Hot temperatures and morbidity : a systematic review and meta–analysis

Extreme temperatures have been shown to have a detrimental effect on health. Hot temperatures can increase the risk of mortality, particularly in people suffering from cardiorespiratory diseases. Given the onset of climate change, it is critical that the impact of temperature on health is understood, so that effective public health strategies can correctly identify vulnerable groups within the population. However, while effects on mortality have been extensively studied, temperature–related morbidity has received less attention. This study applied a systematic review and meta–analysis to examine the current literature relating to hot temperatures and morbidity

Compensating for Missing Data from Longitudinal Studies Using WinBUGS

Missing data is a common problem in survey based research. There are many packages that compensate for missing data but few can easily compensate for missing longitudinal data. WinBUGS compensates for missing data using multiple imputation, and is able to incorporate longitudinal structure using random effects. We demonstrate the superiority of longitudinal imputation over cross-sectional imputation using WinBUGS. We use example data from the Australian Longitudinal Study on Women's Health. We give a SAS macro that uses WinBUGS to analyze longitudinal models with missing covariate date, and demonstrate its use in a longitudinal study of terminal cancer patients and their carers.

A Time-Domain Test for Some Types of Non-Linearity

The bispectrum and third-order moment can be viewed as equivalent tools for testing for the presence of non-linearity in stationary time series. This is because the bispectrum is the Fourier transform of the third order moment. An advantage of the bispectrum is that its estimator comprises terms which are asymptotically independent at distinct bifrequencies under the null hypothesis of linearity. An advantage of the third order moment is that its values at any subset of joint lags can be used in the test, whereas when using the bispectrum the entire (or truncated) third order moment is required to construct the Fourier transform. In this paper we propose a test for non-linearity based upon the estimated third order moment. We use the phase scrambling bootstrap method to give a non-parametric estimate of the variance of our test statistic under the null hypothesis. Using a simulation study we demonstrate that the test obtains its target significance level, with large power, when compared to an existing standard parametric test that uses the bispectrum. Further we show how the proposed test can be used to identify the source of non-linearity due to interactions at specific frequencies. We also investigate implications for heuristic diagnosis of non-stationarity.Third-order moment, bispectrum, non-linear, nonstationary,

Funding grant proposals for scientific research: retrospective analysis of scores by members of grant review panel

Objective To quantify randomness and cost when choosing health and medical research projects for funding

Space-time variation of malaria incidence in Yunnan province, China

BACKGROUND Understanding spatio-temporal variation in malaria incidence provides a basis for effective disease control planning and monitoring. METHODS Monthly surveillance data between 1991 and 2006 for Plasmodium vivax and Plasmodium falciparum malaria across 128 counties were assembled for Yunnan, a province of China with one of the highest burdens of malaria. County-level Bayesian Poisson regression models of incidence were constructed, with effects for rainfall, maximum temperature and temporal trend. The model also allowed for spatial variation in county-level incidence and temporal trend, and dependence between incidence in June-September and the preceding January-February. RESULTS Models revealed strong associations between malaria incidence and both rainfall and maximum temperature. There was a significant association between incidence in June-September and the preceding January-February. Raw standardised morbidity ratios showed a high incidence in some counties bordering Myanmar, Laos and Vietnam, and counties in the Red River valley. Clusters of counties in south-western and northern Yunnan were identified that had high incidence not explained by climate. The overall trend in incidence decreased, but there was significant variation between counties. CONCLUSION Dependence between incidence in summer and the preceding January-February suggests a role of intrinsic host-pathogen dynamics. Incidence during the summer peak might be predictable based on incidence in January-February, facilitating malaria control planning, scaled months in advance to the magnitude of the summer malaria burden. Heterogeneities in county-level temporal trends suggest that reductions in the burden of malaria have been unevenly distributed throughout the province.This project was supported by a University of Queensland New Research Scientist Start-Up Fund grant. RWS is a Wellcome Trust Principal Research Fellow (#079080) and receives additional support from the Wellcome Trust for the Malaria Atlas Project (MAP, http://www.map.ox.ac.uk)

Missing the point: are journals using the ideal number of decimal places? [version 3; referees: 2 approved]

Background: The scientific literature is growing in volume and reducing in readability. Poorly presented numbers decrease readability by either fatiguing the reader with too many decimal places, or confusing the reader by not using enough decimal places, and so making it difficult to comprehend differences between numbers. There are guidelines for the ideal number of decimal places, and in this paper I examine how often percents meet these guidelines. Methods: Percents were extracted from the abstracts of research articles published in 2017 in 23 selected journals. Percents were excluded if they referred to a statistical interval, typically a 95% confidence interval. Counts and percents were calculated for the number of percents using too few or too many decimal places, and these percents were compared between journals. Results: The sample had over 43,000 percents from around 9,500 abstracts. Only 55% of the percents were presented according to the guidelines. The most common issue was using too many decimal places (33%), rather than too few (12%). There was a wide variation in presentation between journals, with the range of ideal presentation from a low of 53% (JAMA) to a high of 80% (Lancet Planetary Health). Conclusions: Many percents did not adhere to the guidelines on using decimal places. Using the recommended number of decimal places would make papers easier to read and reduce the burden on readers, and potentially improve comprehension. It should be possible to provide automated feedback to authors on which numbers could be better presented

Missing the point: are journals using the ideal number of decimal places? [version 2; referees: 2 approved]

Background: The scientific literature is growing in volume and reducing in readability. Poorly presented numbers decrease readability by either fatiguing the reader with too many decimal places, or confusing the reader by not using enough decimal places, and so making it difficult to comprehend differences between numbers. There are guidelines for the ideal number of decimal places, and in this paper I examine how often percents meet these guidelines. Methods: Percents were extracted from the abstracts of research articles published in 2017 in 23 selected journals. Percents were excluded if they referred to a statistical interval, typically a 95% confidence interval. Counts and percents were calculated for the number of percents using too few or too many decimal places, and these percents were compared between journals. Results: The sample had over 43,000 percents from around 9,500 abstracts. Only 55% of the percents were presented according to the guidelines. The most common issue was using too many decimal places (33%), rather than too few (12%). There was a wide variation in presentation between journals, with the range of ideal presentation from a low of 53% (JAMA) to a high of 80% (Lancet Planetary Health).  Conclusions: Many percents did not adhere to the guidelines on using decimal places. Using the recommended number of decimal places would make papers easier to read and reduce the burden on readers, and potentially improve comprehension. It should be possible to provide automated feedback to authors on which numbers could be better presented

Meta-research: Using research to increase the value of health and medical research

My application for an NHMRC Senior Research Fellow

Open versus closed IV infusion systems: a state based model to predict risk of catheter associated blood stream infections

Objectives - To quantify the change in risk of central line associated blood stream infection (CLABSI) following the introduction of a closed infusion container in intensive care units (ICUs) in two Latin American cities. Design - A state-space model was used to describe the flow of admissions through the ICU. This approach correctly treats infection as a time-dependent covariate. Results - A closed system reduced the risk of CLABSI. The hazard ratios for the closed versus open container were between 0.15 and 0.31 (p valuesConclusions - The data reveal costs are saved and health benefits gained from fewer cases of CLABSI after adoption of a closed infusion system. Information is required on the costs of implementing the closed system widely in these settings

Methodological challenges when estimating the effects of season and seasonal exposures on birth outcomes

Background Many previous studies have found seasonal patterns in birth outcomes, but with little agreement about which season poses the highest risk. Some of the heterogeneity between studies may be explained by a previously unknown bias. The bias occurs in retrospective cohorts which include all births occurring within a fixed start and end date, which means shorter pregnancies are missed at the start of the study, and longer pregnancies are missed at the end. Our objective was to show the potential size of this bias and how to avoid it. Methods To demonstrate the bias we simulated a retrospective birth cohort with no seasonal pattern in gestation and used a range of cohort end dates. As a real example, we used a cohort of 114,063 singleton births in Brisbane between 1 July 2005 and 30 June 2009 and examined the bias when estimating changes in gestation length associated with season (using month of conception) and a seasonal exposure (temperature). We used survival analyses with temperature as a time-dependent variable. Results We found strong artificial seasonal patterns in gestation length by month of conception, which depended on the end date of the study. The bias was avoided when the day and month of the start date was just before the day and month of the end date (regardless of year), so that the longer gestations at the start of the study were balanced by the shorter gestations at the end. After removing the fixed cohort bias there was a noticeable change in the effect of temperature on gestation length. The adjusted hazard ratios were flatter at the extremes of temperature but steeper between 15 and 25°C. Conclusions Studies using retrospective birth cohorts should account for the fixed cohort bias by removing selected births to get unbiased estimates of seasonal health effects