Estimates of Under-Five Mortality From a Mobile Phone Survey During the Covid-19 Outbreak

An Observational Study Comparing Three Instruments in Malawi

Bibliographic Data

ID19230747
AuthorsJulio Romero-Prieto (London School of Hygiene & Tropical Medicine), Julio E Romero-Prieto (0000-0002-8131-7821, Department of Population Health, London School of Hygiene and Tropical Medicine, London, UK), Boniface Dulani (0000-0002-0281-3000, University of Malawi), Bruno Masquelier (0000-0002-9585-891X, UCLouvain), Malebogo Tlhajoane (0000-0002-0601-5516, London School of Hygiene & Tropical Medicine), Helleringer (0000-0002-5921-9651, New York University Abu Dhabi), Jethro Banda (0000-0001-8075-8564, Malawi Epidemiology and Intervention Research Unit), Georges Reniers (0000-0001-6582-1692, London School of Hygiene & Tropical Medicine)
Year2026
Volume63
Issue2
Pages617-641
Publication date2026-04-01
Open AccessYes
TypeARTICLE
VenueDemography (JOURNAL)
Journal identifiersISSN: 0070-3370 • E-ISSN: 1533-7790
PublisherDuke University Press (PUBLISHER • US)
DOI10.1215/00703370-12559628
PMID42048260
OpenAlexW7157655131
LanguageEN
References cited37

Under-five mortality estimates for low- and middle-income countries are primarily derived from detailed birth or pregnancy histories collected through in-person household surveys. Such surveys are, however, resource intensive and vulnerable to interruption during epidemic outbreaks and other crises. Remotely deployed mobile phone surveys can circumvent these disadvantages, but their suitability for measuring population-level mortality has not been demonstrated. In this contribution, we examine Malawian mobile phone survey data from the Summary Birth Histories, Truncated Pregnancy Histories, and Full Pregnancy Histories instruments for estimating under-five mortality. Considering the limited penetration and the unequal distribution of mobile phones in Malawi, quota sampling was used to ensure representation of population subgroups where mobile phone ownership is low, and poststratification methods were applied to further attenuate selection bias. Resulting probabilities of dying, or q(x)—before 28 days, 12 months, and 60 months of life—are compared against external estimates from a recent Demographic and Health Survey, a Multiple Indicator Cluster Survey, and model-based estimates from the UN Inter-agency Group of Child Mortality Estimation. Mobile phone survey estimates using the Summary Birth Histories capture the historical trends of q(12m) and q(60m) up to 2018, but they are less reliable for the most recent years. Compared with external sources, estimates from the Truncated Pregnancy Histories appear to be biased downward. Estimates of q(28d), q(12m), and q(60m) from the Full Pregnancy Histories are in line with those published by the UN Inter-agency Group, but they are also suggestive of a mortality excess during the COVID-19 outbreak in 2020‒2022. We conclude that mobile phone surveys are a promising method for collecting under-five mortality data, and particularly so via the Full Pregnancy Histories instrument

Cluster sampling · Estimation · Mobile phone · Observational study · Phone · Population · Pregnancy · Survey methodology · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Global Maternal and Child Health

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