Investigating health impacts of natural resource extraction projects in Burkina Faso, Ghana, Mozambique, and Tanzania: protocol for a mixed methods study

Natural resource extraction projects offer both opportunities and risks for sustainable development and health in host communities. Often, however, the health of the community suffers. Health impact assessment (HIA) can mitigate the risks and promote the benefits of development but is not routinely done in the developing regions that could benefit the most.; Our study aims to investigate health and health determinants in regions affected by extractive industries in Burkina Faso, Ghana, Mozambique, and Tanzania. The evidence generated in our study will inform a policy dialogue on how HIA can be promoted as a regulatory approach as part of the larger research initiative called the HIA4SD (Health impact assessment for sustainable development) project.; The study is a concurrent triangulation, mixed methods, multi-stage, multi-focus project that specifically addresses the topics of governance and policy, social determinants of health, health economics, health systems, maternal and child health, morbidity and mortality, and environmental determinants, as well as the associated health outcomes in natural resource extraction project settings across four countries. To investigate each of these health topics, the project will (1) use existing population-level databases to quantify incidence of disease and other health outcomes and determinants over time using time series analysis; (2) conduct two quantitative surveys on mortality and cost of disease in producer regions; and (3) collect primary qualitative data using focus groups and key informant interviews describing community perceptions of the impacts of extraction projects on health and partnership arrangements between the projects and local and national governance. Differences in health outcomes and health determinants between districts with and without an extraction project will be analyzed using matched geographical analyses in quasi-Poisson regression models and binomial regression models. Costs to the health system and to the households from diseases found to be associated with projects in each country will be estimated retrospectively.; Fieldwork for the study began in February 2019 and concluded in February 2020. At the time of submission, qualitative data collection had been completed in all four study countries. In Burkina Faso, 36 focus group discussions and 74 key informant interviews were conducted in three sites. In Ghana, 34 focus group discussions and 64 key informant interviews were conducted in three sites. In Mozambique, 75 focus group discussions and 103 key informant interviews were conducted in four sites. In Tanzania, 36 focus group discussions and 84 key informant interviews were conducted in three sites. Quantitative data extraction and collection is ongoing in all four study countries. Ethical approval for the study was received in all four study countries prior to beginning the fieldwork. Data analyses are underway and results are expected to be published in 2020 and 2021.; Disentangling the complex interactions of resource extraction projects with their host communities requires an integrative approach drawing on many methodologies under the HIA umbrella. By using complementary data sources to address the question of population health in project areas from several angles, bias and missing data will be reduced, generating high-quality evidence to aid countries in moving toward sustainable development.; DERR1-10.2196/17138

Continuing Progress towards a Phylogeny of Tachinidae

Readers of this newsletter are likely familiar with our ongoing project to establish a framework phylogeny of world Tachinidae (see articles in The Tachinid Times 26 and 27). This collaborative project, involving myself, Jim O’Hara, Kevin Moulton, Pierfilippo Cerretti, Isaac Winkler and a long list of collaborating tachinidophiles was initiated in 2012 with funding from the U.S. National Science Foundation. Our goal is to produce a robust phylogenetic framework of Tachinidae that can be used to inform tachinid taxonomy, systematics research, and the patterns of tachinid evolution. In previous issues of The Tachinid Times we summarized our progress to date in terms of obtaining taxa (e.g., Cerretti et al. 2013, O’Hara et al. 2014) and some of our preliminary phylogenetic findings (Stireman et al. 2013, Winkler et al. 2014). Here, we provide a brief update on some of our recent progress and associated products

Episodic Radiations in the Fly Tree of Life

Flies are one of four superradiations of insects (along with beetles, wasps, and moths) that account for the majority of animal life on Earth. Diptera includes species known for their ubiquity (Musca domestica house fly), their role as pests (Anopheles gambiae malaria mosquito), and their value as model organisms across the biological sciences (Drosophila melanogaster). A resolved phylogeny for flies provides a framework for genomic, developmental, and evolutionary studies by facilitating comparisons across model organisms, yet recent research has suggested that fly relationships have been obscured by multiple episodes of rapid diversification. We provide a phylogenomic estimate of fly relationships based on molecules and morphology from 149 of 157 families, including 30 kb from 14 nuclear loci and complete mitochondrial genomes combined with 371 morphological characters. Multiple analyses show support for traditional groups (Brachycera, Cyclorrhapha, and Schizophora) and corroborate contentious findings, such as the anomalous Deuterophlebiidae as the sister group to all remaining Diptera. Our findings reveal that the closest relatives of the Drosophilidae are highly modified parasites (including the wingless Braulidae) of bees and other insects. Furthermore, we use micro-RNAs to resolve a node with implications for the evolution of embryonic development in Diptera. We demonstrate that flies experienced three episodes of rapid radiation—lower Diptera (220 Ma), lower Brachycera (180 Ma), and Schizophora (65 Ma)—and a number of life history transitions to hematophagy, phytophagy, and parasitism in the history of fly evolution over 260 million y

Prevalence of neurocysticercosis in people with epilepsy in the Eastern Province of Zambia

Zambia is endemic for Taenia solium taeniosis and cysticercosis. In this single-centered, cross-sectional, community-based study, the role of neurocysticercosis (NCC) as a cause of epilepsy was examined. People with epilepsy (PWE, n = 56) were identified in an endemic area using a screening questionnaire followed by in-depth interviews and neurological examination. Computed tomography (CT) was performed on 49 people with active epilepsy (PWAE) and their sera (specific antibody and antigen detection, n = 56) and stools (copro-antigen detection, n = 54) were analyzed. The CT scan findings were compared to a group of 40 CT scan controls. Of the PWE, 39.3% and 23.2% were positive for cysticercal antibodies and antigens, respectively, and 14.8% for coproantigens (taeniosis). Lesions highly suggestive of NCC were detected in 24.5% and definite NCC lesions in 4.1% of CT scans of PWAE. This compares to 2.5% and 0%, respectively, in the control CT scans. Using the Del Brutto diagnostic criteria, 51.8% of the PWAE were diagnosed with probable or definitive NCC and this rose to 57.1% when the adapted criteria, as proposed by Gabriel et al. (adding the sero-antigen ELISA test as a major criterion), were used. There was no statistically significant relationship between NCC, current age, age at first seizure and gender. This study suggests that NCC is the single most important cause of epilepsy in the study area. Additional large-scale studies, combining a community based prevalence study for epilepsy with neuroimaging and serological analysis in different areas are needed to estimate the true impact of neurocysticercosis in endemic regions and efforts should be instituted to the control of T. solium

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Primary gliosarcoma: key clinical and pathologic distinctions from glioblastoma with implications as a unique oncologic entity

This report presents the historical experience, clinical presentation, treatment, prognosis, and pathogenesis of gliosarcoma described to date in the English literature. PubMed query of term “gliosarcoma” was performed, followed by a rigorous review of cited literature. Articles selected for analysis included: (1) case reports of gliosarcoma, (2) review articles of gliosarcoma, and (3) studies of the pathogenesis or genetics of gliosarcoma in humans. Our review identified 219 cases of gliosarcoma in 34 reports and eight articles addressing the pathogenesis. Survival in larger series ranged 4–11.5 months. Features unique to gliosarcoma compared to glioblastoma (GBM) include their temporal lobe predilection, potential to appear similar to a meningioma at surgery, repeated reports of extracranial metastases, and infrequency of EGFR mutations. Published experience is limited to small case series, and the pathogenesis remains unclear. Clinical and pathologic characteristics distinct from GBM suggest that they may warrant specific treatment, separate from conventional GBM therapy

Applying Bayesian model averaging for uncertainty estimation of input data in energy modelling

Background Energy scenarios that are used for policy advice have ecological and social impact on society. Policy measures that are based on modelling exercises may lead to far reaching financial and ecological consequences. The purpose of this study is to raise awareness that energy modelling results are accompanied with uncertainties that should be addressed explicitly. Methods With view to existing approaches of uncertainty assessment in energy economics and climate science, relevant requirements for an uncertainty assessment are defined. An uncertainty assessment should be explicit, independent of the assessor’s expertise, applicable to different models, including subjective quantitative and statistical quantitative aspects, intuitively understandable and be reproducible. Bayesian model averaging for input variables of energy models is discussed as method that satisfies these requirements. A definition of uncertainty based on posterior model probabilities of input variables to energy models is presented. Results The main findings are that (1) expert elicitation as predominant assessment method does not satisfy all requirements, (2) Bayesian model averaging for input variable modelling meets the requirements and allows evaluating a vast amount of potentially relevant influences on input variables and (3) posterior model probabilities of input variable models can be translated in uncertainty associated with the input variable. Conclusions An uncertainty assessment of energy scenarios is relevant if policy measures are (partially) based on modelling exercises. Potential implications of these findings include that energy scenarios could be associated with uncertainty that is presently neither assessed explicitly nor communicated adequately

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives