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The Institute for Global Health and Development

Permanent URI for this collectionhttps://eresearch.qmu.ac.uk/handle/20.500.12289/9

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Author: search.filters.author.Karat, Aaron S.Subject: search.filters.subject.Health Systems

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    Modelling the effect of infection prevention and control measures on rate of Mycobacterium tuberculosis transmission to clinic attendees in primary health clinics in South Africa
    (BMJ, 2021-10-25) McCreesh, Nicky; Karat, Aaron S.; Baisley, Kathy; Diaconu, Karin; Bozzani, Fiammetta; Govender, Indira; Beckwith, Peter; Yates, Tom A.; Deol, Arminder K.; Houben, Rein M. G. J.; Kielmann, Karina; White, Richard G.; Grant, Alison D.
    Background Elevated rates of tuberculosis in health care workers demonstrate the high rate of Mycobacterium tuberculosis (Mtb) transmission in health facilities in high burden settings. In the context of a project taking a whole systems approach to tuberculosis infection prevention and control (IPC), we aimed to evaluate the potential impact of conventional and novel IPC measures on Mtb transmission to patients and other clinic attendees.
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    Health system determinants of tuberculosis mortality in South Africa: A causal loop model
    (BMC, 2021-04-26) Osman, Muhammad; Karat, Aaron S.; Khan, Munira; Meehan, Sue-Ann; von Delft, Arne; Brey, Zameer; Charalambous, Salome; Hesseling, Anneke C.; Naidoo, Pren; Loveday, Marian
    Background: Tuberculosis (TB) is a major public health concern in South Africa and TB-related mortality remains unacceptably high. Numerous clinical studies have examined the direct causes of TB-related mortality, but its wider, systemic drivers are less well understood. Applying systems thinking, we aimed to identify factors underlying TB mortality in South Africa and describe their relationships. At a meeting organised by the ‘Optimising TB Treatment Outcomes’ task team of the National TB Think Tank, we drew on the wide expertise of attendees to identify factors underlying TB mortality in South Africa. We generated a causal loop diagram to illustrate how these factors relate to each other. Results: Meeting attendees identified nine key variables: three ‘drivers’ (adequacy & availability of tools, implementation of guidelines, and the burden of bureaucracy); three ‘links’ (integration of health services, integration of data systems, and utilisation of prevention strategies); and three ‘outcomes’ (accessibility of services, patient empowerment, and socio-economic status). Through the development and refinement of the causal loop diagram, additional explanatory and linking variables were added and three important reinforcing loops identified. Loop 1, ‘Leadership and management for outcomes’ illustrated that poor leadership led to increased bureaucracy and reduced the accessibility of TB services, which increased TB-related mortality and reinforced poor leadership through patient empowerment. Loop 2, ‘Prevention and structural determinants’ describes the complex reinforcing loop between socio-economic status, patient empowerment, the poor uptake of TB and HIV prevention strategies and increasing TB mortality. Loop 3, ‘System capacity’ describes how fragmented leadership and limited resources compromise the workforce and the performance and accessibility of TB services, and how this negatively affects the demand for higher levels of stewardship. Conclusions: Strengthening leadership, reducing bureaucracy, improving integration across all levels of the system, increasing health care worker support, and using windows of opportunity to target points of leverage within the South African health system are needed to both strengthen the system and reduce TB mortality. Further refinement of this model may allow for the identification of additional areas of intervention.