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This policy brief is the result of an interdisciplinary research workshop with academics and practitioners, held at Bielefeld University in Germany on November 2014, in cooperation with COST Action IS1011 on Climate Change and Migration. The Bielefeld Consultation identified the need to raise awareness of the challenges of planned relocation as an adaptive strategy to climate change or as a consequence of climate policies. Acknowledging the risks and failures of planned relocation, the Consultation suggests principals and precautionary measures to ensure climate justice. And as a result of the Consultation, non-conclusive list of minimum standards for planned relocation are put forward for the consideration of policymakers and practitioners engaged in climate change adaptation and mitigation.

In 2012, the Minister of Health and other leaders in the Bangladesh government approached Massachusetts General Hospital to establish the country's first bone marrow transplant program at Dhaka Medical College Hospital to serve the needs of the people of Bangladesh. Stated goals of this collaboration included a broad focus on the care of oncology patients with a specific emphasis on care of patients with hematologic malignancies and of women with gynecologic cancers. The purpose of this article is to describe the international nursing collaboration between Massachusetts General Hospital, Simmons College, the AK Khan Healthcare Trust in Dhaka, and Dhaka Medical College Hospital that was established to share nursing knowledge and to build specialized professional nursing capacities to deliver high-quality cancer care in the public sector. Over the past 3 years, through the educational programs that have been developed within this collaboration—the Enhanced Specialized Nurse Training Program—the Bangladeshi nurses have received continuing professional development based on Western standards of nursing and have been offering nursing care to patients who have undergone chemotherapy and bone marrow transplantation. The challenges, opportunities, and outcomes of this international collaboration have been highly rewarding and mutually beneficial.

Abstract

Background
Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are commonly ordered tests in general medical practice. However, their distribution and significance in older adults is understudied. As such, we aimed to evaluate sex-stratified distribution of both ALT and AST in older adults (≥ 70 years) and assess for associations with mortality.


Methods
Post-hoc analysis of the ASPirin in Reducing Events in the Elderly (ASPREE) randomised, placebo-controlled trial of daily low-dose aspirin for initially relatively healthy older persons. Univariate analysis and multiple logistic regression were used to explore baseline characteristics. Cox regression and restricted cubic splines were used to examine links between transaminase levels and mortality.


Results
Of the 11853 participants with ALT and AST levels, 1054 (8.9%) deaths were recorded over median 6.4 (IQR 5.4-7.6) years. For ALT, the lowest quintiles for males and females were 6-15 U/L and 5-13 U/L respectively; for AST, the lowest quintiles were 8-18 U/L and 7-17 U/L. On both univariate and models adjusted for covariates including age, BMI, frailty, diabetes, and kidney disease, males and females in the lowest quintile of ALT had an increased hazard of mortality (aHR 1.51 [95% CI 1.14-1.99] and aHR 1.39 [95% CI 1.03-1.88] respectively). For the lowest quintile of AST, only males were at increased risk (aHR 1.33 [95% CI 1.04-1.70]). Associations remained significant when removing outliers.


Conclusion
Low ALT levels independently confer an increased hazard of mortality for older males and females; low AST only impacted older male survival. Further evaluation of mechanisms would be worthwhile, and re-evaluating the lower limit of normal for ALT in older adults should be considered.

Genomics, combined with population mobility data, used to map importation and spatial spread of SARS-CoV-2 in high-income countries has enabled the implementation of local control measures. Here, to track the spread of SARS-CoV-2 lineages in Bangladesh at the national level, we analysed outbreak trajectory and variant emergence using genomics, Facebook 'Data for Good' and data from three mobile phone operators. We sequenced the complete genomes of 67 SARS-CoV-2 samples (collected by the IEDCR in Bangladesh between March and July 2020) and combined these data with 324 publicly available Global Initiative on Sharing All Influenza Data (GISAID) SARS-CoV-2 genomes from Bangladesh at that time. We found that most (85%) of the sequenced isolates were Pango lineage B.1.1.25 (58%), B.1.1 (19%) or B.1.36 (8%) in early-mid 2020. Bayesian time-scaled phylogenetic analysis predicted that SARS-CoV-2 first emerged during mid-February in Bangladesh, from abroad, with the first case of coronavirus disease 2019 (COVID-19) reported on 8 March 2020. At the end of March 2020, three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity in Bangladesh, combined with the mobility data, revealed that the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka (the capital of Bangladesh) and the rest of the country, disseminated three dominant viral lineages. Further analysis of an additional 85 genomes (November 2020 to April 2021) found that importation of variant of concern Beta (B.1.351) had occurred and that Beta had become dominant in Dhaka. Our interpretation that population mobility out of Dhaka, and travel from urban hotspots to rural areas, disseminated lineages in Bangladesh in the first wave continues to inform government policies to control national case numbers by limiting within-country travel.

Genomics, combined with population mobility data, used to map importation and spatial spread of SARS-CoV-2 in high-income countries has enabled the implementation of local control measures. Here, to track the spread of SARS-CoV-2 lineages in Bangladesh at the national level, we analysed outbreak trajectory and variant emergence using genomics, Facebook 'Data for Good' and data from three mobile phone operators. We sequenced the complete genomes of 67 SARS-CoV-2 samples (collected by the IEDCR in Bangladesh between March and July 2020) and combined these data with 324 publicly available Global Initiative on Sharing All Influenza Data (GISAID) SARS-CoV-2 genomes from Bangladesh at that time. We found that most (85%) of the sequenced isolates were Pango lineage B.1.1.25 (58%), B.1.1 (19%) or B.1.36 (8%) in early-mid 2020. Bayesian time-scaled phylogenetic analysis predicted that SARS-CoV-2 first emerged during mid-February in Bangladesh, from abroad, with the first case of coronavirus disease 2019 (COVID-19) reported on 8 March 2020. At the end of March 2020, three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity in Bangladesh, combined with the mobility data, revealed that the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka (the capital of Bangladesh) and the rest of the country, disseminated three dominant viral lineages. Further analysis of an additional 85 genomes (November 2020 to April 2021) found that importation of variant of concern Beta (B.1.351) had occurred and that Beta had become dominant in Dhaka. Our interpretation that population mobility out of Dhaka, and travel from urban hotspots to rural areas, disseminated lineages in Bangladesh in the first wave continues to inform government policies to control national case numbers by limiting within-country travel.

Genomics, combined with population mobility data, used to map importation and spatial spread of SARS-CoV-2 in high-income countries has enabled the implementation of local control measures. Here, to track the spread of SARS-CoV-2 lineages in Bangladesh at the national level, we analysed outbreak trajectory and variant emergence using genomics, Facebook 'Data for Good' and data from three mobile phone operators. We sequenced the complete genomes of 67 SARS-CoV-2 samples (collected by the IEDCR in Bangladesh between March and July 2020) and combined these data with 324 publicly available Global Initiative on Sharing All Influenza Data (GISAID) SARS-CoV-2 genomes from Bangladesh at that time. We found that most (85%) of the sequenced isolates were Pango lineage B.1.1.25 (58%), B.1.1 (19%) or B.1.36 (8%) in early-mid 2020. Bayesian time-scaled phylogenetic analysis predicted that SARS-CoV-2 first emerged during mid-February in Bangladesh, from abroad, with the first case of coronavirus disease 2019 (COVID-19) reported on 8 March 2020. At the end of March 2020, three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity in Bangladesh, combined with the mobility data, revealed that the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka (the capital of Bangladesh) and the rest of the country, disseminated three dominant viral lineages. Further analysis of an additional 85 genomes (November 2020 to April 2021) found that importation of variant of concern Beta (B.1.351) had occurred and that Beta had become dominant in Dhaka. Our interpretation that population mobility out of Dhaka, and travel from urban hotspots to rural areas, disseminated lineages in Bangladesh in the first wave continues to inform government policies to control national case numbers by limiting within-country travel.

The VoxTox research programme has applied expertise from the physical sciences to the problem of radiotherapy toxicity, bringing together expertise from engineering, mathematics, high energy physics (including the Large Hadron Collider), medical physics and radiation oncology. In our initial cohort of 109 men treated with curative radiotherapy for prostate cancer, daily image guidance computed tomography (CT) scans have been used to calculate delivered dose to the rectum, as distinct from planned dose, using an automated approach. Clinical toxicity data have been collected, allowing us to address the hypothesis that delivered dose provides a better predictor of toxicity than planned dose. ; JES was supported by Cancer Research UK through the Cambridge Cancer Centre. NGB, ASP and MG are supported by the National Institute of Health Research Cambridge Biomedical Research Centre. KH, MR AMB, EW and SJB were supported by the VoxTox Research Programme, funded by Cancer Research UK. DJN is supported by Addenbrooke's Charitable Trust and Cancer Research UK through the Cambridge Cancer Centre. FMB was supported by the Science and Technology Facilities Council. MPDS was part supported by the VoxTox Research Programme, funded by Cancer Research UK. RJ was part supported by the VoxTox Research Programme, funded by Cancer Research UK. LS is supported by the Armstrong Trust. XC was supported by the Isaac Newton Trust. CBS acknowledges support from the EPSRC Centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging, the Leverhulme Trust, the EU-RISE project CHiPS and the Cantab Capital Institute for the Mathematics of Information. NT was supported by a Gates-Cambridge Scholarship, funded by the Bill and Melinda Gates Foundation, PLY and SYKS by the Singapore Government.

During the initial phase of the COVID-19 pandemic, U.S. conservative politicians and the media downplayed the risk of both contracting COVID-19 and the effectiveness of recommended health behaviors. Health behavior theories suggest perceived vulnerability to a health threat and perceived effectiveness of recommended health-protective behaviors determine motivation to follow recommendations. Accordingly, we predicted that—as a result of politicization of the pandemic—politically conservative Americans would be less likely to enact recommended health-protective behaviors. In two longitudinal studies of U.S. residents, political conservatism was inversely associated with perceived health risk and adoption of health-protective behaviors over time. The effects of political orientation on health-protective behaviors were mediated by perceived risk of infection, perceived severity of infection, and perceived effectiveness of the health-protective behaviors. In a global cross-national analysis, effects were stronger in the U.S. (N = 10,923) than in an international sample (total N = 51,986), highlighting the increased and overt politicization of health behaviors in the U.S.