Electronic Theses and Dissertations (Masters)

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    The relationship between mental distress and somatization in hospital based health care workers in Gauteng during covid-19 pandemic in 2020
    (University of the Witwatersrand, Johannesburg, 2023) Ramuedi, Ntsako Khosa; Kerry Wilson, Nioh
    Background Mental distress among Health Care Workers (HCWs) is an urgent health concern, and somatization is a known outcome of mental distress. The Covid-19 pandemic increased stress for HCWs globally due to working with Covid-19 patients and resource limitations. Although there was already a lot of mental distress in HCWs in prior years, the coronavirus pandemic made matters worse, with 45% of people reporting that the pandemic had a significant negative impact on their lives. Somatization can lead to increased use of health services, sick leave and poor health. Service delivery is also impacted negatively if the service providers are not well or are suffering from the mental distress and are also showing symptoms. Aim To identify if a relationship exists between mental distress and somatization symptoms in Gauteng hospital-based health care workers in 2020. Objectives. To describe the prevalence of mental distress and somatization among health care workers by socio demographic status. To identify the somatization symptoms associated with high GHQ-12 scores in health care workers during Covid-19. To describe the association between mental distress and somatization among health care workers during covid-19 adjusting for demographic variables. Methods Health care workers can be described as anyone working in the health sector or at a health facility. All staff in the three selected hospital facilities in Johannesburg, were given the opportunity participate in the study. The PHQ-15 and GHQ-12 tools were used to collect information on HCWs somatization and mental distress after the first wave of the Covid-19 pandemic in South Africa. The anonymous questionnaire consisted of the two tools and demographic questions was used. The responses to each question on the tools were summed in order to determine severity of mental distress and somatization in HCWs, a higher score indicating more stress and or more somatization. Logistic regression was used to determine the adjusted relationship between somatization and mental distress. Results The study had a sample size of 295. A large proportion of participants (52%) reported suffering somatic symptoms. Males mean somatization score was significantly lower than the females. The majority (62%) of HCWs were troubled indicating a high burden of mental distress in the health care sector. The most commonly reported symptoms were back pain, headaches and being tired or low energy, all three were significantly associated with mental distress among others. There was a positive moderate correlation between PHQ-15 and GHQ-12 scores (0.30592) (p < 0.0001). Logistic regression indicated somatization was significantly associated with mental distress with a significant OR 2.14 (p = 0.0029) adjusted for demographic factors in these workers. Conclusions There was a statistically significant positive relationship between somatization and poor mental health. Health care workers with mental distress may be at risk of somatization, particularly specific symptoms such as back pain, headache and having low energy. Females were more bothered by most of the somatoform symptoms as compared to their male counterparts. Support for health care worker’s mental health is required as well as increased awareness of somatization linked to mental distress. Policies and services need to be developed to protect and support HCWs mental health during times of stress in the sector
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    The use of machine learning techniques in identifying gender differentials in COVID-19 hospitalizations, probabilities of hospitalization outcomes and hidden correlations with demographic and clinical factors
    (2024) Malaatjie, Meghan Abigail
    Background: Sex-differentiated data on hospitalisation frequency, case severity, pre-existing medical conditions, and mortality outcomes amongst Covid-19 hospitalised patients is needed but limited in Gauteng province, the epicentre of the Covid-19 pandemic in South Africa. This study aims to investigate whether Machine Learning techniques can provide insight into gender differentials in COVID-19 hospitalizations throughout the four waves of the pandemic, in the Gauteng province of South Africa. Method: A weak supervision learning algorithm was used to perform binary classification. The training of a DNN was performed on 14 features of patient characteristics (Demographic variables, presence of comorbidity, care received upon admission and setting of care), to separate the two classes of data sets: a) severe disease class (a proxy measure of higher severity, which included those who died during admission or were admitted into an intensive care (ICU) or high care unit (HCU)), and b) less severe disease class. Results: The number of Covid-19 hospitalisations was highest in wave 3 for both males and females, and higher in females than males across all 4 waves. The observed difference in COVID-19 hospitalization frequency between men and women was the highest in the 20 - 40-year age group with a ratio of 1:3. There was a higher frequency of COVID-19 hospitalization for hypertension, diabetes, and HIV frequencies across all age groups. Conclusion: This study demonstrated the utility of machine learning for analysing multidimensional sexdisaggregated data to provide accurate, real-time information for public health monitoring of sexdifferences in the Gauteng province.
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    The impact of the covid-19 pandemic on essential public healthcare services in Gauteng province, South Africa
    (2024) Fonka, Cyril Bernsah
    Background: The Covid-19 pandemic like previous outbreaks has the potential to adversely impact essential healthcare services. Even though the Gauteng province was considered the epicentre of the Covid19 outbreak in South Africa, there is no comprehensive assessment of the effect of Covid-19 on the service utilisation, delivery and health outcomes of routine healthcare services in Gauteng province. Aim: To assess the impact of the Covid-19 pandemic on the utilisation, delivery and health outcomes of essential maternal, neonatal and child health (MNCH) services in Gauteng province, South Africa. Methods: This was a mixed methods study. A longitudinal study design was used to analyse data from the District Health Information Software (DHIS). We compared key MNCH indicators in the pre-Covid-19 period (March 2019-February 2020) to corresponding periods during the Covid-19 outbreak (March 2020- February 2021). The differences were analysed using time plots, linear regression, and Interrupted Time Series Analysis (ITSA) in Stata 17.0, at a 5% level of alpha for statistical significance. In-depth interviews were conducted with senior managers in the Gauteng Department of Health (GDoH) using MS Teams, to explore their perspectives on the impact of Covid-19 on routine healthcare services in the province and their recommendations for dealing with future pandemics. The interviews were recorded, transcribed, coded and analysed thematically using MS word 2016. Results: The Covid-19 pandemic disrupted the utilisation of essential MNCH services in the Gauteng province. The disruption was observed in the time trend plots, and then quantified by comparing the indicator means for the 12-month periods before and during Covid-19. The impact was a statistically significant decline in the mean of three indicators: PHC headcount <5 years declined by 77 103.9 visits (p<0.001), ANC 1st visits before 20 weeks decreased by 3.0% (p=0.002) and PNC visits within 6 days decreased by 10.2% (p<0.001) (Error! Reference source not found.). The ITS regression provided a more nuanced analysis. The decrease in PHC headcount t <5 years and PNC visits within 6 days were due to the immediate effect of the March 2020 Covid-19 lockdown which led to a drop in utilisation services. However, the effect on ANC 1st visits before 20 weeks was a continuous decline in utilisation throughout the Covid-19 period (Error! Reference source not found.). Service delivery and outcome indicators were negatively affected though not significantly. There were no significant recoveries and some indicators rather became worse post-lockdown. The nature of the adverse impact of Covid-19 on MNCH indicators was similar across all five districts, although the degree of disruption varied among the districts and services. The decline in service utilisation for PHC headcount <5 years ANC 1st visits before 20 weeks and PNC visits within 6 days was statistically significant in all districts, except for ANC 1st visits in Johannesburg (Error! Reference source not found.). The decline in PHC headcount <5 years was significantly larger in the three metropolitan districts (Johannesburg, Ekurhuleni and Tshwane) compared to the two non-metropolitan districts (Sedibeng and West Rand) (Table 5). ANC 1st visits before 20 weeks significantly declined in the Ekurhuleni, Sedibeng and West Rand districts compared to Johannesburg. While the decrease in PNC visits within 6 days significantly deteriorated in Johannesburg compared to the other four districts (Error! Reference source not found.). Pneumonia fatality <5 years significantly declined in the pooled analysis, in the Tshwane district alone. The majority of the respondents agreed that the Covid-19 pandemic disrupted essential healthcare services but a few disagreed. Several reasons were advanced for the disruption. On the supply side, they included: (i) the reallocation of resources to fighting Covid-19; (ii) healthcare worker shortages due to Covid-19 illness; (iii) healthcare facilities turning away non-Covid-19 patients; and (iv) Covid-19 screening that increased waiting times. On the demand side are; (i) restrictions on movement and limited public transport during the lockdown; (ii) fears of being infected by Covid-19 at health facilities; and (iii) misinterpretation of health information about the availability of non-Covid services. According to the respondents, the disruption of essential healthcare services had significant consequences, particularly for chronic patients, including treatment interruption, loss of follow-up, and death. The ‘catch-up’ plan and technology were used to improve service delivery during Covid-19. Conclusion: The Covid-19 pandemic disrupted the utilisation of essential healthcare services for MNCH. Although service delivery and health outcomes were less impacted, some outcome indicators at district levels went worst. While there were recovery attempts for service delivery like immunisation, some services rather deteriorated post-Covid-19 lockdown. However, there were mixed findings, fewer routine services were not affected by Covid-19. It is important to continuously assess and redress the unintended impacts of outbreaks even while they are occurring. This requires an understanding of the reasons and mechanisms of service disruption from demand and supply perspectives. Critical policies like lockdowns should be a collective decision, implemented without undermining routine services. High-level policymakers must consider addressing geographical variations of an outbreak’s impact on essential healthcare services. Covid19 may have more complex long-term effects, especially for individuals with adverse social determinants. And it may take longer for some healthcare services to fully recover hence, the need for health systems interventions to prioritise the affected services.