Medicine (RMH) - Theses
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ItemModelling Tuberculosis in Ethiopia: Spatiotemporal Transmission Dynamics and Effects of Public Health Interventions( 2018)Tuberculosis (TB) is now the world’s leading infectious killer with an estimated 10million cases and 1.6 million deaths in 2016. A small number of countries bear the majority of the burden of disease, with two-thirds of cases occurring in only seven countries. TB transmission occurs in both households and the local community, leading to focal disease hotspots which perpetuate TB spread within and across community groups. Integrating spatial analysis with mathematical transmission dynamic models can help in evaluating the role of these hotspots in the spread of TB and understanding the potential impact of geographically targeted interventions. The first part of this thesis evaluates whether TB exhibits spatial heterogeneity in rural and remote regions of Ethiopia using data from all TB patients treated in a remote administrative region of the country. This study demonstrated considerable spatial heterogeneity in TB distribution in this resource-limited setting. However, most of these heterogeneities were accounted for by health facility availability, implying differential case detection between areas with better and poorer access to health care. Thus, this Chapter cautions that spatial analysis of TB and the identification of geographical hotspots using programmatic data alone can be misleading, as it may be strongly influenced by undetected cases, which is in turn dependent on local programmatic performance. Building on the findings outlined above, Chapter three presents a systematic review of methods used in published spatial analyses of TB. From this review, this Chapter elucidates limitations in the current approaches to spatial analysis of TB. Of particular importance is the consistent failure to account for unreported or undetected cases, despite notification data being used in 95 percent of the reviewed studies. The Chapter also describes methodological flaws to many of the studies, in particular the use of conventional regression analysis to draw spatial conclusions. In addition, most spatial analyses of TB distribution used residential information to define the location of patients, which potentially understates the importance of other community settings, despite more than 80% of all transmission events occurring outside households. The study in Chapter 4 proposes a method to address the limitations outlined in the previous chapters – particularly the lack of methods to account for undetected cases. The model estimates both incidence and case detection rates simultaneously across space and time, providing a useful platform for regularly tracking spatial patterns and temporal trends. In addition, this technique is general and can be applied to any disease in any setting. Applied to the Ethiopian setting, this model identifies previously unrecognized areas of high TB burden in locations with no available health care facilities. With the aim of quantifying the role of TB hotspots in community transmission as well as evaluating the potential impact of targeting spatial hotspots, Chapter 5 utilises incidence data generated by the novel method described above to identify spatial TB hotspots. At this point, the thesis constructs spatially structured mathematical models and quantifies the extent to which these hotspots account for the spatial spread of TB. Findings from this work suggest that TB transmission in the same study region in rural Ethiopia is localised and the role of spatial hotspots in the spatial spread is limited, although their impact is considerable in adjacent locations due to very high relative incidence in the hotspot compared to the other regions. Finally, Chapter 6 uses the same model introduced in Chapter 5 to evaluate the impact of various TB intervention strategies before concluding the thesis. Overall, this thesis advances current approaches to spatial analysis and provides a means to account for the problem of undetected cases. It also provides a platform to estimate both incidence and case detection rate simultaneously, and hence could provide as an alternative approach to the spatial interpretation of TB epidemiology. This is of particular importance to high endemic settings, where considerable number of TB cases are missed, and case notification is biased to areas with better access to health care. Importantly, the study also concludes that the impact of spatial TB hotspots on the spatial spread of disease in remote regions of Ethiopia is limited and transmission is predominantly locally driven. Hence, interventions strategies that are spatially targeted may not achieve anticipated outcomes, although the overall effect of these interventions remains considerable due to extremely high incidence in the hotspot regions.
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ItemUsing mathematical modelling to challenge accepted methods and paradigms of tuberculosis control and transmission( 2018)Tuberculosis (TB) represents a major public health issue at the global level. Despite the availability of vaccines and treatments, TB still kills around 1.6 million persons each year due to a combination of unresolved challenges. Firstly, around 40% of diseased individuals are never identified and can therefore not be provided with adequate care. A second substantial challenge is the extremely high prevalence of latent tuberculosis infection (LTBI), which serves as a large reservoir of future disease that is difficult to control. Furthermore, the emergence of drug-resistant TB (DR-TB) has hampered the progress made by TB control in the last decades and required novel strategies to be adopted. Optimal approaches to address these challenges are hampered by substantial knowledge gaps. The lack of a comprehensive epidemiological understanding of TB has also resulted in today’s TB control relying heavily on strong assumptions or preconceived opinions, which are not necessarily supported by evidence. In this thesis, I used mathematical modelling to challenge several of these accepted paradigms. First, this thesis presents a simple model incorporating epidemiological and programmatic characteristics used to quantify the respective contributions of the different pathways leading to DR-TB at re-treatment around the world. This exercise identified failure to detect DR-TB at first presentation as the leading source of DR-TB at re-treatment. This challenges the accepted paradigm that DR-TB results mainly from poor treatment adherence during treatment of drug-susceptible patients. Important geographical heterogeneity was also observed in the results, and so a web-based interface was built to allow the model to be applied immediately to any epidemiological setting. Next, this thesis presents a novel exploration of the relationship between TB incidence and the effectiveness of preventive treatment (PT). Although it is widely accepted that using PT would be less efficient in high-burden settings, the exploration suggests that PT would yield optimal efficiency where TB incidence is as high as 700 new cases/100,000/year. To improve TB modelling methods, this thesis next presents an evaluation of the existing approaches used to simulate the transition from LTBI to active disease. This was done by comparing the reactivation dynamics produced by different model structures to those empirically observed in contacts of infectious TB patients. This exercise demonstrated that two latency compartments are needed to replicate the TB reactivation dynamics in a compartmental model. It further highlighted that the usual cut-off of two or five years used to distinguish late from early latency should be revised to a much shorter duration. Finally, a novel modelling approach combining country-specific social mixing data with time-variant programmatic parameters within a TB agent-based model is presented in this thesis. The newly built tool was used to detail the profile of Mycobacterium tuberculosis (M.tb) transmission and TB burden in the five highest TB burden countries (India, Indonesia, China, the Philippines and Pakistan). Findings include the unexpectedly high contribution of adolescents and young adults to M.tb transmission. This study also provides estimates of the age-specific size of the latent infection pool, along with the age-specific risk that this infection reservoir represents in terms of future disease.
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ItemMathematical modelling for programmatic responses to tuberculosis in the Asia-Pacific( 2016)Despite being a treatable disease, tuberculosis (TB) has not yet been controlled globally, and the burden in Australia’s region remains huge, with two Asia-Pacific countries, India and China, constituting one third of cases worldwide. Moreover, several highly endemic regional hotspots exist and multidrug-resistant TB (MDR-TB) threatens to derail control efforts. The epidemic in the Asia-Pacific region differs markedly from other parts of the world, as transmission is not primarily driven by HIV-coinfection as it is in sub-Saharan Africa, nor by transmission in conjugate settings (such as prisons and hospitals) as in the former Soviet states. Mathematical modelling can help to understand the reasons for our failure to achieve control and to better direct programmatic resources. This thesis first presents the construction of a dynamic ten-compartment model to simulate TB transmission in highly endemic regions of the Asia-Pacific and describes its general characteristics. Findings include the importance of reinfection during late latency, the contribution of community transmission to MDR-TB burden, the importance of properly addressing MDR-TB despite a possible fitness cost and the need to model partially protective vaccines. Next, strategies for TB control were modelled in Western Province, Papua New Guinea, a region characterised by high burden, high proportions of MDR-TB and poor-quality programmatic data. After calibrating to local conditions, the model was used to simulate five programmatic responses to TB and Bayesian inference was employed to explore the uncertainty range around plausible outcomes. The model was then used as the basis for participation in an international collaboration to consider whether the post-2015 Sustainable Development Goals (SDGs) for TB are achievable with current tools. Eleven leading global modelling groups were invited to participate in the multi-modelling exercise to simulate six “ambitious but feasible” interventions for India, China and South Africa. The previously developed model was elaborated to incorporate smear-negative and extrapulmonary TB, initial default and misdiagnosis of MDR-TB, and was then calibrated to each country to capture local TB dynamics before applying interventions. Key conclusions include the small impacts of improved care quality and molecular diagnostics but greater improvements resulting from expansion of access to care, and that active case finding may significantly reduce disease burden. As most targets were not met under the modelled scenarios, future technological advances, such as new treatments and vaccines, are likely to be required to achieve the ambitious rates of decline envisaged in the post-2015 agenda. To improve understanding of TB dynamics, this thesis explores the latent period between infection and active disease. Using Victorian TB Program data, individuals recently infected with M. tuberculosis were linked to subsequently notified active cases, and the resulting dataset was used to perform a survival analysis on the outcome of progression to active disease. I then imputed censorship to account for effective loss to follow-up through death, migration out of the surveillance region and preventive treatment. Results show the five-year risk of disease is 11-18%, several-fold higher than commonly accepted estimates. These revised estimates have important implications for programmatic responses, individual patients and structuring and parameterising compartmental models.
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ItemHIV in Victoria's African communities: reducing risks and improving care( 2013)The acquired immunodeficiency syndrome caused by the human immunodeficiency virus is an important issue for Australia’s African communities. As in other industrialised countries, African immigrants are over-represented in Australia’s HIV epidemic, diagnosed late and endure social isolation after diagnosis, but focused responses, applied without understanding local HIV epidemiology and social context, risk intensifying stigma against African communities and African Australian people living with HIV in Australia. This study explored the social epidemiology and clinical features of HIV in Victoria’s African communities, collecting data from national and Victorian HIV surveillance databases, a clinical case series of African-born HIV patients and a qualitative inquiry with several African communities. Diverse geographical, biological, psychosocial and structural factors influenced exposure, diagnosis, clinical features and experience of living with HIV. Most exposure occurred in Africa, prior to migration, through heterosexual sex. Some occurred after migration, in Australia and abroad, through heterosexual sex and sex between men. Low self-perceived risk and lack of awareness of HIV in Australia contributed to exposure and delayed diagnosis. HIV was understood as a deadly, highly contagious “African” disease, posing little threat in Australia, being one of several intersecting challenges to the wellbeing and cohesion of African communities during resettlement. Understanding of HIV was based largely on experience in Africa and the process of HIV screening during immigration. HIV-related stigma, based on risk stereotypes of sexual immorality and fear of contagion and death, was the major barrier to social support and information. Key clinical issues for African-born PLHIV included high prevalence of TB and viral hepatitis. HIV treatment uptake was high and response was good. HIV exposure via sex between men led to HIV-1 subtype B infection; those with heterosexual or other exposure carried various non-B subtypes. African communities actively participated in the study leading to greater engagement in Victorian and national HIV responses. Study results provided insights into HIV epidemiology and clinical features in Victoria’s African communities and informed a conceptual framework that should further the understanding of HIV epidemiology in mobile and marginalised populations.
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ItemActive approaches to latent tuberculosis: modelling public health strategies towards eliminating tuberculosis in Australia( 2013)The considerable majority of tuberculosis (TB) infections in Australia occur following reactivation in immigrants from high-prevalence countries. Public health strategies aimed at preventing reactivation in immigrants may be valuable in reducing TB incidence towards the international consensus goal of <1 case/million people by 2050. This thesis clarifies the risk of TB disease in immigrant cohorts, and develops a mathematical model of latent TB to evaluate intervention strategies. Modelling demonstrates that the current reservoir of people with latent infection in Australia is sufficiently large that even optimal immigration-related strategies would be unable to eradicate TB, although considerable reduction may be achieved.