Background Influenza is an infectious respiratory illness which causes not only mild illness but also severe illness and death, responsible for about 250,000 to 500,000 deaths worldwide every year. Excess mortality usually had been used to estimate the actually recorded number of deaths that exceeded the number expected on the basis of past seasonal experience so as to assess the influenza related mortality. Previous studies reporting the association with environmental factors, such as ambient temperature and influenza related mortality, varied in different cities. Therefore, the association between environmental factors and excess mortality of influenza is still controversial and inconclusive, particularly in subtropical regions. Furthermore, whether there exists heterogeneity in the influenza disease burden and effect magnitude among different cities in the same subtropic region has been seldom documented so far. Objective The primary aim of this study is to critically assess the association between environmental factors especially weather conditions such as temperature, precipitation and relative humidity and the influenza‐associated mortality via systematic review and quantative analysis. The secondary aim is to compare the effect magnitude of environmental factors on influenza associated mortality between the southern cities of Mainland China and Hong Kong. Method Because influenza disease is difficult to detect or measure, influenza associated excess mortality which includes all cause deaths associated with influenza, respiratory and cardiovascular diseases (R&C) and pneumonia and influenza (P&I) has been used to measure the influenza. Eiligible studies up to February 2013 have been searched in Pubmed, EMBASE database and reference lists of previous reviews. All observational studies including ecological studies which assessed the assoicaitons between environmental factors and influenza‐associated mortality were included. Related excess mortality which had been deal with Poisson model in Hong Kong and related excess mortality which had been deal with negative binomial model in these Mainland southern cities had been collected from the secondary data. Meteorological data in Hong Kong had been collected from the historical data in meteorological observation stations, while the meteorological data in the southern cities of China was collected from China Meteorological Data Sharing Service System. Pearson correlation and linear regression have been used to examine the association between environmental factors and influenza associated mortality. Last, a pooled analysis was conducted by including city*environmental factors (temperature) as an interaction term in the model to detect the effect magnitude in the two kinds of cities. All tests were two‐sided and p values < 0.05 were considered statistically significant. Results A total of 14 papers were included in the critic review. Negative association between environmental fctors and influenza had been reported in many studies, although inconsistent results had also been reported. The excess mortality of pneumonia and influenza disease in the five southern Mainland cities is significant higher than the the one in Hong Kong (P=0.010). No significant difference was observed in all‐cause excess mortalities and cardiovascular and respiratory disease excess mortality between the two regions (P=0.991, P=0.109). In the five Mainland southern cities, there was significant association between temperature and influenza related all‐cause excess mortality, and the significant association was also found between temperature and cardiovascular and respiratory disease excess mortality (r = ‐0.475, P=0.016 and r = ‐0.673, P=0.007, respectively). Moreover, no significant association was found between precipitation and excess mortality in Mainland. While in Hong Kong, the only two significant associations were found between environmental factors, temperature and relative humidity, and P&I excess mortality (r = ‐0.763, P=0.003 and r =‐0.804, P=0.005, respectively). In the pooled analysis, the influence of temperature on R&C and all cause excess mortality was significantly different between Hong Kong and the five southern Mainland cities. With the increasing of the temperature, the excess mortalities reduced in the two counterparts. However, tempereture had a greater effect on the excess mortality in Mainland China cities than in Hong Kong. / published_or_final_version / Public Health / Master / Master of Public Health

Thesis (M.A.)--Georgia State University, 2007. / Title from file title page. Arla G. Bernstein, committee chair; Holley Wilkin, Leonard Teel, committee members. Electronic text (92 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed Oct. 17, 2007. Includes bibliographical references (p. 83-92).

published_or_final_version / abstract / Microbiology / Doctoral / Doctor of Philosophy

published_or_final_version / Public Health / Master / Master of Public Health

Background: The first influenza pandemic in the 21st century, the past 2009 influenza pandemic (pdmH1N1), was caused by a novel H1N1 influenza virus. The virus was first described in April 2009 and is now believed to emerge from re-assortment of bird, pig and human flu viruses. Although this pandemic was relatively mild compared to the past pandemics, better knowledge about its characteristics in transmission dynamics and severity is still of public health interest in order to better prepare for future pandemics. Data: Clinical surveillance data were obtained from eFlu database maintained by Hong Kong Hospital Authority. Information was extracted from all pdmH1N1 virologically confirmed infections (which were all symptomatic) about their dates of symptom onset, and, if applicable, dates of hospitalization, ICU admission and death. Serological data were obtained from various sources: 1) community cross-sectional serological survey; 2) convalescent serological data (from symptomatic and virologically confirmed infections); and 3) serological response kinetics data (from symptomatic and virologically confirmed infections). These serological data combined described serological responses against pdmH1N1 infections in the Hong Kong population from different aspects. Methods: I constructed an age-structured natural history model to mimic the pdmH1N1 transmission dynamics in Hong Kong. The transmission model was linked to hospitalization and serology in order to match the observed data. Based on all the data comprehensively, characteristic transmission parameters (basic reproductive number R0, mean generation time E(Tg), attack rates etc.) in the model were estimated using likelihood-based statistical inferences by Bayesian inference with Markov chain Monte Carlo (MCMC). Results: I estimated that R0 is 1.37 and E(Tg) is 2.16 days, which are both comparable to seasonal flu. Younger age groups <20 years were found to be more susceptible (2.72 times compared to 20-29 age group) to pdmH1N1 infection but older age groups 30-59 years were less susceptible (0.55 times). School closure reduced 0-12 year olds’ within-age-group transmission effectively during the reactive kindergarten and primary school closure from Jun 10 to Jul 9 by 93%. Summer holidays from Jun 10 to Aug 31 also reduced within-group transmission by 65% and 13% for 0-12 and 13-19 years olds respectively. Estimates of infection hospitalization probabilities ranged from 0.2% to 0.9% across age groups. I found that not all infected individuals would have serological response strong enough to be positive in serological test but younger age groups were more likely to have stronger serological response after infection. Conclusions: Clinical surveillance data have been used to estimate the transmission dynamics of pdmH1N1 in 2009. Here, I combined hospitalization surveillance data with serological data collected throughout the first pandemic wave (April to December 2009) from different sources, which could better characterize the transmission dynamics and severity of pdmH1N1 in Hong Kong. Although further validation is needed, serological surveillance should be considered as a supplementary alternative to clinical surveillance in influenza surveillance. / published_or_final_version / Community Medicine / Master / Master of Philosophy

published_or_final_version / Community Medicine / Master / Master of Public Health

published_or_final_version / Community Medicine / Doctoral / Doctor of Philosophy

published_or_final_version / Microbiology / Doctoral / Doctor of Philosophy

published_or_final_version / Community Medicine / Master / Master of Public Health

published_or_final_version / Community Medicine / Master / Master of Philosophy