Sampling stored-product insect pests : a comparison of four statistical sampling models for probability of pest detection

Background: Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. Results: Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,1 the Poisson model,1 the double logarithmic model2 and the compound model3 - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. Conclusions: This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.

Alcohol restrictions and drink driving in remote Indigenous communities in Queensland, Australia

Alcohol restrictions have been implemented in many Indigenous communities internationally, with the aim to reduce alcohol-related harm. Whilst a range of reviews have evaluated such restrictions using different measures, drink driving has been described in several reviews as increasing. Presently, this remains anecdotal; with limited empirical evidence to corroborate these reports. In Australia, the Queensland government introduced alcohol management plans in remote Indigenous communities, during 2002-2003, with total alcohol prohibition commencing in 2008 in some communities. Given road crashes are one of the leading causes of injuries for Indigenous peoples, this study aims to identify if the restrictions have been successful in reducing drink driving or have increased such behaviour. We examine this by reviewing changes in conviction rates and in offender and offence characteristics following the 2008 restrictions. Using de-identified Queensland court drink driving conviction data (2006-2011), from four Indigenous communities, Robust Poisson regression models compared counts of drink driving convictions pre (2006-2008) versus post SRS (2009-2011). Changes in offender characteristics and conviction details (blood alcohol concentration (BAC) and sentencing severity), were examined using chi-squares. Results indicate a decline in convictions after the 2008 SRS in three communities. However, a significant increase in convictions was identified in one study community. Community-level disparity included significant decline in BAC in one community (χ 2=5.58, p=0.02) compared with the three other communities that did not indicate change and a significant increase the number of women convicted in two communities (χ 2=17.36, p<0.01; χ 2=5.79, p=0.04). Alcohol restrictions may have important implications in road safety with these reductions in convictions and BAC in some communities. However, an increase in the number of women convicted and limited changes in BAC for other communities demonstrate the complex relationship between alcohol use, remoteness and driving. Greater focus on demand reduction strategies may be necessary to address alcohol misuse.

Modeling electricity price events as point processes

Energy prices are highly volatile and often feature unexpected spikes. It is the aim of this paper to examine whether the occurrence of these extreme price events displays any regularities that can be captured using an econometric model. Here we treat these price events as point processes and apply Hawkes and Poisson autoregressive models to model the dynamics in the intensity of this process.We use load and meteorological information to model the time variation in the intensity of the process. The models are applied to data from the Australian wholesale electricity market, and a forecasting exercise illustrates both the usefulness of these models and their limitations when attempting to forecast the occurrence of extreme price events.

The effects of hot and cold temperatures on emergency hospital admissions in Brisbane, Australia

As Earth's climate is rapidly changing, the impact of ambient temperature on health outcomes has attracted increasing attention in the recent time. Considerable number of excess deaths has been reported because of exposure to ambient hot and cold temperatures. However, relatively little research has been conducted on the relation between temperature and morbidity. The aim of this study was to characterize the relationship between both hot and cold temperatures and emergency hospital admissions in Brisbane, Australia, and to examine whether the relation varied by age and socioeconomic factors. It aimed to explore lag structures of temperature–morbidity association for respiratory causes, and to estimate the magnitude of emergency hospital admissions for cardiovascular diseases attributable to hot and cold temperatures for the large contribution of both diseases to the total emergency hospital admissions. A time series study design was applied using routinely collected data of daily emergency hospital admissions, weather and air pollution variables in Brisbane during 1996–2005. Poisson regression model with a distributed lag non-linear structure was adopted to assess the impact of temperature on emergency hospital admissions after adjustment for confounding factors. Both hot and cold effects were found, with higher risk of hot temperatures than that of cold temperatures. Increases in mean temperature above 24.2oC were associated with increased morbidity, especially for the elderly ≥ 75 years old with the largest effect. The magnitude of the risk estimates of hot temperature varied by age and socioeconomic factors. High population density, low household income, and unemployment appeared to modify the temperature–morbidity relation. There were different lag structures for hot and cold temperatures, with the acute hot effect within 3 days after hot exposure and about 2-week lagged cold effect on respiratory diseases. A strong harvesting effect after 3 days was evident for respiratory diseases. People suffering from cardiovascular diseases were found to be more vulnerable to hot temperatures than cold temperatures. However, more patients admitted for cardiovascular diseases were attributable to cold temperatures in Brisbane compared with hot temperatures. This study contributes to the knowledge base about the association between temperature and morbidity. It is vitally important in the context of ongoing climate change. The findings of this study may provide useful information for the development and implementation of public health policy and strategic initiatives designed to reduce and prevent the burden of disease due to the impact of climate change.

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.

The association between cold spells and pediatric outpatient visits for asthma in Shanghai, China

Background Asthma is a serious global health problem. However, few studies have investigated the relationship between cold spells and pediatric outpatient visits for asthma. Objective To examine the association between cold spells and pediatric outpatient visits for asthma in Shanghai, China. Methods We collected daily data on pediatric outpatient visits for asthma, mean temperature, relative humidity, and ozone from Shanghai between 1 January 2007 and 31 December 2009. We defined cold spells as four or more consecutive days with temperature below the 5th percentile of temperature during 2007–2009. We used a Poisson regression model to examine the impact of temperature on pediatric outpatient visits for asthma in cold seasons during 2007 and 2009. We examined the effect of cold spells on asthma compared with non-cold spell days. Results There was a significant relationship between cold temperatures and pediatric outpatient visits for asthma. The cold effects on children's asthma were observed at different lags. The lower the temperatures, the higher the risk for asthma attacks among children. Conclusion Cold temperatures, particularly cold spells, significantly increase the risk of pediatric outpatient visits for asthma. The findings suggest that asthma children need to be better protected from cold effects in winter.

A Hybrid Queue-based Bayesian Network Framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and Exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an $R^2$ goodness of fit of 0.9994 and 0.9982 respectively over a 10 hour test period. The utility of the framework is demonstrated on a number of usage scenarios including real time monitoring and `what-if' analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Non-invasive clinical measurement of the viscoelastic properties of tendon using acoustic wave transmission

Background. In isotropic materials, the speed of acoustic wave propagation is governed by the bulk modulus and density. For tendon, which is a structural composite of fluid and collagen, however, there is some anisotropy requiring an adjustment for Poisson's ratio. This paper explores these relationships using data collected, in vivo, on human Achilles tendon and then compares estimates of elastic modulus and hysteresis against published values from in vitro mechanical tests. Methods. Measurements using conventional B-model ultrasound imaging, inverse dynamics and acoustic transmission techniques were used to determine dimensions, loading conditions and longitudinal speed of sound in the Achilles tendon during a series of isometric plantar flexion exercises against body weight. Upper and lower bounds for speed of sound versus tensile stress in the tendon were then modelled and estimates of the elastic modulus and hysteresis of the Achilles tendon derived. Results. Axial speed of sound varied between 1850 and 2090 ms-1 with a non-linear, asymptotic dependency on the level of tensile stress (5-35 MPa) in the tendon. Estimates derived for the elastic modulus of the Achilles tendon ranged between 1-2 GPa. Hysteresis derived from models of the stress-strain relationship, ranged from 3-11%. Discussion. Estimates of elastic modulus agree closely with those previously reported from direct measurements obtained via mechanical tensile tests on major weight bearing tendons in vitro [1,2]. Hysteresis derived from models of the stress-strain relationship is consistent with direct measures from various mamalian tendon (7-10%) but is lower than previous estimates in human tendon (17-26%) [3]. This non-invasive method would appear suitable for monitoring changes in tendon properties during dynamic sporting activities.

Space-time clusters of dengue fever in Bangladesh

Objective:  To examine the space-time clustering of dengue fever (DF) transmission in Bangladesh using geographical information system and spatial scan statistics (SaTScan). Methods:  We obtained data on monthly suspected DF cases and deaths by district in Bangladesh for the period of 2000–2009 from Directorate General of Health Services. Population and district boundary data of each district were collected from national census managed by Bangladesh Bureau of Statistics. To identify the space-time clusters of DF transmission a discrete Poisson model was performed using SaTScan software. Results:  Space-time distribution of DF transmission was clustered during three periods 2000–2002, 2003–2005 and 2006–2009. Dhaka was the most likely cluster for DF in all three periods. Several other districts were significant secondary clusters. However, the geographical range of DF transmission appears to have declined in Bangladesh over the last decade. Conclusion:  There were significant space-time clusters of DF in Bangladesh over the last decade. Our results would prompt future studies to explore how social and ecological factors may affect DF transmission and would also be useful for improving DF control and prevention programs in Bangladesh.

Air pollution, temperature and pediatric influenza in Brisbane, Australia

Previous studies have demonstrated the importance of weather variables in influencing the incidence of influenza. However, the role of air pollution is often ignored in identifying the environmental drivers of influenza. This research aims to examine the impacts of air pollutants and temperature on the incidence of pediatric influenza in Brisbane, Australia. Lab-confirmed daily data on influenza counts among children aged 0-14years in Brisbane from 2001 January 1st to 2008 December 31st were retrieved from Queensland Health. Daily data on maximum and minimum temperatures for the same period were supplied by the Australian Bureau of Meteorology. Winter was chosen as the main study season due to it having the highest pediatric influenza incidence. Four Poisson log-linear regression models, with daily pediatric seasonal influenza counts as the outcome, were used to examine the impacts of air pollutants (i.e., ozone (O3), particulate matter≤10μm (PM10) and nitrogen dioxide (NO2)) and temperature (using a moving average of ten days for these variables) on pediatric influenza. The results show that mean temperature (Relative risk (RR): 0.86; 95% Confidence Interval (CI): 0.82-0.89) was negatively associated with pediatric seasonal influenza in Brisbane, and high concentrations of O3 (RR: 1.28; 95% CI: 1.25-1.31) and PM10 (RR: 1.11; 95% CI: 1.10-1.13) were associated with more pediatric influenza cases. There was a significant interaction effect (RR: 0.94; 95% CI: 0.93-0.95) between PM10 and mean temperature on pediatric influenza. Adding the interaction term between mean temperature and PM10 substantially improved the model fit. This study provides evidence that PM10 needs to be taken into account when evaluating the temperature-influenza relationship. O3 was also an important predictor, independent of temperature.

Spatial analysis of community-onset Staphylococcus aureus bacteremia in Queensland, Australia

OBJECTIVES To investigate and describe the relationship between indigenous Australian populations, residential aged care services, and community-onset Staphylococcus aureus bacteremia (SAB) among patients admitted to public hospitals in Queensland, Australia. DESIGN Ecological study. METHODS We used administrative healthcare data linked to microbiology results from patients with SAB admitted to Queensland public hospitals from 2005 through 2010 to identify community-onset infections. Data about indigenous Australian population and residential aged care services at the local government area level were obtained from the Queensland Office of Economic and Statistical Research. Associations between community-onset SAB and indigenous Australian population and residential aged care services were calculated using Poisson regression models in a Bayesian framework. Choropleth maps were used to describe the spatial patterns of SAB risk. RESULTS We observed a 21% increase in relative risk (RR) of bacteremia with methicillin-susceptible S. aureus (MSSA; RR, 1.21 [95% credible interval, 1.15-1.26]) and a 24% increase in RR with nonmultiresistant methicillin-resistant S. aureus (nmMRSA; RR, 1.24 [95% credible interval, 1.13-1.34]) with a 10% increase in the indigenous Australian population proportion. There was no significant association between RR of SAB and the number of residential aged care services. Areas with the highest RR for nmMRSA and MSSA bacteremia were identified in the northern and western regions of Queensland. CONCLUSIONS The RR of community-onset SAB varied spatially across Queensland. There was increased RR of community-onset SAB with nmMRSA and MSSA in areas of Queensland with increased indigenous population proportions. Additional research should be undertaken to understand other factors that increase the risk of infection due to this organism.

Spatial Patterns of Malaria Reported Deaths in Yunnan Province, China

Malaria has been a heavy social and health burden in the remote and poor areas in southern China. Analyses of malaria epidemic patterns can uncover important features of malaria transmission. This study identified spatial clusters, seasonal patterns, and geographic variations of malaria deaths at a county level in Yunnan, China, during 1991–2010. A discrete Poisson model was used to identify purely spatial clusters of malaria deaths. Logistic regression analysis was performed to detect changes in geographic patterns. The results show that malaria mortality had declined in Yunnan over the study period and the most likely spatial clusters (relative risk [RR] = 23.03–32.06, P < 0.001) of malaria deaths were identified in western Yunnan along the China–Myanmar border. The highest risk of malaria deaths occurred in autumn (RR = 58.91, P < 0.001) and summer (RR = 31.91, P < 0.001). The results suggested that the geographic distribution of malaria deaths was significantly changed with longitude, which indicated there was decreased mortality of malaria in eastern areas over the last two decades, although there was no significant change in latitude during the same period. Public health interventions should target populations in western Yunnan along border areas, especially focusing on floating populations crossing international borders.

Australian baby boomers switched to more environment friendly modes of transport during the global financial crisis

The global financial crisis (GFC) in 2008 rocked local, regional, and state economies throughout the world. Several intermediate outcomes of the GFC have been well documented in the literature including loss of jobs and reduced income. Relatively little research has, however, examined the impacts of the GFC on individual level travel behaviour change. To address this shortcoming, HABITAT panel data were employed to estimate a multinomial logit model to examine mode switching behaviour between 2007 (pre-GFC) and 2009 (post-GFC) of a baby boomers cohort in Brisbane, Australia—a city within a developed country that has been on many metrics the least affected by the GFC. In addition, a Poisson regression model was estimated to model the number of trips made by individuals in 2007, 2008, and 2009. The South East Queensland Travel Survey datasets were used to develop this model. Four linear regression models were estimated to assess the effects of the GFC on time allocated to travel during a day: one for each of the three travel modes including public transport, active transport, less environmentally friendly transport; and an overall travel time model irrespective of mode. The results reveal that individuals were more likely to switch to public transport who lost their job or whose income reduced between 2007 and 2009. Individuals also made significantly fewer trips in 2008 and 2009 compared to 2007. Individuals spent significantly less time using less environmentally friendly transport but more time using public transport in 2009. Baby boomers switched to more environmentally friendly travel modes during the GFC.

Numerical study of lid-driven square cavity with heat generation using LBM

In this study, the mixed convection heat transfer and fluid flow behaviors in a lid-driven square cavity filled with high Prandtl number fluid (Pr = 5400, ν = 1.2×10-4 m2/s) at low Reynolds number is studied using thermal Lattice Boltzmann method (TLBM) where ν is the viscosity of the fluid. The LBM has built up on the D2Q9 model and the single relaxation time method called the Lattice-BGK (Bhatnagar-Gross-Krook) model. The effects of the variations of non dimensional mixed convection parameter called Richardson number(Ri) with and without heat generating source on the thermal and flow behavior of the fluid inside the cavity are investigated. The results are presented as velocity and temperature profiles as well as stream function and temperature contours for Ri ranging from 0.1 to 5.0 with other controlling parameters that present in this study. It is found that LBM has good potential to simulate mixed convection heat transfer and fluid flow problem. Finally the simulation results have been compared with the previous numerical and experimental results and it is found to be in good agreement.

Extreme temperatures and paediatric emergency department admissions

Background Children are particularly vulnerable to the effects of extreme temperatures. Objective To examine the relationship between extreme temperatures and paediatric emergency department admissions (EDAs) in Brisbane, Australia, during 2003–2009. Methods A quasi-Poisson generalised linear model combined with a distributed lag non-linear model was used to examine the relationships between extreme temperatures and age-, gender- and cause-specific paediatric EDAs, while controlling for air pollution, relative humidity, day of the week, influenza epidemics, public holiday, season and long-term trends. The model residuals were checked to identify whether there was an added effect due to heat waves or cold spells. Results There were 131 249 EDAs among children during the study period. Both high (RR=1.27; 95% CI 1.12 to 1.44) and low (RR=1.81; 95% CI 1.66 to 1.97) temperatures were significantly associated with an increase in paediatric EDAs in Brisbane. Male children were more vulnerable to temperature effects. Children aged 0–4 years were more vulnerable to heat effects and children aged 10–14 years were more sensitive to both hot and cold effects. High temperatures had a significant impact on several paediatric diseases, including intestinal infectious diseases, respiratory diseases, endocrine, nutritional and metabolic diseases, nervous system diseases and chronic lower respiratory diseases. Low temperatures were significantly associated with intestinal infectious diseases, respiratory diseases and endocrine, nutritional and metabolic diseases. An added effect of heat waves on childhood chronic lower respiratory diseases was seen, but no added effect of cold spells was found. Conclusions As climate change continues, children are at particular risk of a variety of diseases which might be triggered by extremely high temperatures. This study suggests that preventing the effects of extreme temperature on children with respiratory diseases might reduce the number of EDAs.