Learning about unprecedented events: Agent-based modelling and the stock market impact of COVID-19.

We model the learning process of market traders during the unprecedented COVID-19 event. We introduce a behavioural heterogeneous agents' model with bounded rationality by including a correction mechanism through representativeness (Gennaioli et al., 2015). To inspect the market crash induced by the pandemic, we calibrate the STOXX Europe 600 Index, when stock markets suffered from the greatest single-day percentage drop ever. Once the extreme event materializes, agents tend to be more sensitive to all positive and negative news, subsequently moving on to close-to-rational. We find that the deflation mechanism of less representative news seems to disappear after the extreme event.

Online panel data quality: a sentiment analysis based on a deep learning approach

The rise of online access panels has profoundly changed the market research landscape. Often presented by their owners as very powerful tools, they nevertheless raise important scientific questions, particularly regarding the representativeness of the samples they produce and, consequently, the validity of the information they provide. In this paper, we present an innovative approach, based on deep learning and sentiment analysis techniques, to assess in real time the representativeness of an online panel sample. The idea is to measure the extent to which the opinions of an online panel converge with opinions on social networks. To validate the proposed method, we conducted a case study on the emerging discussion on coronavirus disease (COVID-19) vaccination. The results not only proved the representativeness of online panel sample, but also demonstrated the feasibility and effectiveness of our approach. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

Limitations introduced by a low participation rate of SARS-CoV-2 seroprevalence data.

BACKGROUND: There has been a large influx of COVID-19 seroprevalence studies, but comparability between the seroprevalence estimates has been an issue because of heterogeneities in testing platforms and study methodology. One potential source of heterogeneity is the response or participation rate. METHODS: We conducted a review of participation rates (PR) in SARS-CoV-2 seroprevalence studies collected by SeroTracker and examined their effect on the validity of study conclusions. PR was calculated as the count of participants for whom the investigators had collected a valid sample, divided by the number of people invited to participate in the study. A multivariable beta generalized linear model with logit link was fitted to determine if the PR of international household and community-based seroprevalence studies was associated with the factors of interest, from 1 December 2019 to 10 March 2021. RESULTS: We identified 90 papers based on screening and were able to calculate the PR for 35 out of 90 papers (39%), with a median PR of 70% and an interquartile range of 40.92; 61% of the studies did not report PR. CONCLUSIONS: Many SARS-CoV-2 seroprevalence studies do not report PR. It is unclear what the median PR rate would be had a larger portion not had limitations in reporting. Low participation rates indicate limited representativeness of results. Non-probabilistic sampling frames were associated with higher participation rates but may be less representative. Standardized definitions of participation rate and data reporting necessary for the PR calculations are essential for understanding the representativeness of seroprevalence estimates in the population of interest.

A Tale of Two Cities in Local Democratic Innovation: The Experiences of the Participatory Budget in Milan and the Local Community Development in Reggio Calabria from the Perspective of Edu-Communication

Urban participation formats have experienced a dynamic season of experimentation in Italy in the last 15 years. In this period, two questions about the inclusion and representativeness of the participants in these formats of urban democracy have arisen: How inclusive and representative of urban communities are they? How does the selection of the participatory tools created by the cities collect the community of participants? In identifying a need for education in edu-communication, as defined by Freire, for a better and deeper civic participation to urban democracy, the article presents and discusses two case studies focusing on participatory budget (Milan) and local community development (Reggio Calabria). In the comparisons between genesis, format, and development, the two case studies present the same need for edu-communication functions: civic training, empowering diverse types of citizens for urban decision-making, supporting inclusive democratic processes at the local level, and enhancing comprehensive urban decision-building, open to communities. In this sense, we consider both theoretically and empirically the role of edu-communication as a leverage for better urban democracy, and we detect risks and opportunities in the two case studies that could benefit from a greater use of edu-communication, especially in the post–COVID-19 context and in light of international experiences.

OpenSAFELY: Representativeness of electronic health record platform OpenSAFELY-TPP data compared to the population of England.

Background: Since its inception in March 2020, data from the OpenSAFELY-TPP electronic health record platform has been used for more than 20 studies relating to the global COVID-19 emergency. OpenSAFELY-TPP data is derived from practices in England using SystmOne software, and has been used for the majority of these studies. We set out to investigate the representativeness of OpenSAFELY-TPP data by comparing it to national population estimates.    Methods: With the approval of NHS England, we describe the age, sex, Index of Multiple Deprivation and ethnicity of the OpenSAFELY-TPP population compared to national estimates from the Office for National Statistics. The five leading causes of death occurring between the 1st January 2020 and the 31st December 2020 were also compared to deaths registered in England during the same period.  Results: Despite regional variations, TPP is largely representative of the general population of England in terms of IMD (all within 1.1 percentage points), age, sex (within 0.1 percentage points), ethnicity and causes of death. The proportion of the five leading causes of death is broadly similar to those reported by ONS (all within 1 percentage point).  Conclusions: Data made available via OpenSAFELY-TPP is broadly representative of the English population. Users of OpenSAFELY must consider the issues of representativeness, generalisability and external validity associated with using TPP data for health research. Although the coverage of TPP practices varies regionally across England, TPP registered patients are generally representative of the English population as a whole in terms of key demographic characteristics.

REONTOLOGIZATION OF RELIGIOUS IDENTITY IN THE LIQUID AND GLOBAL WORLD

In this article, I intend to highlight the fact that the realities that are being recorded at the morphological level of contemporary societies (the phenomenon of migration, wars, the dynamics of mobility and communication, the economic pace, the health crisis generated by Covid-19) are bringing to the fore the redefinition of religious identity. What is undeniably clear is that Western societies have become an ethnic and religious mosaic, a diversity that requires specific regulations in terms of norms in order to avoid conflict. However, this ethno-religious diversity also calls for an interpretation of the relationship between identities. The aim of my analysis is to argue as to whether or not religious identity is an inflexible, immobile reality, static in its representativeness towards and in relation to other identities representing different religious cultures. In this respect, I will insist on the role that migration plays in the construction of religious identity. Is religious identity decomposing in the context of the liquid flow of global society? Are the boundaries of such an identity, as structures of individual, social, cultural validation, desubstantiated in the daily experience of religious diversity and in the dynamics of current societal transformations?Alternate :Dans cet article, j'entends souligner le fait que les réalités qui s'enregistrent au niveau morphologique des sociétés contemporaines (le phénomène de migration, les guerres, les dynamiques de mobilité et de communication, le rythme économique, la crise sanitaire générée by Covid-19) mettent au premier plan la redéfinition de l'identité religieuse. Ce qui est indéniable, c'est que les sociétés occidentales sont devenues une mosaïque ethnique et religieuse, une diversité qui nécessite des régulations spécifiques en termes de normes afin d'éviter les conflits. Mais cette diversité ethno-religieuse appelle aussi une lecture des relations entre les identités. Le but de mon analyse est d'argumenter pour savoir si l'identité religieuse est ou non une réalité inflexible, immobile, statique dans sa représentativité envers et par rapport à d'autres identités représentant différentes cultures religieuses. A cet égard, j'insisterai sur le rôle que joue la migration dans la construction de l'identité religieuse. L'identité religieuse se décompose-t-elle dans le contexte du flux liquide de la société mondiale? Les frontières d'une telle identité, en tant que structures de validation individuelle, sociale, culturelle, sont-elles infondées dans l'expérience quotidienne de la diversité religieuse et dans la dynamique des transformations sociétales en cours?Alternate :În acest articol îmi propun să evidenţiez faptul că realităţile care se înregistrează la nivelul morfologic al societăţilor contemporane (fenomenul migraţiei, războaiele, dinamica mobilităţii și comunicării, ritmul economic, criza de sănătate generată). de Covid-19) aduc în prim plan redefinirea identităţii religioase. Ceea ce este incontestabil clar este că societăţile occidentale au devenit un mozaic etnic și religios, o diversitate care necesită reglementări specifice în ceea ce privește normele pentru a evita conflictele. Cu toate acestea, această diversitate etno-religioasă necesită și o interpretare a relaţiei dintre identităţi. Scopul analizei mele este de a argumenta dacă identitatea religioasă este sau nu o realitate inflexibilă, imobilă, statică în reprezentativitatea ei faţă de și în relaţie cu alte identităţi care reprezintă diferite culturi religioase. În acest sens, voi insista asupra rolului pe care îl joacă migraţia în construirea identităţii religioase. Se descompune identitatea religioasă în contextul fluxului lichid al societăţii globale? Graniţele unei astfel de identităţi, ca structuri de validare individuală, socială, culturală, sunt desubstanţiate în experienţa zilnică a diversităţii religioase și în dinamica transformărilor socie ale actuale?

Standardizing States of Emergency: Fragmented Legitimacy of Model Public Health Lawmaking

The promulgation of model laws—exemplary statutes that states can voluntarily choose to adopt—is a prominent strategy that reformers in public health agencies, the legal academy, and non governmental organizations use to improve US public health law and make it more uniform. This article applies the science and technology studies literature on standardization to the process of model lawmaking to analyze how developers negotiate between alternative forms of expertise and utilize different drafting processes to secure the techno-political legitimacy of their model statutes. Drawing on archival records and interviews with thirty-four experts involved in the development of four model public health laws produced between 1999 and 2007, I show how developers work to satisfy multiple, and, at times, competing, audiences. I observe that developers leveraged forms of legal expertise to secure their model laws’ technical legitimacy and emphasized their objectivity, representativeness, and flexibility to promote their political legitimacy. Comparing the four model laws across several indicia of legitimacy, I find that the developers experienced varying degrees of success. This study contributes to the socio legal scholarship on model laws by revealing how they are able to achieve legitimacy, albeit fragmented, even in the context of scientific uncertainty.

The value of network data confirmed by the Covid-19 epidemic and its expanded usages

Data driven analysis is proven to create a competitive advantage to business. Governments and nonprofit organizations also turn to Big Data to harness its benefits and use it for social good. Among different types of data sources, location data collected from mobile networks is especially valuable for its representativeness, real-time observation, and versatility. There is a distinction between mobile positioning data (MPD) generated by the exchanges between mobile devices and the core network;versus over-the-top or system-level location data collecting individual GPS location. MPD is composed of all mobile network events regardless of the mobile phone brand, operating system, app usage, frequency bands or mobile generation;it is uniform and ubiquitous. Getting the best out of MPD relies on the knowledge of how to create an advanced algorithm for homogeneously processing this massive, complex data into insightful indicators. Anonymized and aggregated MPD enables the testing of multiple combinations with other data sources, fully abiding by GDPR, to arrive at innovative solutions. These unique insights can help tackle societal challenges (the state of mobile data for social good June 2017 GSMA, UN Global pulse). It can help to establish accurate statistics about population movements, density, location, social patterns, finances, and ambient environmental conditions. This article demonstrates how MPD has been used to help combat Covid-19 in Europe, the Middle East, and Africa. Furthermore, depending on the future direction, MPD and data analysis can serve powering economic development as well as working toward the Sustainable Development Goals, whilst respecting data privacy.

Quantifying representativeness in randomized clinical trials using machine learning fairness metrics.

OBJECTIVE: We help identify subpopulations underrepresented in randomized clinical trials (RCTs) cohorts with respect to national, community-based or health system target populations by formulating population representativeness of RCTs as a machine learning (ML) fairness problem, deriving new representation metrics, and deploying them in easy-to-understand interactive visualization tools. MATERIALS AND METHODS: We represent RCT cohort enrollment as random binary classification fairness problems, and then show how ML fairness metrics based on enrollment fraction can be efficiently calculated using easily computed rates of subpopulations in RCT cohorts and target populations. We propose standardized versions of these metrics and deploy them in an interactive tool to analyze 3 RCTs with respect to type 2 diabetes and hypertension target populations in the National Health and Nutrition Examination Survey. RESULTS: We demonstrate how the proposed metrics and associated statistics enable users to rapidly examine representativeness of all subpopulations in the RCT defined by a set of categorical traits (eg, gender, race, ethnicity, smoking status, and blood pressure) with respect to target populations. DISCUSSION: The normalized metrics provide an intuitive standardized scale for evaluating representation across subgroups, which may have vastly different enrollment fractions and rates in RCT study cohorts. The metrics are beneficial complements to other approaches (eg, enrollment fractions) used to identify generalizability and health equity of RCTs. CONCLUSION: By quantifying the gaps between RCT and target populations, the proposed methods can support generalizability evaluation of existing RCT cohorts. The interactive visualization tool can be readily applied to identified underrepresented subgroups with respect to any desired source or target populations.

Conducting a multi-country online alcohol survey in the time of the COVID-19 pandemic: Opportunities and challenges.

OBJECTIVES: This contribution provides insights into the methodology of a pan-European population-based online survey, performed without external funding during the COVID-19 pandemic. We present the impact of different dissemination strategies to collect data from a non-probabilistic convenience sample and outline post-stratification weighting schemes, to provide guidance for future multi-country survey studies. METHODS: Description and comparison of dissemination strategies for five exemplary countries (Czechia, Germany, Lithuania, Norway, Spain) participating in the Alcohol Use and COVID-19 Survey. Comparison of the sample distribution with the country's actual population distribution according to sociodemographics, and development of weighting schemes. RESULTS: The dissemination of online surveys through national newspapers, paid social media adverts and dissemination with the support of national health ministries turned out to be the most effective strategies. Monitoring the responses and adapting dissemination strategies to reach under-represented groups, and the application of sample weights were helpful to achieve an analytic sample matching the respective general population profiles. CONCLUSION: Reaching a large pan-European convenience sample, including most European countries, in a short time was feasible, with the support of a broad scientific network.