Evidence map›Paper›PMID 42048260›Full record

Observational studyDemography2026

Estimates of Under-Five Mortality From a Mobile Phone Survey During the COVID-19 Outbreak: An Observational Study Comparing Three Instruments in Malawi.

Julio Romero-Prieto, Boniface Dulani, Bruno Masquelier, Malebogo Tlhajoane, Stéphane Helleringer, Jethro Banda, Georges Reniers

Abstract readObservational StudyComparative Study
In one paragraph

Observational study in Demography, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Julio Romero-PrietoDepartment of Population Health, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0002-8131-7821
Boniface DulaniInstitute of Public Opinion and Research, Zomba, Malawi; Department of Politics and Government, University of Malawi, Zomba, Malawi.ORCID 0000-0001-5548-8398
Bruno MasquelierCentre for Demographic Research, Louvain University, Louvain-la-Neuve, Belgium.ORCID 0000-0002-9585-891X
Malebogo TlhajoaneDepartment of Population Health, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0002-0601-5516
Stéphane HelleringerNew York University Abu Dhabi, Abu Dhabi, United Arab Emirates.ORCID 0000-0002-5921-9651
Jethro BandaMalawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi.ORCID 0000-0001-8075-8564
Georges ReniersDepartment of Population Health, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0001-6582-1692

Funding

Global Age Patterns of Under-Five MortalityR01HD090082 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI GUILLOT, MICHEL · 2017 to 2021
$3.6M
Nutrition, late fetal and neonatal mortality in the African contextR01HD116453 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI MICHEL GUILLOT · 2024 to 2026
$1.4M
NICHD NIH HHS R01 HD090082NICHD NIH HHS R01 HD116453
6 · The paper itself

Abstract

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.

Indexed as

Cell PhoneChild MortalityCOVID-19Infant MortalityAdultChild, PreschoolDisease OutbreaksFemaleHumansInfantInfant, NewbornMalawiMalePregnancyBayesian Poisson regressionChild mortality estimationFull and truncated pregnancy historiesMalawiMobile phone surveys

Identifiers

PMID42048260
PMCPMC13319107

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