the pandemic. Our approach highlights the utility of all-cause mortality data, as well as the significant challenges in interpreting it.

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“…These disease surveillance systems are innovative in the context of India. However, it is widely recognized that reported cases generally capture a small fraction of total infections, and that deaths in these systems are undercounts (8–10). All-cause mortality data, where available, has been used to understand the overall mortality impact of the pandemic (11,12).…”

Section: Introductionmentioning

confidence: 99%

Estimates of pandemic excess mortality in India based on civil registration data

Banaji¹,

Gupta²

2021

Preprint

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Background: The COVID-19 pandemic has had large impacts on population health. These impacts are less well understood in low-and middle-income countries, where mortality surveillance before the pandemic was patchy. Although limited all-cause mortality data are available in India, interpreting this data remains a challenge. Objective: We use existing data on all-cause mortality from civil registration systems of twelve Indian states comprising around 60% of the national population to understand the scale and timing of excess deaths in India during the COVID-19 pandemic. Methods: We characterize the available data, discuss the various reasons why these data are incomplete, and estimate the extent of coverage in the data. Comparing the pandemic period to 2019, we estimate excess mortality in twelve Indian states, and extrapolate our estimates to the rest of India. We explore sensitivity of the estimates to various assumptions, and present optimistic and pessimistic scenarios along with our central estimates. Results: For the 12 states with available all-cause mortality data, we document an increase of 28% in deaths during April 2020-May 2021 relative to expectations from 2019. This level of increase in mortality, if it applies nationally, would imply 2.8-2.9 million excess deaths. More limited data from June 2021 increases national estimates of excess deaths during April 2020-June 2021 to 3.8 million. With more optimistic or pessimistic assumptions, excess deaths during this period could credibly lie between 2.8 million and 5.2 million. We find that the scale of estimated excess deaths is broadly consistent with expectations based on seroprevalence data and international data on COVID-19 fatality rates. Moreover, there is a strong association between the timing of excess deaths, and of recorded COVID-19 deaths. Contribution: We show that the surveillance of pandemic mortality in India has been extremely poor, with around 8-10 times as many excess deaths as officially recorded COVID-19 deaths. Our findings highlight the utility of all-cause mortality data, as well as the significant challenges in interpreting such data from LMICs. These data reveal that India is among the countries most severely impacted by the pandemic. It is likely that in absolute terms India has seen the highest number of pandemic excess deaths of any country in the world.

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All-cause excess mortality in the State of Gujarat, India, during the COVID-19 pandemic (March 2020-April 2021)

Cited by 7 publications

References 15 publications

A systematic review of excess all-cause mortality estimation studies in India during COVID-19 pandemic

A systematic review of excess all-cause mortality estimation studies in India during COVID-19 pandemic

Estimates of pandemic excess mortality in India based on civil registration data

Estimates of pandemic excess mortality in India based on civil registration data

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