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Over 70,000 excess deaths occurred in Europe during the summer of 2003. The resulting societal awareness led to the design and implementation of adaptation strategies to protect at-risk populations. We aimed to quantify heat-related mortality burden during the summer of 2022, the hottest season on record in Europe. We analyzed the Eurostat mortality database, which includes 45,184,044 counts of death from 823 contiguous regions in 35 European countries, representing the whole population of over 543 million people. We estimated 61,672 (95% confidence interval (CI) = 37,643-86,807) heat-related deaths in Europe between 30 May and 4 September 2022. Italy (18,010 deaths; 95% CI = 13,793-22,225), Spain (11,324; 95% CI = 7,908-14,880) and Germany (8,173; 95% CI = 5,374-11,018) had the highest summer heat-related mortality numbers, while Italy (295 deaths per million, 95% CI = 226-364), Greece (280, 95% CI = 201-355), Spain (237, 95% CI = 166-312) and Portugal (211, 95% CI = 162-255) had the highest heat-related mortality rates. Relative to population, we estimated 56% more heat-related deaths in women than men, with higher rates in men aged 0-64 (+41%) and 65-79 (+14%) years, and in women aged 80+ years (+27%). Our results call for a reevaluation and strengthening of existing heat surveillance platforms, prevention plans and long-term adaptation strategies.

International audience

Blood flow produces mechanical frictional forces, parallel to the blood flow exerted on the endothelial wall of the vessel, the so-called wall shear stress (WSS). WSS sensing is associated with several vascular pathologies, but it is first a physiological phenomenon. Endothelial cell sensitivity to WSS is involved in several developmental and physiological vascular processes such as angiogenesis and vascular morphogenesis, vascular remodeling, and vascular tone. Local conditions of blood flow determine the characteristics of WSS, i.e., intensity, direction, pulsatility, sensed by the endothelial cells that, through their effect of the vascular network, impact WSS. All these processes generate a local-global retroactive loop that determines the ability of the vascular system to ensure the perfusion of the tissues. In order to account for the physiological role of WSS, the so-called shear stress set point theory has been proposed, according to which WSS sensing acts locally on vessel remodeling so that WSS is maintained close to a set point value, with local and distant effects of vascular blood flow. The aim of this article is (1) to review the existing literature on WSS sensing involvement on the behavior of endothelial cells and its short-term (vasoreactivity) and long-term (vascular morphogenesis and remodeling) effects on vascular functioning in physiological condition; (2) to present the various hypotheses about WSS sensors and analyze the conceptual background of these representations, in particular the concept of tensional prestress or biotensegrity; and (3) to analyze the relevance, explanatory value, and limitations of the WSS set point theory, that should be viewed as dynamical, and not algorithmic, processes, acting in a self-organized way. We conclude that this dynamic set point theory and the biotensegrity concept provide a relevant explanatory framework to analyze the physiological mechanisms of WSS sensing and their possible shift toward pathological situations.

International audience

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.

Over the past decade, women in Western countries have taken to various social media platforms to share their dissatisfactory experiences with hormonal contraception, which may be pills, patches, rings, injectables, implants or hormonal intrauterine devices (IUDs). These online testimonials have been denounced as spreading "hormonophobia", i.e. an excessive fear of hormones based on irrational causes such as an overestimation of health risks associated with their use, that was already aroused by the recurring media controversies over hormonal contraception. In order to move toward a reproductive justice framework, we propose to study the arguments that women and men (as partners of female users) recently put forward against hormonal contraception to see whether they are related to hormonophobia. The aim of this article is to conduct a systematic review of the recent scientific literature in order to construct an evidence-based typology of reasons for rejecting hormonal contraception, in a continuum perspective from complaints to choosing not to use it, cited by women and men in Western countries in a recent time. The published literature was systematically searched using PubMed and the database from the French National Institute for Demographic Studies (Ined). A total of 42 articles were included for full-text analysis. Eight main categories emerged as reasons for rejecting hormonal contraception: problems related to physical side effects; altered mental health; negative impact on sexuality; concerns about future fertility; invocation of nature; concerns about menstruation; fears and anxiety; and the delegitimization of the side effects of hormonal contraceptives. Thus, arguments against hormonal contraception appeared complex and multifactorial. Future research should examine the provider-patient relationship, the gender bias of hormonal contraception and demands for naturalness in order to understand how birth control could better meet the needs and expectations of women and men in Western countries today.

This paper provides a methodological assessment of the advantages and drawbacks of the origin-based snowballing technique as a reliable method to construct representative samples of international migrants in destination areas. Using data from the MAFE-

BACKGROUND: In eastern and southern Africa, the human immunodeficiency virus (HIV) epidemic appeared first in urban centres and then spread to rural areas. Its overall prevalence is lower in West Africa, with the highest levels still found in cities. Rural areas are also threatened, however, because of the population's high mobility. We conducted a study in three different communities with contrasting infection levels to understand the epidemiology of HIV infection in rural West Africa. METHOD: A comparative cross-sectional study using a standardized questionnaire and biological tests was conducted among samples in two rural communities of Senegal (Niakhar and Bandafassi, 866 and 952 adults, respectively) and a rural community of Guinea-Bissau (Caio, 1416 adults). We compared the distribution of population characteristics and analysed risk factors for HIV infection in Caio at the individual level. RESULTS: The level of HIV infection was very low in Niakhar (0.3%) and Bandafassi (0.0%), but 10.5% of the adults in Caio were infected, mostly with HIV type 2 (HIV-2). Mobility was very prevalent in all sites. Short-term mobility was found to be a risk factor for HIV infection among men in Caio (adjusted odds ratio (aOR) = 2.06; 95% CI: 1.06-3.99). Women from Caio who reported casual sex in a city during the past 12 months were much more likely to be infected with HIV (aOR = 5.61 95% CI: 1.56-20.15). Short-term mobility was associated with risk behaviours at all sites. CONCLUSIONS: Mobility appears to be a key factor for HIV spread in rural areas of West Africa, because population movement enables the virus to disseminate and also because of the particularly risky behaviours of those who are mobile. More prevention efforts should be directed at migrants from rural areas who travel to cities with substantial levels of HIV infection.

Pays d’immigration depuis plus d’un siècle, la France est une société multiculturelle où la diversité des origines atteint un niveau sans précédent. Mais la situation des populations liées à l’immigration, objets d’idées reçues et de représentations stéréotypées, reste mal connue. Souhaitant répondre à ce besoin de connaissances statistiques, l’Ined et l’Insee se sont associés pour réaliser une enquête d’envergure sur la diversité des populations en France et l’étude des discriminations. Réalisée auprès de 22 000 personnes, l’enquête Trajectoires et Origines (TeO) marque une nouvelle étape dans les recherches quantitatives sur les personnes immigrées et leurs descendants. L’origine est-elle en soi un facteur d’inégalités ou simplement de différenciation dans l’accès aux différentes ressources de la vie sociale ? TeO offre des pistes de réflexion en accordant une grande place à la reconstitution des trajectoires scolaires, professionnelles, matrimoniales ou en explorant l’accès au logement et à la santé. L’un des apports majeurs de cet ouvrage, aboutissement de l’enquête TeO, est de combiner une approche à la fois objective et subjective de la discrimination en étudiant, pour la première fois l’expérience du racisme subi, et en ouvrant des perspectives méthodologiques sur l’étude de préjudices vécus du fait de l’origine, la religion ou la couleur de peau.

Au cours des dernières décennies, l’organisation domestique a été affectée par des évolutions majeures, telles que la montée de l’activité féminine et du niveau d’instruction, ou la réduction de la taille des familles. Cet article analyse de quelle manière les temps domestiques et parentaux des hommes et des femmes ont été modifiés par ces transformations depuis 1985. Il étudie les évolutions des moyennes et des distributions de ces deux usages du temps pour l’ensemble des personnes d’âge actif, et il porte un regard particulier sur les changements opérés au sein des couples. Au cours des 25 dernières années, les femmes ont consacré davantage de temps aux activités parentales, mais elles ont sensiblement réduit le temps dédié à l’entretien domestique. Cette baisse tient surtout aux changements de leurs pratiques, et dans une bien moindre mesure à la progression de l’activité féminine et aux changements des structures familiales. La réduction est plus notable pour les femmes qui consacrent le plus de temps à la sphère domestique. Les hommes se sont davantage impliqués dans l’éducation des enfants, les pères peu ou non participants devenant plus rares. Toutefois, la contribution des hommes aux autres tâches domestiques est demeurée stable. En 2010, les femmes effectuent ainsi la majorité des tâches ménagères et parentales – respectivement 71 % et 65 %. Cette inégale répartition montre des résistances à un partage plus égal des tâches. Au sein des couples, les comportements domestiques et parentaux sont liés positivement, mettant en évidence des exigences domestiques et préférences éducatives communes qui vont au‑delà de l’homogamie sociale ainsi qu’une moindre spécialisation des rôles conjugaux au fil du temps. Le nombre de couples dans lesquels l’homme réalise davantage de travail domestique que leur conjointe augmente, ils représentent un quart des couples en 2010.

We examine how far fertility trends respond to family policies in OECD countries. In the light of the recent fertility rebound observed in several OECD countries, we empirically test the impact of different family policy settings on fertility, using data from 18 OECD countries that spans the years 1982 to 2007. Our results confirm that each instrument of the family policy package (paid leave, childcare services and financial transfers) has a positive influence, suggesting that the addition of these supports for working parents in a continuum during the early childhood is likely to facilitate parents' choice to have children. Policy levers do not have similar weight, however: in-cash benefits covering childhood after the year of childbirth and the coverage of childcare services for children under age three have a larger potential influence on fertility than leave entitlements and benefits granted around childbirth. Our findings are robust once controlling for birth postponement, endogeneity, time lagged fertility reactions and for different national contexts, such as economic development, female employment rates, labour market insecurity and childbearing norms.

The Healthy Immigrant Effect (HIE) refers to the fact that recent migrants are in better health than the nonmigrant population in the host country. Central to explaining the HIE is the idea that migrants are positively selected in terms of their socioecono

Abstract Even though Sinitic languages are spoken by more than one billion people, very little research has been carried out on the synchronic grammar of major languages and dialect groups of Chinese, apart from standard Mandarin or putonghuali, and Cantonese to a lesser extent. The same situation applies to the diachrony of Sinitic languages with respect to the exact relationship between Archaic and Medieval Chinese and contemporary dialects.

Auteur : Antonella Romano Titre : La Contre-Réforme Mathématique. Constitution et diffusion d’une culture mathématique jésuite à la Renaissance (1540-1640) Editeur : École française de Rome Lieu de publication : Rome Année de publication : 1999 Collection : Bibliothèque des écoles françaises d'Athènes et de Rome ; 306 Format : 1 vol. (XI-691 p.-[20] p. de pl.) : tabl., cartes, ill., couv. ill. ; 25 cm Annotations : Texte remanié de : Thèse de doctorat : Histoire : Paris 1 : 1996. Bibliogr. p. [623]-673. Index ISSN : 0257-4101 ISBN : 978-2-7283-0568 DOI : 10.3406/befar.1999.1252

Information about pandemic dynamics is crucial to understand the potential impacts on populations, design mitigation strategies and evaluate the efficacy of their implementation. Centralization, standardization and harmonization of data are critical to enable comparisons of the demographic impact of COVID-19 which take into account differences in the age and sex compositions of confirmed infections and deaths. The international data landscape must keep pace with the global march of the pandemic, and researchers must work to triangulate the available data to create comparable measures to monitor and predict its demographic impacts. COVerAGE-DB aims to provide global coverage of key demographic aspects of the COVID-19 pandemic as it unfolds in an up-to-date, transparent and open-access format. COVerAGE-DB offers data with standardized count measures by sex and harmonized age groups, which is a necessary but not sufficient condition to allow comparisons between populations at national and subnational scales. The database is currently under expansion through both the increase in coverage of national and subnational populations and the inclusion of more recent periods as the pandemic continues. At the time of writing, the database contains daily counts of COVID-19 cases, deaths and tests performed, by age and sex, for 108 national and 371 subnational populations around the world, depending on the available data for each source. The date range available for each country or subpopulation varies. In several country series, the database includes the earliest confirmed cases in January 2020. For most populations, the database includes daily time series, beginning from an initial starting date when the data were first released or collected by our team. Figure 1 displays a map of countries included in the database, indicating at least one subnational population from 13 countries. A detailed overview of data availability is given in a searchable table: [https://bit.ly/3kVDrLD]. Availability of national and subnational information on COVID-19 cases, deaths, and tests in the countries included in the database as of 7 January, 2021. Official counts of COVID-19 cases, deaths, and tests are extracted from reports published by official governmental institutions, such as health ministries and statistical offices. Depending on the source, data are collected in a variety of formats, including machine-readable files, pdf tables, html tables, interactive dashboards, press releases, official announcements via Twitter, and in a few instances, from digitized graphics. A full list of data sources is available in a dashboard view [https://bit.ly/2Qg1MxL]. Generally, COVID-19 cases, deaths and tests in age groups are reported as counts, but some sources report data in other metrics (fractions, percentages, ratios) or as summary indicators such as case fatality ratios (CFRs) by age. Reported age intervals vary by source, ranging from single ages to 30-year or greater age bands, and sometimes reported age intervals change over time within sources. Usually data are reported as cross-sectional snapshots of cumulative counts, but some sources give full time series of new cases or deaths, in which case we cumulate counts over time. We also collect standard metadata on each of the sources to capture various characteristics of the collected data, such as the primary collection channels, definitions used and notes on major disruptions or events. An overview of key fields from these metadata is shared as a spreadsheet [https://bit.ly/2FAmKFn]. All source data are entered into standard spreadsheet templates hosted in a central folder on Google Drive. Data entry into the templates is either manual or automatic, depending on the source. R programs collect data from the source templates and compile the merged input database. The merged input file is then subject to a series of automatic validity checks. Initial checks are carried out by the individual responsible for data collection and entry, using an interactive application [https://mpidr.shinyapps.io/cleaning_tracker/]. Data are then harmonized to standard metrics (counts), measures (cases, deaths, tests) and age bands (5- and 10-year age intervals). Harmonization procedures include rescaling to ensure coherence between age distributions and reported total counts. Age group harmonization is done using the penalized composite link model for ungrouping1 which was designed for splitting histograms of count data. Output data also include a file containing selected diagnostics of data quality, such as completeness of age reporting, for each source and date. The complete details on all steps of production are available in the COVerAGE-DB Method Protocol, which is publicly available on the web.2 A table listing which adjustments are applied to each population is available on the project website [https://bit.ly/2E61BSV]. The merged input database, the harmonized output and the data quality files are uploaded daily as zipped csv files to an Open Science Framework repository (OSF) [https://osf.io/mpwjq/]. A GitHub repository [https://bit.ly/2YbtPCJ], which is linked to OSF, contains all R scripts used in the complete production pipeline, including compilation, diagnostics and harmonization. Since collection efforts began for COVerAGE-DB in late March 2020, we are aware of 15 studies using the data, many of which provide R code online and are fully reproducible. Broadly, these studies aim to measure the influence of demographic factors on mortality from COVID-19,3,4 assess the pandemic impact on health and mortality within5,6 and across populations,7–12 analyse COVID-19 data availability and quality,13 propose methodological innovations that allow comparisons of CFRs14 and the development of indirect methods to estimate infections in the population.15,16 The database is also used to monitor COVID-19 impacts in particular age ranges. For instance, UNICEF has used the database for monitoring the burden of the pandemic on children around the world17 and the UN Department of Economic and Social Affairs has used it similarly to focus on older age groups.18 As an example of the analyses that COVerAGE-DB enables, Figure 2 displays changes in the relation between age-specific deaths and cases rates in Colombia, inspired by Figure 1 of Dudel et al.14 We divide both cases and deaths in each age band by the respective population sizes. Diagonal lines indicate age-specific CFRs. The graph illustrates a sharp increase in CFR over age for each sex, and displays considerable sex differences. For instance, men aged 60–69 in Colombia have almost the same CFR (approximately 12% risk of death after COVID-19 disease diagnosis) as women aged 70–79. Relationship between deaths and cases per 100 000 population by age group and sex in Colombia, until 7 November 2020. Diagonal lines indicate the case fatality ratio. We repeat this exercise to compare Colombia with Mexico (see Figure 3), where standardizing by population size is more justified. CFRs and death rates are much higher in Mexico than in Colombia in each age band—around 2-fold—except for ages 80+, which show a substantial reduction in the CFR difference, and much higher death rates for Colombia. Relationship between deaths and cases per 100 000 population by age group in Mexico and Colombia, until 7 November 2020. Diagonal lines indicate the case fatality ratio. This comparison between Colombia and Mexico allows us to illustrate several issues in data quality to be considered when comparing COVID-19 outcomes between populations in general. Besides the economic and sanitary conditions that make Latin American countries more vulnerable to the pandemic, the lack of unambiguous definitions of COVID-19 cases and deaths and the limited testing capacity represent major challenges for data quality assessment.19–21 We focus here on definitions and testing strategies. With respect to COVID-19 case and death definitions, criteria have varied since records started. At the time of data retrieval, both countries use laboratory, clinical and epidemiological criteria to confirm SARS-CoV-2 infections.22,23 However, the vast majority of COVID-19 cases and deaths are confirmed with RT-PCR tests results in both populations (99.6% and 91.6% in Colombia and Mexico, respectively).24,25 Regarding the definition of tests, whereas in Colombia it refers to laboratory samples tested (4.5 M as of 7 November 2020), in Mexico it alludes to persons (2.3 M). Because individuals may be tested more than once, comparison between these two units is not straightforward. Testing performance measures, such as positive rates (e.g. 30% in Colombia and 45% in Mexico26), are essential for interpreting differences in cases and deaths across populations, because they help to assess the extent of infection under-reporting.27 However, differences in test definitions pose serious challenges for direct comparisons. Dates in both sources are comparable, corresponding to the occurrence of events. Since information from both sources relies on individual-level databases, delays in diagnosis and death registration are retrospectively adjusted. Differences in testing capacity and strategy between countries are also key determinants for infection diagnosis. Given both the magnitude of contagion and limited resources in the region, Latin American countries have struggled to increase testing capacity proportionally to the spread of the infection.28,29 Although with very limited capacity, the testing approach of Colombia has been to test as many suspected cases as possible. In contrast, an important part of the test strategy in Mexico has focused on inferring the extent of contagion in the population by using nationally representative samples (known as Centinela, which represent 36.5% of all confirmed infections at the date under observation), and it has gradually included a small proportion of suspected infections outside the Centinela system.23 On 7 November 2020, Colombia performed five times more tests per capita than Mexico. These differences in testing regimes between both countries may account for a substantial part of the CFR discrepancies observed in Figure 3. The differences in definitions and testing strategies between populations highlight challenges in making comparisons and also the need to produce data with sufficient detail to adjust for biases. For this reason, alongside data on cases, deaths and tests, COVerAGE-DB offers additional information on metadata and quality metrics that are needed for a cautious interpretation of the data and their limitations. It is our view that researchers should triangulate creatively from all available data rather than avoid difficult comparisons. Since the beginning of the pandemic, it has been evident that population characteristics are key to understanding the prevalence, spread and fatality of COVID-19 across countries. However, data on cases, deaths and tests disaggregated by age and sex are not easily comparable across countries, and sometimes not even accessible. The main strength of COVerAGE-DB is to provide a centralized, open-access and fully reproducible repository of age-and sex-specific case, death and test counts from COVID-19, collected from official sources and harmonized to standard output formats. The data harmonization process is transparent, following a strict protocol.2 The initial input data are provided alongside the harmonized counts, as well as the code used to harmonize the different input measures, metrics and age groups into comparable granular output metrics. All scripts are written in the open-source R programming language.30 The data sources and limitations are documented for each country in a standard metadata framework. A limitation of the COVerAGE-DB is the heterogeneous and difficult-to-evaluate quality of the underlying data. No single data source can currently claim accurate estimates of COVID-19 incidence or fatalities. Age-specific case counts are highly dependent upon the testing capacity,31 testing strategy32 and differences in the definition of cases across sources and over time. Recorded cases underestimate infections everywhere, with underestimation expected to vary by age, given the relationship between age and case severity.33 The accuracy of diagnostic RT-PCR tests used to confirm infections is also known to vary.34 Furthermore, at any given date, cumulative counts are underestimated because of the lag between infection and a positive test result.35 Death counts from COVID-19 are also likely underestimated for similar reasons and also due to various kinds of delays in death registration. Media reports have circulated about intentional data manipulation in some of the official data covered in the database.36 Excess all-cause mortality has been observed across many regions.37–40 Although some of these deaths likely are from postponing or foregoing treatment from non-COVID-19-related causes, the magnitude of this excess is suggestive that numerous COVID-19-related deaths are classified under different causes. Populations also differ in whether deaths of suspected COVID-19 cases are included in official statistics and in post-mortem practices when an infection is suspected.41 Some populations only report deaths occurring in hospitals, neglecting a potentially sizeable proportion of deaths occurring in institutional settings and at home.42 Most populations currently report all deaths to confirmed SARS-CoV-2 infections as COVID-19 deaths for this database, but the underlying cause of death eventually reported on the death certificate may differ in patients with severe comorbidities. To mitigate biases and misinterpretations due to different practices and definitions, such information is constantly updated and documented in the metadata of the database which are freely accessible to users. Further, a supplementary data quality metrics file contains a suite of data quality indicators that is easily merged with the main output data. Quality metrics include age-reporting completeness, some indicators on how aggressive age harmonization is, and two positivity measures from Our World in Data database on COVID-19 testing.26 All of these issues compromise the comparability of the data contained within the COVerAGE-DB, both across populations at any given time and within populations over time. That is, the database enables direct calculation of age-specific CFRs, but one must be careful when making comparisons. Care must also be taken not to interpret calculated CFRs as infection fatality ratios, the latter of which include both detected and undetected SARS-CoV-2 infections in the denominator. Proper estimation of incidence and fatality, and of total demographic impacts, will likely require triangulating data across numerous sources as these become available. To this end, the COVerAGE-DB was designed to be easily merged with other databases such as the Our World In Data testing or excess mortality data,26 the COVID-19 dashboard of Johns Hopkins,43 the World Population Prospects database44 and the Short Term Mortality Fluctuations database.40 Moreover, given that we have near-complete time series capturing the whole pandemic curve in some places, careful modelling of lag structures might allow some of these data-driven biases to be estimated. Both merged input and harmonized output files can be downloaded directly from the OSF site [https://osf.io/mpwjq doi: 10.17605/OSF.IO/MPWJQ, which contains a folder called ‘Data’ with four files of primary data. Figure 4 shows where to find the files in the OSF repository. View of the Open Science Framework (OSF) repository, File section [https://osf.io/mpwjq/files/]. To download data files, click on Data, and select one of the files. Each of the main data files has a stable link (see Table 1) which always points to the most recent version. Each file is a zipped csv file by the same name. For stable links to download particular versions, click on the version number in the Version column seen in Figure 4. Users can note versions either by referring to timestamps provided in the headers of data files or by referring to OSF file version numbers, which increment with each daily update. The main data files, a description of their content, and their stable URLs 1. inputDB.zip 2. Output_5.zip 3. Output_10.zip 4. qualityMetrics.zip A data dictionary is given in both the OSF wiki [https://osf.io/mpwjq/wiki/home/] and the Method Protocol.2 Files are shared in csv format to be as universally accessible as possible. A guide to getting started using the data in R is also provided [https://bit.ly/3g8nIVU], to merge COVerAGE-DB with other databases, and tips for other statistical packages may also be added. Users are encouraged to reach out for further information or advice on using the database, or to express interest in the project at: [[email protected]]. COVerAGE-DB is an open-access database including cumulative counts of confirmed COVID-19 cases, deaths and tests by age and sex. Original data and sources are provided alongside data and measures in age-harmonized formats. The database is in continuous development. It includes data since January 2020, and as of 7 January 2021, it includes 108 countries and 371 subnational areas. The database also documents variations in definitions of all input data and indicators of reporting completeness across sources and over time. An international team, composed of more than 60 researchers, contributed to the collection of data and metadata in COVerAGE-DB from governmental institutions, as well as to the design and implementation of the data processing and validation pipeline. We encourage researchers interested in supporting this project to send a message to the email: [[email protected]]. We gratefully acknowledge the hard work of health ministries and statistical offices around the world in preparing and disseminating the data included in COVerAGE-DB. AvR, JS, and MRN received funding from European Research Council Starting Grant #716323. EA received funding from Social Sciences and Humanities Research Council (Canada) - Postdoctoral grant #756-2019-0768. STL received funding from European Research Council - Starting Grant #864616. FU received funding from the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health #P2CHD047879. RS received funding from Fonds de recherche du Québec – Société et culture #2019-B2Z-257115. CL received funding from European Research Council - Starting Grant #834103. Tim Riffe,1 Enrique Acosta,1 José Manuel Aburto,2 Diego Alburez-Gutierrez,1 Anna Altová,3 Ainhoa Alustiza,1 Ugofilippo Basellini,1 Simona Bignami,4 Didier Breton,5 Eungang Choi,6 Jorge Cimentada,1 Gonzalo De Armas,7 Emanuele Del Fava,1 Alicia Delgado,8 Viorela Diaconu,1 Jessica Donzowa,1 Christian Dudel,1 Antonia Fröhlich,1 Alain Gagnon,4 Mariana Garcia-Crisóstomo,9 Victor M. Garcia-Guerrero,9 Armando González-Díaz,9 Irwin Hecker,5 Dagnon Eric Koba,4 Marina Kolobova,1 Mine Kühn,1 Mélanie Lépori,5 Chia Liu,10 Andrea Lozer,1 Mădălina Manea,11 Lilian Marey,12 Muntasir Masum,13 Ryohei Mogi,14 Céline Monicolle,15 Saskia Morwinsky,1 Ronald Musizvingoza,16 Mikko Myrskylä,1 Marília R. Nepomuceno,1 Michelle Nickel,1 Natalie Nitsche,1 Anna Oksuzyan,1 Samuel Oladele,17 Emmanuel Olamijuwon,18 Oluwafunke Omodara,17 Soumaila Ouedraogo,19 Mariana Paredes,7 Marius D. Pascariu,20 Manuel Piriz,7 Raquel Pollero,7 Larbi Qanni,1 Federico Rehermann,7 Filipe Ribeiro,21 Silvia Rizzi,22 Francisco Rowe,23 Adil R. Sarhan,24 Isaac Sasson,25 Erez Shomron,25 Jiaxin Shi,1 Rafael Silva-Ramirez,4 Cosmo Strozza,22 Catalina Torres,26 Institute for of of de de de de Institute for the Quality of de et de of for national de recherche of the national de of of national de de

Laurence Talairach-Vielmas explores Victorian representations of femininity in narratives that depart from mainstream realism, from fairy tales by George MacDonald, Lewis Carroll, Christina Rossetti, Juliana Horatia Ewing, and Jean Ingelow, to sensation novels by Wilkie Collins, Mary Elizabeth Braddon, Rhoda Broughton, and Charles Dickens. Feminine representation, Talairach-Vielmas argues, is actually presented in a hyper-realistic way in such anti-realistic genres as children's literature and sensation fiction. In fact, it is precisely the clash between fantasy and reality that enables the narratives to interrogate the real and re-create a new type of realism that exposes the normative constraints imposed to contain the female body. In her exploration of the female body and its representations, Talairach-Vielmas examines how Victorian fantasies and sensation novels deconstruct and reconstruct femininity; she focuses in particular on the links between the female characters and consumerism, and shows how these serve to illuminate the tensions underlying the representation of the Victorian ideal.

Sirs—Compared with non-Hispanic Whites, Hispanics in the US are poorer and less educated, and yet they enjoy a lower all-cause mortality rate. This so-called ‘Hispanic Paradox’ has received much attention over the past 20 years, both in the epidemiological and demographic literature. Besides artefactual explanations (i.e. possible under-reporting of Hispanic deaths on death certificates), competing theories fall into two categories: the ‘salmon bias hypothesis’, according to which migrants are likely to return to their country of origin after they retire or become seriously ill, and, the ‘healthy migrant hypothesis’, according to which those who migrate and remain in the host country are the healthiest and strongest members of their population of origin. To date, two reviews have documented extensively the wealth of literature on the Hispanic paradox. One, which is very critical of the concept, focuses on low birthweight and infant mortality;1 the other, which is relatively supportive, covers all the different health components involved in the paradox (mortality, infant mortality, violence, AIDS, coronary heart disease, stroke, cancer, and diabetes).2 The first concludes that the evidence supporting the paradox is fragile and highlights the potential role of selective processes in explaining the migrants’ advantage, while the second puts forward the complexity of the picture, with variations by age, gender, type of Hispanic group, degree of acculturation, and specific disease or cause of death. Recently, a paper—to be considered as a landmark in the field—has very elegantly established that neither the salmon bias, nor the selection of healthy Hispanic migrants into the US could explain the mortality advantage of the Hispanics, and called for further research on cultural factors, especially those involving favourable health behaviours, to shed more light on this issue.3 While much controversy surrounds the very existence and interpretations of the Hispanic paradox, it has been argued that ‘investigation of this “paradox” may provide additional insights into the ways that social factors affect the health of the population at-large’,2 and that ‘the Hispanic paradox should be a motivator for further research ...’.1 With this in mind, our purpose is to place the Hispanic paradox in a wider geographical and cultural perspective, by pinpointing the remarkable mortality advantage that some Mediterranean migrant groups enjoy in Germany and France. While the literature on migrants’ mortality is relatively scarce in Europe, two methodologically sound studies have provided quite an unexpected picture. In Germany, analysis of register data has established that the age-adjusted mortality of the 2 million Turkish residents was consistently half that of the Germans, and also less than half that of an urban population in Turkey.4 The former findings, which concerned males and females equally, were confirmed by a cohort study (‘German Socio-Economic Panel’) unlikely to be subject to the inaccuracies of denominator figures.5 Convergent features have emerged from a study based on register and census data in France which highlighted the surprisingly low mortality of Moroccan immigrants, whose number had swollen in the early 1980s to nearly 600 000.6 Using an indirect demographic method originally devised to estimate the completeness of vital statistics in developing countries, the authors have found that the proportion of missing deaths among Moroccans was about 23% for men, and negligible for women. After having corrected the numbers of male deaths accordingly, they found an adjusted life expectancy of 73.7 years in the 1980s, as opposed to 71.3 in the French population, and 78.8 in females as opposed to 79.6 in the French population. And yet, the socio-demographic profile of those migrants—they are frequently illiterate, single, and employed largely as manual workers (83%)—is expected to favour higher mortality. Echoing the Hispanic mortality paradox in the US, the above findings convincingly set the case for a Mediterranean migrants mortality paradox in some Western European countries, and have led to a questioning of the classical interpretations prevalent in the epidemiological and demographic literature. Rather than referring to a ‘salmon bias’, the authors of the European studies have wondered about the existence of a ‘mobility bias’ resulting from an inflation of the denominator base, due to migrants often returning to their home country for short or long periods, be it in relation to their health status or not. Indeed, the Mediterranean countries of Southern Europe and North Africa are geographically close to France and Germany, and migrants often return to their home country during holidays or for family reasons. Individual follow-up such as that implemented in the German Socio-Economic Panel provides strong support for the substantive nature of the mortality advantage, as does the persistence of a substantial under-mortality in the Moroccans study after correction for under-registration of deaths. Possible explanations are then either the role of selective processes (‘healthy migrant hypothesis’) or that of health-protective behaviours. The ‘healthy migrant hypothesis’ is particularly difficult to investigate: first, mortality estimates in countries of origin are not always available for comparative purposes; second, even when they are, differences in health care between countries render the comparisons meaningless, and; third, the regions of origin of the migrants in their home countries are likely to be different in their mortality profile from the national average. In Abraido-Lanza et al.’s paper,3 the mortality rates in Puerto Rico, Cuba, and Mexico were found to be lower than those of the US, and this was interpreted by the authors as consistent with a cultural explanation of the Latino mortality paradox. Those comparisons, however, were not very convincing, given that, as pointed out by Landen,7 they involved crude rather than age-standardized mortality rates. In Europe, the French study is the only one which has incorporated comparisons with the country of origin of the migrants (Morocco). The picture which emerges is that of a much higher life expectancy for the migrants than that estimated for the population of Morocco: the gain in life expectancy was 9.9 years for men, and 11.6 years for women. This may reflect the healthy migrant hypothesis, but not necessarily. Generally speaking, international comparisons are extremely difficult to interpret, with countries differing in numerous factors which influence all-cause mortality, among which are social class, economic indicators, and effectiveness and accessibility of health care and other services.8 In addition, one may legitimately wonder to what extent the selection of applicants for immigration on the basis of their health is a plausible explanation of the mortality paradox. Indeed, two questions are left unanswered: first, do the health selection effects persist long enough to explain a mortality advantage decades after it has taken place, and second, if the migrants are healthier at entry, what are the factors underlying their superior health? Concerning the first point, surprisingly little has been published. Study of an industrial cohort in Great Britain has shown that the ‘healthy worker effect’ was no longer visible 15 years after entry in the cohort,9 while conversely an analysis of the Assets and Health Dynamics of the Oldest Old (AHEAD) in the US concludes that good health of a population at young ages is maintained throughout the lifespan.10 As for Hispanics, the literature indicates that their health and health behaviours deteriorate with acculturation.11 Clearly, more empirical and theoretical studies are needed. Supposing health selection is the key explanation to the mortality advantage, then what are the factors underlying the superior health of the migrants? Do they have lower mortality rates just because the health checks have filtered out the disabled and chronically ill? Or do they have more favourable health behaviours? According to Uitenbroek and Verhoeff,12 who have investigated mortality of the Mediterranean migrants in Amsterdam, selection at entry is not a convincing explanation for their remarkable life expectancy. Indeed, in their twenties and early thirties ‘symptoms of the major causes of death, i.e. cancers and cardiovascular disease are rarely present, and it is difficult to imagine how these young people could have been selected on their future susceptibility’ to those diseases. Those authors, in accord with Razum et al.4 are more supportive of the ‘unhealthy re-migration hypothesis’; in fact a more elaborated version of the ‘salmon bias hypothesis’ which assumes that migrants who re-migrate are those who do not cope well socially and economically, and that those migrants are more likely to experience higher mortality in the future. This can be viewed as a kind of ‘indirect selection’ on factors connected to both socio-occupational skills and health capital, similar to that which has been conceptualized regarding unemployment:13 ‘the mechanism would be that both unemployment and health are related to a certain personality trait’. Could we imagine also that an indirect selection is involved in the migration process, with factors connected to both the will and capacity to migrate and to health? In relation to the ‘salmon bias’ concept, Razum et al.4 also question the plausibility of re-migration of severely ill migrants, considering that it is unlikely that Turkish residents return to their home country when they suffer from ‘conditions such as cardiovascular disease for which medical treatment in Germany is readily available and almost free.’ Economic considerations could therefore deter sick migrants from going home, unless they are moribund, but in this case do they have the strength to undertake a journey back home? Abraido-Lanza et al. consider that the role of cultural factors involving favourable health behaviours is an attractive hypothesis to be tested. If it is confirmed, then this would mean that the migrants would be benefiting from the ‘best of both worlds’:14 the favourable habits of their country of origin and the efficiency of the health care system of their host country. Of the two studies in Europe, the one which has examined causes of death and gathered data on health-related habits is the French one, and the results are quite mixed: on one hand, the death rates from cancers and cardiovascular diseases are much lower among Moroccan males than in the French population, on the other hand, their lifetime consumption of tobacco is comparable, though there are indications that their nutritional habits could be more favourable.15 One important feature of the Moroccan community in France is that they drink very little alcohol, and this could play a major role in their mortality advantage: of all countries in the European Community, France is the one with the highest percentage of heavy alcohol drinkers, and it is characterized by a high alcohol-related premature mortality. There might be cohort effects involved in the lower lung cancer mortality of the Moroccans in France, with heavy smoking limited to the younger cohorts who have not yet reached the age at which lung cancer rates start to rise. Also, a role for alcohol consumption in lung cancer aetiology has been suggested in some studies,16 and one may wonder whether Moroccans are protected from lung cancer in part because they drink very little alcohol. Lastly, the potential role of differential exposure to genetic factors of susceptibility to lung cancer17 is worthy of consideration. Greeks in Australia are another Mediterranean migrant group which was found to have an exceptionally high life expectancy in spite of continuing high rates of cigarette smoking, and this was attributed to the offsetting effects of the Mediterranean diet.14 One of the reviews of the Hispanic paradox concluded by saying that there was a reasonable degree of certainty that the paradox was real for some subgroups, among them older Hispanics.2 In France and Germany, the older cohorts of migrants were precisely those which had the most difficult and hazardous working conditions,18,19 in the mines and the automobile industry. They would, therefore, be expected to have higher mortality. In fact, this was the case for migrants from Eastern European countries but not for Mediterranean migrants.20 To date, the causes of the paradox are largely unknown, be it in the US or in Europe, and, as pointed out by Franzini et al.: if the reasons are largely cultural, then the paradox will only exist for as long as a large percentage of Hispanics remain culturally distinct from the rest of the US ... a rare window of opportunity now exists to learn more about how cultural factors influence one’s health....2 The migrants’ mortality paradox raises challenging questions about the nature of the selective processes related to migration, and those questions have a bearing on health-based selection in general and on the potential role of indirect selection in explaining part of the association between socio-demographic factors and health. The opening up of new research avenues is desirable to meet the challenge, along the lines recently delineated by Schwartz, Susser, and Susser.21 More attention should be paid to the historical context of migration and the past living conditions of the different waves of migrants, before and after migration, and to the legal and jurisdictional aspects of re-migration. Shifting the emphasis from individual-based studies to studies of communities as a whole and of the cultural factors that are related to management of health and disease may provide explanatory leads. As pointed out by Palloni,1 studies of migrants in their host countries should be complemented by: studies of the sending populations, including those people who have returned after being migrants, those who could have been migrants but were not, and those who tried unsuccessfully to be migrants. Also, qualitative studies are potentially very informative with respect to the acculturation process and its health-related aspects, to the cultural representations of health, and the range of motives for re-migration. Last but not least, an international perspective on the subject would throw new light on the how’s and why’s of this enduring epidemiological enigma.

Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function, e.g. mean(), median(), even user-written functions. Regression models are summarized and include the reference rows for categorical variables. Common regression models, such as logistic regression and Cox proportional hazards regression, are automatically identified and the tables are pre-filled with appropriate column headers.

After a period of general convergence, the 1960s were marked by the divergence between the life expectancies of eastern European countries, where all progress came to a halt, and those of the rest of Europe where health care made large strides. A hierarchical analysis of age-specific mortality patterns shows that this divergence goes together with the development of very different patterns of age at death; in the countries of eastern Europe, and especially in the USSR, excess mortality at adult ages is spectacularly high. Cause-specific analysis reveals the decisive role played by two kinds of diseases. On the one hand, ?man-made diseases? (alcoholism, smoking, car accidents, etc.) have continued to increase in the east, whereas they were curbed in the west starting in the 1960s. On the other hand, eastern Europe was unable to join the cardiovascular revolution that had enabled the west to increase its life expectancy levels. The considerable divergence between eastern and western Europe should not hide the differences that still remain among western countries. Indeed, mortality patterns are changing in the west, and the traditional opposition between north and south is undergoing radical transformations.

BACKGROUND: Significant differences in COVID-19 incidence by gender, class and race/ethnicity are recorded in many countries in the world. Lockdown measures, shown to be effective in reducing the number of new cases, may not have been effective in the same way for all, failing to protect the most vulnerable populations. This survey aims to assess social inequalities in the trends in COVID-19 infections following lockdown. METHODS: A cross-sectional survey conducted among the general population in France in April 2020, during COVID-19 lockdown. Ten thousand one hundred one participants aged 18-64, from a national cohort who lived in the three metropolitan French regions most affected by the first wave of COVID-19. The main outcome was occurrence of possible COVID-19 symptoms, defined as the occurrence of sudden onset of cough, fever, dyspnea, ageusia and/or anosmia, that lasted more than 3 days in the 15 days before the survey. We used multinomial regression models to identify social and health factors related to possible COVID-19 before and during the lockdown. RESULTS: In all, 1304 (13.0%; 95% CI: 12.0-14.0%) reported cases of possible COVID-19. The effect of lockdown on the occurrence of possible COVID-19 was different across social hierarchies. The most privileged class individuals saw a significant decline in possible COVID-19 infections between the period prior to lockdown and during the lockdown (from 8.8 to 4.3%, P = 0.0001) while the decline was less pronounced among working class individuals (6.9% before lockdown and 5.5% during lockdown, P = 0.03). This differential effect of lockdown remained significant after adjusting for other factors including history of chronic disease. The odds of being infected during lockdown as opposed to the prior period increased by 57% among working class individuals (OR = 1.57; 95% CI: 1.00-2.48). The same was true for those engaged in in-person professional activities during lockdown (OR = 1.53; 95% CI: 1.03-2.29). CONCLUSIONS: Lockdown was associated with social inequalities in the decline in COVID-19 infections, calling for the adoption of preventive policies to account for living and working conditions. Such adoptions are critical to reduce social inequalities related to COVID-19, as working-class individuals also have the highest COVID-19 related mortality, due to higher prevalence of comorbidities.