Occupational and Environmental Challenges and Effects of COVID-19 Testing Implementation Experienced by HIV Viral Load Laboratory Staff within a Public Health Sector Laboratory in South Africa
Sarang, S.; Matingo-Mutava, E.; Cassim, N.
Show abstract
BackgroundThe COVID-19 pandemic required South African public sector HIV viral load (VL) laboratories to scale up Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing while maintaining essential HIV services. This placed additional pressure on diagnostic services. This dual mandate introduced significant occupational and environmental challenges (OEC) for staff that remain underexplored. ObjectiveThis study aimed to investigate the OEC and effects that staff experienced during the implementation of COVID-19 testing at public sector VL laboratories in South Africa. MethodsA quantitative, cross-sectional study utilised a census approach among technical and support staff. Data were collected via a structured REDCap questionnaire using 5-point Likert scales. Pre- and post-implementation challenges were assessed across four domains: workload, environmental conditions (space, ventilation, waste), communication, and PPE availability. Statistical analyses included the Wilcoxon Signed-Rank and Spearmans correlation tests. ResultsPerceived occupational challenges increased significantly across all domains post-implementation. Staff workload saw the highest rise (mean score 3.02 to 3.53). Adverse health effects were pervasive; 80.2% of staff reported burnout/fatigue, and 76.5% reported increased anxiety/stress. A strong positive correlation was observed between post-COVID-19 challenges and adverse mental and physical health outcomes (rho = 0.449, p < 0.001). Furthermore, 35.8% of staff considered resigning due to increased job demands. ConclusionIntegrating COVID-19 testing exacerbated systemic weaknesses, causing measurable psychological injury and threatening workforce retention. Findings suggest that the diagnostic workforce requires formal crisis surge staffing models and institutionalised mental health support to safeguard personnel and maintain essential services during future health emergencies.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.