Multi-variate model of T cell clonotype competition and homeostasis.

Diversity of the naive T cell repertoire is maintained by competition for stimuli provided by self-peptides bound to major histocompatibility complexes (self-pMHCs). We extend an existing bi-variate competition model to a multi-variate model of the dynamics of multiple T cell clonotypes which share stimuli. In order to understand the late-time behaviour of the system, we analyse: (i) the dynamics until the extinction of the first clonotype, (ii) the time to the first extinction event, (iii) the probability of extinction of each clonotype, and (iv) the size of the surviving clonotypes when the first extinction event takes place. We also find the probability distribution of the number of cell divisions per clonotype before its extinction. The mean size of a new clonotype at quasi-steady state is an increasing function of the stimulus available to it, and a decreasing function of the fraction of stimuli it shares with other clonotypes. Thus, the probability of, and time to, extinction of a new clonotype entering the pool of T cell clonotypes is determined by the extent of competition for stimuli it experiences and by its initial number of cells.

Understanding the use/non-use of an internet-based intervention complementing standard depression treatment: A qualitative study of user's experiences.

Introduction: There is sufficient evidence about the effectiveness of internet-based interventions; however, the users' level of adoption and utilization remains low, with this phenomenon requiring adequate explanation. Objective: The aim of this qualitative study was to explore the users' perceptions and experience of a web-based program (ASCENSO), designed to complement (usual) in-person depression treatment. Method: Twelve participants of the ASCENSO program, comprised of adult individuals (M = 44.3, SD = 13.4) of both genders (67% women) undergoing treatment for depression, were interviewed through semi-structured interviews. The data obtained from these interviews were analyzed utilizing a constructivist grounded theory approach. The interviews were transcribed and analyzed by trained coders. A constant comparative analysis of emergent themes was conducted. Results: These show that users employ and appreciate the program when their interaction with it emulates a "humanized relationship," that is, when the program is proactive in assisting users with their requests and when it responds in a pertinent and individualized manner to their emotional states and needs. Conclusions: Our findings highlight the challenges associated with the development of algorithms capable of attracting different potential users. These should be designed to generate a virtual relationship that emulates human interaction and targets the characteristics of each user, for example, considering the specific phenomenology of their health condition, their present emotional states, and perceived needs. Elements that will vary as mental symptomatology evolve.

Prognostic Factors and Markers in Non-Small Cell Lung Cancer: Recent Progress and Future Challenges.

Lung cancer is a highly aggressive neoplasm and, despite the development of recent therapies, tumor progression and recurrence following the initial response remains unsolved. Several questions remain unanswered about non-small cell lung cancer (NSCLC): (1) Which patients will actually benefit from therapy? (2) What are the predictive factors of response to MAbs and TKIs? (3) What are the best combination strategies with conventional treatments or new antineoplastic drugs? To answer these questions, an integrative literature review was carried out, searching articles in PUBMED, NCBI-PMC, Google Academic, and others. Here, we will examine the molecular genetics of lung cancer, emphasizing NSCLC, and delineate the primary categories of inhibitors based on their molecular targets, alongside the main treatment alternatives depending on the type of acquired resistance. We highlighted new therapies based on epigenetic information and a single-cell approach as a potential source of new biomarkers. The current and future of NSCLC management hinges upon genotyping correct prognostic markers, as well as on the evolution of precision medicine, which guarantees a tailored drug combination with precise targeting.

How did the COVID-19 crisis affect different types of workers in the developing world?

This paper examines how the COVID-19 pandemic affected the employment of different groups of workers across 40 mostly low and middle-income countries. Employment outcomes during the crisis are tracked through high-frequency phone surveys conducted by the World Bank and national statistics offices. Our results show that larger shares of female, young, less educated, and urban workers stopped working at the beginning of the pandemic. Gender gaps in work stoppage stemmed mainly from gender differences within sectors rather than differential employment patterns of men and women across sectors. Differences in work stoppage between urban and rural workers were markedly smaller than those across gender, age, and education groups. Preliminary results from 10 countries suggest that following the initial shock at the start of the pandemic, employment rates partially recovered between April and August 2020, with greater gains for those groups that had borne the brunt of the early jobs losses. Although the high-frequency phone surveys over-represent household heads and therefore overestimate employment rates, a validation exercise for five countries suggests that they provide a reasonably accurate measure of disparities in employment levels by gender, education, and urban/rural location following the onset of the crisis, although they perform less well in capturing disparities between age groups. These results shed new light on the distributional labor market consequences of the COVID-19 crisis in developing countries, and suggest that real-time phone surveys, despite their lack of representativeness, are a valuable source of information to measure differential employment impacts across groups during an unfolding crisis.

Bayesian inference for optimal dynamic treatment regimes in practice.

In this work, we examine recently developed methods for Bayesian inference of optimal dynamic treatment regimes (DTRs). DTRs are a set of treatment decision rules aimed at tailoring patient care to patient-specific characteristics, thereby falling within the realm of precision medicine. In this field, researchers seek to tailor therapy with the intention of improving health outcomes; therefore, they are most interested in identifying optimal DTRs. Recent work has developed Bayesian methods for identifying optimal DTRs in a family indexed by ψ via Bayesian dynamic marginal structural models (MSMs) (Rodriguez Duque D, Stephens DA, Moodie EEM, Klein MB. Semiparametric Bayesian inference for dynamic treatment regimes via dynamic regime marginal structural models. Biostatistics; 2022. (In Press)); we review the proposed estimation procedure and illustrate its use via the new BayesDTR R package. Although methods in Rodriguez Duque D, Stephens DA, Moodie EEM, Klein MB. (Semiparametric Bayesian inference for dynamic treatment regimes via dynamic regime marginal structural models. Biostatistics; 2022. (In Press)) can estimate optimal DTRs well, they may lead to biased estimators when the model for the expected outcome if everyone in a population were to follow a given treatment strategy, known as a value function, is misspecified or when a grid search for the optimum is employed. We describe recent work that uses a Gaussian process ( G P ) prior on the value function as a means to robustly identify optimal DTRs (Rodriguez Duque D, Stephens DA, Moodie EEM. Estimation of optimal dynamic treatment regimes using Gaussian processes; 2022. Available from: https://doi.org/10.48550/arXiv.2105.12259). We demonstrate how a G P approach may be implemented with the BayesDTR package and contrast it with other value-search approaches to identifying optimal DTRs. We use data from an HIV therapeutic trial in order to illustrate a standard analysis with these methods, using both the original observed trial data and an additional simulated component to showcase a longitudinal (two-stage DTR) analysis.

Translational Bioinformatics Applied to the Study of Complex Diseases.

Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment of cancer. An integrative literature review was carried out, obtaining articles through several websites, among them: PUBMED, Science Direct, NCBI-PMC, Scientific Electronic Library Online (SciELO), and Google Academic, published in English, Spanish, and Portuguese, indexed in the referred databases and answering the following guiding question: "How does TBI provide a scientific understanding of complex diseases?" An additional effort is aimed at the dissemination, inclusion, and perpetuation of TBI knowledge from the academic environment to society, helping the study, understanding, and elucidating of complex disease mechanics and their treatment.

Recurrent networks endowed with structural priors explain suboptimal animal behavior.

The strategies found by animals facing a new task are determined both by individual experience and by structural priors evolved to leverage the statistics of natural environments. Rats quickly learn to capitalize on the trial sequence correlations of two-alternative forced choice (2AFC) tasks after correct trials but consistently deviate from optimal behavior after error trials. To understand this outcome-dependent gating, we first show that recurrent neural networks (RNNs) trained in the same 2AFC task outperform rats as they can readily learn to use across-trial information both after correct and error trials. We hypothesize that, although RNNs can optimize their behavior in the 2AFC task without any a priori restrictions, rats' strategy is constrained by a structural prior adapted to a natural environment in which rewarded and non-rewarded actions provide largely asymmetric information. When pre-training RNNs in a more ecological task with more than two possible choices, networks develop a strategy by which they gate off the across-trial evidence after errors, mimicking rats' behavior. Population analyses show that the pre-trained networks form an accurate representation of the sequence statistics independently of the outcome in the previous trial. After error trials, gating is implemented by a change in the network dynamics that temporarily decouple the categorization of the stimulus from the across-trial accumulated evidence. Our results suggest that the rats' suboptimal behavior reflects the influence of a structural prior that reacts to errors by isolating the network decision dynamics from the context, ultimately constraining the performance in a 2AFC laboratory task.

Semiparametric Bayesian inference for optimal dynamic treatment regimes via dynamic marginal structural models.

Considerable statistical work done on dynamic treatment regimes (DTRs) is in the frequentist paradigm, but Bayesian methods may have much to offer in this setting as they allow for the appropriate representation and propagation of uncertainty, including at the individual level. In this work, we extend the use of recently developed Bayesian methods for Marginal Structural Models to arrive at inference of DTRs. We do this (i) by linking the observational world with a world in which all patients are randomized to a DTR, thereby allowing for causal inference and then (ii) by maximizing a posterior predictive utility, where the posterior distribution has been obtained from nonparametric prior assumptions on the observational world data-generating process. Our approach relies on Bayesian semiparametric inference, where inference about a finite-dimensional parameter is made all while working within an infinite-dimensional space of distributions. We further study Bayesian inference of DTRs in the double robust setting by using posterior predictive inference and the nonparametric Bayesian bootstrap. The proposed methods allow for uncertainty quantification at the individual level, thereby enabling personalized decision-making. We examine the performance of these methods via simulation and demonstrate their utility by exploring whether to adapt HIV therapy to a measure of patients' liver health, in order to minimize liver scarring.

Estudio piloto de un programa basado en Internet para la prevención e intervención temprana de la depresión en adolescentes / Feasibility and effectiveness of an Internet-based program for the prevention and early intervention of depression inInternet adolescents

Resumen Antecedentes: la alta prevalencia de depresión en la adolescencia y sus graves consecuencias, asociadas a su falta de detección y tratamiento, estimulan el interés en la investigación respecto a su prevención e intervención tempranas. Las intervenciones basadas en las tecnologías de la información y la comunicación (TIC), dada su flexibilidad y capacidad de difusión, representan oportunidades innovadoras; no obstante, en Latinoamérica hay poca evidencia sobre su impacto y eficacia. Objetivo y metodología: se realiza un estudio piloto cuantitativo cuasiexperimental que busca evaluar la factibilidad del programa basado en Internet "Cuida tu Ánimo", mediante las variables de uso y aceptabilidad, y la estimación del efecto, en 215 adolescentes (103 grupo activo, 112 grupo control) de dos instituciones educativas de la ciudad de Medellín. Se evaluaron las interacciones de los adolescentes con el Programa, su uso-aceptabilidad, el nivel de sintomatología depresiva y otros aspectos relacionados. Resultados: los adolescentes reportan alta aceptación y uso muy moderado del Programa. Señalan el aprendizaje sobre depresión y detección temprana del riesgo que les proporcionó el Programa; y recomiendan aumentar la interactividad de la plataforma web, generar contenidos más diversos y entretenidos, y aumentar los niveles de presencialidad de la intervención. Conclusiones: los programas basados en las TIC pueden ser un complemento favorable para la prevención e intervención tempranas de la depresión en adolescentes. Dada la dificultad de asociar la estimación del efecto del Programa con su uso, se recomienda en estudios futuros utilizar un diseño que permita relacionar los indicadores de uso con los de resultado (dosis-efecto).

Abstract Background: the high prevalence of depression in adolescence and its serious consequences, associated with its lack of detection and treatment, stimulate interest in research regarding its early prevention and intervention. Interventions based on information and communication technologies (ICT), given their flexibility and capacity for dissemination, represent innovative opportunities; however, in Latin America there is little evidence on their impact and efficacy. Objective and Methods: a quasi-experimental quantitative pilot study was carried out to evaluate the feasibility, through the variables of use and acceptability, and the estimated effect of the Internet-based program "Cuida tu Ánimo", in 215 adolescents (103 active group, 112 control group) from two educational institutions. The adolescents' interactions with the program, its use-acceptability, and the level of depressive symptomatology and other related aspects were evaluated. Results: the adolescents report high acceptance and very moderate use of the Program. They point out that the program allowed them to learn about depression and early detection of risk; also, they recommend increasing the interactivity of the web platform, designing more diverse and entertaining content, and increasing the presence of the intervention. Conclusions: Internet-based programs such as Cuida tu Ánimo can be a favorable complement for the prevention and early intervention of depression in adolescents. Considering the difficulty in relating the estimation of the Program's effect with its use, it is recommended that future studies include a design that permits associating the use indicators with the outcome indicators (dose-effect).

Pre-existing humoral immunity to human common cold coronaviruses negatively impacts the protective SARS-CoV-2 antibody response.

SARS-CoV-2 infection causes diverse outcomes ranging from asymptomatic infection to respiratory distress and death. A major unresolved question is whether prior immunity to endemic, human common cold coronaviruses (hCCCoVs) impacts susceptibility to SARS-CoV-2 infection or immunity following infection and vaccination. Therefore, we analyzed samples from the same individuals before and after SARS-CoV-2 infection or vaccination. We found hCCCoV antibody levels increase after SARS-CoV-2 exposure, demonstrating cross-reactivity. However, a case-control study indicates that baseline hCCCoV antibody levels are not associated with protection against SARS-CoV-2 infection. Rather, higher magnitudes of pre-existing betacoronavirus antibodies correlate with more SARS-CoV-2 antibodies following infection, an indicator of greater disease severity. Additionally, immunization with hCCCoV spike proteins before SARS-CoV-2 immunization impedes the generation of SARS-CoV-2-neutralizing antibodies in mice. Together, these data suggest that pre-existing hCCCoV antibodies hinder SARS-CoV-2 antibody-based immunity following infection and provide insight on how pre-existing coronavirus immunity impacts SARS-CoV-2 infection, which is critical considering emerging variants.

An Adjunctive Internet-Based Intervention to Enhance Treatment for Depression in Adults: Randomized Controlled Trial.

BACKGROUND: Internet-based interventions promise to enhance the accessibility of mental health care for a greater number of people and in more remote places. Their effectiveness has been shown for the prevention and treatment of various mental disorders. However, their potential when delivered as add-on to conventional treatment (ie, blended care) is less clear. OBJECTIVE: The aim of this study is to study the effectiveness of an internet intervention (ASCENSO) implemented in addition to face-to-face treatment as usual (TAU) for depression. METHODS: A 2-arm, parallel-group, randomized controlled trial was conducted in an outpatient private mental health care center in Chile. In all, 167 adults, diagnosed with major depressive disorder, without severe comorbidities, and with internet access, were included. Eighty-four participants were assigned to the intervention group and received medical and psychological TAU from the mental health center plus access to the ASCENSO online platform. The control group (n=83) received only TAU. The ASCENSO platform includes psycho-educational information, depressive symptom monitoring and feedback, and managing emergencies based on the principles of cognitive behavioral therapy. Emergency management was mental health provider-assisted. TAU includes access to primary care physicians and psychiatrists, to a brief individual psychotherapy, and to medication when needed. The baseline questionnaires were administered in person, and 6- and 9-months assessments were conducted online. Depression symptoms and quality of life were measured by self-administered questionnaires, and treatment adherence was determined via the Mental Health Center's internal records. The usage of ASCENSO was assessed by server logs. Reduction on depressive symptomatology was considered as the primary outcome of the intervention and quality of life as a secondary outcome. RESULTS: Of the 84 participants in the intervention group, 5 participants (6%) never accessed the online platform. Of the remaining 79 participants who accessed ASCENSO, 1 (1%, 1/79) did not answer any of the symptom questionnaire, and most participants (72/79, 91%) answered the monitoring questionnaires irregularly. The ASCENSO intervention implemented in addition to face-to-face care did not improve the outcome of the usual care delivered at the mental health center, either in terms of reduction of depressive symptoms (F2,6087= 0.48; P=.62) or in the improvement of quality of life (EQ-5D-3L: F2,7678=0.24; P=.79 and EQ-VAS: F2,6670= 0.13; P=.88). In contrast, for the primary (F2,850=78.25; P<.001) and secondary outcomes (EQ-5D-3L: F2,1067=37.87; EQ-VAS: F2,4390= 51.69; P<.001) in both groups, there was an improvement from baseline to 6 months (P<.001), but there was no change at 9 months. In addition, no effects on adherence to or use of TAU were found. Finally, the dropout rate for the face-to-face treatment component was 54% (45/84) for the intervention group versus 39% (32/83) for the control group (P=.07). CONCLUSIONS: The fact that the adjunctive access to ASCENSO did not improve outcome could be due to both the rather high effectiveness of TAU and to patients' limited use of the online platform. TRIAL REGISTRATION: ClinicalTrials.gov NCT03093467; https://clinicaltrials.gov/ct2/show/NCT03093467.

Proactive and reactive accumulation-to-bound processes compete during perceptual decisions.

Standard models of perceptual decision-making postulate that a response is triggered in reaction to stimulus presentation when the accumulated stimulus evidence reaches a decision threshold. This framework excludes however the possibility that informed responses are generated proactively at a time independent of stimulus. Here, we find that, in a free reaction time auditory task in rats, reactive and proactive responses coexist, suggesting that choice selection and motor initiation, commonly viewed as serial processes, are decoupled in general. We capture this behavior by a novel model in which proactive and reactive responses are triggered whenever either of two competing processes, respectively Action Initiation or Evidence Accumulation, reaches a bound. In both types of response, the choice is ultimately informed by the Evidence Accumulation process. The Action Initiation process readily explains premature responses, contributes to urgency effects at long reaction times and mediates the slowing of the responses as animals get satiated and tired during sessions. Moreover, it successfully predicts reaction time distributions when the stimulus was either delayed, advanced or omitted. Overall, these results fundamentally extend standard models of evidence accumulation in decision making by showing that proactive and reactive processes compete for the generation of responses.

Feasibility and Acceptability of "Cuida tu Ánimo" (Take Care of Your Mood): An Internet-Based Program for Prevention and Early Intervention of Adolescent Depression in Chile and Colombia.

The rapid internet penetration in Latin American countries has made it possible to implement digital mental health interventions. "Cuida tu Ánimo" (Take Care of Your Mood) is an internet-based program for the prevention and early intervention of depression in adolescents. A pilot study was conducted in Chile and Colombia to study the feasibility and acceptability of the program and estimate its effects. There were 199 participants (53.3% women; mean age = 14.8 years, SD = 1.0) recruited from two schools in Chile and two schools in Colombia. Qualitative and quantitative methods were applied for data collection and analyses. Although the levels of acceptance were moderate to high across all variables, adherence was lower than expected. The participants deemed important for an intervention of this type offered a higher level of interaction with team members through internet-based and face-to-face activities. Post-intervention outcomes show a reduction in depressive and anxious symptoms in adolescents in Chile, while there were no significant changes in the level of symptomatology in adolescents in Colombia. The women used the program more than the men. Results show the need to improve the intervention by increasing its levels of customization and developing strategies to achieve better adherence. The contradictory results of the program in Chile and Colombia suggest the importance of other variables beyond the content of the intervention, such as the setting or context of the intervention.

Quantifying T Cell Cross-Reactivity: Influenza and Coronaviruses.

If viral strains are sufficiently similar in their immunodominant epitopes, then populations of cross-reactive T cells may be boosted by exposure to one strain and provide protection against infection by another at a later date. This type of pre-existing immunity may be important in the adaptive immune response to influenza and to coronaviruses. Patterns of recognition of epitopes by T cell clonotypes (a set of cells sharing the same T cell receptor) are represented as edges on a bipartite network. We describe different methods of constructing bipartite networks that exhibit cross-reactivity, and the dynamics of the T cell repertoire in conditions of homeostasis, infection and re-infection. Cross-reactivity may arise simply by chance, or because immunodominant epitopes of different strains are structurally similar. We introduce a circular space of epitopes, so that T cell cross-reactivity is a quantitative measure of the overlap between clonotypes that recognize similar (that is, close in epitope space) epitopes.

Design of COVID-19 staged alert systems to ensure healthcare capacity with minimal closures.

Community mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including France's ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As proof-of-concept, we describe the optimization and maintenance of the staged alert system that has guided COVID-19 policy in a large US city (Austin, Texas) since May 2020. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.

Distinct circuits in rat central amygdala for defensive behaviors evoked by socially signaled imminent versus remote danger.

Animals display a rich repertoire of defensive responses adequate to the threat proximity. In social species, these reactions can be additionally influenced by the behavior of fearful conspecifics. However, the majority of neuroscientific studies on socially triggered defensive responses focuses on one type of behavior, freezing. To study a broader range of socially triggered reactions and underlying mechanisms, we directly compared two experimental paradigms, mimicking occurrence of the imminent versus remote threat. Observation of a partner currently experiencing aversive stimulation evokes passive defensive responses in the observer rats. Similar interaction with a partner that has just undergone the aversive stimulation prompts animals to increase active exploration. Although the observers display behaviors similar to those of the aversively stimulated demonstrators, their reactions are not synchronized in time, suggesting that observers' responses are caused by the change in their affective state rather than mimicry. Using opsins targeted to behaviorally activated neurons, we tagged central amygdala (CeA) cells implicated in observers' responses to either imminent or remote threat and reactivated them during the exploration of a novel environment. The manipulation revealed that the two populations of CeA cells promote passive or active defensive responses, respectively. Further experiments confirmed that the two populations of cells at least partially differ in expression of molecular markers (protein kinase C-δ [PKC-δ] and corticotropin-releasing factor [CRF]) and connectivity patterns (receiving input from the basolateral amygdala or from the anterior insula). The results are consistent with the literature on single subjects' fear conditioning, suggesting that similar neuronal circuits control defensive responses in social and non-social contexts.

Design of COVID-19 Staged Alert Systems to Ensure Healthcare Capacity with Minimal Closures.

Community mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including France's ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.

Terminación de la psicoterapia desde la perspectiva de los pacientes / Psychotherapy Termination from the Patients' Perspective

Resumen El aumento de la oferta de servicios de psicoterapia en las últimas décadas justifica el estudio de los elementos relacionados con su terminación, y su relación con el cumplimiento de los objetivos y la adherencia de los pacientes al tratamiento. Objetivo: identificar los factores que influyen en la terminación de los procesos psicoterapéuticos desde la perspectiva de los pacientes. Metodología: se utilizó un diseño de investigación mixto de triangulación concurrente; se aplicaron encuestas estructuradas y entrevistas en profundidad sobre el fin de la terapia. A nivel cuantitativo se realizaron análisis descriptivos y de regresión, y, a nivel cualitativo, reducción de datos, comparación constante y triangulación de la información. Participaron 137 pacientes de dos centros universitarios de atención psicológica en Antioquia (Colombia), 100 participantes respondieron una encuesta y los restantes una entrevista cualitativa. Resultados: se identificaron tres dimensiones relacionadas con la terminación de los procesos psicoterapéuticos: el cumplimiento o no de los objetivos, el tipo de atribución causal del paciente (interna o externa) y la persona que decide finalizar. La mayoría de los pacientes del estudio dejaron de asistir a psicoterapia sin cumplir sus objetivos o con un cumplimiento parcial de estos, por atribuciones externas y por decisión propia. Discusión: los aspectos institucionales, terapéuticos y de la vida del paciente tienen un rol significativo en la terminación de los procesos psicoterapéuticos. Además, se plantea la importancia de considerar en la formación de los terapeutas las características de los procesos de cierre y los diferentes marcadores asociados con la terminación prematura.

Abstract The increase in the supply of psychotherapy services in recent decades justifies the study of the elements related to its termination. This is one of the main topics to understand achievement of therapeutic goals and adherence of patients in psychotherapy. Aim: to identify the factors that influence termination of psychotherapeutic processes from the patients' perspective. Method: a mixed research design of concurrent triangulation was used; and structured surveys inquiring and in-depth interviews about psychotherapy termination were conducted. It was carried out at the quantitative level, both descriptive and regression analyses, and at the qualitative level, data reduction, constant comparison, and triangulation of information. A total of 137 patients from two higher education centers of psychological care in Antioquia (Colombia) participated, 100 answered a survey and the remaining participants were interviewed in-depth. Results: Results show three dimensions that allow various conceptualizations of therapy termination: achievement of goals, causal attribution and the person who decides to terminate. Most of the patients in the study dropped out of psychotherapy without the completion of their objectives or with a partial completion of these, due to external attributions and their own decision. Discussion: it was discussed how institutional, therapeutic, and life patient´s aspects have a significant role in termination of psychotherapeutic processes. As well as the importance of considering therapists´ training in relation to the characteristics of these processes and the different indicators associated with premature termination.

Timing social distancing to avert unmanageable COVID-19 hospital surges.

Following the April 16, 2020 release of the Opening Up America Again guidelines for relaxing coronavirus disease 2019 (COVID-19) social distancing policies, local leaders are concerned about future pandemic waves and lack robust strategies for tracking and suppressing transmission. Here, we present a strategy for triggering short-term shelter-in-place orders when hospital admissions surpass a threshold. We use stochastic optimization to derive triggers that ensure hospital surges will not exceed local capacity and lockdowns are as short as possible. For example, Austin, Texas-the fastest-growing large city in the United States-has adopted a COVID-19 response strategy based on this method. Assuming that the relaxation of social distancing increases the risk of infection sixfold, the optimal strategy will trigger a total of 135 d (90% prediction interval: 126 d to 141 d) of sheltering, allow schools to open in the fall, and result in an expected 2,929 deaths (90% prediction interval: 2,837 to 3,026) by September 2021, which is 29% of the annual mortality rate. In the months ahead, policy makers are likely to face difficult choices, and the extent of public restraint and cocooning of vulnerable populations may save or cost thousands of lives.