An anti-infodemic virtual center for the Americas.

The Pan American Health Organization/World Health Organization (PAHO/WHO) Anti-Infodemic Virtual Center for the Americas (AIVCA) is a project led by the Department of Evidence and Intelligence for Action in Health, PAHO and the Center for Health Informatics, PAHO/WHO Collaborating Center on Information Systems for Health, at the University of Illinois, with the participation of PAHO staff and consultants across the region. Its goal is to develop a set of tools-pairing AI with human judgment-to help ministries of health and related health institutions respond to infodemics. Public health officials will learn about emerging threats detected by the center and get recommendations on how to respond. The virtual center is structured with three parallel teams: detection, evidence, and response. The detection team will employ a mixture of advanced search queries, machine learning, and other AI techniques to sift through more than 800 million new public social media posts per day to identify emerging infodemic threats in both English and Spanish. The evidence team will use the EasySearch federated search engine backed by AI, PAHO's knowledge management team, and the Librarian Reserve Corps to identify the most relevant authoritative sources. The response team will use a design approach to communicate recommended response strategies based on behavioural science, storytelling, and information design approaches.

El centro virtual contra la infodemia para la Región de las Américas de la Organización Panamericana de la Salud/Organización Mundial de la Salud (OPS/OMS) es un proyecto liderado por el Departamento de Evidencia e Inteligencia para la Acción en la Salud de la OPS y el Center for Health Informatics de la Universidad de Illinois, centro colaborador de la OPS/OMS en sistemas de información para la salud, con la participación de personal y consultores de la OPS en toda la Región. Su objetivo es crear un conjunto de herramientas que combinen inteligencia artificial (IA) y los criterios humanos para apoyar a los ministerios de salud y las instituciones relacionadas con la salud en la respuesta a la infodemia. Los funcionarios de salud pública recibirán formación sobre las amenazas emergentes detectadas por el centro y recomendaciones sobre cómo abordarlas. El centro virtual está estructurado en tres equipos paralelos: detección, evidencia y respuesta. El equipo de detección empleará una combinación de consultas mediante búsqueda avanzada, aprendizaje automático y otras técnicas de IA para evaluar más de 800 millones de publicaciones nuevas en las redes sociales al día con el fin de detectar amenazas emergentes en el ámbito de la infodemia tanto en inglés como en español. El equipo de evidencia hará uso del motor de búsqueda federado EasySearch y, con el apoyo de la IA, el equipo de gestión del conocimiento de la OPS y la red Librarian Reserve Corps, determinará cuáles son las fuentes autorizadas más pertinentes. El equipo de respuesta utilizará un enfoque vinculado al diseño para difundir las estrategias recomendadas sobre la base de las ciencias del comportamiento, la narración de historias y el diseño de la información.

O Centro Virtual Anti-Infodemia para as Américas (AIVCA, na sigla em inglês) da Organização Pan-Americana da Saúde/Organização Mundial da Saúde (OPAS/OMS) é um projeto liderado pelo Departamento de Evidência e Inteligência para a Ação em Saúde da OPAS e pelo Centro de Informática em Saúde da Universidade de Illinois, EUA (Centro Colaborador da OPAS/OMS para Sistemas de Informação para a Saúde), com a participação de funcionários e consultores da OPAS de toda a região. Seu objetivo é desenvolver um conjunto de ferramentas ­ combinando a inteligência artificial (IA) com o discernimento humano ­ para ajudar os ministérios e instituições de saúde a responder às infodemias. As autoridades de saúde pública aprenderão sobre as ameaças emergentes detectadas pelo centro e obterão recomendações sobre como responder. O centro virtual está estruturado com três equipes paralelas: detecção, evidência e resposta. A equipe de detecção utilizará consultas de pesquisa avançada, machine learning (aprendizagem de máquina) e outras técnicas de IA para filtrar mais de 800 milhões de novas postagens públicas nas redes sociais por dia, a fim de identificar ameaças infodêmicas emergentes em inglês e espanhol. A equipe de evidência usará o mecanismo de busca federada EasySearch, com apoio de IA, da equipe de gestão de conhecimento da OPAS e do Librarian Reserve Corps (LRC), para identificar as fontes abalizadas mais relevantes. A equipe de resposta usará uma abordagem de design para comunicar estratégias de resposta recomendadas com base em abordagens de ciência comportamental, narração de histórias e design da informação.

An anti-infodemic virtual center for the Americas

[ABSTRACT]. The Pan American Health Organization/ World Health Organization (PAHO/WHO) Anti-Infodemic Virtual Center for the Americas (AIVCA) is a project led by the Department of Evidence and Intelligence for Action in Health, PAHO and the Center for Health Informatics, PAHO/WHO Collaborating Center on Information Systems for Health, at the University of Illinois, with the participation of PAHO staff and consultants across the region. Its goal is to develop a set of tools—pairing AI with human judgment—to help ministries of health and related health institutions respond to infodemics. Public health officials will learn about emerging threats detected by the center and get recommendations on how to respond. The virtual center is structured with three parallel teams: detection, evidence, and response. The detection team will employ a mixture of advanced search que- ries, machine learning, and other AI techniques to sift through more than 800 million new public social media posts per day to identify emerging infodemic threats in both English and Spanish. The evidence team will use the EasySearch federated search engine backed by AI, PAHO’s knowledge management team, and the Librar- ian Reserve Corps to identify the most relevant authoritative sources. The response team will use a design approach to communicate recommended response strategies based on behavioural science, storytelling, and information design approaches.

[RESUMEN]. El centro virtual contra la infodemia para la Región de las Américas de la Organización Panamericana de la Salud/Organización Mundial de la Salud (OPS/OMS) es un proyecto liderado por el Departamento de Eviden- cia e Inteligencia para la Acción en la Salud de la OPS y el Center for Health Informatics de la Universidad de Illinois, centro colaborador de la OPS/OMS en sistemas de información para la salud, con la participación de personal y consultores de la OPS en toda la Región. Su objetivo es crear un conjunto de herramientas que combinen inteligencia artificial (IA) y los criterios humanos para apoyar a los ministerios de salud y las instituciones relacionadas con la salud en la respuesta a la infodemia. Los funcionarios de salud pública reci- birán formación sobre las amenazas emergentes detectadas por el centro y recomendaciones sobre cómo abordarlas. El centro virtual está estructurado en tres equipos paralelos: detección, evidencia y respuesta. El equipo de detección empleará una combinación de consultas mediante búsqueda avanzada, aprendizaje automático y otras técnicas de IA para evaluar más de 800 millones de publicaciones nuevas en las redes sociales al día con el fin de detectar amenazas emergentes en el ámbito de la infodemia tanto en inglés como en español. El equipo de evidencia hará uso del motor de búsqueda federado EasySearch y, con el apoyo de la IA, el equipo de gestión del conocimiento de la OPS y la red Librarian Reserve Corps, determinará cuáles son las fuentes autorizadas más pertinentes. El equipo de respuesta utilizará un enfoque vinculado al diseño para difundir las estrategias recomendadas sobre la base de las ciencias del comportamiento, la narración de historias y el diseño de la información.

[RESUMO]. O Centro Virtual Anti-Infodemia para as Américas (AIVCA, na sigla em inglês) da Organização Pan-Ameri- cana da Saúde/Organização Mundial da Saúde (OPAS/OMS) é um projeto liderado pelo Departamento de Evidência e Inteligência para a Ação em Saúde da OPAS e pelo Centro de Informática em Saúde da Uni- versidade de Illinois, EUA (Centro Colaborador da OPAS/OMS para Sistemas de Informação para a Saúde), com a participação de funcionários e consultores da OPAS de toda a região. Seu objetivo é desenvolver um conjunto de ferramentas — combinando a inteligência artificial (IA) com o discernimento humano — para ajudar os ministérios e instituições de saúde a responder às infodemias. As autoridades de saúde pública aprenderão sobre as ameaças emergentes detectadas pelo centro e obterão recomendações sobre como responder. O centro virtual está estruturado com três equipes paralelas: detecção, evidência e resposta. A equipe de detecção utilizará consultas de pesquisa avançada, machine learning (aprendizagem de máquina) e outras técnicas de IA para filtrar mais de 800 milhões de novas postagens públicas nas redes sociais por dia, a fim de identificar ameaças infodêmicas emergentes em inglês e espanhol. A equipe de evidência usará o mecanismo de busca federada EasySearch, com apoio de IA, da equipe de gestão de conhecimento da OPAS e do Librarian Reserve Corps (LRC), para identificar as fontes abalizadas mais relevantes. A equipe de resposta usará uma abordagem de design para comunicar estratégias de resposta recomendadas com base em abordagens de ciência comportamental, narração de histórias e design da informação.

An anti-infodemic virtual center for the Americas / Un centro virtual contra la infodemia para la Región de las Américas / Um centro virtual anti-infodemia para as Américas

ABSTRACT The Pan American Health Organization/World Health Organization (PAHO/WHO) Anti-Infodemic Virtual Center for the Americas (AIVCA) is a project led by the Department of Evidence and Intelligence for Action in Health, PAHO and the Center for Health Informatics, PAHO/WHO Collaborating Center on Information Systems for Health, at the University of Illinois, with the participation of PAHO staff and consultants across the region. Its goal is to develop a set of tools—pairing AI with human judgment—to help ministries of health and related health institutions respond to infodemics. Public health officials will learn about emerging threats detected by the center and get recommendations on how to respond. The virtual center is structured with three parallel teams: detection, evidence, and response. The detection team will employ a mixture of advanced search queries, machine learning, and other AI techniques to sift through more than 800 million new public social media posts per day to identify emerging infodemic threats in both English and Spanish. The evidence team will use the EasySearch federated search engine backed by AI, PAHO's knowledge management team, and the Librarian Reserve Corps to identify the most relevant authoritative sources. The response team will use a design approach to communicate recommended response strategies based on behavioural science, storytelling, and information design approaches.

RESUMEN El centro virtual contra la infodemia para la Región de las Américas de la Organización Panamericana de la Salud/Organización Mundial de la Salud (OPS/OMS) es un proyecto liderado por el Departamento de Evidencia e Inteligencia para la Acción en la Salud de la OPS y el Center for Health Informatics de la Universidad de Illinois, centro colaborador de la OPS/OMS en sistemas de información para la salud, con la participación de personal y consultores de la OPS en toda la Región. Su objetivo es crear un conjunto de herramientas que combinen inteligencia artificial (IA) y los criterios humanos para apoyar a los ministerios de salud y las instituciones relacionadas con la salud en la respuesta a la infodemia. Los funcionarios de salud pública recibirán formación sobre las amenazas emergentes detectadas por el centro y recomendaciones sobre cómo abordarlas. El centro virtual está estructurado en tres equipos paralelos: detección, evidencia y respuesta. El equipo de detección empleará una combinación de consultas mediante búsqueda avanzada, aprendizaje automático y otras técnicas de IA para evaluar más de 800 millones de publicaciones nuevas en las redes sociales al día con el fin de detectar amenazas emergentes en el ámbito de la infodemia tanto en inglés como en español. El equipo de evidencia hará uso del motor de búsqueda federado EasySearch y, con el apoyo de la IA, el equipo de gestión del conocimiento de la OPS y la red Librarian Reserve Corps, determinará cuáles son las fuentes autorizadas más pertinentes. El equipo de respuesta utilizará un enfoque vinculado al diseño para difundir las estrategias recomendadas sobre la base de las ciencias del comportamiento, la narración de historias y el diseño de la información.

RESUMO O Centro Virtual Anti-Infodemia para as Américas (AIVCA, na sigla em inglês) da Organização Pan-Americana da Saúde/Organização Mundial da Saúde (OPAS/OMS) é um projeto liderado pelo Departamento de Evidência e Inteligência para a Ação em Saúde da OPAS e pelo Centro de Informática em Saúde da Universidade de Illinois, EUA (Centro Colaborador da OPAS/OMS para Sistemas de Informação para a Saúde), com a participação de funcionários e consultores da OPAS de toda a região. Seu objetivo é desenvolver um conjunto de ferramentas — combinando a inteligência artificial (IA) com o discernimento humano — para ajudar os ministérios e instituições de saúde a responder às infodemias. As autoridades de saúde pública aprenderão sobre as ameaças emergentes detectadas pelo centro e obterão recomendações sobre como responder. O centro virtual está estruturado com três equipes paralelas: detecção, evidência e resposta. A equipe de detecção utilizará consultas de pesquisa avançada, machine learning (aprendizagem de máquina) e outras técnicas de IA para filtrar mais de 800 milhões de novas postagens públicas nas redes sociais por dia, a fim de identificar ameaças infodêmicas emergentes em inglês e espanhol. A equipe de evidência usará o mecanismo de busca federada EasySearch, com apoio de IA, da equipe de gestão de conhecimento da OPAS e do Librarian Reserve Corps (LRC), para identificar as fontes abalizadas mais relevantes. A equipe de resposta usará uma abordagem de design para comunicar estratégias de resposta recomendadas com base em abordagens de ciência comportamental, narração de histórias e design da informação.

Effect of a Social Norm Email Feedback Program on the Unnecessary Prescription of Nimodipine in Ambulatory Care of Older Adults: A Randomized Clinical Trial.

Importance: Nimodipine is a highly prescribed drug for the treatment of cognitive impairment and dementia in Argentina. There is little evidence to support the use of nimodipine for cognitive impairment and dementia. Objective: To test the effectiveness of a behavioral intervention based on social norm feedback to reduce prescription of nimodipine for cognitive impairment in Argentina. Design, Setting, and Participants: This pragmatic parallel-group randomized clinical trial included 2 arms with a 1:1 allocation ratio. General practitioner physicians in the national health care system for older adults in Argentina (INSSJP-PAMI) with history of high nimodipine prescription rate were enrolled. The study was conducted from May 2019 to October 2019, and data were analyzed from November 2019 to February 2020. Interventions: The treatment group received 2 emails with evidence-based information about nimodipine plus the individual's level of nimodipine prescription compared with their peers. The control group received 2 emails with general information about the risks of overprescription in older adults. Main Outcomes and Measures: The primary outcome was the cumulative number of nimodipine prescriptions per 1000 prescriptions of all drugs made by the targeted physicians during the 6 months of the study. Secondary outcomes included annual monetary savings attributable to the intervention and physicians' qualitative perceptions of the acceptability of the procedure. Results: Of 1811 physicians enrolled, 906 physicians (354 [39.1%] women; mean [SD] age, 57.10 [10.73] years) were randomized to treatment and 905 participants (331 [36.6%] women; mean [SD] age, 56.49 [10.47] years) to the control group. Physicians in the treatment group wrote a mean of 93.25 (95% CI, 89.27 to 97.24) prescriptions of nimodipine, compared with 98.99 (95% CI, 95.00 to 102.98) prescriptions among practitioners in the control group during the half-year of the intervention (mean difference, -5.73 [95% CI, -11.38 to -0.10] prescriptions; P = .046), which meant a 5.79% reduction. Regression analysis revealed a significant association of the group condition with number of prescriptions per 1000 total prescriptions when controlling for baseline prescriptions (B = -0.312 [95% CI, -0.465 to -0.160]; P < .001). The observed difference corresponds to a 4.48% reduction in nimodipine prescriptions per 1000 prescriptions of all drugs made by physicians in the treated group compared with the control group. Physicians who effectively opened the email in the treatment group (427 physicians [47.1%]) prescribed the drug 11.3% less compared with the control group (426 physicians) (mean difference, -10.78 [95% CI, -18.53 to -3.03] prescriptions; P = .006). Expenditures were 7.18% lower in the treatment group, resulting in an estimated annual net cost benefit of US $234 893.35 (95% CI, $225 565.35 to $237 112.30). Conclusions and Relevance: In this randomized clinical trial, the social norm email feedback program showed an effect on curbing the nonrecommended prescription of nimodipine. It was highly cost-effective and well accepted by participants. Trial Registration: ISRCTN.org identifier: ISRCTN17823729.

The power of knowledge about dementia in Latin America across health professionals working on aging.

INTRODUCTION: Expert knowledge is critical to fight dementia in inequitable regions like Latin American and Caribbean countries (LACs). However, the opinions of aging experts on public policies' accessibility and transmission, stigma, diagnostic manuals, data-sharing platforms, and use of behavioral insights (BIs) are not well known. METHODS: We investigated opinions among health professionals working on aging in LACs (N = 3365) with regression models including expertise-related information (public policies, BI), individual differences (work, age, academic degree), and location. RESULTS: Experts specified low public policy knowledge (X2  = 41.27, P < .001), high levels of stigma (X2  = 2636.37, P < .001), almost absent BI knowledge (X2  = 56.58, P < .001), and needs for regional diagnostic manuals (X2  = 2893.63, df = 3, P < .001) and data-sharing platforms (X2 = 1267.5, df = 3, P < .001). Lack of dementia knowledge was modulated by different factors. An implemented BI-based treatment for a proposed prevention program improved perception across experts. DISCUSSION: Our findings help to prioritize future potential actions of governmental agencies and non-governmental organizations (NGOs) to improve LACs' dementia knowledge.

Dynamical predictions of insular hubs for social cognition and their application to stroke.

The insular cortex (IC) is considered a rich hub for context-sensitive emotions/social cognition. Patients with focal IC stroke provide unique opportunities to study socio-emotional processes. Nevertheless, Couto et al. (2013b) have recently reported controversial results regarding IC involvement in emotion and social cognition. Similarly, patients with similar lesions show high functional variability, ranging from almost totally preserved to strongly impaired behavior. Critical evidence suggests that the variability of these patients in the above domains can be explained by enhanced neuroplasticity, compensatory processes, and functional remapping after stroke. Therefore, socio-emotional processes would depend on long-distance connections between the IC and frontotemporal regions. We propose that predictive coding and effective connectivity represent a novel approach to explore functional connectivity and assess compensatory, contralateral, and subsidiary network differences among focal stroke patients. This approach would help explain why socio-emotional performance is so variable within this population.

Time to Tango: expertise and contextual anticipation during action observation.

Predictive theories of action observation propose that we use our own motor system as a guide for anticipating and understanding other people's actions through the generation of context-based expectations. According to this view, people should be better in predicting and interpreting those actions that are present in their own motor repertoire compared to those that are not. We recorded high-density event-related potentials (ERPs: P300, N400 and Slow Wave, SW) and source estimation in 80 subjects separated by their level of expertise (experts, beginners and naïves) as they observed realistic videos of Tango steps with different degrees of execution correctness. We also performed path analysis to infer causal relationships between ongoing anticipatory brain activity, evoked semantic responses, expertise measures and behavioral performance. We found that anticipatory activity, with sources in a fronto-parieto-occipital network, early discriminated between groups according to their level of expertise. Furthermore, this early activity significantly predicted subsequent semantic integration indexed by semantic responses (N400 and SW, sourced in temporal and motor regions) which also predicted motor expertise. In addition, motor expertise was a good predictor of behavioral performance. Our results show that neural and temporal dynamics underlying contextual action anticipation and comprehension can be interpreted in terms of successive levels of contextual prediction that are significantly modulated by subject's prior experience.

Organization of brain networks governed by long-range connections index autistic traits in the general population.

BACKGROUND: The dimensional approach to autism spectrum disorder (ASD) considers ASD as the extreme of a dimension traversing through the entire population. We explored the potential utility of electroencephalography (EEG) functional connectivity as a biomarker. We hypothesized that individual differences in autistic traits of typical subjects would involve a long-range connectivity diminution within the delta band. METHODS: Resting-state EEG functional connectivity was measured for 74 neurotypical subjects. All participants also provided a questionnaire (Social Responsiveness Scale, SRS) that was completed by an informant who knows the participant in social settings. We conducted multivariate regression between the SRS score and functional connectivity in all EEG frequency bands. We explored modulations of network graph metrics characterizing the optimality of a network using the SRS score. RESULTS: Our results show a decay in functional connectivity mainly within the delta and theta bands (the lower part of the EEG spectrum) associated with an increasing number of autistic traits. When inspecting the impact of autistic traits on the global organization of the functional network, we found that the optimal properties of the network are inversely related to the number of autistic traits, suggesting that the autistic dimension, throughout the entire population, modulates the efficiency of functional brain networks. CONCLUSIONS: EEG functional connectivity at low frequencies and its associated network properties may be associated with some autistic traits in the general population.