Public Decision Research Articles

Improving Transparency of Decision Models Through the Application of Decision Analytic Models with Omitted Objects Displayed (DAMWOOD).

The coronavirus disease 2019 (COVID-19) pandemic has increased public awareness of the influence of epidemiological and economic decision models on public policy decisions. Alongside this is an increased scrutiny on the development, analysis, reporting and utilisation of decision models for public policy making. Therefore, it is important that model developers can clearly explain and justify to all stakeholders what is included and excluded from a model developed to support decision-making, to both improve transparency and trust in decision-making. Our aim is to provide tools for improving communication between modellers and decision-makers, leading to improved transparency in decision-making. To do so, we extend the recently described directed acyclic graphs with omitted objects displayed (DAGWOOD) approach from Haber et al. (Ann Epidemiol 68:64-71, 2022) to decision analytic models, giving the decision analytic models with omitted objects displayed (DAMWOOD) approach. DAMWOOD is a framework for the identification of objects omitted from a decision model, as well as for consideration of the effects of omissions on model outcomes. Objects omitted from a decision model are classed as either an exclusion (known and unknown confounders), misdirection (alternative model pathways) or structure (e.g. model type, methods for estimating relationships between objects). DAMWOOD requires model developers to use explicit statements and provide illustration of included and omitted objects, supporting communication with model users and stakeholders, allowing them to provide input and feedback to modellers about which objects to include or omit in a model. In developing DAMWOOD, we considered two challenges we encountered in modelling for pandemic policy response. First, the scope of the decision problem is not always made sufficiently explicit by decision-makers, requiring modellers to intuit which policy options should be considered, and/or which outcomes should be considered in their evaluation. Second, there is rarely sufficient transparency to ensure stakeholders can see what is included in models and why. This limits stakeholders' ability to advocate to decision-makers for the prioritisation of specific outcomes and challenge the model results. To illustrate the application of DAMWOOD, we apply it to a previously published COVID-19 vaccine allocation optimisation model. The DAMWOOD diagrams illustrate the ways in which it is possible to improve the communication of model assumptions. The diagrams make explicit which outcomes are omitted and provide information on the expected impact of the omissions on model results. We discuss the usefulness of DAMWOOD for framing the decision problem, communicating the model structure and results and engaging with those making and affected by the decisions the model is developed to inform.

Pengaruh kompetensi dan integritas pada kualitas audit dengan key audit matters sebagai moderasi

This research aims to determine the influence of competency and integrity on audit quality with key audit matters as moderation at public accounting firms in DKI Jakarta that are active and registered with the Financial Services Authority (OJK). This research uses primary data with a survey method, namely distributing questionnaires with sample determination using a random sampling method, which 127 respondents used to spread across several Public Accounting Firms in DKI Jakarta. The data analysis method used in this research is the multiple regression method. This research shows that competence and integrity positively affect audit quality, and related moderating variables show that key audit matters (KAMs) cannot strengthen the relationship between competence and integrity on audit quality. Public interest statements Ensuring auditors' competency and integrity and effectively utilizing key matters (KAM) makes the audit process more transparent. This fosters greater public confidence in audited financial reports and ensures the reliability of company-provided information. Regulating the influence of competence and integrity on audit quality through KAM is expected to enhance transparency in financial information management, allowing for more informed public investment and financial decisions.

Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccination Against SARS-CoV-2 Omicron XBB and BA.2.86/JN.1 Lineage Hospitalization and a Comparison of Clinical Severity-IVY Network, 26 Hospitals, October 18, 2023-March 9, 2024.

Assessing variant-specific COVID-19 vaccine effectiveness (VE) and severity can inform public health risk assessments and decisions about vaccine composition. BA.2.86 and its descendants, including JN.1 (referred to collectively as "JN lineages"), emerged in late 2023 and exhibited substantial divergence from co-circulating XBB lineages. We analyzed patients hospitalized with COVID-19-like illness at 26 hospitals in 20 U.S. states admitted October 18, 2023-March 9, 2024. Using a test-negative, case-control design, we estimated effectiveness of an updated 2023-2024 (Monovalent XBB.1.5) COVID-19 vaccine dose against sequence-confirmed XBB and JN lineage hospitalization using logistic regression. Odds of severe outcomes, including intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) or death, were compared for JN versus XBB lineage hospitalizations using logistic regression. 585 case-patients with XBB lineages, 397 case-patients with JN lineages, and 4,580 control-patients were included. VE in the first 7-89 days after receipt of an updated dose was 54.2% (95% CI = 36.1%-67.1%) against XBB lineage hospitalization and 32.7% (95% CI = 1.9%-53.8%) against JN lineage hospitalization. Odds of ICU admission (adjusted odds ratio [aOR] 0.80; 95% CI = 0.46-1.38) and IMV or death (aOR 0.69; 95% CI = 0.34-1.40) were not significantly different among JN compared to XBB lineage hospitalizations. Updated 2023-2024 COVID-19 vaccination provided protection against both XBB and JN lineage hospitalization, but protection against the latter may be attenuated by immune escape. Clinical severity of JN lineage hospitalizations was not higher relative to XBB.

Impact of twelve immunization-preventable infectious diseases on population health using disability-adjusted life years (DALYs) in Spain

BackgroundThe objective of this study is to estimate the burden of selected immunization-preventable infectious diseases in Spain using the Burden of Communicable Diseases in Europe (BCoDE) methodology, as well as focusing on the national immunization programme and potential new inclusions.MethodsThe BCoDE methodology relies on an incidence and pathogen-based approach to calculate disease burden via disability-adjusted life year (DALY) estimates. It considers short and long-term sequelae associated to an infection via outcome trees. The BCoDE toolkit was used to populate those trees with Spanish-specific incidence estimates, and de novo outcome trees were developed for four infections (herpes zoster, rotavirus, respiratory syncytial virus [RSV], and varicella) not covered by the toolkit. Age/sex specific incidences were estimated based on data from the Spanish Network of Epidemiological Surveillance; hospitalisation and mortality rates were collected from the Minimum Basic Data Set. A literature review was performed to design the de novo models and obtain the rest of the parameters. The methodology, assumptions, data inputs and results were validated by a group of experts in epidemiology and disease modelling, immunization and public health policy.ResultsThe total burden of disease amounted to 163.54 annual DALYs/100,000 population. Among the selected twelve diseases, respiratory infections represented around 90% of the total burden. Influenza exhibited the highest burden, with 110.00 DALYs/100,000 population, followed by invasive pneumococcal disease and RSV, with 25.20 and 10.57 DALYs/100,000 population, respectively. Herpes zoster, invasive meningococcal disease, invasive Haemophilus influenza infection and hepatitis B virus infection ranked lower with fewer than 10 DALYs/100,000 population each, while the rest of the infections had a limited burden (< 1 DALY/100,000 population). A higher burden of disease was observed in the elderly (≥ 60 years) and children < 5 years, with influenza being the main cause. In infants < 1 year, RSV represented the greatest burden.ConclusionsAligned with the BCoDE study, the results of this analysis show a persisting high burden of immunization-preventable respiratory infections in Spain and, for the first time, highlight a high number of DALYs due to RSV. These estimates provide a basis to guide prevention strategies and make public health decisions to prioritise interventions and allocate healthcare resources in Spain.

Safety assessment of brexanolone in the FAERS database: real adverse event analysis and discussion of side effects

ABSTRACT Background Postpartum depression (PPD) is linked to hormonal changes. Brexanolone, the first FDA-approved drug for PPD, is a potential treatment. This study analyzes Brexanolone’s safety using the FAERS database, highlighting its adverse effects and potential risk factors. Methods We analyzed FAERS data from Q3 2019 to Q3 2023, evaluating adverse reactions to Brexanolone. The analysis includes demographics, reporting regions, reporter identities, and types of adverse reactions. Results Most reports are from the United States, with consumers and physicians as primary reporters. Adverse reactions mainly involve severe systemic diseases, administration site reactions, injuries, intoxication, operational complications, and mental disorders. Specific adverse reactions include incorrect drug monitoring, PPD, intrusive thoughts, delayed treatment efficacy, sedation complications, product discontinuation, misuse, infusion site leakage and pain, and medication errors. Conclusion The study confirms known safety information about Brexanolone and provides comprehensive data for medical practices and public health decisions. However, relying on spontaneous reports may introduce biases and incomplete information. Continued monitoring and reporting of adverse reactions to newer drugs like Brexanolone remain crucial.

A frugal CRISPR kit for equitable and accessible education in gene editing and synthetic biology

Equitable and accessible education in life sciences, bioengineering, and synthetic biology is crucial for training the next generation of scientists, fostering transparency in public decision-making, and ensuring biotechnology can benefit a wide-ranging population. As a groundbreaking technology for genome engineering, CRISPR has transformed research and therapeutics. However, hands-on exposure to this technology in educational settings remains limited due to the extensive resources required for CRISPR experiments. Here, we develop CRISPRkit, an affordable kit designed for gene editing and regulation in high school education. CRISPRkit eliminates the need for specialized equipment, prioritizes biosafety, and utilizes cost-effective reagents. By integrating CRISPRi gene regulation, colorful chromoproteins, cell-free transcription-translation systems, smartphone-based quantification, and an in-house automated algorithm (CRISPectra), our kit offers an inexpensive (~$2) and user-friendly approach to performing and analyzing CRISPR experiments, without the need for a traditional laboratory setup. Experiments conducted by high school students in classroom settings highlight the kit’s utility for reliable CRISPRkit experiments. Furthermore, CRISPRkit provides a modular and expandable platform for genome engineering, and we demonstrate its applications for controlling fluorescent proteins and metabolic pathways such as melanin production. We envision CRISPRkit will facilitate biotechnology education for communities of diverse socioeconomic and geographic backgrounds.

Fostering the use of reflective learning strategies in teaching big data analytics and data science: Enhancing the quality of epidemiological evidence and decision-making

PURPOSEThis study investigated the frequency of use and perceived effectiveness of reflective learning strategies among university educators and practitioners in big data analytics and data science, including epidemiologists. Reflective learning fosters critical thinking and problem-solving skills essential for navigating the complexities of big data. It encourages systematic evaluation of methodologies and the identification and mitigation of biases. These skills are particularly relevant in epidemiology, where the prediction and management of disease outbreaks, as well as public health decisions, increasingly depend on big data analytics. METHODOLOGYA cross-sectional design was employed with a diverse sample of 93 participants from multiple countries, averaging 15 years of teaching and practice experience. Informed by the Diffusion of Innovation Theory and the Theory of Planned Behavior, data were collected in Fall 2023 using an online questionnaire. The questionnaire focused on personal disposition, contextual favorability, and characteristics of reflective learning as predictors of the frequency and perceived effectiveness of reflective learning, analyzed using multiple regression modeling. Acceptable levels of reliability and criterion validity were achieved. This study was approved by the Ethics Panel of Canterbury Christ Church University, UK. RESULTSIn general, reflective learning strategies were perceived as effective for enhancing cognitive skills, such as critical thinking and problem-solving, but less so for technical skills like algorithm and model selection. Preferred methods included real-world applications, problem-based learning, and collaborative projects. Frequency of use was positively correlated with perceived effectiveness. Personal disposition and characteristics of reflective learning scores were significant predictors of frequency of use (R-squared = 0.32), with older participants being less engaged. The characteristics of reflective learning score was the sole significant predictor of perceived effectiveness, though with a modest predictive value (R-squared = 0.09). Contextual favorability did not significantly predict either frequency of use or perceived effectiveness of reflective learning strategies, implying a lesser role for external factors as drivers of engagement. CONCLUSIONSThis study underscores the importance of reflective learning in enhancing analytical and problem-solving skills, and suggests that intrinsic motivation may be a key factor underpinning the use of reflective learning strategies by educators and practitioners in big data analytics and data science. These findings have major implications for curriculum and professional development, particularly for epidemiologists who must continuously adapt to new data and methodologies to effectively address public health challenges.

High-dimensional private and social optimal policy valuation model for non-renewable natural resource extraction projects for multivariate public policy decisions

We present a model to find the value and sensitivity function associated with the exploitation of a non-renewable natural resource both for the mining company (private optimum) and for the government (social optimum). Improvements over previous studies are achieved by achieving a multivariate model of optimal policy valuation under a Markov decision process with stopping times based on multiple real options, proposing an iterative algorithm of stochastic approximation with supervised dynamic programming decision under Monte Carlo scenarios until obtaining convergence. Applied to a mining project (Tía María) and extended to the total reserves of a country (Peru), it provides additional decision criteria for fiscal public policy, negotiations, concessions, tax levels, community reparations, as well as benefit estimation, discounted from the potential environmental cost in countries abundant in natural resources that wish to achieve sustainability.

The Ministerial Advisory Committees and 3 years of COVID-19 expertise - is the Department of Health's model for information-sharing pandemic-ready?

Effective pandemic decision-making depends on scientific expert evidence, transparency about public health policy decision-making, its rationales and the evidence on which it is based. The South African government laudably committed its COVID-19 response to be guided by science and evidence. Yet, the expert advice that it received was not always readily made available to the public. This submission analyses the time elapsed between the submission of COVID-19 Ministerial Advisory Committees memoranda to the Minister of Health, and the Department of Health's subsequent publication of these for the period August 2020 - January 2024. It also summarises the outcomes of the Health Justice Initiative's access to information legal action against the department on expert advice and government decision-making during the pandemic.

Predicting Particulate Matter (PM 10) Levels in Morocco: A 5-Day Forecast Using the Analog Ensemble Method.

Accurate prediction of Particulate Matter (PM 10) levels, an indicator of natural pollutants such as those resulting from dust storms, is crucial for public health and environmental planning. This study aims to provide accurate forecasts of PM 10 over Morocco for five days. The Analog Ensemble (AnEn) and the Bias Correction (AnEnBc) techniques were employed to post-process PM 10 forecasts produced by the Copernicus Atmosphere Monitoring Service (CAMS) global atmospheric composition forecasts, using CAMS reanalysis data as a reference. The results show substantial prediction improvements: the Root Mean Square Error (RMSE) decreased from 63.83 μg/m 3 in the original forecasts to 44.73 μg/m 3 with AnEn and AnEnBc, while the Mean Absolute Error (MAE) reduced from 36.70 μg/m 3 to 24.30 μg/m 3. Additionally, the coefficient of determination (R 2) increased more than twofold from 29.11% to 65.18%, and the Pearson correlation coefficient increased from 0.61 to 0.82. This is the first use of this approach for Morocco and the Middle East and North Africa and has the potential for translation into early and more accurate warnings of PM 10 pollution events. The application of such approaches in environmental policies and public health decision making can minimize air pollution health impacts.

A survey of the representativeness and usefulness of wastewater-based surveillance systems in 10 countries across Europe in 2023.

Wastewater-based surveillance (WBS) has become a widespread method to monitor transmission of SARS-CoV-2 and other human pathogens in Europe. We conducted a survey about WBS systems' objectives, approaches, representativeness and usefulness in 10 invited European countries in 2023, i.e. Austria, Belgium, Denmark, Finland, Greece, Hungary, Italy, Luxembourg, the Netherlands and Norway. All countries completed the study questionnaire about their SARS-CoV-2 WBS systems, and shared information about WBS of other pathogens as deemed relevant. SARS-CoV-2 WBS systems primarily monitored national and subnational trends (population coverage: 25-99%), and a majority (8/10) also tracked variant distribution. Nine of 10 countries reported that their SARS-CoV-2 WBS systems were representative of their population and all countries remarked that the findings were valuable for public health decision-making. Results were shared with relevant public health authorities and published via dedicated websites and/or dashboards. WBS systems of other pathogens were mostly in the early stages, with some countries implementing pilots. Notable exceptions were the well-established poliovirus surveillance systems in Finland, Italy and the Netherlands. This study brings understanding the diverse landscape of WBS in Europe, offering insights for future developments and collaborations. Furthermore, it highlights the need for further integration of WBS into other European surveillance systems.

E-Cigarette Characteristics and Cigarette Cessation Among Adults Who Use E-Cigarettes

Population-level health outcomes associated with e-cigarettes depend in part on the association between e-cigarettes and combustible cigarette cessation. The US Food and Drug Administration has authority to regulate e-cigarette characteristics, including flavor and device type. To investigate whether e-cigarette characteristics are associated with cigarette cessation behaviors among adults in the US population who use e-cigarettes. This cohort study was conducted using longitudinal data collected in 2014 to 2021 by the Population Assessment of Tobacco and Health Study, a population-based, US nationally representative study. Participants were sampled from the civilian noninstitutionalized population using a 4-staged, stratified sampling design. Data were weighted and analyzed from 1985 adults ages 21 or older who smoked cigarettes daily and had used e-cigarettes in the past 30 days. Data were analyzed in May 2021 to May 2024. The following e-cigarette characteristics were assessed: use frequency (daily and nondaily), flavor type (tobacco, menthol or mint, sweet, and combination), device type (disposable, cartridge, and tank), and year of data collection as a proxy for the evolving e-cigarette marketplace. The following cigarette cessation behaviors were assessed: making a cigarette quit attempt, cigarette cessation among individuals who made a quit attempt, and overall cigarette discontinuation regardless of quit attempts. Associations were evaluated between e-cigarette characteristics (assessed at baseline in 1 approach and assessed at follow-up in another approach) and cigarette cessation outcomes, controlling for demographic, cigarette smoking, and other e-cigarette use characteristics. The study sample consisted of 1985 participants representing adults in the population (mean age, 40.0 years [95% CI, 39.2-40.9 years]; 49.4% [95% CI, 46.3%-52.6%] male; 11.4% [95% CI, 9.6%-13.4%] Black, 80.7% [95% CI, 77.8%-83.3%] White, and 8.0% [95% CI, 6.3%-10.0%] other race; 9.2% [95% CI, 7.5%-11.2%] Hispanic). Daily vs nondaily e-cigarette use was associated with greater overall cigarette discontinuation rates (12.8% [95% CI, 9.1%-17.7%] vs 6.1% [95% CI, 4.8%-7.7%]; adjusted odds ratio [aOR], 2.26 [95% CI, 1.34-3.81]), and use of e-cigarettes in 2019 to 2021 vs 2014-2015 to 2015-2016 was also associated with greater overall cigarette discontinuation rates (12.0% [95% CI, 8.8%-16.0%] vs 5.3% [95% CI, 2.9%-9.3%]; aOR, 2.75 [95% CI, 1.13-6.67]). Use of menthol or mint vs tobacco flavor e-cigarettes was associated with greater overall cigarette discontinuation rates (9.2% [95% CI, 6.6%-12.8%] vs 4.7% [95% CI, 3.0%-7.1%]; aOR, 2.63 [95% CI, 1.32-5.27]) only when assessing e-cigarette use at baseline. E-cigarette device type was not associated with cigarette discontinuation rates in adjusted analyses. In this study, daily e-cigarette use and use of e-cigarettes in 2019 to 2021 were consistently associated with greater cigarette discontinuation rates. These findings suggest that research focused on e-cigarettes marketed in recent years is needed to inform product regulation and public health policy decisions.

The Risk Of Perpetuating Health Disparities Through Cost-Effectiveness Analyses.

Cost-effectiveness analyses are commonly used to inform health care and public health policy decisions. However, standard approaches may systematically disadvantage marginalized groups by incorporating assumptions of persisting health inequities. We examined how competing risks, baseline health care costs, and indirect costs can differentially affect cost-effectiveness analyses for racial and ethnic minority populations. We illustrate that these structural factors can reduce estimated quality-adjusted life-years and cost savings for disadvantaged groups, making interventions focused on disadvantaged populations appear less cost-effective. For example, analyses of a sugar-sweetened beverage tax may estimate higher costs per quality-adjusted life-year gained for Black versus White populations because of differences in competing risks and insurance status that manifest in higher health care cost savings from averted disease among White people. To ensure that cost-effectiveness assessments do not perpetuate inequities, alternative approaches are needed that account for the impact of structural factors on different groups and that consider scenarios in which health inequities are reduced. Sensitivity analyses focusing on health equity could help advance interventions that disproportionately benefit disadvantaged communities.

EFFECT OF CONTINUOUS PROFESSIONAL DEVELOPMENT ON STUDENTS ACADEMIC PERFORMANCE IN NINE YEARS BASIC EDUCATION SCHOOLS OF RWANDAA CASE OF NYARUGURU DISTRICT

Background: This study investigated the effect of continuous professional development on students Academic performance in nine-year basic education schools in Nyaruguru district, Rwanda. The specific objectives were to identify continuous professional development Programmes practiced in nine years basic education in Rwandan schools, to analyze the students academic performance due to continuous professional development in Rwandan schools and to assess the influence of continuous professional development on students performance in nine-year basic education schools in Rwanda. This study is useful to all stakeholders in education sector such as public institutions, decision makers, district authorities, head teachers, teachers, learners and scholars. The researcher applied a descriptive correlational study, targeting 5 head teachers, 150 teachers and 88 School based mentors. This study selected respondents and key informants purposively and randomly. A study sample of 243 respondents was obtained by use of Yamanes formula. Materials and Methods: Information was analyzed using statistical package for social sciences version 26.0 to generate descriptive statistics in terms of frequency, percentage, mean and standard deviation. Inferential statistics were produced in terms of correlation and regression coefficient for determining size effect between variables. Results:English proficiency factors indicated that 79.2% strongly agree that Educational document preparation, and 82.6% strongly agreed that Teaching techniques, 79.9% strongly agreed that Course content, 77.2% strongly agreed that Classroom management show continuous professional development Programmes in Nyaruguru District, Rwanda, Results on the students academic performance 79.4% strongly agreed that improved academic performance, 82.6% Strongly agreed that high national examination. Additionally, 77.9% Strongly agreed that improved personality development 68.5%. Strongly agreed that improved personal development, 78.5% strongly agreed that improved academic performance indicates student academic performance. Results from objective three reveal a strong positive correlation between academic performance improvement, educational document preparation, teaching techniques, course content, and slow learners treatment, suggesting effective policies and professional development time, and that they were positively and statistically correlated since most of their levels of significance were greater than 0.05 in association. Conclusion: It is advised that the Ministry of Education and the REB (Rwanda Education Board) develop effective policies and devote adequate time for CPD in schools. They should also organize school principals to enhance CPD practice. To offer effective, ongoing professional support for teachers, it is strongly suggested that certified CPD facilitators be recruited and principals skilled in educational leadership and management be hired throughout all secondary schools across different districts. Relevant professional training programs should be developed in response to the unique training requirements of professors. To do this, competent authorities at all levels must pay close attention to this issue. To improve their abilities, school principals should emphasize CPD and actively involve themselves in peer learning. There is a need to carry out a research on The study recommends more research into the effects of continuous profession development on teachers performance in teaching career.

Effects of COVID-19-targeted non-pharmaceutical interventions on pediatric emergency department use: a quasi-experimental study interrupted time-series analysis in North Italian hospitals, 2017 to 2022.

The use of Non-Pharmaceutical Interventions (NPIs) during the COVID-19 pandemic is debated. Understanding the consequences these measures may have on vulnerable populations including children and adolescents is important. This is a multicenter, quasi-experimental before-after study involving 12 hospitals of the North Italian Emilia-Romagna Region, with NPI implementation as the intervention event. The 3 years preceding NPI implementation (in March 2020) constituted the pre-pandemic phase. The subsequent 2 years were further subdivided into a school closure phase (SC) and a subsequent mitigation measures phase (MM) with milder restrictions. Interrupted Time Series (ITS) regression analysis was used to calculate PED Standardized Incidence Rate Ratios (SIRR) on the diagnostic categories exhibiting the greatest frequency and/or variation. In the 60 months of the study there were 765,215 PED visits. Compared to the pre-pandemic rate, overall PED presentations dropped by 58 and 39% during SC and MM, respectively. "Symptoms, signs and Ill-defined conditions," "Injury and poisoning" and "Diseases of the Respiratory System" accounted for 74% of the reduction. A different pattern was instead seen for "Mental Disorders," which exhibited the smallest decrease during SC, and is the only category which rose already at the end of SC. ITS analysis confirmed the strong decrease during SC (level change, IRR 0.17, 95%CI 0.12-0.27) and a significant increase in MM (slope change, IRR 1.23, 95%CI 1.13-1.33), with the sharpest decline (-94%) and rise (+36%) observed in the "Diseases of the Respiratory System" category. Mental Disorders showed a significant increasing trend of 1% monthly over the whole study period exceeding pre-pandemic levels at the end of MM. Females and adolescents showed higher increasing rates both in SC and MM. NPIs appear to have influenced PED attendance in different ways according to diagnostic categories, mirroring different mechanisms of action. These effects are beneficial in some cases and harmful in others, and establishing a clear balance between pros and cons is a difficult task for public health decision makers. The role of NPIs on PED use appropriateness deserves investigation. The rise in pediatric mental disorders independent of the pandemic makes interventions addressing these issues urgent.

CONCEPTUALISATION OF THE DEFINITION «URBANISED AREAS»

The article outlines theoretical approaches to explaining the essence of urbanisation as a trend in the development of modern society. The article establishes that at the present stage of development of post-industrial urbanism, new theories and concepts of urban development are emerging. Scientists pay considerable attention to knowledge and high technologies. In the context of urban development, there are trends towards suburbanisation, as well as decentralisation and an increased role for local governments. Theories of urbanisation that are typical of post-industrial society characterise urbanism as a process that is directly related to political, economic and social factors. The author's own approaches to building the conceptual apparatus are proposed, taking into account the subject of this study and the identified characteristics of urbanised areas, in particular, the concepts of «urbanisation», «city», «agglomeration» are clarified. It is established that public management of development of urbanised areas is the exercise by public authorities of targeted influence on various spheres of urban public life with a view to ensuring intensive and extensive development of urbanised areas and improving the living standards of the population. An approach to the classification of urbanised territories for the purposes of public administration is proposed, which allows identifying the properties of urbanised territories and, accordingly, taking them into account in the formation and implementation of the State policy, strategies and public administration decisions on the development of urbanised territories, in particular: by the form of territorial settlement, planning structure, population density, level of urban development, functions performed by it, environmental status, as well as the level of economic and social development of the relevant territory, the level of damage and the level of security.

Modeling rare plant habitat together with public land managers using an iterative, coproduced process to inform decision‐making on multiple‐use public lands

AbstractPublic lands across the United States are managed for multiple uses, resources, and values ranging from energy development to rare plant conservation. Intensified energy development and other land use changes across the Southwestern United States have increased the need for proactive management to mitigate impacts to rare plants. Habitat suitability models can inform decision‐making and lead to more effective conservation of rare plants and their habitats, but high‐quality models that are suited for use at local scales are lacking for many species. Our team of scientists and managers developed ensembles of habitat suitability models for five rare plant species in New Mexico using a coproduced, iterative framework complemented by comprehensive ground truthing and tailoring of products for use in public land decisions. Our process resulted in substantial differences from initial models through changes to environmental predictors, species occurrence and background data, and development of new species‐specific predictors. Involving species experts and end users in model development can strengthen the process and resulting model and build understanding and trust in final products. Both factors can promote use of models to inform public land permitting and planning decisions that may affect rare plants, including by guiding development away from highly suitable habitats.

Insights from the 2021 OECD Trust Survey: How people evaluate the trustworthiness of government institutions &amp; implications for policymakers

The inaugural OECD Survey on the Drivers of Trust in Public Institutions asked respondents in 22 OECD countries to evaluate the trustworthiness of national and local governments and other public institutions as well as to report their perceptions and experiences with various public governance–related drivers of trust (factors likely to affect trust) in those institutions. The main drivers include the government’s competence (as indicated by its reliability and responsiveness) and government values, including integrity, openness, and fairness. The article highlights the key findings of the survey and of analyses exploring the impact of various drivers on trust. The results underscore that people are relatively satisfied with delivery of public services and governments’ reliability, but it is crucial to enhance citizens’ perceptions of governments’ responsiveness and their perceived ability to influence public decision-making. The article also addresses the policy implications of the research and describes ways some countries have already used the country-specific findings as a guide to developing policies for reinforcing their citizens’ trust.

Analyzing Google COVID-19 Vaccine Intent Search Trends and Vaccine Readiness in the United States: Panel Data Study.

Factors such as anxiety, worry, and perceptions of insufficient knowledge about a topic motivate individuals to seek web-based health information to guide their health-related decision-making. These factors converged during the COVID-19 pandemic and were linked to COVID-19 vaccination decision-making. While research shows that web-based search relevant to COVID-19 was associated with subsequent vaccine uptake, less is known about COVID-19 vaccine intent search (which assesses vaccine availability, accessibility, and eligibility) as a signal of vaccine readiness. To increase knowledge about vaccine intent search as a signal of vaccine readiness, we investigated the relationship between COVID-19 vaccine readiness and COVID-19 vaccine intent relative search volume on Google. We compiled panel data from several data sources in all US counties between January 2021 and April 2023, a time during which those with primary COVID-19 vaccinations increased from <57,000 to >230 million adults. We estimated a random effects generalized least squares regression model with time-fixed effects to assess the relationship between county-level COVID-19 vaccine readiness and COVID-19 vaccine intent relative search volume. We controlled for health care capacity, per capita COVID-19 cases and vaccination doses administered, and sociodemographic indicators. The county-level proportions of unvaccinated adults who reported that they would wait and see before getting a COVID-19 vaccine were positively associated with COVID-19 vaccine intent relative search volume (β=9.123; Z=3.59; P<.001). The county-level proportions of vaccine-enthusiast adults, adults who indicated they were either already vaccinated with a primary COVID-19 vaccine series or planned to complete the vaccine series soon, were negatively associated with COVID-19 vaccine intent relative search volume (β=-10.232; Z=-7.94; P<.001). However, vaccine intent search was higher in counties with high proportions of people who decided to wait and see and lower in counties with high proportions of vaccine enthusiasts. During this period of steep increase in COVID-19 vaccination, web-based search may have signaled differences in county-level COVID-19 vaccine readiness. More vaccine intent searches occurred in high wait-and-see counties, whereas fewer vaccine intent searches occurred in high vaccine-enthusiast counties. Considering previous research that identified a relationship between vaccine intent search and subsequent vaccine uptake, these findings suggest that vaccine intent search aligned with people's transition from the wait-and-see stage to the vaccine-enthusiast stage. The findings also suggest that web-based search trends may signal localized changes in information seeking and decision-making antecedent to vaccine uptake. Changes in web-based search trends illuminate opportunities for governments and other organizations to strategically allocate resources to increase vaccine uptake. Resource use is part of the larger public policy decisions that influence vaccine uptake, such as efforts to educate the public during evolving public health crises, including future pandemics.

Development of a unit conversion tool for five quantitative anti-spike assays and agreement analysis of three qualitative anti-nucleocapsid assays for SARS-CoV-2.

Commercially available assays for measuring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) anti-spike (S) or anti-nucleocapsid (N) antibodies differ in units, making results comparisons challenging. This study aimed to develop conversion equations between five quantitative anti-S antibody tests and to assess the agreement over time between three qualitative anti-N antibody tests. Blood samples from 24 216 vaccinated healthcare workers in Hiroshima Prefecture, Japan, were analyzed for anti-S antibodies using five quantitative tests (Abbott, Fujirebio, Ortho, Sysmex, Roche) and for anti-N antibodies using three qualitative tests (Abbott, Sysmex, Roche). Geometric mean regression was performed to establish equations for converting measured values between the five quantitative tests. Fleiss κ statistic was used to assess the agreement between the three qualitative tests. A strong correlation (Pearson's coefficient r > 0.9) was found for each pair of the five quantitative tests measuring anti-S antibodies, enabling the development of equations to convert values between each pair. Using these equations, which are based on the original output unit of each test, values obtained from one test can be transformed to be equivalent to the corresponding values in another test. For the three tests for anti-N antibodies, the agreement was substantial in the total sample (Fleiss' κ, 0.74) and moderate among those with self-reported past coronavirus disease 2019 (COVID-19) infection (Fleiss' κ, 0.39). The agreement decreased with time after infection. Reduced agreement between anti-N antibodies tests over time suggests caution in comparing seroepidemiological studies of COVID-19 exposure based on anti-N antibodies measurement. The findings could help improve antibody measurement systems and inform public health decision-makers.