Exact and approximate Bayesian inference for low count time series models with intractable likelihoods

In this paper we present a new simulation methodology in order to obtain exact or approximate Bayesian inference for models for low-valued count time series data that have computationally demanding likelihood functions. The algorithm fits within the framework of particle Markov chain Monte Carlo (PMCMC) methods. The particle filter requires only model simulations and, in this regard, our approach has connections with approximate Bayesian computation (ABC). However, an advantage of using the PMCMC approach in this setting is that simulated data can be matched with data observed one-at-a-time, rather than attempting to match on the full dataset simultaneously or on a low-dimensional non-sufficient summary statistic, which is common practice in ABC. For low-valued count time series data we find that it is often computationally feasible to match simulated data with observed data exactly. Our particle filter maintains $N$ particles by repeating the simulation until $N+1$ exact matches are obtained. Our algorithm creates an unbiased estimate of the likelihood, resulting in exact posterior inferences when included in an MCMC algorithm. In cases where exact matching is computationally prohibitive, a tolerance is introduced as per ABC. A novel aspect of our approach is that we introduce auxiliary variables into our particle filter so that partially observed and/or non-Markovian models can be accommodated. We demonstrate that Bayesian model choice problems can be easily handled in this framework.

Book Review : "The Psychology of Eating : From Healthy to Disordered Behaviour"

WHEN JANE Ogden embarked on writing a book about the psychology of eating I wonder whether she realized the enormity of the task given the breadth of research literature in this field. Through a series of 12 closely related chapters on eating, health, food choice, dieting, obesity, body image, eating disorders and others, an extensive range of areas of the psychology of eating is covered. As well as these areas, included within each chapter is a discussion of the significance of historical, cultural, social and familial factors, theoretical approaches and empirical data in the understanding of the multifaceted problems related to eating. At the end of each chapter there is a box entitled ‘Towards an integrated model of diet’ that links the content with that of the following chapters...

The Social Construction of Anorexia Nervosa

"In this wide-ranging book, Julie Hepworth casts a critical light on our contemporary understanding of anorexia nervosa. She locates contemporary discourses of anorexia nervosa within their historical context, showing how current practices continue to be influenced by medicine, psychology, ideology and politics. She argues that anorexia nervosa must be considered within the political, social and gendered relationships that continue to contribute to its definition. The book demonstrates the need for a new conceptualization of anorexia nervosa which would draw on the insights of discourse theory, feminism and postmodernism to create new understandings of anorexia nervosa within contemporary health care practices." -- publisher website

Discussion paper and working paper series : Motivations, expectations and experiences of Australian rural and regional planners

Despite playing an extremely important role in shaping communities, the role and contribution of planners is not widely understood or acknowledged. At the same time, there is a shortage of planners in Australia, especially in non-urban areas. Thus, though an online survey of 185 rural and regional planners, this research explores their motivations, expectations and experiences. Most enjoyed and felt confident in their role, explaining that they valued the relaxed family orientated rural lifestyle and the varied nature of the planning work. Although they sometimes felt isolated, the non-urban location provided quicker progression to senior roles, the ability to engage directly with the community and to see the consequences of their decisions. Only half felt their education had prepared them well for their role, citing gaps in terms of computerised modelling, team leadership and conflict resolution skills. Their feedback centred on providing a more practical course, focussing more on regional planning, and encouraging urban and rural experience placements. As the first study to quantifiably explore rural and regional Australian planners perceptions of their role and challenges, the findings illustrate current experiences, key planning challenges, perceived educational gaps and future priorities.

Vibrational spectroscopic characterization of the phosphate mineral series eosphorite–childrenite–(Mn,Fe)Al(PO4)(OH)2·(H2O)

The phosphate mineral series eosphorite–childrenite–(Mn,Fe)Al(PO4)(OH)2·(H2O) has been studied using a combination of electron probe analysis and vibrational spectroscopy. Eosphorite is the manganese rich mineral with lower iron content in comparison with the childrenite which has higher iron and lower manganese content. The determined formulae of the two studied minerals are: (Mn0.72,Fe0.13,Ca0.01)(Al)1.04(PO4, OHPO3)1.07(OH1.89,F0.02)·0.94(H2O) for SAA-090 and (Fe0.49,Mn0.35,Mg0.06,Ca0.04)(Al)1.03(PO4, OHPO3)1.05(OH)1.90·0.95(H2O) for SAA-072. Raman spectroscopy enabled the observation of bands at 970 cm−1 and 1011 cm−1 assigned to monohydrogen phosphate, phosphate and dihydrogen phosphate units. Differences are observed in the area of the peaks between the two eosphorite minerals. Raman bands at 562 cm−1, 595 cm−1, and 608 cm−1 are assigned to the �4 bending modes of the PO4, HPO4 and H2PO4 units; Raman bands at 405 cm−1, 427 cm−1 and 466 cm−1 are attributed to the �2 modes of these units. Raman bands of the hydroxyl and water stretching modes are observed. Vibrational spectroscopy enabled details of the molecular structure of the eosphorite mineral series to be determined.

Raman, infrared and near-infrared spectroscopic characterization of the herderite-hydroxylherderite mineral series

Natural single-crystal specimens of the herderite-hydroxylherderite series from Brazil, with general formula CaBePO4(F,OH), were investigated by electron microprobe, Raman, infrared and near-infrared spectroscopies. The minerals occur as secondary products in granitic pegmatites. Herderite and hydroxylherderite minerals show extensive solid solution formation. The Raman spectra of hydroxylherderite are characterized by bands at around 985 and 998 cm-1, assigned to ν1 symmetric stretching mode of the HOPO33- and PO43- units. Raman bands at around 1085, 1128 and 1138 cm-1 are attributed to both the HOP and PO antisymmetric stretching vibrations. The set of Raman bands observed at 563, 568, 577, 598, 616 and 633 cm-1 are assigned to the ν4 out of plane bending modes of the PO4 and H2PO4 units. The OH Raman stretching vibrations of hydroxylherderite were observed ranging from 3626 cm-1 to 3609 cm-1. The infrared stretching vibrations of hydroxylherderites were observed between 3606 cm-1 and 3599 cm-1. By using a Libowitzky type function, hydrogen bond distances based upon the OH stretching bands were calculated. Characteristic NIR bands at around 6961 and 7054 cm-1 were assigned to the first overtone of the fundamental, whilst NIR bands at 10194 and 10329 cm-1 are assigned to the second overtone of the fundamental OH stretching vibration. Insight into the structure of the herderite-hydroxylherderite series is assessed by vibrational spectroscopy.

Econometric Modelling with Time Series : Specification, Estimation and Testing

This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Impact of a school-based food garden on attitudes and identification skills regarding vegetables and fruit : a 12-month intervention trial

Objective To determine changes in ability to identify specific vegetables and fruits, and attitudes towards vegetables and fruit, associated with the introduction of a school-based food garden. Design A 12-month intervention trial using a historical control (control n 132, intervention n 120), class-based, self-administered questionnaires requiring one-word answers and 3-point Likert scale responses. Setting A state primary school (grades 4 to 7) in a low socio-economic area of Brisbane, Australia. Intervention The introduction of a school-based food garden, including the funding of a teacher coordinator for 11 h/week to facilitate integration of garden activities into the curriculum. Main outcome measures Ability to identify a series of vegetables and fruits, attitudes towards vegetables and fruit. Analysis Frequency distributions for each item were generated and χ2 analyses were used to determine statistical significance. Exploratory factor analysis was employed to detect major trends in data. Results The intervention led to enhanced ability to identify individual vegetables and fruits, greater attention to origins of produce (garden-grown and fresh), changes to perceived consumption of vegetables and fruits, and enhanced confidence in preparing fruit and vegetable snacks, but decreased interest in trying new fruits. Conclusions The introduction of this school-based food garden was associated with skill and attitudinal changes conducive to enhancing vegetable and fruit consumption. The ways in which such changes might impact on dietary behaviours and intake require further analysis.

Using cultural-historical activity theory (CHAT) to study the relationship between school leadership and organisational change

This study aimed to identify how school leaders’ practices influence department activities during school transformation. The method used to explore emerging disturbances and contradictions within and between school departments was based on Cultural Historical Activity Theory (CHAT). The findings show that in order to implement educational changes in schools successfully, leaders should promote the change they envision as being highly consistent with the current collective identity (shared object) of the departments. From this perspective, the systemic components of the school departments are given a sense of preservation and continuity, rather than loss.

Spatiotemporal model or time series model for assessing city-wide temperature effects on mortality?

Most studies examining the temperature–mortality association in a city used temperatures from one site or the average from a network of sites. This may cause measurement error as temperature varies across a city due to effects such as urban heat islands. We examined whether spatiotemporal models using spatially resolved temperatures produced different associations between temperature and mortality compared with time series models that used non-spatial temperatures. We obtained daily mortality data in 163 areas across Brisbane city, Australia from 2000 to 2004. We used ordinary kriging to interpolate spatial temperature variation across the city based on 19 monitoring sites. We used a spatiotemporal model to examine the impact of spatially resolved temperatures on mortality. Also, we used a time series model to examine non-spatial temperatures using a single site and the average temperature from three sites. We used squared Pearson scaled residuals to compare model fit. We found that kriged temperatures were consistent with observed temperatures. Spatiotemporal models using kriged temperature data yielded slightly better model fit than time series models using a single site or the average of three sites' data. Despite this better fit, spatiotemporal and time series models produced similar associations between temperature and mortality. In conclusion, time series models using non-spatial temperatures were equally good at estimating the city-wide association between temperature and mortality as spatiotemporal models.

Sunshine, rainfall, humidity and child pneumonia in the tropics : time-series analyses

Few studies have formally examined the relationship between meteorological factors and the incidence of child pneumonia in the tropics, despite the fact that most child pneumonia deaths occur there. We examined the association between four meteorological exposures (rainy days, sunshine, relative humidity, temperature) and the incidence of clinical pneumonia in young children in the Philippines using three time-series methods: correlation of seasonal patterns, distributed lag regression, and case-crossover. Lack of sunshine was most strongly associated with pneumonia in both lagged regression [overall relative risk over the following 60 days for a 1-h increase in sunshine per day was 0·67 (95% confidence interval (CI) 0·51–0·87)] and case-crossover analysis [odds ratio for a 1-h increase in mean daily sunshine 8–14 days earlier was 0·95 (95% CI 0·91–1·00)]. This association is well known in temperate settings but has not been noted previously in the tropics. Further research to assess causality is needed.

Travel time prediction on signalised urban arterials by applying SARIMA modelling on Bluetooth data

Travel time prediction has long been the topic of transportation research. But most relevant prediction models in the literature are limited to motorways. Travel time prediction on arterial networks is challenging due to involving traffic signals and significant variability of individual vehicle travel time. The limited availability of traffic data from arterial networks makes travel time prediction even more challenging. Recently, there has been significant interest of exploiting Bluetooth data for travel time estimation. This research analysed the real travel time data collected by the Brisbane City Council using the Bluetooth technology on arterials. Databases, including experienced average daily travel time are created and classified for approximately 8 months. Thereafter, based on data characteristics, Seasonal Auto Regressive Integrated Moving Average (SARIMA) modelling is applied on the database for short-term travel time prediction. The SARMIA model not only takes the previous continuous lags into account, but also uses the values from the same time of previous days for travel time prediction. This is carried out by defining a seasonality coefficient which improves the accuracy of travel time prediction in linear models. The accuracy, robustness and transferability of the model are evaluated through comparing the real and predicted values on three sites within Brisbane network. The results contain the detailed validation for different prediction horizons (5 min to 90 minutes). The model performance is evaluated mainly on congested periods and compared to the naive technique of considering the historical average.

Assessing the short-term effects of heatwaves on mortality and morbidity in Brisbane, Australia : comparison of case-crossover and time series analyses

Background Heat-related impacts may have greater public health implications as climate change continues. It is important to appropriately characterize the relationship between heatwave and health outcomes. However, it is unclear whether a case-crossover design can be effectively used to assess the event- or episode-related health effects. This study examined the association between exposure to heatwaves and mortality and emergency hospital admissions (EHAs) from non-external causes in Brisbane, Australia, using both case-crossover and time series analyses approaches. Methods Poisson generalised additive model (GAM) and time-stratified case-crossover analyses were used to assess the short-term impact of heatwaves on mortality and EHAs. Heatwaves exhibited a significant impact on mortality and EHAs after adjusting for air pollution, day of the week, and season. Results For time-stratified case-crossover analysis, odds ratios of mortality and EHAs during heatwaves were 1.62 (95% confidence interval (CI): 1.36–1.94) and 1.22 (95% CI: 1.14–1.30) at lag 1, respectively. Time series GAM models gave similar results. Relative risks of mortality and EHAs ranged from 1.72 (95% CI: 1.40–2.11) to 1.81 (95% CI: 1.56–2.10) and from 1.14 (95% CI: 1.06–1.23) to 1.28 (95% CI: 1.21–1.36) at lag 1, respectively. The risk estimates gradually attenuated after the lag of one day for both case-crossover and time series analyses. Conclusions The risk estimates from both case-crossover and time series models were consistent and comparable. This finding may have implications for future research on the assessment of event- or episode-related (e.g., heatwave) health effects.

Effects of temperature on mortality in Chiang Mai city, Thailand : a time series study

Background The association between temperature and mortality has been examined mainly in North America and Europe. However, less evidence is available in developing countries, especially in Thailand. In this study, we examined the relationship between temperature and mortality in Chiang Mai city, Thailand, during 1999–2008. Method A time series model was used to examine the effects of temperature on cause-specific mortality (non-external, cardiopulmonary, cardiovascular, and respiratory) and age-specific non-external mortality (<=64, 65–74, 75–84, and > =85 years), while controlling for relative humidity, air pollution, day of the week, season and long-term trend. We used a distributed lag non-linear model to examine the delayed effects of temperature on mortality up to 21 days. Results We found non-linear effects of temperature on all mortality types and age groups. Both hot and cold temperatures resulted in immediate increase in all mortality types and age groups. Generally, the hot effects on all mortality types and age groups were short-term, while the cold effects lasted longer. The relative risk of non-external mortality associated with cold temperature (19.35°C, 1st percentile of temperature) relative to 24.7°C (25th percentile of temperature) was 1.29 (95% confidence interval (CI): 1.16, 1.44) for lags 0–21. The relative risk of non-external mortality associated with high temperature (31.7°C, 99th percentile of temperature) relative to 28°C (75th percentile of temperature) was 1.11 (95% CI: 1.00, 1.24) for lags 0–21. Conclusion This study indicates that exposure to both hot and cold temperatures were related to increased mortality. Both cold and hot effects occurred immediately but cold effects lasted longer than hot effects. This study provides useful data for policy makers to better prepare local responses to manage the impact of hot and cold temperatures on population health.

The health effects of temperature : current estimates, future projections, and adaptation strategies

Climate change is expected to be one of the biggest global health threats in the 21st century. In response to changes in climate and associated extreme events, public health adaptation has become imperative. This thesis examined several key issues in this emerging research field. The thesis aimed to identify the climate-health (particularly temperature-health) relationships, then develop quantitative models that can be used to project future health impacts of climate change, and therefore help formulate adaptation strategies for dealing with climate-related health risks and reducing vulnerability. The research questions addressed by this thesis were: (1) What are the barriers to public health adaptation to climate change? What are the research priorities in this emerging field? (2) What models and frameworks can be used to project future temperature-related mortality under different climate change scenarios? (3) What is the actual burden of temperature-related mortality? What are the impacts of climate change on future burden of disease? and (4) Can we develop public health adaptation strategies to manage the health effects of temperature in response to climate change? Using a literature review, I discussed how public health organisations should implement and manage the process of planned adaptation. This review showed that public health adaptation can operate at two levels: building adaptive capacity and implementing adaptation actions. However, there are constraints and barriers to adaptation arising from uncertainty, cost, technologic limits, institutional arrangements, deficits of social capital, and individual perception of risks. The opportunities for planning and implementing public health adaptation are reliant on effective strategies to overcome likely barriers. I proposed that high priorities should be given to multidisciplinary research on the assessment of potential health effects of climate change, projections of future health impacts under different climate and socio-economic scenarios, identification of health cobenefits of climate change policies, and evaluation of cost-effective public health adaptation options. Heat-related mortality is the most direct and highly-significant potential climate change impact on human health. I thus conducted a systematic review of research and methods for projecting future heat-related mortality under different climate change scenarios. The review showed that climate change is likely to result in a substantial increase in heatrelated mortality. Projecting heat-related mortality requires understanding of historical temperature-mortality relationships, and consideration of future changes in climate, population and acclimatisation. Further research is needed to provide a stronger theoretical framework for mortality projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution and mortality displacement. Most previous studies were designed to examine temperature-related excess deaths or mortality risks. However, if most temperature-related deaths occur in the very elderly who had only a short life expectancy, then the burden of temperature on mortality would have less public health importance. To guide policy decisions and resource allocation, it is desirable to know the actual burden of temperature-related mortality. To achieve this, I used years of life lost to provide a new measure of health effects of temperature. I conducted a time-series analysis to estimate years of life lost associated with changes in season and temperature in Brisbane, Australia. I also projected the future temperaturerelated years of life lost attributable to climate change. This study showed that the association between temperature and years of life lost was U-shaped, with increased years of life lost on cold and hot days. The temperature-related years of life lost will worsen greatly if future climate change goes beyond a 2 °C increase and without any adaptation to higher temperatures. The excess mortality during prolonged extreme temperatures is often greater than the predicted using smoothed temperature-mortality association. This is because sustained period of extreme temperatures produce an extra effect beyond that predicted by daily temperatures. To better estimate the burden of extreme temperatures, I estimated their effects on years of life lost due to cardiovascular disease using data from Brisbane, Australia. The results showed that the association between daily mean temperature and years of life lost due to cardiovascular disease was U-shaped, with the lowest years of life lost at 24 °C (the 75th percentile of daily mean temperature in Brisbane), rising progressively as temperatures become hotter or colder. There were significant added effects of heat waves, but no added effects of cold spells. Finally, public health adaptation to hot weather is necessary and pressing. I discussed how to manage the health effects of temperature, especially with the context of climate change. Strategies to minimise the health effects of high temperatures and climate change can fall into two categories: reducing the heat exposure and managing the health effects of high temperatures. However, policy decisions need information on specific adaptations, together with their expected costs and benefits. Therefore, more research is needed to evaluate cost-effective adaptation options. In summary, this thesis adds to the large body of literature on the impacts of temperature and climate change on human health. It improves our understanding of the temperaturehealth relationship, and how this relationship will change as temperatures increase. Although the research is limited to one city, which restricts the generalisability of the findings, the methods and approaches developed in this thesis will be useful to other researchers studying temperature-health relationships and climate change impacts. The results may be helpful for decision-makers who develop public health adaptation strategies to minimise the health effects of extreme temperatures and climate change.