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2022-’23 Malawi rapid mortality mobile phone survey (RaMMPS) dataset


Author(s) : David Amadi, Julio Romero-Prieto, Funny Muthema, Jacob Saikolo, Michael Chasukwa, Jethro Banda, Monica Jamali, Emmanuel Souza, Tathagata Bhattacharjee, Malebogo Tlhajoane, Stéphane Helleringer, Georges Reniers, Boniface Dulani
Data in Brief

Abstract


In countries with limited civil registration and vital statistics systems, mortality estimates are often derived from periodic censuses and household surveys. Mobile Phone Surveys (MPS) offer a potentially cost-effective and efficient alternative for mortality monitoring. However, their utility for this purpose still requires rigorous evaluation. The Rapid Mortality Mobile Phone Surveys (RaMMPS) project aims to develop and validate methodologies for collecting mortality data through phone-based surveys. The Malawi RaMMPS fieldwork was conducted between 24 January 2022 and 28 July 2023 and included several survey modules, including respondent background characteristics, COVID-19 vaccination status, deaths in the household in the three months prior to the interview, parental survival histories, sibling survival histories, and pregnancy histories. The resulting datasets can be used for estimating mortality and assessing the impact of the COVID-19 pandemic. Survey paradata can be used for analysing respondent engagement and the data collection process in an MPS.


Original language en
Pages (from-to) 112221
Volume 63
Publication status Published - 2025

UN SDGs

This research output contributes to the following United Nations (UN) Sustainable Development Goals (SDGs)

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10.1016/j.dib.2025.112221

UN SDGs

This research output contributes to the following United Nations (UN) Sustainable Development Goals (SDGs)

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10.1016/j.dib.2025.112221
    1. Mortality, morbidity and health-seeking behaviour during the Ebola epidemic 2014–2015 in Monrovia results from a mobile phone survey. Kuehne (2016). PLoS Negl. Trop. Dis., Vol. 10, (8).
      https://doi.org/10.1371/journal.pntd.0004899
    2. High-frequency phone surveys on COVID-19: good practices, open questions. Gourlay (2021). Food Policy, Vol. 105.
      https://doi.org/10.1016/j.foodpol.2021.102153
    3. Remote surveying in a pandemic: research synthesis. Henderson (2020). Innovat. Poverty Action.
    4. Measuring excess mortality during the COVID-19 pandemic in low-and lower-middle income countries: the need for mobile phone surveys. Adjiwanou (2020). SocArXiv (4bu3q).
    5. Collecting mortality data via mobile phone surveys: a non-inferiority randomized trial in Malawi. Chasukwa (2022). PLOS Global Public Health, Vol. 2, (8).
      https://doi.org/10.1371/journal.pgph.0000852
    6. Measuring adult mortality from mobile phone surveys in Burkina Faso, Malawi and the Democratic Republic of the Congo. Dianou (2025). medRxiv.
    7. Mobile phone survey estimates of perinatal mortality in Malawi: a comparison of data from truncated and full pregnancy histories. Reniers (2025). Trop. Med. Int. Health.
      https://doi.org/10.1111/tmi.14109
    8. Health surveys using mobile phones in developing countries: automated active strata monitoring and other statistical considerations for improving precision and reducing biases. Labrique (2017). J. Med. Internet Res., Vol. 19, (5), pp. e121.
      https://doi.org/10.2196/jmir.7329
    9. . .
      NSO, 2018 Malawi Population and Housing Census: main Report, National Statitical Office, Zomba, 2019, p. 299.
    10. Interrogating the quality and completion of mortality mobile phone interviews conducted in Malawi during COVID-19: an examination of interviewer–respondent interactions. Souza (2024). Demogr. Res., Vol. 51, pp. 1471.
      https://doi.org/10.4054/DemRes.2024.51.46
    11. . .
      AAPOR, Standard definitions: final dispositions of case codes and outcome rates for surveys, 2023.
    12. . .
      NSO, ICF, Malawi Demographic and Health Survey 2015-16, Zomba (Malawi) and Rockville (Maryland, USA), 2017.
    13. Interactive voice response surveys as a method for increasing the representativeness of rural respondents in a mortality mobile phone survey: findings from Malawi. Tlhajoane (2025). Trop. Med. Int. Health, Vol. 30, (9), pp. 937.
      https://doi.org/10.1111/tmi.70005
    14. Measuring under-5 mortality and fertility through mobile phone surveys: an assessment of selection bias in 34 low-income and middle-income countries. Sánchez-Páez (2023). BMJ Open., Vol. 13, (11).
      https://doi.org/10.1136/bmjopen-2023-071791
    15. Selection bias in adult mortality measurement through mobile phone surveys in low- and middle- income countries. Ahmed (2024). Demogr. Res., Vol. 51, pp. 1167.
      https://doi.org/10.4054/DemRes.2024.51.37

UN SDGs

This research output contributes to the following United Nations (UN) Sustainable Development Goals (SDGs)

sdg

Access document

10.1016/j.dib.2025.112221