Convergence of marine megafauna movement patterns in coastal and open oceans.

The extent of increasing anthropogenic impacts on large marine vertebrates partly depends on the animals' movement patterns. Effective conservation requires identification of the key drivers of movement including intrinsic properties and extrinsic constraints associated with the dynamic nature of the environments the animals inhabit. However, the relative importance of intrinsic versus extrinsic factors remains elusive. We analyze a global dataset of ∼2.8 million locations from >2,600 tracked individuals across 50 marine vertebrates evolutionarily separated by millions of years and using different locomotion modes (fly, swim, walk/paddle). Strikingly, movement patterns show a remarkable convergence, being strongly conserved across species and independent of body length and mass, despite these traits ranging over 10 orders of magnitude among the species studied. This represents a fundamental difference between marine and terrestrial vertebrates not previously identified, likely linked to the reduced costs of locomotion in water. Movement patterns were primarily explained by the interaction between species-specific traits and the habitat(s) they move through, resulting in complex movement patterns when moving close to coasts compared with more predictable patterns when moving in open oceans. This distinct difference may be associated with greater complexity within coastal microhabitats, highlighting a critical role of preferred habitat in shaping marine vertebrate global movements. Efforts to develop understanding of the characteristics of vertebrate movement should consider the habitat(s) through which they move to identify how movement patterns will alter with forecasted severe ocean changes, such as reduced Arctic sea ice cover, sea level rise, and declining oxygen content.

Bayesian spatial and spatio-temporal approaches to modelling dengue fever: a systematic review.

Dengue fever (DF) is one of the world's most disabling mosquito-borne diseases, with a variety of approaches available to model its spatial and temporal dynamics. This paper aims to identify and compare the different spatial and spatio-temporal Bayesian modelling methods that have been applied to DF and examine influential covariates that have been reportedly associated with the risk of DF. A systematic search was performed in December 2017, using Web of Science, Scopus, ScienceDirect, PubMed, ProQuest and Medline (via Ebscohost) electronic databases. The search was restricted to refereed journal articles published in English from January 2000 to November 2017. Thirty-one articles met the inclusion criteria. Using a modified quality assessment tool, the median quality score across studies was 14/16. The most popular Bayesian statistical approach to dengue modelling was a generalised linear mixed model with spatial random effects described by a conditional autoregressive prior. A limited number of studies included spatio-temporal random effects. Temperature and precipitation were shown to often influence the risk of dengue. Developing spatio-temporal random-effect models, considering other priors, using a dataset that covers an extended time period, and investigating other covariates would help to better understand and control DF transmission.

Bayesian Networks to Compare Pest Control Interventions on Commodities Along Agricultural Production Chains.

The production of an agricultural commodity involves a sequence of processes: planting/growing, harvesting, sorting/grading, postharvest treatment, packing, and exporting. A Bayesian network has been developed to represent the level of potential infestation of an agricultural commodity by a specified pest along an agricultural production chain. It reflects the dependency of this infestation on the predicted level of pest challenge, the anticipated susceptibility of the commodity to the pest, the level of impact from pest control measures as designed, and any variation from that due to uncertainty in measure efficacy. The objective of this Bayesian network is to facilitate agreement between national governments of the exporters and importers on a set of phytosanitary measures to meet specific phytosanitary measure requirements to achieve target levels of protection against regulated pests. The model can be used to compare the performance of different combinations of measures under different scenarios of pest challenge, making use of available measure performance data. A case study is presented using a model developed for a fruit fly pest on dragon fruit in Vietnam; the model parameters and results are illustrative and do not imply a particular level of fruit fly infestation of these exports; rather, they provide the most likely, alternative, or worst-case scenarios of the impact of measures. As a means to facilitate agreement for trade, the model provides a framework to support communication between exporters and importers about any differences in perceptions of the risk reduction achieved by pest control measures deployed during the commodity production chain.

Using a Bayesian network to clarify areas requiring research in a host-pathogen system.

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease-driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host-pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious-disease systems.

Creating a Sustainability Scorecard as a predictive tool for measuring the complex social, economic and environmental impacts of industries, a case study: assessing the viability and sustainability of the dairy industry.

Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.

Understanding the spatial distribution and hot spots of collared Bornean elephants in a multi-use landscape.

In the Kinabatangan floodplain, Sabah, Malaysian Borneo, oil palm and settlements have reduced and fragmented lowland tropical forests, home to around 200 endangered Bornean elephants (Elephas maximus borneensis). In this region, elephants range within forests, oil palm and community areas. The degree to which elephants are using these areas remains unclear. We used GPS telemetry data from 2010 to 2020 for 14 collared elephants to map their entire known ranges and highly used areas (hot spots) across four land use categories and estimate time spent within these. The use of land use types across elephants varied significantly. Typically, females had strong fidelity to forests, yet many of these forests are threatened with conversion. For the three males, and several females, they heavily used oil palm estates, and this may be due to decreased landscape permeability or foraging opportunities. At the pooled level, the entire range and hot spot extents, constituted 37% and 34% for protected areas, respectively, 8% and 11% for unprotected forests, 53% and 51% for oil palm estates, and 2% for community areas. Protecting all forested habitats and effectively managing areas outside of protected areas is necessary for the long-term survival of this population.

Effect of vitamin D supplementation on muscle strength: a systematic review and meta-analysis.

UNLABELLED: This systematic review demonstrates that vitamin D supplementation does not have a significant effect on muscle strength in vitamin D replete adults. However, a limited number of studies demonstrate an increase in proximal muscle strength in adults with vitamin D deficiency. INTRODUCTION: The purpose of this study is to systematically review the evidence on the effect of vitamin D supplementation on muscle strength in adults. METHODS: A comprehensive systematic database search was performed. Inclusion criteria included randomised controlled trials (RCTs) involving adult human participants. All forms and doses of vitamin D supplementation with or without calcium supplementation were included compared with placebo or standard care. Outcome measures included evaluation of strength. Outcomes were compared by calculating standardised mean difference (SMD) and 95% confidence intervals. RESULTS: Of 52 identified studies, 17 RCTs involving 5,072 participants met the inclusion criteria. Meta-analysis showed no significant effect of vitamin D supplementation on grip strength (SMD -0.02, 95%CI -0.15,0.11) or proximal lower limb strength (SMD 0.1, 95%CI -0.01,0.22) in adults with 25(OH)D levels > 25 nmol/L. Pooled data from two studies in vitamin D deficient participants (25(OH)D <25 nmol/L) demonstrated a large effect of vitamin D supplementation on hip muscle strength (SMD 3.52, 95%CI 2.18, 4.85). CONCLUSION: Based on studies included in this systematic review, vitamin D supplementation does not have a significant effect on muscle strength in adults with baseline 25(OH)D >25 nmol/L. However, a limited number of studies demonstrate an increase in proximal muscle strength in adults with vitamin D deficiency.

Spatial and temporal clusters of Barmah Forest virus disease in Queensland, Australia.

OBJECTIVE: To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems and spatial scan statistic (SaTScan). METHODS: We obtained BFV disease cases, population and statistical local areas (SLAs) boundary data from Queensland Health and Australian Bureau of Statistics, respectively, during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200 km radius and varying time windows from 1 to 12 months were chosen (for the space-time analysis). RESULTS: The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. CONCLUSIONS: This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing ongoing surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.

Test-retest reliability of hand-held dynamometry and functional tests in systemic lupus erythematosus.

The aim of this study was to evaluate the test-retest reliability and determine the degree of measurement error of tests of isometric muscle strength and upper and lower limb function in women with systemic lupus erythematosus (SLE). Twelve women with SLE (age 39.8 ± 10 years) were assessed on two occasions separated by a 7-10-day interval. Strength of six muscle groups was measured using a hand-held dynamometer; function was measured by the 30-s sit to stand test and the 30-s 1 kg arm lift. Relative reliability was estimated using the intraclass correlation coefficient (ICC), model 2,1 (ICC2,1). Absolute reliability was estimated using standard error measurement and the minimal detectable difference was calculated. All ICCs were greater than 0.87. Muscle strength would need to increase by between 18% and 39% in women with SLE to be 95% confident of detecting real changes. The functional tests demonstrated a systematic bias between trials. This study demonstrates that hand-held dynamometry in SLE can be performed with excellent reliability. Further work needs to be completed to determine the number of trials necessary for both the 30-s sit to stand and 30-s 1 kg arm lift to decrease the systematic bias.

Pollutant concentrations within households in Lao PDR and association with housing characteristics and occupants' activities.

The paper presents the results of a study conducted to investigate indoor air quality within residential dwellings in Lao PDR. Results from PM(10), CO, and NO(2) measurements inside 167 dwellings in Lao PDR over a five month period (December 2005-April 2006) are discussed as a function of household characteristics and occupant activities. Extremely high PM(10) and NO(2) concentrations (12 h mean PM(10) concentrations 1275 ± 98 µg m(-3) and 1183 ± 99 µg m(-3) in Vientiane and Bolikhamxay provinces, respectively; 12 h mean NO(2) concentrations 1210 ± 94 µg m(-3) and 561 ± 45 µg m(-3) in Vientiane and Bolikhamxay, respectively) were measured within the dwellings. Correlations, ANOVA analysis (univariate and multivariate), and linear regression results suggest a substantial contribution from cooking and smoking. The PM(10) concentrations were significantly higher in houses without a chimney compared to houses in which cooking occurred on a stove with a chimney. However, no significant differences in pollutant concentrations were observed as a function of cooking location. Furthermore, PM(10) and NO(2) concentrations were higher in houses in which smoking occurred, suggestive of a relationship between increased indoor concentrations and smoking (0.05 < p < 0.10). Resuspension of dust from soil floors was another significant source of PM(10) inside the house (634 µg m(-3), p < 0.05).

Association between indoor air pollution measurements and respiratory health in women and children in Lao PDR.

UNLABELLED: This article presents the results of a study on the association between measured air pollutants and the respiratory health of resident women and children in Lao PDR, one of the least developed countries in Southeast Asia. The study, commissioned by the World Health Organisation, included PM(10), CO and NO(2) measurements made inside 181 dwellings in nine districts within two provinces in Lao PDR over a 5-month period (12/05-04/06), and respiratory health information (via questionnaires and peak expiratory flow rate (PEFR) measurements) for all residents in the same dwellings. Adjusted odds ratios were calculated separately for each health outcome using binary logistic regression. There was a strong and consistent positive association between NO(2) and CO for almost all questionnaire-based health outcomes for both women and children. Women in dwellings with higher measured NO(2) had more than triple of the odds of almost all of the health outcomes, and higher concentrations of NO(2) and CO were significantly associated with lower PEFR. This study supports a growing literature confirming the role of indoor air pollution in the burden of respiratory disease in developing countries. The results will directly support changes in health and housing policy in Lao PDR. PRACTICAL IMPLICATIONS: This is the first study that investigated indoor air quality and its impact within residential dwellings in Lao PDR, which is one of the poorest and least developed countries in south-east Asia, with a life-expectancy of 56 years in 2008. While there have been other studies published on indoor air quality in other developing countries, the situation in Laos is different because the majority of houses in Laos used wood stoves, and therefore, emissions from wood burning are the dominant sources of indoor air pollution. In other countries, and studies, while emission from wood burning was investigated, wood was rarely the main or the only fuel used, as the houses used in addition (or solely) dung, kerosene or coal. The study quantified, for the first time, concentrations in houses two provinces in Laos PDR and shed light on the impact of human activities and urban design on pollutant concentrations and respiratory health. This study contributes to the accumulation of evidence to provide more reliable estimates of risk and a more informed basis for decision-making by concerned governments and communities.

Perceptions of the ethical conduct of cancer trials by oncology nurses.

Informed consent and subject protection are internationally mandated requirements for the ethical conduct of research; however, the monitoring of the day-to-day conduct of research may be insufficient for ensuring consistent compliance with required ethical ideals. Oncology nurses were surveyed about their perceptions of ethical issues relevant to cancer trials research. Utilising an investigator-developed instrument, multi-item scales assessed six ethical domains. Of 192 respondents, 95% or more held definite views in 12 of 15 items about patient understanding of cancer trials, informed consent and the welfare of participants. Approximately 95% perceived that patients consented freely and knew how to withdraw from a trial, and 81% perceived better monitoring of trial than non-trial patients. However, more than 80% of respondents perceived that at times patients had unrealistic expectations of participation, and more than 50% perceived that participants sometimes did not understand the nature and risk of cancer trials. Although the conative attributes of patients place limits on the goals of bioethics, the results of this study show first that oncology nurses have opinions about ethical constructs directly linked to the daily conduct of cancer clinical trials, and second that this link warrants further investigation in order to benchmark trial conduct against the ideals of ethical research.

Characterization of expiration air jets and droplet size distributions immediately at the mouth opening.

Size distributions of expiratory droplets expelled during coughing and speaking and the velocities of the expiration air jets of healthy volunteers were measured. Droplet size was measured using the interferometric Mie imaging (IMI) technique while the particle image velocimetry (PIV) technique was used for measuring air velocity. These techniques allowed measurements in close proximity to the mouth and avoided air sampling losses. The average expiration air velocity was 11.7 m/s for coughing and 3.9 m/s for speaking. Under the experimental setting, evaporation and condensation effects had negligible impact on the measured droplet size. The geometric mean diameter of droplets from coughing was 13.5 µm and it was 16.0 µm for speaking (counting 1-100). The estimated total number of droplets expelled ranged from 947 to 2085 per cough and 112-6720 for speaking. The estimated droplet concentrations for coughing ranged from 2.4 to 5.2 cm-3 per cough and 0.004-0.223 cm-3 for speaking.

Ozone modifies associations between temperature and cardiovascular mortality: analysis of the NMMAPS data.

OBJECTIVES: Both ambient ozone and temperature are associated with human health. However, few data are available on whether ozone modifies temperature effects. This study aims to explore whether ozone modified associations between maximum temperature and cardiovascular mortality in the USA. METHODS: The authors obtained data from the US National Morbidity, Mortality, and Air Pollution Study (NMMAPS) website. They used two time-series Poisson regression models (a response surface model and a stratification model) to examine whether ozone modified associations between maximum temperature and cardiovascular mortality (CVM) in 95 large US communities during 1987-2000 in summer (June to September). Bayesian meta-analysis was used to pool estimates in each community. RESULTS: The response surface model was used to examine the joint effects of temperature and ozone on CVM in summer. Results indicate that ozone positively modified the temperature-CVM associations across the different regions. The stratification model quantified the temperature-CVM associations across different levels of ozone. Results show that in general the higher the ozone concentration, the stronger the temperature-CVM associations across the communities. A 10 degrees C increase in temperature on the same day was associated with an increase in CVM by 1.17% and 8.31% for the lowest and highest level of ozone concentrations in all communities, respectively. CONCLUSION: Ozone modified temperature effects in different regions in the USA. It is important to evaluate the modifying role of ozone when estimating temperature-related health impacts and to further investigate the reasons behind the regional variability and mechanism for the interaction between temperature and ozone.

A Bayesian approach to assess interaction between known risk factors: the risk of lung cancer from exposure to asbestos and smoking.

We review the literature on the combined effect of asbestos exposure and smoking on lung cancer, and explore a Bayesian approach to assess evidence of interaction. Previous approaches have focussed on separate tests for an additive or multiplicative relation. We extend these approaches by exploring the strength of evidence for either relation using approaches which allow the data to choose between both models. We then compare the different approaches.

Evaluation of oestrogen and progesterone receptor status in HER-2 positive breast carcinomas and correlation with outcome.

AIM: HER-2/neu amplification occurs in 15-25% of breast carcinomas. This oncogene, also referred to as c-erbB-2, encodes a transmembrane tyrosine kinase receptor belonging to the epidermal growth factor receptor family. HER-2 over-expression is reported to be associated with a poor prognosis in breast carcinoma patients and in some studies is associated with a poorer response to anti-oestrogen therapy. These patients are less likely to benefit from CMF (cyclophosphamide, methotrexate, fluorouracil)-based chemotherapy compared with anthracycline-based chemotherapy. The aim of this study was to evaluate breast carcinomas to determine hormone receptor status and if there is a difference in breast cancer specific survival for HER-2 positive patients. METHODS: A total of 591 breast carcinomas were evaluated using immunohistochemistry (IHC) for oestrogen receptor (ERp), progesterone receptor (PRp) and three different HER-2 antibodies (CB11, A0485 and TAB250). Percentage of tumour cells and intensity of staining for ERp were evaluated using a semiquantitative method. RESULTS: Of the 591 tumours, 91 (15.4%) showed 3+ membrane staining for HER-2 with one or more antibodies. Of these 91 tumours, 41 (45.1%) were ERp+/PRp+, seven (7.7%) were ERp+/PR-, six (6.6%) were ERp-/PRp+ and 37 (40.7%) were ERp-/PR-. Of HER-2 positive tumours, 5.5% showed >80% 3+ staining for ERp compared with 31.8% of 0-2+ HER-2 tumours; 24.2% of HER-2-positive tumours showed 60% or more cells with 2+ or 3+ staining for ERp. Treatment data were available for 209 patients and no difference was observed in breast cancer specific survival (BCSS) with HER-2 status and tamoxifen. CONCLUSION: Oestrogen receptor status cannot be used to select tumours for evaluation of HER-2 status, and oestrogen and progesterone receptor positivity does not preclude a positive HER-2 status. There is a higher proportion of ERp negative tumours associated with HER-2 positivity, however, more than 20% of HER-2 positive tumours show moderate or strong staining for ERp. HER-2 positive patients in this study did not show an adverse BCSS with tamoxifen treatment unlike some previous studies.

Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors.

Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement ('random error') than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts -19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements.

Bayesian meta-analysis, with application to studies of ETS and lung cancer.

Meta-analysis enables researchers to combine the results of several studies to assess the information they provide as a whole. It has been used to give a systematic overview of many areas in which data on a possible association between an exposure and an outcome have been collected in a number of studies but where the overall picture remains obscure, both as to the existence or size of the effect. This paper outlines some innovations in meta-analysis, based on using Markov chain Monte Carlo (MCMC) techniques for implementing Bayesian hierarchical models, and compares these with a more well-known random effects (RE) model. The new techniques allow different aspects of variation to be incorporated into descriptions of the association, and in particular enable researchers to better quantify differences between studies. Both the classical and Bayesian methods are applied, in this paper, to the current collection of studies of the association between incidence of lung cancer in female never-smokers and exposure to environmental tobacco smoke (ETS), both in the home through spousal smoking and in the workplace. In this paper it is demonstrated that compared with the RE model, the Bayesian methods: (a) allow more detailed modeling of study heterogeneity to be incorporated; (b) are relatively robust against a wide choice of specifications of such information on heterogeneity; (c) allow for more detailed and satisfactory statements to be made, not only about the overall risk but about the individual studies, on the basis of the combined information. For the workplace exposure data set, the Bayesian methods give a somewhat lower overall estimate of relative risk of lung cancer associated with ETS, indicating the care that needs to be taken in using point estimates based on any one method of analysis. On the larger spousal data set the methods give similar answers. Some of the other concerns with meta-analysis are also considered. These include: consistency between different geographic areas (Asia and the United States), and our studies show that Bayesian methods permit an account of the overall picture to be taken, thus improving the ability to estimate accurately in the subgroups; and publication bias which, as shown with the spousal exposure data, may lead to an inflated excess risk.

Socioeconomic status and infant mortality in Australia: a national study of small urban areas, 1985-89.

This study uses small-area data for the period 1985-89 to examine the relationship between socioeconomic status and infant mortality in each of the mainland State capital cities of Australia. An unweighted OLS regression analysis based on 195 Statistical Local Areas (SLAs) that recorded five or more deaths over the reference period shows that standardised infant mortality ratios were significantly higher in areas with greater concentrations of low income families. This relationship was independent of the effects of low birthweight, Aboriginality, ethnicity and variability between each of the capital cities. To test for the robustness of this result a sensitivity analysis was undertaken. This involved (a) performing a Principal Components Analysis on a wide range of sociodemographic variables to derive factor scales that were subsequently included in a regression analysis, (b) using weighted least-squares regression and a Poisson generalised linear model and (c) including in the analysis all SLAs irrespective of the number of infant deaths. The sensitivity analysis supported the results of this study, thus validating the observed association between the socioeconomic characteristics of urban areas and their rate of infant mortality. Despite marked reductions in overall rates of infant mortality over the last century in Australia. socioeconomic disparities were still evident during the mid-to-late 1980s. Whether and to what extent this situation persisted during the early-to-mid 1990s will be known in the near future when the next collection of area-based data are publicly released. The results of this study, therefore, represent an important baseline against which more contemporary national trends can be monitored.

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions.

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to 'empty' reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence.