Monitoring the Ebola Crisis Using Mobile Phone Surveys

Etang, Alvin; Himelein, Kristen

doi:10.1007/978-3-030-25120-8_2

Cited by 23 publications

(14 citation statements)

References 2 publications

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“…The 2014 Ebola outbreak in West Africa and the 2017 drought- and conflict-related food insecurity crisis in Nigeria, Somalia, South Sudan, and Yemen led to a need for timely data on how people’s livelihoods were affected. In both cases, phone surveys were deployed to meet emerging data demands ( Etang and Himelein, 2020 , Pape, 2020 ). The COVID-19 crisis is no different in the way policymakers, academics and the general public rushed to look for data to understand the evolution and impact of the pandemic.…”

Section: High Frequency Phone Surveys On Covid-19: How They Shaped Up In Developing Countriesmentioning

confidence: 99%

Viewpoint: High-frequency phone surveys on COVID-19: Good practices, open questions

et al. 2021

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Following the onset of the COVID-19 pandemic, face-to-face survey data collection efforts came to a halt due to lockdowns, limitations on mobility and social distancing requirements. What followed was a surge in phone surveys to fulfill rapidly evolving needs for timely and policy-relevant microdata for understanding the socioeconomic impacts of and responses to the pandemic. Even as the face-to-face survey data collection efforts are resuming in different parts of the world with COVID-19 safety protocols, the rapidly-acquired experience with phone surveys on the part of national statistical offices and survey practitioners in low- and middle-income countries appears to have formed the foundation for phone surveys to be more commonly implemented in the post-pandemic era, in response to other shocks and as complementary efforts to face-to-face surveys. Informed by the practical experience with the high-frequency phone surveys that have been implemented with support from the World Bank Living Standards Measurement Study (LSMS) to monitor the socioeconomic impacts of the COVID-19 pandemic, this paper provides an overview of options for the design and implementation of phone surveys to collect representative data from households and individuals. Further, the discussion identifies the requirements for phone surveys to be a mainstay in the toolkits of national statistical offices and the directions for future research on the design and implementation of phone surveys.

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Section: High Frequency Phone Surveys On Covid-19: How They Shaped Up In Developing Countriesmentioning

confidence: 99%

Viewpoint: High-frequency phone surveys on COVID-19: Good practices, open questions

et al. 2021

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“…A recent study using phone survey data from Ethiopia, Malawi, Nigeria, and Uganda shows that recalibrating survey weights is relatively successful at overcoming coverage and non-response biases at the household-level [ 15 ]. Reweighting was also used to improve the representativeness of a study on the impacts of the Ebola crisis in Liberia and Sierra Leone, albeit without a systematic attempt at assessing the relative success of this method [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Representativeness of individual-level data in COVID-19 phone surveys: Findings from Sub-Saharan Africa

2021

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The COVID-19 pandemic has created urgent demand for timely data, leading to a surge in mobile phone surveys for tracking the impacts of and responses to the pandemic. Using data from national phone surveys implemented in Ethiopia, Malawi, Nigeria and Uganda during the pandemic and the pre-COVID-19 national face-to-face surveys that served as the sampling frames for the phone surveys, this paper documents selection the biases in individual-level analyses based on phone survey data. In most cases, individual-level data are available only for phone survey respondents, who we find are more likely to be household heads or their spouses and non-farm enterprise owners, and on average, are older and better educated vis-a-vis the general adult population. These differences are the result of uneven access to mobile phones in the population and the way that phone survey respondents are selected. To improve the representativeness of individual-level analysis using phone survey data, we recalibrate the phone survey sampling weights based on propensity score adjustments that are derived from a model of an individual’s likelihood of being interviewed as a function of individual- and household-level attributes. We find that reweighting improves the representativeness of the estimates for phone survey respondents, moving them closer to those of the general adult population. This holds for both women and men and for a range of demographic, education, and labor market outcomes. However, reweighting increases the variance of the estimates and, in most cases, fails to overcome selection biases. This indicates limitations to deriving representative individual-level estimates from phone survey data. Obtaining reliable data on men and women through future phone surveys will require random selection of adult interviewees within sampled households.

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“…They show that recalibrating household weights is relatively successful at overcoming these biases at the household level -somewhat contrary to what we find for individual-level data. Both our paper and Ambel et al (forthcoming) use a similar reweighting model as Etang and Himelein (2020) who recalibrated phone survey weights in the context of the Ebola crisis to improve the representativeness of survey respondents vis-à-vis face-to-face survey respondents in Liberia and Sierra Leone. Our paper differs by virtue of our attempt at assessing the individuallevel phone survey data's representativeness of the entire adult population.…”

Section: Introductionmentioning

confidence: 99%

Representativeness of Individual-Level Data in COVID-19 Phone Surveys: Findings from Sub-Saharan Africa

Brubaker¹,

Kilic²,

Wollburg³

2021

Policy Research Working Papers

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The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

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Monitoring the Ebola Crisis Using Mobile Phone Surveys

Cited by 23 publications

References 2 publications

Viewpoint: High-frequency phone surveys on COVID-19: Good practices, open questions

Viewpoint: High-frequency phone surveys on COVID-19: Good practices, open questions

Representativeness of individual-level data in COVID-19 phone surveys: Findings from Sub-Saharan Africa

Representativeness of Individual-Level Data in COVID-19 Phone Surveys: Findings from Sub-Saharan Africa

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