The Financial Impact of COVID-19 from the Perspective of Media Coverage: Evidence from China

This paper merges three textual models to construct a series of indicators, which can yield more refined proxies for financial media coverage, to measure the impacts of COVID-19 on Chinese financial markets. Results show that the basic indicator Granger causes the volatilities of bond and stock markets and contributes more to the stock market after the outbreak of COVID-19. Next, four specific market-related indicators have significant effects on the corresponding financial market after the outbreak. Finally, the policy-related indicator has a significant effect on four financial markets after the outbreak, and it causes greater volatility in the stock market. This paper can help the government to stabilize the financial market by managing financial media attention. © 2023 Taylor & Francis Group, LLC.

Korean Language NLP Model Based Emotional Analysis of LGBTQ Social Media Communities

Sexual minorities are increasingly gaining social visibility and legal rights guarantees at the constitutional level across much of the world, from South America, the United States, and Europe to Japan, Taiwan, and Thailand. At the same time, the COVID-19 pandemic has brought on significant mental health challenges for the public due to accompanying social and economic impact and measures, most of them adverse. Given pre-existing studies highlighting the minority demographic's vulnerability to depression and other mental health symptoms, and the increasing availability of accessible NLP tools, datasets, and models, this paper uses an emotional classification model to analyze emotional trends in queer communities on social media. Using KoBERT with a pre-labelled dataset containing some forty thousand scraped social media posts labelled with emotions, patterns of emotional expression on Twitter in the queer community is revealed. Resulting data provided a validation of the viability of this method of analyzing trends in negative and positive emotional expression as well as the impact COVID-19 had on online queer communities in early 2020 but revealed limitations. © 2023 IEEE.

Considering equity in priority setting using transmission models: Recommendations and data needs.

OBJECTIVES: Disease transmission models are used in impact assessment and economic evaluations of infectious disease prevention and treatment strategies, prominently so in the COVID-19 response. These models rarely consider dimensions of equity relating to the differential health burden between individuals and groups. We describe concepts and approaches which are useful when considering equity in the priority setting process, and outline the technical choices concerning model structure, outputs, and data requirements needed to use transmission models in analyses of health equity. METHODS: We reviewed the literature on equity concepts and approaches to their application in economic evaluation and undertook a technical consultation on how equity can be incorporated in priority setting for infectious disease control. The technical consultation brought together health economists with an interest in equity-informative economic evaluation, ethicists specialising in public health, mathematical modellers from various disease backgrounds, and representatives of global health funding and technical assistance organisations, to formulate key areas of consensus and recommendations. RESULTS: We provide a series of recommendations for applying the Reference Case for Economic Evaluation in Global Health to infectious disease interventions, comprising guidance on 1) the specification of equity concepts; 2) choice of evaluation framework; 3) model structure; and 4) data needs. We present available conceptual and analytical choices, for example how correlation between different equity- and disease-relevant strata should be considered dependent on available data, and outline how assumptions and data limitations can be reported transparently by noting key factors for consideration. CONCLUSIONS: Current developments in economic evaluations in global health provide a wide range of methodologies to incorporate equity into economic evaluations. Those employing infectious disease models need to use these frameworks more in priority setting to accurately represent health inequities. We provide guidance on the technical approaches to support this goal and ultimately, to achieve more equitable health policies.

Application and Prospect of Big Data in the Prevention and Control of Major Epidemics

In recent years, various epidemic viruses have seriously threatened the safety of human life. Big data network technology follows the law of network evolution and is an inevitable choice for effective prevention and control of major epidemics. This article takes the epidemic data at the time of the COVID-19 outbreak as the research object, and analyzes the application of big data technology to people's travel, communication and life in the epidemic from the perspective of big data. This article analyzes the correlation between crowd activities and the spread of the epidemic, the crowd mobile network model, the spatial clustering of cases, and the development trend of the epidemic. The results of the study showed that the number of online communities increased from 17 before the outbreak to 21 after the outbreak, and the average community space was reduced to 80.95% before the outbreak. The ratio of the amount of activity between communities to the amount of activities within the community was changed from before the outbreak. The reduction of 0.31 from 0.31 to 0.20 after the outbreak indicates that the scope of crowd activities has shrunk after the outbreak, and population activities among communities have weakened. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Recalibrating the notion of modelling for policymaking during pandemics.

COVID-19 disease models have aided policymakers in low-and middle-income countries (LMICs) with many critical decisions. Many challenges remain surrounding their use, from inappropriate model selection and adoption, inadequate and untimely reporting of evidence, to the lack of iterative stakeholder engagement in policy formulation and deliberation. These issues can contribute to the misuse of models and hinder effective policy implementation. Without guidance on how to address such challenges, the true potential of such models may not be realised. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was formed to address this gap. CMCC is a global collaboration between decision-makers from LMICs, modellers and researchers, and development partners. To understand the limitations of existing COVID-19 disease models (primarily from high income countries) and how they could be adequately support decision-making in LMICs, a desk review of modelling experience during the COVID-19 and past disease outbreaks, two online surveys, and regular online consultations were held among the collaborators. Three key recommendations from CMCC include: A 'fitness-for-purpose' flowchart, a tool that concurrently walks policymakers (or their advisors) and modellers through a model selection and development process. The flowchart is organised around the following: policy aims, modelling feasibility, model implementation, model reporting commitment. Holmdahl and Buckee (2020) A 'reporting standards trajectory', which includes three gradually increasing standard of reports, 'minimum', 'acceptable', and 'ideal', and seeks collaboration from funders, modellers, and decision-makers to enhance the quality of reports over time and accountability of researchers. Malla et al. (2018) A framework for "collaborative modelling for effective policy implementation and evaluation" which extends the definition of stakeholders to funders, ground-level implementers, public, and other researchers, and outlines how each can contribute to modelling. We advocate for standardisation of modelling processes and adoption of country-owned model through iterative stakeholder participation and discuss how they can enhance trust, accountability, and public ownership to decisions.

Role of academic publishers in 10 years: a perspective from the Chairman of Elsevier

While it is unfortunate that we are unable to come together in person, I believe that there is a silver lining in this coronavirus disease 2019 (COVID-19) pandemic for the global publishing industry. The pandemic has allowed us to pause and reflect on our recent progress so that we can accelerate into an exciting new era of scientific research and discovery. © 2022 Korean Council of Science Editors

Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review.

BACKGROUND: How best to prioritise COVID-19 vaccination within and between countries has been a public health and an ethical challenge for decision-makers globally. We reviewed epidemiological and economic modelling evidence on population priority groups to minimise COVID-19 mortality, transmission, and morbidity outcomes. METHODS: We searched the National Institute of Health iSearch COVID-19 Portfolio (a database of peer-reviewed and pre-print articles), Econlit, the Centre for Economic Policy Research, and the National Bureau of Economic Research for mathematical modelling studies evaluating the impact of prioritising COVID-19 vaccination to population target groups. The first search was conducted on March 3, 2021, and an updated search on the LMIC literature was conducted from March 3, 2021, to September 24, 2021. We narratively synthesised the main study conclusions on prioritisation and the conditions under which the conclusions changed. RESULTS: The initial search identified 1820 studies and 36 studies met the inclusion criteria. The updated search on LMIC literature identified 7 more studies. 43 studies in total were narratively synthesised. 74% of studies described outcomes in high-income countries (single and multi-country). We found that for countries seeking to minimise deaths, prioritising vaccination of senior adults was the optimal strategy and for countries seeking to minimise cases the young were prioritised. There were several exceptions to the main conclusion, notably that reductions in deaths could be increased if groups at high risk of both transmission and death could be further identified. Findings were also sensitive to the level of vaccine coverage. CONCLUSION: The evidence supports WHO SAGE recommendations on COVID-19 vaccine prioritisation. There is, however, an evidence gap on optimal prioritisation for low- and middle-income countries, studies that included an economic evaluation, and studies that explore prioritisation strategies if the aim is to reduce overall health burden including morbidity.

The journey to UHC: how well are vertical programmes integrated in the health benefits package? A scoping review.

BACKGROUND: Countries are recommended to progressively work towards universal health coverage (UHC), and to make explicit choices regarding the expansion of priority services. However, there is little guidance on how to manage the inclusion of vertical programmes, funded by external partners, in health benefits packages (HBP) in low and middle-income countries (LMICs). OBJECTIVE: We conducted a scoping review to map the inclusion of six vertical programmes (HIV, tuberculosis, malaria, maternal and child health, contraceptives, immunisation) in 26 LMICs. METHODS: We identified 26 LMICs with an HBP that was not aspirational (eg, with evidence of implementation or funding). For each HBP, we collected information on the corresponding UHC scheme, health financing at the time of establishment, revisions since inception and entitlements. For each vertical programme, we developed a list of tracer interventions based on the Disease Control Priorities 3 and the 100 Core Health Indicators List. We then used this list of tracer interventions to map the coverage of the six vertical programmes. RESULTS: The review shows that there is no common starting point for countries embarking into UHC. Some HBPs were almost three decades old. Whole package revisions are rare. The inclusion of vertical programme does not follow a given pattern based on health financing indicators or country's income group. Maternal child health services are the most often included and family planning the least. Six countries in our sample covered all vertical programmes, while one covered only one of six. CONCLUSIONS: This review has shown that there has been a long history of countries facing this question and we have provided the first mapping of inclusion of vertical programmes in UHC. The results of the mapping can inform decisions in countries embarking in UHC.

Beyond COVID-19: A Whole of Health Look at Impacts During the Pandemic Response

From the Abstract: Substantial evidence has emerged relating to the potential magnitude of the indirect health effects of the coronavirus pandemic. We know, from previous crises and outbreaks (e.g., the Ebola outbreak), that indirect health effects are significant and could outweigh the direct toll from the disease itself. This paper provides an overview of the lessons learned from previous outbreaks and economic crises in relation to indirect health effects as well as a framework for adopting a whole of health approach to the COVID [coronavirus disease 2019] response. This framework articulates indirect health impacts around four distinct but interrelated sets of impacts: economic, environmental, health systems, and social/behavioural. We apply this framework to discuss what is known already on the indirect health impacts of COVID-19. Given the rapidly changing nature of the outbreak and the constant publication of new evidence, this paper summarizes our current best knowledge and understanding, adopting a horizontal view to contextualise COVID-19 within the health system, and the whole economy.COVID-19 (Disease);Public health