From Necessity to Opportunity
The COVID-19 pandemic has disrupted survey and data systems globally and especially in low- and middle-income countries. Lockdowns necessitated remote data collection as demand for data on the impacts of the pandemic surged. Phone surveys started being implemented at a national scale in many places...
Gespeichert in:
Hauptverfasser: | , , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The COVID-19 pandemic has disrupted
survey and data systems globally and especially in low- and
middle-income countries. Lockdowns necessitated remote data
collection as demand for data on the impacts of the pandemic
surged. Phone surveys started being implemented at a
national scale in many places that previously had limited
experience with them. As in-person data collection resumes,
the experience gained provides the grounds to reflect on how
phone surveys may be incorporated into survey and data
systems in low- and middle-income countries. This includes
agricultural and rural surveys supported by international
survey programs such as the World Bank’s Living Standards
Measurement Study—Integrated Surveys on Agriculture, the
Food and Agriculture Organization’s AGRISurvey, or the
50x2030 Initiative. Reviewing evidence and experiences from
before and during the pandemic, the paper analyzes and
provides guidance on the scope of and considerations for
using phone surveys for agricultural data collection. It
addresses the domains of sampling and representativeness,
post-survey adjustments, questionnaire design, respondent
selection and behavior, interviewer effects, as well as cost
considerations, all with an emphasis on the particularities
of agricultural and rural surveys. Ultimately, the
integration of phone interviews with in-person data
collection offers a promising opportunity to leverage the
benefits of phone surveys while addressing their
limitations, including the depth of content constraints and
potential coverage biases, which are especially challenging
for agricultural and rural populations in low- and
middle-income countries. |
---|