SARS-CoV-2 Serostatus and COVID-19 Illness Characteristics by Variant Time Period in Non-Hospitalized Children and Adolescents.

OBJECTIVE: To describe COVID-19 illness characteristics, risk factors, and SARS-CoV-2 serostatus by variant time period in a large community-based pediatric sample. DESIGN: Data were collected prospectively over four timepoints between October 2020 and November 2022 from a population-based cohort ages 5 to 19 years old. SETTING: State of Texas, USA. PARTICIPANTS: Participants ages 5 to 19 years were recruited from large pediatric healthcare systems, Federally Qualified Healthcare Centers, urban and rural clinical practices, health insurance providers, and a social media campaign. EXPOSURE: SARS-CoV-2 infection. MAIN OUTCOME(S) AND MEASURE(S): SARS-CoV-2 antibody status was assessed by the Roche Elecsys® Anti-SARS-CoV-2 Immunoassay for detection of antibodies to the SARS-CoV-2 nucleocapsid protein (Roche N-test). Self-reported antigen or PCR COVID-19 test results and symptom status were also collected. RESULTS: Over half (57.2%) of the sample (N = 3911) was antibody positive. Symptomatic infection increased over time from 47.09% during the pre-Delta variant time period, to 76.95% during Delta, to 84.73% during Omicron, and to 94.79% during the Omicron BA.2. Those who were not vaccinated were more likely (OR 1.71, 95% CI 1.47, 2.00) to be infected versus those fully vaccinated. CONCLUSIONS: Results show an increase in symptomatic COVID-19 infection among non-hospitalized children with each progressive variant over the past two years. Findings here support the public health guidance that eligible children should remain up to date with COVID-19 vaccinations.

Patients' Perspectives on Life and Recovery 1 Year After COVID-19 Hospitalization.

BACKGROUND: Many patients hospitalized for COVID-19 experience prolonged symptoms months after discharge. Little is known abou t patients' personal experiences recovering from COVID-19 in the United States (US), where medically underserved populations are at particular risk of adverse outcomes. OBJECTIVE: To explore patients' perspectives on the impact of COVID-19 hospitalization and barriers to and facilitators of recovery 1 year after hospital discharge in a predominantly Black American study population with high neighborhood-level socioeconomic disadvantage. DESIGN: Qualitative study utilizing individual, semi-structured interviews. PARTICIPANTS: Adult patients hospitalized for COVID-19 approximately 1 year after discharge home who were engaged in a COVID-19 longitudinal cohort study. APPROACH: The interview guide was developed and piloted by a multidisciplinary team. Interviews were audio-recorded and transcribed. Data were coded and organized into discrete themes using qualitative content analysis with constant comparison techniques. KEY RESULTS: Of 24 participants, 17 (71%) self-identified as Black, and 13 (54%) resided in neighborhoods with the most severe neighborhood-level socioeconomic disadvantage. One year after discharge, participants described persistent deficits in physical, cognitive, or psychological health that impacted their current lives. Repercussions included financial suffering and a loss of identity. Participants reported that clinicians often focused on physical health over cognitive and psychological health, an emphasis that posed a barrier to recovering holistically. Facilitators of recovery included robust financial or social support systems and personal agency in health maintenance. Spirituality and gratitude were common coping mechanisms. CONCLUSIONS: Persistent health deficits after COVID-19 resulted in downstream consequences in participants' lives. Though participants received adequate care to address physical needs, many described persistent unmet cognitive and psychological needs. A more comprehensive understanding of barriers and facilitators for COVID-19 recovery, contextualized by specific healthcare and socioeconomic needs related to socioeconomic disadvantage, is needed to better inform intervention delivery to patients that experience long-term sequelae of COVID-19 hospitalization.

Validating a Proteomic Signature of Severe COVID-19.

COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19. DESIGN: Prospective observational cohort study. SETTING: Two hospitals in the United States. PATIENTS: One hundred sixty-seven hospitalized adults with COVID-19. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: We measured 713 plasma proteins in 167 hospitalized patients with COVID-19 using a high-throughput platform. We classified patients as nonsevere versus severe COVID-19, defined as the need for high-flow nasal cannula, mechanical ventilation, extracorporeal membrane oxygenation, or death, at study entry and in 7-day intervals thereafter. We compared proteins measured at baseline between these two groups by logistic regression adjusting for age, sex, symptom duration, and comorbidities. We used lead proteins from dysregulated pathways as inputs for elastic net logistic regression to identify a parsimonious signature of severe disease and validated this signature in an external COVID-19 dataset. We tested whether the association between corticosteroid use and mortality varied by protein signature. One hundred ninety-four proteins were associated with severe COVID-19 at the time of hospital admission. Pathway analysis identified multiple pathways associated with inflammatory response and tissue repair programs. Elastic net logistic regression yielded a 14-protein signature that discriminated 90-day mortality in an external cohort with an area under the receiver-operator characteristic curve of 0.92 (95% CI, 0.88-0.95). Classifying patients based on the predicted risk from the signature identified a heterogeneous response to treatment with corticosteroids (p = 0.006). CONCLUSIONS: Inpatients with COVID-19 express heterogeneous patterns of plasma proteins. We propose a 14-protein signature of disease severity that may have value in developing precision medicine approaches for COVID-19 pneumonia.

Causal Bayesian machine learning to assess treatment effect heterogeneity by dexamethasone dose for patients with COVID-19 and severe hypoxemia.

The currently recommended dose of dexamethasone for patients with severe or critical COVID-19 is 6 mg per day (mg/d) regardless of patient features and variation. However, patients with severe or critical COVID-19 are heterogenous in many ways (e.g., age, weight, comorbidities, disease severity, and immune features). Thus, it is conceivable that a standardized dosing protocol may not be optimal. We assessed treatment effect heterogeneity in the COVID STEROID 2 trial, which compared 6 mg/d to 12 mg/d, using a causal inference framework with Bayesian Additive Regression Trees, a flexible modeling method that detects interactive effects and nonlinear relationships among multiple patient characteristics simultaneously. We found that 12 mg/d of dexamethasone, relative to 6 mg/d, was probably associated with better long-term outcomes (days alive without life support and mortality after 90 days) among the entire trial population (i.e., no signals of harm), and probably more beneficial among those without diabetes mellitus, that were older, were not using IL-6 inhibitors at baseline, weighed less, or had higher level respiratory support at baseline. This adds more evidence supporting the use of 12 mg/d in practice for most patients not receiving other immunosuppressants and that additional study of dosing could potentially optimize clinical outcomes.

Relevance of microRNAs in SARS-CoV-2 infection of primary human hepatocytes

Introduction Entry factors angiotensin converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) facilitate Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) entry into the host cells. Despite SARS-CoV-2s preference for respiratory system, extra-pulmonary organ involvement has been suggested. Recent studies report that SARS-CoV-2 leads to direct hepatic impairment in COVID-19 patients, necessitating further investigations about hepatic involvement. ACE2 and TMPRSS2 are expressed in primary human hepatocytes (PHH), suggesting a possible susceptibility to SARS-CoV-2. Despite this, data on infection and factors modulating functional regulation of SARS-CoV-2 infection in PHH are lacking. MicroRNAs (miRNAs) are approximately 22 nucleotide-long non-coding RNAs that have been shown to regulate various cellular processes including virus-host interactions. We aimed to study the susceptibility of PHH to SARS-CoV-2 and to evaluate the potential of miRNAs in modulating viral infection. Materials and methods We investigated the role of miRNAs to regulate SARS-CoV-2 infection in PHH in vitro. To strengthen our fndings, we analysed liver autopsies from COVID-19 patients. Results We demonstrate that PHH can be readily infected with SARS-CoV-2, resulting in robust replication and sustained host responses as indicated by the upregulation of several interferon-stimulated genes. In silico analyses unravelled miR-200c-3p, miR-429 and miR-141-3p as candidate miRNAs targeting ACE2 and, let-7c-5p targeting TMPRSS2. Expression of these miRNAs reduced SARS-CoV-2 infection in PHH. Furthermore, expression of several endogenous miRNAs was altered upon SARS-CoV-2 infection in PHH and human liver autopsies. Conclusion Our results show that PHH are susceptible towards SARS-CoV-2 and cellular miRNAs can diminish SARS-CoV-2 viral burden.

Optimal control of the coronavirus pandemic with both pharmaceutical and non-pharmaceutical interventions.

Coronaviruses are types of viruses that are widely spread in humans, birds, and other mammals, leading to hepatic, respiratory, neurologic, and enteric diseases. The disease is presently a pandemic with great medical, economical, and political impacts, and it is mostly spread through physical contact. To extinct the virus, keeping physical distance and taking vaccine are key. In this study, a dynamical transmission compartment model for coronavirus (COVID-19) is designed and rigorously analyzed using Routh-Hurwitz condition for the stability analysis. A global dynamics of mathematical formulation was investigated with the help of a constructed Lyapunov function. We further examined parameter sensitivities (local and global) to identify terms with greater impact or influence on the dynamics of the disease. Our approach is data driven to test the efficacy of the proposed model. The formulation was incorporated with available confirmed cases from January 22, 2020, to December 20, 2021, and parameterized using real-time series data that were collected on a daily basis for the first 705 days for fourteen countries, out of which the model was simulated using four selected countries: USA, Italy, South Africa, and Nigeria. A least square technique was adopted for the estimation of parameters. The simulated solutions of the model were analyzed using MAPLE-18 with Runge-Kutta-Felberg method (RKF45 solver). The model entrenched parameters analysis revealed that there are both disease-free and endemic equilibrium points. The solutions depicted that the free equilibrium point for COVID-19 is asymptotic locally stable, when the epidemiological reproduction number condition ( R 0 < 1 ) . The simulation results unveiled that the pandemic can be controlled if other control measures, such as face mask wearing in public areas and washing of hands, are combined with high level of compliance to physical distancing. Furthermore, an autonomous derivative equation for the five-dimensional deterministic was done with two control terms and constant rates for the pharmaceutical and non-pharmaceutical strategies. The Lagrangian and Hamilton were formulated to study the model optimal control existence, using Pontryagin's Maximum Principle describing the optimal control terms. The designed objective functional reduced the intervention costs and infections. We concluded that the COVID-19 curve can be flattened through strict compliance to both pharmaceutical and non-pharmaceutical strategies. The more the compliance level to physical distance and taking of vaccine, the earlier the curve is flattened and the earlier the economy will be bounce-back.

Antibody duration after infection from SARS-CoV-2 in the Texas Coronavirus Antibody Response Survey.

Understanding the duration of antibodies to the SARS-CoV-2 virus that causes COVID-19 is important to controlling the current pandemic. Participants from the Texas Coronavirus Antibody REsponse Survey (Texas CARES) with at least one nucleocapsid protein antibody test were selected for a longitudinal analysis of antibody duration. A linear mixed model was fit to data from participants (n= 4,553) with one to three antibody tests over 11 months (10/1/2020-9/16/2021), and models fit showed that expected antibody response after COVID-19 infection robustly increases for 100 days post-infection, and predicts individuals may remain antibody positive from natural infection beyond 500 days, depending on age, body mass index, smoking or vaping use, and disease severity (hospitalized or not; symptomatic or not).

Rebound Phenomenon after Nirmatrelvir/Ritonavir Treatment of Coronavirus Disease-2019 in High-Risk Persons.

In a cohort of 483 high-risk patients treated with nirmatrelvir/ritonavir for coronavirus disease-2019, two patients (0.4%) required hospitalization by day 30. Four patients (0.8%) experienced rebound of symptoms, which were generally mild, at median of 9 days after treatment, and all resolved without additional COVID-19-directed therapy.

Optimal control of the coronavirus pandemic with both pharmaceutical and non-pharmaceutical interventions

Coronaviruses are types of viruses that are widely spread in humans, birds, and other mammals, leading to hepatic, respiratory, neurologic, and enteric diseases. The disease is presently a pandemic with great medical, economical, and political impacts, and it is mostly spread through physical contact. To extinct the virus, keeping physical distance and taking vaccine are key. In this study, a dynamical transmission compartment model for coronavirus (COVID-19) is designed and rigorously analyzed using Routh–Hurwitz condition for the stability analysis. A global dynamics of mathematical formulation was investigated with the help of a constructed Lyapunov function. We further examined parameter sensitivities (local and global) to identify terms with greater impact or influence on the dynamics of the disease. Our approach is data driven to test the efficacy of the proposed model. The formulation was incorporated with available confirmed cases from January 22, 2020, to December 20, 2021, and parameterized using real-time series data that were collected on a daily basis for the first 705 days for fourteen countries, out of which the model was simulated using four selected countries: USA, Italy, South Africa, and Nigeria. A least square technique was adopted for the estimation of parameters. The simulated solutions of the model were analyzed using MAPLE-18 with Runge–Kutta–Felberg method (RKF45 solver). The model entrenched parameters analysis revealed that there are both disease-free and endemic equilibrium points. The solutions depicted that the free equilibrium point for COVID-19 is asymptotic locally stable, when the epidemiological reproduction number condition

Successful Third Kidney Transplantation in a Nigerian Kidney Transplant Center: A Case Report.

Patients with end-stage renal disease have limited options in the course of their management. Kidney transplantation (KT) remains the gold standard for the management of renal replacement therapy. There is increasing evidence supporting the viability of third and fourth KTs. Due to the complexities of carrying out a successful third KT and the scarcity of living organ donors, it is not a common procedure in Nigeria's few renal transplant centres. To date, there is no reported case of a successful third KT in Nigeria. Here, we present the first reported case of a third KT carried out in Nigeria on a 44-year-old hypertensive, hepatitis B-infected, non-diabetic male patient. He had the first living donor KT eight years ago, which he lost due to poor immunosuppressive medication adherence. He then had a second living donor, KT, four years ago. Both KTs were from altruistic donors and were performed in the same hospital outside Nigeria. He developed allograft nephropathy after receiving the AstraZeneca COVID-19 vaccine 16 months ago and lost the second graft as a result. He was worked up and transplanted at our centre. Third kidney transplantation can be performed successfully despite the challenges of human leukocyte antigen (HLA) sensitization, antibiotic resistance, and surgical placement of the graft.

Validating a Proteomic Signature of Severe COVID-19

OBJECTIVES: COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19. DESIGN: Prospective observational cohort study. SETTING: Two hospitals in the United States. PATIENTS: One hundred sixty-seven hospitalized adults with COVID-19. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: We measured 713 plasma proteins in 167 hospitalized patients with COVID-19 using a high-throughput platform. We classified patients as nonsevere versus severe COVID-19, defined as the need for high-flow nasal cannula, mechanical ventilation, extracorporeal membrane oxygenation, or death, at study entry and in 7-day intervals thereafter. We compared proteins measured at baseline between these two groups by logistic regression adjusting for age, sex, symptom duration, and comorbidities. We used lead proteins from dysregulated pathways as inputs for elastic net logistic regression to identify a parsimonious signature of severe disease and validated this signature in an external COVID-19 dataset. We tested whether the association between corticosteroid use and mortality varied by protein signature. One hundred ninety-four proteins were associated with severe COVID-19 at the time of hospital admission. Pathway analysis identified multiple pathways associated with inflammatory response and tissue repair programs. Elastic net logistic regression yielded a 14-protein signature that discriminated 90-day mortality in an external cohort with an area under the receiver-operator characteristic curve of 0.92 (95% CI, 0.88–0.95). Classifying patients based on the predicted risk from the signature identified a heterogeneous response to treatment with corticosteroids (p = 0.006). CONCLUSIONS: Inpatients with COVID-19 express heterogeneous patterns of plasma proteins. We propose a 14-protein signature of disease severity that may have value in developing precision medicine approaches for COVID-19 pneumonia.

Immune Modulation in Sepsis, ARDS, and Covid-19 - The Road Traveled and the Road Ahead

Leligdowicz et al. consider the history and future of immunomodulating therapies in sepsis and ARDS, including ARDS due to Covid-19, and remark on the larger challenge of clinical research on therapies for syndromes with profound clinical and biologic heterogeneity.

Methodology to estimate natural- and vaccine-induced antibodies to SARS-CoV-2 in a large geographic region.

Accurate estimates of natural and/or vaccine-induced antibodies to SARS-CoV-2 are difficult to obtain. Although model-based estimates of seroprevalence have been proposed, they require inputting unknown parameters including viral reproduction number, longevity of immune response, and other dynamic factors. In contrast to a model-based approach, the current study presents a data-driven detailed statistical procedure for estimating total seroprevalence (defined as antibodies from natural infection or from full vaccination) in a region using prospectively collected serological data and state-level vaccination data. Specifically, we conducted a longitudinal statewide serological survey with 88,605 participants 5 years or older with 3 prospective blood draws beginning September 30, 2020. Along with state vaccination data, as of October 31, 2021, the estimated percentage of those 5 years or older with naturally occurring antibodies to SARS-CoV-2 in Texas is 35.0% (95% CI = (33.1%, 36.9%)). This is 3× higher than, state-confirmed COVID-19 cases (11.83%) for all ages. The percentage with naturally occurring or vaccine-induced antibodies (total seroprevalence) is 77.42%. This methodology is integral to pandemic preparedness as accurate estimates of seroprevalence can inform policy-making decisions relevant to SARS-CoV-2.

Prevalence of SARS-CoV-2 in Pregnant Women Assessed by RT-PCR in Franconia, Germany: First Results of the SCENARIO Study (SARS-CoV-2 prEvalence in pregNAncy and at biRth In FrancOnia).

Purpose Detection of SARS-CoV-2-infected pregnant women admitted to maternity units during a pandemic is crucial. In addition to the fact that pregnancy is a risk factor for severe COVID-19 and that medical surveillance has to be adjusted in infected women and their offspring, knowledge about infection status can provide the opportunity to protect other patients and healthcare workers against virus transmission. The aim of this prospective observational study was to determine the prevalence of SARS-CoV-2 infection among pregnant women in the hospital setting. Material and Methods All eligible pregnant women admitted to the nine participating hospitals in Franconia, Germany, from 2 June 2020 to 24 January 2021 were included. COVID-19-related symptoms, secondary diseases and pregnancy abnormalities were documented. SARS-CoV-2 RNA was detected by RT-PCR from nasopharyngeal swabs. The prevalence of acute SARS-CoV-2 infection was estimated by correcting the positive rate using the Rogan-Gladen method. The risk of infection for healthcare workers during delivery was estimated using a risk calculator. Results Of 2414 recruited pregnant women, six were newly diagnosed RT-PCR positive for SARS-CoV-2, which yielded a prevalence of SARS-CoV-2 infection of 0.26% (95% CI, 0.10 - 0.57%). Combining active room ventilation and wearing FFP2 masks showed an estimated reduction of risk of infection for healthcare workers in the delivery room to < 1%. Conclusions The prevalence of newly diagnosed SARS-CoV-2 infection during pregnancy in this study is low. Nevertheless, a systematic screening in maternity units during pandemic situations is important to adjust hygienic and medical management. An adequate hygienic setting can minimise the calculated infection risk for medical healthcare workers during patients' labour.

Comparison of Persistent Symptoms Following SARS-CoV-2 Infection by Antibody Status in Nonhospitalized Children and Adolescents.

BACKGROUND: The prevalence of long-term symptoms of coronavirus disease 2019 (COVID-19) in nonhospitalized pediatric populations in the United States is not well described. The objective of this analysis was to examine the presence of persistent COVID symptoms in children by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody status. METHODS: Data were collected between October 2020 and May 2022 from the Texas Coronavirus Antibody REsponse Survey, a statewide prospective population-based survey among 5-90 years old. Serostatus was assessed by the Roche Elecsys Anti-SARS-CoV-2 Immunoassay for detection of antibodies to the SARS-CoV-2 nucleocapsid protein. Self-reported antigen/polymerase chain reaction COVID-19 test results and persistent COVID symptom status/type/duration were collected simultaneously. Risk ratios for persistent COVID symptoms were calculated versus adults and by age group, antibody status, symptom presence/severity, variant, body mass index and vaccine status. RESULTS: A total of 82 (4.5% of the total sample [n = 1813], 8.0% pre-Delta, 3.4% Delta and beyond) participants reported persistent COVID symptoms (n = 27 [1.5%] 4-12 weeks, n = 58 [3.3%] >12 weeks). Compared with adults, all pediatric age groups had a lower risk for persistent COVID symptoms regardless of length of symptoms reported. Additional increased risk for persistent COVID symptoms >12 weeks included severe symptoms with initial infection, not being vaccinated and having unhealthy weight (body mass index ≥85th percentile for age and sex). CONCLUSIONS: These findings highlight the existence of nonhospitalized youth who may also experience persistent COVID symptoms. Children and adolescents are less likely to experience persistent COVID symptoms than adults and more likely to be symptomatic, experience severe symptoms and have unhealthy weight compared with children/adolescents without persistent COVID symptoms.

The impact of Covid-19 pandemic on services for children and adolescents with ADHD: results from a survey of paediatricians in the United Kingdom.

Background: The Covid-19 pandemic has led to huge disruptions and multi-domain healthcare crisis, with additional impact on children and young people (CYP) affected by Attention Deficit and Hyperactivity Disorder (ADHD). Methods: We conducted an online survey and obtained responses from 62 Paediatricians who provide ADHD services for CYP about their experience of Service disruption and adaptations during the first Covid-19 lockdown in the United Kingdom between March and June 2020. The responses were both quantitative and qualitative. Results: The Paediatricians reported huge service disruptions such that almost half ceased the assessment of new patients with ADHD, and only 5% were able to offer physical monitoring for most patients. However, all respondents had adopted telemedicine, which allowed them to maintain high levels of non-physical service provision for existing patients. The Paediatricians used risk stratification strategies to determine which patients were more likely to benefit from the limited available face to face appointments for physical monitoring. The Paediatricians demonstrated clinical pragmatism to meet the needs of their patients such as starting medication without physical exam especially if the patient's behaviour was so challenging that it was presenting a crisis at home, and setting aside monthly limits for stimulant medications. Some respondents reported helpful cross-service collaborations to support CYP with ADHD and their families. Conclusion: The Covid-19 pandemic has had adverse effect on many CYP with ADHD and caused huge disruption to the ADHD services that support them. As the pandemic continues to cause disruptions to ADHD services, the service adaptations emerging from the literature including some of those identified in this study could be useful to support more stable and sustainable ADHD services, both during and after the pandemic.

Best practice guidance for digital contact tracing apps: A cross-disciplinary review of the literature

Background: Digital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are. Objective: This study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app. Methods: A collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing. Results: Ethical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app. Conclusions: In conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

State Effectiveness and Crises in East and Southeast Asia: The Case of COVID-19

East and Southeast Asian countries have recorded significant success in dealing with the COVID-19 pandemic. They have employed more effective crisis management strategies than countries in many other parts of the world. This article examines in detail the experiences of two of Asia’s pandemic success stories—South Korea and Vietnam—to identify the ways in which they responded to COVID-19 and how they related to state effectiveness. The lessons learned from the analysis of South Korean and Vietnamese crisis management include: the importance of preparedness and decisive action;the need for flexibility to cope with changing circumstances;that there are alternative crisis management strategies to reach the same desired outcomes;and that crisis management is best served by securing unity of purpose among government, citizens, civil society and the private sector. State effectiveness is a foundation for such features of successful crisis management.