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Did socio-ecological factors drive the spatiotemporal patterns of pandemic influenza A (H1N1)?
Institution:1. The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China;2. Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China;3. Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong, China;4. National Heart & Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom;5. School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China;6. Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China;7. Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
Abstract:BackgroundPandemic influenza A (H1N1) has a significant public health impact. This study aimed to examine the effect of socio-ecological factors on the transmission of H1N1 in Brisbane, Australia.MethodologyWe obtained data from Queensland Health on numbers of laboratory-confirmed daily H1N1 in Brisbane by statistical local areas (SLA) in 2009. Data on weather and socio-economic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive (CAR) model was used to quantify the relationship between variation of H1N1 and independent factors and to determine its spatiotemporal patterns.ResultsOur results show that average increase in weekly H1N1 cases were 45.04% (95% credible interval (CrI): 42.63–47.43%) and 23.20% (95% CrI: 16.10–32.67%), for a 1 °C decrease in average weekly maximum temperature at a lag of one week and a 10 mm decrease in average weekly rainfall at a lag of one week, respectively. An interactive effect between temperature and rainfall on H1N1 incidence was found (changes: 0.71%; 95% CrI: 0.48–0.98%). The auto-regression term was significantly associated with H1N1 transmission (changes: 2.5%; 95% CrI: 1.39–3.72). No significant association between socio-economic indexes for areas (SEIFA) and H1N1 was observed at SLA level.ConclusionsOur results demonstrate that average weekly temperature at lag of one week and rainfall at lag of one week were substantially associated with H1N1 incidence at a SLA level. The ecological factors seemed to have played an important role in H1N1 transmission cycles in Brisbane, Australia.
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