Glioblastoma (GBM) is the most common primary malignant brain tumor with a high mortality rate. The current treatment consists of surgical resection, radiation, and chemotherapy; however, the median survival rate is only 12–18 months despite these alternatives, highlighting the urgent need to find new strategies. The heterogeneity of GBM makes this tumor difficult to treat, and the immunotherapies result in an attractive approach to modulate the antitumoral immune responses favoring the tumor eradication. The immunotherapies for GMB including monoclonal antibodies, checkpoint inhibitors, vaccines, and oncolytic viruses, among others, have shown favorable results alone or as a multimodal treatment. In this review, we summarize and discuss promising immunotherapies for GBM currently under preclinical investigation as well as in clinical trials. Glioblastoma multiforme (GBM) stands as the most frequent and aggressive form of the central nervous system (CNS) primary neoplasms. The standard protocol for treating this malignancy recommends, if possible, maximal surgical resection of the tumor mass followed by radiotherapy with adjuvant and concomitant temozolomide or a combination of procarbazine, lomustine, and vincristine (PCV schedule) for recurrent glioblastoma . Howeverβ, VEFG, and interleukin- (IL-) 6 and 10 [During the early tumor formation, immune surveillance allows carrying out antitumor immune responses mediated by M1 macrophages, natural killer cells (NKs), and antigen-specific lymphocytes. However, GBM cells become able to elicit a series of mechanisms that permit the recruitment of monocytes that become tumor-associated macrophages (TAMs) as well as the recruitment of tumor tolerogenic lymphocytes like T regulatory cells (Tregs) with the production of anti-inflammatory cytokines such as TGF-6 and 10 , 4, besi6 and 10 , 6. Thes6 and 10 , 8.Considering the immunosuppressive tumor environment, new therapies are emerging focused on reactivating the immune response against tumors as promising tools for the increase in tumor clearance and the improving patient survival. Immunotherapeutic strategies encompass the use of different substances to stimulate the antitumor immune response or the elimination of immunosuppressive cells, as well as the use of substances produced by immune components to combat tumor proliferation and immune evasion. Immunotherapeutic approaches involve the passively mediated administration of monoclonal antibodies, the use of adjuvants and cytokines, or the active-mediated immunization by antigen vaccination or transplantation of activated dendritic cells or trained cytotoxic lymphocytes, exploiting the humoral and cellular components of the immune system to directly inhibit tumor growth and abrogate the tumor-mediated immune suppressive mechanisms or to activate the innate/adaptive immune response against the tumor . Some ofToday, the development of immunotherapeutic tools to combat GBM has begun to be tested in clinical trials. Until mid-2021, 1,646 clinical trials for GBM had been registered in the clinical trial database of the United States National Institutes of Health, of which 22.53% use one or more immunotherapeutic strategies alone or in combination with SOC .Within immunotherapeutic strategies, monoclonal antibodies are the most frequently used agents in GBM patients  possess an engineered surface receptor that combines the antigen-binding region of an antibody with the intracellular activation domains of T cell receptors thereby killing tumor cells by recognizing unique malignant cell surface antigens (neoantigens) . CAR-Ts α, IFN-β, or IFN-γ have been used in GBM clinical trials. These cytokines allow the proliferation and activation of lymphocyte antitumor responses.Oncolytic viruses are also an immunotherapeutic approach, which selectively infect malignant cells that promote cell lysis; furthermore, viral particles could activate innate immune response contributing to antitumor activity . Also, rAll these immunotherapeutic approaches are being tested in clinical trials and will be explained in detail in the next sections. Additionally, Monoclonal antibodies tested in GBM patients are targeted to block the mechanisms elicited by malignant cells that suppress antitumor immune responses . The immISRCTN84434175).The combination of ipilimumab with nivolumab in untreated GBM patients has been tested in clinical trials showing partial responses accompanied by increased immune infiltrates in tumor tissue, but there was no improvement in the progression-free survival (PFS) or OS . When niIn addition to the blockade of CTLA-4 and PD-1, other checkpoint molecules such as the T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) and the lymphocyte activation gene 3 (LAG-3) have been used as targets for a monoclonal antibody in GBM clinical trials. Clinical trials on the immune checkpoint inhibitors alone may have not shown high therapeutic efficacies, but the results of the immune phenotyping demonstrated that the use of these drugs allowed initiating the reactivation of antitumor immune responses. However, more information is needed focused on the combinatorial effect of these neoadjuvant treatments together with the administration of the standardized drugs against GBM.Tumor-associated antigens are molecules present in normal tissues but overexpressed in malignant cells, while neoantigens are tumor-specific molecules derived from mutations in the tumor cell genome . The ideα 2 (IL13Rα2) is a poor patient survival prognostic indicator, which is overexpressed by more than 50% of GBM [α2-specific CAR-Ts have been evaluated in phase I clinical trials showing the tolerability and safety of its intracranial administration. Also, it increases the necrotic volume and reduces IL3Rα2 expression in GBM tissue compared with paired pretreatment samples as well as tumor partial remission and complete tumor remission in one of the patients enrolled in this study [The development and efficacy of a range of CAR-Ts targeted against different surface molecules representative of GBM tissue have been challenged in patients. IL-13 receptor % of GBM . IL13Rα2is study , 52. Theis study , is relais study –56. EGFRis study . Meanwhiis study . Furtheris study .The transplant of engineered CAR-Ts has shown promising results in the treatment of GBM; however, current treatments only have focused on the administration of single-targeted cells limiting these tools by ignoring those malignant cells which do not express the target molecule of CAR-Ts.γ and IL-6, a signature of the activation of the engineered lymphocytes [In addition to blocking antibodies against the immune checkpoint molecules, PD-1 has been recently exploited as a tool target of chimeric switch receptor-engineered lymphocytes. Cytotoxic lymphocytes armed with this receptor can recognize PD-1 expressed on the surface of tumor cells and can eliminate them due to the transmembrane and cytosolic domains of this receptor, corresponding to the activation domains of the protein CD28 . A phasephocytes . These rα2, the human epidermal growth factor receptor (HER-2) and EGFRvIII, was made possible by analysing interpatient variability of multiple GBM samples, showing tumor cell-specific cytotoxicity and tumor remission in vitro and in vivo models [Multitargeted CAR-Ts for treating GBM have been started to be used in preclinical models, but evidence in clinical trials is further needed to determine their therapeutic efficacy. The development of third-generation CAR-Ts has allowed more accurate responses by modifying CAR-Ts for evasion of checkpoint inhibition as well as the expression of costimulatory molecules that allow better antitumor responses. Those have been tested against GBM, showing promising results in preclinical models. Specifically, anti-EGFRvIII CAR-Ts with a deleted expression of PD-1 have shown better antiglioma activity and longer survival in mice than in those CAR-Ts with wild-type PD-1 expression . In the o models .α), IL-13, IL-4, and EGFRvIII. The common toxins used to produce immunotoxins are the Pseudomonas exotoxin A and diphtheria toxin .in vitro and decreased tumor volume after implantation of malignant glioma stem cells in vivo, representing a low-cost tool for the treatment of GBM [in vitro [Herein, we describe the recent advances in immunotoxins against GBM in the last years. One of the targets in GBM is the cancer stem cells (CSC), which are a small population of slow-dividing and self-renewing glioma cells. The glioma stem cells express the antigen CD133, which has been related to tumor resistance to chemotherapy . Recentlt of GBM . Anotherin vitro . The calin vitro . The antin vitro . Other iin vitro , 87–89, in vitro . As withVaccination is a type of immunotherapy focused on the tumor-associated antigens. Antigens for cancer vaccines should be expressed only by malignant cells to kill specifically tumor cells. In GBM, the EGFRvIII-targeted vaccine Rindopepimut, a selective tumor-specific antigen peptide vaccine targeting the EGFRvIII mutation, has demonstrated antitumor immune activation in GBM patients as well as longer OS than that of temozolomide-treated patients . Howeverα2). A clinical study using ICT-107 following conventional treatment showed a nonsignificant trend toward increased PFS. Also, the use of ICT-107 vaccine showed a reduction in CD133 expression in some GBM patients [ICT-107 is another vaccine tested for GBM that consists in an autologous dendritic cell pulsed ex vivo with tumor and CSC antigens , which activate the innate immune system and latterly the adaptive immune response. In this line, recently it was demonstrated that the administration of microvesicles released after C6 cells were irradiated reduced more than 50% tumor volume, increased the infiltrating T lymphocytes, and promoted the apoptosis of glioma cells compared with the group that was not immunized with these microvesicles . The usein vitro, which was also related to both a reduction in the intracerebral tumor growth and prolongation of animal survival, but it was observed that this vaccine activates the antitumor immunity [In recent years, the use of oncolytic viruses has gained importance as a tool for the treatment of various solid tumors due to their tropism and selective replication in tumor cells. Evidence shows that oncolytic viruses are useful by reducing tumor bulk but also in the immune reactivation of antitumor responses . The effimmunity . Recentlimmunity . Moreoveimmunity .γ levels [In the case of clinical trials, the administration of intratumorally attenuated parvovirus resulted in a slight increase in the median OS; however, there is an increased number of infiltrating lymphocytes and IFN-γ levels . The useγ levels . HoweverIn addition to the use of anti-PD-1/PD-L1 or anti-CTLA-4 antibodies, the search of immune inhibitory blockade mechanisms has led to the study of metabolic pathways used by malignant cells to shape tumor microenvironment and to induce immune modulation. One of these routes that become to receive attention is the catabolism of tryptophan through the kynurenine pathway (KP). Evidence shows that one of the limiting enzymes of the KP, the indoleamine-2,3-dioxygenase (IDO), is overexpressed in different neoplasms including GBM, and its expression levels correlate with increased tumor-infiltrated TAM and Treg and with patient poor prognosis –118. TheAdditionally, L-kynurenine, the product of Trp degradation by IDO or TDO, has been involved in the GBM pathology since the kynurenine-AhR pathway can contribute to increasing the growth and motility of tumor cells and suppresses the immune response. Furthermore, the KP-derived metabolites have been implied with the generation of Tregs and the induction of apoptosis in lymphocyte subsets ; thus, tmut tumors present a better prognosis; with the unmethylation of the 8-methylguanosine methyltransferase (MGMT) promoter, GBM with methylated MGMT show a better prognosis than that with unmethylated MGMT and EGFR amplification [As mentioned above, GBM remains as an incurable disease and the low impact of current protocols for the treatment of GBM has been associated with the high prevalence of tumor recurrence mainly due to the development of drug resistance, intratumoral heterogeneity, and the given phenotypic plasticity by CSC able to change their metabolic activity under stress conditions –129. Allfication .wt patients who showed a good response to these antibodies also showed enrichment for MAPK mutations, while nonresponsive patients showed enrichment of PTEN mutations [In the case of the different immunotherapeutic approaches reviewed here that are on clinical trials, it is noteworthy that some of them report differences in the clinical outcomes based on genotypic and phenotypic characteristics of the patients. It was demonstrated that patients who showed a long-term follow-up after treatment with antibodies targeted to immune checkpoint molecules had methylation of the MGMT promoter, a marker of good prognosis of GBM , 45. IDHutations .The use of CAR-Ts and peptide vaccines against tumor-specific antigens and neoantigens has demonstrated clearance of tumor cells that carry such targets , 59, 81;Finally, the genetic profiling of patient-derived tumors could show useful information on which therapeutic strategies would be optimal for an individual but also to monitor how different tumors respond to a certain treatment.Herein, the immunotherapeutic strategies that are currently accepted for GBM treatment and those which are in the first stages of the clinical study with promising results were discussed. Until now, preclinical studies have led to the expansion of the knowledge of the immunological landscape occurring in GBM, allowing the development of more accurate tools that stimulate an antitumor response. On the other hand, the immunotherapeutic strategies tested in GBM patients have not shown the efficient results expected in terms of OS; however, evidence of antitumor immune activation and increase in tumor progression-free survival are promising traits for further development of different immunological strategies to combat GBM. Furthermore, the use of combined immunotherapy strategies to combat malignant neoplasms shows encouraging results in preclinical models that lay the foundation for the beginning of its study in clinical protocols. A combination of schemes that override tumor-induced immunosuppressive mechanisms, together with those strategies that potentiate the activation of antitumor immune response, is worthy of attention. Deeper research of the immune behavior of GBM could lead to the development of more efficient tools for the treatment of this disease and therefore to the clinical acceptance of these strategies for a generalized treatment program to combat GBM.


A 60-years-old male with high cholesterol and a Modified Medical Research Council (mMRC) dyspnoea score of 2 was admitted with a history of fever, cough, dyspnoea. Initial chest radiograph (A) showed bronchiectasis in right base with pneumonia in the left base. A diagnosis of COVID-19 was confirmed with positive SARS-CoV-2 RT-PCR on nasal swab. There were some typical findings on CT images. According to the CT images (B), the case was classified as of stage I consolidation with multiple peripheral ground glass opacities with interlobular septal thickening were seen in anterior and inferior lingular segment of left upper lobe, posterior basal segment of left lower lobe, posterior segment of right upper lobe, and medial segment of right middle lobe. Initially he was on IV steroids and therapeutic doses of heparin. He was maintaining his oxygen saturation to 96%. Ten (10) days after hospitalization and normalization of all inflammatory markers, he has Modified Medical Research Council (mMRC) dyspnoea score 1 and oxygen-independent. The patient was asked for follow up in 6 weeks. Due to the mMRC of 1 and short history, it is assumed that the fibrosis was not present prior to the COVID-19 diagnosis. The early use of antifibrotics may prevent this devastating complication, but it is difficult to predict who is likely to progress to pulmonary fibrosis. Early rehabilitation protocol for post-acute COVID-19 patients can minimize dyspnea and shortness of breath even for minimal activities.


Despite the growing importance of the cerebellum as a region highly vulnerable to accumulating molecular errors in schizophrenia, limited information is available regarding altered molecular networks with potential therapeutic targets. To identify altered networks, we conducted one-shot liquid chromatography–tandem mass spectrometry in postmortem cerebellar cortex in schizophrenia and healthy individuals followed by bioinformatic analysis (PXD024937 identifier in ProteomeXchange repository). A total of 108 up-regulated proteins were enriched in stress-related proteins, half of which were also enriched in axonal cytoskeletal organization and vesicle-mediated transport. A total of 142 down-regulated proteins showed an enrichment in proteins involved in mitochondrial disease, most of which were also enriched in energy-related biological functions. Network analysis identified a mixed module of mainly axonal-related pathways for up-regulated proteins with a high number of interactions for stress-related proteins. Energy metabolism and neutrophil degranulation modules were found for down-regulated proteins. Further, two double-hit postnatal stress murine models based on maternal deprivation combined with social isolation or chronic restraint stress were used to investigate the most robust candidates of generated networks. CLASP1 from the axonal module in the model of maternal deprivation was combined with social isolation, while YWHAZ was not altered in either model. METTL7A from the degranulation pathway was reduced in both models and was identified as altered also in previous gene expression studies, while NDUFB9 from the energy network was reduced only in the model of maternal deprivation combined with social isolation. This work provides altered stress- and mitochondrial disease-related proteins involved in energy, immune and axonal networks in the cerebellum in schizophrenia as possible novel targets for therapeutic interventions and suggests that METTL7A is a possible relevant altered stress-related protein in this context. Schizophrenia (SZ) is a complex polygenic psychiatric disorder involving dysregulation of multiples pathways  with an n = 12) and control healthy subjects (n = 14) that we obtained using single shot liquid chromatography–tandem mass spectrometry analysis  between SZ and control cases and the corrected p-value  adjusted to FDR < 0.1). Most of the significant changes were displayed between 0.2 and 0.6 Log2 FC . No differences were observed between the SZ and control groups for any demographic or tissue-related variables . Using m Log2 FC  D. We fo Log2 FC . Eighty- Log2 FC .Of the 108 up-regulated proteins, those related to stress were found to be the most enriched in the disease category analysis, comprising 12% of the total altered proteins . The up-Of the 142 down-regulated proteins, those involved in mitochondrial diseases were found to be the most enriched in the disease category analysis, also comprising 12% of the total altered proteins . AnalysiFor the subsequent analyses, the altered proteins also reported in gene expression and proteomic analyses in the cerebellum and in iPSC model for schizophrenia at mRNA level were used see E. We thuFor the enriched up-regulated pathways, the network analysis showed overlapping pathways that were mainly related to axonal development and functioning A. The veNetwork analysis of enriched pathways for the down-regulated proteins revealed two distinct modules, one related to energy metabolism and the other consisting of neutrophil degranulation pathways B. The neWe used publicly available immunocytochemistry data to assess the expression of proteins of the up-regulated and down-regulated networks in the different layers of the cerebellum. In the up-regulated mixed module, most of the proteins were expressed at medium to high levels in all cerebellar layers with the exception of ARRB1 and SNX5 from axon guidance, which were only expressed in Purkinje neurons A. No infFor each network module, we identified one or two robust protein candidates for further investigation of the influence of early postnatal stress based on the detected LFQ-intensity fold change and coefficient of variation (<0.35) . The selTwo independent double-hit murine stress models were used. The models were maternal deprivation combined with an additional stressor: social isolation (MD/Iso) or chronic restraint stress (MD/RS). Altered behavior was confirmed in these models . CLASP1 Our study characterized the proteomic alterations for the cerebellar cortex in chronic schizophrenia. To the best of our knowledge, this is the first time in which the individual proteomic signature allows most SZ cases to be segregated from healthy controls in unsupervised analysis, similarly as that achieved in some gene expression studies ,29.A subset of the up-regulated proteins has been previously related to stress diseases. In this context, psychosocial stress has been shown to be mediated by cortisol, resulting in decreased blood flow in the cerebellum, and to be associated with the altered resting state of this area ,23. OtheIn our proteomic study, we found up-regulated pathways related to vesicle-mediated transport. In neurons, altered transport could limit effectiveness in neuronal communication . DefectiOur proteomic study showed an altered axon guidance pathway in the cerebellum. Defects in neuronal connectivity during development have been proposed as an important cause of the etiopathology of SZ ,46. A stThe down-regulated proteins were enriched in proteins with an implication in mitochondrial diseases. Most of the proteins of this category were also found in the group of proteins related to oxidative phosphorylation and TCA in this study. In SZ, altered mitochondrial function has been previously reported . FurtherWe found a down-regulation of proteins involved in the energy production in the cerebellum in schizophrenia. The cerebellum represents 11% of human brain weight , and theEvidence of mitochondrial dysfunction in SZ includes genetic , metabolIn our study, NDUFB9, the most robust candidate of the energy network involved in respiratory electron transport, was reduced in schizophrenia. It was also observed to be down-regulated in the double-hit postnatal stress murine model that combined maternal deprivation with social isolation but not in combination with chronic restraint stress, suggesting that the down-regulation of respiratory electron chain proteins altered in schizophrenia could be a social stress-induced response.NDUFB9 is one of the multiple energy proteins that we found widely expressed in the cerebellum with moderate expression in the cerebellar granule layer and Purkinje layer. This protein is involved in the assembly of Complex I. Together with the activity of Complex I, NDUFB9 has been investigated in other brain areas in SZ ,63. ThusOur study observed down-regulation of several proteins involved in the various processes of the neutrophil degranulation pathway in cerebellar tissue. Neutrophil degranulation is one of the first defense barriers against infection . An imbaMETTL7A, a member of the METTL family of methyltransferases, is of interest as it has been poorly studied; indeed, only one study investigated its role in RhoBTB1 signaling in maintaining Golgi integrity , a functThe use of the human postmortem brain constitutes a valuable tool to understand the molecular pathways altered in several psychiatric disorders. However, it has limitations. Firstly, confounding factors such as age, postmortem delay and pH must be carefully explored. In our proteomic study, we did not find any association between these variables and the significantly altered proteins in the cerebellum. Secondly, patients with chronic schizophrenia had long-term and heterogeneous antipsychotics medications. Some candidates from the upregulated proteins are involved in drug to drug interactions, which suggest a possible effect of antipsychotic medications on our findings. Although, no associations were found with a chlorpromazine equivalent dose and altered proteins, the effect of antipsychotic could not be completely rule out. Thirdly, our study only included men, who do not represent a real population of this disorder. Fourthly, our study consisted entirely of elderly individuals due to the type of sample available.n = 12) and healthy controls (n = 14) were obtained from the neurologic tissue collection of the Parc Sanitari Sant Joan de Déu Brain Bank  (30) and the Institute of Neuropathology of the Universitari de Bellvitge Hospital , respectively. We matched SZ and control groups by gender , age, postmortem delay (PMD) and pH  for quality control and further analysis  1 beta subcomplex subunit 9 (NDUFB9); (3) CLIP-associating protein 1 (CLASP1); (4) 14-3-3 protein zeta/delta (YWHAZ); and (5) beta-actin (β-actin). See Three pregnant Wistar rats  at gestation day 15 were individually housed in a controlled setting. One of the litters was used as a control group and the other as a double-hit model randomly. After birth, at postnatal day (PD) 9, both litters were exposed to maternal deprivation for 24 h. On PD21, the pups were weaned, and one of the litters was isolated for 5 weeks (PD21-56); the pups were housed individually and denied physical contact with their siblings. After isolation, the pups were regrouped (MD/Iso). The other litter was exposed to restraint stress between PD 72 and 78 for 6 h every day (MD/RS). These conditions represent well-suited murine models for the study of neuropsychiatric dysfunctions ,81. Grout-test for parametric quantitative variables and the Mann–Whitney U test for non-parametric variables. Spearman or Pearson correlation analysis was carried out to detect association of our proteomic data with other clinical-, demographic- and tissue-related variables . For experiments with animal models, we performed outliers analysis using the ROUT method, unpaired Student t-tests for parametric variables and Mann–Whitney U tests for non-parametric variables. Statistical analysis was performed with Graph Prism version 7.00 . The significance level was set to 0.05.Normal distribution of variables was determined using the D’Agostino–Pearson test. Demographics and tissue feature of the samples were compared between cases and controls using Student’s Altogether, our study provides altered stress- and mitochondrial disease-related proteins involved in energy, immune and axonal networks in the cerebellum in schizophrenia, suggesting that the accumulation of altered events in these networks could lead to a failure in the normal cerebellar functions, impairing synaptic response and the defense mechanisms of this region against external harmful injuries in schizophrenia. Further double hit murine models point out that some of the molecular network alterations observed in schizophrenia could be induced by different combinations of stress exposure during the late postnatal developmental phase of the cerebellum. Thus, these results suggest that the cerebellum is an area vulnerable to accumulate molecular errors induced by stress during early postnatal life in schizophrenia. These findings could provide a panel of possible molecular targets and pathways related to stress and mitochondrial function to explore specific antipsychotic treatments in these murine stress models. These pre-clinical studies could be useful for the development of novel combinations of antipsychotics for schizophrenia in future clinical studies.


Can rapid psychometrically sound adaptive diagnostic screening and dimensional severity measures be developed for posttraumatic stress disorder?Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.In this diagnostic study including 713 US military veterans, the Computerized Adaptive Diagnostic–Posttraumatic Stress Disorder measure was shown to have excellent diagnostic accuracy. The Computerized Adaptive Test–Posttraumatic Stress Disorder also provided valid severity ratings and demonstrated convergent validity with the Post-Traumatic Stress Disorder checklist for In this study, the Computerized Adaptive Diagnostic–Posttraumatic Stress Disorder and Computerized Adaptive Test–Posttraumatic Stress Disorder measures appeared to provide valid screening diagnoses and severity scores, with substantial reductions in patient and clinician burden. Veterans from recent and past conflicts have high rates of posttraumatic stress disorder (PTSD). Adaptive testing strategies can increase accuracy of diagnostic screening and symptom severity measurement while decreasing patient and clinician burden.To develop and validate a computerized adaptive diagnostic (CAD) screener and computerized adaptive test (CAT) for PTSD symptom severity.A diagnostic study of measure development and validation was conducted at a Veterans Health Administration facility. A total of 713 US military veterans were included. The study was conducted from April 25, 2017, to November 10, 2019.Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) (PCL-5). A subsample of 304 participants were interviewed using the Clinician-Administered Scale for PTSD for DSM-5.The participants completed a PTSD-symptom questionnaire from the item bank and provided responses on the PTSD Checklist for DSM-5 PTSD diagnosis with high sensitivity and specificity as evidenced by an area under the curve of 0.91 . The CAT-PTSD demonstrated convergent validity with the PCL-5 (r = 0.88) and also tracked PTSD diagnosis . The CAT-PTSD reproduced the final 203-item bank score with a correlation of r = 0.95 with a mean of only 10 adaptively administered items, a 95% reduction in patient burden.Of the 713 participants, 585 were men; mean (SD) age was 52.8 (15.0) years. The CAD-PTSD reproduced the Clinician-Administered Scale for PTSD for Using a maximum of only 6 items, the CAD-PTSD developed in this study was shown to have excellent diagnostic screening accuracy. Similarly, using a mean of 10 items, the CAT-PTSD provided valid severity ratings with excellent convergent validity with an extant scale containing twice the number of items. The 10-item CAT-PTSD also outperformed the 20-item PCL-5 in terms of diagnostic accuracy. The results suggest that scalable, valid, and rapid PTSD diagnostic screening and severity measurement are possible. This diagnostic study develops and validates a tool for use in diagnostic screening of US military veterans for posttraumatic stress disorder. Disease burden associated with PTSD is also notable among veterans from previous conflicts. Magruder and colleagues2 estimated the temporal course of PTSD among Vietnam veterans and identified 5 mutually exclusive groups . Based on these findings, the authors suggested that PTSD remains “a prominent issue” for many who served.2(p2) Among adults in the US without a history of military service, lifetime incidence of PTSD is estimated at 6.8%,3 with women being twice as likely as men to be diagnosed with the condition.4Posttraumatic stress disorder (PTSD) in US military veterans is recognized as one of the signature injuries of the conflicts in Iraq and Afghanistan. Fulton et al5 Limitations of classical test theory are amplified when measuring complex conditions, such as PTSD.5Provision of evidence-based treatment for those with PTSD is contingent on accurate identification. Traditionally, this identification has required the use of measures developed using classical test theory .6(p271) Such exposure can be secondary to directly experiencing, witnessing, learning about (occurred in a close family member or friend), and/or experiencing repeated or extreme exposure to aversive details regarding 1 or more traumatic events. Symptom-based criteria include intrusive symptoms , avoidance of stimuli , and negative alterations in cognitions and mood associated with the events .6Diagnostically, criterion A events of PTSD include “exposure to actual or threatened death, serious injury, or sexual violence.”7 identified 3 classes of individuals among Dutch veterans with PTSD, including average, severe, and highly severe symptom severity classes. Among trauma-exposed, inner-city primary care patients, Rahman et al8 examined data to assess associations between PTSD subclasses and major depressive disorder. The investigators identified 4 subclasses, including high severity and comorbidity, moderate severity, low PTSD and high depression, and resilient. These findings highlight the need to identify strategies capable of measuring complex traits.As would be expected based on the above-stated criteria, individuals with PTSD experience a wide range of symptoms with varying severity. Using latent profile analysis, Jongedijk et al9 thereby increasing the precision of measurement and accuracy of diagnostic screening and minimizing clinician and patient burden.10 For complex disorders, such as PTSD, in which items are selected from distinct yet related subdomains , selection of items is based on multidimensional rather than unidimensional item response theory (IRT).11 Adaptive diagnosis and measurement are fundamentally different. In measurement  the objective is to move the items to the severity level of the patient. In computerized adaptive diagnosis (CAD), we move the items at the tipping point between a positive and negative diagnosis.12 Both methods are adaptive but are based on different statistical approaches. The CAT is based on unidimensional or multidimensional IRT and the model does not include an external criterion, such as a structured clinical interview . External criteria, such as the CAPS-5, or extant measures, such as the PTSD Checklist for DSM-5 (PCL-515), can be used to validate the CAT, but these tools are not used to derive a CAT. By contrast, CAD is based on machine-learning models for supervised learning . We can use the same set of symptom items as the CAT to derive a CAD, but here we need an external criterion, such as the CAPS-5, to train the machine-learning model. CAD adaptively derives a binary screening diagnosis with an associated level of confidence, and CAT derives a dimensional severity measure that can be used to assess the severity of the underlying disorder and change in severity over time. CAD and CAT are complementary but are fundamentally different in theory and application. To do large-scale screening and measurement of PTSD, both measures are needed.One alternative to administering traditional assessment measures is computerized adaptive testing (CAT) in which a person’s initial item responses are used to determine a provisional estimate of their standing on the measured trait, which is then used for the selection of subsequent items,16 anxiety,17 mania/hypomania,18 psychosis,19 suicide risk,20 and substance use disorders21) indicates that one can create large item banks (hundreds of items for a given disorder), from which a small optimal subset of items can be adaptively administered for a given individual with no or minimal loss of information, yielding a substantial reduction in patient and clinician burden while maintaining high sensitivity and specificity for diagnostic categorization, as well as high correlation with extant self- and clinician-rated symptom severity standard measures. For CAD, Gibbons et al12 noted that the CAD for diagnosis of major depressive disorder reproduced the hour-long Structured Clinical Interview for DSM-5 Research Version (SCID)13 diagnosis of major depressive disorder in less than a minute, using an average of 4 adaptively selected self-reported items, while maintaining sensitivity of 0.95 and specificity of 0.87 for the clinical DSM-5 diagnosis. Such assessment tools (diagnostic screening [CAD] and severity assessment [CAT]) are currently lacking for PTSD based on DSM-5 criteria.Evidence for other mental health conditions , as well as 3 additional subdomains . A 104-item bank was constructed. Eighty-nine of these items were retained to further develop and validate a computerized test for PTSD (P-CAT). Although the DSM-5 was not completed at that time, the authors indicated that they included items related to domains that they expected to be included. Similarly, because DSM-5 measures were not yet developed, validation measures 25 were based on DSM-IV criteria. Moreover, to “minimize burden and distress for participants,”24(p118) the SCID PTSD module26 vs the Clinician-Administered PTSD scale27 was administered. Work by Weathers et al28 suggests that the CAPS is the most valid measure of PTSD relative to other clinical interviews or self-report measures. According to Eisen et al,24 although concurrent validity was supported by high correlations, sensitivity and specificity were variable and the P-CAT was found to not be as reliable among those with “low levels of PTSD.”24(p1120) Although there are similarities between the CAT-PTSD and the P-CAT in terms of the underlying method, there are important differences as well. First, unlike the CAT-PTSD, which varies in length and has fixed precision of measurement, the P-CAT is fixed in length and allows the precision of measurement to vary. This difference has implications for longitudinal assessments in which constant precision of measurement is important and is assumed in most statistical models for the analysis of longitudinal data.29 Second, the P-CAT item bank was limited to 89 items, whereas our item bank has 211 items. As such, these new methods provide better coverage of the entire PTSD continuum and have more exchangeable items at any point on that continuum. Third, we have developed both a CAT for the measurement of severity and a CAD for diagnostic screening. Diagnostic screening based on a CAD generally outperforms thresholding a continuous CAT-based measure, using fewer items.12 The limitation of CAD is that it does not provide a quantitative determination, a gap that is filled by the CAT-PTSD. In combination, however, CAT and CAD can be used for both screening and measurement.Using DSM-5 criteria, this study aimed to develop and test the psychometric properties of the CAD-PTSD (diagnostic screener) and the CAT-PTSD  against the standard criterion measure (CAPS-5),14 as well as the PCL-5.15Based on 16 First, a large item bank containing 211 PTSD symptom items was developed to create both the CAD-PTSD and CAT-PTSD measures, using separate analyses.We developed the CAD-PTSD and CAT-PTSD scales using the general method introduced by Gibbons and colleagues.30) and then simulating CAT from the complete item response patterns (211 items) to select optimal CAT tuning parameters from 1200 different simulations. Next, the CAT-PTSD scale was validated against an extant PTSD scale, the PCL-5  and the CAPS-5 . For CAD, we used an extremely randomized trees algorithm31 to develop a classifier for the CAPS-5 PTSD diagnosis based on adaptive administration of no more than 6 items from the bank.12 Classification accuracy was assessed using data not used to calibrate the model.The CAT-PTSD measure was developed by first calibrating the item bank using a multidimensional IRT model . In such cases, the bifactor model, originally developed by Gibbons and Hedeker33 for binary response data and later extended by Gibbons et al30 for ordinal (polytomous) response data, permits each item to tap the primary dimension of interest  and 1 subdomain , thereby accommodating the residual dependence and allowing for the retention of most items in the final model. The bifactor model of Gibbons and Hedeker33 was the first example of a confirmatory item factor analysis model, and they suggested that it is computationally tractable regardless of the number of dimensions, in stark contrast to exploratory item factor analytic models. Furthermore, the estimated bifactor loadings are rotationally invariant, greatly simplifying interpretability of the model estimates. The bifactor model provides a parameter related to each item’s ability to discriminate high and low levels of the underlying primary and secondary latent variables, and severity parameters for the k-1 thresholds between the k ordinal response categories. The bifactor model produces a score and uncertainty estimate on the primary dimension for each participant as well as for each of the subdomains. Complete details regarding the models and estimation are provided by Gibbons and Hedeker33 for binary response data and Gibbons et al30 for ordinal response data.Most applications of IRT are based on unidimensional models that assume that all of the association between the items is explained by a single primary latent dimension or factor . However, mental health constructs are inherently multidimensional; for example, in the area of depression, items may be sampled from the mood, cognition, behavior, and somatic subdomains, which produce residual associations between items within the subdomains that are not accounted for by the primary dimension. If we attempt to fit such data to a traditional unidimensional IRT model, we will typically have to discard most candidate items to achieve a reasonable fit of the model to the data. Bock and Aitkin16 This process continues until the uncertainty falls below a predefined threshold, in our case, 5 points on a 100-point scale. The CAT has several tuning parameters16 that we select by simulating CAT from the complete response patterns. Twelve hundred simulations are conducted, and we select the tuning parameters that minimize the number of items administered and maximize the correlation with the total bank score. The tuning parameters include the level of uncertainty at which we stop the adaptive test, a second stopping rule based on available information remaining in the item bank at the current level of severity, and an additional random component that selects the maximally informative item or the second maximally informative item to increase variety in the items administered. We select the next maximally informative item based on the following item information criteria. Item information describes the information contained in a given item for a specific severity estimate. Our goal is to administer the item with maximum item information at each step in the adaptive process.Once the entire bank  is calibrated, we have estimates of each item’s associated severity and we can adaptively match the severity of the items to the severity of the person. We do not know the severity of the person in advance of testing, but we learn it as we adaptively administer items. Beginning with an item in the middle of the severity distribution, we administer the item, obtain a categorical response, estimate the person’s severity level and the uncertainty in that estimate, and select the next maximally informative item.12 developed the first CAD for major depressive disorder. CADs are based on machine learning methods, such as a random forest,34 of lower dimension than the dimensionality of the entire item bank, with the goal of minimizing loss of information from the full-bank classifier so that patient and clinician burden are minimized. The critical machine learning problem is to place a constraint on the number of features (symptom items) that may be used per sample. To this end, we used the extra-trees method 31 with the objective of further randomizing tree building in the context of numerical input features, where the choice of the optimal cutpoint is responsible for a large proportion of the variance of the induced tree. The choice of the extra-trees classifier was optimized among a set of possible state-of-the-art algorithms, including random forests, gradient descent, support vector machines, neural networks, and AdaBoost. The extra-trees approach produced superior out-of-sample classification performance, particularly under the restriction of the total number of items that may be used to reach a decision. In our model, we used 2 decision trees in each ensemble, where the depth of each tree is limited to 3, resulting in a total of 6 items being adaptively administered in each test. In addition, the use of 2 decision trees that are combined linearly allows for an additional degree of freedom over using a single decision tree depth of 6 , resulting in a substantial increase in performance. The large size of the item bank implies that several alternative models  could be obtained, allowing for the generation of a number of possible tests with different sets of items being administered in each test. For each patient, we randomly select 1 such extra-trees model and administer the test, which presents 6 items adaptively as we traverse the 2-component decision trees based on the specific patient responses. An example of a 3-estimator ensemble (1 of 2 used in constructing a test) is shown in the eFigure in the 35Unlike a CAT, which is criterion-free, a CAD uses the diagnostic information  to derive a classifier based on a subset of the symptoms in the item bank that maximize the association between the items and the diagnosis. A CAD is used for diagnostic screening, whereas a CAT is used for symptom severity measurement. Gibbons et alVeterans were eligible if they were between the ages of 18 and 89 years and able to provide written informed consent. Participants (n = 713) were recruited from a mountain state metropolitan Veterans Affairs Medical Center between April 25, 2017, and November 10, 2019. Institutional review board approval was obtained from the Colorado Multiple Institutional Review Board. Participants received financial compensation.36A convenience sample (n = 304) was recruited via flyers posted at the local Veterans Affairs Medical Center and surrounding community-based outpatient clinics. The research team also distributed study information to mental health and primary care clinicians at the local Veterans Affairs Medical Center to facilitate recruitment. In addition, veterans who had participated in previous research with existing consent to be contacted for future studies were mailed study-specific flyers with study contact information. Once eligibility was determined by the study team, participants were invited to complete an in-person study visit wherein clinical interview measures, including the CAPS-5, were administered by trained research personnel (L.M.B.). Interview schedules were reviewed by licensed clinicians (L.A.B. and L.M.B.) for quality management. Self-report measures were completed on paper, and the PTSD item bank was administered using research electronic data capture (REDCap).36To recruit the remaining participants (n = 409) required for all planned analyses (n = 713), efforts were made to identify, via the VA Corporate Data Warehouse, those with varying levels of psychiatric symptom burden based on past mental health treatment obtained. This population included veterans who received services through an inpatient or outpatient psychiatric unit, PTSD residential program, mental health clinic, or primary care clinic at the local Veterans Affairs Medical Center or community-based outpatient clinics since 2009. Duplicates with those already enrolled were removed. Letters of invitation were sent to 9350 potential participants, 5.1% expressed interest, and 409 (4.4%) completed the study procedures. These 409 participants completed the PCL-5 and PTSD item bank via REDCap.We developed an item bank containing 211 PTSD items drawn from 16 existing self-report and clinician-administered PTSD scales  for the receiver operating characteristic curve with 10-fold cross-validation using Stata, version 16 (StataCorp LLC). The Pearson r correlation coefficient test was used to assess the association between the CAT-PTSD score and the PCL-5 score. Using 2-sided testing, findings were considered significant at P < .05.The bifactor IRT models were fitted with the POLYBIF program. Improvement in fit of the bifactor model over a unidimensional alternative was determined using a likelihood ratio χIn 2 = 14 928203; P < .001).Data from 713 participants were used to calibrate the 211 PTSD items. Following removal of 8 items with poor discrimination (loadings <0.3) on the primary dimension, 203 items remained . The bifactor model significantly improved the fit over a unidimensional IRT alternative . Median length of assessment was 59 seconds .Simulated adaptive testing from complete PTSD item bank responses revealed that using a mean of 10 items per participant  in the CAT-PTSD, we maintained a correlation of 16 These decision rules yielded thresholds of CAT-PTSD scores of 35  for none vs mild, 47  for mild vs moderate, and 60  for moderate vs severe. Although the actual score should be relied on for measurement and the assessment of change, these categories may be useful for clinical decision-making.To aid in patient triage, severity thresholds were selected based on sensitivity and specificity for the CAPS-5 diagnosis of PTSD. Scores on the CAT-PTSD can range from 0 to 100 and map on to PTSD severity categories. Categories of none, mild, moderate, and severe were selected; the shift between none and mild was selected to have high sensitivity and moderate specificity, mild vs moderate to have high sensitivity and high specificity, and moderate vs severe to have high specificity.37 No loss of diagnostic predictive accuracy between the full 203-item bank classification  and the 10-item (average) CAT-PTSD was found, demonstrating that the CAT extracted full information from the total item bank using a mean of only 10 items from the 203 items. By contrast, the diagnosis based on the PCL-5 (using a threshold score of 33) had lower diagnostic predictive accuracy  using twice the number of items (20 items). Convergent validity between the CAT-PTSD and PCL-5 was demonstrated .Validation occurred using 304 individuals who participated in CAPS-5 diagnostic interviews and 713 who participated in the PCL-5. We validated the CAT-PTSD against the CAPS-5 diagnosis  and against the PCL-5 . Diagnostic predictive validity for the CAT-PTSD was demonstrated against the CAPS-5  using 10-fold cross-validation so that classification accuracy was assessed in patients not used in estimating the logistic regression. This AUC represents excellent discrimination per Hosmer et al.37 Mean test time was 35 seconds . Combined use of the CAD-PTSD and CAT-PTSD was a mean of 94 seconds.Data from 304 participants with CAPS-5 diagnostic interviews were used to calibrate the CAD-PTSD, using all 211 items. The 6-item CAD-PTSD (a 97% reduction in items) produced a cross-validated AUC of 0.91  for the clinician-rated CAPS-5 PTSD diagnosis . This leIn r = 0.88). Despite the high correlation, the CAT-PTSD outperformed the PCL-5 in terms of diagnostic accuracy (AUC = 0.85 vs 0.75), using half the number of items. Relative to the full item bank of 203 items, the CAD-PTSD had a 97% reduction of items and the CAT-PTSD had a 95% reduction of items while maintaining a correlation of r = 0.95 with the total 203-item bank score for the CAT-PTSD.Among US military veterans, we have developed an adaptive diagnostic screener and a dimensional severity measure for PTSD and have examined their validity in terms of tracking results of a structured clinical interview and an extant severity measure. The CAD reproduced the CAPS-5 with outstanding diagnostic accuracy (AUC = 0.91). As expected, the CAD-PTSD outperformed the CAT-PTSD in terms of diagnostic accuracy (AUC = 0.91 vs AUC = 0.85), with a 40% reduction in the number of items (6 vs 10). Nevertheless, the CAT-PTSD had classification accuracy in the excellent range. The CAT-PTSD demonstrated convergent validity against the PCL-5 with high correlation 16 but only 0.84 for the fixed-length Patient Health Questionnaire-9.40The advantages of self-assessments over rater-based evaluations are substantial. Self-assessments are not limited to the availability of highly trained interviewers and can be administered in or out of the clinic on internet-capable devices . Self-assessments also eliminate interviewer bias and reduce costs, thereby enhancing scalability. During clinical visits, clinicians and patients can use saved time to focus on treatment planning. An additional advantage of adaptive tests is for longitudinal assessments in which response bias associated with repeated administration of the same items is eliminated because the items change across assessments. One might hypothesize that changing the items results in decreased test-retest reliability, but in fact the reverse is true. Beiser and colleagues41 found that CAT depression and suicidality measures, developed using the same technology, outperformed traditional fixed-length clinician-rated  and self-rated (Beck Depression Inventory44) measures in terms of sensitivity to change.The CAT-PTSD produces a continuous severity score on a scale of 0 to 100 with 5 points of precision. The continuous severity score can be thresholded into clinically useful categories of none, mild, moderate, and severe, as we have illustrated. The continuous severity score from the CAT-PTSD is ideal for longitudinal assessments, because its precision is fixed on repeated measurements, in contrast to traditional short-form tests. Furthermore, the CAT-PTSD adapts to changing psychopathologic characteristics by targeting the severity of the items to the severity of the patient, further improving the precision of measurement and the ability to assess change. A recent ketamine randomized clinical trial45 in a cloud computing environment for routine test administration on internet-capable devices, such as smartphones, tablets, notebooks, and computers, and providing an advanced programming interface that can be interfaced with the electronic health record. To accommodate literacy issues, audio to the self-report questions can be enabled. Because the generation and testing of subdomain scores is beyond the scope of this study, future research in this area is warranted.Future directions include the need for additional field testing, which would also allow for evaluation of the acceptability and feasibility of implementing these tools in clinical settings, including via telehealth, which has been increasingly implemented as a result of the COVID-19 pandemic. Use of telehealth assessment will in part be facilitated by designing a graphical user interface46This study has limitations. The CAD-PTSD and CAT-PTSD do not allow for evaluation and monitoring of specific symptoms to the extent that they may not always be adaptively administered. However, items from the 5 subdomains are available from most interviews and can be used to assess specific subdomains of PTSD . In addition, this study was conducted exclusively in English. Independent replication of our findings in other patient populations and in other languages  is needed.The findings of this study suggest that, among veterans, the CAD-PTSD and CAT-PTSD appear to provide valid diagnostic screening and dimensional severity scores, with substantial reductions in patient and clinician burden. These measures are scalable and can be integrated into electronic health record systems for routine use in health care settings.


In addition, an inverse association between mean daily calcitriol dose and COVID-19 severity or mortality was observed in treated patients, independently of renal function. Our findings point out that patients with advanced chronic kidney disease could benefit from calcitriol supplementation during the COVID-19 pandemic. Treatment with calcitriol, the hormonal form of vitamin D, has shown beneficial effects in experimental models of acute lung injury. In this study, we aimed to analyze the associations between calcitriol supplementation and the risk of SARS-CoV2 infection or COVID-19 mortality. Individuals ≥18 years old living in Catalonia and supplemented with calcitriol from April 2019 to February 2020 were compared with propensity score matched controls. Outcome variables were SARS-CoV2 infection, severe COVID-19 and COVID-19 mortality. Associations between calcitriol supplementation and outcome variables were analyzed using multivariable Cox proportional regression. A total of 8076 patients were identified as being on calcitriol treatment. Advanced chronic kidney disease and hypoparathyroidism were the most frequent reasons for calcitriol supplementation in our population. Calcitriol use was associated with reduced risk of SARS-CoV2 infection (HR 0.78 [CI 95% 0.64–0.94],  Infection with the new coronavirus SARS-CoV2 is characterized by an important clinical variability, ranging from completely asymptomatic cases to patients who develop a systemic disease COVID-19) with severe lung involvement and high mortality. This clinical heterogeneity and the fact that the disease more severely affects older individuals with associated comorbidities , nditions . To the best of our knowledge, this is the first study that analyzes the associations between calcitriol supplementation, the active metabolite of vitamin D and COVID-19 outcomes. Several clinical trials and two metanalysis have shown beneficial effects of cholecalciferol or ergocalciferol supplementation to prevent respiratory infections ,22. HoweIn this large population-based cohort, we observed significant reductions in the risk of severe COVID-19 and COVID-19 mortality in patients supplemented with calcitriol compared to matched controls. These associations were remarkable in patients in stages 4 or 5 CKD, where calcitriol use was associated with 43% reduction in COVID-19 mortality. Patients with advanced CKD may have lower endogenous synthesis of calcitriol  due to iOur results should be viewed with caution. Although this study is population-based and the multivariate analysis indicates that calcitriol treatment is an independent variable associated with significantly better COVID-19 outcomes, the population on calcitriol treatment is specially enriched in patients diagnosed with CKD and associated comorbidities; thus, these results cannot be extrapolated to the general population. Calcitriol is often used to prevent or treat mineral and bone disorders associated with CKD. According to KDIGO, which offers evidence-based clinical practice guidelines for kidney disease, pre-COVID-19 instructions offer that calcitriol supplements should be reserved for patients with CKD stages 4 or 5 with severe and progressive secondary hyperparathyroidism . Our resWe did not find lower rates of SARS-CoV2 infection with the use of calcitriol in the whole cohort, and the use of higher doses of calcitriol were not associated with lower risk of SARS-CoV2 infection in treated patients. These results would suggest that pathophysiological mechanisms that intervene in the process of infection are different from those that take place in the minority of patients that develop severe lung or systemic inflammation. Calcitriol exerts anti-inflammatory effects that can be mediated through several mechanisms, such as decreasing the production of pro-inflammatory cytokines , inhibitWe think that our study has some strengths, including the assessment of COVID-19 outcomes in a large population under calcitriol supplementation and the use of a matched cohort of controls. This study also has some limitations. First, there are the limitations of an observational cohort. Although we were comprehensive in analyzing many covariables, it is possible that there are still important covariables not considered in the matching process that may disbalance the treated and control groups. For this reason, we also analyzed the dosing of calcitriol to assess the associations between calcitriol doses and COVID-19 outcomes within the treated group, observing similar results. Second, our data were obtained from the registries of the health administration of the government of Catalonia, which are fed by the diagnoses issued by family physicians, hospital discharge reports or medicines supplied by pharmacies, with the inherent limitations of administrative data. Third, our population is mainly of Caucasian origin and we cannot exclude that our results may be different in other ethnic groups. Finally, we decided to focus our analysis on the first wave of the pandemic, with a higher number of severe cases and mortality. However, the diagnosis of SARS-CoV2 in that phase could not be ascertained with PCR in all the cases, and some patients received a clinical diagnosis without a confirmatory microbiological confirmation.In this large, population-based study, we have shown that supplementation with calcitriol was associated with significant reductions in COVID-19 severity and mortality, particularly in patients with advanced CKD. In our opinion, a clinical trial to confirm the effects of calcitriol on COVID-19 would be justified. Meanwhile, calcitriol supplementation should be considered in patients with CKD during the COVID-19 pandemic.


The precise diagnosis of COVID-19 is of outmost importance in order to effectively treat patients and prevent SARS-CoV-2 transmission. Herein, we evaluated the sensitivity and specificity of the COVID-19 Antigen Detection Kit  compared with PCR in nasopharyngeal and nasal samples. A total of 114 positive and 244 negative nasopharyngeal specimens confirmed by PCR were used in this comparative study. When the PCR positive Cycle Threshold (Ct) value was ≤25, CG sensitivity was 100%. When the PCR positive Ct value was ≤33, CG sensitivity was 99%. When the PCR positive Ct value was ≤40, CG sensitivity was 89.47%. Regarding nasal swabs, a total of 109 positive and 250 negative specimens confirmed by PCR were used. When the PCR positive Ct value was ≤25, CG sensitivity was 100%. When the PCR positive Ct value was ≤33, CG sensitivity was 96.12%. When the PCR positive Ct value was ≤37, CG sensitivity was 91.74%. Specificity was above 99% regardless of the Ct value of PCR positivity for both nasopharyngeal and nasal specimens. Overall, the CG showed high sensitivity and specificity when the PCR Ct value was less than 33. Therefore, CG can be used for screening early in the disease course. Confirmatory PCR is essential when a false negative result is suspected. The outbreak of the new coronavirus SARS-CoV-2) infection has become a global public health crisis . Researc infectioSARS-CoV-2 is a single-stranded RNA virus that can primarily cause upper and lower respiratory tract infections after invading the human body. The main symptoms are fever, fatigue, and dry cough. In severe cases, breathing difficulties may gradually occur. Some patients have mild or even no symptoms, whereas others may present with a constellation of symptoms originating from several organs in the body . AsymptoAlthough the therapeutic approach for patients with COVID-19 has been significantly improved since the onset of the pandemic, prompt diagnosis remains the cornerstone of optimal therapeutic intervention and prevention of SARS-CoV-2 transmission . The diaAs an auxiliary diagnostic method, the antibody detection kit can simultaneously detect IgM and IgG antibodies . The proFurthermore, antigen detection kits aim to detect the pathogen itself, and, therefore, they provide direct evidence of viral infection even at the early stages of the disease ,24. The In this context, herein we evaluated the COVID-19 Antigen Detection Kit  produced by Zhuhai Lituo Biotechnology Co., Ltd., which aims to detect the N protein of the SARS-CoV-2.Two retrospective studies were designed to assess the COVID-19 antigen detection kit  manufactured by Zhuhai Lituo Biotechnology Co., Ltd., Changsha, Hunan, China. The institutional review board of the General Hospital Jesenice approved the study (Number 2020/02). Participants provided oral informed consent for their samples to be evaluated for SARS-CoV-2 testing. We compared the results from the COVID-19 antigen detection kit  with the RT-PCR results of samples from clinical cases with suspected COVID-19 in order to determine the sensitivity, specificity, and accuracy of the new method. As we aimed to assess the role of the COVID-19 antigen detection kit  in the early detection of COVID-19, only patients reporting symptoms for a maximum of 7 days were included. Two kinds of specimens were used for evaluation: nasal swabs and nasopharyngeal swabs. Nasopharyngeal swabs are the most widely used clinical diagnostic specimens for the antigen test due to their high sensitivity and specificity . HoweverAll samples were collected from patients suspected of having COVID-19 at a single center in Slovenia. Nasal and nasopharyngeal swabs were simultaneously collected from the same patient. The swab specimens were collected as follows: The sampling swab was inserted into the nasopharyngeal/nasal cavity with the most secretions. The swabs were rotated gently, pressed on the nasopharyngeal/nasal wall three times, then inserted into the other nostril and the above steps were repeated. The swab head was then removed from the nasopharyngeal/nasal cavity quickly and was immersed in the sample treatment solution. After collection, the specimens were processed with the extraction buffer provided by the COVID-19 antigen detection kit . The test was completed within 10 min. For negative specimens, the reagents actually can give out results in around 3 min. However, we still recommend to read the results between 10 to 15 min. Results after 15 min should not be considered valid. Left over fluids with appropriate swabs were transferred in two UTM mini transport media . Two specimens were used for extraction of RNA. Two specimens of each patient were collected simultaneously; one for the experiment kit and one for RT-PCR reagent detection. The CE marked two gene reverse transcriptase polymerase chain reaction (RT-PCR)  was used as comparator throughout the clinical evaluation. The handling of all samples was performed in accordance with the institutional rules of microbiologic safety.The new coronavirus particles are wrapped with a lipid bilayer membrane. There are three glycoproteins on the membrane surface: Spike Protein ; Membrane glycoprotein ; Membrane Protein  . One of This kit adopts the double antibody sandwich method to qualitatively detect novel coronavirus antigens in human nasopharyngeal, oropharyngeal, and nasal swab specimens, and saliva specimens. The kit uses colloidal gold to label anti-human coronavirus monoclonal antibody 1. Then, coronavirus monoclonal antibody 2 and polyclonal antibody goat anti-mouse IgG is coated in nitrocellulose membrane.When the tested sample is positive, the antigen in the specimen binds to the antibody 1 labeled with colloidal gold. Then, the antigen is chromatographed to the detection area and binds to the pre-coated anti-human coronavirus monoclonal antibody 2 to form a double antibody sandwich complex, which generates red color. Both antibody 1 and antibody 2 form specific binding with the N-protein on the SARS-CoV-2. The remaining colloidal gold-labeled antibody is combined with the polyclonal antibody at the quality control line to generate red color. Negative samples generate red color only at the quality control line.The Cycle Threshold (Ct) value cut-offs of 25 and 33 are based on the normal requirements in most of the tenders in the EU. The Ct value of 40 can distinguish between the presence or absence of coronavirus infections in RT-PCR reagents; therefore, we set this cut-off as the highest value.The evaluation indicators for this clinical evaluation include sensitivity, specificity, and accuracy. The sensitivity of a test is its ability to determine the patient cases correctly. To estimate the sensitivity of the COVID-19 antigen detection kit , we calculated the proportion of true positives in patient cases (PCR positive). The specificity of a test is its ability to determine the healthy cases correctly (PCR negative and no symptoms of COVID-19). To estimate the specificity of the COVID-19 antigen detection kit , we calculated the proportion of true negative in healthy cases. The accuracy of a test is its ability to differentiate the patient and healthy cases correctly. To estimate the accuracy of the COVID-19 antigen detection kit , we calculated the proportion of true positive and true negative in all evaluated cases. We used Cohen’s Kappa formula to analyze the raw data.Overall, 358 nasal and 358 nasopharyngeal swabs were simultaneously collected from the same patients. One additional nasal swab was taken from a patient that developed another symptom of COVID-19 the next day.Regarding the evaluation of nasopharyngeal samples, the COVID-19 antigen detection kit  and PCR detection kit were used simultaneously to test nasopharyngeal swab specimens, which were sampled at the Primary Care Health Care institution and General Hospital Jesenice, Slovenia. A total of 114 positive and 244 negative specimens confirmed by PCR were used in this comparative study. The minimum Ct value of PCR positivity was 13.4 and the maximum Ct value was 38.4. There were 70 specimens with a Ct value of less than 25, 30 specimens with a Ct value between 25 to 33, and 14 specimens with a Ct value above 33.When the Ct value of PCR positivity was less than 25, the antigenic test detected all 70 PCR positive samples. The antigenic test detected only one false positive out of 244 PCR negative samples . TherefoRegarding the evaluation of nasal swabs, we performed a comparative study between the new antigen test and RT-PCR. The COVID-19 antigen detection kit  and PCR detection kit were used simultaneously. A total of 109 positive and 250 negative specimens confirmed by PCR were used in this study. The Ct value of PCR positivity ranged from 16.7 to 36.9. Among the PCR positive samples, 61 had a Ct value less than 25, 103 had a Ct value less than 33, and 109 had a Ct value less than 37.Among the samples with PCR Ct values less than 25, the antigen test detected all positive specimens . ImportaIn this study we present an independent clinical evaluation of the immunochromatographic COVID-19 antigen detection kit  in nasopharyngeal and nasal swabs compared with RT-PCR, among patients suspected of having COVID-19. The new antigen test had excellent diagnostic accuracy (above 95%), regardless the type of specimen and the Ct value of PCR positivity. The specificity of the antigen test was also above 99% in all settings. The sensitivity of the antigen test was really encouraging and ranged between 89% and 100%. When the Ct value of PCR positivity increased to 33 and above, a drop in sensitivity became evident in both the nasopharyngeal and nasal specimens. Higher Ct values of PCR positivity are associated with a decreased concentration of SARS-CoV-2 viral particles in the solution and, therefore, the detection rate of positive samples with the antigen test decreases. For this reason, we included only patients suspected of having COVID-19 and with suspected COVID-19-related symptoms with a duration of no more than 7 days, in order to assure an adequate concentration of the virus in the specimens.Furthermore, the absolute sensitivity value was lower for the nasal specimens in Ct values of PCR positivity less than 33 but higher for the nasal specimens in Ct values of PCR positivity less than 40, as compared with the corresponding values for the nasopharyngeal specimens. These slight differences may be attributed to the number of patients with high PCR Ct values in each sub study; more specifically, 8 patients had PCR Ct values between 35 and 38 in the nasopharyngeal sub study, whereas in the nasal sub study only 2 patients had PCR Ct values in that range.Our results are comparable to other studies. One study compared two analyzer-based tests to single gene SARS-CoV-2 RT-PCR. The chromatographic immunoassay BD Veritor System for Rapid Detection of SARS-CoV-2 nucleocapsid antigen (Veritor) showed a high positive percent agreement with the PCR results ranging from 81.8% to 87.5%, which is compatible to the high accuracy rates found in our study . Based oAnother study compared several immunochromatographic antigen tests to RT-PCR. Sensitivity was between 16% to 85%. The wide sensitivity range was attributed to the use of non-validated samples . In one Another study evaluated the Standard Q COVID-19 Ag test , which is a rapid chromatographic immunoassay, for the detection of SARS-CoV-2 nucleocapsid antigen in 454 respiratory specimens. Similar to our results, the sensitivity and specificity were 98.33% and 98.73%, respectively .FindDx platform has published several validations of immunochromatographic antigen SARS-CoV-2 assays. Our approach showed similar performance to the best SARS-CoV-2 antigen immunochromatographic tests in other comparisons  ,32. A stIn a Cochrane meta-analysis, the sensitivity of antigen tests varied considerably from 0% to 94% across five studies on 943 samples . In an uOur study has some limitations. It was performed in a single centre and, thus, the level of expertise of the personnel performing the sampling may be different from other hospital settings. Therefore, the education of all health care workers is very important in order to safely and accurately perform this procedure. Furthermore, we included only symptomatic patients presenting with symptoms with a duration of less than 7 days; thus, generalization of our results for asymptomatic carriers and patients with long lasting symptoms should be made with caution. Another potential limitation lies in the fact that our study focuses on RT-PCR for the diagnosis of COVID-19. Although the approved RT-PCR detection kits have high sensitivity and specificity rates, the results should be interpreted in association with clinical and radiological findings in a tailored manner.In conclusion, our results show that the COVID-19 Antigen Detection Kit  fulfils the WHO criteria for point-of-care COVID-19 tests of 80% sensitivity and 97% specificity in health care settings. Nasopharyngeal and nasal swabs have comparable high sensitivity, specificity, and accuracy in symptomatic patients with COVID-19 symptoms experienced for less than 7 days. Nasal swabs may be more convenient to collect in the clinical practice, especially in high patient volume settings. In the case of a negative antigen test despite high COVID-19 suspicion, a confirmatory PCR is necessary as the gold standard method.


The COVID-19 epidemic has differentially impacted communities across England, with regional variation in rates of confirmed cases, hospitalisations and deaths. Measurement of this burden changed substantially over the first months, as surveillance was expanded to accommodate the escalating epidemic. Laboratory confirmation was initially restricted to clinical need (“pillar 1”) before expanding to community-wide symptomatics (“pillar 2”). This study aimed to ascertain whether inconsistent measurement of case data resulting from varying testing coverage could be reconciled by drawing inference from COVID-19-related deaths.We fit a Bayesian spatio-temporal model to weekly COVID-19-related deaths per local authority (LTLA) throughout the first wave (1 January 2020–30 June 2020), adjusting for the local epidemic timing and the age, deprivation and ethnic composition of its population. We combined predictions from this model with case data under community-wide, symptomatic testing and infection prevalence estimates from the ONS infection survey, to infer the likely trajectory of infections implied by the deaths in each LTLA.A model including temporally- and spatially-correlated random effects was found to best accommodate the observed variation in COVID-19-related deaths, after accounting for local population characteristics. Predicted case counts under community-wide symptomatic testing suggest a total of 275,000–420,000 cases over the first wave - a median of over 100,000 additional to the total confirmed in practice under varying testing coverage. This translates to a peak incidence of around 200,000 total infections per week across England. The extent to which estimated total infections are reflected in confirmed case counts was found to vary substantially across LTLAs, ranging from 7% in Leicester to 96% in Gloucester with a median of 23%.Limitations in testing capacity biased the observed trajectory of COVID-19 infections throughout the first wave. Basing inference on COVID-19-related mortality and higher-coverage testing later in the time period, we could explore the extent of this bias more explicitly. Evidence points towards substantial under-representation of initial growth and peak magnitude of infections nationally, to which different parts of the country contribute unequally.The online version contains supplementary material available at 10.1186/s12889-022-13069-0. The COVID-19 epidemic has impacted communities heterogeneously across England since evidence first emerged of local transmission in March 2020 [related deaths, including both test-confirmed and clinically suspected cases (where the disease is considered to be the primary cause of death or a contributing factor) - can be considered more consistently recorded over time. We seek to exploit the biological link between the two sources of data to obtain a clearer picture of the burden of COVID-19 during the first wave, and to quantify the extent of under-ascertainment - by which we mean the gap between reported, confirmed cases and total infections - during scale up of testing.In particular, laboratory confirmation of cases was initially restricted to urgent clinical need of patients and healthcare staff (“pillar 1”) before being expanded to encompass all symptomatic cases in the wider community (“pillar 2”) from 18 May 2020 . These dObserved variation in the rate of COVID-19-related deaths can be considered a result of two spatially varying components: variation in incidence of infection and variation in fatality risk among those infected. Several individual-level characteristics have been highlighted as risk factors for COVID-19 case fatality - including age, deprivation and belonging to certain ethnic groups - all of which are themselves geographically clustered  were excluded. Local authority shapefiles and single-age population estimates were obtained from the Office for National Statistics (ONS) [Anonymised line lists of reported COVID-19-related deaths between 1 January and 30 June 2020 were provided by Public Health England (PHE). COVID-19-related deaths were considered to include those with COVID-19 recorded as an underlying cause, or where COVID-19 was mentioned as a contributing factor but not specified as cause of death. These two categories included a total of 52,560 reported deaths in England which occurred between 5 January and 30 June 2020, of which 39,332 had laboratory-confirmed infections and 13,228 non-confirmed but suspected. Counts were then aggregated by lower-tier local authority (LTLA), week of death (counted from Wednesday 1 January 2020) and 10-year age group. Aggregation by week was chosen in order to avoid excessive zero or low counts and potential day-of-week reporting effects, and to obtain a smoother representation of the epidemic curve. Records which did not have a LTLA provided (cs (ONS)  and matcLTLAs can be classified into one of four geographical categories: London borough , metropolitan district (11.5%), non-metropolitan district (60.3%) and unitary authority (17.9%). The former two categories capture the major urban areas of the country  with high connectivity both nationally and internationally, while the latter capture predominantly rural areas and smaller towns or cities.PCR-confirmed cases (i.e. COVID-19 infections identified through both pillar 1 and pillar 2 surveillance) were obtained from the same source and aggregated to the same spatial and temporal resolution. Finally, estimates of infection prevalence in England were obtained from the ONS COVID-19 infection survey pilot (15) which was initiated in May 2020. These are presented as an estimated percentage  of the population who would test positive via PCR for COVID-19 during rolling fortnightly intervals.prior to the expansion of symptomatic community testing on 18 May 2020 will be referred to as pre-P2 cases, and infections confirmed following expansion of testing will be referred to as post-P2 cases. It is noted that, due to piloting of pillar 2 testing among high-risk groups, a proportion of pre-P2 cases will have been detected via the pillar 2 route. We conservatively define the surveillance policy change from the point at which pillar 2 was fully available to all symptomatic individuals - assuming that case data from this point most accurately reflect the increased coverage of the expanded system - and define the terminology according to this distinction. We will also introduce the concept of predicted-P1+P2 cases, meaning the predicted infections which would have been PCR-confirmed in the hypothetical scenario in which symptomatic community testing had been in place since the beginning of the epidemic (January 2020). These predicted-P1+P2 cases form a subset of total symptomatic cases, conditional on the additional criteria that the case must be both symptomatic and seek and obtain a confirmatory positive test result. Lateral flow devices were not introduced for asymptomatic testing until later in the year [COVID-19-related deaths, i.e., those where either PCR-confirmed or clinically diagnosed COVID-19 infection is recorded on the death certificate.For the remainder of the paper, infections confirmed with a positive PCR test and recorded in official case data the year  and therR-INLA [Bayesian mixed effects models for deaths per week and per LTLA were fitted using integrated nested Laplace approximation (INLA), implemented via the R package R-INLA , 16.E, were calculated for each LTLA to serve as an offset in models. Expected counts were based on age-specific weekly mortality rates averaged over the observed time period and over the country as a whole. See Additional file i were assumed to follow a negative binomial (NB) distribution, with log link function, offset by log (Ei).To facilitate comparison in observed deaths across local authorities with different population age distributions, age-adjusted expected deaths, In addition to age, two population level characteristics were considered as risk factors for case fatality: level of deprivation and distribution of ethnicity. The Index of Multiple Deprivation (IMD) score is defined as a relative measure of deprivation between Lower Super Output Areas (LSOAs) and incorporates a range of social, economic and health factors . LSOAs aThe temporal dependence in the data was modelled using a combination of random effects with random walk (RW) correlation structures . A seconModels without any specified spatial structure were compared to those with independent and identically-distributed (IID) random effects per LTLA, and with a combination of IID and structured, conditional auto-regressive effects Baseline Observed deaths ~ log(E) (offset) + Overall epidemic trend (RW2) + calendar week trend (RW1) + covariates ; no spatial structure.(B)A + geography-dependent epidemic trends(C)A + IID spatial structure.(D)B + IID spatial structure.(E)A + BYM spatial structure.(F)B + BYM spatial structure.Six models were fitted and compared:The distributions of structured random effects  were fit with penalised complexity priors on the precision and BYM mixing parameters , and fixAll analyses were performed in R version 3.6.3 (2020-02-29). All code used to run these analyses have been made available at 10.5281/zenodo.5763664.n = 1000) were drawn to explore the uncertainty in predictions and aggregated over LTLAs to give total trajectories over time.Models were compared using the Widely Applicable Information Criterion (WAIC)  and log predicted-P1 + P2 cases from modelled deaths in the primary analysis, while a sensitivity analysis was conducted assuming two- and three-week lags. This choice was informed by the swab-death delay distribution observed in this dataset , while also considering an external report from the COVID Clinical Information Network (CO-CIN) [It was assumed that post-P2 cases (swabbed from 18 May 2020 onwards) were reflective of the higher coverage surveillance and less obscured by capacity constraints. A fixed lag of 1 week between date of swabbing and date of death was applied to infer (CO-CIN)  which suThe approach taken to infer predicted-P1 +P2 cases from reported deaths consisted of three steps. First, smoothed trajectories of deaths per week and per LTLA, corrected for spatial heterogeneity in case-fatality risk factors, were obtained from the fitted model . An LTLA-level ratio of cases per covid-related death  was then estimated for every week beyond 18 May 2020 and for each posterior sample, lagging the modelled death counts by 1 week  and comparing to post-P2 cases. CPDRs were summarised over all post-P2 weeks to obtain a median and IQR for each LTLA, which were then used to scale up the posterior samples over the whole time period. This yielded an estimate of the magnitude of cases giving rise to those deaths, which would have been detected under expanded surveillance. The distributions across posterior samples are summarised into 1, 25, 75 and 99% quantiles - yielding 50 and 98% Credible Intervals (CrI) - for presentation.The previous steps yield local trajectories of COVID-19 cases which would have been detected through combined hospital and community-based symptomatic testing, had such capacity been available throughout the first epidemic wave. However, post-P2 cases detected under expanded surveillance remain a subset of the total number of infections, which also include those that are asymptomatic or otherwise undetected. The ONS COVID-19 infection survey pilot  suggesteA summary of the observed incidence of covid-related deaths and pre−/post-P2 confirmed cases is shown in Fig. Overall, COVID-19-related mortality rates ranged from 10 per 100,000 in South Hampshire to 196 per 100,000 in Hertsmere . Cumulative incidence of confirmed cases was more varied between LTLAs, ranging from 71 per 100,000 in Torridge in North Devon, to 1040 per 100,000 in the East Midlands city of Leicester . Supplementary Fig. SBy comparison of information criteria (WAIC) and cross-validated log score, it is clear that adjustment for epidemic timing and the specified fatality risk covariates (model A) were insufficient alone to explain the spatial distribution of deaths across England. Out of the six candidate models, the BYM spatial model and temporal trends specific to the geography of the LTLA was selected as offering the lowest WAIC and best cross-validated fit (model F) Table . Models The final model suggested strong associations between weekly rates of COVID-19-related deaths in a LTLA, quintiles of deprivation score and proportion of minority ethnicities in the population , after adjusting for the size and age distribution of the local population  of the residual spatial variation  could be explained by correlation between neighbouring LTLAs as opposed to random noise. This suggests that there is correlation in observed mortality in neighbouring areas which is not explained by similarities in the size, age distribution, ethnic composition or deprivation level of their populations. A decomposition of the fitted spatial random effects for each LTLA is illustrated in Supplementary Fig. SPrior to the expansion of pillar 2 surveillance, the median CPDR per LTLA was 4.1 confirmed cases per covid-related death . From 18 May 2020 onwards, this increased to a median of 5.2 with more variation between LTLAs . Further detail of the spatial heterogeneity in CPDR across the country is illustrated in Supplementary Fig. S.0). FromFigure The four geography types contribute unevenly to this difference. In London, the reconstructed counts suggest a relative under-representation of the peak incidence in observed confirmed cases, which narrows relatively rapidly from April onwards as numbers decline and testing capacity increases. The implied under-ascertainment in London is of a much smaller magnitude than the other three geographies; in particular for metropolitan districts and unitary authorities, results suggest that, at the height of the epidemic, confirmed cases potentially constituted less than half of the symptomatic cases which would have been detected under the expanded system. For the predominantly rural non-metropolitan districts the difference at the peak is less substantial, though still greater than that of London. From late-April, total confirmed case incidence across these LTLAs actually exceeds the reconstructed counts, by a small margin which diminishes towards the beginning of the summer see Fig. .Assuming a longer two-week lag between testing and death yields a much larger difference of 86%, and for 3 weeks this increases further to 135%. A comparison of reconstructed national totals based on three different lags is included in Supplementary Table SFigure n = 231,817) constitute 17.5% (98% CrI 13.3 to 22.3%).This yields a cumulative total of 1.3 million infections (98% CrI 1.04 to 1.74 million) throughout the first wave, of which the observed confirmed cases , or well-documented risk factors of COVID-19 death . Similarities in risk between neighbouring LTLAs can be an important factor to consider for the design of local mitigation strategies, particularly in response to the detection of new variants.related deaths as opposed to deaths directly attributed to COVID-19 among confirmed cases.Assuming that the epidemic curve of deaths represents a specific subset of total symptomatic - i.e., detectable under Pillar 1 and 2 testing strategies - infections, this analysis suggests that over 100,000 additional cases may have been counted across the country in the absence of the initial constraints on testing capacity. The uncertainty around this estimate is relatively broad , predominantly as a result of uncertainty in the case-per-death ratio used to translate between the two measures. The increased heterogeneity between LTLAs in estimated CPDR following pillar 2 expansion may to some extent be attributed to much lower counts of both cases and deaths as the epidemic waned, and the occurrence of local outbreaks. Overall, we estimate around four post-P2 confirmed cases per covid-related death across all LTLAs, or equivalently a rate of 0.25 deaths per case. This is higher than estimates of the case-fatality rate i.e. the rate of deaths among confirmed cases, due to our broader definition of covid-Cases ascertained, even under the expanded system, remain a subset of total infections. The case estimates obtained here were therefore combined with estimates of infection incidence from the ONS’s pilot survey in order to explore the rate of detection over time and between LTLAs. This investigation suggested that, following the roll-out of symptomatic community testing, around a quarter of infections in England were being detected - a value consistent with estimates obtained by Colman et al.  for the The extent of this under-ascertainment was found to vary not only over time alongside the expansion of testing capacity, but also between LTLAs. Comparing the final model fit to the observed deaths suggested relatively little deviation of each LTLA from the fitted geography-specific trends, yet the reconstructed infections differ from observed test positives with much more variation between LTLAs. Greater observed incidence rates appeared to coincide with poorer detection of total infections - perhaps reflecting the impact of reaching testing capacity - yet this trend was found to be inconsistent between regions. This demonstrates the sporadic nature of case observation over time and space and highlights certain areas of the country in which surveillance was perhaps more strongly impacted by testing constraints. These differences may in part be attributed to local variation in the relationship between cases and deaths which isn’t sufficiently captured by the assumed case-fatality covariates. We therefore advise that LTLA-specific estimates should be interpreted with consideration of the local context.. Genomic analysis suggests that importations into the UK alone peaked mid-March with up to 1000 per day [Early projections based on critical care admissions by Jit et al.  suggeste per day .symptomatic infections across the UK had occurred by mid-April 2020 with a magnitude of around 100,000 per day, and concluded that during March only 3–10% of such cases were being detected. This suggests a substantially higher peak than our estimate for England alone of just over 200,000 total infections per week - on average 28,000 per day - even accounting for the distribution of population between the constituent countries. Our estimates suggest that the percentage of these total infections reflected in confirmed case counts varied from around 7% at the start of March to 11% at the end, slightly higher than the detection rate Russell et al. estimated among symptomatic infections. Overall, estimates of infection incidence appear to be variable across studies, at least in part due differences in case definitions and aggregation over space and time.Russell et al.  took a dThe interpretation of these findings depends on several key assumptions, most importantly that variability over time in the ratio of confirmed cases to COVID-19-related deaths is predominantly the result of varying accessibility of testing. It is however plausible that fatality risk would have varied over time, potentially increasing towards the peak of the wave due to strain on hospitals forcing re-prioritisation of care or decreasing later on as treatment options improved. Also, it was assumed that variability in the delay from swabbing to death on the individual level would be diluted by aggregation, hence a fixed-value lag  would suffice. Summarising observed delays between swabbing and death within the available data gave no reason to suggest a difference between the time periods pre- and post-pillar 2 expansion, therefore the same fixed lag was assumed throughout the epidemic wave. A more exact approach, however, would have been to incorporate the full distribution of swab-death delays and redistribute the observed deaths in time according to an imputed point of detection.Only three broad characteristics were considered as case-fatality risk factors, which essentially serve as proxy measures for complex combinations of underlying comorbidities and health indicators across the population. Dichotomising self-identified ethnicity in a population into “majority” and “minority” groups is crude, given that risk has been found to differ between ethnic groups in different ways . We implIn individual level analysis, comorbidities such as cardiovascular disease, diabetes, and cancer were shown to have an association with mortality after adjusting for both ethnicity and deprivation level . The locFinally, this approach does not account for the dynamics of transmission in and around long-term residential care facilities during the early months of the pandemic, within which many deaths during the first wave occurred . The natEffective and efficient control of an infectious disease epidemic relies on appropriate quantification of risk at a local level from available surveillance data. However, there are many reasons for which such data may not be equally representative of disease burden across different regions and populations. In the case of the COVID-19 epidemic in England, it is known that limitations in testing capacity distorted the observed trajectory of cases during the first wave. In this analysis, by combining more consistently reported data on deaths and more representative case data from later in the epidemic, it was possible to reconstruct a plausible trajectory of symptomatic cases which could have been detected in the absence of the early testing constraints, and further to infer the total number of infections these reported cases would represent. This facilitated a comparison between the two testing policies and highlighted heterogeneity in case ascertainment across different regions of the country.The burden of disease and impact of the response to this pandemic will be evaluated in detail for years to come. Considering how changes in surveillance policy can obscure the spread of an epidemic - using methods such as those demonstrated here - will be essential, in particular for understanding the consequences of the country’s initial level of pandemic preparedness.Additional file 1. Supplementary Materials.Additional file 2.  Final predicted-P1+P2 and total infections for the entire time series in each LTLA.