Background The dynamics of influenza virus transmission are not yet fully understood, hindering the appropriate development and implementation of control and mitigation strategies. One major uncertainty relates to the profile of infectiousness over time in humans infected by influenza virus, and how variation in infectiousness might contribute to the risk of transmission in households. Methods In 2008 and 2009, two large community-based studies were conducted to study the household transmission of influenza viruses in Hong Kong. I analyzed data on viral shedding and disease in participants, and used statistical models to examine how viral shedding patterns and other factors might affect the risk of influenza virus transmission in households, both within individuals over time, and between individuals with different patterns in viral shedding. Results The patterns of viral shedding relative to the time of illness (acute respiratory illness; ARI) onset in naturally acquired infections were found to be largely comparable to the patterns observed in experimental infections. Viral shedding detected by RT-PCR peaks around the day of ARI onset after which levels of shedding declined over around 7 days, and viral shedding tended to be greater in children than adults. The patterns of viral shedding in cases of seasonal A subtypes were similar, although the trends of shedding in cases of seasonal B differed with some indication of a plateau in shedding for up to 5 days after illness onset. The risk of household influenza transmission was significantly associated with log10 viral shedding, though not with influenza related signs and symptoms such as cough. Conclusions The patterns of viral shedding observed in naturally-acquired influenza A virus infections correlated with the pattern of infectiousness over time after onset of illness. The majority of infectiousness was estimated to occur within 2-3 days of illness onset, with implications for isolation strategies. The heterogeneous nature of individual viral shedding suggests the possibility of substantial variation in infectiousness, particularly among children. / published_or_final_version / Community Medicine / Doctoral / Doctor of Philosophy

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published_or_final_version / Community Medicine / Master / Master of Public Health

Avian influenza H5N1 is one kind of important bird flu. Unfortunately, this virus has swiftly evolved and become highly pathogenic to humans and poultry, resulting in 100% of death in infected poultry and over 60% of mortality among infected human population. Moreover, the virus tends to reassort with other influenza viruses, such as the current swine flu H1N1, to establish themselves in environments and further this epidemic all over the world. The World Health Organization (WHO) has in fact warned that highly pathogenic avian influenza H5N1 poses a graver risk of a global human pandemic than at any time since the Hong Kong outbreak (H3N2) in the 1960s. / Finally, avian influenza is an inter-disciplinary issue across virology, medical geography, and spatial epidemiology. How to quantify and integrate knowledge from different disciplines remains a challenge in fully understanding the disease. We propose a method to formally integrate genetic analysis that identifies the evolution of the H5N1 virus in space and time, epidemiological analysis that determines socio-environmental factors associated with H5N1 occurrence and statistical analysis that identifies outbreak dusters. Our integrated results show a significant advance in findings over reports in, for instance, Gilbert et al. (2008) and we believe our findings are more precise and informative in representing the occurrence and the space-time dynamics of H5N1 spread. Overall, unlike traditional influenza studies, our work sets up a solid foundation for the inter-disciplinary study of this and other spatial infectious diseases. / First, we apply multifractal detrended fluctuation analysis to determine the temporal scaling behavior of outbreaks in Asia, Europe, Africa, and the whole of the world between December 2003 to March 2009. Long-range correlation and multifractality, two important properties characterizing the scaling behavior of complex dynamics, are first detected in the outbreak time series. In addition, this study identifies different temporal scaling behaviors of outbreaks of these continents 8,nd specific seasonal patterns in Asia. These findings confirm our perspective that avian-influenza outbreak behaviors are self-similar over time and are spatially heterogeneous. / One key to preventing such a calamity is to obtain a thorough understanding of the mechanisms of avian influenza transmission and its spatio-temporal patterns of dispersal. The issues at stake are outbreaks' spatial and temporal patterns, the interrelationship of these with the evolution of influenza viruses in such a way that geography is understood as a dimension of the disease's virology, and the human and avian behaviors and socio-ecological environments associated with H5Nl spread. This thesis sets out to study these problems in detail and propose solutions. / Second, we conduct a spatial analysis for global trends and local clusters of H5N1 outbreaks at multiple geographical scales. Currently, the local K function used in a point pattern analysis searches outbreak clusters, assuming the disease is spatially homogeneous. The thesis proposes a much more efficient method to measure the degree of clusters accurately. The modified function works by weighting outbreaks through distances, counting the number of the weighted outbreaks for each lattice point no matter whether the disease emerges in a grid. This weighted local K function extends cluster analysis from a point pattern to lattice data. Spatial representation in these terms then seeks to explore local patterns of H5N1 over a continuous space. / Third, we study a set of socio-environmental factors, which are plausibly associated with the occurrence of H5N1. Spatial epidemiological models are built for predicting the disease at both continental and national levels, covering Indonesia, China, and the whole of East-Southeast Asia. We evaluate the statistical models using 1,000 bootstrap replicates, showing a consistently high rate of prediction, assessed by statistics: AUC, Kappa Index, and pseudo R square. / Ge, Erjia. / Advisers: Yee Leung; Tung Fung. / Source: Dissertation Abstracts International, Volume: 73-06, Section: A, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 169-197). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Traditional Public Health decision-support can benefit from the Web and social media revolution. This dissertation presents approaches to mining social media benefiting public health epidemiology. Through discovery and analysis of trends in Influenza related blogs, a correlation to Centers for Disease Control and Prevention (CDC) influenza-like-illness patient reporting at sentinel health-care providers is verified. A second approach considers personal beliefs of vaccination in social media. A vaccine for human papillomavirus (HPV) was approved by the Food and Drug Administration in May 2006. The virus is present in nearly all cervical cancers and implicated in many throat and oral cancers. Results from automatic sentiment classification of HPV vaccination beliefs are presented which will enable more accurate prediction of the vaccine's population-level impact. Two epidemic models are introduced that embody the intimate social networks related to HPV transmission. Ultimately, aggregating these methodologies with epidemic and social network modeling facilitate effective development of strategies for targeted interventions.