Methods matter: computational modelling in public health policy and planning

This work is aimed at understanding and unifying information on epidemiological modelling methods and how those methods relate to public policy addressing human health, specifically in the context of infectious disease prevention, pandemic planning, and health behaviour change. This thesis employs multiple qualitative and quantitative methods, and presents as a manuscript of several individual, data-driven projects that are combined in a narrative arc. The first chapter introduces the scope and complexity of this interdisciplinary undertaking, describing several topical intersections of importance. The second chapter begins the presentation of original data, and describes in detail two exercises in computational epidemiological modelling pertinent to pandemic influenza planning and policy, and progresses in the next chapter to present additional original data on how the confidence of the public in modelling methodology may have an effect on their planned health behaviour change as recommended in public health policy. The thesis narrative continues in the final data-driven chapter to describe how health policymakers use modelling methods and scientific evidence to inform and construct health policies for the prevention of infectious diseases, and concludes with a narrative chapter that evaluates the breadth of this data and recommends strategies for the optimal use of modelling methodologies when informing public health policy in applied public health scenarios.

Estimation of whole body muscle, adipose/fat mass, validation in health and during weight loss. Development of prediction equations using MRI as reference method

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.

Endemic zoonoses: a one health approach

Endemic zoonotic diseases remain a serious but poorly recognised problem in affected communities in developing countries. Despite the overall burden of zoonoses on human and animal health, information about their impacts in endemic settings is lacking and most of these diseases are continuously being neglected. The non-specific clinical presentation of these diseases has been identified as a major challenge in their identification (even with good laboratory diagnosis), and control. The signs and symptoms in animals and humans respectively, are easily confused with other non-zoonotic diseases, leading to widespread misdiagnosis in areas where diagnostic capacity is limited. The communities that are mostly affected by these diseases live in close proximity with their animals which they depend on for livelihood, which further complicates the understanding of the epidemiology of zoonoses. This thesis reviewed the pattern of reporting of zoonotic pathogens that cause febrile illness in malaria endemic countries, and evaluates the recognition of animal associations among other risk factors in the transmission and management of zoonoses. The findings of the review chapter were further investigated through a laboratory study of risk factors for bovine leptospirosis, and exposure patterns of livestock coxiellosis in the subsequent chapters. A review was undertaken on 840 articles that were part of a bigger review of zoonotic pathogens that cause human fever. The review process involves three main steps: filtering and reference classification, identification of abstracts that describe risk factors, and data extraction and summary analysis of data. Abstracts of the 840 references were transferred into a Microsoft excel spread sheet, where several subsets of abstracts were generated using excel filters and text searches to classify the content of each abstract. Data was then extracted and summarised to describe geographical patterns of the pathogens reported, and determine the frequency animal related risk factors were considered among studies that investigated risk factors for zoonotic pathogen transmission. Subsequently, a seroprevalence study of bovine leptospirosis in northern Tanzania was undertaken in the second chapter of this thesis. The study involved screening of serum samples, which were obtained from an abattoir survey and cross-sectional study (Bacterial Zoonoses Project), for antibodies against Leptospira serovar Hardjo. The data were analysed using generalised linear mixed models (GLMMs), to identify risk factors for cattle infection. The final chapter was the analysis of Q fever data, which were also obtained from the Bacterial Zoonoses Project, to determine exposure patterns across livestock species using generalized linear mixed models (GLMMs). Leptospira spp. (10.8%, 90/840) and Rickettsia spp. (10.7%, 86/840) were identified as the most frequently reported zoonotic pathogens that cause febrile illness, while Rabies virus (0.4%, 3/840) and Francisella spp. (0.1%, 1/840) were least reported, across malaria endemic countries. The majority of the pathogens were reported in Asia, and the frequency of reporting seems to be higher in areas where outbreaks are mostly reported. It was also observed that animal related risk factors are not often considered among other risk factors for zoonotic pathogens that cause human fever in malaria endemic countries. The seroprevalence study indicated that Leptospira serovar Hardjo is widespread in cattle population in northern Tanzania, and animal husbandry systems and age are the two most important risk factors that influence seroprevalence. Cattle in the pastoral systems and adult cattle were significantly more likely to be seropositive compared to non-pastoral and young animals respectively, while there was no significant effect of cattle breed or sex. Exposure patterns of Coxiella burnetii appear different for each livestock species. While most risk factors were identified for goats (such as animal husbandry systems, age and sex) and sheep (animal husbandry systems and sex), there were none for cattle. In addition, there was no evidence of a significant influence of mixed livestock-keeping on animal coxiellosis. Zoonotic agents that cause human fever are common in developing countries. The role of animals in the transmission of zoonotic pathogens that cause febrile illness is not fully recognised and appreciated. Since Leptospira spp. and C. burnetii are among the most frequently reported pathogens that cause human fever across malaria endemic countries, and are also prevalent in livestock population, control and preventive measures that recognise animals as source of infection would be very important especially in livestock-keeping communities where people live in close proximity with their animals.

Antiplatelet therapy and clinical outcomes in cardiovascular diseases

Cardiovascular diseases (CVD) is a leading cause of death in the world. Despite effective treatment regimens for ischaemic heart disease (IHD) and ischaemic stroke, mortality and recurrence rates remain high. Antiplatelet therapy is on effective treatment and reduces the risk of recurrent heart attack and stroke. Nevertheless, there are patients who stopped or interrupted their antiplatelet therapy for certain reasons or some patients may be resistant or poor responders to antiplatelet therapy. Furthermore, there is evidence of rebound effect in platelet activity after antiplatelet cessation and this may associate with increased risk of cardiovascular event. This thesis is divided into five main chapters (chapters 3 to 7) which attempt to provide data to help resolve the uncertainty. Chapter 1 highlights the background of cardiovascular diseases and the global burden of cardiovascular and cerebrovascular diseases. The metabolism of platelets, antiplatelet therapy and current antiplatelet therapy guidelines are described, followed by discussion of the risk of cardiovascular event and changes in antiplatelet therapy. Chapter 2 describes the data source from Virtual International Stroke Trial Archive (VISTA) and National Health Service Greater Glasgow and Clyde (NHSGGC) Safe Haven, followed by definition of outcome measures. In chapter 3, Virtual International Stroke Trial Archive (VISTA) data was examined to test whether continue with the same antiplatelet therapy or changing to a new antiplatelet regimen reduces the risk of subsequent events in patients who experience a stroke whilst taking antiplatelet therapy. The findings indicate that subjects who switch to a new antiplatelet regimen after stroke did not have a lower early recurrence rate than subjects who continued with the same antiplatelet therapy. Observations on bleeding complications were similar in both groups. However, changing antiplatelet regimen after stroke was associated with more favourable functional outcome across a full scale modified Rankin Scale (mRS) at 90 days. In chapter 4, association between early or later initiation of antiplatelet with a recurrent ischaemic stroke and bleeding complications was assessed using VISTA data. The findings indicate that there was no association between a recurrent ischaemic stroke and timing of initiation of antiplatelet drug after stroke. However, early initiation was associated with increased risk of bleeding. In terms of functional outcomes, this study demonstrated that the mid-time and late initiation of antiplatelet therapy after acute stroke are associated with better functional outcomes compared with early initiation. In chapter 5, a nested case-control study was performed to explore the rate of antiplatelet cessation and interruption in a sample of patients with recent ischaemic stroke and to assess the risk of cardiovascular events associated with cessation and interruption of antiplatelet. It was found that there was no increased risk of cardiovascular event among patients who had early cessation or interrupted/stopped antiplatelet therapy within 90 days following acute ischaemic stroke. In chapter 6, the incidence and predictors of cardiovascular events after DAPT cessation were evaluated. The incidence of cardiovascular event while taking DAPT and following discontinuation of DAPT was 15.7% and 16.7% respectively. This study found that increasing age was associated with an increased risk of cardiovascular event, whereas, revascularization-treated patients and longer duration of DAPT, were each associated with a decreased risk. The duration of DAPT six months and less was associated a significantly higher risk for cardiovascular event. In chapter 7, an untargeted metabolomics analysis was performed while on DAPT (aspirin plus ticagrelor) and once they stopped ticagrelor to identify metabolite changes associated with cardiovascular events after stopping DAPT. Ten ACS patients were recruited in this study and data were analysed for seven patients. Three hundred eleven putative metabolites were identified. This study found 16 putative metabolites significantly altered following ticagrelor cessation. Of these, seven metabolites were from lipid pathway and down-regulated some up to 3-fold. On the other hand, adenosine, from nucleotide metabolism was upregulated up to 2.6-fold. It concluded that there are changes in numerous pathways following DAPT discontinuation and whether these changes differ in patients who have cardiovascular event after stopping DAPT warrant further investigation. In chapter 8, a summary of the findings of this thesis are presented as well as the future directions of research in this area.