To provide comprehensive population-level estimates of the burden of healthcare-associated influenza.Retrospective cross-sectional study.US Influenza Hospitalization Surveillance Network (FluSurv-NET) during 2012–2013 through 2018–2019 influenza seasons.Laboratory-confirmed influenza-related hospitalizations in an 8-county catchment area in Tennessee.The incidence of healthcare-associated influenza was determined using the traditional definition  in addition to often underrecognized cases associated with recent post-acute care facility admission or a recent acute care hospitalization for a noninfluenza illness in the preceding 7 days.Among the 5,904 laboratory-confirmed influenza-related hospitalizations, 147 (2.5%) had traditionally defined healthcare-associated influenza. When we included patients with a positive influenza test obtained in the first 3 days of hospitalization and who were either transferred to the hospital directly from a post-acute care facility or who were recently discharged from an acute care facility for a noninfluenza illness in the preceding 7 days, we identified an additional 1,031 cases .Including influenza cases associated with preadmission healthcare exposures with traditionally defined cases resulted in an 8-fold higher incidence of healthcare-associated influenza. These results emphasize the importance of capturing other healthcare exposures that may serve as the initial site of viral transmission to provide more comprehensive estimates of the burden of healthcare-associated influenza and to inform improved infection prevention strategies. Transmission of influenza to patients has occurred in a variety of healthcare settings, often as the result of infected healthcare personnel, and it is associated with increased length of stay and poor outcomes. Despite this impact, comprehensive estimates of the incidence of healthcare-associated influenza are limited. The most commonly used method to capture the burden of this important nosocomial infection defines healthcare-associated influenza as an influenza case diagnosed after day 3 of hospitalization, which ignores other preadmission healthcare exposures. Most published reports also only describe the experience of outbreaks at single institutions or the epidemiology of pandemic strains. Lack of standardized surveillance definitions and variation in clinician-driven testing inhibit comparability between these published studies and likely underestimate the number of healthcare-associated influenza hospitalizations.Accounting for an estimated 140,000–710,000 hospitalizations and 12,000–52,000 deaths in the United States annually since 2010, Although this frequency was relatively low, Jhung et al and Cummings et al found that patients with healthcare-associated influenza were more likely to have severe outcomes, including the need for ICU-level care, mechanical ventilation, and longer hospital stays. These studies, however, omit important preadmission healthcare exposures  that may have served as the initial location of viral transmission. Limited to cases identified using the traditional definition of healthcare-associated influenza with test positivity and symptom onset after day 3 of hospitalization, these studies likely underestimated the overall burden of healthcare-associated influenza.Of the few published population-level estimates in the United States, the proportion of healthcare-associated influenza ranged from 0.4% to 2.8% of patients admitted with influenza.To perform a more comprehensive assessment of healthcare-associated influenza that includes preadmission healthcare exposures, we used data from the US Influenza Hospitalization Surveillance Network (FluSurv-NET) to evaluate the population-level burden of healthcare-associated influenza over 7 influenza seasons. The incidence of healthcare-associated influenza using the traditional definition was compared to that calculated with the addition of cases associated with recent post-acute care facility admission or a recent acute care hospitalization for a noninfluenza illness to better understand the frequency of other healthcare exposures that result in hospitalization for influenza. The EIP is a collaborative network organized by the Centers for Disease Control and Prevention in partnership with state health departments and academic medical centers. Within FluSurv-NET, persons of any age residing within the defined catchment area admitted between October and April of every year with a positive influenza test collected within 14 days prior to or during the hospitalization are included. For each identified case, medical history, clinical course, medical interventions, and outcomes are obtained through medical chart abstraction performed by trained personnel. In this study, persons meeting the FluSurv-NET case definition and admitted between 2012 and 2019 and residing in an 8-county catchment area in middle Tennessee  were included. Laboratory confirmation was defined as a positive influenza test by molecular assay, rapid antigen testing, or viral culture.FluSurv-NET is a population-based, multicenter surveillance system that collects data on laboratory-confirmed influenza-associated hospitalizations in pediatric and adult patients in acute care hospitals within predefined counties in the 14 states participating in the Emerging Infections Program (EIP). To include other preadmission healthcare settings in which influenza virus exposure and transmission may have occurred, we identified persons with a positive influenza test collected in the first 3 days of hospitalization who either (1) were transferred from a post-acute care facility, or (2) were discharged from an acute care facility for a noninfluenza illness in the 7 days preceding the index influenza admission  have been reported with their 95% confidence intervals (CI). Analyses were conducted in Stata version 16 software . This study was approved by the Vanderbilt University Medical Center and Tennessee Department of Health Institutional Review Boards.Cases described as healthcare-associated influenza by either the traditional or expanded definitions were expressed as a percentage of the total laboratory-confirmed influenza-related hospitalizations by annual influenza season and overall. Additionally, the proportion of positive cases attributed to each type of healthcare exposure  were calculated. We calculated unadjusted incidence rates per 100,000 population stratified by type of healthcare exposure by year and overall using the number of cases meeting the definitional criteria as the numerator and the population within the predefined catchment area, as recorded by the National Center for Health Statistics’ vintage bridged-race postcensal population estimates,Among the 5,904 laboratory-confirmed influenza-related hospitalizations from 2012 through 2019 in the surveillance catchment area, most patients (52%) were aged ≥65 years , were non-Hispanic White (73%), and had 1 or more underlying medical condition (91% of adults) (Table P < .001) and a longer median length of stay .Of these influenza-related hospitalizations, 147 (2.5%) had traditionally defined healthcare-associated influenza. Relative to the total cohort, these patients had a higher proportion of ICU admission  and non-Hispanic White . Within this group, the median length of stay more closely resembled that of the total cohort; however, similar to cases defined using only the traditional definition, the cohort identified with the additional healthcare exposures had a higher proportion of ICU admission than the total cohort of laboratory-confirmed influenza .The inclusion of persons with a positive influenza test obtained in the first 3 days of hospitalization with a preadmission healthcare exposure identified an additional 1,031 cases . Of these additional cases, 289 (4.9%) were transferred from a post-acute care facility, 682 (11.6%) had a recent acute care hospital admission in the preceding 7 days, and 60 (1%) had both a recent acute care hospital admission and contact with a post-acute care facility . This rate increased to 10.2 per 100,000  when the more comprehensive expanded definition of healthcare-associated influenza was used. Relative to the traditional definition, the incidence rate ratio of healthcare-associated influenza by the expanded definition was over 8-fold higher   after a non-ILI encounter during periods of high respiratory virus transmission. Improved understanding of how these healthcare settings may contribute to healthcare-associated influenza has important implications for horizontal infection control practices and may generate novel ways to lessen viral spread. These settings often present unique challenges to the general application of infection prevention practices that differ from those used in inpatient facilities, but these settings provide care for a number of particularly vulnerable patients with a burgeoning aging population and shift in the delivery of increasingly complex subspecialty care to outpatient settings.Outbreaks of influenza in long-term care facilities have been well described, Timely recognition leads to rapid implementation of respiratory isolation precautions and reduced subsequent nosocomial transmission. As the results of this study suggest, healthcare-associated influenza has been associated with adverse outcomes, including longer length of stay, as well as increased need for ICU-level care, mechanical ventilation, and mortality relative to community-acquired influenza.Standardized and more complete definitions of healthcare-associated influenza could also improve clinician awareness and early detection of influenza as patients hospitalized with influenza may not present with the common signs and symptoms associated with an influenza-like illness. We did not apply any multipliers to the burden estimate to account for testing practices; therefore, these burden estimates are very conservative. Secondly, categorizing cases as community- or healthcare-associated based on the date of test positivity may lead to misclassification, particularly without chart review to assess for symptoms consistent with ILI before test positivity. Not all potential preadmission healthcare exposures  were captured in the expanded definition, possibly leading to misattribution of cases as community-associated if the actual viral transmission occurred in these healthcare settings. Additionally, only influenza cases that required hospitalization were captured. Notably, the delay between admission and the date of test positivity used in the traditional definition is conservative based on the median incubation period for influenza , thereby increasing the specificity of our definition. For these reasons, these results still may underestimate the true burden of healthcare-associated influenza. Conversely, including cases that occurred within 7 days of discharge from an acute care facility may misrepresent some cases that were actually community acquired. The challenge in attributing a source of transmission of a case of influenza must be acknowledged, as one can rarely determine this with absolute confidence. Hence, the use of the term “healthcare associated” and not “healthcare acquired,” which provides the association that can direct infection prevention interventions that should reduce healthcare-associated virus transmission even with the inability to definitively attribute the source of transmission of a specific case. Lastly, while these study results support the need for comprehensive and systematic surveillance of healthcare-associated influenza, there are barriers to capturing these other exposures accurately as part of a routine surveillance program. Improved data collection and tracking in the electronic medical record could assist with this effort.This study had several limitations. First, determination of an influenza-related hospitalization is dependent on clinician-driven testing. Variability in clinical practice and institutional testing protocols may have resulted in significant underrecognition of influenza burden.In summary, restricting surveillance of healthcare-associated influenza to only those cases possibly acquired during the current acute care admission underestimates the prevalence of this important yet underrecognized nosocomial infection. Standardization of definitions and surveillance methods could improve the understanding of influenza transmission and inform clinical practice and infection prevention strategies to mitigate healthcare-associated transmission across all types of healthcare facilities.


Intravascular ultrasound (IVUS) imaging has been extensively utilized to visualize atherosclerotic coronary artery diseases and to guide coronary interventions. To receive ultrasound signals within the vessel wall safely and effectively, miniaturized ultrasound transducers that meet the strict size constraints and have a simple manufacturing procedure are highly demanded. In this work, the first known IVUS probe that employs a backing-layer-shared dual-frequency structure and a single coaxial cable is introduced, featuring a small thickness and easy interconnection procedure. The dual-frequency transducer is designed to have center frequencies of 30 MHz and 80 MHz, and both have an aperture size of 0.5 mm × 0.5 mm. The total thickness of the dual-frequency transducer is less than 700 µm. In vitro phantom imaging and ex vivo porcine coronary artery imaging experiments are conducted. The low-frequency transducer achieves spatial resolutions of 40 µm axially and 321 µm laterally, while the high-frequency transducer exhibits axial and lateral resolutions of 17 µm and 247 µm, respectively. A bandpass filter is utilized to separate the ultrasound images. Combining in vitro phantom imaging analysis with ex vivo imaging validation, a comprehensive demonstration of the promising application of the proposed miniature ultrasound probe is established. When atherosclerotic plaques rupture within the coronary arteries, this becomes the primary trigger of coronary artery disease, a condition that can lead to severe complications such as acute coronary syndrome and sudden cardiac death ,2. AtherIntravascular ultrasound (IVUS) imaging technology utilizes miniaturized ultrasound transducers inserted into blood vessels to analyze the morphology of plaque tissue, allowing for the visualization of cross-sectional coronary artery walls and the quantitative assessment of lumen dimensions and plaque characteristics ,7. TradiA recent advancement in ultrasound imaging is the utilization of harmonic IVUS imaging . This inHigh-frequency IVUS imaging holds significant promise for enhancing arterial characterization due to its improved axial resolution, and it offers comparable penetration depth to that of OCT . To be sPrevious studies have demonstrated the advantages of multi-frequency ultrasound catheters, which provide both deep imaging capabilities and high-resolution imaging ,27,28. HIn this work, for the first time, we implemented a configuration where a low-frequency ultrasound transducer element (30 MHz) and a high-frequency ultrasound transducer element (80 MHz) were arranged back-to-back, sharing a single backing layer. This innovative design enabled the dual-frequency transducer to have an overall thickness of less than 700 µm. In addition, in order to simplify the interconnection of the dual-frequency transducer, a single coaxial cable was utilized, while a digital filter was employed to separate signals from each transducer element. We conducted in vitro phantom imaging and ex vivo porcine coronary artery imaging experiments to demonstrate the deep penetration capability of the low-frequency transducer and the high-resolution imaging of the lumen area achieved by the high-frequency transducer. These experimental results serve to validate the feasibility of the proposed dual-frequency IVUS probe in overcoming limitations associated with conventional IVUS catheters.The designed structure of the backing-layer-shared dual-frequency transducer is depicted in The Krimholtz–Leedom–Matthaei (KLM) model is utilized to design the structure and size of the dual-frequency ultrasound transducer. The parameters of the proposed IVUS transducer are detailed in The fabricated backing-layer-shared dual-frequency transducer is illustrated in To compare the performance of the proposed backing-layer-shared dual-frequency transducer with that of single-element ultrasound transducers, two ultrasound transducers with center frequencies of 30 MHz and 80 MHz were fabricated as a comparison group, maintaining the same layer parameters and transducer size as the proposed probe.The piezoelectric and acoustic properties of the dual-frequency transducer were characterized. The dielectric property and electrical impedance of the dual-frequency transducer were assessed in air using an impedance analyzer . The experimental setup for the pulse–echo response is illustrated in The imaging evaluation setup, as illustrated in In this work, a wire phantom was first fabricated to assess the spatial resolution of the proposed ultrasound probe, as shown in A blood vessel phantom was then created to mimic the human coronary artery, with an inner diameter of 6 mm and a vessel wall thickness of 3 mm. Gelatin  was dissolved in thermal water at a weight ratio of 30% using a magnetic stirring heater. Sigmcell Cellulose  was added to the solution as scattering particles at a weight ratio of 3% . The othEx vivo porcine coronary artery imaging was also conducted in this study. The pulse–echo responses of the dual-frequency transducer were evaluated and illustrated in The wire phantom images obtained with the proposed dual-frequency transducer are presented in The wire phantom images, along with the axial and lateral profiles, provide a comprehensive understanding of the resolution performance of the dual-frequency transducer. The enhanced axial resolution facilitates the identification of small abnormalities or lesions, while the improved lateral resolution enables the accurate differentiation of adjacent structures. The obtained results demonstrate that the low-frequency transducer effectively captures larger-scale features with satisfactory axial and lateral resolution. Conversely, the high-frequency transducer excels in imaging fine details with superior axial and lateral resolution, allowing for an enhanced visualization of intricate structures. Consequently, these features empower the dual-frequency transducer to provide valuable insights into the anatomical and pathological aspects of the imaged objects.The image acquired by the low-frequency transducer effectively captures the complete vessel structure. And the high-frequency transducer excels in providing high-resolution imaging, allowing for a detailed examination of surface features. Consequently, the blood vessel phantom images obtained using the proposed ultrasound probe provide compelling evidence of its deep penetration ability and high-resolution capability. This combination is crucial in clinical applications. The deep penetration capability of the low-frequency transducer facilitates the examination of deeper anatomical structures, and the high-resolution competence of the high-frequency transducer allows for the detection of subtle abnormalities and the visualization of intricate surface details.Ex vivo porcine coronary artery images acquired by the proposed dual-frequency transducer are presented in The utilization of micromachined ultrasound transducers in intravascular diagnosis and evaluation has been well established. Ultrahigh frequency transducers have emerged as a promising approach, offering exceptional imaging resolution comparable to the OCT imaging method. The practical implementation of a combined IVUS and OCT method presents challenges, primarily due to the complex structure and high production costs involved. To address these limitations, a dual-frequency transducer has been designed specifically for observing different situations within blood vessels. The integration of both low and high frequencies in an ultrasound catheter allows for a versatile imaging approach. The low-frequency transducer enables deep penetration, while the high-frequency transducer provides detailed information about the blood vessels. Nevertheless, the fabrication process of the dual-frequency transducer poses its own challenges. Manufacturing the two transducers individually and connecting each to a separate coaxial cable results in a relatively large probe thickness and a complex manufacturing process.In this paper, we introduced the first known demonstration of a novel backing-layer-shared dual-frequency ultrasound probe with center frequencies of 30 MHz and 80 MHz. This innovative design offers several advantages over conventional transducers for intravascular ultrasound imaging applications. One key feature is the utilization of a single backing layer with a back-to-back structure, allowing for a compact thickness of less than 700 µm. This compact form factor is essential for applications where space constraints are a concern. Furthermore, the incorporation of a single coaxial cable to connect the transducer not only minimizes the overall size of the probe but also simplifies the fabrication process. This streamlined design reduces fabrication complexity and enhances the efficiency of manufacturing, enabling the cost-effective production of the dual-frequency transducer.The proposed dual-frequency transducer featured a compact back-to-back structure with the size of 0.5 mm × 0.5 mm. This size is optimized for optimal performance and ease of integration into IVUS imaging systems. The compact dimensions make the transducer suitable for applications requiring high-resolution imaging in confined spaces. The probe was excited simultaneously, and the received images from different frequency ranges were separated using bandpass filters. The utilization of bandpass filters becomes particularly advantageous due to the significant disparity between the frequency spectra of 30 MHz and 80 MHz. This stark contrast in frequencies enables the filters to accurately isolate and separate the respective signals, thereby facilitating the distinct imaging of the different frequency ranges. By eliminating unwanted interference and isolating the desired frequency components, the bandpass filters enhance the clarity and quality of the received images.The electrical impedance magnitudes illustrated the fact that the dual-frequency transducer exhibited resonant frequencies of 30.1 MHz and 97 MHz, respectively. The measured resonant frequency of the high-frequency transducer was slightly higher than the intended value, potentially attributed to signal transition delay and loss introduced by the long coaxial cable used in the setup. The higher frequency signals are more susceptible to attenuation, resulting in a higher resonant frequency being measured. The pulse–echo responses confirmed that the dual-frequency transducer had center frequencies of 32 MHz and 76 MHz, aligning with the designed values. The low-frequency transducer exhibited a −6 dB bandwidth of 62%, indicating its ability to effectively transmit and receive a wide range of frequencies. Similarly, the high-frequency transducer exhibited a bandwidth of 51%, highlighting its considerable potential for ultrasound imaging. The substantial bandwidths offered by the dual-frequency transducer indicate its capability to capture a broad spectrum of frequencies, which is crucial for achieving high-resolution and detailed ultrasound images.In vitro wire phantom imaging was conducted in this study to assess the spatial resolution of the proposed ultrasound probe. The axial resolution for the low-frequency transducer was measured to be 40 µm, while the lateral resolution was determined to be 321 µm. For the high-frequency transducer, the axial resolution was found to be 17 µm, with a lateral resolution of 247 µm. The wire phantom imaging results exhibit a spatial resolution comparable to that of the previous dual-frequency transducer, thereby clearly demonstrating the high-resolution capability of the proposed transducer. To further evaluate the imaging performance, a blood vessel phantom was created to mimic a human blood vessel. The low-frequency transducer produced ultrasonic images that effectively depicted the overall structure of the blood vessel with its deep penetration capability. On the other hand, the high-frequency transducer exhibited a limited penetration depth of approximately 2 mm. While the imaging depth was constrained, it compensated for this by providing more detailed surface information of the phantom. This enhanced surface visualization enables a better characterization of surface structures, enhancing the overall diagnostic capabilities of the high-frequency transducer.Moreover, ex vivo imaging of a porcine coronary artery was conducted to assess the performance of the transducer in a realistic situation. The low-frequency transducer illustrated its deep penetration ability by effectively visualizing the integrated blood vessel structure. The acquired images provided a comprehensive representation of the vessel morphology and enabled an accurate assessment of its overall structure. In contrast, the high-frequency transducer exhibited superior imaging resolution, providing clearer and more detailed information about the inner surface of the porcine blood vessel. This enhanced imaging resolution allows for a better visualization and characterization of subtle features, enabling the precise evaluation and diagnosis of potential abnormalities. The imaging of porcine coronary artery highlights the strengths and capabilities of the proposed dual-frequency ultrasound probe.In our study, the implementation of a back-to-back configuration for the dual-frequency transducer, in conjunction with a signal processing strategy that employs filtering techniques, addresses potential interactions between the higher harmonics of the low frequency (30 MHz) and the fundamental frequency of the high frequency (80 MHz). The back-to-back configuration physically separates the transmission and reception of the low- and high-frequency signals, minimizing direct interactions between these frequency components. To further control these interactions, we utilize filters designed to isolate specific frequency components and attenuate undesired harmonics. This approach allows us to enhance the clarity and precision of imaging tissue structures. Consequently, the potential for interference between different frequency ranges is effectively managed, aligning with the imaging goals with the structure design and signal processing strategies.In this study, we selected PZT-5H as the piezoelectric layer due to its outstanding stability. However, in comparison to single crystal materials such as PMN-PT and PIN-PMN-PT, PZT-5H exhibits a higher insertion loss. Furthermore, while the spatial resolution achieved with the proposed ultrasound transducer is of value, it falls short of matching the resolution capabilities of OCT. Nevertheless, our design offers a low-complexity and miniature approach for intravascular imaging compared to an OCT-IVUS hybrid system, which addresses the need for practical and accessible imaging solutions in certain clinical scenarios.For the comparison group of single-element ultrasound transducers with center frequencies of 30 MHz and 80 MHz, in vitro wire phantom imaging experiments were conducted under identical experimental conditions to assess and compare the imaging resolution achieved by the different transducers. The results of these imaging experiments are presented in This work is the first to present a backing-layer-shared dual-frequency ultrasound probe with a single coaxial cable interconnection for potential IVUS imaging applications. The proposed dual-frequency ultrasound probe not only features both high IVUS imaging resolution and deep penetration depth, but also fits the IVUS probe’s strict size constraints for clinical applications as well as reduces the interconnection complexity in IVUS probes. The dual-frequency ultrasound transducer was designed, fabricated, and characterized, which had center frequencies of 30 MHz and 80 MHz, respectively. The aperture size of both the low-frequency transducer element and the high-frequency element was 0.5 mm × 0.5 mm. The −6 dB bandwidth of the low-frequency transducer element and the high-frequency element was 62% and 51%, respectively. In vitro phantom imaging experiments demonstrated that the low-frequency transducer element achieved spatial resolutions of 40 µm axially and 321 µm laterally, while the high-frequency transducer element exhibited axial and lateral resolutions of 17 µm and 247 µm, respectively. Ex vivo porcine coronary artery imaging experiments validated the IVUS imaging capability of the developed probe. The quantitative results presented in this work provide a complete initial demonstration of future potential of the backing-layer-shared dual-frequency ultrasound probe. In the future, we anticipate that the backing-layer-shared dual-frequency ultrasound probe will open up new avenues for IVUS imaging applications. Further research directions include optimizing the probe’s design and exploring its potential for in vivo imaging to ensure its compatibility with clinical settings. By contributing to refine and develop the backing-layer-shared dual-frequency ultrasound probe, we aim to enhance its performance and expand its applicability, ultimately contributing to the advancement of IVUS imaging in clinical practice.


The COVID-19 global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has infected hundreds of millions of individuals. Following COVID-19 infection, a subset can develop a wide range of chronic symptoms affecting diverse organ systems referred to as post-acute sequelae of SARS-CoV-2 infection (PASC), also known as long COVID. A National Institutes of Health-sponsored initiative, RECOVER: Researching COVID to Enhance Recovery, has sought to understand the basis of long COVID in a large cohort. Given the range of symptoms that occur in long COVID, the mechanisms that may underlie these diverse symptoms may also be diverse. In this review, we focus on the emerging literature supporting the role(s) that viral persistence or reactivation of viruses may play in PASC. Persistence of SARS-CoV-2 RNA or antigens is reported in some organs, yet the mechanism by which they do so and how they may be associated with pathogenic immune responses is unclear. Understanding the mechanisms of persistence of RNA, antigen or other reactivated viruses and how they may relate to specific inflammatory responses that drive symptoms of PASC may provide a rationale for treatment. The Mechanistic Pathways task force within the National Institutes of Health Researching COVID to Enhance Recovery (RECOVER) consortium seeks a mechanistic understanding of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC), also known as ‘long COVID,’ to guide treatments. In a majority of individuals infected with SARS-CoV-2, live virus is fully cleared within days to a few weeks after infection and no longer detectable in the respiratory system. However, resolution of viral RNA or antigen from the respiratory epithelia or other tissue sites can be slow, and in some cases viruses may persist in forms that are not well understood. Fundamental questions regarding the relationship between persistence of SARS-CoV-2 and longevity of symptoms of PASC are unresolved. SARS-CoV-2 infection can result in long-term symptoms even if the infection is mild or asymptomatic. There is a wide range of PASC symptoms that can affect different organ systems, including cardiac, respiratory, and neurological processes. Most clinical monitoring of the virus has been conducted in the respiratory tract, although other compartments have been found to harbor SARS-CoV-2. Interestingly, inflammatory responses to SARS-CoV-2 infection can co-exist with re-activation of herpesvirus infections, such as Epstein–Barr virus (EBV). In particular, EBV has been suggested to be associated with chronic fatigue, brain fog, or other symptoms that may resemble PASC symptoms. In fact, infection with other viral or bacterial pathogens has been linked to the development of chronic symptoms in a subset of infected individuals . Viral pThe subcommittee identified two priority areas of research with several subtopics see  that maySARS-CoV-2 primarily infects individuals through the respiratory epithelium by entering cells that carry the ACE-2 receptor and TMPRSS2 coreceptor in the nasal or upper respiratory epithelium . DiverseSARS-CoV-2 RNA can persist for many weeks in the respiratory tract of individuals that have recovered clinically from COVID-19 , though Little is known regarding the presence of SARS-CoV-2 viral particles when RNA for SARS-CoV-2 is detectable. Is persisting virus replicating or non-replicating? Most studies that address this issue have been designed to examine the infectiousness of individuals whose fluids test positive for viral RNA. The ability to culture virus from secretions generally is limited to the earlier phases of recovery , except In peripheral blood monocytes, persistence of S1 antigen has been detected by antibody and mass spectrometry in 4 out of 11 severe COVID-19 patients and 1 out of 26 PASC patients, in some cases up to 15 months post infection. In this study, only fragmented RNA could be detected, suggesting that the antigen is not being expressed actively from these cells . Viral RAnalysis of biopsies from the gastrointestinal tract by immunofluorescence against S and by PCR suggested that antigen persisted in the small bowel in 7 of 14 individuals who were asymptomatic at 4 months after the onset of coronavirus disease . In patiThe typical half-life of mRNA in the cell is generally thought to be short lived, measured in minutes to hours rather than months or years, and there are not thought to be major exceptions for specific RNAs . Thus, tRepeated antigen exposure is a critical component for the induction of robust and durable adaptive immune responses. In fact, antigen-specific T and B cell populations usually contract once the inducing antigen is cleared. Ongoing evolution of antigen-specific immunity can therefore be evidence for chronic and/or latent infection or persistent antigen presence in the absence of active viral replication, resulting in chronic stimulation of adaptive immune responses. There is a comprehensive body of evidence suggesting that titers of IgM and IgG antibodies against the receptor-binding domain (RBD) of the spike protein of SARS-CoV-2 significantly decrease over time while SARS-CoV-2-specific CD4+ and CD8+ T cell response remain more stable . In contSevere COVID-19 can result in decreased frequencies and functional exhaustion of antiviral cytotoxic lymphocytes, including cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells, as well as diminished frequencies of plasmacytoid dendritic cells (pDCs) . In factInnate immune responses in PASC are complex and subject of ongoing in-depth studies. Multiple studies have demonstrated that antibodies generated against cytokines and chemokines correlate with COVID-19 severity and PASC, but a clear consensus on when these responses are protective or pathogenic has been elusive. It appears likely that early type I IFN responses are required for protection against severe acute disease, but delayed responses could be pathogenic . ChronicMany instances of long-term shedding of SARS-CoV-2 have been reported, even after resolution of symptomatic disease. It is possible that chronic production of live virus, viral RNA, or viral protein could lead to onset of PASC, as mentioned above. If this association is found, then monitoring patients post-infection for shedding would be a first step in identifying those at highest risk for long-term disease for potential intervention. Some efforts have been made to determine whether there is a correlation with PASC and viral shedding. One study reported that there was no association of SARS-CoV-2 shedding in saliva and onset of PASC . Viral RTherefore, several questions remain regarding long-term SARS-CoV-2 shedding and PASC. First and foremost, is there a clear association between the two? One consideration in answering this question lies on the site of sample acquisition for viral shedding. Nasal swabs or saliva are the most accessible samples for monitoring long-term shedding, but it is possible that long-term viral shedding that occurs in the tissue(s) affected by PASC could be more informative. Furthermore, the nature of long-term SARS-CoV-2 shedding needs clarification: does long-term shedding represent only non-infectious genomic RNA or long-lived viral protein, or does it include live virus replication? Understanding the nature and location of long-term SARS-CoV-2 shedding could lead to insights with potential correlative effects with PASC onset.In some viral infections, antibodies that bind but do not neutralize the virus lead to antibody-dependent enhancement (ADE), a process that increases viral invasion of cells and leads to more severe pathogenesis  and respiratory syncytial virus (RSV) . ADE canBack-boosting of antibodies that recognize seasonal coronaviruses has been recognized early in the pandemic  with oneacute SARS-CoV-2 infection  involved in this process. Understanding of this mechanism is the first step in identifying potential interventions in at-risk individuals. Known mechanisms of EBV reactivation in non-COVID settings include host/viral miRNAs , other vReactivation of latent viruses has been linked to the dysregulation of the host immune response during acute SARS-CoV-2 infection, that is, by disabling the host type I interferon response via autoantibodies , resultiIdentifying effective treatments for PASC and its many manifestations will be greatly aided by a better understanding of the role that viral persistence plays in different patients. Given the ability of coronaviruses to infect and reinfect individuals over a lifetime, viral persistence seems likely to play a role in PASC. There is ample evidence for persistence of SARS-CoV-2 viral RNA and proteins in several tissues, including respiratory tract, GI tract, olfactory mucosa, and the central nervous system. The mechanisms of persistence may involve replication or the action of viral replication machinery; however, exactly how viral components persist in individuals is still unclear. If persistence of antigen requires viral polymerase or protease, this provides a strong rationale for testing antivirals in patients. If the persistence is fully independent of replication, then it may be that vaccines that target more diverse genetic targets or other immunomodulators may be beneficial in targeting persistent virus.The presence of persistent viral antigen and RNA may be the result of incomplete immunity where holes in the immune response permit viral persistence, but there also appears to be evidence that persistent inflammation as a reaction to persistent antigen is causing pathology. A deeper understanding of the adaptive immune responses, including T-cell and B-cell responses, may provide rationales for targeted therapies either to enhance clearance of persistent antigens, or to limit persistent inflammatory responses that are causing damage.The evidence for reactivation of other latent viruses also appears to be implicated; these provide a rationale for more extended testing for reactivation of EBV and other viruses during PASC or similar post-viral syndromes. Treatment of these viral co-infections may also provide an avenue for therapeutic trials where evidence of persistent viral activation is present.A major challenge of the treatment of PASC is that it appears to be a highly diverse condition, potentially with several different pathogenetic mechanisms that each will require a distinct treatment approach. Tissue sampling and studies are also particularly important to have a true understanding of the presence and role of viral persistence. Deeper explorations of the mechanisms of viral persistence should aid in the design of clinical trials to match symptoms with trials of drugs that can target specific pathogenic pathways. Studies such as RECOVER that have comprehensive and longitudinal patient data and samples can help answer some of the questions raised above.


It is crucial to estimate the duration of SARS-CoV-2 shedding to inform public health interventions. We aimed to estimate viral shedding time among laboratory-confirmed COVID-19 cases in South Africa.we analyzed COVID-19 PCR results from 5 March to 31 December 2020. We included cases with at least 2 consecutive positive PCR tests and a subsequent negative test. We performed multiple linear regression to determine the association between shedding time and predictor variables . We included 2752 cases that met the inclusion criteria.about 39.9% (1099/2752) of participants were inpatients and 60.1% (1653/2752) were outpatients. The median shedding time was 17 days (range: 1-128). There was no difference in shedding time between males and females and between hospitalized patients and outpatients. Individuals aged 0-4 years had the lowest shedding time . After adjusting for age, sex and province, shedding time was shorter for hospitalized patients compared to outpatients . Six provinces  had a significant association with shedding time.the duration of viral shedding within our population varies from 1-128 days. Although prolonged shedding might not necessarily indicate infectiousness, individual patient monitoring and management are needed for patients with prolonged shedding. Further studies are required to explore the association between comorbidities and SARS-CoV-2 shedding time. Coronavirus disease 2019 (COVID-19) is an illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) . DespiteDuring the study period (March - December 2020), three COVID-19 variants  were dominant variants of concern that were circulating in South Africa. Currently, there is no effective treatment available for COVID-19 patients. With little known about SARS-CoV-2, clinical trials are being conducted on different treatment options however, there is no strong evidence of improved health outcomes . In 2020Viral shedding time is a useful guide for infectivity and can be used to establish the duration of isolation, and quarantine and inform contact tracing guidelines ,8. With South Africa has reported the highest number of SAR-CoV-2 infections in Africa. Numerous studies have been conducted globally to estimate the duration of SARS-CoV-2 viral shedding however, no study has estimated viral shedding time for laboratory-confirmed COVID-19 cases in the South African population. Given the rapid spread of the virus, limited information, and treatment options, preventative measures such as quarantine are very important in reducing infections, mortality, and the burden on the health system. South Africa is of particular importance due to its unique epidemiological profile consisting of high HIV/AIDS prevalence, high Tuberculosis incidence, and high death rates from non-communicable diseases such as diabetes.Since there is no routine test available to measure infectiousness, determining infectiousness, determining viral shedding time, and understanding the associated predictors will play a significant role in informing infection prevention and control measures in COVID-19 patients. This information could be used to understand the association between viral shedding and infectivity and the effectiveness of using a PCR test for infectiousness or re-infection. The results from this study can assist in refining infection control strategies such as clinical management of COVID-19 patients, contact tracing and isolation or quarantine, and in understanding the potential difference of positive PCR tests over time. Clinical management is important in improving health outcomes and quality of care to infected patients. This study aimed to estimate viral shedding time among laboratory-confirmed COVID-19 cases in South Africa.Study design and procedures: we performed a cross-sectional analytic study using COVID-19 data obtained from the COVID-19 Notifiable Medical Condition List (NMCList). The study included laboratory results from public and private clinical laboratories in South Africa that reported COVID-19 test results to the NMCList database. The study population consisted of all laboratory-confirmed COVID-19 patients reported to the NMCList database from March to December 2020. We included all laboratory-confirmed COVID-19 patients who had at least two positive PCR test results and subsequently tested negative. The maximum period between the last positive test and the negative test should be 7 days. The person should have done consecutive testing no longer than 14 days between the repeat positive PCR tests. We excluded positive cases that were tested using antigen tests and cases that took a repeat test after 14 days of continuing positivity.Data sources: COVID-19 test results were reported to the NMCList database hosted by the National Institute for Communicable Diseases (NICD). COVID-19 is a category 1 Notifiable Medical Condition (NMC) with a requirement of immediate reporting upon clinical suspicion or laboratory diagnosis followed by a written notification within 24 hours. Clinical data of patients tested for COVID-19 are collected using the NMC reporting platform, which is a national reporting system in South Africa. Both RT-PCR and antigen COVID-19 test results are stored in the NMCList database and reported to the National Department of Health (NDoH). Individuals who have multiple test results are identified using a unique identifier (case_id). Other variables stored in the NMCList include personal identifiers , demographic information , and health facility information. Data from the NMCList is stored in the NICD surveillance data warehouse. The DATCOV system is an active, prospective sentinel surveillance program for COVID-19 in South Africa. This online platform enables private and public healthcare facilities to submit hospital admissions data for COVID-19 patients. COVID-19 admissions trends are monitored and the epidemiology of the disease in hospitalized patients within the country is described. Admission status  was used as a proxy to determine disease severity. Hospitalized patients were defined as patients with severe disease and outpatients as patients with mild disease.Data collection: we extracted data from the NMCList and DATCOV databases. It was assumed that COVID-19 cases that were not in the DATCOV database were not hospitalized. We applied a deterministic method to identify repeat test results from the same individuals and to link patients between the NMCList and DATCOV databases. The patients´ national identity or passport number was used as the linking variable. The linkage helped us determine patients who were admitted and those who were not.Case definitions: COVID-19 case: “a confirmed case of COVID-19 is a person with laboratory confirmation of SARS-CoV-2 infection (using an RT-PCR assay), irrespective of clinical signs and symptoms between March and December 2020” [er 2020” . NegativOutcome variable: the outcome variable is COVID-19 viral shedding time measured in days. Viral shedding time (days) was defined as the period from the date of specimen collection for the first positive PCR test to the date of specimen collection for the last positive test prior to the first negative PCR test. The date of specimen collection for the first positive test was subtracted from the date of specimen collection for the last positive test to obtain the shedding time (in days). The date of onset of viral shedding was defined as the day the specimen of a case was collected since laboratory data had no variable for the date of symptoms onset. This approach catered to individuals who would have been symptomatic or asymptomatic. Explanatory variables included sex, age, province, number of tests done and the severity of COVID-19 (inpatient versus outpatient). The defaults were selected based on the literature.Statistical analysis: data were analyzed using STATA 15 . Characteristics of study participants were reported using descriptive statistics. Categorical variables  were presented using absolute numbers and percentages. Normally distributed continuous variables (age) were reported using means and standard deviations while medians and ranges were used when continuous variables were not normally distributed (shedding time). Initially, simple linear regression was done to assess the association between the dependent variable (shedding time) and each predictor variable. Predictor variables with a p-value of <0.1 from the simple linear regression were added to the multiple linear regression model. We determined differences in shedding time by age, sex, hospital admission status, and province. We reported effect estimates and 95% confidence intervals. We considered a p-value of less than 0.05 as statistically significant.Ethical considerations: the study was conducted in accordance with the Declaration of Helsinki and approved by the Human Research Ethics Committee at the University of the Witwatersrand (Clearance Certificate No. M210443).Characteristics of the study population: there were 1 057 161 COVID-19 cases reported from 5 March to 31 December 2020 in South Africa. Out of these cases, 2752 (0.26%) met the inclusion criteria. Shedding time in COVID-19 patients:In This study aimed to estimate the viral shedding time among laboratory-confirmed COVID-19 cases in South Africa. Understanding SARS-CoV-2 shedding time is important for determining effective public health interventions such as the duration of isolation and wearing of masks. Viral shedding can be used as a proxy for infectivity, therefore is important for the clinical management of COVID-19 cases. We found that the median shedding time in our sample was 17 days from the symptom onset date or date of specimen collection. Shedding time ranged from 1 to 128 days. Our study showed a 1-day difference in the median shedding time between males and females and between inpatients and outpatients. We also found a slight difference in shedding time between age groups.A study conducted on the Canadian population  found thAge group 0-14 years had a median shedding time of 14 days which was the lowest among other age groups. Age group 25-34 reported the highest shedding time with a median shedding time of 18 days. The slight difference in shedding time between age groups might be because people live in families and communities where people of different age groups live together, allowing for transmission to happen within different age groups. Our study found that South African children had a lower shedding time compared to children in South Korea who were reported to have an average shedding time of 17.6 days . AnotherChildren and young adults are more likely to have mild disease and less likely to have severe or fatal COVID-19 compared to adults . The ageViral shedding can continue for longer periods in some patients. Two cases had a shedding time greater than 100 days. The cases were a 77-year-old inpatient male who shed the virus for 108 days and a 34-year-old outpatient male who shed the virus for up to 128 days. A study of 38 COVID-19 patients with prolonged shedding reported that the longest shedding time they observed was 118 days and was a 77-year-old male . AlthougOlder adults usually have a higher prevalence of comorbidities, such as obesity, hypertension, and heart disease, which are associated with severe COVID-19 compared to children . AlthougTherefore, it is important to monitor viral shedding in outpatients or patients with mild disease because they can shed the virus longer and could potentially be a source of future COVID-19 outbreaks. Our findings indicate that infection control strategies provided by the CDC and the NDoH should take into account prolonged shedding and its impact on disease transmission. Our study found a significant association between inpatients and shedding time. Inpatients had 1 day less shedding time compared to outpatients. Based on our results, it is important for patients with mild disease or asymptomatic patients to follow public health interventions such as quarantine and wearing of masks as recommended. Studies show that COVID-19 patients who are hospitalized usually have COVID-19 symptoms, and comorbidities and are more likely to be older -38. It wSeveral studies have reported no association between viral shedding time and sex ,40,41. TThe strengths of our study include the following: We used data from the whole population with COVID-19 to estimate shedding time. Also, we included both inpatients and outpatients which allowed us to estimate the difference in shedding time within the two groups. We only used test results that were tested using PCR-test which is the gold standard. This is essential for accurate results thus ensuring that negative tests were correctly identified therefore giving accurate estimates of shedding duration. With limited treatment options during the study period, our results may be used to understand the viral shedding duration and factors associated with viral shedding. This information may be used to strengthen surveillance and facilitate early intervention which will reduce disease transmission.Our study had some limitations. Firstly, data received from the NMCList did not include clinical information about the cases. Secondly, due to the secondary nature of the study, we could not get certain variables that could have assisted in determining other factors affecting shedding time within the population. Also, we could not analyze the impact of vaccines and treatment on shedding time. Thirdly, due to the exclusion of patients with a single positive result, selection bias could have been introduced, which might have also affected external validity, thereby potentially compromising the generalizability of our findings. Lastly, our study was retrospective and contained a relatively small sample size however, the results may be useful in understanding the transmission dynamics of COVID-19. Therefore, we recommend that a similar study should be conducted on a larger sample. Viral shedding before symptom onset and before testing was not measurable using the data we obtained. It is likely that viral shedding occurs beyond the time points we have described. It is also possible that the shedding time presented in our study is likely to be an underestimate of the true shedding time in the population.Our study found a significant association between the hospital admission status of COVID-19 patients and shedding time. There was a 1-day difference in shedding time between inpatients and outpatients. Therefore, there is a need to strengthen prevention and control strategies such as contact tracing as both inpatients and outpatients can shed the virus for a similar duration. We discovered that factors such as age and sex were not associated with shedding time. The duration of viral shedding within the population of South Africa varies from 1 to 128 days. Although prolonged shedding might not necessarily indicate infectiousness, individual patient monitoring and management are needed for patients with prolonged shedding. Furthermore, to control SARS-CoV-2 infection, different approaches to effectively address transmission risk in asymptomatic patients are required.Our study only looked at four predictor variables . We recommend that further studies be conducted, including more variables such as comorbidities, socio-economic status, level of education and vaccination status. Since continuous positivity might not necessarily mean infectivity, we recommend that future studies consider evaluating live viruses within the population and do a follow-up on cases with prolonged shedding to assess their contacts. This can assist in figuring out infectivity and can be used to inform isolation and quarantine requirements. We also recommend that studies evaluate the impacts of possible symptom recrudescence on shedding time and its impacts on SARS-COV-2 transmission.COVID-19 is an infectious disease transmitted from person to person by small droplets or contact with contaminated surfaces;COVID-19 can mutate, causing variants that could be more infectious and could lead to severe disease.This study reports on viral shedding time in COVID-19 patients in the South African population in 2020 before the introduction of the COVID-19 vaccines;The study shows factors associated with shedding time in the population;The findings in this paper could assist other researchers to understand the transmission dynamics of SARS-CoV-2 in a low-income country and use the information for public health interventions.


Despite the LGBTQ+ population facing higher mental health risks, there has been a dearth of research focusing on developing tailored interventions targeting them. This study aimed to assess the effectiveness of a digital multicomponent intervention in promoting help-seeking for mental health issues in LGBTQ+ young adults.LGBTQ+ community’s higher susceptibility to worse mental health outcomes and more help-seeking barriers compared to the n = 144) were stratified by gender assigned at birth  and randomly allocated (1:1 ratio) to the intervention or active control parallel condition by generating a random number table, so they were blinded to the intervention condition. All participants received online psychoeducational videos, online facilitator-led group discussions, and electronic brochures in December 2021 and January 2022, with the final follow-up in April 2022. The contents of the video, discussion, and brochure are help-seeking for the intervention group and general mental health knowledge for the control group. The primary outcomes were help-seeking intentions for emotional problems and suicidal ideation and attitudes toward seeking help from mental health professionals at the 1-month follow-up. The analysis was performed by including all participants based on their randomized group regardless of adherence to the protocol. A linear mixed model (LMM) was used for analysis. All models were adjusted for baseline scores. Chinese Clinical Trial Registry: ChiCTR2100053248.We recruited LGBTQ+ young adults aged between 18 and 29 who scored moderate or above on at least 1 dimension of the Depression Anxiety Stress Scale 21 and did not have help-seeking experiences in the past 12 months. Participants (n = 72), a significant improvement was found in help-seeking intentions for suicidal ideation in the intervention group (n = 70) at post-discussion , 1-month , and 3-month follow-ups . There was also a significant improvement in the intervention condition on the help-seeking intention for emotional problems at 1-month  and 3-month follow-ups  compared with the control group. Participants’ depression and anxiety literacy and help-seeking encouragement related knowledge in intervention conditions showed significant improvements. There were no significant improvements in actual help-seeking behaviors, self-stigma toward seeking professional assistance, depression, and anxiety symptoms. No adverse events or side effects were observed. However, the follow-up time point was limited to 3 months which might not be long enough for drastic mindset and behavioral changes in help-seeking to occur.A total of 137 (95.1%) participants completed a 3-month follow-up, and 4 participants from the intervention condition and 3 from the control condition did not complete the final survey. Compared with the control group (The current intervention was an effective approach in promoting help-seeking intentions, mental health literacy, and help-seeking encouragement-related knowledge. Its brief yet integrated intervention format could also be utilized in treating other imminent concerns confronted by LGBTQ+ young adults.Chictr.org.cn, ChiCTR2100053248. In a randomized controlled trial, Runsen Chen and colleagues investigate the impact of a multi-component digital intervention to promote help-seeking for mental health problems and suicide in sexual and gender diverse young adults. cis-heterosexual counterparts, are less likely to seek help for mental problems due to minority stress, stigma, and difficulty in acquiring sexual- and gender-affirmative care.Members of the LGBTQ+ community, compared to their Findings from past studies suggest that psychoeducational videos, facilitator-led group discussions, and help-seeking brochures are all key influential factors for individuals’ help-seeking.Nevertheless, few studies have investigated the effectiveness of multicomponent approaches and digital online-based interventions targeted at LGBTQ+ young adults’ help-seeking behaviors.We conducted a single-blind parallel-group randomized control trial to evaluate the efficacy of a digital online-based multicomponent intervention in promoting help-seeking among LGBTQ+ young adults with mental health problems.We included 144 participants recruited between December 3, 2021 and January 12, 2022 through online platforms who had no help-seeking experience within the past 12 months.We randomized 72 participants to the help-seeking promoting condition and compared them to 72 who received general health knowledge condition. The study was conducted over 5 months.Our findings indicated that an integrated intervention that combines psychoeducational videos, facilitator-led group discussions, and help-seeking brochures was effective in improving LGBTQ+ young adults’ general help-seeking intentions.Our study offers preliminary evidence that digital interventions can improve help-seeking for LGBTQ+ young adults with mental health difficulties.Integration of digital interventions by policymakers to care provided to LGBTQ+ young adults may help to improve help-seeking and mental health outcomes on a wider societal level. Such cidality ,6,7. Forcidality ,9.The minority stress model accentuates that the barriers resulting in the LGBTQ+ population’s reluctance to help-seeking can be categorized into distal and proximal stressors ,10,11. Fcis-heterosexual population, there is little research targeting the LGBTQ+ population that utilizes an integrated approach with the aim to promote all 3 outcomes, leaving a critical gap in the literature. Specifically, 1 randomized clinical trial that centered on promoting LGBTQ+ individuals’ help-seeking was conducted in a German setting, with its emphasis on difficulties related to “coming out” [To our best knowledge, despite much research on promoting help-seeking intentions, improving help-seeking attitudes, and encouraging actual help-seeking behaviors in the ing out” . The stuing out” . Furthering out” .It is an important objective to improve LGBTQ+ young adults help-seeking for mental health conditions. It is equally important to improve their attitude and intention toward help-seeking from both professionals and the general population . Seekingcis-heterosexual population, resulting in a gap in the literature that the current study aims to fill [The World Health Organization (WHO) postulates that mobile technology health interventions are featured by the effective utilization of mobile technologies to meet the unmet needs of traditional health service delivery . As prev to fill .Given the absence of research in promoting the LGBTQ+ population’s help-seeking intentions and attitudes using a digital online-based multicomponent approach, the present study sought to test the potential efficacy of this intervention. We employed a control condition in which participants would undergo the same intervention process with the same online format and time length while no mental help-seeking contents  in the intervention condition were involved. This study examined the efficacy of the digital online-based multicomponent help-seeking intervention targeting the LGBTQ+ population by comparing results of primary outcomes  and secondary outcomes  from participants in the intervention condition against the control condition.We conducted this single-blind parallel-group superiority randomized controlled trial to demonstrate the effectiveness of a brief digital online-based multicomponent intervention to promote help-seeking in LGBTQ+ young adults. The present study is reported in accordance with the Consolidated Standards of Reporting Trials (CONSORT) guideline  code on the advertisement poster, participants who were willing to join the study answered the screening questionnaire and provided their contact numbers. Participants aged between 18 and 29 years old who self-identified as a member of the LGBTQ+ community were eligible to participate if they were living in China, had stable internet connections, scored moderate or above on at least 1 dimension  of the Depression Anxiety Stress Scale 21 ,33, and Participants were excluded if they met one or more of the following criteria: had a history of being diagnosed with psychotic disorder, such as schizophrenia; have had suicidal attempt(s) in the last 6 months; currently have severe suicide ideations; could not complete all assessments and intervention procedures in a quiet, undisturbed space; or had help-seeking experience(s) from MHPs in the past 12 months. Participants have a one-to-one telephone conversation with a researcher to confirm whether they meet the inclusion and exclusion criteria.Participants who met the study criteria went through the one-to-one consent-informing phase with one of the researchers via phone again. The electronic consent was sent to participants, and pictures of the handwritten signed consent or e-signature consent were returned to the researchers. Participants were recruited in 2 time periods: 80 participants were enrolled in December 2021, and 64 participants were enrolled in January 2022. All enrolled participants provided informed consent in written format. Participants have the right to withdraw their informed consent without reason at any time during the intervention and follow-up period, and their data will not be used in the analysis.First, a random number table was generated by a researcher who was not involved in the intervention using IBM SPSS Statistics version 26.0. Each participant was assigned a unique number in the order of enrolling in the study. Then, the unique number of participants was separated from other information and sent to the researcher who generated the random number table, and this researcher, using the random number table, assigned participants to intervention or control condition. In this process, this researcher will not be exposed to other personal information of participants. Even though the recruitment of participants is divided into 2 periods, because the unified random number table generated in advance is used, the randomization process was guaranteed to be single-random.A total of 144 participants who signed the informed consent form were stratified by gender assigned at birth  and then randomly allocated (1:1) to the experimental or control condition. Participants were masked to their group assignment, although they were informed of the existence of another group. The unified numbering procedure for all participants was used to minimize the possibility of participants knowing their groups according to the assigned number. Due to the nature of the present study, masking the study group facilitators was impossible. Nevertheless, we minimized the experimenter effect by having 3 group facilitators assigned to the experimental and control conditions, respectively.Following randomization, participants were asked to complete the online baseline questionnaire and to choose their time slots to participate in the group discussion based on their schedules. Researchers then grouped participants according to their selected time slots. Each group, consisting of 4 to 6 participants, was assigned 1 researcher as the group facilitator to help participants complete all the intervention procedures. The entire intervention was conducted on an online video conferencing platform . Each participant received the encrypted online meeting link of one’s group and was notified to attend the meeting as scheduled. Due to the sudden changes in the schedules or dropouts, there were 2 groups that had only 3 participants.This digital online-based intervention has incorporated 3 key therapeutic components, including (1) online animated psychoeducational videos ; (2) onlThe current intervention was developed by the study team. Regarding the intervention videos, 5 modules in the intervention video were all presented from the perspective of LGBTQ+ populations, and the characters used were LGBTQ+ friendly. The intervention video also contains LGBTQ+-friendly doctors and practitioners in the psychology and psychiatry fields and 2 role models from the LGBTQ+ community . Regarding facilitator-led group discussions, structured interview guidelines were created by the supervisor of the project and were printed out during group discussions. During facilitator-led group discussions, 3 facilitators acquired participants’ verbal consent and introduced confidentiality to them. The help-seeking brochure was graphically designed by one of the research assistants. Its content included LGBTQ+-friendly knowledge and help-seeking resources. As mentioned in our study protocol , all matRegarding the intervention process, group facilitators delivered this brief digital online-based multicomponent intervention by leading participants in completing the following 3 essential steps: (1) watching the entire 15-min intervention video  with other group members in the online conference room; (2) actively participating in the structured discussions regarding intervention video and electronic psychoeducational brochure with other participants in the online conference room; and (3) freely accessing and reviewing the intervention video and electronic brochure post-discussion via web link given.All 3 facilitators of the current study had a master’s degree in psychology and received 7 times internal training (2 to 3 h for each training) from 2 senior researchers  before the start of the study (see investigators training section in appendix). The intervention process was recorded and checked to ensure intervention fidelity. Two senior researchers listened to the recordings of the intervention procedure independently and evaluated the fidelity of facilitators. The fidelity evaluation using a list developed by the research team, which included 6 items assessing video fluency, facilitators’ involvement, facilitators’ friendliness, participants’ activity, participants’ emotional involvement, and the overall evaluation of the process. Each item scored 0 to 5, using the average score of 6 items to evaluate the completion of a group discussion. Two senior researchers each listened to 6 recordings, including 3 intervention group recordings and 3 control group recordings from 3 facilitators, respectively. The average fidelity scores given by the 2 senior researchers were from 4.58 to 4.67 (full score of 5 points).Qualtrics.com but can store videos and contents for guest viewing and downloading through the online address and password sent out by the researchers), during the course of the study. The electronic psychoeducational brochures for both conditions were sent out by researchers to participants directly for them to save and view at any moment during their free time. After group discussion and a brief introduction of the brochure, participants in the experimental and the control conditions were asked to complete an online post-discussion questionnaire. Participants were also asked to complete online questionnaires at 1-month and 3-month follow-ups. If participants did not reply within 5 days of receiving the online questionnaire link, they would receive a reminder text asking them to complete the questionnaire as soon as possible. If participants still did not reply within 2 days after the reminder, they would be marked as lost to follow up at this time point. Participants in the control condition also received the intervention video and psychoeducational brochure same as the intervention condition after the 3-month follow-up.Intervention videos for both conditions were safely stored in a password-protected online server at Wenjuanxing, a Chinese online survey platform .The primary outcomes were participants’ changes in general help-seeking intentions for emotional problems and suicidal ideation and attitudes toward seeking help from MHPs between baseline and 1-month follow-up. The general help-seeking intentions were measured by the General Help-Seeking Questionnaire (GHSQ), the validity of which in Chinese participants had been validated by previous research . GHSQ coParticipants’ changes in general help-seeking intentions for emotional problems and suicidal ideation and attitudes toward seeking help from MHPs between baseline and post-discussion and 3-month post-intervention were defined as the secondary outcomes. Other secondary outcomes included participants’ actual help-seeking behaviors measured by the Chinese validated version of the Actual Help-Seeking Questionnaire (AHSQ) , particiSince the GHSQ and AHSQ have the “not applicable” option, these 2 variables used the average value of valid items for analysis, while other variables used the total score. According to previous research, we did the additional analysis of the GHSQ by dichotomizing responses into “0” for “Highly unlikely” and “Unlikely,” and “1” for “Highly likely” and “Likely” .n = 144), assuming 20% attrition and a 1:1 allocation ratio during randomization [Based on previous research, moderate effect sizes of help-seeking intentions (Cohen’s d = 0.53) and help-seeking attitudes (Cohen’s d = 0.58) were expected for the present study’s primary outcomes . The sammization , which wAnalyses for both primary and secondary outcomes were done from the following time points, respectively: (1) post-discussion; (2) 1-month follow-up; and (3) 3-month follow-up, with the exception of actual help-seeking behaviors of participants, which did not include the post-discussion measurement time point. The analysis was performed by including all participants based on their randomized group regardless of adherence to the protocol. The missing data was not processed since it is less than 5%. We used linear mixed model (LMM) to analyze the difference between the intervention effect on the primary outcomes and secondary outcomes, with the baseline score included as a covariate. The fixed effects included intervention, time of assessment, and interactions. The random intercepts of participants were considered in the random effects of the models, and all models were estimated using maximum-likelihood estimation methods.t test as a measure to investigate whether there were differences in participants’ evaluations of intervention quality between the intervention and control conditions. All statistical analyses were performed with IBM SPSS Statistics version 26.0 and R software version 4.2. The significance level of each analysis will be set to 0.05 while simultaneously reporting a 95% confidence interval. Considering the accuracy and robustness of the results, we have modified the analytical procedures mentioned in our protocol. Firstly, considering the multiple primary outcomes leading to a higher type I error rate, we used the Bonferroni correction method to adjust the P value of the 3 primary outcomes. Furthermore, we added a sensitivity analysis for all outcomes in the Appendix , and the results were presented in the Appendix . In addiAppendix , which pn = 144), recruitment was discontinued. During the post-discussion phase, 2 participants in the intervention condition withdrew their written consent and dropped out of the study, leaving 142 participants for primary analyses, and 139 out of 142 participants completed the intervention procedure, with 3 participants in the control condition dropping out before the start of the intervention. One participant in the intervention condition did not successfully submit baseline data, and 138 (95.8%) of 144 participants had successfully completed the 1-month follow-up questionnaire, and 137 (95.1%) of 144 participants had completed the 3-month follow-up questionnaire  (p = 0.013)  . For the= 0.013) . However= 0.013) .p = 0.005) and 3-month follow-up . For the help-seeking intention of emotional issues, the intervention effect showed a significant improvement at 3-month follow-ups  and no significant improvement at post-discussion .For secondary outcomes, results showed that compared with the control condition, participants in the intervention condition had a significant improvement in the help-seeking intention of suicidal ideation at post-discussion  and 1-month follow-up . It was also worth noting that such intervention effect remained strongly significant at the 3-month follow-up . Furthermore, participants’ help-seeking encouragement-related knowledge had significant improvement at post-discussion, 1-month follow-up, and 3-month follow-up .For other secondary outcomes, there was no significant improvement in help-seeking behaviors and professional help-seeking stigma. Regarding the results of depression and anxiety literacy, participants in the intervention condition showed significantly improved depression and anxiety literacy at post-discussion  were observed between conditions in this study . The resThis randomized controlled trial aimed to examine the efficacy of a digital online-based multicomponent intervention promoting help-seeking in LGBTQ+ young adults with mental health problems. Compared to the control condition, participants who received the intervention showed improvements in general help-seeking intentions for both emotional problems and suicidal ideations. The significant differences at the primary time points (1-month follow-up) prove that the intervention program of the current study is effective. The mean differences between groups of help-seeking intention between baseline and 1-month follow-up were 0.17 for emotional problems and 0.19 for suicidal ideation. Compared with other similar studies ,47, the There is no cut-off value of the current scales used to assess the intentions of help-seeking ,47. We bAside from the improvements mentioned above, the intervention did not significantly promote participants’ professional help-seeking attitude and reduce participants’ help-seeking stigma. One potential explanation of these findings could be that the intricate connection between professional help-seeking attitude and help-seeking stigma has formulated a vicious cycle, blocking the intervention effect. Previous research indicated that help-seeking from LGBTQ+ individuals to professionals was deemed undesirable by the LGBTQ+ community in China due to the common idea embedded in the community culture that “help from each other (peer support)” could be more helpful compared to taking the risk of facing invalidation, discrimination, and prejudice to meet non-affirmative professionals, contributing to negative professional help-seeking attitudes and less motivation to seek help when in need ,37,48–51We also found the scores of primary outcomes of participants in the control condition increased over time. One possible explanation is that participants in the control condition have the placebo effect. That is, participants think they have accepted effective intervention, so they gave an increased score, which was also the effect of single-blinding. In addition, for the protection of participants at risk of suicide, we added a directory including 3 kinds of safety resources at the end of both brochures received by participants in the control condition and intervention condition. The increase in the help-seeking score of participants in the control condition may be due to this directory. With the purpose of avoiding the interference of these confounding factors, the current study was designed as a randomized controlled trial to verify the effectiveness of the intervention contents. Therefore, the impact of the directory on help-seeking was balanced between participants in 2 conditions.Based on the structured discussion outline of the intervention condition , particiOne of the strengths of the current study was the willingness of participants to trust the researchers and disclose personal information such as educational background and family income. The potential reason for this is that, at the informed consent stage before the research, the researchers introduced the confidential content in the informed consent to the participants in detail, which also promoted the participants’ trust in the researcher so that they were willing to authentically answer their personal information. Considering the effectiveness of the primary outcomes in the current study and the high completion rate of participants, we believe that the digital online-based multicomponent intervention  could also be applied to other general populations, so as to effectively promote help-seeking for mental health.There were several other strengths from an implementation standpoint that needed to be addressed. First, the present intervention was conducted with high fidelity and completed with low dropout rates. Three group facilitators have received fidelity training on delivering this evidence-based intervention pre-intervention and passed the fidelity assessment examining adherence to study protocol, quality of delivery, and participant responsiveness with high fidelity ratings. Second, under the benefits of high fidelity, the completion rate was extremely high (95%), which was much higher compared to the average completion rate (80%) for most randomized controlled trials, suggesting that not only did we precisely and accurately implement intervention procedures as planned but also the high level of urgency of such interventions for the LGBTQ+ population . The reaThe primary limitation is that this study did not effectively promote participants’ actual help-seeking behaviors. The potential explanation could be the inference of the particular time period chosen to conduct both the present study and its post-intervention follow-ups. Chinese New Year  has always been the most celebrated national holiday in China, during which families, friends, and relatives reunite with each other. However, due to lower levels of both personal privacy and security arising from large family gatherings, it could also be the least possible occasion in which LGBTQ+ young adults would risk revealing their identities for help-seeking, subsequently blocking their actual help-seeking behaviors. Together with the impact of the pandemic , even if they intended to seek help, significantly reduced availability and accessibility of resources was a difficulty they must overcome. The second limitation of this study was that the present study was limited to 3-month follow-ups, which might not be long enough for drastic mindset and behavioral changes in help-seeking to occur. Future studies should extend the follow-up time. The third limitation was that half of the participants of the current sample were transgender, nonbinary, genderqueer, or questioning population. This is because the promotion of online recruitment advertising of this study has been promoted by many LGBTQ+ community organizers. Online posters have been released through social media platforms, such as WeChat or QQ groups, which are popular in the Chinese LGBTQ+ community. Since our study received recognition from community organizers in the LGBTQ+ community, especially organizers from the transgender community, transgender young adults who usually could not be reached via posters and online research participation campaigns expressed their interest in participating in our study, explaining why there were more transgender participants in our study.The present study strives to examine the efficacy of the digital online-based multicomponent intervention aiming to promote help-seeking in LGBTQ+ young adults. The intervention was found to be an effective integrated model for enhancing LGBTQ+ young adults’ general help-seeking intentions and promoting their depression and anxiety literacy. Although the clinical significance of the present study’s findings warrants future research, the results of the present study add to an emerging breadth of evidence indicating that a brief, digital, online-based, and multicomponent intervention holds great potential in downscaling currently existing mental health barriers faced by the LGBTQ+ population.S1 CONSORT Checklist(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S1 Protocol(DOCX)Click here for additional data file.S1 Data(CSV)Click here for additional data file.S2 Data(CSV)Click here for additional data file.