Leverhulme Trust

≈ 350,000). We use the fact that national examinations took place before and after lockdown and compare progress during this period to the same period in the 3 previous years. The Netherlands underwent only a relatively short lockdown (8 wk) and features an equitable system of school funding and the world's highest rate of broadband access. Still, our results reveal a learning loss of about 3 percentile points or 0.08 standard deviations. The effect is equivalent to one-fifth of a school year, the same period that schools remained closed. Losses are up to 60% larger among students from less-educated homes, confirming worries about the uneven toll of the pandemic on children and families. Investigating mechanisms, we find that most of the effect reflects the cumulative impact of knowledge learned rather than transitory influences on the day of testing. Results remain robust when balancing on the estimated propensity of treatment and using maximum-entropy weights or with fixed-effects specifications that compare students within the same school and family. The findings imply that students made little or no progress while learning from home and suggest losses even larger in countries with weaker infrastructure or longer school closures.

Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the coronavirus disease 2019 (COVID-19) pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly, how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider the age composition of local and national contexts as well as intergenerational interactions. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted forecasting of hospitalization and critical care needs.

Food production is a major driver of greenhouse gas (GHG) emissions, water and land use, and dietary risk factors are contributors to non-communicable diseases. Shifts in dietary patterns can therefore potentially provide benefits for both the environment and health. However, there is uncertainty about the magnitude of these impacts, and the dietary changes necessary to achieve them. We systematically review the evidence on changes in GHG emissions, land use, and water use, from shifting current dietary intakes to environmentally sustainable dietary patterns. We find 14 common sustainable dietary patterns across reviewed studies, with reductions as high as 70-80% of GHG emissions and land use, and 50% of water use (with medians of about 20-30% for these indicators across all studies) possible by adopting sustainable dietary patterns. Reductions in environmental footprints were generally proportional to the magnitude of animal-based food restriction. Dietary shifts also yielded modest benefits in all-cause mortality risk. Our review reveals that environmental and health benefits are possible by shifting current Western diets to a variety of more sustainable dietary patterns.

We report here the genome sequence of an ancient human. Obtained from ∼4,000-year-old permafrost-preserved hair, the genome represents a male individual from the first known culture to settle in Greenland. Sequenced to an average depth of 20×, we recover 79% of the diploid genome, an amount close to the practical limit of current sequencing technologies. We identify 353,151 high-confidence single-nucleotide polymorphisms (SNPs), of which 6.8% have not been reported previously. We estimate raw read contamination to be no higher than 0.8%. We use functional SNP assessment to assign possible phenotypic characteristics of the individual that belonged to a culture whose location has yielded only trace human remains. We compare the high-confidence SNPs to those of contemporary populations to find the populations most closely related to the individual. This provides evidence for a migration from Siberia into the New World some 5,500 years ago, independent of that giving rise to the modern Native Americans and Inuit. For the first time, the sequence of a near-complete nuclear genome has been obtained from the tissue of an ancient human. It comes from permafrost-preserved hair, about 4,000 years old, of a male palaeo-Eskimo of the Saqqaq culture, the earliest known settlers in Greenland. Functional single-nucleotide polymorphism (SNP) assessment was used to assign possible phenotypic characteristics. The analysis provides evidence for a migration from Siberia into the New World some 5,500 years ago, independent of the migration that gave rise to the modern Native Americans and Inuit. Elsewhere in the issue we profile the paper's last author Eske Willerslev, who headed the project and found the lock of hair in a Copenhagen museum basement — after a fruitless search among the archaeological sites of Peary Land. The first genome sequence of an ancient human is reported. It comes from an approximately 4,000-year-old permafrost-preserved hair from a male from the first known culture to settle in Greenland. Functional single-nucleotide polymorphism (SNP) assessment is used to assign possible phenotypic characteristics and high-confidence SNPs are compared to those of contemporary populations to find those most closely related to the individual.

We present an Aboriginal Australian genomic sequence obtained from a 100-year-old lock of hair donated by an Aboriginal man from southern Western Australia in the early 20th century. We detect no evidence of European admixture and estimate contamination levels to be below 0.5%. We show that Aboriginal Australians are descendants of an early human dispersal into eastern Asia, possibly 62,000 to 75,000 years ago. This dispersal is separate from the one that gave rise to modern Asians 25,000 to 38,000 years ago. We also find evidence of gene flow between populations of the two dispersal waves prior to the divergence of Native Americans from modern Asian ancestors. Our findings support the hypothesis that present-day Aboriginal Australians descend from the earliest humans to occupy Australia, likely representing one of the oldest continuous populations outside Africa.

New financing alternatives, such as microfinance, crowdfunding, and peer–to–peer lending, have expanded rapidly. To date, few studies have investigated the antecedents and consequences of these financing mechanisms. This special issue provides an academic foundation for understanding new financial options that entrepreneurs can now use to start and grow ventures. In the introductory article, we integrate strands of the literature on emerging innovations in entrepreneurial finance and provide a framework for a systematic approach to new research questions. We conclude with a discussion of the six papers in the special issue and demonstrate how they contribute to the framework.

Native Americans derive from a small number of Asian founders who likely arrived to the Americas via Beringia. However, additional details about the initial colonization of the Americas remain unclear. To investigate the pioneering phase in the Americas we analyzed a total of 623 complete mtDNAs from the Americas and Asia, including 20 new complete mtDNAs from the Americas and seven from Asia. This sequence data was used to direct high-resolution genotyping from 20 American and 26 Asian populations. Here we describe more genetic diversity within the founder population than was previously reported. The newly resolved phylogenetic structure suggests that ancestors of Native Americans paused when they reached Beringia, during which time New World founder lineages differentiated from their Asian sister-clades. This pause in movement was followed by a swift migration southward that distributed the founder types all the way to South America. The data also suggest more recent bi-directional gene flow between Siberia and the North American Arctic.

As COVID-19 vaccines are rolled out across the world, there are growing concerns about the roles that trust, belief in conspiracy theories, and spread of misinformation through social media play in impacting vaccine hesitancy. We use a nationally representative survey of 1476 adults in the UK between 12 and 18 December 2020, along with 5 focus groups conducted during the same period. Trust is a core predictor, with distrust in vaccines in general and mistrust in government raising vaccine hesitancy. Trust in health institutions and experts and perceived personal threat are vital, with focus groups revealing that COVID-19 vaccine hesitancy is driven by a misunderstanding of herd immunity as providing protection, fear of rapid vaccine development and side effects, and beliefs that the virus is man-made and used for population control. In particular, those who obtain information from relatively unregulated social media sources-such as YouTube-that have recommendations tailored by watch history, and who hold general conspiratorial beliefs, are less willing to be vaccinated. Since an increasing number of individuals use social media for gathering health information, interventions require action from governments, health officials, and social media companies. More attention needs to be devoted to helping people understand their own risks, unpacking complex concepts, and filling knowledge voids.

Abstract Exporting involves sunk costs, so some firms export whilst others do not. This proposition derives from a number of models of firm behavior and has been exposed to microeconometric analysis. Evidence from the latter suggests that exporting firms are generally more productive than nonexporters. They self‐select, in that they are more productive before they enter export markets, but the evidence suggests that entry does not make them any more productive. This paper investigates exporting and firm performance for a large panel of UK manufacturing firms, applying matching techniques. The authors find that exporters are more productive and they do self‐select. In contrast to other evidence, however, exporting further increases firm productivity.

The presumed higher productivity of foreign firms and resulting spillovers to domestic firms has led governments to offer financial incentives to foreign firms. We investigate if there is any productivity or wage gap between foreign and domestic firms in the UK and if the presence of foreign firms in a sector raises the productivity of domestic firms. Our results indicate that foreign firms do have higher productivity than domestic firms and they pay higher wages. We find no aggregate evidence of intra‐industry spillovers. However, firms with low productivity relative to the sector average, in low‐skill low foreign competition sectors gain less from foreign firms.

Well-resolved molecular gene trees illustrate the concept of descent with modification and exhibit the opposing processes of drift and migration, both of which influence population structure. Phylogenies of the maternally inherited mtDNA genome and the paternally inherited portion of the nonrecombining Y chromosome retain sequential records of the accumulation of genetic diversity. Although knowledge regarding the diversity of the entire human genome will be needed to completely characterize human genetic evolution, these uniparentally inherited loci are unique indicators of gender in modulating the extant population structure. We compare and contrast these loci for patterns of continuity and discreteness and discuss how their phylogenetic diversity and progression provide means to disentangle ancient colonization events by pioneering migrants from subsequent overlying migrations. We introduce new results concerning Y chromosome founder haplogroups C, DE, and F that resolve their previous trifurcation and improve the harmony with the mtDNA recapitulation of the out-of-Africa migration.

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

OBJECTIVE: To quantify the relation between food prices and the demand for food with specific reference to national and household income levels. DESIGN: Systematic review with meta-regression. DATA SOURCES: Online databases of peer reviewed and grey literature (ISI Web of Science, EconLit, PubMed, Medline, AgEcon, Agricola, Google, Google Scholar, IdeasREPEC, Eldis, USAID, United Nations Food and Agriculture Organization, World Bank, International Food Policy Research Institute), hand searched reference lists, and contact with authors. STUDY SELECTION: We included cross sectional, cohort, experimental, and quasi-experimental studies with English abstracts. Eligible studies used nationally representative data from 1990 onwards derived from national aggregate data sources, household surveys, or supermarket and home scanners. DATA ANALYSIS: The primary outcome extracted from relevant papers was the quantification of the demand for foods in response to changes in food price (own price food elasticities). Descriptive and study design variables were extracted for use as covariates in analysis. We conducted meta-regressions to assess the effect of income levels between and within countries on the strength of the relation between food price and demand, and predicted price elasticities adjusted for differences across studies. RESULTS: 136 studies reporting 3495 own price food elasticities from 162 different countries were identified. Our models predict that increases in the price of all foods result in greater reductions in food consumption in poor countries: in low and high income countries, respectively, a 1% increase in the price of cereals results in reductions in consumption of 0.61% (95% confidence interval 0.56% to 0.66%) and 0.43% (0.36% to 0.48%), and a 1% increase in the price of meat results in reductions in consumption of 0.78% (0.73% to 0.83%) and 0.60% (0.54% to 0.66%). Within all countries, our models predict that poorer households will be the most adversely affected by increases in food prices. CONCLUSIONS: Changes in global food prices will have a greater effect on food consumption in lower income countries and in poorer households within countries. This has important implications for national responses to increases in food prices and for the definition of policies designed to reduce the global burden of undernutrition.

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

BACKGROUND: Variations in the age patterns and magnitudes of excess deaths, as well as differences in population sizes and age structures, make cross-national comparisons of the cumulative mortality impacts of the COVID-19 pandemic challenging. Life expectancy is a widely used indicator that provides a clear and cross-nationally comparable picture of the population-level impacts of the pandemic on mortality. METHODS: Life tables by sex were calculated for 29 countries, including most European countries, Chile and the USA, for 2015-2020. Life expectancy at birth and at age 60 years for 2020 were contextualized against recent trends between 2015 and 2019. Using decomposition techniques, we examined which specific age groups contributed to reductions in life expectancy in 2020 and to what extent reductions were attributable to official COVID-19 deaths. RESULTS: Life expectancy at birth declined from 2019 to 2020 in 27 out of 29 countries. Males in the USA and Lithuania experienced the largest losses in life expectancy at birth during 2020 (2.2 and 1.7 years, respectively), but reductions of more than an entire year were documented in 11 countries for males and 8 among females. Reductions were mostly attributable to increased mortality above age 60 years and to official COVID-19 deaths. CONCLUSIONS: The COVID-19 pandemic triggered significant mortality increases in 2020 of a magnitude not witnessed since World War II in Western Europe or the breakup of the Soviet Union in Eastern Europe. Females from 15 countries and males from 10 ended up with lower life expectancy at birth in 2020 than in 2015.

AIM: To develop a consensus paper on the central points of an international invitational think-tank on nursing and artificial intelligence (AI). METHODS: We established the Nursing and Artificial Intelligence Leadership (NAIL) Collaborative, comprising interdisciplinary experts in AI development, biomedical ethics, AI in primary care, AI legal aspects, philosophy of AI in health, nursing practice, implementation science, leaders in health informatics practice and international health informatics groups, a representative of patients and the public, and the Chair of the ITU/WHO Focus Group on Artificial Intelligence for Health. The NAIL Collaborative convened at a 3-day invitational think tank in autumn 2019. Activities included a pre-event survey, expert presentations and working sessions to identify priority areas for action, opportunities and recommendations to address these. In this paper, we summarize the key discussion points and notes from the aforementioned activities. IMPLICATIONS FOR NURSING: Nursing's limited current engagement with discourses on AI and health posts a risk that the profession is not part of the conversations that have potentially significant impacts on nursing practice. CONCLUSION: There are numerous gaps and a timely need for the nursing profession to be among the leaders and drivers of conversations around AI in health systems. IMPACT: We outline crucial gaps where focused effort is required for nursing to take a leadership role in shaping AI use in health systems. Three priorities were identified that need to be addressed in the near future: (a) Nurses must understand the relationship between the data they collect and AI technologies they use; (b) Nurses need to be meaningfully involved in all stages of AI: from development to implementation; and (c) There is a substantial untapped and an unexplored potential for nursing to contribute to the development of AI technologies for global health and humanitarian efforts.

Abstract Porous organic molecular materials are a subclass of porous solids that are defined by their modular, molecular structures, and the absence of extended covalent or coordination bonding in the solid‐state. As a result, porous molecular materials are soluble and they can be processed into different forms, such as mixed matrix membranes. The structure of the porous modules can be fine‐tuned for specific applications, such as gas isotope separations, and in some cases the solid‐state properties of these materials can be defined by the structure of the porous molecule as viewed in isolation. In this review, the authors focus on the design of porous organic molecular materials and how their properties can be tuned for specific applications by using crystal engineering techniques. The authors distinguish between strategies where porosity is defined largely by the molecule itself, for example, in porous organic cages, and cases where porosity is generated by the solid‐state crystalline assembly. They emphasize the importance of computational techniques in the de novo design of functional, porous organic molecular materials, and how molecular modeling is applied to understand the properties of these materials.

The contribution of language history to the study of the early dispersals of modern humans throughout the Old World has been limited by the shallow time depth (about 8000 +/- 2000 years) of current linguistic methods. Here it is shown that the application of biological cladistic methods, not to vocabulary (as has been previously tried) but to language structure (sound systems and grammar), may extend the time depths at which language data can be used. The method was tested against well-understood families of Oceanic Austronesian languages, then applied to the Papuan languages of Island Melanesia, a group of hitherto unrelatable isolates. Papuan languages show an archipelago-based phylogenetic signal that is consistent with the current geographical distribution of languages. The most plausible hypothesis to explain this result is the divergence of the Papuan languages from a common ancestral stock, as part of late Pleistocene dispersals.

The origin of contemporary Europeans remains contentious. We obtained a genome sequence from Kostenki 14 in European Russia dating from 38,700 to 36,200 years ago, one of the oldest fossils of anatomically modern humans from Europe. We find that Kostenki 14 shares a close ancestry with the 24,000-year-old Mal'ta boy from central Siberia, European Mesolithic hunter-gatherers, some contemporary western Siberians, and many Europeans, but not eastern Asians. Additionally, the Kostenki 14 genome shows evidence of shared ancestry with a population basal to all Eurasians that also relates to later European Neolithic farmers. We find that Kostenki 14 contains more Neandertal DNA that is contained in longer tracts than present Europeans. Our findings reveal the timing of divergence of western Eurasians and East Asians to be more than 36,200 years ago and that European genomic structure today dates back to the Upper Paleolithic and derives from a metapopulation that at times stretched from Europe to central Asia.

Suspension of face-to-face instruction in schools during the COVID-19 pandemic has led to concerns about consequences for student learning. So far, data to study this question have been limited. Here we evaluate the effect of school closures on primary school performance using exceptionally rich data from the Netherlands (n≈350,000). We use the fact that national exams took place before and after lockdown, and compare progress during this period to the same period in the three previous years. The Netherlands underwent only a relatively short lockdown (8 weeks), and features an equitable system of school funding and the world's highest rate of broadband access. Still, our results reveal a learning loss of about 3 percentile points or 0.08 standard deviations. The effect is equivalent to a fifth of a school year, the same period that schools remained closed. Losses are up to 60% larger among students from less-educated homes, confirming worries about the uneven toll of the pandemic on children and families. Investigating mechanisms, we find that most of the effect reflects the cumulative impact of knowledge learned rather than transitory influences on the day of testing. Results remain robust when balancing on the estimated propensity of treatment and using maximum entropy weights, or with fixed-effects specifications that compare students within the same school and family. The findings imply that students made little or no progress whilst learning from home, and suggest losses even larger in countries with weaker infrastructure or longer school closures.