How much is tuberculosis screening worth? Estimating the value of active case finding for tuberculosis in South Africa, China, and India

BACKGROUND: Current approaches are unlikely to achieve the aggressive global tuberculosis (TB) control targets set for 2035 and beyond. Active case finding (ACF) may be an important tool for augmenting existing strategies, but the cost-effectiveness of ACF remains uncertain. Program evaluators can often measure the cost of ACF per TB case detected, but how this accessible measure translates into traditional metrics of cost-effectiveness, such as the cost per disability-adjusted life year (DALY), remains unclear. METHODS: We constructed dynamic models of TB in India, China, and South Africa to explore the medium-term impact and cost-effectiveness of generic ACF activities, conceptualized separately as discrete (2-year) campaigns and as continuous activities integrated into ongoing TB control programs. Our primary outcome was the cost per DALY, measured in relationship to the cost per TB case actively detected and started on treatment. RESULTS: Discrete campaigns costing up to $1,200 (95$3,800 (95% UR 2,706–6,392) in China, and $9,400 (95$1,000 to detect and initiate treatment for each extra case of active TB. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-014-0216-0) contains supplementary material, which is available to authorized users

A comparison of mean winds and gravity wave activity in the northern and southern polar MLT

Mean winds and waves observed in the mesosphere and lower thermosphere with MF radars located at Davis (69°S, 78°E) and Poker Flat (65°N, 147°W) are compared. Measurements covering the period from 1999 to mid 2000 show differences in the strength of the horizontal wind fields. In the southern hemisphere the zonal and meridional winds reach their maximum values near the summer solstice, but are delayed by 2–3 weeks in the northern hemisphere. Gravity wave variances also show significant differences, as do the strength of vertical velocities.Andrew Dowdy and Robert A. Vincent, Kiyoshi Igarashi and Yasuhiro Murayama, Damian J. Murph

Using historical tropical cyclone climate datasets to examine wind speed recurrence for coastal Australia

Likelihood estimates of extreme winds, including those from tropical cyclones (TCs) at certain locations are used to inform wind load standards for structural design. Here, wind speed average recurrence intervals (ARIs) determined from TC climate data dating back to the 1970s in two quantile–quantile adjusted reanalysis datasets (ERA5 and BARRA [1990]), and best-track observations for context, were compared with Standardized ARIs (AS/NZS) across seven tropical and two subtropical Australian inland coastal regions. The novelty of this work lies in determining TC-wind speed ARIs from a range of datasets that are not typically used to evaluate this metric. Inherent differences between the data used to determine the Standard ARIs (large sample size allow for larger extrapolations; GEV function) and TC data ARIs (smaller sample size and less certain data; the more asymptotic Lognormal/Weibull functions are used) led to the use of different extreme value functions. Results indicated that although these are two distinct ways of determining design wind speeds, when they are considered equivalent, there was a moderate reproduction of the ARI curves with respect to the Standard in both reanalysis datasets, suggesting that similar analyses using climate model products can provide useful information on these types of metrics with some caveats. Trends in TC wind strength affecting coastal Australia were also analyzed, indicating a potential slight downtrend in tropical West coast TC wind strength and slight uptrend for tropical East coast TC wind strength, noting considerable uncertainty given the short time period and limitations of data quality including over longer time periods. Such trends are not only limited to the relationship between TC intensity and anthropogenic warming, but also to regional changes in TC frequency and track direction. This could lead to significant trends emerging in regional Australian TC wind gust strength before several decades of warming have occurred. It is hoped that climate models can provide both longer-term and a more homogenous base for these types of evaluations and subsequent projections with respect to climate change simulations. © 2022, Crown

Multi-decadal increase of forest burned area in Australia is linked to climate change

Fire activity in Australia is strongly affected by high inter-annual climate variability and extremes. Through changes in the climate, anthropogenic climate change has the potential to alter fire dynamics. Here we compile satellite (19 and 32 years) and ground-based (90 years) burned area datasets, climate and weather observations, and simulated fuel loads for Australian forests. Burned area in Australia’s forests shows a linear positive annual trend but an exponential increase during autumn and winter. The mean number of years since the last fire has decreased consecutively in each of the past four decades, while the frequency of forest megafire years (>1 Mha burned) has markedly increased since 2000. The increase in forest burned area is consistent with increasingly more dangerous fire weather conditions, increased risk factors associated with pyroconvection, including fire-generated thunderstorms, and increased ignitions from dry lightning, all associated to varying degrees with anthropogenic climate change

Assessment and improvement of biotransfer models to cow’s milk and beef used in exposure assessment tools for organic pollutants

The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants

Comparison of various climate change projections of eastern Australian rainfall

The Australian eastern seaboard is a distinct climate entity from the interior of the continent, with different climatic influences on each side of the Great Dividing Range. Therefore, it is plausible that downscaling of global climate models could reveal meaningful regional detail, or ‘added value’, in the climate change signal of mean rainfall change in eastern Australia un-der future scenarios. However, because downscaling is typically done using a limited set of global climate models and downscaling methods, the results from a downscaling study may not represent the range of uncertainty in plausible projected change for a region suggested by the ensemble of host global climate models. A complete and unbiased representation of the plausible changes in the climate is essential in producing climate projections useful for future planning. As part of this aim it is important to quantify any differences in the change signal between global climate models and downscaling, and understand the cause of these differ-ences in terms of plausible added regional detail in the climate change signal, the impact of sub-sampling global climate models and the effect of the downscaling models themselves. Here we examine rainfall projections in eastern Australia under a high emissions scenario by late in the century from ensembles of global climate models, two dynamical downscaling models and one statistical downscaling model. We find no cases where all three downscaling methods show the same clear regional spatial detail in the change signal that is distinct from the host models. However, some downscaled projections suggest that the eastern seaboard could see little change in spring rainfall, in contrast to the substantial rainfall decrease inland. The change signal in the downscaled outputs is broadly similar at the large scale in the various model outputs, with a few notable exceptions. For example, the model median from dynamical downscaling projects a rainfall increase over the entirety of eastern Australia in autumn that is greater than the global models. Also, there are some instances where a downscaling method produces changes outside the range of host models over eastern Australia as a whole, thus ex-panding the projected range of uncertainty. Results are particularly uncertain for summer, where no two downscaling studies clearly agree. There are also some confounding factors from the model configuration used in downscaling, where the particular zones used for statis-tical models and the model components used in dynamical models have an influence on results and produce additional uncertainty

Connections of climate change and variability to large and extreme forest fires in southeast Australia

The 2019/20 Black Summer bushfire disaster in southeast Australia was unprecedented: the extensive area of forest burnt, the radiative power of the fires, and the extraordinary number of fires that developed into extreme pyroconvective events were all unmatched in the historical record. Australia’s hottest and driest year on record, 2019, was characterised by exceptionally dry fuel loads that primed the landscape to burn when exposed to dangerous fire weather and ignition. The combination of climate variability and long-term climate trends generated the climate extremes experienced in 2019, and the compounding effects of two or more modes of climate variability in their fire-promoting phases (as occurred in 2019) has historically increased the chances of large forest fires occurring in southeast Australia. Palaeoclimate evidence also demonstrates that fire-promoting phases of tropical Pacific and Indian ocean variability are now unusually frequent compared with natural variability in preindustrial times. Indicators of forest fire danger in southeast Australia have already emerged outside of the range of historical experience, suggesting that projections made more than a decade ago that increases in climate-driven fire risk would be detectable by 2020, have indeed eventuated. The multiple climate change contributors to fire risk in southeast Australia, as well as the observed non-linear escalation of fire extent and intensity, raise the likelihood that fire events may continue to rapidly intensify in the future. Improving local and national adaptation measures while also pursuing ambitious global climate change mitigation efforts would provide the best strategy for limiting further increases in fire risk in southeast Australia

Rapid Diagnosis of Tuberculosis with the Xpert MTB/RIF Assay in High Burden Countries: A Cost-Effectiveness Analysis

A cost-effectiveness study by Frank Cobelens and colleagues reveals that Xpert MTB/RIF is a cost-effective method of tuberculosis diagnosis that is suitable for use in low- and middle-income settings