Public Response Research Articles

Revictimization of women victims of intimate partner violence in the French press: A social representations approach.

This study aims to analyze how the press portrays cases of revictimization experienced by women in France, through the lens of social representation theory. An exploratory, descriptive study was conducted using a corpus of 157 online press articles. A total of 187,773 words and 5,240 segments were analyzed using Iramuteq version 7, employing top-down hierarchical classification and lexical similarity analysis. The analysis identified four classes: 1. Violent incidents (25.5%); 2. Political actions against violence (26%); 3. Institutional revictimization (26.6%) and 4. Violence and breaking the silence (21.9%). The findings illustrate how media portrayals contribute to the construction of social representations surrounding revictimization. Class 1 reveals a focus on extreme cases of violence, such as femicides, and highlights a potential gender bias in media reporting through the omission of terms like 'femicide'. Class 2 demonstrates the influence of ideological perspectives on the portrayal of political measures against violence, with conservative outlets framing such actions within traditional values, while progressive newspapers advocate for systemic reform. Class 3 shows a gap in the conceptualization of institutional revictimization in the French press compared to other countries, revealing how conservative portrayals can minimize systemic issues and perpetuate harmful stereotypes. Class 4 shows the role of female journalists in addressing various forms of violence, despite the limited impact of the #MeToo movement in recent coverage. Collectively, these findings elucidate how media representations shape public attitudes and institutional responses to gender-based violence through the lens of social representations.

A multiple behaviour temporal network analysis for health behaviours during COVID-19.

The aim of this study was to examine the temporal dynamics of multiple health behaviours (physical activity, alcohol consumption, healthy eating, cigarette consumption, recreational drug use, vaping), and pandemic-related health behaviours (e.g., hand washing, physical distancing) using network psychometrics. The International COVID-19 Awareness and Responses Evaluation (iCARE) study is an international multi-wave observational cohort study of public awareness, attitudes, and responses to public health policies implemented to reduce the spread of COVID-19 on people around the world. A sub-sample of longitudinal data from Canadians (n = 254) was analysed across four waves (February-July 2020). We used temporal network models to fit temporal networks, contemporaneous networks, and between-subject networks from items within the iCARE survey. Positive temporal associations were observed between physical activity and healthy eating, and a bidirectional relationship was evident between outdoor mask use and vaping. A contemporaneous network revealed positive associations between consumption behaviours (vaping, cigarette use, alcohol use, and recreational drug use), and negative associations between physical activity and drug use, and healthy eating and cigarette use. Health behaviours are interconnected and can be modelled as networks or behavioural systems. The application of temporal network analysis to the study of multiple health behaviours is well suited to address key research questions in the field such as 'how do multiple health behaviours co-vary with one another over time'. Future research using time series data and measuring affective and cognitive mediators of behaviour, in addition to health behaviours, has the potential to contribute valuable hypothesis-generating insights.

Publics in local media reporting on harm reduction: Rightfully worried local witnesses or uneducated obstacles to change

BackgroundIn 2018, the planned opening of a second Needle and Syringe Exchange Program (NSP) unit in Stockholm, Sweden, was stopped with reference to protests from the public. Local Stockholm media cited stakeholders who claimed that the initiative was led by politicians with “zero knowledge about what makes citizens upset” and referred to reported public concern over a preschool located near the planned NSP unit. This case highlights the significant role of the public – and the idea of public opinion – in relation to political and medial aspects of alcohol and other drug (AOD) issues. Our aim is to scrutinize how “the public” is produced in local print media reports on harm reduction measures such as the NSP, to illuminate how these representations operate and what reality/ies they co-produce. MethodsWe analyzed 171 articles reporting on harm reduction in local Stockholm print media from 2012 to 2023. The themes identified in the analysis emerged from a combination of data-driven empirical observations and a theory-driven approach grounded in the influential literature on publics and counterpublics by Michael Warner and Nancy Fraser. ResultsThe overarching articulation in the material is that of a singular and homogeneous public. Public opinion regarding local experiences of individual drug use and harm reduction is depicted as being driven by fear and worry over living alongside “messy others”, thereby producing a public of worried local community witnesses. This production of the public takes on two different meanings depending on the narrative of the articles: 1) as righteous and entitled, 2) as ignorant and irrational. As a result, the public comes to operate as either a consulted public deserving consideration in the implementation of harm reduction policies or as an uneducated political obstacle to change. Consequently, the public is assigned both a counterpublic and a dominant public identity. ConclusionsWhen the representation of the worried public is repeatedly echoed by the media, it becomes hard to ignore in policy-making processes. The implications of such media representations are significant, as they risk disguising the complex nature of publics as a diverse group of individuals while reproducing taken-for-granted ideas about local communities opposing harm reduction measures. In addition, the appropriation of a counterpublic identity narrows the discursive space for action. Taken together, the repetition of a singular worried public and the appropriation of the counterpublic position make it nearly impossible to imagine alternative public responses to harm reduction. As a consequence, this can limit well-needed policy responses to AOD issues.

High expression of LncRNA HOTAIR is a risk factor for temozolomide resistance in glioblastoma via activation of the miR-214/β-catenin/MGMT pathway

HOX transcript antisense RNA (HOTAIR) is upregulated in glioblastoma (GBM) and associated with temozolomide (TMZ) resistance. However, the mechanisms underlying HOTAIR-mediated TMZ resistance remains poorly understood. HOTAIR expression in glioma-related public datasets and drug response estimation were analyzed using bioinformatics. These findings were verified by overexpressing HOTAIR in TMZ-sensitive U251 cells and/or silencing HOTAIR in resistant U251 cells (U251R). The cytotoxic effects were evaluated using cell viability assay and flow cytometry analysis of cell cycle and apoptosis. In this study, we found that HOTAIR was upregulated in TMZ-resistant GBM cell lines and patients with high HOTAIR expression responded poorly to TMZ therapy. HOTAIR knockdown restored TMZ sensitivity in U251R cells, while HOTAIR overexpression conferred TMZ resistance in U251 cells. Wnt/β-catenin signaling was enriched in patients with high HOTAIR expression; consistently, HOTAIR positively regulated β-catenin expression in U251 cells. Moreover, HOTAIR-mediated TMZ resistance was associated with increased MGMT protein level, which resulted from the HOTAIR/miR-214-3p/β-catenin network. Besides, GBM with high HOTAIR expression exhibited sensitivity to methotrexate. Methotrexate enhanced TMZ sensitivity in U251R cells, accompanied by reduced expression of HOTAIR and β-catenin. Thus, we conlcude that HOTAIR is a risk factor for TMZ resistance and methotrexate may represent a potential therapeutic drug for patients with high HOTAIR expression level.

Attitude, Behavior, and Practices of Infection Control (Hand Washing, Social Distancing and Wearing Mask) among Communities During COVID-19 Outbreak in Areas, (Orangi, Baldia, Movach, Site, Garden, Nazimabad, Qayyumabad) of Karachi, Pakistan

Background Novel corona virus infectious disease covid-19 was first time reported in Wuhan city of China at the end of December 2019.[1] Which proliferated rapidly in China and then around the globe in 209 countries of USA, Europe, Australia, and Asia as well as Pakistan. The death toll around the world has been reached to more than 42 million and 2 billion have been affected so far,[3] in Pakistan the death toll reached to 23 thousand and affected population reached to 10 million and still numbers increasing rapidly.[5] Government taken Various measures in Pakistan for the control of covid-19. Despite of having insufficient funds Pakistan also taken accurate quantify like planned special hospitals, laboratories for testing, isolation facilities, mindfulness drive and lock down to minimize spread virus. Despite the government strict policy towards COVID-19 there are many people who are unable to follow the measures which add into the rapid spread of virus. the aim of the study is to assess the attitude, behavior, and practice among the resident of Karachi specifically those who are residing in SITE area, Orangi Town, Baldia Town, Movach Goth, Nazimabad, Garden, Qayyumabad and Gulshan-e-Iqbal to know the public response towards following SOPs.  Method A self-administered questionnaire was designed, based on determined attitude, behavior, and practices among the resident of Karachi during COVID-19 outbreak. Questionnaire were prepared at google form and accessible online for the participants. The questionnaire was processed to the residents of Karachi, between the duration from 12, June to 10, July 2021. The collected data was analyzed with help of SPSS version 26.0 (IBM) to identify the attitude behavior and practices of people during COVID-19 outbreak. The responses were analyzed based on age, gender, level of education, and income, to identify statistical correlation by utilizing chi square test.  Results The study included 318 participants, out of which 193(61%) males and 125(39%) were female. The majority (291;92%) of the participant was familiar with the covid 19, (94%; 299) of the participant were concerned about the health of their families, (95%;303) agreed that self- care and protection can reduce the possibility to get infected by COVID-19 infection, a vast majority (98%; 313) participants were following cough etiquettes.  Conclusion All of the study participants were from Karachi and they have reasonably good attitude, behavior and practices towards COVID-19 precautions, but still there must be given further awareness to cope with the social and psychological impact of the COVID-19 on public health, and also awareness session should be taken into account to reduce the spread of the infection COVID-19.

Leveraging Social Media Data for Forest Fires Sentiment Classification: A Data-Driven Method

Background: The rise in forest fires over the last two years, which is due to rise in dry weather conditions and human activities, have greatly impacted an area of 1.6 million hectares, leading to significant ecological, economic, and health issues, hence the need to improve disaster response strategies. Previous research determined the lack of coverage regarding public response during forest fires with conventional methods such as satellite images and sensor data. However, social media platforms provide real-time information generated by users, along with location information of disaster events. Sentiment analysis helps in understanding the public reactions and responses to natural disasters, thereby increasing awareness about forest fires. Objective: The purpose of this research is to assess the efficiency of Long Short-Term Memory (LSTM) method in classifying sentiment for social networks in regard to forest fires. This research aims to examine the effect of TF-IDF, unigram, and the FastText features on the effectiveness of the classification of sentiment. Methods: The precision, recall, and F1 score of 2, 3, and 4 determined in the LSTM models with commonly available sentiment analysis tools, such as the Vader Sentiment Analysis and SentiWordNet was used to evaluate the performance of the model. Results: With an improvement of roughly 10%, the four layers of the LSTM model generated the best performance for the evaluation of sentiments about forest fires. The LSTM model with FastText achieved F1, recall and precision scores of 0.649, 0.641, and 0.659, which exceeds lexicon-based method including SentiWordNet and Vader. Conclusion: The experimental results showed that the LSTM model outperformed lexicon-based methods when used to analyse the tweets related to forest fire. Additional research is required to integrate rule-based models and LSTM models to develop a more robust model for dynamic data. Keywords: Forest Fire, Disaster, Long Short-Term Memory, LSTM, Vader, SentiWordnet

The Theory of Dyadic Morality and Moral Identity Explain the Public's Response to Harm Done by Government and Organisations

ABSTRACTHarm functions complexly in moral judgement but has been treated differently in the Social Intuitionist Model (SIM) and the Theory of Dyadic Morality (TDM). Both the SIM and TDM see felt harm as an outcome of experienced negative moral emotions (e.g., disgust), but the SIM regards harm as a kind of epiphenomenon in the sense that it does not affect moral judgement or behaviour, whereas the TDM interprets harm as an essential mediator of the link between negative moral emotions and immorality. The TDM also develops an explanation for how harm functions to initiate reactions to triggering events marked by an intentional agent causing injury to a vulnerable social actor. Here norms serve a regulatory function modulating the effects of harm committed by the agent on negative moral emotions. We conduct two experiments on representative samples of adults () and address two different moral contexts (companies doing badly and government doing badly with respect to a threatened health crisis), two different normative moderators (moral identity and belief in conspiracies) and two different moral action tendencies (intentions and word of mouth). Harm is found to have direct and contingent mediated effects on moral action tendencies, in accord with the TDM. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement.

The European Mobile Laboratory: key insights from a decade of outbreak response

Abstract EMLab has responded to emergencies including the West Africa Ebola virus outbreak (2014-2016), the COVID-19 pandemic, and outbreaks of yellow fever, Marburg virus, and Lassa fever. It has deployed mobile labs and experts to many countries, including Guinea, Liberia, Sierra Leone, Nigeria, Uganda, the Democratic Republic of the Congo, Germany, and Greece. With accumulated experience from each deployment, EMLab’s diagnostic expertise has evolved beyond RT-PCR and serological testing to include basic point-of-care tests, haematology, and genomic surveillance capacities, also focusing on interoperability with other response capacities such as EMTs. Critical to mission success, the organization works closely with the WHO and GOARN, and was certified in 2023 as an official German response capacity within the European Civil Protection Pool. The two-year continuous deployment from 2014-2016 was pivotal in shaping EMLab’s evolution, also leading to significant capacity-building efforts in West Africa. In Guinea, for example, a surveillance network of three diagnostic laboratories has been established and successfully detected cases of viral haemorrhagic fevers, including the re-emergence of Ebola virus and the first reported case of Marburg virus in Guinea in 2021. Ultimately, EMLab’s extensive experience demonstrates that effective public health emergency response requires constant evolution, strategic partnerships, and a commitment to building local capacities, paving the way for a more resilient and prepared global health community.

Public Perception of the Higher Education System under the Regime of the Islamic Emirate of Afghanistan

A modern, free, and dynamic higher education system is the basic and critical element of successful nation, and it can contribute to the progress and development of a country. Under both regimes of the Islamic Emirates of Afghanistan, the higher education system has undergone significant changes to align with the government’s interpretation of Islamic principles. This study is important to understand how Afghan society views the changes and policies implemented in the education sector under the current regime. The research study aims to evaluate public sentiment regarding access, quality, and inclusivity of higher education, particularly in relation to gender, curriculum changes, and ideological shifts. This paper focuses on the Taliban’s higher education system and investigates public responses to educational policies. This paper will offer recommendations to all stakeholders involved in the Afghan higher education system, aimed at improving its management and development during this crucial period. This work employs non-doctrinal and library research methodology. Non-doctrinal research examines how laws are applied and experienced in practice by collecting data through surveys, interviews, field studies, and observations. In this research study, data was collected through a questionnaire and then analyzed through SPSS. Moreover, in the library research methodology, most of the reputable and trustworthy academic sources such as textbooks, scholarly published and unpublished journal articles, law reports, and online websites related to the research area were analyzed through descriptive, explanatory, and analytical research approaches. The Afghan higher education system, established in the 1930s, has faced continuous political pressures, especially during periods of conflict like the Soviet invasion and civil war from the 1980s to 1990s. Women face major limitations in higher education, including restrictions on fields of study and exclusion from faculty positions, raising concerns about gender equality and access to education.

The impact of misinformation on social media in the context of natural disasters

Abstract Background Rapid dissemination of information during natural disasters plays a crucial role in managing public responses and ensuring safety. Social media can be a tool to disseminate lifesaving information but is also a ground for the propagation of misinformation. This study examines the impact of misinformation spread through social media in the context of natural disasters and explores related dynamics, effects, and countermeasures. Methods Cochrane and PRISMA recommendations were used for protocol development and sound reporting. Key terms related to misinformation, social media and natural disasters were used, with the search conducted in PubMed, and without time limitation for adequate capture. Only research papers in English were eligible for inclusion. Journal and article quality were considered. No restriction was imposed on country or age of target populations. Results Findings reveal significant influence of misinformation on public behaviour during disasters, often leading to panic and hindering effective disaster management. Specific characteristics of misinformation were identified, incl. its origins and spread mechanisms; proximity -both spatial and social- was found to be a critical factor in terms of spread and reach. Emerging evidence highlights the importance of trusted sources to effectively counter misinformation, yet response time remains a critical challenge. Technical detection of misinformation can help combat it but requires further enhancements for real-time application in diverse disaster scenarios. Conclusions Misinformation on social media poses complex challenges to disaster management, affecting both individual and societal resilience. Proactive communication strategies are critical, as is the development of advanced verification tools, and public education strategies to combat misinformation. Future research should focus on refining strategies to enhance disaster preparedness and response, ensuring a resilient and well-informed public.

Social Cohesion in Different Periods of the Pandemic: What Works in Reducing COVID-19 Mortality

Abstract Background Inconsistent results were reported regarding the effects of social cohesion dimensions on COVID-19 mortality rate (MR). Most studies have indicated that trust in civil services, but not participating in social activities, reduces COVID-19 MR, possibly because of the highly contagious nature of this disease. In this study, we investigated how the effects of various dimensions of social cohesion on COVID-19 MR vary across different phases of the pandemic. Methods This longitudinal study was conducted using data from 86 countries that participated in the 2017-2020 World Values Survey. The measures of social cohesion were identified by aggregating survey responses to the country level. COVID-19 MR was calculated-using data from the European Centre for Disease Prevention and Control-separately for three distinct periods during the pandemic (January 2021-June 2022). A factor analysis was conducted to identify the dimensions of social cohesion, and negative binomial regression models were constructed to analyze data for each period. Results The factor analysis revealed three dimensions of social cohesion: social participation and inclusion, health service equality, and trust in civil services and democracy. Our findings suggest that each dimension of social cohesion uniquely affected COVID-19 outcomes in different periods of the pandemic. Trust in civil services and a positive attitude toward democracy are strongly associated with a low COVID-19 MR. However, this association was observed only in the early and middle stages of the pandemic. By contrast, our study demonstrated that in the late stage of the pandemic, increased social participation and inclusion helped combat COVID-19. Conclusions This study underscores the importance of collective cohesion and solidarity in mobilizing public responses against pandemic situations. This study emphasizes that preventive or regulatory interventions should be tailored to different phases of a pandemic. Key messages • COVID-19 mortality rate was negatively associated with trust in civil services during the early two periods and with social participation and social inclusion during the late period of the pandemic. • This study emphasizes that preventive or regulatory interventions should be tailored to different phases of a pandemic.

Do apologies promote the reintegration of former combatants? Lessons from a video experiment in Colombia

Transitional justice practices frequently involve public apologies where former combatants confess their wrongdoings and ask for forgiveness, with the underlying assumption that such displays facilitate the reintegration of ex-combatants into society. However, little is known about the public response to ex-combatant apologies. In this article, we investigate the causal effect of an armed group apology on attitudes toward ex-combatant reintegration in Colombia. Our study builds on a novel experiment implemented in Meta, a conflict-ridden department of Colombia. The experiment entailed exposing a subset of participants to a video in which a former rebel group leader apologizes for violent acts committed by their armed group during the civil war. To examine the extent to which external actors influence the effectiveness of apologies, we incorporated third-party ‘encouragements to forgive’ (endorsements) in two additional treatment conditions. Our analysis demonstrates that, on average, participants do not exhibit higher reintegration attitudes when exposed to the apology, regardless of third-party endorsements. However, the absence of a treatment effect is not due to an indifference to the apology. In an exploratory heterogeneity analysis, we show that the apology induces negative effects on some indicators of reintegration attitudes among participants that did not support the peace agreement. This finding aligns with qualitative data gathered in a follow-up survey, which indicates that opponents of the peace agreement generally describe negative emotional responses to the FARC-EP apology. The results call for a reconsideration of unchallenged prescriptions of public apologies after conflict.

Sentiment Analysis of Twitter Users Towards the Kartu Prakerja Program Using the Naive Bayes Method

This study conducts a sentiment analysis of Twitter users regarding the Indonesian government’s Kartu Prakerja program, utilizing the Naive Bayes method for classification. Launched in 2020 to enhance employability skills amidst the COVID-19 pandemic, the program has garnered various public responses. A total of 836 tweets containing the keyword "Kartu Prakerja" were collected using the Twitter API and analyzed to determine sentiment distribution. Results indicate a predominance of neutral sentiment (800 tweets), with only 17 positive and 22 negative tweets. The Naive Bayes method achieved an accuracy of 95%, demonstrating its effectiveness in sentiment classification. However, comparisons with other methods, such as Support Vector Machine (SVM) and Recurrent Neural Network (RNN), reveal that these techniques yield higher accuracy rates (98.34% and 96%, respectively). This research highlights the importance of sentiment analysis in understanding public perceptions and informs policymakers about areas needing improvement. The findings underscore the potential of integrating advanced machine learning techniques to enhance sentiment analysis and provide insights into the effectiveness of government programs like Kartu Prakerja.

Coordinating public and government responses to air pollution exposure: A multi-source data fusion approach

Aligning public demand with government supply of clean air aids in efficient air pollution control and enhancement of public happiness. However, comparative empirical analyses of public and government attention to air quality changes are still sparse due to data and methodological constraints. Here, we adopt multi-source data fusion approaches to assess the impacts of air pollution exposure on public and government attention. Specifically, remote and social sensing data, alongside keywords extracted from textual data, are utilized to quantify air pollution exposure and corresponding public and government attention levels in 273 Chinese cities from 2011 to 2019, and a two-stage least squares regression model is employed to tackle reverse causality issues underlying the exposure-response relationship. Our findings reveal that, on average, a unit increase in PM2.5 levels would result in a 17.7% growth in public attention and a 12.7% rise in government attention, respectively, suggesting that demand-driven public attention tends to be more sensitive to air quality changes than policy-driven government attention. Results for the spatial-temporal heterogeneity further demonstrate that public attention varies across time and space, whereas government attention remains relatively consistent. Additionally, we have identified 116 cities exhibiting disparities between the public and government responses to air quality changes, calling for environmental policy refinements to better serve the needs of residents. This study emphasizes the necessity of public engagement in environmental governance and offers rich policy implications for air pollution control in China.

Public health rapid response in managing COVID-19 outbreaks in residential aged care facilities: a regional public health unit perspective.

We describe here the impact of managing coronavirus disease 2019 (COVID-19) outbreaks, during January-August 2022, in residential aged care facilities (RACFs) in Central Queensland, Australia, following the deployment of a public health rapid response team (PHRRT, comprising a medical officer, a communicable disease nurse, and an epidemiologist) from a regional public health unit (PHU). Our existing vaccine preventable diseases surveillance framework was used in identifying any symptomatic resident, triggering a PHRRT response. We found that the Hospital in the Home (HiTH) admission and death events were significantly lower after the introduction of the PHRRT than in the outbreaks that occurred before. Based on our experience with a PHRRT-led approach in mitigating the burden of outbreaks, we recommend regular reflection on optimising resources and practices in RACFs. Effective communication from PHUs can improve the RACFs' preparedness and capacity to respond, and can inform the best practice model to protect the highly susceptible elderly residents and their staff.

Information asymmetry and public response: Evidence from the housing market

This paper takes the introduction of commission collection from sellers in the Chinese housing market as a significant shock, and reveals the role that information asymmetry plays in the market by examining the public's response to two types of commission collection. Our findings indicate that when sellers transition from a commission model that is solely borne by buyers to one that is shared between both buyers and sellers, the listing prices of housing decline significantly, by approximately 1.6 % to 2.3 %. In contrast, when sellers face no change in the commission structure, their listing prices do not show a significant decline. This reduction is primarily attributed to the new commission model mitigating the information asymmetry that sellers experience. This research offers valuable insights into the impact of information asymmetry in housing markets.

From COVID-19 to monkeypox: a novel predictive model for emerging infectious diseases

The outbreak of emerging infectious diseases poses significant challenges to global public health. Accurate early forecasting is crucial for effective resource allocation and emergency response planning. This study aims to develop a comprehensive predictive model for emerging infectious diseases, integrating the blending framework, transfer learning, incremental learning, and the biological feature Rt to increase prediction accuracy and practicality. By transferring features from a COVID-19 dataset to a monkeypox dataset and introducing dynamically updated incremental learning techniques, the model's predictive capability in data-scarce scenarios was significantly improved. The research findings demonstrate that the blending framework performs exceptionally well in short-term (7-day) predictions. Furthermore, the combination of transfer learning and incremental learning techniques significantly enhanced the adaptability and precision, with a 91.41% improvement in the RMSE and an 89.13% improvement in the MAE. In particular, the inclusion of the Rt feature enabled the model to more accurately reflect the dynamics of disease spread, further improving the RMSE by 1.91% and the MAE by 2.17%. This study underscores the significant application potential of multimodel fusion and real-time data updates in infectious disease prediction, offering new theoretical perspectives and technical support. This research not only enriches the theoretical foundation of infectious disease prediction models but also provides reliable technical support for public health emergency responses. Future research should continue to explore integrating data from multiple sources and enhancing model generalization capabilities to further enhance the practicality and reliability of predictive tools.

Collaborative Real-World Evidence Among Regulators: Lessons and Perspectives.

The International Coalition of Medicines Regulatory Authorities (ICMRA), comprising 38 global medicines regulatory authorities, collaborates on shared challenges, notably during the COVID-19 pandemic. This article focuses on the ICMRA COVID-19 Real-World Evidence (RWE) and Observational Studies Working Group. The Working Group aimed to address challenges related to RWE and observational studies during the pandemic, resulting in impactful studies and ICMRA statements on international collaboration for RWE and COVID-19 vaccine safety. Reflecting on 3 years of collaboration, the Working Group surveyed members for insights, and recommendations were formulated to enhance research preparedness, collaboration, and response to future public health emergencies. The lessons learned highlight the importance of global collaborations, governance structures for rapid decision-making, and effective utilization of existing networks. Recommendations include the establishment of an international governance structure, a "coalition of the willing" for swift research collaboration, dedicated sub-groups, periodic workshops, common protocols, joint timelines, and data model templates, leveraging existing infrastructure, and strengthening outreach for transparency and engagement. The Working Group envisions repurposing into an RWE strategic and operational entity, contributing to global public health emergency response mechanisms. In conclusion, the Working Group's success lies in effective communication, collaborative research, and leveraging existing infrastructure, with ongoing contributions to global emergency response mechanisms.

Long-term validation of inner-urban mobility metrics derived from Twitter/X

Urban mobility analysis using Twitter as a proxy has gained significant attention in various application fields; however, long-term validation studies are scarce. This paper addresses this gap by assessing the reliability of Twitter data for modeling inner-urban mobility dynamics over a 27-month period in the. metropolitan area of Rio de Janeiro, Brazil. The evaluation involves the validation of Twitter-derived mobility estimates at both temporal and spatial scales, employing over 1.6 × 1011 mobile phone records of around three million users during the non-stationary mobility period from April 2020 to. June 2022, which coincided with the COVID-19 pandemic. The results highlight the need for caution when using Twitter for short-term modeling of urban mobility flows. Short-term inference can be influenced by Twitter policy changes and the availability of publicly accessible tweets. On the other hand, this long-term study demonstrates that employing multiple mobility metrics simultaneously, analyzing dynamic and static mobility changes concurrently, and employing robust preprocessing techniques such as rolling window downsampling can enhance the inference capabilities of Twitter data. These novel insights gained from a long-term perspective are vital, as Twitter - rebranded to X in 2023 - is extensively used by researchers worldwide to infer human movement patterns. Since conclusions drawn from studies using Twitter could be used to inform public policy, emergency response, and urban planning, evaluating the reliability of this data is of utmost importance.

Pandemic Palliatives and COVID-19 Coping: Toward the Development of a “Coping with Crisis Communications” (COCCO) Scale

ABSTRACT The COVID-19 pandemic underscored the critical role of coping strategies during global crises and demonstrated how official communications shape public responses. This study evaluates the psychometric validity of a novel pentadic “Coping with Crisis Communication” (COCCO) Scale, which categorizes coping behaviors into five behavioral responses: moving-with, moving-against, moving-outward, moving-away, and moving-inward. A national representative survey of 742 Swiss residents, conducted in February 2022, measured these coping responses to official COVID-19 communications from the Swiss Federal Office of Public Health (FOPH) and traditional Swiss news media (TNM). Items were developed to assess how participants engaged with, opposed, reached outward for support, distanced from, or internalized the messages. Confirmatory factor analyses tested multiple models (5-, 6-, 7-, and 8-factor structures) based on both the initial pentadic theory and data-driven refinements. While the original 5-factor model showed insufficient fit, a 7-factor model (moving-with, moving-toward, moving-against, moving-outward, moving-away, negative-moving-inward, positive-moving-inward) provided a satisfactory factor solution. This model exhibited measurement invariance across the three language versions of the scale (French, Italian, German) and across the two communication contexts (FOPH, TNM). The COCCO scale offers an effective, movement-based assessment of coping strategies in response to crisis communications, serving as a valuable tool for understanding public behavior during global crises.