The impact of COVID-19 in South Africa during the first year of the crisis: Evidence from the NIDS-CRAM survey

ABSTRACT

This paper provides an introduction to this Special Issue of Development Southern Africa that evaluates the impact of COVID-19 in South Africa, one year into the pandemic. All of the papers use evidence from the National Income Dynamics Study – Coronavirus Rapid Mobile Survey (NIDS-CRAM), a five-wave longitudinal survey conducted from April 2020 to July 2021. As we write this article in June 2022, South Africa has just returned to the same level of GDP that it had at the end of 2019. This two-year period marks one of the most tumultuous in the country’s economic history. We showcase results pertaining to employment, income support, hunger, schooling, early childhood development, mental health, and vaccine hesitancy. We also reflect on the policy learnings that can be gleaned in each of these domains and draw on some of the international lessons learnt to point to the way forward.

KEYWORDS:

• COVID-19
• NIDS-CRAM
• socio-economic impact
• survey data

Acknowledgements

The authors would like to acknowledge the massive contribution of Nic Spaull (Stellenbosch University), founder and Principle Investigator of the NIDS-CRAM project. Nic conceptualised the project, brought together the team of academics and data scientists, and worked tirelessly to ensure that each subsequent wave of data was released to policy-makers, the media and the broader public as quickly as possible. A project of this size would have been impossible to pull off without the support of many other parties. These include the excellent data team at SALDRU at the University of Cape Town consisting of Reza Daniels (also one of the Principal Investigators), Tim Brophy and Kim Ingle; the team leads; members of the steering committee; members of the working groups on sampling, data collection and quality, and the various subject themes; the data collection company AskAfrica; all the authors on the over 70 working papers and technical reports; the many reviewers and discussants; partners in government; and, importantly, the survey participants themselves. Without the hard work, dedication and collegiality from all of these stakeholders, the NIDS-CRAM project would not have been realised. Last but not least, the authors would like to gratefully acknowledge the generous funding from the Allan & Gill Gray Philanthropy Fund, the Federated Employers Mutual Education Fund, and the Michael & Susan Dell Foundation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 For more details of the survey, including the sampling design and weighting approach, see Ingle et al (2021). Access to the data, working papers, and links for the webinars associated with each release, is publicly available at the survey website: https://cramsurvey.org/

2 Note that Levels 1–5 denoted progressively more restrictive lockdown regulations. ‘Adjusted’ lockdown levels denote the relaxation of some of the original regulations at each lockdown level.

3 See Appendix Table A.1 in Casale and Shepherd (2022) in this issue for a detailed discussion of which lockdown regulations were associated with each wave of NIDS-CRAM.

4 See Casale and Shepherd (2022), Appendix Table A.1, in this issue for details on school and childcare facility closures and reopenings during the various NIDS-CRAM waves.

5 In addition to insufficient statistical power, another limitation of the NIDS-CRAM survey is that due to interview length constraints, information on occupation and sector was not collected for the job held in February 2020. This means there is no pre-pandemic baseline against which to compare later occupational and sectoral distributions.

6 For example, the authors note that twice as many households reported running out of money to buy food in a single month, i.e. April 2020, as did in the entire year of 2017.

7 Shielding is measured as occurring when no children are reported to have gone hungry in the week preceding the interview, even though an adult in the same household went hungry during that week.

8 Depressed mood was measured using a two-question version of the Patient Health Questionnaire (PHQ-2), which asks respondents about how often in the previous two weeks they have ‘had little interest or pleasure in doing things’ and how often they ‘have been feeling down, depressed or hopeless’. These questions can be used to screen for depression and identify people at risk who require further evaluation (Hunt et al 2021).

9 Unlike with Grades R-12, in South Africa the ECCE sector largely relies on fees collected from caregivers to stay open, with only a small percentage of operators benefiting from state subsidies which are paid to registered providers on a child attending per day basis. This means that during lockdowns and government-enforced closures, when children couldn’t attend, most operators would have lost their primary source of income. Also, the majority of workers in the sector are not registered for UIF and initially would have been unable to claim from the UIF-TERS (Wills & Kika-Mistry, 2022). When they were allowed to reopen, the financial feasibility of many ECCE operators remained tenuous given costly safety protocols and child capacity limits.

10 In NIDS-CRAM Waves 4 and 5, respondents were asked to what extent they agreed or disagreed with the statement ‘If a vaccine for COVID-19 were available, I would get it’. The four response options were: ‘Strongly agree, somewhat agree, somewhat disagree, and strongly disagree’. Vaccine acceptance was defined to include both those who ‘strongly’ or ‘somewhat’ agree with the statement, while vaccine reluctance or hesitancy was defined as those who ‘strongly’ or ‘somewhat’ disagreed, as well as those who said that they did not know (Burger et al 2021).