Excess mortality in low-and lower-middle-income countries: A systematic review and meta-analysis
Abstract Background The COVID-19 pandemic caused a massive death toll, but its effect on mortality remains uncertain in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality in LLMICs, including methods, data sources, and drivers of exce...
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creator | Gmanyami, J Jarynowski, A Belik, V Lambert, O Amuasi, J H Quentin, W |
description | Abstract
Background
The COVID-19 pandemic caused a massive death toll, but its effect on mortality remains uncertain in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality in LLMICs, including methods, data sources, and drivers of excess mortality.
Methods
A protocol was registered in PROSPERO (ID: CRD42022378267). We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus for studies conducted in LLMICs on excess mortality which included at least a one-year non-COVID-19 period as the comparator, and with publication date from 2019 to date. The meta-analysis included studies with extractable data on excess mortality, methods, population size, and observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio with 95% confidence intervals.
Results
The review included 21 studies (5 from Africa), of which 11 were included in the meta-analysis (2 from Africa). Of 1,405,128,717 individuals, 2,161,846 deaths were expected, and 3,633,661 deaths were reported. The pooled excess mortality was 104.7 deaths per 100,000 population. The risk of excess mortality was 1.68 (95% CI: 1.67, 1.68 p |
doi_str_mv | 10.1093/eurpub/ckad160.017 |
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Background
The COVID-19 pandemic caused a massive death toll, but its effect on mortality remains uncertain in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality in LLMICs, including methods, data sources, and drivers of excess mortality.
Methods
A protocol was registered in PROSPERO (ID: CRD42022378267). We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus for studies conducted in LLMICs on excess mortality which included at least a one-year non-COVID-19 period as the comparator, and with publication date from 2019 to date. The meta-analysis included studies with extractable data on excess mortality, methods, population size, and observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio with 95% confidence intervals.
Results
The review included 21 studies (5 from Africa), of which 11 were included in the meta-analysis (2 from Africa). Of 1,405,128,717 individuals, 2,161,846 deaths were expected, and 3,633,661 deaths were reported. The pooled excess mortality was 104.7 deaths per 100,000 population. The risk of excess mortality was 1.68 (95% CI: 1.67, 1.68 p < 0.001). Data sources included public cemeteries, civil registration systems, obituary notifications, surveys, funeral counts, burial site imaging, and demographic surveillance systems. Techniques used to estimate excess mortality were mainly statistical modelling and geospatial analysis. Of the 21 studies, only one reported on drivers of excess mortality and found higher excess mortality in urban settings.
Conclusions
Our results show that excess mortality in LLMICs during the pandemic was substantial even if it was considerably lower than in high-income countries. There is uncertainty around excess mortality estimates given comparatively weak data. Further studies are needed to identify the drivers of excess mortality by exploring different methods and data sources.</description><identifier>ISSN: 1101-1262</identifier><identifier>EISSN: 1464-360X</identifier><identifier>DOI: 10.1093/eurpub/ckad160.017</identifier><language>eng</language><publisher>Oxford University Press</publisher><subject>Parallel Programme</subject><ispartof>European journal of public health, 2023-10, Vol.33 (Supplement_2)</ispartof><rights>The Author(s) 2023. Published by Oxford University Press on behalf of the European Public Health Association. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10595406/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10595406/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,725,778,782,862,883,27913,27914,53780,53782</link.rule.ids></links><search><creatorcontrib>Gmanyami, J</creatorcontrib><creatorcontrib>Jarynowski, A</creatorcontrib><creatorcontrib>Belik, V</creatorcontrib><creatorcontrib>Lambert, O</creatorcontrib><creatorcontrib>Amuasi, J H</creatorcontrib><creatorcontrib>Quentin, W</creatorcontrib><title>Excess mortality in low-and lower-middle-income countries: A systematic review and meta-analysis</title><title>European journal of public health</title><description>Abstract
Background
The COVID-19 pandemic caused a massive death toll, but its effect on mortality remains uncertain in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality in LLMICs, including methods, data sources, and drivers of excess mortality.
Methods
A protocol was registered in PROSPERO (ID: CRD42022378267). We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus for studies conducted in LLMICs on excess mortality which included at least a one-year non-COVID-19 period as the comparator, and with publication date from 2019 to date. The meta-analysis included studies with extractable data on excess mortality, methods, population size, and observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio with 95% confidence intervals.
Results
The review included 21 studies (5 from Africa), of which 11 were included in the meta-analysis (2 from Africa). Of 1,405,128,717 individuals, 2,161,846 deaths were expected, and 3,633,661 deaths were reported. The pooled excess mortality was 104.7 deaths per 100,000 population. The risk of excess mortality was 1.68 (95% CI: 1.67, 1.68 p < 0.001). Data sources included public cemeteries, civil registration systems, obituary notifications, surveys, funeral counts, burial site imaging, and demographic surveillance systems. Techniques used to estimate excess mortality were mainly statistical modelling and geospatial analysis. Of the 21 studies, only one reported on drivers of excess mortality and found higher excess mortality in urban settings.
Conclusions
Our results show that excess mortality in LLMICs during the pandemic was substantial even if it was considerably lower than in high-income countries. There is uncertainty around excess mortality estimates given comparatively weak data. Further studies are needed to identify the drivers of excess mortality by exploring different methods and data sources.</description><subject>Parallel Programme</subject><issn>1101-1262</issn><issn>1464-360X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNqNkF1LwzAUhosoOKd_wKv8gWw5_Ugab2SM-QEDbxS8i1l6qtG2GUm72X9vR4fgnVfvgXOel8MTRdfAZsBkMsfOb7vN3HzpAjibMRAn0QRSntKEs9fTYQYGFGIen0cXIXwyxjKRx5PobfVtMARSO9_qyrY9sQ2p3J7qpjgkelrboqiQ2sa4GolxXdN6i-GGLEjoQ4u1bq0hHncW9-SA1djqgddVH2y4jM5KXQW8OuY0erlbPS8f6Prp_nG5WFMDOQgqpdaQJHGRyQ0f_sxFlm6AMSlTwXmS5iZGkNIIRBSYaCZKiIFzYFyUKRbJNLodewcPNRYGhy91pbbe1tr3ymmr_m4a-6He3U4By2SWMj40xGOD8S4Ej-UvDEwdLKvRsjpaVoPlAaIj5Lrtf-5_ANG-hGI</recordid><startdate>20231024</startdate><enddate>20231024</enddate><creator>Gmanyami, J</creator><creator>Jarynowski, A</creator><creator>Belik, V</creator><creator>Lambert, O</creator><creator>Amuasi, J H</creator><creator>Quentin, W</creator><general>Oxford University Press</general><scope>TOX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>5PM</scope></search><sort><creationdate>20231024</creationdate><title>Excess mortality in low-and lower-middle-income countries: A systematic review and meta-analysis</title><author>Gmanyami, J ; Jarynowski, A ; Belik, V ; Lambert, O ; Amuasi, J H ; Quentin, W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1817-99aa1332d59b61268754b100994766348c2e199c7eee7e3a07f121661067f4ed3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Parallel Programme</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gmanyami, J</creatorcontrib><creatorcontrib>Jarynowski, A</creatorcontrib><creatorcontrib>Belik, V</creatorcontrib><creatorcontrib>Lambert, O</creatorcontrib><creatorcontrib>Amuasi, J H</creatorcontrib><creatorcontrib>Quentin, W</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>European journal of public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gmanyami, J</au><au>Jarynowski, A</au><au>Belik, V</au><au>Lambert, O</au><au>Amuasi, J H</au><au>Quentin, W</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Excess mortality in low-and lower-middle-income countries: A systematic review and meta-analysis</atitle><jtitle>European journal of public health</jtitle><date>2023-10-24</date><risdate>2023</risdate><volume>33</volume><issue>Supplement_2</issue><issn>1101-1262</issn><eissn>1464-360X</eissn><abstract>Abstract
Background
The COVID-19 pandemic caused a massive death toll, but its effect on mortality remains uncertain in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality in LLMICs, including methods, data sources, and drivers of excess mortality.
Methods
A protocol was registered in PROSPERO (ID: CRD42022378267). We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus for studies conducted in LLMICs on excess mortality which included at least a one-year non-COVID-19 period as the comparator, and with publication date from 2019 to date. The meta-analysis included studies with extractable data on excess mortality, methods, population size, and observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio with 95% confidence intervals.
Results
The review included 21 studies (5 from Africa), of which 11 were included in the meta-analysis (2 from Africa). Of 1,405,128,717 individuals, 2,161,846 deaths were expected, and 3,633,661 deaths were reported. The pooled excess mortality was 104.7 deaths per 100,000 population. The risk of excess mortality was 1.68 (95% CI: 1.67, 1.68 p < 0.001). Data sources included public cemeteries, civil registration systems, obituary notifications, surveys, funeral counts, burial site imaging, and demographic surveillance systems. Techniques used to estimate excess mortality were mainly statistical modelling and geospatial analysis. Of the 21 studies, only one reported on drivers of excess mortality and found higher excess mortality in urban settings.
Conclusions
Our results show that excess mortality in LLMICs during the pandemic was substantial even if it was considerably lower than in high-income countries. There is uncertainty around excess mortality estimates given comparatively weak data. Further studies are needed to identify the drivers of excess mortality by exploring different methods and data sources.</abstract><pub>Oxford University Press</pub><doi>10.1093/eurpub/ckad160.017</doi><oa>free_for_read</oa></addata></record> |
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subjects | Parallel Programme |
title | Excess mortality in low-and lower-middle-income countries: A systematic review and meta-analysis |
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