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Estimation of All-Cause Excess Mortality by Age-Specific Mortality Patterns of COVID-19 Pandemic in Peru in 2020

55 Pages Posted: 6 Apr 2021

See all articles by Peter Lloyd-Sherlock

Peter Lloyd-Sherlock

University of East Anglia (UEA)

Shah Ebrahim

London School of Hygiene & Tropical Medicine

Ramón Martínez

Pan American Health Organization

Martin McKee

London School of Hygiene & Tropical Medicine

Enrique Acosta

Max Planck Society for the Advancement of the Sciences - Max Planck Institute for Demographic Research

Lucas Sempé

University of East Anglia (UEA)

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Abstract

Background: All-cause excess mortality is a comprehensive measure of the combined direct and indirect effects of COVID-19 on mortality. Estimates are usually derived from Civil Registration and Vital Statistics (CRVS) systems, but these do not include non-registered deaths, which may be affected by changes in vital registration coverage over time.

Methods: We use quasi-Poisson models to estimate excess registered mortality in Peru during the first wave of the COVID-19 pandemic during 2020. We use logistic mixed-effects models to estimate the completeness of the new online registration system (SINADEF) at this time.

Findings: We estimate that registered mortality nationally underestimates mortality by 30·1% (95% CI 28·9% - 32·7%). We estimate total all-cause excess mortality during the period of analysis at 142,875 (95% CI 127,163 - 155,739) of which 99,814 (95% CI 85,605 - 110,738) were captured by the vital registration system. Deaths at age 60 and over accounted for 74·9% (95% CI 74·9% - 75·0%) of total excess deaths, while there were fewer deaths than expected in younger age groups. Lima region, on the Pacific coast and including the national capital, accounts for 76,158 (95% CI 72,740 - 79,212) excess deaths, while the regions of Apurimac and Pasco account for less than 300 excess deaths.

Interpretation: Estimating excess mortality in low- and middle-income countries (LMICs) such as Peru must take under-registration of mortality into account. Combining demographic trends with data from administrative registries reduces uncertainty and measurement errors. In countries like Peru, this is likely to produce significantly higher estimates of excess mortality than studies that do not take these effects into account.

Funding Statement: None.

Declaration of Interests: RM is a staff member of the Pan American Health Organization. The author alone is responsible for the views expressed in this publication, and they do not necessarily represent the decisions or policies of the Pan American Health Organization. All other authors declare no competing interests.

Suggested Citation

Lloyd-Sherlock, Peter and Ebrahim, Shah and Martínez, Ramón and McKee, Martin and Acosta, Enrique and Sempé, Lucas, Estimation of All-Cause Excess Mortality by Age-Specific Mortality Patterns of COVID-19 Pandemic in Peru in 2020. Available at SSRN: https://ssrn.com/abstract=3820553 or http://dx.doi.org/10.2139/ssrn.3820553

Peter Lloyd-Sherlock

University of East Anglia (UEA) ( email )

School of Development Studies
Norwich, Norfolk NR4 7TJ
United Kingdom

Shah Ebrahim

London School of Hygiene & Tropical Medicine

Keppel Street
London, WC1E 7HT
United Kingdom

Ramón Martínez

Pan American Health Organization ( email )

Washington, DC
United States

Martin Mckee

London School of Hygiene & Tropical Medicine ( email )

United Kingdom

Enrique Acosta

Max Planck Society for the Advancement of the Sciences - Max Planck Institute for Demographic Research ( email )

Doberaner Str. 114
Rostock 18057, 53113
Germany

Lucas Sempé (Contact Author)

University of East Anglia (UEA) ( email )

Norwich Research Park
Norwich, Norfolk NR4 7TJ
United Kingdom

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