Economic Growth and Government Spending Nexus: Empirical Evidence from Lesotho

This study examines the long-run and causal relationship between government spending and economic growth in Lesotho using the ARDL bounds testing procedure for the period 1980 to 2012. Although several studies, have investigated causality between government expenditure and economic growth, none explored differentiating short run and long run causality. The results of our study indicate a stable long-term relationship between government spending and economic growth in Lesotho. However, the Granger causality test shows the direction running from economic growth to government expenditure, confirming Wagner’s Law in Lesotho. In addition, the outcomes of this study fail to support the Keynesian theory. The results highlight the need for policy makers to shift public outlays towards investment in physical infrastructure which will stimulate growth and consequently improve fiscal sustainability as opposed to recurrent expenditure.Keywords: Economic Growth, Fiscal Policy, Cointegration, Causality, Wagner’ La

Axon diameter mapping using diffusion MRI

Axon diameter plays a key role in the function and performance of nerve pathways of the central and peripheral nervous system. Therefore, there is a growing interest in imaging axon diameter non-invasively. One such technique is using diffusion MRI. The purpose of this thesis is to test the feasibility of axon diameter imaging using diffusion MRI. This thesis provides for the first time a thorough experimental framework for evaluation and comparison of diffusion MR sequences, specifically two promising sequences: SDE and OGSE. The thesis involves designing a phantom to determine intrinsic sensitivity of the diffusion sequences to axon diameters. Additional experiments involving an ex vivo monkey brain and a viable rat sciatic nerve are carried out. The comparison of OGSE and SDE sequences across all different experiments demonstrate that OGSE is better than SDE. Diameter estimates of the optimal sequences are compared to the ground truth and the accuracy are found to depend on the gradient strength and SNR. For clinical scanners (G=62 mT/m and SNR>20), diameters of 5 μm are below the resolution limit. At G=300 mT/m and SNR=20, the resolution limit is 2.5 μm within an ex vivo monkey brain, causing overestimated diameters; however, an excellent prediction of the low-high-low diameter trend across the corpus callosum is observed. For G=800 mT/m and SNR=10, the resolution limit is at 2.5-3 μm for a viable rat sciatic nerve and excellent histology match is obtained. This thesis demonstrates that axon diameter imaging using diffusion MRI is possible in the nervous system. The small axons of the central nervous system require strong gradients, which are increasingly becoming more available, and peripheral nervous system have axons that are large enough to be imaged at clinical gradient strengths. This, therefore, opens up possibilities of using axon diameters as biomarkers for neurodegenerative diseases and peripheral nerve regeneration studies

Organisational culture and the integrated chronic diseases management model implementation fidelity in South Africa: a cross-sectional study.

OBJECTIVE: To assess whether organisational culture influences the fidelity of implementation of the Integrated Chronic Disease Management (ICDM) model at primary healthcare (PHC) clinics. DESIGN: A cross-sectional study. SETTING: The ICDM model was introduced in South African clinics to strengthen delivery of care and improve clinical outcomes for patients with chronic conditions, but the determinants of its implementation have not been assessed. PARTICIPANTS: The abbreviated Denison organisational culture (DOC) survey tool was administered to 90 staff members to assess three cultural traits: involvement, consistency and adaptability of six PHC clinics in Dr. Kenneth Kaunda and West Rand (WR) health districts. PRIMARY AND SECONDARY OUTCOME MEASURES: Each cultural trait has three indices with five items, giving a total of 45 items. The items were scored on a Likert scale ranging from one (strongly disagree) to five (strongly agree), and mean scores were calculated for each item, cultural traits and indices. Descriptive statistics were used to describe participants and clinics, and Pearson correlation coefficient to asses association between fidelity and culture. RESULTS: Participants' mean age was 38.8 (SD=10.35) years, and 54.4% (49/90) were nurses. The overall mean score for the DOC was 3.63 (SD=0.58). The involvement (team orientation, empowerment and capability development) cultural trait had the highest (3.71; SD=0.72) mean score, followed by adaptability (external focus) (3.62; SD=0.56) and consistency (3.56; SD=0.63). There were no statistically significant differences in cultural scores between PHC clinics. However, culture scores for all three traits were significantly higher in WR (involvement 3.39 vs 3.84, p=0.011; adaptability 3.40 vs 3.73, p=0.007; consistency 3.34 vs 3.68, p=0.034). CONCLUSION: Leadership intervention is required to purposefully enhance adaptability and consistency cultural traits of clinics to enhance the ICDM model's principles of coordinated, integrated, patient-centred care

The cost and cost implications of implementing the integrated chronic disease management model in South Africa.

BACKGROUND: A cost analysis of implementation of interventions informs budgeting and economic evaluations. OBJECTIVE: To estimate the cost of implementing the integrated chronic disease management (ICDM) model in primary healthcare (PHC) clinics in South Africa. METHODS: Cost data from the provider's perspective were collected in 2019 from four PHC clinics with comparable patient caseloads (except for one). We estimated the costs of implementing the ICDM model current activities for three (facility reorganization, clinical supportive management and assisted self-management) components and additional costs of implementing with enhanced fidelity. Costs were estimated based on budget reviews, interviews with management teams, and other published data. The standard of care activities such as medication were not included in the costing. One-way sensitivity analyses were carried out for key parameters by varying patient caseloads, required infrastructure and staff. Annual ICDM model implementation costs per PHC clinic and per patient per visit are presented in 2019 US dollars. RESULTS: The overall mean annual cost of implementing the ICDM model was $148 446.00 (SD:$65 125.00) per clinic. Current ICDM model activities cost accounted for 84% ($124 345.00) of the annual mean cost, while additional costs for higher fidelity were 16$24 102.00). The mean cost per patient per visit was $6.00 (SD:$0.77); $4.94 (SD:0.70) for current cost and$1.06 (SD:0.33) for additional cost to enhance ICDM model fidelity. For the additional cost, 49% was for facility reorganization, 31% for adherence clubs and 20% for training of nursing staff. In the sensitivity analyses, the major cost drivers were the proportion of effort of assisted self-management staff and the number of patients with chronic diseases receiving care at the clinic. CONCLUSION: Minimal additional cost are required to implement the ICDM model with higher fidelity. Further research on the cost-effectiveness of the ICDM model in middle-income countries is required

Feasibility of Data-Driven, Model-Free Quantitative MRI Protocol Design: Application to Brain and Prostate Diffusion-Relaxation Imaging

Brain; Protocol design; Quantitative MRI (qMRI)Cerebro; Diseño de protocolo; Resonancia magnética cuantitativa (qMRI)Cervell; Disseny del protocol; Ressonància magnètica quantitativa (qMRI)Purpose: We investigate the feasibility of data-driven, model-free quantitative MRI (qMRI) protocol design on in vivo brain and prostate diffusion-relaxation imaging (DRI). Methods: We select subsets of measurements within lengthy pilot scans, without identifying tissue parameters for which to optimise for. We use the “select and retrieve via direct upsampling” (SARDU-Net) algorithm, made of a selector, identifying measurement subsets, and a predictor, estimating fully-sampled signals from the subsets. We implement both using artificial neural networks, which are trained jointly end-to-end. We deploy the algorithm on brain (32 diffusion-/T1-weightings) and prostate (16 diffusion-/T2-weightings) DRI scans acquired on three healthy volunteers on two separate 3T Philips systems each. We used SARDU-Net to identify sub-protocols of fixed size, assessing reproducibility and testing sub-protocols for their potential to inform multi-contrast analyses via the T1-weighted spherical mean diffusion tensor (T1-SMDT, brain) and hybrid multi-dimensional MRI (HM-MRI, prostate) models, for which sub-protocol selection was not optimised explicitly. Results: In both brain and prostate, SARDU-Net identifies sub-protocols that maximise information content in a reproducible manner across training instantiations using a small number of pilot scans. The sub-protocols support T1-SMDT and HM-MRI multi-contrast modelling for which they were not optimised explicitly, providing signal quality-of-fit in the top 5% against extensive sub-protocol comparisons. Conclusions: Identifying economical but informative qMRI protocols from subsets of rich pilot scans is feasible and potentially useful in acquisition-time-sensitive applications in which there is not a qMRI model of choice. SARDU-Net is demonstrated to be a robust algorithm for data-driven, model-free protocol design.This project was funded by the Engineering and Physical Sciences Research Council (EPSRC EP/R006032/1, M020533/1, G007748, I027084, N018702). This project has received funding under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 634541 and 666992, and from: Rosetrees Trust (United Kingdom, funding FG); Prostate Cancer United Kingdom Targeted Call 2014 (Translational Research St.2, project reference PG14-018-TR2); Cancer Research United Kingdom grant ref. A21099; Spinal Research (United Kingdom), Wings for Life (Austria), Craig H. Neilsen Foundation (United States) for jointly funding the INSPIRED study; Wings for Life (#169111); United Kingdom Multiple Sclerosis Society (grants 892/08 and 77/2017); the Department of Health’s National Institute for Health Research (NIHR) Biomedical Research Centres and UCLH NIHR Biomedical Research Centre; Champalimaud Centre for the Unknown, Lisbon (Portugal); European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 101003390. FG is currently supported by the investigator-initiated PREdICT study at the Vall d’Hebron Institute of Oncology (Barcelona), funded by AstraZeneca and CRIS Cancer Foundation

Conversation analysis

Peer reviewe

Process evaluation of fidelity and costs of implementing the Integrated Chronic Disease Management model in South Africa: mixed methods study protocol.

INTRODUCTION: The South African Department of Health has developed and implemented the Integrated Chronic Disease Management (ICDM) model to respond to the increased utilisation of primary healthcare services due to a surge of non-communicable diseases coexisting with a high prevalence of communicable diseases. However, some of the expected outcomes on implementing the ICDM model have not been achieved. The aims of this study are to assess if the observed suboptimal outcomes of the ICDM model implementation are due to lack of fidelity to the ICDM model, to examine the contextual factors associated with the implementation fidelity and to calculate implementation costs. METHODS AND ANALYSIS: A process evaluation, mixed methods study in 16 pilot clinics from two health districts to assess the degree of fidelity to four major components of the ICDM model. Activity scores will be summed per component and overall fidelity score will be calculated by summing the various component scores and compared between components, facilities and districts. The association between contextual factors and the degree of fidelity will be asseseed by multivariate analysis, individual and team characteristics, facility features and organisational culture indicators will be included in the regression. Health system financial and economic costs of implementing the four components of the ICDM model will be calculated using an ingredient approach. The unit of implementation costs will be by activity of each of the major components of the ICDM model. Sensitivity analysis will be carried out using clinic size, degree of fidelity and different inflation situations. ETHICS AND DISSEMINATION: The protocol has been approved by the University of Cape Town and University of the Witwatersrand Human Research ethics committees. The results of the study will be shared with the Department of Health, participating health facilities and through scientific publications and conference presentations

A mixed methods approach to exploring the moderating factors of implementation fidelity of the integrated chronic disease management model in South Africa

Abstract: Background: Chronic care models like the Integrated Chronic Disease Management (ICDM) model strive to improve the efficiency and quality of care for patients with chronic diseases. However, there is a dearth of studies assessing the moderating factors of fidelity during the implementation of the ICDM model. The aim of this study is to assess moderating factors of implementation fidelity of the ICDM model. Methods: This was a cross-sectional mixed method study conducted in two health districts in South Africa. The process evaluation and implementation fidelity frameworks were used to guide the assessment of moderating factors influencing implementation fidelity of the ICDM model. We interviewed 30 purposively selected healthcare workers from four facilities (15 from each of the two facilities with lower and higher levels of implementation fidelity of the ICDM model). Data on facility characteristics were collected by observation and interviews. Linear regression and descriptive statistics were used to analyse quantitative data while qualitative data were analysed thematically. Results: The median age of participants was 36.5 (IQR: 30.8–45.5) years, and they had been in their roles for a median of 4.0 (IQR: 1.0–7.3) years. The moderating factors of implementation fidelity of the ICDM model were the existence of facilitation strategies (training and clinical mentorship); intervention complexity (healthcare worker, time and space integration); and participant responsiveness (observing operational efficiencies, compliance of patients and staff attitudes). One feature of the ICDM model that seemingly compromised fidelity was the inclusion of tuberculosis patients in the same stream (waiting areas, consultation rooms) as other patients with non-communicable diseases and those with HIV/AIDS with no clear infection control guidelines. Participants also suggested that poor adherence to any one component of the ICDM model affected the implementation of the other components. Contextual factors that affected fidelity included supply chain management, infrastructure, adequate staff, and balanced patient caseloads. Conclusion: There are multiple (context, participant responsiveness, intervention complexity and facilitation strategies) interrelated moderating factors influencing implementation fidelity of the ICDM model. Augmenting facilitation strategies (training and clinical mentorship) could further improve the degree of fidelity during the implementation of the ICDM model

Tuberculosis patients at the human-animal interface: Potential zooanthroponotic and zoonotic transmission

Background Human-to-animal transmission of M. tuberculosis (Mtb) is reported in South Africa but there is a paucity of epidemiological data. The aim of this One Health manuscript is to describe zooanthroponotic exposure of domestic animals to TB patients, virtually all of whom had laboratory confirmed pulmonary Mtb disease. Methods This cross-sectional study was nested within two TB contact tracing studies and collected data from 2017 to 2019. TB index patients and their households in three provinces of South Africa were recruited. A questionnaire was administered to households, assessing type and number of animals owned, degree of exposure of animals to humans, and veterinary consultations. For this analysis, we compared descriptive variables by animal-keeping status (animal-keeping vs non-animal keeping households), calculated the chi square and respective p-values. Results We visited 1766 households with at least one confirmed case of TB, 33% (587/1766) had livestock or companion animals. Of non-animal-owning households, 2% (27/1161) cared for other community members' livestock. Few (16%, 92/587) households kept animals in their dwelling overnight, while 45% (266/587) kept animals outside the home, but within 10 m of where people slept and ate. Most (81%, 478/587) of people in animal-owning households were willing for their animal/s to have a TB skin test, but <1% (5/587) of animals had been skin-tested; 4% (24/587) of animal-owning households had a veterinary consultation in the past six months, and 5% (31/587) reported one of their animals dying from natural causes in the prior six months. Conclusion Our survey suggests that a high proportion of patients with TB live in settings facilitating close contact with domestic animal species with known susceptibility to Mtb. There is a substantial exposure of household animals to patients with TB and therefore risk of both transmission to, and spillback from animals to humans