This multidisciplinary project adopted a 'whole systems' approach using methods from epidemiology, anthropology, and health systems research (Systems dynamic modelling) to understand the context, practice, and the potential for effective implementation of IPC for TB in South Africa. This project was conducted over four years (2017–2021) and had three stages: 1) observe & measure (data collection), 2) combine & design (system dynamics workshops) 3) model & cost (mathematical and economic modelling). These three phases of the project addressed seven research question. Research question 1 described the policy and systems context by looking at how South African policies on IPC for TB have evolved and been implemented. We spoke with members of civil society, and policymakers. For Research question 2, which related to the epidemiological context, we estimated how much TB transmission happens in clinics compared to other community locations. We estimated how many adults attending clinics had active TB and/or TB symptoms. We also estimated the risk of contact between people with infectious TB and other clients within clinics, and separately estimated, among community members, the frequency of social contacts in clinics as compared to other settings where people meet. Research questions 3 and 4 examined the effect of clinic design and working practices on transmission and looked to understand healthcare workers perceptions of risk and responsibility. We used structured and in-depth qualitative methods to document IPC practice in health clinics considering the role of clinic design, organisation of care, work practices, as well as health care worker, manager, and patient ideas about risk and responsibility in IPC. We spoke to patients, health workers, as well as specialists in primary care, IPC, and the built environment. The collected data enabled us to calculate the ventilation of waiting areas and consultation rooms; and we examined how people moved around clinics and where they spent time. Research question 5 involved the designing of whole-systems interventions to improve TB infection prevention and control. We used system dynamics modelling (SDM) to bring our data together and design interventions. With researchers, patient and union representatives, practitioners from clinics and hospitals, and policymakers from District, Provincial, and National Departments of Health, we developed ‘models’ (diagrams) of the system and identified targets for interventions to reduce Mtb transmission. Our collaborators prioritised interventions based on how likely they were to be effective and how easily they could be implemented. Research questions 6 and 7 involved synthesis of all these data to develop a package of health systems interventions to reduce DR-TB transmission in clinics, adapted to the constraints and opportunities of the South African health system. We used mathematical and economic modelling to project the potential impact of interrupting clinic-based transmission on community-wide TB incidence, and the consequent economic benefits for health systems and households.Drug-resistant tuberculosis (DR-TB) is a major threat to global public health, causing one in four estimated worldwide deaths attributable to antimicrobial resistance. In South Africa, DR-TB transmission within clinics, particularly to HIV-positive people, is well-documented. Most TB transmission happens before people start TB treatment, but DR-TB transmission may continue after treatment is started, raising concern as DR-TB services in South Africa are decentralised from hospitals to primary care clinics. The extent to which exposure in clinics, as compared to other community settings, drives ongoing transmission of DR-TB requires better definition, to mobilise necessary resources to address this problem. Guidelines for clinics concerning infection prevention and control (IPC) measures to reduce DR-TB transmission are widely available. There is ample evidence that recommended measures are not put into practice, but limited understanding of the reasons. A comprehensive approach to understanding barriers to implementation is required to design effective IPC interventions for DR-TB. Failure of IPC measures for DR-TB is often attributed to health care workers (HCW) failure to adhere to guidelines. Cognisant that HCW are part of a health system with specific organizational features, we examine how the health system as a whole supports IPC measures. We investigate the biological, environmental, infrastructural, and social dynamics of DR-TB transmission in clinics in two provinces in South Africa (KwaZulu-Natal and Western Cape). Our aim is to provide evidence for effective ways to improve IPC for DR-TB, addressing not only behavioural factors, but also the ways in which clinic space, infrastructure, work and patient flows are managed, and a rights-based occupational health ethos might be cultivated. Our innovative approach brings together a team from several scientific disciplines. Taking a 'whole systems' approach, we will use methods from epidemiology, anthropology, and health systems research to understand the context, practice, and the potential for effective implementation of IPC for DR-TB. We will examine how South African policies on IPC for TB have evolved and been implemented. The epidemiological context will be defined by estimating how much DR-TB transmission happens in clinics compared to other community locations. We will estimate the risk of contact between people with infectious DR-TB and other clients within clinics, and separately estimate, among community members, the frequency of social contacts in clinics as compared to other settings where people meet. We will use structured and in-depth qualitative methods to document IPC practice in health clinics: the role of clinic design, organisation of care, work practices, as well as HCW, manager, and patient ideas about risk and responsibility in IPC. In collaboration with key stakeholders, we will use health systems mapping and model-building exercises to visually document the environmental and organizational barriers and enablers to implementing optimal DR-TB IPC. Synthesis of all these data will lead to development of a package of health systems interventions to reduce DR-TB transmission in clinics, adapted to the constraints and opportunities of the South African health system. We will use mathematical and economic modelling to project the potential impact of interrupting clinic-based transmission on community-wide TB incidence, and the consequent economic benefits for health systems and households. In addition to significant academic, policy and programme-relevant outputs, the project will create an interdisciplinary platform for future implementation and evaluation of health systems strategies to improve IPC. It will stimulate discussion between researchers working on DR-TB and other drug-resistant infections, and foster greater public awareness of the importance of systems that minimize the risk of airborne infections in health facilities.

This study was conducted over four years (2017–2021) and had three stages: 1) observe & measure (data collection), 2) combine & design (system dynamics workshops), and 3) model & cost (mathematical and economic modelling). All data collection was done before the start of the COVID-19 pandemic. Data collection. For the policy setting we conducted in-depth interviews with policy actors (health system, researchers, activists) at various levels of the health system, from local clinics to global policymaking bodies as well as specialists in primary care, IPC, and the built environment. The prevalence of TB survey involved randomly selecting adults (≥18 years) attending 2 primary healthcare clinics who were interviewed and requested to give sputum for mycobacterial culture. For the clinic setting we used structured and unstructured observations and formal interviews and focus group discussions and informal conversations with clinic managers, health care workers, and patients. Patient flow was mapped in the clinics - unique barcodes were used to track attendees’ movements in 11 clinics in two provinces, multiple imputation was used to estimate missing arrival and departure times, and mixed-effects linear regression to examine associations with visit duration . Clinic ventilation was measured in clinic spaces using a tracer-gas release method.