Publikationsdatenbank

Excess mortality during the COVID-19 pandemic in low-income and lower middle-income countries:
protocol for a systematic review and meta-analysis (2023)

Art

Vortrag

Autoren

Gmanyami, Jonathan Mawutor

Jarynowski, Andrzej (WE 16)

Belik, Vitaly (WE 16)

Lambert, Oscar

Amuasi, John

Quentin, Wilm

Kongress

German-West African Centre for Global Health and Pandemic Prevention (G-WAC). 2. Joint Digital Symposium

Düsseldorf, 09.10.2023

Quelle

Sprache

Englisch

Verweise

URL (Volltext): https://www.egms.de/static/en/meetings/gwac2023/23gwac11.shtml

DOI: 10.3205/23gwac11

Kontakt

Institut für Veterinär-Epidemiologie und Biometrie

Königsweg 67
14163 Berlin
+49 30 838 56034
epi@vetmed.fu-berlin.de

Abstract / Zusammenfassung

Research question:
This review sought to answer the following questions:

1.
What is the estimated level of excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries (LLMICs)?
2.
What methods and data are used to estimate excess mortality in LLMICs?
3.
What are the factors influencing excess mortality in LLMICs?

Methods:
The 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. These included studies with at least a one-year non-COVID-19 period as the comparator in estimating excess mortality and with publication dates from 2019 to date. The meta-analysis included studies with extractable data on excess mortality estimates, methods, population size, and observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio of excess mortality with 95% confidence intervals.

Results:
The review included 25 studies, of which 7 were included in the meta-analysis. 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 per pandemic period. The risk of excess mortality was 1.68 (95% CI: 1.67, 1.68 p<0.001). Data sources included civil registration systems, obituary notifications, surveys, public cemeteries, funeral counts, burial site imaging, and demographic surveillance systems. Techniques used to estimate expected deaths during the pandemic were mainly statistical forecast modelling and geospatial analysis. Of the 21 studies, only one found higher excess mortality in urban settings.

Discussion:
These findings contribute to a better understanding of the effect of the COVID-19 pandemic on excess mortality in LLMICs. Excess mortality in LLMICs during the pandemic was substantial; higher than direct COVID-19 mortality. Even though the availability of reliable data was a problem in many countries, the identified methods may inform future studies to provide more reliable estimates of excess mortality in LLMICs. Further studies are needed to identify the drivers of excess mortality in LLMICs, and methods identified in this review may inform future analyses.