Severe Acute Respiratory Syndrome Coronavirus 2 is the causative agent of Coronavirus Disease 2019 in humans. To date, little is known about the persistence of antibodies against SARS-CoV-2 in animals under natural conditions, in particular susceptible pets such as cat. This study reports the detection and monitoring of the humoral response against SARS-CoV-2 including the detection of immunoglobulins G specific for receptor binding domain of SARS-CoV-2 spike protein by an enzyme-linked immunosorbent assay and neutralizing antibodies by virus neutralization assay. Results showed that these antibodies last longer than 16 months in two naturally apparently healthy infected cats with the absence of clinicopathological findings during the follow-up. Moreover, re-infection is also possible with an important increase in virus neutralization test titers in both animals with no evident systemic signs found during each physical examination and with values of hematologic and biochemical parameters inside the normal reference intervals. Our results confirm a slow but progressive decrease of the kinetics and immunity of neutralizing antibodies in cats after the infection. Furthermore, similar to humans SARS-CoV-2 reinfection can stimulate an increase of the neutralizing antibodies determined by these two serological techniques in domestic cats. SARS-CoV-2 is a coronavirus and the causative agent of the new coronavirus disease 2019 (COVID-19) in humans. This zoonotic betacoronavirus is capable of infecting different animals, being the transmission of SARS-CoV-2 virus from human to domestic animals, the most common route in pets  detected by plaque reduction neutralization test (PRNT)   is considered the gold standard technique of humoral response against the virus  to detect the presence of seropositive pets.Antibodies to SARS-CoV-2 were determined by an indirect ELISA for the detection of IgG specific for RBD, described previously  was performed as described previously .Blood samples were collected from the jugular or cephalic veins into tube with anticoagulant (EDTA) for complete blood count (CBC) using an automatic haematological counter IDEXX Procyte Dx . In the case of biochemistry profile, blood samples were collected in a plain tube to obtain serum. Serum samples were analysed with an automatic veterinary chemistry analyser  to determine the following parameters: glucose, total protein concentrations, albumin, blood urea nitrogen, creatinine, calcium, inorganic phosphorus, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, gamma glutamyl transferase, total bilirubin, amylase, globulins, and serum amyloid A. These samples were stored at 4º C for a maximum of 12 h. Three aliquots from each serum sample were stored at -80 °C until testing. All the samples used in this study to detect the presence of anti-RBD by the in-house ELISA and VNT were thawed only once. Serum protein electrophoresis was also performed by agarose gel electrophoresis system . The electrophoretic curve was displayed and read with Gelscan . Laboratory parameters were considered altered when they were outside the reference intervals. Futhermore, the presence of antibodies against the feline coronavirus (FCoV) was tested by a rapid immunochromatographic test Both case 1 and case 2 were asymptomatic during the follow-up and after the SARS-CoV-2 reinfection. Moreover, none clinicopathological abnormalities were detected by CBC, biochemical profile and serum protein electrophoresis. A negative result was also obtained by the rapid test to detect the presence of antibodies against FCoV in both cases.The serological results are shown in Table The evaluation and study of the humoral immune response against SARS-CoV-2 virus based on detecting neutralizing antibodies is essential and of interest to understand immune-mediated mechanisms that might help to protect susceptible animals from SARS-CoV-2 reinfection. To the best of our knowledge, this is the first report that demonstrates that the SARS-CoV-2 reinfection in cats causes an increase of the neutralizing antibodies after the reinfection under natural conditions detected by two different serological methods including ELISA test and VNT in two healthy cats.Results of antibody longevity after 12 months detected in this study are in accordance with those reported in several longitudinal studies in humans (Yang et al. In human medicine, there is a controversial aspect about the anti-SARS-CoV-2 antibody level and the clinical status of the COVID-19 patients. Some studies detected a more rapid decrease in antibody levels in patients with mild symptoms or asymptomatic compared to patients with more severe clinical signs (Long et al. In veterinary, there is a lack of information about the antibody persistence except for one study published in Italy with the detection of SARS-CoV-2 neutralizing antibodies in pets up to 10 months since the first positive result using four different serological methods (Decaro et al. In addition, no previous information concerning the antibodies kinetics in animals regarding SARS-CoV-2 reinfection have been published. Our results showed that the level of antibodies decreased with time after infection, as detected by ELISA at different time points. In these cats, the presence of a new reinfection stimulated the antibody response detected by an increase in the production of neutralizing antibodies. In conclusion, our study demonstrates the persistence of neutralizing antibodies up 12 months after the first sampling in the cats evaluated. Moreover, SARS-CoV-2 reinfection promotes an increase of the immune response with an elevation of antibody titers detected by anti-RBD ELISA and VNT.


Statistical modeling is a crucial phase for decision-making and predicting future events. Data arising from engineering-related fields have most often complex structures whose failure rate possesses mixed state behaviors . For the data sets whose failure rates are in the mixed state, the utilization of the traditional probability models is not a suitable choice. Therefore, searching for more flexible probability models that are capable of adequately describing the mixed state failure data sets is an interesting research topic for researchers. In this paper, we propose and study a new statistical model to achieve the above goal. The proposed model is called a new beta power very flexible Weibull distribution and is capable of capturing five different patterns of the failure rate such as uni-modal, decreasing-increasing-decreasing, bathtub, decreasing, increasing-decreasing-increasing shapes. The estimators of the new beta power very flexible Weibull distribution are obtained using the maximum likelihood method. The evaluation of the estimators is assessed by conducting a simulation study. Finally, the usefulness and applicability of the new beta power very flexible Weibull distribution are shown by analyzing two engineering data sets. Using four information criteria, it is observed that the new beta power very flexible Weibull distribution is the best-suited model for dealing with failure times data sets. The selection and implementation of a suitable and appropriate probability model for capturing the mixed state behavior of real-life data are very crucial. The selection of an inappropriate probability model to use for analyzing data sets with complex nature often leads to poor and misguided results; see Klakattawi et al. Among the available probability distributions  the two-parameter Weibull model has attracted many researchers for data modeling in applied sectors. Due to its closed-form cumulative distribution function (CDF) and different monotonic hazard function (HF), the Weibull distribution is a very competent probability distribution. For analyzing the biomedical and reliability phenomena, most often the Weibull distribution is the first choice of many researchers to implement. For instance, (i) Liu et al. W be the Weibull distributed random variable with parameters Suppose α, some visual illustrations of For fixed •Increasing behavior, when •Constant behavior, when •Decreasing behavior, when From We can see that Among the existing modifications of the Weibull model, one of the interesting modified forms of the Weibull distribution is called the very flexible Weibull (VF-Weibull) distribution due to Ahmad and Hussain In this paper, we also introduce a new version of the Weibull distribution for modeling the reliability data sets possessing the mixed state HF. The proposed model is called a new beta power very flexible Weibull (NBPVF-Weibull) distribution. The NBPVF-Weibull is introduced by combining Eq. In Section 2W, are given byAssume We can see that for Using Eq. Corresponding to σ, some visual descriptions of For different values of σ are presented in The plots of 3Here, we proceed with two basic aims. First, it provides the derivation  of the maximum likelihood estimators (MLEs) 3.1n random samples observed from the PDF Assume β, respectively.By solving 3.2In this subsection, we provide a brief simulation study to evaluate the behaviors of the MLEs β. The selected parameter values are given by For the NBPVF-Weibull model, the simulation study is carried out for different sets of parameter values of •Bias•Mean square error (MSE)Two evaluation criteria are selected to see the performances of For the NBPVF-Weibull distribution, the simulation studies are conducted using the The values of evaluation criteria are also computed for n (size of the samples) increases, the•β tend to stable.MLEs of •Biases of •MSEs of From 4Here, we illustrate the applications of the NBPVF-Weibull to show its importance in engineering and other related sectors. To prove the superior performance of the NBPVF-Weibull distribution, we consider and analyze two engineering applications  related to the failure of secondary reactor pumps (Data 1) and failure times of electronic machines (Data 2).4.1The first engineering data set is about the failure time of the secondary reactor pumps occurs; see El-Desouky et al. Corresponding to the engineering applications, the values of certain key statistics are provided in 4.2•Weibull•F-Weibull•EF-Weibull•E-WeibullUsing the considered Data 1 and Data 2, we show the superior performances of the NBPVF-Weibull distribution by comparing its results with other selected rival probability distributions. The selected rival distributions are very competent and known probability models for modeling the engineering data sets. The CDFs of the selected rival models are4.3•Akaike information criterion (AIC)•Consistent AIC (CAIC)•Bayesian information criterion (BIC)•Hannan Quinn information criterion (HQIC)In this subsection, we consider certain selection criteria  to compare the NBPVF-Weibull distribution's fitting power with the above selected rival probability models. These information criteria are used to indicate the best-suited distribution for the engineering data sets discussed above. The numerical results of the information criteria are calculated using the formulas:k, n, and In the formulas of the above information criteria, the terms 4.4Here, we apply the NBPVF-Weibull and other rival probability distributions to the waiting time till the failure of secondary reactor pumps occurs. For this data set, the MLEs In addition to the numerical evaluation in 4.5Here, we show the second application of the NBPVF-Weibull distribution by considering the failure times of electronic machines (per 1000 h). Using Data 2, we compare the results  of the NBPVF-Weibull distribution with the above rival probability models. Corresponding to Data 2, the values of Besides the numerical comparison in 5In this paper, we studied a novel modified extension of the VF-Weibull distribution by incorporating the beta power transformation method. The proposed modification of the VF-Weibull distribution was called a new beta power very flexible Weibull distribution. The proposed NBPVF-Weibull distribution was able to capture four different shapes of its PDF such as bimodal, decreasing, uni-modal, and decreasing-increasing-decreasing functions. The NBPVF-Weibull distribution was also able to capture five different shapes of its HF such as uni-modal, decreasing-increasing-decreasing, bathtub, decreasing, and modified uni-modal  functions. The MLEs of the NBPVF-Weibull model were mathematically derived and their performances were evaluated through a simulation study. Furthermore, the uniqueness of the MLEs of the NBPVF-Weibull distribution was also shown visually. Finally, two engineering data sets related to the failure times were analyzed to show the superior fitting power of the NBPVF-Weibull distribution. Using certain information criteria, it was shown practically that the NBPVF-Weibull model is the best-suited choice for analyzing the failure times data sets.Faridoon Khan; Ahmad Zubair; Saima K. Khosa; Mohammed Ahmed Alomair; Abdullah Mohammed Alomair; Abdulaziz khalid Alsharidi: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.The authors declare no competing interests.


International Journal of Molecular Sciences on “Recent Advances in Biochemistry and Molecular Biology of Infectious Diseases”. Recent epidemic outbreaks of emerging, re-emerging, and neglected infectious diseases have demonstrated the importance of applying control and prevention measures. A glaring example is the current COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has challenged researchers to understand and control the disease, leading to the development of diagnostic tests and vaccines in a very short term. Although adaptive vaccines were developed with different antigens that showed high degrees of protection, the primary focus was on the immunity induced by the spike protein, even without fully understanding the pathogenesis. The SARS-CoV-2 spreads within epithelial cells of the mucosa in the upper and, possibly, lower respiratory tracts. While virus dissemination can be controlled by the host’s immune response, a potentially lethal mechanism can arise in the second phase of the infection, diffusing to pulmonary alveoli. Marked by an uncontrolled burst of cytokines/inflammatory factors , it can compromise respiratory function, and, as a consequence, lead to multi-organ failure. While mRNA-based vaccines represent the most innovative approach for prophylaxis against SARS-CoV-2-induced disease, the cumulated data indicate that the response to mRNA vaccines is ineffective in counteracting the viral replication in the upper respiratory tract, despite displaying efficacy in containing the development of severe disease. Considering that the antiviral immunity elicited by intramuscularly delivered mRNA vaccines is expected to show similar quantitative and qualitative features in the upper and lower respiratory tracts, differing outcomes are unexpected. Further investigations concluded that a possible inhibitory effect on alveolar macrophages, as a consequence of the diffusion of extracellular and/or cell-associated spike protein, can be envisioned as a key event counteracting the cytokine storm [This Editorial highlights the various observations made in the Special Issue of the p = 0.0015). In addition, EAT suppressed the expression of tumor necrosis factor-alpha (TNFα), a crucial proinflammatory cytokine. As a result, continuous EAT suppressed submucosal cell aggregation and reduced inflammatory cytokines. Thus, it has been suggested that EAT may contribute to the improvement in systemic inflammatory diseases through the suppression of IL-6 expression [The respiratory tract is the gateway for the SARS-CoV-2 virus, and the region called the epipharynx, located behind the nasal cavity, is responsible for upper respiratory tract immunity. It is also the site of frequent acute and chronic inflammation. Previous reports have suggested that chronic epipharyngitis is involved in local symptoms such as cough and postnasal drip that are associated with systemic inflammatory diseases such as IgA nephropathy and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and Long COVID. Epipharyngeal abrasive therapy (EAT), an effective treatment for chronic epipharyngitis in Japan, has been reported to be effective for these intractable diseases. The sedation of chronic epipharyngitis by EAT appears to induce the suppression of inflammatory cytokines and improve systemic symptoms, which is considered to be one of its potential mechanisms. Nishi et al. [p = 0.0208 and p = 0.0244, respectively). The results suggest that EAT treatment can down-regulate the expression of SARS-CoV-2 entry factors ACE2 and TMPRSS2. The authors concluded that EAT could be a potential preventative measure for COVID-19 [The epipharynx is a primary target for SARS-CoV-2 replication in the early stage of COVID-19 due to its high expression of the SARS-CoV-2 entry factors angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2). Nishi et al.  also evaCOVID-19 .Long COVID is the collective term used to denote the persistence of symptoms in those who have recovered from SARS-CoV-2 infection. The disease referred to as long COVID could be related to organ damage, post-viral syndrome, post-critical care syndrome, and others; thus, clinical evaluations should focus on identifying the pathophysiology followed by appropriate remedial measures. In a review by Figueres et al. , variousDiagnostic testing for SARS-CoV-2 is an essential component of the global strategy for preventing and controlling COVID-19. Since the beginning of the pandemic, numerous studies have evaluated the diagnostic sensitivity of different respiratory and oral specimens for SARS-CoV-2 detection. The pandemic has since been dominated by the emergence of new variants; the latest variant being spread since November 2021 is the Omicron variant, characterized by numerous mutations and changes in host tropism in vitro that might affect the diagnostic performance of tests depending on the sampling location. In a prospective study, Figueres et al.  highlighIn the same year, Kritikos et al.  suggesteLeishmania spp. homologous to receptors for activated C kinase (LACK) and phosphoenolpyruvate carboxykinase (PEPCK) protein, which are strong immunogens and candidates for use in the development of novel vaccine strategies. Because Leishmania spp. is an intracellular protozoan with several escape mechanisms, a vaccine must provoke cellular and humoral immune responses. The study focused on the potential for T immunity based on in silico predictions and the experimental characterization of antigenic epitopes that might interact with mice or human major histocompatibility complex class I. Following predictions for immunogenicity using the Immune Epitope Database (IEDB) and the Database of MHC Ligands and Peptide Motifs (SYFPEITHI), 26 peptides were selected for interaction assays with infected mouse lymphocytes by flow cytometry and ELISpot. This strategy identified nine antigenic peptides that were strong candidates for developing a peptide vaccine against leishmaniasis [In this issue, an article was also included that involves the development of methodologies for the determination of T epitopes of a protein from maniasis .Another interesting article searched for B-cell specific epitopes for diagnostic purposes using a peptide microarray methodology and describes a map of linear IgG epitopes in cholera toxin (CT) . EighteeA motivating manuscript was added, which developed a quantitative PCR (qPCR) to differentiate between infectious and inactive red sea bream iridovirus (RSIV). This qPCR assay was based on the use of propidium monoazide (PMAxx), a photoactive dye that can penetrate damaged viral particles and that binds to viral DNA. Bound viral DNA inhibits qPCR amplification, providing a mechanism to effectively differentiate infectious and inactive viruses. Furthermore, this non-invasive method will aid in establishing a disease prediction system and epidemiological analysis using seawater .This issue also includes a paper that compared the classical molecular method of mechanics energy minimization with that of quantum biochemistry. The study analyzed interactions in the structure of the co-crystallized protease NS2B-NS3 of the ZIKA virus with the inhibitors benzoic acid (5YOD) and benzimidazole-1-ylmethanol (5H4I). The quantum-level results identified essential residues for stabilizing the 5YOD and 5H4I complexes after classical energy minimization, which matched previously published experimental data. These results suggest that this approach could be more promising for the design of novel inhibitors acting on NS2B-NS3 that can be extended to other pathogens .Toxoplasma gondii is a widespread intracellular pathogen that infects humans and various animals. Huang et al. [T. gondii with a half-maximal effective concentration (EC50) of 0.22 μM. DHA significantly increases parasites’ ROS levels and decreases the mitochondrial membrane potential, which could be reversed by ferroptosis inhibitors (DFO). Moreover, the ferroptosis inducer RSL3 inhibits T. gondii with an EC50 of 0.75 µM that can also enhance the DHA-induced ROS level. In combination, DHA and RSL3 significantly increased the anti-Toxoplasma effect compared to DHA alone. In summary, the paper suggests that combining DHA and RSL3 may be an alternative treatment for toxoplasmosis [g et al. , studyinlasmosis .The study by Zhang et al.  focuses Leishmania sp. for use in vaccination and B-cell specific epitopes for the development of specific serological diagnostic tests; (5) comparison of methodologies in order to trial enzymatic inhibitors, and evaluation of drug repositioning for toxoplasmosis.Overall, this Special Issue is a potpourri of investigative efforts applying biochemistry and molecular biology approaches to infectious disease that have generated new perspectives. These have involved (1) the identification of key events to counteract the cytokine storm that occurs in SARS-CoV-2 infection through a possible inhibitory effect on alveolar macrophages; (2) the effectiveness of saliva-based RT-PCR for the early detection of the Omicron variant; (3) EAT as a potential COVID-19 preventative method; (4) development of a methodology for the molecular diagnosis of iridovirus, and identification of T epitopes for


Blended cognitive behavioral therapy (bCBT)—the combination of cognitive behavioral therapy and digital mental health applications—has been increasingly used to treat depression and anxiety disorders. As a resource-efficient treatment approach, bCBT appears promising for addressing the growing need for mental health care services, for example, as an early intervention before the chronification of symptoms. However, further research on the efficacy and feasibility of integrated bCBT interventions is needed.This study aimed to evaluate the efficacy of a novel bCBT program comprising short (25 min), weekly face-to-face therapy sessions combined with a smartphone-based digital health app for treating mild to moderate symptoms of depression or anxiety.This prospective uncontrolled trial comprised 2 measurement points (before and after treatment) and 2 intervention groups. We recruited university students with mild to moderate symptoms of depression or anxiety. On the basis of the primary symptoms, participants were assigned to either a depression intervention group (n=67 completers) or an anxiety intervention group (n=33 completers). Participants in each group received 6 weekly individual psychotherapy sessions via videoconference and completed modules tailored to their respective symptoms in the smartphone-based digital health app.d=−0.70 to −0.90; P<.001). The anxiety group experienced significant improvements in the symptoms of generalized anxiety assessed with the Generalized Anxiety Disorder-7 scale with a large effect size  but not in symptoms of anxiety assessed with the Beck Anxiety Inventory . In addition, both groups experienced significant improvements in their perceived self-efficacy  and quality of life related to psychological health . Work and social adjustment of patients improved significantly in the depression group  but not in the anxiety group . Patients’ mental health literacy improved in the anxiety group  but not in the depression group . Patient satisfaction with the bCBT program and ratings of the usability of the digital app were high in both treatment groups.The depression group displayed medium to large improvements in the symptoms of depression (Cohen This study provides preliminary evidence for the feasibility and efficacy of a novel brief bCBT intervention. The intervention effects were generalized across a broad spectrum of patient-reported outcomes. Hence, the newly developed bCBT intervention appears promising for treating mild to moderate depression and anxiety in young adults. Depression and anxiety disorders are widespread ,2. Both University students are particularly at risk for developing depression and anxiety disorders . SeveralIn up to 75% of the cases, both disorders start in mid-20 years of age . Early iCommonly recommended treatment options for depression and anxiety include psychotherapy and pharmacotherapy . RegardiPrevious studies support the efficacy and feasibility of bCBT programs for treating depression and anxiety -45. SomeFurther arguments for the use of bCBT can be found in the acceptability of bCBT treatments. Acceptance ratings by psychotherapists and patients have been found to be higher for bCBT than for stand-alone iCBT programs ,54. For elona therapy, for use in bCBT. This app was designed to overcome the limitations of iCBT and the existing bCBT programs. Previous bCBT interventions typically use face-to-face sessions and a smartphone-based digital health app as distinct therapeutic elements  and posttreatment [T1]) and 2 intervention groups (depression and anxiety). During the 6-week intervention, participants received weekly individual CBT sessions (25 min each) over the web via videoconference and used the depression or anxiety module of Ethics approval for this study was obtained from the Ethical Board of the University of Mannheim (EK Mannheim 27/2021).This study comprised 2 university student samples, one with mild to moderate symptoms of depression and one with mild to moderate symptoms of anxiety. A total of 107 participants were initially recruited in the study. Depending on their symptomatology, 71 participants were assigned to the depression group and 36 participants were assigned to the anxiety intervention group. Between the pre- and postintervention points, 3 participants dropped out from the depression sample and 3 participants dropped out from the anxiety sample. The data of 1 participant from the depression sample were lost because of a technical problem. In the depression sample, 67 participants  completed the study by taking part in both assessment points. In the anxiety sample, 33 participants  completed the study by taking part in both assessment points. d=0.80), a high power to detect a medium (98.09% for Cohen d=0.50), and a small power to detect a small (36.46% for Cohen d=0.20) within-group effect in the depression group. Similarly, post hoc power analyses (α=.05) showed that the study had a high power to detect a large (99.37% for Cohen d=0.8), a moderate power to detect a medium (79.54% for Cohen d=0.5), and a small power to detect a small (20% for Cohen d=0.2) within-group effect in the anxiety group.Post hoc power analyses (Cronbach α=.05) showed that the study had a high power to detect a large , participants completed a web-based survey consisting of the Patient Health Questionnaire-9 (PHQ-9) ,62, the elona therapy app, and (4) having a smartphone with iOS or Android operating systems and an internet connection. The exclusion criteria used in the study were as follows: (1) acute suicidality (a score of 2 or 3 on the item 9 of the PHQ-9), (2) current or prior International Classification of Diseases, 10th Revision (ICD-10) bipolar disorder, (3) current or prior ICD-10 borderline personality disorder, (4) current or prior ICD-10 psychotic disorder, (5) symptoms of posttraumatic stress disorder or dissociative experiences, (6) current or prior self-harm (addressed only in the screening with a therapist), (7) current or prior ICD-10 alcohol or substance dependency (except nicotine), and (8) psychotherapeutic or psychopharmacological treatment in the previous year.The inclusion criteria used in the study were as follows: (1) mild to moderate symptoms of depression or anxiety , (2)The second step, the screening process, comprised a video-based interview with a clinical psychologist currently in advanced postgraduate psychotherapeutic training (interview duration: approximately 25 min). The 2-step inclusion process was used to cross-validate self-report responses with clinical assessments and to assess sensitive inclusion criteria  thoroughly and empathically. In the screening interview, inclusion and exclusion criteria were revisited by psychologists, and participants with nonelevated or severe symptoms of depression or anxiety using ICD-10 criteria and those presenting suicidality or other exclusion criteria were excluded. Those with severe symptom levels were advised to consult appropriate health care services and were provided with contact information of emergency services. Participants meeting all the inclusion criteria and none of the exclusion criteria after the second screening step were recruited to the study and assigned to either the depression or the anxiety intervention group, depending on their respective symptomatology. For persons who displayed both elevated symptoms of depression and anxiety, assignment to the depression or anxiety group was jointly decided by the participant and interviewing clinical psychologist (shared decision-making). All interviewing clinical psychologists received interview training from an experienced licensed psychotherapist before the study and supervision throughout the recruitment phase.The participants received bCBT for depression or anxiety over 6 weeks. The weekly 25-minute video-based individual CBT sessions comprised psychoeducation, internet-based therapeutic exercises , and joint reflections on those tasks. elona therapy on their smartphones. elona therapy provides patients with relevant interventions, helpful activities, exercises, and psychoeducational resources related to their respective symptoms. The app content can be individualized according to the patient’s needs, for example, based on their diagnosis, therapy progress, and joint therapeutic decisions. elona therapy has been developed based on current treatment recommendations and evidence-based CBT interventions [elona therapy provides a 2-sided interface for patients (smartphone app) and psychotherapists (web application). Through the web application, psychotherapists can track individual progress, adapt resources and interventions displayed in the patient’s app, and assign tasks based on the content of the face-to-face CBT sessions. Psychotherapists can choose from over 400 available content pieces. Through the smartphone app, patients can access psychoeducational content , complete interactive homework tasks, record their mood in a diary format, write notes or questions relevant to their therapy sessions, and plan or schedule new activities. In addition, participants can create their personal toolkit of preferred content and tasks within the app. Although the intervention program for this study was manualized to some degree, the participating therapists were encouraged to further individualize the digital content in the elona therapy app appropriate for the patient’s needs. Patients were encouraged to use the app approximately 25 minutes per week, mirroring a session duration. elona therapy app for patients with symptoms of depression or anxiety. The participating clinical psychologists received training on the use and functions of elona therapy by a senior licensed psychotherapist before the study.To improve their progress between the weekly sessions, patients engaged in additional between-session homework using ventions -69. The This study comprised a broad set of outcome measures, covering symptoms of depression and anxiety, perceived functioning, well-being, satisfaction with the treatment program, and competencies -75. We aThe symptoms of depression were the primary outcome for the depression group and a secondary outcome for the anxiety group. We assessed the symptoms of depression with 2 well-established self-report instruments: the PHQ-9 ,62 and tThe symptoms of anxiety were the primary outcome for the anxiety group and a secondary outcome for the depression group. We assessed the symptoms of anxiety with 2 well-established self-report instruments: the GAD-7 ,64 and tQuality of life was assessed with the WHOQOL-BREF scale ,86. ThisPatients’ adjustment to work and social life was assessed with the Work and Social Adjustment Scale (WSAS) ,89. Thisstrongly disagree to 4 strongly agree. Previous work demonstrated the reliability and validity of the GSE [We assessed the participants’ perceived self-efficacy with the General Perceived Self-Efficacy Scale (GSE) . This sc the GSE ,92. The We assessed mental health literacy  with a 20-item version of the Mental Health Literacy Scale (MHLS) ,94. The We assessed patient satisfaction with their treatment at T1 using the German version of the Client Satisfaction Questionnaire (CSQ-8) ,96. The elona therapy app was assessed with the German version of the System Usability Scale (SUS) [The usability of the le (SUS) ,99. The le (SUS) ,101. TheParticipating therapists were instructed to report in case their patients experienced any serious adverse events. Serious adverse events include negative events that are harmful or threatening beyond transient distress and are life-threatening or require hospitalization. Self-harm, suicidal ideation, or attempts are potentially serious adverse events.t tests. Statistical analyses were conducted based on completers, including only participants who have completed at least 1 questionnaire after treatment. In addition, we evaluated our measurement instruments’ reliability (Cronbach α), and we computed the pre-post effect sizes (Cohen d) for each outcome. For the depression group, we treated the depression measures (PHQ-9 and BDI-II) as primary outcomes and all other measures as secondary outcomes. For the anxiety group, we treated the anxiety measures (BAI and GAD-7) as primary outcomes and all other measures as secondary outcomes.We evaluated the changes from before to after the treatment using 2-tailed paired sample elona therapy app during the intervention period. Participants in the anxiety group completed on average 24.1 tasks and spent 106.9 minutes using the elona therapy app during the intervention period. The mean number of completed face-to-face sessions in the depression group was 5.64 , and the mean number of completed face-to-face sessions in the anxiety group was 5.55 . Patient engagement with elona therapy was high; only 1 patient in the depression group was a minimal user, which is defined as using elona therapy for <15 minutes for the entire study period, with only 7 minutes of total use time.On average, participants in the depression sample completed 21.6 tasks and spent a total of 88.12 minutes using the t tests, and the corresponding effect sizes (Cohen d) for the depression group. Regarding symptoms of depression (primary outcome), we observed significant improvements in the PHQ-9 score  and the BDI-II score . Regarding the secondary outcomes, the symptoms of anxiety assessed with the GAD-7  and BAI  and maladjustment assessed with the WSAS  significantly decreased. In addition, perceived self-efficacy assessed with the GSE  and quality of life assessed with the WHOQOL-BREF  significantly improved. One secondary outcome, mental health literacy in the MHLS, did not significantly improve during the intervention period . At the postintervention point, participants rated the usability of the smartphone-based digital health app for treating depression as high . Partict tests, and the corresponding effect sizes (Cohen d) for the anxiety group. Regarding symptoms of anxiety (primary outcome), we observed significant improvements in the GAD-7 score  but not in the BAI score . Regarding the secondary outcomes, the symptoms of depression assessed with the PHQ-9  and the BDI-II  significantly decreased. In addition, perceived self-efficacy , mental health literacy , overall quality of life and general health , and psychological health  assessed with the WHOQOL-BREF significantly improved. Maladjustment assessed with the WSAS , physical health , quality of life related to social relationships , and quality of life related to one’s environment  assessed with the WHOQOL-BREF did not significantly improve in the intervention period. At the postintervention point, participants rated the usability of the smartphone-based digital health app for treating symptoms of anxiety as high . Particelona therapy app. The intervention evaluated in this study produced within-group effect sizes that were considerably larger than those observed in waitlist control groups over similar periods [This study investigated the efficacy and feasibility of a 6-week bCBT program for mild to moderate depression or anxiety in university students. Overall, participants showed improvements in their primary symptoms, which generalized to other symptom domains, quality of life, and self-efficacy. In addition, participants reported high satisfaction with the intervention program and the  periods ,103 suggd=0.87) and anxiety (Cohen d=0.88), as observed in our study [In addition, a previous meta-analysis on the effectiveness of standard evidence-based psychological treatments in practices revealed similarly large pre-post treatment effect sizes for depression . The GAD-7 primarily assesses symptoms of generalized (cognitive) anxiety, whereas the BAI comprises various items capturing physical symptoms of anxiety . Our intervention’s focus on the cognitive aspects of anxiety and psychoeducation rather than in vivo exposure therapy may explain this finding.Regarding within-group differences between intervention outcomes, we observed larger effects for the symptoms of depression or anxiety than for secondary outcomes such as work and social adjustment or self-efficacy. This pattern of findings is in line with a previous meta-analysis  and may elona therapy app  with mild to moderate symptoms. The findings may have limited generalizability to populations with different characteristics and to other student samples in different cultures or different regions of Germany. Fifth, we only used patient-reported outcomes in this study. The use of only self-report may provide a limited depiction of patients’ situations owing to patients’ possible inaccurate evaluation of their situation or response biases such as social desirability bias. Further work can complement some of the outcome measures  by a clinical rating scale such as therapist rating questionnaires.As this study was planned as an uncontrolled trial, several limitations point toward future research directions. First, this study comprised only 2 measurement points (before and after the assessment). Future research with more measurement points is needed to establish the ideal duration of the evaluated bCBT intervention . Further work should also test the stability of the obtained improvements through follow-up assessments. Second, as a feasibility study focusing on within-group improvements, this study did not include control groups. Thus, future research using appropriate active  or passive  groups is needed. In addition, dismantling studies could be useful for evaluating the effects of different elements of the This trial used only a quantitative study design, which may inform researchers only limitedly about the investigated program. To explore patients’ in-depth experiences with this novel bCBT program, an additional qualitative study was needed. As a follow-up to this trial, we invited all participants who had completed the last face-to-face session with their therapist to participate in a follow-up interview conducted by an interviewer who was not involved in the therapeutic process. The results of this qualitative investigation were published in a separate article .Further work is needed to assess the efficacy and feasibility of the evaluated bCBT program in other groups and individuals with more severe symptomatology.In summary, this feasibility study provided preliminary evidence based on an uncontrolled pre-post trial design for the efficacy of a novel bCBT program for treating mild to moderate depression and anxiety. Promisingly, substantial symptom improvements were generalized across various outcomes and were accompanied by high patient satisfaction and adherence. Future research is needed to evaluate the efficacy of the evaluated program in different populations and over longer time intervals.


Most of the participants were female (72.32%), and aged from 26 to 66 years old . Linear regressions weighted by inverse probability weighting using the propensity score showed that, after follow-up of 5 years, the intervention group demonstrated significantly greater increases in all items and total scores for the PEI-2 , greater decreases in the DASS depression score (B = −1.98 p = 0.001), and greater increases in the Mental Component Summary score of the SF-12v2  than the comparison group. The HEP may be an effective intervention enabling adults from low-income families to manage their health-related issues and improve their mental health, as evidenced by our study.Health empowerment can be an effective way to reduce health inequities. This prospective cohort study evaluated the 5 year impact of a health empowerment program (HEP) on health outcomes among adults from low-income families. The Patient Enablement Instrument version 2 (PEI-2), Depression, Anxiety and Stress Scale 21 (DASS-21), and 12 item Short-Form Health Survey version 2 (SF-12v2) were administered at baseline and follow-up for both intervention and comparison groups. A total of 289 participants ( Poverty is a global problem linked to poor health outcomes . In addiPrimary healthcare plays a key role in improving public health and reducing health inequities ,9. StartThere is a growing body of literature on the benefits of health empowerment (HE) interventions. First, HE helps improve health-related abilities, such as health literacy  and utilThe HE interventions reported in the literature tend to be highly controlled, unidimensional strategies delivered exclusively to either parents or children in low-income families using short-term outcomes ,27,28,34Hong Kong has undergone rapid economic development since the late 20th century, becoming a high-income region . HoweverIn 2012, the Trekkers Family Enhancement Scheme (TFES) was initiated by a local philanthropic group, the Kerry Group Kuok Foundation (Hong Kong) Limited (KGKF). The TFES offer supports related to health, education, employment, and environmental harmony to 200 low-income families in Tung Chung. A health empowerment program (HEP) with intercalated annual health assessments, health literacy and self-care enablement courses, and health ambassador training was delivered regularly to support the health of the TFES families. This study aimed to evaluate the 5 year effectiveness of the HEP for the health of low-income families. We examined whether the HEP was associated with greater health enablement, better mental health, and higher health-related quality of life over a 5 year follow-up.The present study was a prospective, comparative cohort study. It involved two groups of low-income families with young children studying in grades 1–3 (aged 7 to 11). All TFES families were invited to enroll in the HEP (herein referred to as “intervention families”), and low-income families who had not participated in the TFES were also recruited in Tung Chung and Kwai Chung as the comparison group. Kwai Chung is also a developing satellite residential district with similar sociodemographics and public healthcare facilities as Tung Chung . Familien = 191 for the intervention group, n = 178 for the comparison group), and 357 adults  provided consent and completed the baseline assessment. There were 68 participants who did not complete the follow-up assessment at 5 years, representing a drop-out rate of 19% . Overall, 78% of participants  completed the follow-up assessment. These participants were included in the analysis. The mean and median durations of these participants’ follow-ups were both five years. Most of participants were females (72.32%), and their averaged age was 41.63 years old (SD = 6.91). The subject recruitment and follow-up flowchart is presented in There were 369 adults in total invited from July 2012 to September 2015 , which has been found to be valid and reliable among the local Chinese people . It inclThe secondary outcomes included negative emotional states and health-related quality of life (HRQOL). We used the Chinese version of the Depression, Anxiety and Stress Scale 21 (DASS-21) to capture participants’ negative emotional states. This measure has shown good reliability in the Chinese setting . DASS-21We utilized the Chinese 12 item Short-Form Health Survey Version 2 (SF-12v2) to measure HRQOL. The Chinese SF-12v2 has shown good validity and reliability among Chinese populations ,49. The Socioeconomic status, general state of health, and physician factors were found to be associated with patient enablement . Given tThe Chinese PEI-2, DASS-21, SF-12v2, and the covariates questionnaire were administered by a trained interviewer in person or by telephone. All outcome and covariate data were self-reported.p values lower than 0.05 indicating statistical significance.Data analyses were based on the complete-case analysis and only participants without missing values were included. We used STATA version 16.0  to conduct all the statistical analyses. The presented tests of significance were two-tailed, with p value, with p > 0.05 indicating an optimal balance between two groups.Descriptive statistics were used to present participants’ baseline characteristics. Inverse probability weighting based on propensity scores was used to account for residual confounding bias and minimize differences in the characteristics of the two groups. We first used a logistic regression model to calculate each participant’s propensity score, with adjustment for the aforementioned baseline covariates. The balance of baseline covariates between the two groups before and after the inverse probability weighting was assessed according to the 2R and F-test of overall significance are reported; the unstandardized coefficients (B), 95% confidence level, and p-value are reported to indicate the effects of the intervention on each dependent outcome variable; furthermore, a power analysis for a two-sample means test was applied to calculate the post hoc power. To assess the robustness of the results, we conducted a sensitivity analysis of the multiple linear regressions, adjusting for baseline covariates, without inverse probability weighting.Cronbach’s α coefficient was measured to test the reliability for internal consistency for each measure, with values larger than 0.7 representing good reliability. Linear regressions weighted by inverse probability weighting using propensity scores were applied to identify the independent effects of the HEP on the participants’ changes in PEI-2, DASS-21, and SF-12v2 scores from baseline to the 5 year follow-up. We first conducted preliminary tests to check the assumptions of the multiple linear regression . We checked that there were no cases of outliers . AlthouThe current study received ethical approval (UW 12–517) from the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster.The measures showed good reliability with the data from the current study, including the PEI-2 (Cronbach’s α = 0.90), DASS-21 , and SF-12v2 . The PEI-2, DASS-21, and SF-12v2 scores at the baseline and follow-up assessments before and after weighting are presented in p < 0.001). Additionally, the HEP was significantly associated with a greater decrease in the DASS depression score . Nevertheless, the differences in the changes in the DASS anxiety and stress scores between the two groups were not significant. There was a positive association between the HEP and increases in MCS scores , but there was no difference in the changes in PCS scores between groups. The results consistently showed significantly greater increases in all the items and the total score for the PEI-2 in the HEP group than in the comparison group in the sensitivity analysis using multiple linear regression to adjust for baseline covariates  and mental HRQOL (SF-12v2 MCS score) and greater decreases in depressive symptoms (DASS depression score) than those without involvement in the HEP intervention.Previous studies have demonstrated the effectiveness of various HEPs in improving participants’ health-related outcomes, but most of them were short-term studies lasting for only a few months with follow ups of less than one year . In partThe findings of the present study complement those of previous studies in affirming the long-term effectiveness of HEPs in improving participants’ self-care enablement and mental health. One explanation regarding the mechanism of how HEPs increase enablement and mental health is that regular health assessments engage participants and raise their health awareness ; the heaAdditionally, previous studies have indicated that HEPs can stimulate the adoption of healthy habits. For example, a Korean study showed that utilizing 8 week lifestyle improvement education, group discussions, and exercise training enabled 27 hypertensive older adults to increase physical activity and reduce sedentary behavior . In contThe comparison between the current HEP and other HE interventions involving low-income families ,29,30,31The findings of the current intervention contribute to the current health empowerment literature in three key ways. First, health empowerment among low-income families is feasible and has sustainable effectiveness. Second, both adults and children should be involved in the regular health assessment and self-care enablement activities in light of the close links among family members’ health and the mutual influence on health-seeking behavior. Third, multi-dimensional but intercalated components can be utilized to enhance not only health promotion knowledge and practice but also accessible professional support to solve health problems. The various components provided insights into the design of future complex health interventions in real-world settings.There are four potential limitations worthy of further discussion. First, participants in the HEP were those who volunteered to join and may therefore have had a prior interest in receiving health information and resources. Additionally, the intervention was limited to people who were currently residing in one district in Hong Kong, so the sample cannot be viewed as representative. Non-randomization and district limitations may affect the generalizability of the findings and their external validity. Second, since it was not a randomized control trial, the observed and unobserved confounding variables could not be fully accounted for in the analysis. However, our main analysis adjusted for residual confounding by applying inverse probability weighting based on propensity score. Third, we used face-to-face or telephone interviews to collect data. Furthermore, data regarding the variables of interest were based on participants’ self-reports. The different data collection methods and the self-reported data could have had the potential to cause measurement errors, but this was equally applicable to both the intervention and comparison groups. Finally, the long recruitment period and the loss of participants during follow up could have led to bias in the results. Nevertheless, the drop-out rates in this cohort study in both groups were lower than the upper limit of the acceptable rate  , which sThis study shows the effectiveness of a longitudinal HEP in enabling self-care and improving mental health among adults from low-income families. It offers insights into the feasibility and applicability of HEPs in real-world community settings. Given the increasingly wide income inequality and the close link between poverty and poor health, similar HEPs may help to break the vicious cycle. This opens a new research agenda regarding how HEP care models can be more widely implemented to enhance health equity.


Opioid overdose fatalities are preventable with timely administration of naloxone, an opioid antagonist, during an opioid overdose event. Syringe service programs have pioneered naloxone distribution for potential bystanders of opioid overdose. The objective of this study was to pilot test a multi-component implementation strategy—the systems analysis and improvement approach for naloxone —with the goal of improving naloxone distribution by syringe service programs.Two syringe service programs participated in a 6-month pilot of SAIA-Naloxone, which included (1) analyzing program data to identify gaps in the naloxone delivery cascade, (2) flow mapping to identify causes of attrition and brainstorm programmatic changes for improvement, and (3) conducting continuous quality improvement to test and assess whether modifications improve the cascade. We conducted an interrupted time series analysis using 52 weeks of data before and 26 weeks of data after initiating SAIA-Naloxone. Poisson regression was used to evaluate the association between SAIA-Naloxone and the weekly number of participants receiving naloxone and number of naloxone doses distributed.Over the course of the study, 11,107 doses of naloxone were distributed to 6,071 participants. Through SAIA-Naloxone, syringe service programs prioritized testing programmatic modifications to improve data collection procedures, proactively screen and identify naloxone-naïve participants, streamline naloxone refill systems, and allow for secondary naloxone distribution. SAIA-Naloxone was associated with statistically significant increases in the average number of people receiving naloxone per week  and average number of naloxone doses distributed per week  beyond the underlying pre-SAIA-Naloxone levels. These initial increases were extended by ongoing positive changes over time .SAIA-Naloxone has strong potential for improving naloxone distribution from syringe service programs. These findings are encouraging in the face of the worsening opioid overdose crisis in the United States and support testing SAIA-Naloxone in a large-scale randomized trial within syringe service programs. Contributions to the literatureSAIA-Naloxone was an acceptable and feasible implementation strategy to optimize community-based naloxone distribution within two syringe services programs that participated for 6 months.SAIA-Naloxone provided opportunities for syringe service program staff to use data to inform decision-making and programmatic modifications that improve access to naloxone among its participants.SAIA-Naloxone improved access to naloxone, thereby increasing chances that people who use drugs can reverse overdoses.SAIA-Naloxone might be an effective strategy to address disparities in naloxone distribution.An estimated 2.2 million people in the United States (US) have an opioid use disorder, and less than 20% of them are currently receiving treatment , 2. In aOpioid-related overdose deaths are preventable with naloxone, a medication that displaces opioids from the brain receptors to which they attach, reversing the opioid-induced respiratory depression that leads to a fatal overdose . A prescSyringe services programs (SSPs), which provide access to and disposal of sterile syringes and injection equipment for people who use drugs, are ideal venues for naloxone distribution as they reach people who are at high risk of observing or experiencing opioid overdose and have staff who are culturally competent in providing services for people who use opioids . While SAs a multi-component implementation strategy, the systems analysis and improvement approach (SAIA) has the potential to improve SSP-based naloxone distribution by centering analysis of service gaps, mapping service flow, and continuous quality improvement. The original SAIA trial focused on the prevention of mother-to-child HIV transmission cascade, where antiretroviral therapy coverage increased threefold and screening for HIV-exposed infants increased 17-fold . AdditioAt the individual-level, naloxone is an effective opioid antagonist that can prevent opioid overdose mortality when administered quickly and appropriately during an opioid overdose event , 21. EffThe naloxone delivery cascade refers to a series of linked, sequential steps considered necessary for naloxone programs to fully realize the life-saving benefits of the intervention at the population-level. These steps include screening individuals who present for syringe services for naloxone engagement, training potential bystanders who have not been previously engaged on how to reverse an overdose with naloxone, equipping trained bystanders with naloxone to use during observed overdoses, and refilling their supply of naloxone as needed. If followed, these steps could maximize the effectiveness of naloxone by ensuring bystanders have immediate access to naloxone and can administer it when needed.Our study included two SSPs with ongoing naloxone distribution in California. SSPs provide access to and disposal of syringes and injection equipment for PWID and offer a range of other prevention services . They arTwo SSPs with naloxone programs located in large urban centers in California were enrolled. The first SSP (Site 1) was a standalone non-profit organization that began distributing syringes in 1993 and naloxone in 2000. In 2020, site 1 had 8 full time staff, 3 part time staff and 4 volunteers. The organization had an annual budget of $876,869, with funding from their county health department, private foundations, and other community-based organizations. In 2019 and 2020, they served approximately 3,000 participants annually. In addition to providing syringes and naloxone, this SSP provides on-site HIV and HCV counseling and testing; fentanyl test strips; nutritional support; abscess and wound care; individual risk reduction counseling and linkage to substance use treatment.The second SSP (Site 2) was part of a county health department that began distributing syringes in 1994 and naloxone in 2017. In 2020, site 2 had 3 full time staff and 2 part time staff. The organization had an annual budget of $319,518 with funding from the county and state health departments. SSP services are provided across the county five days a week at five pop-up sites by county employees. Across 2019 and 2020, they served approximately 700 participants annually. In addition to providing syringes and naloxone, this SSP provides on-site STD, HIV, and HCV testing; fentanyl test strips; and referrals to mental health, and substance use treatment.n = 6 at Site 1; n = 5 at Site 2) to orient them to SAIA and, using principles of focus group discussions, elicit ways in which it should be adapted. Key adaptations for SAIA-Naloxone that resulted from these meetings involved modifying data collection instruments, primarily to reduce data collection burden and align data elements with the Naloxone Cascade Analysis Tool (NCAT) [For this study, we adapted the original SAIA implementation strategy for naloxone delivery within SSPs  by directly engaging staff at the two SSPs that were participating in the 6-month pilot study , 23, 24.l (NCAT) . NCAT inl (NCAT) .Like the original SAIA, SAIA-Naloxone included  analyzinOur primary outcomes included the weekly number of people receiving naloxone and the weekly number of naloxone doses distributed. Improvements in these outcomes signal improvements along the naloxone delivery cascade and reflect improvements in effective naloxone coverage among SSP participants. Further, we focus on these two outcomes as prior research has demonstrated that these metrics significantly predict opioid overdose mortality rates at the community-level , 29. SSPWe marked each SSP’s SAIA-Naloxone start date as the week following our first meeting with the organization’s implementation team to complete actions 1 through 3 of Table To assess the association between SAIA-Naloxone and access to naloxone among communities served by the SSPs, we conducted an interrupted time-series analysis . We util1) provides the pre-SAIA-Naloxone trend for the outcome. For this analysis, this covers the 52-week period prior to the first SAIA-Naloxone meeting the SSP provider. A significant coefficient on the intervention indicator (β2) would indicate a one-time change in the outcome beyond the pre-period trend due to SAIA-Naloxone. A significant coefficient on the interaction between the intervention and time (β3) would indicate a shift in the outcome trend in the post-period from the pre-period due to initiating SAIA-Naloxone. The models were adjusted for SSP participant volume as a continuous variable and season as a 4-level categorical variable (X). We report 2-sided p-values and considered p < 0.05 the cut-off for statistical significance. Statistical analyses were performed using Stata 16.0 .The coefficient on the time indicator  during the implementation period, suggesting that SAIA-Naloxone was acceptable and feasible as an implementation strategy. In addition, the introduction of SAIA-Naloxone at SSPs was associated with statistically significant increases in the number of participants receiving naloxone each week and the number of naloxone doses distributed each week. Further, SAIA-Naloxone was associated with significant increases in the trend of these outcomes, with more participants receiving naloxone and more doses distributed each week. Based on these findings, SAIA-Naloxone has strong potential to optimize the naloxone delivery cascade for SSP participants and prevent opioid-involved overdose deaths.Prior studies have demonstrated that Black and Latinx PWID were 25% and 47% less likely, respectively, to receive naloxone compared to white PWID . As partBeyond these outcomes, it is possible that SAIA-Naloxone improved aspects of the internal environment of the SSPs. For example, external facilitators engaged the full implementation team which could have shifted power dynamics and allowed front-line staff the opportunity to express their ideas about what is contributing to drop-offs in the naloxone delivery cascade and potential ways to improve them. This could provide an opportunity for innovative, prioritized approaches to emerge from any of the staff members, not just SSP leadership, potentially contributing to a strengthened culture within the organization. Further, leveraging data to engage in continuous quality improvement through multiple cycles of SAIA-Naloxone could foster a learning mindset among SSP staff and might improve the implementation climate for naloxone. Future research should evaluate the impact of SAIA-Naloxone on key implementation determinants like organizational culture and implementation climate and the extent to which they operate as mechanisms through which SAIA-Naloxone improves access to naloxone.It is important to consider the findings of this study in light of the emerging body of research regarding factors internal and external to SSPs that are related to larger scale naloxone distribution. Results from two national surveys of SSPs have identified that higher levels of community support, more sustained implementations, larger annual budgets, more days of service, and being a non-governmental entity are associated with higher levels of naloxone distribution 17, . While SWhile the findings from this pilot study are promising, there are some limitations to consider. In piloting SAIA-Naloxone, we did not randomly select SSPs, randomly assign SSPs to receive SAIA-Naloxone, nor were we able to use a design with a robust control. Still, the use of an interrupted time series approach allowed us to assess changes within SSPs and provided an estimate of the outcomes above and beyond what would have been expected in the absence of SAIA-Naloxone . This deSAIA-Naloxone is a feasible implementation strategy that leverages programmatic data and principles of continuous quality improvement to increase access to naloxone among SSP participants who are likely bystanders of opioid-related overdoses. Ensuring this population is prepared and equipped to reverse overdoses and prevent fatalities is essential to combatting the worsening opioid overdose crisis in the US.


The COVID-19 pandemic has shaken everyday life causing morbidity and mortality across the globe. While each country has been hit by the pandemic, individual countries have had different infection and health trajectories. Of all welfare state institutions, healthcare has faced the most immense pressure due to the pandemic and hence, we take a comparative perspective to study COVID-19 related health system performance. We study the way in which health system characteristics were associated with COVID-19 excess mortality and case fatality rates before Omicron variant.This study analyses the health system performance during the pandemic in 43 OECD countries and selected non-member economies through three healthcare systems dimensions: (1) healthcare finance, (2) healthcare provision, (3) healthcare performance and health outcomes. Health system characteristics-related data is collected from the Global Health Observatory data repository, the COVID-19 related health outcome indicators from the Our World in Data statistics database, and the country characteristics from the World Bank Open Data and the OECD statistics databases.We find that the COVID-19 excess mortality and case fatality rates were systematically associated with healthcare system financing and organizational structures, as well as performance regarding other health outcomes besides COVID-19 health outcomes.Investments in public health systems in terms of overall financing, health workforce and facilities are instrumental in reducing COVID-19 related mortality. Countries aiming at improving their pandemic preparedness may develop health systems by strengthening their public health systems. In March 2020, World Health Organization (WHO) declared the coronavirus disease COVID-19) as a global pandemic. Before that, the first cases were identified in the city of Wuhan in China, and quickly, this novel severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) evolved internationally into a public health emergency 9 as a gl, even thNumerous previous studies show that the risk factors for COVID-19 outcomes relate to socioeconomic, environmental, individual demographic and health factors   higher total healthcare expenditure is associated with reduced COVID-19 excess mortality and case fatality rates; (2) healthcare system financing types with higher total and public health expenditure have better COVID-19 outcomes; (3) healthcare system provision types with better access to care and higher level of provisional resources are connected with better COVID-19 outcomes; and (4) healthcare system combined types  with high level of resources are associated with reduced COVID-19 excess mortality and case fatality rates. To examine these expectations, next, we move onto describing the research data and methods.In this study, we analyse the health system performance during the COVID-19 pandemic in 43 high-income countries (high-income and upper-middle-income economies by World Bank lending categories) through their healthcare financing, provision and public health characteristics. The countries were chosen because they represent distinctive healthcare systems from various geographical areas and are OECD’s member states or their selected non-member economies  which are OECD’s key collaboration partners and some of the world’s largest economies. Of the non-member economies, India was excluded because of data availability issues. Moreover, due to the data availability and comparability, we restricted our analyses to countries whose healthcare characteristics-related data is collected and made available by the WHO and OECD. Table The COVID-19 related health outcome indicators, COVID-19 excess mortality and case fatality rate, and the indicator of the burden of disease are collected from the Our World in Data statistics database , 30. TheThe country characteristics-related data are from the World Bank Open Data database  that contains free and open access information on global development  and fromWe applied regression analysis to summarise the influence of explanatory variables upon the COVID-19 outcomes (see ). We useIn preparatory analysis we applied one-way analysis of variance (ANOVA) to evaluate whether there is evidence that the group means of countries of different healthcare system types differ in relation to COVID-19 outcomes. We used the Tukey multiple comparison test to investigate which of the means were different when ANOVA test showed evidence for differing group means . In prelTo analyse the impact of health system structures on COVID-19 outcomes, we use COVID-19 excess mortality rate as the main dependent variable and COVID-19 case fatality rate as the second dependent variable for sensitivity checks. Figure The measure of excess mortality provides an estimate of the additional number of deaths during COVID-19 pandemic compared to the deaths if the pandemic had not occurred . The excBeaney et al.  note excThe all-cause excess deaths measure has several advantages which Corrao et al.  describeThe COVID-19 case fatality rate instead, is measured as the number of confirmed COVID-19 deaths divided by the number of confirmed COVID-19 cases. Rather than being constant, the case fatality rate reflects the severity of the disease in a particular context, at a particular time and in a particular population . Case faFor explaining the COVID-19 outcomes, we use measures of health system characteristics and healthcare system types. Previous research has studied healthcare financing –19, healSecond, we use the healthcare system financing, provision and combined types to explain the variation in COVID-19 outcomes between countries. Tables Healthcare system financing types categorize countries based on their current total, public and private out-of-pocket health expenditure characteristics. Higher CHE reflects better financial capacity of healthcare systems to provide health services; higher share of public health expenditure reflects larger public responsibility over healthcare financing whereas higher share of private expenditure presents larger role of private households in covering healthcare costs . For exaTable The healthcare system combined types reflect health systems’ financing, provision and population health outcomes characteristics. The health financing and provision characteristics are the same as described above whereas population health outcomes are measured as measles-vaccine coverage among 1-years-olds, life expectancy, distribution of life expectancy, maternal and cancer mortality. For example, the first combined type represents health systems which are characterized by the lowest share of out-of-pocket expenditure, the highest level of CHE and government health expenditure. The healthcare supply is on a high level. Primary care is mainly organized in the private sector, but gatekeeping practices vary from strict to non-existent. These countries produce the best population health outcomes in terms of high measles-vaccine coverage, high life expectancy, small differences in life expectancy between males and females, low maternal and cancer mortality. The other three healthcare system combined types and the countries representing them are presented in Table The country characteristics-related data, GDP per capita, DALYs and population share of 80-year-olds and over are used as control variables in the regression models , the number of hospital beds and doctors. In final models these measures we left out as they did not present a statistically significant relationship with the outcome variables or improve the model fits.In Tables We see statistically significant relationships between all the financing characteristics and excess mortality and case fatality rate. The connections have the same directions with both dependent variables with and without control variables (except Model 2c). We find that higher CHE and public health expenditure are associated with lower excess mortality and case fatality rates, whereas a higher share of out-of-pocket expenditure is related to higher excess mortality and case fatality rates. The financing characteristics seem to explain around 15 to 30% of the variation in excess mortality and case fatality rates. However, when the controls are added, the significant connections mostly decrease or disappear.After controlling for other variables and the outlier countries, the results indicate that the population share of 80-year-olds and over has no statistically significant relationship with COVID-19 outcomes. However, in Models 1c-6c the negative relationships between advanced age and COVID-19 outcomes diminishes or becomes positive when the country-controls are added since they represent countries with younger populations but with high excess mortality and case fatality rates. DALYs have a strong and positive relationship with excess mortality and case fatality, indicating that the greater previous burden of disease is associated with higher numbers of COVID-19 excess mortality and case fatality. GDP per capita, net-of-controls, has a strong and negative relationship with excess mortality and also, a negative relationship with case fatality: higher GDP is associated with lower excess mortality and case fatality rates.Tables Compared to the second financing type, financing types 3 and 4 have higher excess mortality and case fatality rates. It appears that health systems with a lower share of private health expenditure and a high level of CHE and public health expenditure produce better COVID-19 outcomes (such as systems in the financing type 2) than health systems with a higher share of private out-of-pocket payments, a lower level of CHE and public financing.When comparing provision types, we notice that provision type 1 is associated with the best COVID-19 outcomes in relation to the other provision types. Healthcare systems of provision type 1 differ from the other provision types especially in terms of greater number of hospital beds and better coverage of essential health services. However, the results with provision types do not indicate strong associations with COVID-19 outcomes.Finally, compared to the healthcare system combined type 1, the combined types 3 and 4 seem to have higher rates of excess mortality and case fatality. Health systems with a low share of out-of-pocket expenditure, and a high level of CHE, government health expenditure, healthcare employment, hospital beds and essential health services seem to produce better COVID-19 related health outcomes (systems such as combined type 1). The health systems of the combined type 1 also produce the best other population health outcomes  which may indicate that health systems that had a good performance even before COVID-19 pandemic, have also been able to perform better during the COVID-19 pandemic.At the beginning of this paper, we hypothesized that (1) higher total healthcare expenditure is associated with reduced COVID-19 excess mortality and case fatality rates; (2) healthcare system financing types with higher total and public health expenditure produce better COVID-19 outcomes; (3) healthcare system provision types with better access to care and higher level of provisional resources are connected with better COVID-19 outcomes; and (4) healthcare system combined types with high level of resources are associated with reduced COVID-19 excess mortality and case fatality rates. Our findings support these expectations and find support from earlier research on the relationship between health outcomes and health system characteristics. The results suggest that higher health financing and provision resources contribute to lower COVID-19 excess mortality and case fatality rates. Also, better public health outcomes prior to COVID-19 pandemic seem to indicate better COVID-19 outcomes. Our findings indicate that strengthening the overall health financing, workforce and facilities of national public health systems reduces COVID-19 related mortality.Our findings indicate that lower COVID-19 excess mortality and case fatality rates are associated with higher total healthcare expenditure which has also been connected to better health outcomes such as lower mortality rates –18. The While the relationship between healthcare system types and COVID-19 outcomes, or other health outcomes, is underexplored in previous literature, our findings indicate that healthcare system types provide a useful tool for understanding differences in COVID-19 outcomes in high-income countries. Even though Simoes et al.  did not Limitations of this study relate to the reliability of the data and the complexity of measuring COVID-19 health outcomes. As noted earlier, the databases from which the data for constructing the excess mortality and case fatality rates are sourced, are from several different national and international sources. Thus, the data collection and reporting methods vary across countries. For the excess mortality indicator, the coverage and reliability of the data varies across countries, and some of the countries might have reported incomplete mortality numbers underestimating the excess mortality rates (see ). The saDue to the complexity of the COVID-19 pandemic and used COVID-19 indicators, COVID-19 outcomes cannot fully be explained with healthcare characteristics. COVID-19 is likely to be connected to geographical and welfare state related factors such as social protection and different reactions to buffer the pandemic; for example, the different trajectories of Sweden and other Nordic countries (strict versus loose COVID-19 response) , or situPrevious research has found evidence for alternative drivers of mortality in societies that might have impacted the excess mortality during the pandemic. Studies suggest that diminished healthcare use might have affected the excess mortality rates e.g. , 57), wh, wh57]),The COVID-19 case fatality rate instead is affected by the reporting of the number of COVID-19 deaths in healthcare, as listing COVID-19 as the cause of death requires a positive SARS-CoV-2 test which affects the official counts especially when the testing capacity is low . EspeciaHowever, we are not trying to provide an overall explanation for COVID-19 outcomes but to disentangle the possible role of healthcare system characteristics in tackling pandemics such as COVID-19. Our analyses consider the impact of societal characteristics in terms of GDP, DALYs and population share over 80-year-olds on COVID-19 outcomes and the results show that these factors are connected to the outcomes. Previous studies also find similar results of advanced population age and underlying health conditions being connected to higher COVID-19 caseloads and overall mortality , 50. HowTo conclude, our findings suggest that before Omicron variant COVID-19 excess mortality and case fatality rates were systematically associated with healthcare systems’ financing, provision and public health outcome characteristics, and that healthcare system types provide a tool for understanding differences in COVID-19 outcomes in high-income countries. Although the study setting did not allow causal inferences, our results suggest that investments in public health systems in terms of overall financing and a high level of health workforce and facilities are instrumental in reducing COVID-19 related mortality. Countries aiming at improving their pandemic preparedness may develop health systems by strengthening their public health systems.


Fibre breaks govern the strength of unidirectional composite materials under tension. The progressive development of fibre breaks is studied using in situ X-ray computed tomography, especially with synchrotron radiation. However, even with synchrotron radiation, the resolution of the time-resolved in situ images is not sufficient for a fully automated analysis of continuous mechanical deformations. We therefore investigate the possibility of increasing the quality of low-resolution in situ scans by means of super-resolution (SR) using 3D deep learning techniques, thus facilitating the subsequent fibre break identification. We trained generative neural networks (GAN) on datasets of high—(0.3 μm) and low-resolution (1.6 μm) statically acquired images. These networks were then applied to a low-resolution (1.1 μm) noisy image of a continuously loaded specimen. The statistical parameters of the fibre breaks used for the comparison are the number of individual breaks and the number of 2-plets and 3-plets per specimen volume. The fully automated process achieves an average accuracy of 82% of manually identified fibre breaks, while the semi-automated one reaches 92%. The developed approach allows the use of faster, low-resolution in situ tomography without losing the quality of the identified physical parameters. Unidirectional composites (UD) are widely used in industry for their high mechanical properties-to-weight ratio . One of 3) in the targeted high sub-µm resolution. For continuous in situ scanning, the image quality is significantly lower. Owing to the inherent limitations of CT, a 3D image of a specimen at a higher resolution requires increased X-ray flux and exposure time and introduces limitations in the specimen’s size [Recently, X-ray computed tomography (CT) became the most utilised technique for experimental evaluation of fibre break development during tensile tests . Combinen’s size . CT data−3, it can take several working days to identify all the fibre breaks in one volume manually [For low-resolution images (LR), all the identification needs to be performed manually, and several attempts over the same volume are needed to find all the fibre breaks. Considering that in situ scans produce dozens of volumes, and fibre break densities can reach up ~1000 mmmanually . The resGenerally, there are two methods used to improve the resolution of CT images: hardware- and software-based. When synchrotron radiation is exploited, the best and most expensive hardware is already used, so it is not always possible to upgrade. One of the software-based solutions to address the resolution limitations of tomography is to use image quality enhancement with super-resolution (SR) techniques ,21,22,23Super-resolution techniques are mainly available for 2D images. For 3D images, they can be implemented only in the slice direction, not the in-plane direction  or by avIn this work, we propose the use of deep learning-based super-resolution for CT image quality improvement and, specifically, for enabling automated fibre break analysis in unidirectional composites. To achieve super-resolution of CT images, we developed a deep learning architecture that combines ESRGAN and CycleGAN, which can handle 3D images and generate high-quality results without needing paired data. The study was performed for two types of carbon fibre/epoxy unidirectional composite with already known fibre break distribution . The quaThis study is based on the materials and data obtained by Breite et al.  and, recTwo carbon fibre cross-ply laminates were used: one for training the neural networks and another for validation. Cross-ply laminates are employed to efficiently apply loads to microscale specimens inside the SRCT load rig. The transverse ply did not affect the measured longitudinal fibre breaks.The first material was produced from prepregs manufactured at KU Leuven in a hot-melt drum winder. The T700SC-12K-50C carbon fibres (Toray Industries) were impregnated with Sicomin SR8500 KTA313 epoxy resin. The composite had a The second material was made from Grafil 34-700WD-24 K-1.4%A carbon fibres  and proprietary 736LT epoxy resin at North Thin Ply Technology (Switzerland). For this material, a ndations ,39.After bonding 1 mm thick 2014-T6 aluminium panels in the end tab regions using 3M Scotch-Weld EC 9323 B/A structural adhesive, miniaturised double-edge-notched tensile specimens (DENT specimens) were prepared from the cured materials, using a water-jet cutter, according to the dimensions specified in In total, data was acquired during two separate beamtimes at the TOMCAT beamline at Swiss Light Source (SLS). During the first beamtime, KU Leuven, INSA Lyon, and the University of Southampton performed the SRCT measurements together. INSA Lyon provided the tension-compression rig  for the 2. In addition, the T700SC LR scan was adjusted to match the 34-700 LR scans in terms of average grayscale values, contrast, and sharpness. Out of 17 low-resolution scans of the 34-700 specimen with fibre break development under continuous load, four images were prepared for fibre break analysis and verification of the super-resolution algorithm: initial , intermediate load (75% load), high load (94% load), and before failure (98% load). Absorption-based tomography reconstruction was performed using the Gridrec algorithm  without In this work, a generative adversarial network (GAN ) was desThe generator and discriminator are convolutional neural networks with modifications described below. The Enhanced Super-Resolution generator  with reThe network was enhanced with the CycleGAN methodology , which aPython 3.8 and TensorFlow 2.9 frameworks were utilised to process the CT data, implement the deep learning architecture, and train models. The learning process of neural networks was performed on a workstation with a 12-Core Xeon 4214 processor, a 16 GB Tesla V100 graphical card, and 64 GB of RAM.3 for low-resolution images and 128 × 128 × 128 pixel3 for high- and super-resolution images. We used a volume overlap of 3 pixels for low-resolution and 12 pixels for high-resolution images. The total training data set consisted of 4560 LR and HR small volumes.Because deep learning and CT processing are hardware-intensive tasks, CT volumes were divided into smaller volumes as follows: 32 × 32 × 32 pixelADAM stochastic gradient descent solver  was appl process . The tot process . The tra process .Low-resolution volumes were enhanced by super-resolution and full-scale SR images were obtained. The overlap allowed us to perform the enhancement almost seamlessly.3.The reference data for fibre break locations were obtained by several manual inspections of images for fibre break analysis, which were performed in detail on the last volume before failure ,36. For For this paper, all darker regions are called voids, including possible fibre breaks and cracks. For image segmentation, three segmentation algorithms were analysed: RootPainter, ImageJ with Weka segmentation plugin, and InSegt. A modified RootPainter algorithm  was impl5 pixels in volume), which were analysed manually.The RootPainter algorithm is based on deep learning techniques and implements a U-Net network for image segmentation with a batch size of 4 and 3 × 3 kernels. The network was trained according to the RootPainter documentation. The training was performed interactively on partially annotated images, and later on corrective annotations, until the algorithm produced satisfactory results. To locate fibre centre points, only the central parts of the fibres without edges were used for training. Part of the InSegt Fibre code  was implTwo methods were used to distinguish the fibre breaks from the voids. The first method searched for fibre sections above and below a void along the smallest diameter of a fitted ellipsoid; the voids located between the fibre sections are considered to be fibre breaks. The second method required a CT image of the initial state of the specimen. The resolution of the initial state image was also increased with super-resolution, and a MATLAB image registration algorithm was implemented to align the initial state image with the loaded state images. The voids intersected by the initial fibre trajectories were considered fibre breaks, as was the case in , for higThe clustering of fibre breaks was analysed according to geometric criteria based on stress redistribution caused by a fibre break. In line with , two fibThe accuracy of fibre break identification was analysed using statistical classification . In thisFor semi-automatic identification, the fibre breaks manually identified from large-fused objects are also taken into account and false positives are checked. The miss rate indicates the percentage of fibre breaks that were not found by the automated algorithms.SRCT images of a continuously loaded (in situ) specimen were analysed as a validation set. Compared to statically acquired images, in situ images not only have a lower resolution but also higher noise and less precise edges of the objects due to movement during image acquisition. For example, voids in the in situ image are not represented as spheres or ellipsoids, but as vortex artefacts with the void as their centre see . This cr3 (1.4 GB) to SR images of 4236 × 1792 × 6660 px3 (90 GB). A significant improvement in image quality can be observed: fibre cross-sections become more visible, the fibre edges become defined enough to be visually and computationally distinguished, and fibres do not blend into each other anymore. Stitching artefacts can be found upon careful inspection of the centre of the image in Super-resolution algorithms were applied to the in situ synchrotron images. Despite the significant quality improvement, deep learning deviations are present: (1) several fibres are not round anymore, (2) in rare cases, the edges of the fibres can seamlessly merge into the matrix  of the fibres are tracked along the entire volume without interruption or loss of tracking. This suggests that super-resolution and deep learning segmentation can be used to enable automatic fibre tracking in low-resolution CT images of fibre-reinforced composite materials.In low-resolution images see , due to Fibre breaks are found amongst the segmented voids. After manual analysis of a few fibre breaks, an average volume was calculated, which mostly varies between 1000 and 50,000 pixels in volume and the diameter of circumscribed ellipsoids is longer than 20 pixels. After filtering according to these parameters, only voids that could potentially be fibre breaks remain. The voids with a volume much larger than the volume of the average fibre break are treated separately, as such voids may represent a cluster of fibre breaks.Fibre break identification is performed according to the procedures described in If a scan before loading is available, then the second method can be used. This method provides better results, and there is only one parameter to optimise, the minimum distance from a void centre to the fibre trajectory, in order to consider the analysed void as a fibre break. The accuracy of the fibre break identification is lower when analysing volumes with a large number of fibre breaks. This is because the algorithm is not able to recognise individual fibre breaks in densely packed fused objects, as shown in At this stage of image processing, it is challenging to separate such clusters into individual voids. During the image processing, such clusters could be handled manually by an operator who would be shown the low-resolution, super-resolution, and segmented images, similar to Fibre breaks were clustered using the geometric criteria described in Image processing of the enhanced images takes a considerable amount of time. Once the super-resolution network was trained, the SR application took about four hours to increase the resolution of the whole volume, six hours to segment an SR image into fibres and voids, and one hour for image processing, tracking fibre trajectories, calculating void sizes, and identifying fibre breaks. In addition, approximately one hour of manual work was required to analyse large objects and eliminate false positives for the image before failure . This is much faster than the 3–5 working days required for manual analysis, especially when considering that one hour of hands-on time was required.Super-resolution can increase the speed of identification not only of fibre breaks in unidirectional composites but also of other manufacturing defects in composite materials such as delamination, matrix cracking, voids, or porosity. The developed algorithm can help researchers working on models for strength assessment based on fibre breaks. One can try to train the algorithm on one material and transfer the super-resolution capabilities to other similar materials, such as demonstrated by training on T700SC and validating on 34-700WD. However, there are limitations to using machine learning algorithms on data that are significantly different from the training dataset; such algorithms will not be able to work with significantly distinct data. If a new type of feature is introduced in the images, machine learning algorithms will produce unexpected results and miss important features. One reason why features may be missed after SR is that, in low-resolution images, there is not enough information about them to reconstruct correctly. The spatial resolution of the LR image determines the minimum feature size that can be reconstructed, which should be at least two pixels per feature size. Another reason is that the features are not well represented in the training data, in which case the model can fill in the feature with the structure it is most familiar with . For exaA super-resolution algorithm has been designed and applied in order to improve the image quality of low-resolution synchrotron CT scans. The algorithm is based on deep learning architecture developed by combining Enhanced Super-Resolution GAN and CycleGAN. The neural networks were trained on high-resolution and low-resolution scans of a stationary carbon fibre composite and applied to another much larger low-resolution image of a continuously loaded specimen.As a result, the super-resolution images have more precise fibre and void boundaries with only minor deep learning-based artefacts. To segment the images, we chose RootPainter software, which was the most suitable algorithm for our case. With this software, precise identification of fibres and voids was achieved. The quality of the segmentation allows the study of fibre trajectories and void locations.Super-resolution processing enabled automated identification of fibre breaks using void location and fibre trajectories. Two algorithms have been implemented: one using the information from only the loaded image and the other using fibre trajectories from the unloaded image. The average accuracies of the methods are 76% and 82%, respectively, for the fully automated process and 86% and 92% for the semi-automated process with a miss rate of less than 5.3%. The fibre break clustering outputs similar results, with minor deviations, due to inconsistent fibre break centre locations. Super-resolution makes it possible to use faster, low-resolution in situ CT scans on continuously loaded specimens with limited compromises on the quality of physical parameter identification. The developed methodology can be used for faster, but less accurate, fibre break identification for strength assessment models.