Interview transcripts for: "Understanding the impact of COVID-19 pandemic and its control measures on women and children: Zimbabwe case study" – User Guide

Persistent identifier

10.17037/DATA.00004258

Description

Data collected as part of the MaCOCO study to investigate the impact of COVID-19 control measures upon child and women's health in Sub-Saharan African countries. It consists of a set of transcripts that record key informant interviews (KIIs), focus group discussion, and household interviews. Interviews covered direct threats posed by COVID-19 as well as the social, educational, and economic harms associated with lockdown and other infection prevention and control measures. Research was conducted in four countries (Ghana, Tanzania, Uganda and Zimbabwe), with this data relating to Zimbabwe.

Interview transcripts are available via Figshare - https://doi.org/10.6084/m9.figshare.29046431

Data collection methods

Five experienced research assistants with a Master of Science in Social Science, fluent in English, Ndebele, and Shona conducted a household survey through interviews, key informant interviews (KIIs), and focus group discussions (FGDs). All research assistants attended a two-day orientation training session on the study objectives and expected outcomes. Prior to their use, all the study tools were piloted in similar urban settings. After piloting, the tools were appropriately revised to ensure their alignment with the pilot feedback and the research objectives.

To assess the impact of COVID-19 on households, we conducted 20 household interviews in Harare and Bulawayo with equal representation of the three aforementioned economic strata. Household heads were interviewed to determine their socioeconomic characteristics. A topic guide was developed to explore the experiences of households during the COVID-19 pandemic, focusing on their perceptions of control measures, livelihoods, and access to social services such as health and education. Additionally, the guides asked about their coping strategies during the pandemic.

To gain a broader community perspective, we conducted four FGDs with community members: two in Harare with 9 and 10 participants, and two in Bulawayo with 11 and 13 participants, respectively. Each FGD lasted between 2 two three hours, including a plenary discussion. The discussions were conducted in an open space while observing COVID-19 rules and regulations. Initially, using an FGD guide, all groups of participants were asked to discuss the following topics: the COVID-19 pandemic evolution in the country, policy implementation, livelihood experiences, and how they felt about pandemic management, in breakout groups of to 3-4 people for 60 minutes, guided by a research assistant. The summary of the breakout discussions were presented to a larger group to allow for corroboration.

To understand the broader vulnerability context and transformative structures and processes, a total of 18 purposive in-depth KIIs in person or on Zoom lasting on average 1h were conducted with stakeholders, including community-based organizations (CBOs) (n=5), city health managers (n=5 from Harare City Health and n=3 from Bulawayo City Health), as well as national program managers and policymakers (n=5). The KIIs questions aimed to gather informants’ experiences and perspectives on COVID-19 and its control measures. They also explored issues related to access to health services and treatment during the pandemic, including policy formulation and implementation.

Data analysis

All interviews and FDGs were recorded, transcribed verbatim, translated from Shona or Ndebele to English, and transferred to NVivo14.23.3 (QSR International) (61) software version for analysis. In the field, notes were taken, and daily interview summaries were subsequently written to aid interpretation. Guided by the SULF framework, we conducted a hybrid deductive and inductive thematic analysis of data. The deductive aspect of the analysis involved using codes developed a priori from SULF. Among these deductively produced high-level codes, lower-level codes were inductively generated using content analysis. Pattern coding was used to identify patterns across and within the data sources. This allowed the condensation of data into fewer relevant analytical concepts. For validity, pattern coding was conducted by three experienced researchers who reviewed all transcripts and identified the descriptive codes through consensus. This analytical approach helped maintain a focus on the holistic livelihood impact of the COVID-19 pandemic on households.

Resources

• Interview transcripts made available on Figshare - https://doi.org/10.6084/m9.figshare.29046431
• Understanding the impact of the COVID-19 pandemic on households’ livelihoods in Zimbabwe: A qualitative study using the sustainable urban livelihood framework - https://doi.org/10.12688/wellcomeopenres.24314.1

Geographic regions

Zimbabwe

Key dates

• Data collection period: April - December 2021
• Date submitted to repository: 4 July 2024

Population

Healthcare workers and community groups.

Keywords

COVID-19, SARS coronavirus, Lockdown, Health policy

Language of written material

English, Ndebele

Project information

Creators

Associated roles

File description