Infectious diseases, dividend policy, and independent directors: Evidence from textual analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Ungpakorn S
PROVIDER: S-EPMC9894484 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature
Publications
Infectious diseases, dividend policy, and independent directors: Evidence from textual analysis.
Ungpakorn Saranyu S Chatjuthamard Pattanaporn P Jiraporn Pornsit P Phiromswad Piyachart P
PloS one 20230202 2
We investigated the effect of uncertainty associated with infectious diseases on corporate dividend policy. We used a unique text-based measure of infectious diseases that includes not only the Covid-19, but also other important diseases, such as SARs, MERs, and Ebola. Based on a sample of 287,151 firm-year observations across four decades (from 1985 to 2021), our results show that a higher level of uncertainty associated with infectious diseases significantly reduce dividends. Interestingly, we ...[more]
Similar Datasets
Project description:BackgroundIn collaboration with local partners, we reviewed 18 national policy documents across two sub-Saharan African countries identified as pre-dividend nations by the World Bank in 2017: Nigeria and Tanzania. Our aim was to assess national policies in pre-dividend countries and to determine whether national strategies were primed to capitalize on changing demographic structures, maximally attain the demographic dividend, and augment socio-economic growth.MethodsWe conducted policy reviews by focusing on five key sectors of the Gates Institute Demographic Dividend Framework: Family Planning, Maternal and Child Health, Education, Women's Empowerment, and Labor Market. This framework was developed as a tool for countries to apply targeted policies for accelerating the demographic dividend based on their demographic structure. For each component we used a comprehensive list of indicators, defined via a systematic literature review, through which we assessed national policies aimed at maximizing the demographic dividend.ResultsBetween the two countries, we observed persistent gaps in policies targeting family planning. Although more comprehensive, policies addressing maternal and child health, education, women's empowerment, and labor market still lagged in their specificity and measurability. We identified specific policy amendments and alternatives that Nigeria and Tanzania could consider to mitigate these gaps. We also stress the importance of designing measurable policy initiatives across sectors.ConclusionsBased on these recommendations, as Nigeria, Tanzania, and other pre-dividend nations start experiencing rapid demographic changes, they may consider implementing routine policy reviews to strengthen policies across the five key sectors and harness the benefits of a demographic dividend.
| S-EPMC10240741 | biostudies-literature
Project description:BackgroundOnly a small number of previous efforts to describe the experiences of organizations that produce clinical practice guidelines (CPGs), undertake health technology assessments (HTAs), or directly support the use of research evidence in developing health policy (i.e., government support units, or GSUs) have relied on interviews and then only with HTA agencies. Interviews offer the potential for capturing experiences in great depth, particularly the experiences of organizations that may be under-represented in surveys.MethodsWe purposively sampled organizations from among those who completed a questionnaire in the first phase of our three-phase study, developed and piloted a semi-structured interview guide, and conducted the interviews by telephone, audio-taped them, and took notes simultaneously. Binary or categorical responses to more structured questions were counted when possible. Themes were identified from among responses to semi-structured questions using a constant comparative method of analysis. Illustrative quotations were identified to supplement the narrative description of the themes.ResultsWe interviewed the director (or his or her nominee) in 25 organizations, of which 12 were GSUs. Using rigorous methods that are systematic and transparent (sometimes shortened to 'being evidence-based') was the most commonly cited strength among all organizations. GSUs more consistently described their close links with policymakers as a strength, whereas organizations producing CPGs, HTAs, or both had conflicting viewpoints about such close links. With few exceptions, all types of organizations tended to focus largely on weaknesses in implementation, rather than strengths. The advice offered to those trying to establish similar organizations include: 1) collaborate with other organizations; 2) establish strong links with policymakers and stakeholders; 3) be independent and manage conflicts of interest; 4) build capacity; 5) use good methods and be transparent; 6) start small and address important questions; and 7) be attentive to implementation considerations. The advice offered to the World Health Organization (WHO) and other international organizations and networks was to foster collaborations across organizations.ConclusionThe findings from our interview study, the most broadly based of its kind, extend to both CPG-producing organizations and GSUs the applicability of the messages arising from previous interview studies of HTA agencies, such as to collaborate with other organizations and to be attentive to implementation considerations. Our interview study also provides a rich description of organizations supporting the use of research evidence, which can be drawn upon by those establishing or leading similar organizations in LMICs.
| S-EPMC2639615 | biostudies-literature
Project description:The Global Rapid Identification of Threats System (GRITS) is a biosurveillance application that enables infectious disease analysts to monitor nontraditional information sources (e.g., social media, online news outlets, ProMED-mail reports, and blogs) for infectious disease threats. GRITS analyzes these textual data sources by identifying, extracting, and succinctly visualizing epidemiologic information and suggests potentially associated infectious diseases. This manuscript evaluates and verifies the diagnoses that GRITS performs and discusses novel aspects of the software package. Via GRITS' web interface, infectious disease analysts can examine dynamic visualizations of GRITS' analyses and explore historical infectious disease emergence events. The GRITS API can be used to continuously analyze information feeds, and the API enables GRITS technology to be easily incorporated into other biosurveillance systems. GRITS is a flexible tool that can be modified to conduct sophisticated medical report triaging, expanded to include customized alert systems, and tailored to address other biosurveillance needs.
| S-EPMC5028852 | biostudies-literature
Project description:ObjectivesThroughout the coronavirus disease 2019 pandemic, susceptible-infectious-recovered (SIR) modeling has been the preeminent modeling method to inform policy making worldwide. Nevertheless, the usefulness of such models has been subject to controversy. An evolution in the epidemiological modeling field is urgently needed, beginning with an agreed-upon set of modeling standards for policy recommendations. The objective of this article is to propose a set of modeling standards to support policy decision making.MethodsWe identify and describe 5 broad standards: transparency, heterogeneity, calibration and validation, cost-benefit analysis, and model obsolescence and recalibration. We give methodological recommendations and provide examples in the literature that employ these standards well. We also develop and demonstrate a modeling practices checklist using existing coronavirus disease 2019 literature that can be employed by readers, authors, and reviewers to evaluate and compare policy modeling literature along our formulated standards.ResultsWe graded 16 articles using our checklist. On average, the articles met 6.81 of our 19 categories (36.7%). No articles contained any cost-benefit analyses and few were adequately transparent.ConclusionsThere is significant room for improvement in modeling pandemic policy. Issues often arise from a lack of transparency, poor modeling assumptions, lack of a system-wide perspective in modeling, and lack of flexibility in the academic system to rapidly iterate modeling as new information becomes available. In anticipation of future challenges, we encourage the modeling community at large to contribute toward the refinement and consensus of a shared set of standards for infectious disease policy modeling.
| S-EPMC8110035 | biostudies-literature
Project description:RationaleThe host-pathogen relationship is inherently dynamic and constantly evolving. Applying an implementation science lens to policy evaluation suggests that policy impacts are variable depending upon key implementation outcomes (feasibility, acceptability, appropriateness costs) and conditions and contexts.Covid-19 case studyExperiences with non-pharmaceutical interventions (NPIs) including masking, testing, and social distancing/business and school closures during the COVID-19 pandemic response highlight the importance of considering public health policy impacts through an implementation science lens of constantly evolving contexts, conditions, evidence, and public perceptions. As implementation outcomes (feasibility, acceptability) changed, the effectiveness of these interventions changed thereby altering public health policy impact. Sustainment of behavioral change may be a key factor determining the duration of effectiveness and ultimate impact of pandemic policy recommendations, particularly for interventions that require ongoing compliance at the level of the individual.Practical framework for assessing and evaluating pandemic policyUpdating public health policy recommendations as more data and alternative interventions become available is the evidence-based policy approach and grounded in principles of implementation science and dynamic sustainability. Achieving the ideal of real-time policy updates requires improvements in public health data collection and analysis infrastructure and a shift in public health messaging to incorporate uncertainty and the necessity of ongoing changes. In this review, the Dynamic Infectious Diseases Public Health Response Framework is presented as a model with a practical tool for iteratively incorporating implementation outcomes into public health policy design with the aim of sustaining benefits and identifying when policies are no longer functioning as intended and need to be adapted or de-implemented.Conclusions and implicationsReal-time decision making requires sensitivity to conditions on the ground and adaptation of interventions at all levels. When asking about the public health effectiveness and impact of non-pharmaceutical interventions, the focus should be on when, how, and for how long they can achieve public health impact. In the future, rather than focusing on models of public health intervention effectiveness that assume static impacts, policy impacts should be considered as dynamic with ongoing re-evaluation as conditions change to meet the ongoing needs of the ultimate end-user of the intervention: the public.
| S-EPMC10469790 | biostudies-literature
Project description:Most of the knowledge regarding genes and proteins is stored in biomedical literature as free text. Extracting information from complex biomedical texts demands techniques capable of inferring biological concepts from local text regions and mapping them to controlled vocabularies. To this end, we present a sentence-based correspondence latent Dirichlet allocation (scLDA) model which, when trained with a corpus of PubMed documents with known GO annotations, performs the following tasks: 1) learning major biological concepts from the corpus, 2) inferring the biological concepts existing within text regions (sentences), and 3) identifying the text regions in a document that provides evidence for the observed annotations. When applied to new gene-related documents, a trained scLDA model is capable of predicting GO annotations and identifying text regions as textual evidence supporting the predicted annotations. This study uses GO annotation data as a testbed; the approach can be generalized to other annotated data, such as MeSH and MEDLINE documents.
| S-EPMC3243146 | biostudies-literature
Project description:The chapter describes bacerial, viral, parasitic and fungal infections commonly detected in pet birds. The chapter includes history, etiology, susceptible hosts, transmission, pathogenesis, clinical symptoms, lesion, diagnosis, zoonosis, Treatment and control strategy of Tuberculosis, Salmonellosis, Chlamydiosis, Campylobacteriosis, Lyme disease, other bacterial infection, Newcastle disease, Avian Influenza infection, West Nile Virus infection, Usutu virus infection, Avian Borna Virus infection, Beak and feather disease, other viral infection, Toxoplasmosis, Giardiasis, Cryptosporidiosis, other parasitic infection, Cryptococcosis, Aspergillosis, Other fungal infections.
| S-EPMC7121861 | biostudies-literature
Project description:The dataset presented in this data article was compiled from 100 published and unpublished empirical studies that employed Lintner׳s dividend payout model or related extensions over the period 1957-2016. Besides the reported degree of dividend smoothing and its estimation precision the data include a wide set of underlying study design characteristics such as the time period of analysis, the type of firms investigated or the econometric estimator employed. The data are related to the research article "What drives dividend smoothing? A meta-regression analysis of the Lintner model" (Fernau and Hirsch, 2018).
| S-EPMC6362866 | biostudies-literature
Project description:This study investigates the impact of environmental, social, and governance (ESG) scores on dividend policy, while taking into account the moderating effect of financial sustainability. It examines data from companies listed on the Saudi Exchange, during the period spanning the years from 2013 to 2022. According to the findings of panel regression analysis, there is a strong positive correlation between ESG performance and dividend payments. In essence, businesses that exhibit strong ESG practices continuously maintain dividend payments as a way of demonstrating their dedication to both stakeholders and shareholders. Furthermore, financial sustainability exerts an enhancing influence on the ESG-dividend relationship, indicating that the positive effect of ESG on dividend yields is significant in financially sustainable companies compared to their peers. It is noteworthy that these conclusions hold up well even when put through sensitivity studies using different estimating methods. The implications of these results extend to a broad spectrum of stakeholders, including investors, management, analysts, and policymakers. They provide valuable insights for companies and markets seeking to expand their ESG initiatives.
| S-EPMC11620373 | biostudies-literature
Project description:OBJECTIVE:The outbreak of infectious diseases has a negative influence on public health and the economy. The prediction of infectious diseases can effectively control large-scale outbreaks and reduce transmission of epidemics in rapid response to serious public health events. Therefore, experts and scholars are increasingly concerned with the prediction of infectious diseases. However, a knowledge mapping analysis of literature regarding the prediction of infectious diseases using rigorous bibliometric tools, which are supposed to offer further knowledge structure and distribution, has been conducted infrequently. Therefore, we implement a bibliometric analysis about the prediction of infectious diseases to objectively analyze the current status and research hotspots, in order to provide a reference for related researchers. METHODS:We viewed "infectious disease*" and "prediction" or "forecasting" as search theme in the core collection of Web of Science from inception to 1 May 2020. We used two effective bibliometric tools, i.e., CiteSpace (Drexel University, Philadelphia, PA, USA) and VOSviewer (Leiden University, Leiden, The Netherlands) to objectively analyze the data of the prediction of infectious disease domain based on related publications, which can be downloaded from the core collection of Web of Science. Then, the leading publications of the prediction of infectious diseases were identified to detect the historical progress based on collaboration analysis, co-citation analysis, and co-occurrence analysis. RESULTS:1880 documents that met the inclusion criteria were extracted from Web of Science in this study. The number of documents exhibited a growing trend, which can be expressed an increasing number of experts and scholars paying attention to the field year by year. These publications were published in 427 different journals with 11 different document types, and the most frequently studied types were articles 1618 (83%). In addition, as the most productive country, the United States has provided a lot of scientific research achievements in the field of infectious diseases. CONCLUSION:Our study provides a systematic and objective view of the field, which can be useful for readers to evaluate the characteristics of publications involving the prediction of infectious diseases and for policymakers to take timely scientific responses.
| S-EPMC7504049 | biostudies-literature