Protective Behaviors and Secondary Harms Resulting From Nonpharmaceutical Interventions During the COVID-19 Epidemic in South Africa: Multisite, Prospective Longitudinal Study
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Abstract
In March 2020, South Africa implemented strict nonpharmaceutical interventions (NPIs) to contain the spread of COVID-19. Over the subsequent 5 months, NPI policies were eased in stages according to a national strategy. COVID-19 spread throughout the country heterogeneously; the disease reached rural areas by July and case numbers peaked from July to August. A second COVID-19 wave began in late 2020. Data on the impact of NPI policies on social and economic well-being and access to health care are limited.
Objective
We aimed to determine how rural residents in three South African provinces changed their behaviors during the first COVID-19 epidemic wave.
Methods
The South African Population Research Infrastructure Network nodes in the Mpumalanga (Agincourt), KwaZulu-Natal, (Africa Health Research Institute) and Limpopo (Dikgale-Mamabolo-Mothiba) provinces conducted up to 14 rounds of longitudinal telephone surveys among randomly sampled households from rural and periurban surveillance populations every 2-3 weeks. Interviews included questions on the following topics: COVID-19–related knowledge and behaviors, the health and economic impacts of NPIs, and mental health. We analyzed how responses varied based on NPI stringency and household sociodemographics.
Results
In total, 5120 households completed 23,095 interviews between April and December 2020. Respondents’ self-reported satisfaction with their COVID-19–related knowledge and face mask use rapidly rose to 85% and 95%, respectively, by August. As selected NPIs were eased, the amount of travel increased, economic losses were reduced, and the prevalence of anxiety and depression symptoms fell. When the number of COVID-19 cases spiked at one node in July, the amount of travel dropped rapidly and the rate of missed daily medications doubled. Households where more adults received government-funded old-age pensions reported concerns about economic matters and medication access less often.
Conclusions
South Africans complied with stringent, COVID-19–related NPIs despite the threat of substantial social, economic, and health repercussions. Government-supported social welfare programs appeared to buffer interruptions in income and health care access during local outbreaks. Epidemic control policies must be balanced against the broader well-being of people in resource-limited settings and designed with parallel support systems when such policies threaten peoples’ income and access to basic services.
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SciScore for 10.1101/2020.11.12.20230136: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Consent: Ethical considerations: All households had previously given consent to be contacted by phone and each primary respondent gave recorded, verbal consent.
IRB: All study procedures were discussed with each nodes’ existing community advisory groups and approved by Limpopo, Mpumalanga and KwaZulu-Natal’s provincial Department of Health Research Ethics Committees (REC), the University of KwaZulu-Natal’s Biomedical REC, the University of the Witwatersrand’s Human REC (Medical) and the University of Limpopo’s Turfloop REC.Randomization Study design: In March 2020, SAPRIN initiated plans for each HDSS node to implement a high-intensity, longitudinal telephonic … SciScore for 10.1101/2020.11.12.20230136: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Consent: Ethical considerations: All households had previously given consent to be contacted by phone and each primary respondent gave recorded, verbal consent.
IRB: All study procedures were discussed with each nodes’ existing community advisory groups and approved by Limpopo, Mpumalanga and KwaZulu-Natal’s provincial Department of Health Research Ethics Committees (REC), the University of KwaZulu-Natal’s Biomedical REC, the University of the Witwatersrand’s Human REC (Medical) and the University of Limpopo’s Turfloop REC.Randomization Study design: In March 2020, SAPRIN initiated plans for each HDSS node to implement a high-intensity, longitudinal telephonic survey covering at least 750 randomly selected households in each setting, using telephone numbers extracted from each node’s most recent census. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Data analysis was conducted in Stata v15.1 (StataCorp, College Station, TX, USA) and R v4.0.2 [22]. StataCorpsuggested: (Stata, RRID:SCR_012763)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and limitations: This study has limitations. As with all observational studies, generalizability beyond our study population, in this case rural and peri-urban areas of eastern South Africa, is uncertain. This concern is tempered by our ability to compare and combine data across multiple sites and to triangulate with other studies of Covid-19 impact in South Africa and sub-Saharan African. While household cellphone ownership is high, there was evidence that poorer households in these areas were somewhat less likely to participate, which will affect response levels although less so the trends we focus on. Our data are self-reported, and thus represent perceived needs and impacts, and reported behaviour change may reflect desirability biases. However, even with such biases, findings provide insight into the perceptions and lived experiences of these communities. Again, triangulating our findings with digital data sources can help. Finally, we do not have data on identical questions from the pre-Covid period, however, we are able to leverage similar information on many topics from earlier surveillance. Nevertheless, the study also has several strengths, notably a clearly defined sampling base, high response and low attrition rates, frequent follow-up and linkage to pre-Covid household data. Many of these benefits arise from the nature of the existing SAPRIN surveillance infrastructure, reinforcing the importance of long-term population-based surveillance systems that c...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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