published_or_final_version / Community Medicine / Master / Master of Public Health

Introduction Tuberculosis (TB) remains a major global health problem. Globally, the incidence and mortality of TB were 122 and 18 per 100 000 population in 2012, while TB notification and death rate were 67.9 and 2.8 per 100 000 population in Hong Kong. With improvement in diagnosis and case finding, the TB incidence, prevalence and mortality rate were descending. Also, TB treatment success and detection rates were increasing. TB is still an infectious disease leading to considerable burden in Hong Kong. Many studies have found seasonal pattern of TB in other countries or cities. However, the reason of seasonality of tuberculosis is still remain unknown. This dissertation assessed yearly trends and seasonal variability of tuberculosis and the potential impact of meteorological variables on seasonality of TB in Hong Kong from 2001 to 2012. The finding could help us to better understand the pattern and the factors associated with seasonality of TB, and to inform future TB research and health policy strategies for TB control. Method Firstly, we did a literature review of seasonality of TB. Then we assessed the disease burden, trends and seasonality of TB. The data of TB age-specific and sex-specific notifications and notification rate, TB disease form-specific notifications and meteorological observations are mainly aggregated sources downloaded from public websites. Descriptive analysis methods were used to assess the characteristics of disease burden of TB and analytical analysis methods were used to assess the trends of TB age-specific, sex-specific notification rates and disease form-specific TB notifications in Hong Kong from 2001 to 2012. We assessed the seasonality of TB in Hong Kong from 2001 to 2012 with a Serfling model. Lastly, we used linear regression model to assess the potential impact of the meteorological predictors on the seasonality. Results The mean TB notification rate and death rate were 83.4 and 3.6 per 100, 000 population respectively in 2001 -2012. The overall trends of TB notification rate and death rate are descending in Hong Kong for the period. The disease burden of TB was much higher but decline faster for men than that for female. For age-specific descending trends of disease burden of TB, the trends were faster as the age groups getting older. In most of the reviewed studies from 1971 to 2012,the peak of TB cases was mainly in spring and summer and trough in winter. The seasonal pattern of TB of some countries and cities had different characteristics stratified by factors such as gender, sex, latitude and disease form. Most of the studies suggested that vitamin D deficiency, indoor activities, meteorological observations and health care seeking behaviour are the main possible factors contributing to seasonality of TB. TB notifications in Hong Kong exhibited a peak in summer and trough in winter. Except duration of sunshine, all meteorological variables including temperature, humidity, and solar radiation were significantly associated with monthly TB notification rate. The final predictive model included predictors such as time, temperature and solar radiation. 1 deg. C increase in monthly mean temperature was associated with 0.12(with 95% CI of (0.084, 0.16)) per 100, 000 population increasing of TB monthly notification rate, while 1 MJ/m2increase in monthly global solar radiation was associated with 0.064(with 95% CI of (0.005, 0.12)) per 100, 000 population decreasing of TB monthly notification rate. By comparing different models, temperature seemed to explain the observed seasonal pattern, while solar radiation had a more independent effect. Conclusion The study showed a higher TB disease burden in male which increases with age. The peak season of TB transmission should be in winter. We suggest more effective TB control strategies focusing on target groups including children, elders and relapse cases. As a general measure, we may encourage outdoor activities and more exposure to sunlight. We also suggest further studies to explore the relationship between humidity and vitamin D deficiency and seasonality of TB. / published_or_final_version / Public Health / Master / Master of Public Health

published_or_final_version / Community Medicine / Doctoral / Doctor of Philosophy

More than one-third of the world population is infected with Tuberculosis (TB). World Health Organization has declared Tuberculosis as a global public health emergency in 1993. The people, affected by TB, are usually living in developing countries. In fact, TB is especially prevalent in Southeast Asia. China has been listed as a country with a high TB burden yet there are 150 “one-way permit” holders, across the border in China, for settlement purposes in Hong Kong. There is neither any health requirement nor obligatory physical examination before entry into Hong Kong. Unlike other developed countries, Hong Kong has no screening policy for people from Mainland China for migration purpose. The aim of this project is to explore the possibilities for different screening policies for new immigrants in Hong Kong, similar to those adopted by developed countries. Objectives include: (a) review of research articles and (b) careful perusal of selected government documents. Electronic databases of research articles for migration screening policy and data from World Health Organization, United Nations and other international and local authorizes were searched and analyzed to suggest practical policies for Hong Kong. Findings indicate that most developed countries have implemented pre-arrival screening policy, which is not practical in Hong Kong. Studies showed no significant difference between ‘pre’, ‘on’ or ‘post’ arrival programmes. Post arrival screening could be considered as the most suitable option for Hong Kong, according to the analyses of the data. Tuberculosis and Chest Service, Department of Health has the capacity to act as the screening authority for settlement purpose and could provide expert recommendation to Immigration Department about the health status of permanent residency applicants. Given the importance of screening, in various countries, to reduce the incidence of TB, Hong Kong could and should adopt a screening policy in order to decrease new notifications and enhance the local public health status. / published_or_final_version / Public Health / Master / Master of Public Health

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

published_or_final_version / Microbiology / Master / Master of Philosophy

Pang, Tak Ting Phoebe. / "September 2010." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 153-161). / Abstracts in English and Chinese. / Acknowledgement --- p.I / Abstract --- p.II / 摘要 --- p.IV / List of Figures --- p.V / List of Tables --- p.VII / Abbreviations --- p.VIII / Chapter CHAPTER ONE --- INTRODUCTION --- p.1 / Chapter 1.1 --- Historical perspective of tuberculosis --- p.1 / Chapter 1.1.1 --- Sanatorium care --- p.2 / Chapter 1.1.2 --- Vaccination --- p.2 / Chapter 1.1.3 --- Drug treatment --- p.3 / Chapter 1.1.4 --- Transmission dynamics of tuberculosis --- p.3 / Chapter 1.1.5 --- Resurgence of tuberculosis --- p.4 / Chapter 1.2 --- Current global and local tuberculosis epidemiology --- p.6 / Chapter 1.2.1 --- "Tuberculosis and HIV/AIDS, drug resistance in the world" --- p.6 / Chapter 1.2.2 --- Global epidemiology of tuberculosis --- p.9 / Chapter 1.2.3 --- Local epidemiology of tuberculosis --- p.9 / Chapter 1.2.4 --- "Tuberculosis, HIV/AIDS and drug resistance in Hong Kong" --- p.14 / Chapter 1.2.5 --- Approaches in studying tuberculosis epidemiology --- p.15 / Chapter 1.3 --- Determinants of tuberculosis epidemiology --- p.17 / Chapter 1.3.1 --- TB determinants in the triad of epidemiology --- p.17 / Chapter 1.3.2 --- Rise of spatial epidemiology --- p.18 / Chapter 1.4 --- Recent developments of spatial epidemiology --- p.21 / Chapter 1.4.1 --- Spatial epidemiology and infectious disease --- p.21 / Chapter 1.4.2 --- Disease mapping --- p.22 / Chapter 1.4.3 --- Geographic information system --- p.22 / Chapter 1.4.4 --- Statistics in spatial epidemiology --- p.23 / Chapter CHAPTER TWO --- LITERATURE REVIEW --- p.24 / Chapter 2.1 --- Objective of literature review --- p.24 / Chapter 2.2 --- Literature search --- p.25 / Chapter 2.2.1 --- Strategy for literature search --- p.25 / Chapter 2.2.2 --- Results for literature search --- p.25 / Chapter 2.3 --- Spatial perspective in tuberculosis epidemiology --- p.31 / Chapter 2.3.1 --- Mapping the spatial pattern --- p.32 / Chapter 2.3.2 --- Understanding the spatial pattern --- p.32 / Chapter 2.3.3 --- Modelling the spatial pattern --- p.33 / Chapter 2.4 --- Neighbourhood determinants of tuberculosis --- p.34 / Chapter 2.4.1 --- TB and demographics --- p.35 / Chapter 2.4.2 --- TB and socioeconomic status --- p.36 / Chapter 2.4.3 --- TB and the environment --- p.38 / Chapter 2.4.4 --- TB and care factors --- p.40 / Chapter 2.5 --- Techniques applied in studying tuberculosis epidemiology --- p.41 / Chapter 2.5.1 --- Constructing spatial data --- p.41 / Chapter 2.5.2 --- Disease maps used --- p.45 / Chapter 2.5.3 --- "Integrated approach using spatial statistics, conventional statistics and molecular analysis" --- p.52 / Chapter 2.6 --- Research gap and thesis objectives --- p.55 / Chapter 2.6.1 --- Research gap --- p.55 / Chapter 2.6.2 --- Thesis objective --- p.56 / Chapter CHAPTER THREE --- METHODOLOGY --- p.57 / Chapter 3.1 --- Rationale and approach --- p.57 / Chapter 3.1.1 --- Logical flow of the study --- p.57 / Chapter 3.1.2 --- Methodological flow of the study --- p.60 / Chapter 3.2 --- Choosing spatial units --- p.63 / Chapter 3.3 --- Data collection --- p.69 / Chapter 3.3.1 --- Tuberculosis data --- p.70 / Chapter 3.3.2 --- Spatial data --- p.70 / Chapter 3.3.3 --- Neighbourhood data --- p.70 / Chapter 3.4 --- Data manipulation --- p.73 / Chapter 3.4.1 --- Tuberculosis data --- p.73 / Chapter 3.4.2 --- Spatial data --- p.74 / Chapter 3.4.3 --- Neighbourhood data --- p.74 / Chapter 3.5 --- Centrographic analysis --- p.76 / Chapter 3.5.1 --- Types of centrographic statistics --- p.76 / Chapter 3.6 --- Exploratory spatial data analysis --- p.78 / Chapter 3.6.1 --- Spatial proximity matrix --- p.78 / Chapter 3.6.2 --- Moran's Index --- p.79 / Chapter 3.6.3 --- Local Indicator of Spatial Association --- p.79 / Chapter 3.7 --- Explanatory analysis --- p.81 / Chapter 3.7.1 --- Selecting variables for modelling --- p.82 / Chapter 3.7.2 --- Ordinary linear regression --- p.82 / Chapter 3.7.3 --- Geographically weighted regression --- p.83 / Chapter CHAPTER FOUR --- RESULTS --- p.85 / Chapter 4.1 --- Overview --- p.85 / Chapter 4.1.1 --- Individual level --- p.85 / Chapter 4.1.2 --- Aggregated level --- p.89 / Chapter 4.2 --- Results for centrographic analysis --- p.97 / Chapter 4.3 --- Results for exploratory spatial data analysis --- p.101 / Chapter 4.3.1 --- Results for Moran's Index --- p.101 / Chapter 4.3.2 --- Results for Local Indicator of Spatial Association --- p.103 / Chapter 4.4 --- Results for explanatory analysis --- p.110 / Chapter 4.4.1 --- Correlation analysis and variables selection --- p.110 / Chapter 4.4.2 --- Results for ordinary linear regression --- p.114 / Chapter 4.4.3 --- Results for geographically weighted regression --- p.116 / Chapter CHAPTER FIVE --- DISCUSSION --- p.131 / Chapter 5.1 --- Preamble --- p.131 / Chapter 5.1.1 --- Methods overview --- p.132 / Chapter 5.1.2 --- Results overview --- p.132 / Chapter 5.1.3 --- Layout of this chapter --- p.134 / Chapter 5.2 --- Neighbourhood determinants in relation to TB --- p.135 / Chapter 5.2.1 --- Crowding and tuberculosis --- p.135 / Chapter 5.2.2 --- Poverty and tuberculosis --- p.137 / Chapter 5.2.3 --- Immigrants and tuberculosis --- p.138 / Chapter 5.2.4 --- Marital status and tuberculosis --- p.139 / Chapter 5.2.5 --- Implication of local parameter estimates of association --- p.140 / Chapter 5.3 --- Study design for spatial epidemiology --- p.142 / Chapter 5.3.1 --- Application of spatial dependence in spatial epidemiology --- p.142 / Chapter 5.3.2 --- Choosing spatial units --- p.144 / Chapter 5.4 --- Methodological concern in this study --- p.146 / Chapter 5.4.1 --- Concern over disease mapping --- p.146 / Chapter 5.4.2 --- Application of geographically weighted regression --- p.148 / Chapter 5.5 --- Limitation of the study --- p.150 / Chapter 5.6 --- Conclusion --- p.152 / REFERENCE --- p.153 / APPENDIX --- p.162 / Appendix 1 How to calculate TB SNR? --- p.162 / Appendix 2 How GWR works? --- p.164 / Appendix 3 What is AIC? --- p.165 / Appendix 4 How Monte Carlo test works? --- p.166 / Appendix 5 List of GWR output --- p.167