Cargando…
Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic
BACKGROUND: Estimates of excess mortality are required to assess and compare the impact of the COVID-19 pandemic across populations. For India, reliable baseline prepandemic mortality patterns at national and subnational level are necessary for such assessments. However, available data from the Civi...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627370/ https://www.ncbi.nlm.nih.gov/pubmed/34824138 http://dx.doi.org/10.1136/bmjgh-2021-007399 |
_version_ | 1784606841425100800 |
---|---|
author | Rao, Chalapati John, Amrit Jose Yadav, Ajit Kumar Siraj, Mansha |
author_facet | Rao, Chalapati John, Amrit Jose Yadav, Ajit Kumar Siraj, Mansha |
author_sort | Rao, Chalapati |
collection | PubMed |
description | BACKGROUND: Estimates of excess mortality are required to assess and compare the impact of the COVID-19 pandemic across populations. For India, reliable baseline prepandemic mortality patterns at national and subnational level are necessary for such assessments. However, available data from the Civil Registration System (CRS) is affected by incompleteness of death recording that varies by sex, age and location. METHODS: Under-reporting of CRS 2019 deaths was assessed for three age groups (< 5 years, 15–59 years and ≥60 years) at subnational level, through comparison with age-specific death rates from alternate sources. Age-specific corrections for under-reporting were applied to derive adjusted death counts by sex for each location. These were used to compute life expectancy (LE) at birth by sex in 2019, which were compared with subnational LEs from the Global Burden of Disease (GBD) 2019 Study. RESULTS: A total of 9.92 million deaths (95% UI 9.70 to 10.02) were estimated across India in 2019, about 2.28 million more than CRS reports. Adjustments to under-five and elderly mortality accounted for 30% and 56% of additional deaths, respectively. Adjustments in Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh accounted for 75% of all additional deaths. Adjusted LEs were below corresponding GBD estimates by ≥2 years for males at national level and in 20 states, and by ≥1 year for females in 12 states. CONCLUSIONS: These results represent the first-ever subnational mortality estimates for India derived from CRS reported deaths, and serve as a baseline for assessing excess mortality from the COVID-19 pandemic. Adjusted life expectancies indicate higher mortality patterns in India than previously perceived. Under-reporting of infant deaths and those among women and the elderly is evident in many locations. Further CRS strengthening is required to improve the empirical basis for local mortality measurement across the country. |
format | Online Article Text |
id | pubmed-8627370 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-86273702021-12-01 Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic Rao, Chalapati John, Amrit Jose Yadav, Ajit Kumar Siraj, Mansha BMJ Glob Health Original Research BACKGROUND: Estimates of excess mortality are required to assess and compare the impact of the COVID-19 pandemic across populations. For India, reliable baseline prepandemic mortality patterns at national and subnational level are necessary for such assessments. However, available data from the Civil Registration System (CRS) is affected by incompleteness of death recording that varies by sex, age and location. METHODS: Under-reporting of CRS 2019 deaths was assessed for three age groups (< 5 years, 15–59 years and ≥60 years) at subnational level, through comparison with age-specific death rates from alternate sources. Age-specific corrections for under-reporting were applied to derive adjusted death counts by sex for each location. These were used to compute life expectancy (LE) at birth by sex in 2019, which were compared with subnational LEs from the Global Burden of Disease (GBD) 2019 Study. RESULTS: A total of 9.92 million deaths (95% UI 9.70 to 10.02) were estimated across India in 2019, about 2.28 million more than CRS reports. Adjustments to under-five and elderly mortality accounted for 30% and 56% of additional deaths, respectively. Adjustments in Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh accounted for 75% of all additional deaths. Adjusted LEs were below corresponding GBD estimates by ≥2 years for males at national level and in 20 states, and by ≥1 year for females in 12 states. CONCLUSIONS: These results represent the first-ever subnational mortality estimates for India derived from CRS reported deaths, and serve as a baseline for assessing excess mortality from the COVID-19 pandemic. Adjusted life expectancies indicate higher mortality patterns in India than previously perceived. Under-reporting of infant deaths and those among women and the elderly is evident in many locations. Further CRS strengthening is required to improve the empirical basis for local mortality measurement across the country. BMJ Publishing Group 2021-11-25 /pmc/articles/PMC8627370/ /pubmed/34824138 http://dx.doi.org/10.1136/bmjgh-2021-007399 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://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://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Rao, Chalapati John, Amrit Jose Yadav, Ajit Kumar Siraj, Mansha Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic |
title | Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic |
title_full | Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic |
title_fullStr | Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic |
title_full_unstemmed | Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic |
title_short | Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic |
title_sort | subnational mortality estimates for india in 2019: a baseline for evaluating excess deaths due to the covid-19 pandemic |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627370/ https://www.ncbi.nlm.nih.gov/pubmed/34824138 http://dx.doi.org/10.1136/bmjgh-2021-007399 |
work_keys_str_mv | AT raochalapati subnationalmortalityestimatesforindiain2019abaselineforevaluatingexcessdeathsduetothecovid19pandemic AT johnamritjose subnationalmortalityestimatesforindiain2019abaselineforevaluatingexcessdeathsduetothecovid19pandemic AT yadavajitkumar subnationalmortalityestimatesforindiain2019abaselineforevaluatingexcessdeathsduetothecovid19pandemic AT sirajmansha subnationalmortalityestimatesforindiain2019abaselineforevaluatingexcessdeathsduetothecovid19pandemic |