Vaccines are needed to protect from SARS-CoV-2, the virus causing COVID-19. Vaccines that induce large quantities of high affinity virus-neutralizing antibodies may optimally prevent infection and avoid unfavorable effects. Vaccination trials require precise clinical management, complemented with detailed evaluation of safety and immune responses. Here, we review the pros and cons of available vaccine platforms and options to accelerate vaccine development towards the safe immunization of the world’s population against SARS-CoV-2. Favorable vaccines, used in well-designed vaccination strategies, may be critical for limiting harm and promoting trust and a long-term return to normal public life and economy. The COVID-19 pandemic holds great challenges for which the world is only partially prepared ,3. To liThe diagnosis of SARS-CoV-2 infection is achieved through detection of viral RNA from a nasal pharyngeal swab or saliva, by nucleic acid tests (NATs) or tests that detect viral protein antigens ,7. In inThe world can probably not afford to let the majority of citizens undergo SARS-CoV-2 infection, as the overall burden would be enormous. Current data indicate that a pandemic COVID-19 outbreak infects only low percentages  of the population, at least in countries that take effective measures against viral spread [The immune response to the SARS-CoV-2 involves innate immune activation and antigen-specific responses of B and T cells . ProtectHere, we review the mechanistic understanding of immunity and vaccination against SARS-CoV-2. We discuss vaccine target antigens and current vaccine candidates in preclinical and clinical testing. We also focus on the development and validation of precision serology to support preclinical and clinical evaluation of vaccine candidates and research on immune responses induced by natural infection. The basic and applied knowledge acquired during the last few decades is highly useful to design promising vaccines with increased likelihood of inducing protective immune responses and avoiding adverse effects and harmful disease enhancement. Now, probably more than ever, the world depends on rational effective strategies built on robust scientific evidence.Vaccine development has started at a strongly accelerated pace already, shortly after the beginning of the SARS-CoV-2 outbreak ,12,13. AIn view of the urgency of making vaccines available for billions of people, one must primarily focus on vaccines that can be produced in massive amounts and for which the production knowhow and facilities are available or can be built rapidly .Vaccines can be based on whole viruses (live-attenuated or inactivated), viral vectors, nanoparticles or virus-like particles, subunit components, proteins/peptides, RNA, DNA or live cells. The first vaccine trial against COVID-19 was started in China on February 15, 2020 , using dBox 1Currently there is no vaccine available against these two viral threats ,26. NeveA study of non-human primates vaccinated with an inactivated virus showed high levels of neutralizing antibodies, high levels of protection and no unfavorable disease enhancement . In the Nanoparticles and virus-like particles (VLPs) have delivered successful vaccines. They can be engineered to display epitopes of foreign viruses on their surface, rendering those epitopes highly immunogenic. Molecules that stimulate innate immunity can be encapsulated within VLPs to enhance immune responses and trigger favorable T helper type 1 (Th1) polarized immune responses (type 1 immunity) rather than potentially disease enhancing Th2 polarization .The clinical trials that are now urgently needed to evaluate the COVID-19 vaccine candidates serve to determine optimal vaccine dose and scheduling and whether multiple booster vaccinations are required. Usually, more robust and long-term immunity can be induced by sequential vaccinations, possibly necessary for those with expected weak immune responses, such as in elderly or immune deficient individuals . The cliclinicaltrials.gov, clinicaltrialsregister.eu and/or chictr.org.cn. At present, 24 and 142 vaccine candidates are in clinical and preclinical evaluation, respectively [The time required for vaccines reaching the wider public also highly depends on regulatory authorities and their flexibility to accelerate the process and vaccine approval, as compared to standard procedures established for less urgent health threats. The WHO roadmap  providesProtection induced by currently available vaccines against viruses is primarily based on virus-neutralizing antibodies. Such antibodies usually block the interaction of the virus with its cellular receptor or prevent conformational changes required for fusion of the virus with the cell membrane. The SARS-CoV-1 virus has been studied in substantial detail . Recent Box 2The family of SARS-CoV-1 viruses consists of several groups of strains (comparable to many other viruses) hosted by animals, humans or both . The antS protein interaction with ACE2 is well described for both SARS-CoV-1 and -2 and relies on a particular domain within the S protein, the so-called receptor binding domain (RBD). Indeed, most antibodies capable of neutralizing coronaviruses are directed against RBD ,52 Box . Hence, The second most frequent choice is to use the whole S1 subunit. Other vaccine manufacturers use the full-length S protein  and/or tVaccine antigens may be used in the form of protein or peptides. A recent study has shown that a SARS-CoV-2 S1-Fc fusion protein readily induced neutralizing antibodies in non-human primates . ProteinThe most obvious isotype to be induced by a COVID-19 vaccine is IgG, preferably the more protective IgG1 and IgG3 subclasses. However, IgA may also be of importance to reduce infection of mucosa and epithelial cells in the respiratory tract, as well as endothelial cells, which may be widely targeted by the virus. While mucosal immunization at a large scale in a rapid fashion might be difficult, the use of an adjuvant that triggers the production of IgA might be an important consideration. TLR7/8 and TLR9 ligands are good candidates as they potently promote IgA responses ,63.CD4 and CD8 T cells recognize and react to SARS-CoV-2 antigens , contribT cell antigens must be presented by HLA molecules on the surface of antigen-presenting cells and infected cells. As HLA molecules differ in most people due to the huge genetic HLA polymorphism, viral recognition by T cells is based on a very large diversity of antigenic peptide/HLA complexes. Each person has her/his own T cell specificities for those antigenic peptides that bind to her/his HLA molecules. Vaccines containing short antigenic peptides or mini-genes will not work for most people, i.e., for those whose HLA molecules cannot present the respective antigenic peptides. In contrast, vaccination with long peptides or full-length viral proteins or corresponding DNA/RNA are potentially useful for many or all individuals.CD8 cytotoxic T cells primarily recognize viral peptides that are synthesized within the infected cell. In contrast, protein antigens that are picked up from the extracellular space are poorly presented to CD8 T cells. The one exception to this rule is in small fractions of dendritic cells that are capable of so-called cross-presentation, i.e., the cellular uptake of extracellular protein  and the presentation of processed peptides on HLA class I molecules to CD8 T cells . Cross-pAs compared to antibody induction, it is generally more challenging to induce long-term T cell responses through vaccination. Most vaccines are either attenuated pathogens or more often dead/synthetic vaccines which do not replicate in vivo. Yet, substantial microbial replication in vivo is usually required for the induction of strong T cell responses . It is tThe induction of CD4 T cell help is often not rate limiting in vaccination, probably because low numbers of these cells are already sufficient for supporting antibody production. Nevertheless, vaccination may fail due to CD4 T cell non-responsiveness. Since T cell help can be provided by CD4 T cells with other specificities by intermolecular help, a smart approach is to supplement vaccines by inserting microbial antigens to which most humans are already immunized . The conIt is not recommended to vaccinate for T cell responses without also efficiently inducing neutralizing antibodies, because the latter are likely the crucial key effectors, and also because T cells, particularly CD8 T cells, can cause extended tissue damage through their cytotoxicity against infected cells, which is likely increased in the absence of antibodies that neutralize the viruses in the extracellular space. Indeed, pure CD8 T cell responses induced by vaccination may enhance potentially lethal immunopathology .A concrete safety concern is the potential activation of Th2 cells. This was first observed in a clinically tested respiratory syncytial virus (RSV) vaccine, which consisted of inactivated virus and worsened clinical symptoms, with the deaths of two children upon infection with RSV. Disease enhancement was caused by Th2 cell-mediated eosinophilia, a problem associated with vaccines for respiratory vaccines. It is therefore essential to skew the response by vaccination towards Th1 polarization. Indeed, combining inactivated RSV with TLR-agonists reduces lung pathology upon viral challenge in murine models . ExperieAntibodies can either protect from infection and/or disease severity or be inefficient in doing so. In addition, some antibodies can be harmful. Antibody-mediated enhanced disease may be caused by two different mechanisms. The first is called antibody-dependent enhancement (ADE) of infection, which occurs when antibodies promote viral uptake via Fcγ receptors A, therebThere is no evidence in humans that ADE of infection occurs with SARS-CoV-1 . HoweverThe second mechanism is ADE of inflammation B. ActivaTogether, these data suggest that efficient and safe strategies of vaccination may be achieved by the preferential usage of antigens that display neutralizing epitopes and the relative avoidance of other epitopes to limit the risk through disease enhancing antibodies. Hence, RBD or RIS alone, perhaps combined with the fusion peptide, could be optimal, as other parts of the S protein and the other SARS-CoV-2 surface proteins could be potentially involved in ADE. Furthermore, vaccines that promote Th1 cell responses are preferable, which can be achieved by using viruses/viral vectors or innate immune stimulators with type 1 polarization capabilities ,88,89.Most respiratory viruses induce IgM, followed by IgG and IgA antibody responses. Seroconversion to SARS-CoV-2 infection occurred after 7 days in about half of the patients and by day 14 in nearly all patients . On averUnfortunately, most serology tests cannot directly determine whether the detected antibodies neutralize the virus, a mandatory parameter if protection is to be predicted. Upscaling of neutralizing antibody testing is limited because assays that directly demonstrate neutralization of SARS-CoV-2 must be done with the virus itself, which is only safe in highly specialized biosafety level-3 laboratories. Many groups have developed neutralization assays with retroviruses or vesicular stomatitis virus (VSV) pseudotyped with the SARS-CoV-2 S protein, allowing neutralization assays to be done in biosafety level-2 facilities ,94,95,96SARS-CoV-2 is known to mutate, bearing the risk that existing neutralizing antibodies may lose their protective power . Even thAssessment of Th2 cytokines such as IL-4/IL-5, or IL-17 as a marker for Th17 cells, may help to evaluate the risk of disease enhancement. Furthermore, measurements of cytokines and inflammatory parameters are important for monitoring patients with (risk of) severe SARS, in which strong cytokine production and inflammatory reactions may be associated with lung damage ,102. IncT cells are infrequently analyzed, and only in specialized laboratories, because viable cells require special and labor intensive laboratory handling . The greThere is currently still only little understanding of the relationships between SARS-CoV-2 infection, antibody responses and protection. A central issue is to determine whether vaccine candidates induce immunity. There are serious ethical and technical limitations to challenging vaccinated volunteers with live wild-type viruses with the aim of determining vaccine effectiveness. Alternatively, challenging with seasonal coronaviruses or attenuated viruses could be considered for this purpose, substantially reducing the risk for trial participants. In any case, trials should include volunteers with a high risk of natural infection, such as populations in highly affected regions and healthcare workers.Based on the current evidence, SARS-CoV-2 infection induces at least some degree of immunity, perhaps even in the majority of individuals . HoweverInteresting insights are offered from studying seasonal coronavirus common cold infections, which occur typically in winter to spring and are usually of mild nature . Indeed,A reason for the short duration of protection may be that coronaviruses have an interesting strategy to evade neutralizing antibody induction. As discussed previously for adenoviruses , SARS viA major hurdle is the very limited pre-existing clinical experience with any coronavirus vaccine, increasing the failure risk of COVID-19 vaccine trials and consequent delay. Fortunately, the ongoing multitude of parallel vaccine development may compensate for the experience deficit. Furthermore, there are many basic, translational and preclinical data in coronavirus research, which together with the massive ongoing scientific effort forms a favorable basis for rapid progress.We suggest that COVID-19 vaccines are promising when they induce large quantities of high affinity neutralizing antibodies and only relatively low amounts of other antibodies and immune responses bearing the risk of disease enhancement. Targeted by most neutralizing antibodies, RBD may be the virus’ Achilles heel. However, it is still only partially possible to predict vaccine efficacy and safety . It remaThe large scale use of vaccines inducing neutralizing antibodies is the best option to maximize the percentage of the population with immunity to SARS-CoV-2. It is realistic to achieve herd immunity through vaccination, whereas broad natural infection appears too risky for humans and the economy, unless viral spread induces immunity in much larger fractions of the world’s population than currently known and expected, possibly in countries with less rigorous measures for avoiding viral spread. Due to the urgency, COVID-19 vaccination is given high priority.Once proven efficient and safe, vaccines should undergo registration to ensure that the world is prepared for current and possible future SARS-CoV-2 outbreaks. At the same time, measures should be put in place, as is the case for influenza virus vaccines, that allow the rapid adaptation of existing vaccine platforms to newly emerging coronaviruses.


They functionally characterize a number of these interactions, leveraging the information to identify promising candidate molecules for drug-repurposing.In a recent study published in Science,Since 2002, there were three major outbreaks of novel coronaviruses in humans. SARS-CoV-1 emerged in 2002, MERS-CoV in 2013, and SARS-CoV-2 in 2019. While the first two viruses only spread regionally and caused under 1000 deaths each, SARS-CoV-2 has caused almost 55 million cases and over 1.3 million deaths globally as of November 2020. The rapid succession of outbreaks necessitates research into the conserved features of coronaviruses to build upon this knowledge should yet another coronaviral disease emerge. Conserved interactions are also more likely to be essential for virus function and less likely to rapidly evolve to develop drug resistance.2 with mass-spectrometry data obtained from a screen using tagged SARS-CoV-1 and MERS-CoV proteins as baits  dataits Fig. 1. ImmunoACE2, respectively. By measuring viral RNA in the supernatant or titrating the virus on Vero-E6 cells, they identified 31 and 40 dependency factors by siRNA and CRISPR screen, respectively, and three and four viral restriction factors , the matching based on RSS and PS resulted in an OR of 0.46 (0.23–0.93), demonstrating a potential benefit of typical antipsychotics in preventing the need for mechanical ventilation.Gordon et al. present an impressive tour de force by combining the generation of a widely useful resource on coronavirus host-pathogen interactions with both mechanistic and clinical insights, leveraging these to provide new avenues in the treatment of COVID-19. These will have to be investigated further to assess their efficacy and safety in a clinical setting, as well as patient populations that could benefit from them. Both antipsychotics and indomethacin can have serious adverse effects. Indomethacin can interfere with hypertensive medication, thus potentially exacerbating this risk factor for COVID-19, and impair kidney function as is also observed in COVID-19. IFN-β on the other hand may only be effective in early stages of the disease as viral clearance is mostly completed at ten days after the onset of symptoms, a time span below the average duration of mechanical ventilation in critical cases.


A young male with long-standing type 1 diabetes mellitus, chronic kidney disease, and known ventricular hypertrophy presented with dyspnea and abdominal pain and was diagnosed with coronavirus disease 2019 (COVID-19) infection. On day nine of hospital admission, patient developed ventricular tachycardia with electrocardiogram (ECG) changes and elevation in troponin level consistent with myocarditis and development of cardiogenic shock. Bedside limited echo demonstrated signs of tamponade and patient underwent surgical pericardial window procedure. He was also noted to develop marked prolongation of corrected QT interval (QTc) while on amiodarone. Coronavirus disease 2019 (COVID-19)-induced myocarditis has been noted to be a relatively late complication in the natural history of the disease. Pericardial effusion with tamponade physiology in this setting has been infrequently reported .A 30-year-old Latino male with a history of type 1 diabetes for the past 16 years, diabetic nephropathy with chronic kidney disease (CKD) stage III, glaucoma, hypertension, and obesity presented to the emergency department with bilateral abdominal flank pain and shortness of breath. The patient additionally had symptoms of fatigue, tiredness, and lightheadedness. The patient did not report any fever, hemoptysis, chest pain, palpitation, or syncope at presentation.Reverse transcription-polymerase chain reaction (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was positive on the day of admission. On admission, laboratory test values were brain natriuretic peptide of 557 pg/mL, creatinine of 4.74 mg/dL, blood urea nitrogen of 63 mg/dL, white blood cell count of 5.4 K/UL, hemoglobin of 6.6 g/dL, and platelet count of 220 K/UL. The liver function test result was normal, and ferritin was 218 ng/mL which increased to 1346 ng/mL on the 10th day after admission. C-reactive protein was 89 mg/L on the second day after admission and increased to 259 mg/L on the 10th day after admission. Troponin I was 0.09 ng/mL on admission, then increased to 7.52 ng/mL on the 10th day after admission and then decreased to 2.57 on day 12. The gene Xpert RT-PCR test for SARS-CoV-2 was positive 24 days after the initial diagnosis. The partial thromboplastin time was persistently elevated less than two times the upper limit of normal, and D-dimer was significantly elevated to 10 times that of normal on day 11. Blood cultures and sputum culture screens were negative, and procalcitonin was not elevated. The initial computed tomography of the chest on day three showed typical changes consistent with COVID-19 pneumonia with right pleural effusion and pericardial effusion  requirement continued to progressively increase over 12 hours to 100% supplemental oxygen by a high-flow nasal cannula system. The patient was switched to noninvasive positive pressure ventilation, but he continued to require an FiO2 of 80%. Later on the same day, the patient developed respiratory distress and was subsequently intubated and started on mechanical ventilatory support per the Acute Respiratory Distress Syndrome Network trial protocol. Continuous renal replacement therapy was also initiated for the patient for acute on chronic renal failure with volume overload. By day nine of hospitalization, the patient's oxygenation status had improved down to 60% FiO2, but during the evening of the same day, he developed episodes of hypotension, and norepinephrine and vasopressin infusion for vasopressor support were initiated. The patient also had episodes of non-sustained ventricular tachycardia. Twelve-lead ECG showed a wide QRS complex along with new-onset left bundle branch block Figure .Amiodarone infusion was initiated for high risk of malignant arrhythmia. Bedside echocardiography was performed, and it showed large pericardial effusion with early diastolic right ventricle prolapse along with a markedly thickened ventricular wall Figure .The patient was examined in January 2020, and at that time, an echocardiogram showed moderate ventricular hypertrophy along with trivial pericardial effusion. Based on these past results and the current situation, the patient underwent a surgical pericardial window procedure. Amiodarone was discontinued due to marked elevation in the corrected QT interval (QTc) to 853 ms Figure . The patImprovement in hemodynamics post-procedure was noted, with discontinuation of vasopressor support on the same day. The patient was extubated on day five postpericardiotomy after 15 days of mechanical ventilator support. The patient was discharged home on day 27 of hospitalization. Before discharge, he was hemodynamically stable without any ECG abnormality, had normal left ventricular systolic function, and trivial pericardial effusion on two-dimensional echocardiography and was oxygenating well on room air.Acute respiratory distress syndrome is the most common indication for transferring patients with COVID-19 to the intensive care unit and the primary cause of death in this patient population. Cardiac involvement with myopericarditis is a relatively late phenomenon in the disease progression but is suspected to be the primary reason for sudden cardiac death in patients with COVID-19 ,4. A fewSix months before the current hospital admission, our patient exhibited ventricular hypertrophy and trivial pericardial effusion at baseline echocardiography. Due to the development of acute kidney injury (AKI) on chronic kidney disease at presentation, the patient was hypervolemic, which led to pleural effusion and worsening of pericardial effusion compared to baseline echo. On approximately day 10 after presentation, our patient developed myopericarditis features with conduction abnormalities, QRS prolongation, non-sustained ventricular tachycardia, and elevation in troponin disproportionate to AKI. The patient also developed cardiogenic shock requiring vasopressor support. Bedside point-of-care echocardiography was diagnostic of early pericardial tamponade with significant systolic function impairment due to decreased cardiac filling. Post-pericardiotomy, vasopressor support was slowly withdrawn over 24 hours, and the ventilator was no longer necessary on postoperative day five.Pericardial tamponade should be strongly considered in the differential diagnosis of acute hypotension with signs of myocarditis in COVID-19 patients, particularly with acute renal failure. Due to the variable and limited availability of standard echocardiography for patients in airborne isolation because of infection control concerns, bedside point-of-care echocardiography is very useful in determining a differential diagnosis of hemodynamic instability in critically ill patients. Marked prolongation of QTc was noted in our patient on amiodarone, which suggests the need for close monitoring of QTc in patients with myocarditis who are receiving QTc-prolonging medications.


Plasmodium falciparum malaria during the rainy season. In response to the global COVID-19 pandemic, Malaria Consortium adapted its SMC delivery model to ensure safety of distributors, data collectors and beneficiaries. We conducted a SMC monitoring survey in July 2020 in the states of Bauchi, Jigawa, Kano, Katsina, Sokoto and Yobe, with questions on COVID-19 prevention behaviours and symptoms, and belief in misinformation. We investigated the associations between receipt of information on COVID-19 by different sources, including from SMC distributors, and these three outcomes using logistic generalised estimating equations. We also considered moderation of effectiveness of message delivery by SMC distributors and adherence to use of face coverings.Seasonal malaria chemoprevention (SMC) using sulfadoxine-pyrimethamine and amodiaquine is an efficacious intervention for protection of children against p < 0.001) and symptoms  and lower odds of belief in COVID-19 misinformation . The associations between message delivery by SMC distributors and the three outcomes were moderated by their adherence to face covering use. Receipt of information by other sources used to deliver government public health messages, including radio and health facility workers, was also associated with knowledge of COVID-19.We obtained a representative sample of 40,157 caregivers of eligible children aged 3–59 months, of which 36,914 (91.92%) reported knowledge of COVID-19. The weighted proportions of respondents who correctly identified COVID-19 prevention behaviours and symptoms, and who reported belief in COVID-19 misinformation, were 80.52% , 81.72% (95% CI 81.23–82.20) and 22.90% (95% CI 22.24–23.57). Receipt of information on COVID-19 from SMC distributors during the campaign was significantly associated with higher odds of caregiver knowledge of COVID-19 prevention behaviours (odds ratio [OR] 1.78, 95% CI 1.64–1.94, Malaria Consortium’s SMC programme was successfully adapted in the context of COVID-19 and was a conduit for high-quality public health messages. Standard SMC monitoring and evaluation activities can be adapted to gather evidence on emerging public health issues such as the global COVID-19 pandemic. Plasmodium falciparum malaria. The World Health Organization (WHO) recommends SMC administration to children aged 3–59 months in areas of high transmission to provide chemotherapeutic protection during the rainy season, when most deaths occur [Seasonal malaria chemoprevention (SMC) using one dose of sulfadoxine-pyrimethamine (SP) in combination with three daily doses amodiaquine (AQ) has been shown to be an efficacious –4 and cohs occur . In 2020hs occur .In response to the ongoing global COVID-19 pandemic, the global SMC community in collaboration with Malaria Consortium published guidelines  to suppoWhile there exists some evidence on knowledge and attitudes of COVID-19 in various settings, including Nigeria , there rThe purpose of this study was to describe the prevalence of knowledge of COVID-19 prevention behaviours and common symptoms suggestive of COVID-19, and belief in misinformation about COVID-19 among caregivers of children eligible for SMC in six Nigerian states covered by the SMC programme, and to investigate the relationship between these outcomes and receipt of COVID-19 information by SMC distributors and other 5were collected from 18 July to 4 August 2020 as part of the routine cross-sectional end-of-cycle survey for SMC cycle 1 in the states of Bauchi, Jigawa, Kano, Katsina, Sokoto and YobeAdditional questions related to COVID-19 were included in the survey for the purpose of this study, which respondents were asked if they reported that they had ever heard of ‘COVID-19’ or ‘coronavirus disease’ .Three outcomes were investigated. Knowledge of COVID-19 prevention was assessed based on spontaneous identification of at least one COVID-19 prevention behaviour listed on Malaria Consortium’s SMC ‘job aid’ 6. KnowleRespondents in compounds visited by SMC distributors were asked whether they had received information on COVID-19 from them and whether distributors were wearing masks or face coveringsAfter undertaking a descriptive analysis of each variable by state, we employed logistic generalised estimating equations with an exchangeable correlation structure to account for clustering of responses within wards to investigate the associations between information sources and the three outcomes . Post-saOf a total 40,157 respondents, 36,914 91.92% reportedThe statistical analysis found that receipt of information on COVID-19 from SMC distributors during the campaign was significantly associated with around 75% higher odds of caregiver knowledge of COVID-19 prevention behaviours and symptoms and negatively associated with belief in COVID-19 misinformation Table , model 1p < 0.001) with larger effect sizes and negatively associated with belief in misinformation  (model 3). Receipt of information via local leaders, health facility workers, CHWs, radio, television and town announcers was associated with knowledge of prevention behaviours. In addition to these sources, provision of information through religious leaders and other sources were positively associated with knowledge of symptoms. Word of mouth, after mutual adjustment for receipt of COVID-19 information via other sources including SMC distributors, was negatively associated with knowledge of COVID-19 prevention behaviours. Receipt of information via radio and health facility workers was negatively associated with belief in COVID-19 misinformation.Similar associations were found for models 2 and 3, before and after adjustment for receipt of COVID-19 information through other sources. Receipt of information from SMC distributors not wearing face coverings was significantly associated with increased knowledge of COVID-19 prevention behaviours and symptoms; no association was found for belief in misinformation. Meanwhile, receipt of information from SMC distributors wearing face coverings was positively associated with knowledge of prevention behaviours  and symptoms  is uncertain. Given its objective of rapidly assessing SMC programme coverage and quality of delivery over a wide geographic area, it was impractical to include questionnaire items on demographic variables to investigate individual-level predictors of the three outcomes. Reporting of information sources relied on caregiver recall. Another limitation was that of the language of the survey form; inconsistencies may have arisen in question phrasing during interpretation into Hausa, and difficulties in comprehension by non-native Hausa users may have been a cause of misreporting by caregivers. Responses indicating receipt of COVID-19 information via ‘word of mouth’ may have been a result of misinterpretation by both caregivers and data collectors. This category may have covered sources other than ‘family or friends’; interpretation of associations between receipt of information via word of mouth and study outcomes should therefore be interpreted with caution.While the results imply that national public health information campaigns in Nigeria were effective at increasing knowledge of COVID-19 and reducing belief in misinformation, vaccination or mass drug administration programmes, such as SMC, can also serve as conduits for high-quality public health messages and may complement efforts to reduce disease transmission. Their routine monitoring and evaluation activities, such as beneficiary surveys, may be quickly adapted to gather evidence on emerging public health issues such as the global COVID-19 pandemic.


Adults with chronic conditions are disproportionately burdened by COVID-19 morbidity and mortality. Although COVID-19 mobile health  apps have emerged, research on attitudes toward using COVID-19 mHealth tools among those with chronic conditions is scarce.This study aimed to examine attitudes toward COVID-19, identify determinants of COVID-19 mHealth tool use across demographic and health-related characteristics, and evaluate associations between chronic health conditions and attitudes toward using COVID-19 mHealth tools .We used nationally representative data from the COVID-19 Impact Survey collected from April to June 2020 . Primary exposure was a history of chronic conditions, which were defined as self-reported diagnoses of cardiometabolic, respiratory, immune-related, and mental health conditions and overweight/obesity. Primary outcomes were attitudes toward COVID-19 mHealth tools, including the likelihood of using (1) a mobile phone app to track COVID-19 symptoms and receive recommendations; (2) a website to track COVID-19 symptoms, track location, and receive recommendations; and (3) an app using location data to track potential COVID-19 exposure. Outcome response options for COVID-19 mHealth tool use were extremely/very likely, moderately likely, or not too likely/not likely at all. Multinomial logistic regression was used to compare the likelihood of COVID-19 mHealth tool use between people with different chronic health conditions, with not too likely/not likely at all responses used as the reference category for each outcome. We evaluated the determinants of each COVID-19 mHealth intervention using Poisson regression.Of the 10,760 respondents, 21.8% of respondents were extremely/very likely to use a mobile phone app or a website to track their COVID-19 symptoms and receive recommendations. Additionally, 24.1% of respondents were extremely/very likely to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. After adjusting for age, race/ethnicity, sex, socioeconomic status, and residence, adults with mental health conditions were the most likely to report being extremely/very or moderately likely to use each mHealth intervention compared to those without such conditions. Adults with respiratory-related chronic diseases were extremely/very  and moderately likely  to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19.Our study demonstrates that attitudes toward using COVID-19 mHealth tools vary widely across modalities  and chronic health conditions. These findings may inform the adoption of long-term engagement with COVID-19 apps, which is crucial for determining their potential in reducing disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions. Since the declaration of the COVID-19 pandemic in the United States, over 7 million COVID-19 cases have been identified, and more than 200,000 lives have been lost . EmerginThe proliferation of COVID-19 mobile health  tools for tracking COVID-19 statistics, monitoring potential COVID-19 symptoms, and reducing the social and mental health impacts of the COVID-19 pandemic has emerged simultaneously with the emergence of the pandemic -64. SeveThe aims of this study were (1) to identify differences in attitudes toward COVID-19 mHealth tools across individuals with chronic health conditions; (2) to evaluate associations between having a preexisting chronic health condition and attitudes toward using COVID-19 mobile-based apps and websites to track potential COVID-19 exposure and symptoms; and (3) to identify determinants of mHealth intervention use. To accomplish these study objectives, we used publicly available data from the COVID-19 Impact Survey, which was designed to provide a nationally representative sample of the US adult population and offer national insights about the American population’s experiences during the COVID-19 pandemic.Data for our analyses were obtained from the publicly available COVID-19 Household Impact Survey, which was conducted by the nonpartisan and objective research organization NORC  at the University of Chicago for the Data Foundation. The COVID-19 Household Impact Survey is a philanthropic effort to provide national and regional statistics about physical health, mental health, economic security, and social dynamics in the United States . The surAmeriSpeak is a probability-based panel that is funded and operated by the NORC at the University of Chicago. It is designed to be representative of the US household population. During the initial recruitment phase of the AmeriSpeak panel for the COVID-19 Impact Survey, randomly selected US households were sampled using area probability and address-based sampling methods. These sampled households were then contacted by US mail, telephone, and field interviewers . The panel provides sample coverage for approximately 97% of the US household population. Those excluded from the sample include people with post office box–only addresses, addresses not listed in the US Postal Service Delivery Sequence File, and newly constructed dwellings. Although most AmeriSpeak households can participate in surveys via the internet, households without web access are able to participate in AmeriSpeak surveys by telephone. Interviews were conducted in English and Spanish. Interviews were conducted with adults who were aged ≥18 years and represented the 50 states and the District of Columbia. Panelists were offered a US $5 monetary incentive for completing the survey. With regard to the number of participants invited and percentage of interviews completed by week, 11,133 panelists were invited and 19.7% of interviews were completed in week 1, 8570 panelists were invited and 26.1% of interviews were completed in week 2; and 10,373 panelists were invited and 19.7% of interviews were completed in week 3 . The anaOur primary outcomes for this analysis were participants’ attitudes and willingness toward using COVID-19 mHealth tools to track potential COVID-19 exposure and symptoms. To characterize attitudes toward the use of COVID-19 mHealth tools for tracking potential COVID-19 exposure, we used participant’s responses to the following question: “If this option was available to you, how likely would you install an app on your phone that tracks your location and sends push notifications if you might have been exposed to COVID-19”?To characterize attitudes toward the use of COVID-19 mHealth tools for tracking potential COVID-19 symptoms and recommendations, we used participant’s responses to the following 2 questions: (1) “If this option was available to you, how likely would you use a website to log your symptoms and location and get recommendations about COVID-19”; and (2) “If this option was available to you, how likely would you install an app on your phone that asks you questions about your own symptoms and provides recommendations about COVID-19”?For each of the 3 outcomes, the provided response options were extremely likely, very likely, moderately likely, not too likely, and not likely at all. Due to the small sample sizes, the extremely likely and very likely response options were combined into 1 category, and the not too likely and not likely at all response options were also combined into 1 category. This was done for each outcome.The primary predictor for this analysis was participants’ self-reports on a chronic health condition. Within the survey, participants were asked to reply “yes, no, or not sure” to the following question: “Has a doctor or other health care provider ever told you that you have any of the following: Diabetes; High blood pressure or hypertension; Heart disease, heart attack or stroke; Asthma; Chronic lung disease or COPD; Bronchitis or emphysema; Allergies; a Mental health condition; Cystic fibrosis; Liver disease or end-stage liver disease; Cancer; a Compromised immune system; or Overweight or obesity.” Given the small sample sizes reported among certain categories of health conditions, we further aggregated health conditions into the following 5 categories: cardiometabolic , overweight/obesity, respiratory , immune-related , and mental health conditions.The following covariates were included in the multivariable analyses: age categories , sex , race/ethnicity categories , education categories , residence , and household income . These covariates were chosen based on the review of mHealth disparities literature and COVID-19 disparities literature -83.P value of <.10 was used as criteria to include variables in the multivariable Poisson regression model. For multivariable Poisson regression models, adjusted prevalence ratios and 95% confidence intervals for each independent variable were calculated.Descriptive statistics are presented as percentages for all respondents unless otherwise labeled, and include a margin of error of 3.0 percentage points for 95% confidence intervals among all adults. Chi-square tests were used for the univariate comparison of categorical variables, including age, sex, race/ethnicity, education, income, residence, and chronic health conditions. For COVID-19 mHealth outcomes, we used multinomial logistic regression to compare the likelihood of COVID-19 mHealth tool use across people with different chronic health conditions after adjusting for age, sex, race/ethnicity, education, income, and residence. For each COVID-19 mHealth outcome, we compared participants’ likelihood of using COVID-19 mHealth tools to those in the not likely to use group . To estimate determinants of being extremely/very likely to use each COVID-19 mHealth intervention, we computed prevalence ratios via Poisson regression using the robust estimation of standard errors -86. PoteThe Type I error was maintained at 5%. Due to the exploratory nature of this analysis, we did not include an adjustment for multiple comparisons ,88. All Histories of chronic health conditions ranged from 15.5% of respondents reporting a history of mental health conditions to 37.8% reporting a history of cardiometabolic diseases. The most common chronic conditions reported were cardiometabolic diseases (37.8%) and overweight/obesity (33.1%). Furthermore, 21.8% of adults reported that they were extremely or very likely to install a mobile phone app to record symptoms and obtain recommendations about COVID-19, and 21.1% reported that they were extremely or very likely to use a website to log their symptoms and location and receive recommendations about COVID-19. Additionally, 24.1% of adults reported that they were extremely or very likely to install an app on their phone to track their location and receive push notifications about whether they may have been exposed to COVID-19.P=.004), potentially download and use an app to track their location and potential COVID-19 exposure (P<.001), and use a website to log COVID-19 symptoms and receive recommendations (P=.005). Compared to nonobese participants, respondents who reported being obese were significantly more likely to potentially download and use an app to track their location and potential COVID-19 exposure (P=.039). In the univariate analysis, no other significant differences in attitudes toward using COVID-19 mHealth tools were observed in respondents with a history of respiratory conditions or immune-related conditions.As shown in Compared to adults without a history of mental health conditions, adults a history of mental health conditions were extremely likely and moderately likely to potentially download and use an app to track COVID-19 symptoms and receive health recommendations about COVID-19 . Adults with a history of mental health conditions were extremely likely and moderately likely to download and use an app to track location and potential COVID-19 exposure compared to adults without a history of mental health conditions . Compared to adults without a history of mental health conditions, adults with a history of mental health conditions were extremely likely and moderately likely to use of a website to log their COVID-19 symptoms .Compared to nonobese participants, adults who reported being obese were extremely likely to download and use an app to track location and potential COVID-19 exposure . Participants who were obese were also moderately likely to use a website to log their COVID-19 symptoms compared to nonobese participants .This study analyzed differences and associations between attitudes toward using COVID-19 mHealth tools and various chronic health conditions. Compared to adults without a history of chronic health conditions, adults with chronic health conditions were more likely to potentially use COVID-19 apps or websites to monitor potential COVID-19 exposure and symptoms. Yet, attitudes toward COVID-19 mHealth tools varied significantly across people with different chronic disease conditions and modalities . Our study findings highlight the potential for mHealth tools to improve disease self-management and reduce health disparities among individuals with chronic health conditions.Our study highlighted disparities in attitudes toward COVID-19 mHealth tools across age, sex, race/ethnicity, education, and region. We observed that women in our sample were more likely to report positive attitudes toward using an app or website to track potential COVID-19 exposures or symptoms compared to men. This is consistent with prior studies that focused on disparities in mHealth use among the general population ,89. PrevOur study also highlighted several novel findings. The first was that respondents with a racial/ethnic minority background had a greater likelihood of using COVID-19 mHealth tools than non-Hispanic White respondents in our entire sample. Hispanic , Asian , and non-Hispanic Black  respondents were significantly more likely to potentially use mHealth tools for tracking COVID-19 exposure and symptoms. These attitudes may indicate greater awareness among racial and ethnic minority communities with regard to increased susceptibility to COVID-19 morbidity and mortality ,25,92. AThe second novel finding was observed when examining age-related disparities in COVID-19 mHealth attitudes. Contrary to many prior studies that have documented increased mHealth tool use among younger adults, respondents aged 18-29 years reported being less likely to use apps or websites for tracking COVID-19 symptoms and exposure compared to participants aged ≥60 years. These differences may indicate that older adults have a greater awareness of the risks of COVID-19 than younger adults. These differences may also indicate potential misperceptions of COVID-19 risk among younger populations ,94.We also observed geographic differences in attitudes toward COVID-19 mHealth tools with participants from the Midwest, South, and West, who reported less interest in using apps or websites to track COVID-19 symptoms and exposure compared to respondents from the Northeast. These disparities are consistent with prior studies that focused on regional differences in the digital divide, as well as studies of COVID-19 preventive behaviors across the United States . Our finOur findings are important, given the accumulating evidence for cardiovascular diseases, obesity, and diabetes being risk factors for COVID-19 incidence and mortality. In our previous study, which analyzed COVID-19 preventive behaviors among US adults, we observed that adults with chronic health conditions were significantly more likely to engage in many COVID-19 preventive behaviors, such as hand washing, using a face mask, and maintaining appropriate social distancing in public ,33. The Lastly, our findings highlight the potential that mHealth tools have for reducing chronic disease disparities in disease management and outcomes beyond the COVID-19 pandemic. Although there has been a proliferation of mHealth tools for people with chronic health conditions, the acceptability and long-term use of mHealth tools have varied considerably across people with different chronic conditions ,102. VarOur results should be interpreted within the context of several limitations. First, a history of chronic health conditions was based on self-reported data rather than medical records. Therefore, there may be potential for recall or misclassification bias for the chronic health conditions reported in this analysis. Additionally, while we acknowledge the increasing importance of considering multiple chronic conditions, given the complexity of examining multiple chronic conditions by both number and the combination of different chronic condition types, the examination of attitudes toward using COVID-19 mHealth tools among individuals with multiple chronic conditions was beyond the scope of this analysis. Second, attitudes toward potential COVID-19 mHealth tool use were based on self-reports rather than downloads or monitoring patterns of actual mHealth tool usage. As such, there may be potential for social desirability bias in terms of the reported COVID-19 mHealth attitudes, which may not correlate with actual COVID-19 mHealth tool use.Despite these limitations, our study has notable strengths. First, the sampling methods used to obtain a nationally representative sample of the US adult population provided the opportunity for increased generalizability. Our findings may be helpful to clinicians and public health officials when guiding mHealth messaging for COVID-19 prevention, symptom monitoring, and health recommendations. Additionally, our study results are drawn from a population that is diverse in terms of social and demographic characteristics and health statuses. Since the COVID-19 pandemic has exacerbated health inequities across different social groups and groups with chronic health conditions, public health strategies that consider the utility of mHealth approaches across diverse contexts will have a vital role in reducing COVID-19 disparities.Our study extends previous research in this field by analyzing attitudes toward various COVID-19 mHealth tools across a nationally representative sample of US adults with and without chronic health conditions. Future directions for research may include the examination of COVID-19 mHealth tool use among individuals with multiple chronic conditions and associations between COVID-19 mHealth tool use and COVID-19 knowledge and preventive behaviors. Our study results have several implications concerning the development of COVID-19 mHealth tools. As the use of mHealth apps has been found to impact the improvement of health outcomes across a range of chronic health conditions, the development of COVID-19 apps should focus on user preferences and consider differences in COVID-19 susceptibility across people with different chronic disease conditions. Combining big data analytic approaches with qualitative data from individuals with chronic health conditions may yield additional insights in increasing the acceptability of and long-term engagement with COVID-19 apps. Lastly, incorporating opportunities for the real-time tracking of potential COVID-19 exposure and symptoms among existing health apps for people with chronic conditions  may provide additional opportunities to strengthen prevention and early detection efforts among populations that are vulnerable to COVID-19 morbidity and mortality.


Overall, sensitivity for the detection of consolidation was higher than for GGO . No differences could be found in disease extent estimation between mlCXR and CXR, even though the detection of GGO could be improved. Diagnostic confidence was better on mlCXR compared to CXR (p = 0.013). Conclusion: In line with the current literature, the sensitivity for detection and quantification of COVID-19-pneumonia was moderate with CXR and could be improved when mlCXR was used for image interpretation.Purpose: To evaluate diagnostic accuracy of conventional radiography (CXR) and machine learning enhanced CXR (mlCXR) for the detection and quantification of disease-extent in COVID-19 patients compared to chest-CT. Methods: Real-time polymerase chain reaction (rt-PCR)-confirmed COVID-19-patients undergoing CXR from March to April 2020 together with COVID-19 negative patients as control group were retrospectively included. Two independent readers assessed CXR and mlCXR images for presence, disease extent and type (consolidation vs. ground-glass opacities (GGOs) of COVID-19-pneumonia. Further, readers had to assign confidence levels to their diagnosis. CT obtained ≤ 36 h from acquisition of CXR served as standard of reference. Inter-reader agreement, sensitivity for detection and disease extent of COVID-19-pneumonia compared to CT was calculated. McNemar test was used to test for significant differences. Results: Sixty patients  were included. Inter-reader agreement improved from good to excellent when mlCXR instead of CXR was used (k = 0.831 vs. k = 0.742). Sensitivity for pneumonia detection improved from 79.5% to 92.3%, however, on the cost of specificity 100% vs. 71.4% ( As the COVID-19 pandemic caused by SARS-CoV-2 spreads in the world, there is growing interest in the role and appropriateness of conventional chest radiographs (CXR) and computed tomography (CT) for management of patients with suspected or known COVID-19 infection. As the chest CT and CXR imaging pattern is non-specific and overlaps with other infections, the diagnostic value of imaging for COVID-19 is low and dependents upon radiographic interpretation. One study found that 56% of patients who presented within two days of diagnosis had a normal CT ,4. ThereConventional radiography, however, plays a role in the detection and follow-up of lung changes in patients with COVID-19, and CT should be reserved for hospitalized, symptomatic patients with specific clinical indications such as the investigation for pulmonary embolism or other complications [COVID-19 pneumonia, often presents as diffuse or patchy ground-glass opacities (GGO), which are less dense than classic consolidations, and therefore, the difference of density between normal lung tissue and the infectious process is less obvious and can be easily missed . For thiAccordingly, the purpose of this study was to compare the diagnostic accuracy of conventional CXR and mlCXR for the detection and quantification of the disease extent in COVID-19 patients compared to chest CT.The local ethics committee as well as the institutional review Board (IRB) approved the study and written informed consent was sought from all patients. Project number ID 2020-00092. In this retrospective cohort study, we included data from consecutive adult symptomatic patients with real time polymerase chain reaction (rt-PCR)-proven COVID-19 infection who have been admitted to our institution between March and April 2020. COVID-19 patients were diagnosed according to the “pneumonia diagnosis protocol for novel coronavirus infection ”  with twoElectronic medical records served as source data for the collection of demographics, clinical, laboratory, and treatment data.Since a high percentage of the COVID-19 population showed infective consolidation on CXR which would constitute in an unbalanced study population, we decided to add a control group with normal imaging studies: patients undergoing CXR and CT within 36 h from January 2014 to December 2015 were selected in order to be sure to have patients without COVID-19 infection.All patients underwent CXR in posteroanterior and lateral projection or anteroposterior projection at a tube current of 7mA and a tube voltage of 130kVp according to the institutions standard protocol. The mlCXR images were generated with the use of a commercially available software package  which is a machine learning based software tool that generates two additional images: (1) an “enhanced image” where visual quality of the chest X-ray is optimized by increasing the conspicuousness of pulmonary structures and (2) a “bone supressed image” where bony structures such as the clavicles or the ribs are eliminated from the image.Single-energy CT with or without intravenous contrast agent was performed in all patients on a third-generation CT scanner  equipped with an integrated high-resolution detector . Scanning parameters were as follows: CT was performed at 100 kVp with quality reference current-time product of 80 mAs, a pitch of 1.2, gantry rotation time 0.5 s, slice acquisition of 192 × 0.6 mm by means of a z-flying focal spot. The onsite CT technician detailed the breathing instructions to the patient.All images were reconstructed with advanced modelled iterative reconstruction  at a strength level of 3, using a slice thickness of 1.5 mm, an increment of 1 mm, and a tissue convolution kernel (Bl34). The image matrix was 512 × 512 pixels.The images were presented to two independent readers  in two reading rounds. In the first reading round, the CXR images were assessed. In the second reading round, readers had to assess the mlCXR images , but not the CXR images. The second reading round was performed two weeks apart from the first one in order to lower the risk of a recall bias.In both rounds, both readers independently assessed the images for the presence (yes/no) and disease extent  ((I) <25%, (II) 25–50%, (III) >50–75%, (IV) >75%) of pneumonia in the conventional images. To keep the readout as simple as possible, we chose to rate the overall percentage of affected lung parenchyma, and not the affected lung parenchyma in each single lobe. Estimation of disease extend was rated correctly when both CXR and CT estimates were in the same of the four disease extent categories. Additionally, readers had to assign confidence levels to their diagnosis on a 4-point score: (I) confident of true finding, (II) probable true finding, (III) probably no finding, and (IV) definitely no finding. Images were assessed in a random order over a time period of two days. In both reading rounds readers were blinded to the clinical information.CTs (which served as standard of reference) were read by a third reader  using the same classifications as for conventional radiography (presence (yes/no) and disease extent (I–IV). Additionally, the reader had to state the type of lung changes present on CT . If both, classic consolidation and GGOs, were present the reader had to state that both types were present. The reader was aware of patients’ symptoms but blinded to CXR and mlCXR diagnosis .Analyses were performed using the picture archiving and communication system (PACS) of our hospital  on a high-definition liquid crystal display monitor .Statistical analyses were conducted using commercially available software . Continuous variables were expressed as mean +/− standard deviation (SD) while categorical variables were expressed as frequencies or percentages.p–value below 0.05 was considered to indicate statistical significance.Cohen’s Kappa (κ) was used to assess inter-reader agreement. Κ-results were stratified qualitatively by score .n = 2), infective consolidation (n = 10), search for metastasis (n = 5), trauma (n = 1), and pulmonary embolism (n = 1).Patients in the control group underwent imaging for the following reasons: evaluation of the aorta  at time of CT. Patients suffered from the following comorbidities: Cardiovascular disease (19.5%), arterial hypertension (31.7%), diabetes (26.8%), chronic renal dysfunction (22.0%), and chronic pulmonary disease (7.3%). Detailed information on clinical findings can be found in p = 0.013). Similarly, disease extent correlated better with enhanced CXR than with standard CXR (correct estimations in 77.3% of cases vs. 52.3% of cases), differences in the estimation of disease extent, however, were only tendencies (p = 0.590), Thirty-nine out of 60 patients showed signs of pneumonia in form of consolidation or GGO on CT (65%). Inter-reader agreement improved from good to excellent when mlCXR instead of CXR was used (k = 0.831 vs. k = 0.742). The sensitivity and specificity for the detection of pneumonia on CXR was of 79.5% and 100%, respectively . DiagnosThe current COVID-19 pandemic calls for reliable imaging tools allowing for proper management of patients with SARS-CoV-2 infection frequently affecting the lungs. Non-contrast chest CT showed to have high sensitivity and specificity for the detection, severity assessment, and monitoring of COVID-19 associated lung changes ,4, but hCXR however, suffers some limitations such as a moderate diagnostic accuracy for the detection of pathologic lung changes compared to other imaging modalities such as CT ,10 with CXR is a projection-based imaging method, i.e., a three-dimensional structure is projected onto a two-dimensional image. Therefore, despite the high spatial resolution, CXR often lacks the possibility to differentiate structures with equal or similar density adjacent to each other or suffers from superposition of different structures . The relWhile in DER more images have to be acquired in order to obtain the differently weighted images (at cost of higher dose), in the present study we used a machine learning based post-processing algorithm that enables the subtraction of structures that contain calcium  in order to generate the “bone suppressed image” and a second image where pulmonary findings are enhanced. The advantages of the new method are that (1) no special equipment is needed, (2) the patient is not exposed to more radiation dose, and (3) no motion artifacts occur .COVID-19 pneumonia often presents as diffuse or patchy GGO ,3,4, whiThe higher sensitivity observed with eCRX in our study came at cost of lower specificity. False positive findings are a well-known problem of all computer-aided detection (CAD) software, as the developers have to find the trade-off between high sensitivity and high specificity ,15. SomeThe discrepancy in disease extent between CXR and CT might be mainly attributed to two factors. First, the physical properties of CXR in which structures of equal or similar density cannot be distinguished from each other. Second, the properties of COVID-19 pneumonia per se: (a) location in lung areas that are hidden and thus difficult to detect on CXR and (b) that COVID-19 pneumonia often consists in GGOs that are less visible on CXR. mlCXR is extremely powerful in difficult lung areas, where processes covered by overlapping structures  and enhances lung processes—this could additionally explain the higher sensitivity for the detection and quantification of COVID-19 pneumonia on mlCXR.Although chest radiography is considered not sensitive for the detection of pulmonary involvement in the early stage of COVID-19 pneumonia, in the current pandemic setting, chest radiography holds its position as useful diagnostic tool for monitoring rapid progression of lung abnormalities in COVID patients, particularly in intensive care units .Noteworthy, we need to keep in mind that any sever viral pneumonia looks similar on imaging, which will pose a major problem with the upcoming flu season. The radiologist is not able to distinguish different viral entities with CXR or CT alone. Said this, rt-PCR remains the standard of reference in diagnosing COVID-19 infection.Limitations of this study were as follows: Firstly, the retrospective setting and the relatively small sample size. Secondly, with imaging, we can only capture pathologic changes in the lung parenchyma, but we are not able to quantify lung function. Therefore, the amount and even distribution of infective consolidation on chest imaging in a given set of COVID patients might look similar but not necessarily correlate with clinical severity in all cases due to variations in baseline lung function. Thirdly, although there was a two-week washout period between reading the CXR and mlCXR images, it might be insufficient to completely exclude a recall bias. Fourthly, we cannot distinguish with the current study if the improved sensitivity of mlCXR was due to bone suppression or conspicuity enhancement since the two post-processed image datasets were simultaneously evaluated.In conclusion, in line with the current literature, sensitivity for detection and quantification of COVID-19-pneumonia was moderate with CXR and could be improved when mlCXR was used for image interpretation. There is a tendency to underestimate the extent of COVID-19 changes in CXR, which should be taken into consideration for patient management when determining the therapy plan based on conventional imaging.


P < 0.05, Kaplan-Meier analysis and log-rank test, P < 0.01). Similar prognostic value of HCCLnc-4 has been further verified in two other independent sets. Stratified analysis and multivariate Cox regression analysis suggested the independence of HCCLnc-4 for prediction of HCC patient survival from traditional clinicopathological factors. Area under curve (AUC) analysis suggested that HCCLnc-4 could compete sufficiently with, or might be even better than classical pathological staging systems to predict HCC patient prognosis in the same data sets. Functional analysis and network analysis suggested the potential implication of lncRNA biomarkers. Our study developed and validated the lncRNA prognostic index of HCC patients, warranting further clinical evaluation and preventive interventions.Prognostic stratification in hepatocellular carcinoma (HCC) patients is still challenging. Long non-coding RNAs (lncRNAs) have been proven to play a crucial role in tumorigenesis and progression of cancers. The aim of this study is to develop a useful prognostic index based on lncRNA signature to identify patients at high risk of disease progression. We obtained lncRNA expression profiles from three publicly available datasets from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). By the risk scoring method, we built an individualized four-lncRNA signature (HCCLnc-4) to predict survival of HCC patients in the discovery set (ROC curve, AUC: 0.83, 95% CI: 0.65-1.00,  Hepatocellular carcinoma (HCC), as the most common type of liver cancers, ranks as the fifth most common cancer globally and is the second most common cause of death by cancer worldwide MALAT1HOTAIRCASC15, lncRNA CCAT1, lncRNA CCAT2, lncRNA LASP1-AS, lncRNA LINC00673, lncRNA LOC90784, lncRNA NEAT1, and lncRNA SBF2-AS1 might act as prognostic biomarkers to predict HCC progression or recurrence lncRNAs are typically defined as non-coding transcripts longer than 200 nucleotides In this study, from the perspective of lncRNA expression pattern, applying three datasets of gene expression profiles from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) for 447 HCC patients, we investigated associations between expression levels of lncRNAs and survival outcomes of HCC patients. By the risk scoring method, we established and validated an individualized four-lncRNA signature in different datasets. Functional analysis suggested the four lncRNAs and related genes might be involved in known HCC-related pathophysiologic processes.https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14520) dataset contained two batches of samples. The smaller batch included 22 HCC samples, generated by Affymetrix Human Genome U133A 2.0 Array platform, were used to train a prognostic signature. The larger batch included 225 HCC samples, generated by Affymetrix HT Human Genome U133A Array, were used as the first validation dataset (test cohort-1). The second validation dataset was composed of 200 TCGA HCC samples from TANRIC database (TANRIC: An interactive open platform to explore the function of lncRNAs in cancer.), denoted as test cohort-2. All non-coding transcripts included in the three datasets were for patients treated with surgery only. In addition, the RNA and miRNA expression data, as well as the clinical data of HCC patients were obtained from TCGA (https://tcga-data.nci.nih.gov/tcga/). The flow chart of the study is described in Figure The GSE14520 , obtained from the Affymetrix official website. BioMart in Ensembl database was applied to convert Affymetrix microarray IDs to Ensembl IDs together with the corresponding gene type. We only retained genes annotated as 'lincRNA', 'sense_intronic', 'processed_transcript', 'anti-sense', 'sense_overlapping', '3prime_overlapping_ncrna', or 'misc_RNA'. Next, for the probe sets from the Refseq database, those IDs beginning with 'NR' were retained, and transcript IDs labeled with 'NP' were deleted. We removed probe set IDs annotated as 'microRNA', 'snoRNAs', ' pseudo-genes' and other small RNAs. Finally, 842 lncRNA-specific probes corresponding to 351 lncRNAs were obtained for further analysis. When multiple probes were mapped to the same lncRNA, expression values of these probes were integrated by using the median value to represent the expression value of the single lncRNAs. All of the raw data were processed using affy and related R packages with Robust Multi-array Average approach for background normalization as per the package instruction.P < 0.001 as selection criteria). Then the combinations of lncRNAs related to HCC patients' OS were analyzed by repeated comparison analysis to identify the best prognostic model for predicting the OS of patients. Next, the lncRNA expression signature, termed HCCLnc-4, was established by the risk scoring method, as described by Lossos et al The association between expression levels of lncRNAs and HCC patients' overall survival (OS) was evaluated by univariate Cox proportional hazards regression analysis  Pearson correlation coefficients were calculated between lncRNAs and protein-coding genes (PCGs) or miRNAs. Functional enrichment analysis for the correlated PCGs was performed using DAVID Bioinformatics Tool (Three HCC patient cohorts with definitive OS information were included in this study. The patient cohort from GSE14520 (GPL571 platform) was selected as a discovery cohort. The patient cohorts from GSE14520 (GPL3921 platform) and TCGA (TANRIC) were used as independent validation cohorts to verify the robustness of the lncRNA biomarkers . All 447 patients used in this study were clinically and pathologically diagnosed with HCC. The mean OS time was 31.8 months , 40.4 months , and 24.6 months , respectively. All the statistical information was summarized in Table P < 0.001 as selection criteria) were identified. Then the combinations of these lncRNAs related to patient OS were analyzed, and a model consisting of four lncRNAs was identified as the best prognostic model for predicting the OS of patients. All these four lncRNAs were verified in the NCBI database and classified as ncRNAs in this website. The detailed information of these four lncRNAs is shown in Table As shown in Figure P < 0.01, see in Table  P < 0.05), indicating HCCLnc-4 had high sensitivity and specificity to predict the prognostic survival of patients in the discovery set. And the risk score value of -8.77, which produced the shortest distance to the point of perfect prediction of the ROC curve, was selected as the cutoff point. Using the same cutoff point produced from the ROC curve, patients were divided into low-risk (n = 16) and high-risk groups (n = 6). Kaplan-Meier analysis and log-rank test were then performed. Compared with the low-risk group, patients in the high-risk group had significantly shorter OS time  and 0.62  for test cohort-1 and test cohort-2, respectively , as seen in Figure Next, the robustness of HCCLnc-4 was tested in the other two validation cohorts. Univariate Cox regression analysis shows that the levels of the HCCLnc-4 were significantly associated with patient survival both in test cohort-1  comparing with those produced by other clinicopathological factors. In addition, AUC produced by HCCLnc-4 was the largest in test cohort-1 , comparing to those produced by TNM staging  and BCLC staging , and was similar to that produced by TNM staging  in test cohort-2 . These data suggest that HCCLnc-4 could compete sufficiently with classical clinical and pathological staging systems to predict HCC patient OS.To determine the superiority of HCCLnc-4 for prediction of HCC patient OS, we calculated AUC that produced by different clinicopathological factors to compare them with that produced by HCCLnc-4. As can be seen in Table P < 1E-10 as selection criteria) of paired lncRNA and PCGs expression profiles. The functional enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway revealed that PCGs positively correlated with lncRNAs were involved in rRNA processing process and spliceosome pathway, while PCGs negatively correlated with lncRNAs were enriched in GO terms mostly related to metabolic process and KEGG pathways, including Complement and coagulation cascades, Metabolic pathways, and PPAR signaling pathway, etc. The HCCLnc-4 associated biological processes and pathways can be found in To explore the function of HCCLnc-4, we identified highly positively or negatively correlated PCGs with at least one of 4 lncRNAs by calculating the Pearson correlation coefficient  were found to be involved in liver pathology or HCC Using The ability to recognize patients with high risk would aid the decision for HCC management. Several clinical prognostic indicators have been proposed to discriminate patients who stand to benefit from liver transplantation. However, they are still insufficient or not sensitive enough for predicting HCC patients at high risk for recurrence and selecting those at low risk As the newly identified class of ncRNA, lncRNAs participate in tumor proliferation, metastasis, invasion, energy regulation, and tumor-initiating cells self-renewal UPB1, SOCS2, and RTN3P < 0.05) and 0.69  of HCCLnc-4 in our study, indicating well or possibly higher sensitivity and specificity of HCCLnc-4 to predict the prognostic survival of HCC patients compared to the recently published mRNA-based signature in the same data sets. These results suggested that HCCLnc-4 was an individualized and robust prognostic marker to predict HCC patient survival.Recent studies found that some of the microarray probes on the commonly used arrays are likely to map to lncRNAs MAPKAPK5 antisense RNA 1 , one of 4 HCC prognosis-related lncRNAs, was differentially expressed between HCC tissues and adjacent non-tumor tissues and negatively associated with OS of HCC patients MAPKAPK5-AS1 is positively correlated with HCCLnc-4 and negatively associated with the OS of HCC patients in our study. Upregulation of MAPKAPK5-AS1 in HCC patients with vascular invasion was also observed MAPKAPK5-AS1 is co-expressed with the genes involved in ribosome and spliceosome pathways, which have been partly elucidated elsewhere DGCR9, ENSG00000273032), one of the 4 HCC prognosis-related lncRNAs in our study, is also one lncRNA of a 9-lncRNA risk score system for the prognostic prediction of patients with HBV-positive HCC DGCR9 was negatively associated with the 9-lncRNA risk score and positively correlated with OS of HBV-positive HCC patients. In our study, a similar association between the expression level of DGCR9 and HCC patient OS was also observed, though our study included patients with HBV either positive or negative. Furthermore, in the network analysis  might act as a ceRNA to intervene in HCC pathogenesis by competitively associated to miR-122 and miR-885, which have been found to be involved in liver diseases or liver cancer Though more than ten thousand lncRNAs have been discovered in human, functional studies of these lncRNAs are still in its early stages. Several limitations should be noted in our study. Firstly, we obtain lncRNA expression profiles from the commonly used arrays, so not expression profiles of all lncRNAs were analyzed in our study. Secondly, our model could not include all the potential important prognostic factors, such as steatosis and nonalcoholic fatty liver disease (NAFLD), because the information of these factors was unavailable in the publicly published datasets. Thirdly, prospective studies with larger sample sizes are needed to validate the prognostic value of HCCLnc-4 in HCC patients. Fourthly, the potential biological mechanisms behind the associations between HCCLnc-4 and OS of HCC patients remains to be investigated in further studies.In conclusion, our study suggested the potential of lncRNA signature as novel candidate biomarkers in the prognosis of HCC, or potential biological functions of lncRNAs in hepatocarcinogenesis.Supplementary figures and tables.Click here for additional data file.


The pre-excitation can be intermittent, and thus is not always present in ECG. The presence and degree of pre-excitation is dependent on characteristics of conduction through the atrioventricular (AV) node, which in turn can be affected by autonomous tone, medication, a conduction system disease, or mechanical injury. In addition to adenosine provocation test, unmasking of an accessory pathway (AP) has been reported during anesthesia,We report 2 cases involving patients in whom previously unrecognized pre-excitation was unmasked after aortic valve surgery. The incidence of newly discovered pre-excitation after aortic valve surgery or transcatheter aortic valve replacement is not known.A 30-year-old man was referred for echocardiography because of a systo-diastolic murmur. He was diagnosed with a significant aortic valve stenosis (maximum velocity 3 m/s) and regurgitation, and was referred for cardiac surgery. Prior to surgery, his ECG was normal with no clear pre-excitation A. The aoDuring the EP study, catheters were placed in the coronary sinus, along the His bundle, and in the right ventricular apex. Partial pre-excitation was demonstrated at baseline with PQ 124 ms, AH 74 ms, and HV 30 ms. Ventricular pacing at 700 ms cycle length lead to ventriculoatrial (VA) dissociation. The pre-excitation disappeared during atrial pacing from the coronary sinus. Incremental atrial pacing revealed frequency-dependent left-sided bundle branch block at the pacing cycle length of 580 ms and a Wenckebach point of 310 ms. During isoproterenol challenge no pre-excitation was seen, and incremental ventricular pacing disclosed decremental retrograde AV nodal conduction with a VA block at 610 ms. The AP was not ablated in the absence of malignant features or symptoms that could have been attributed to the pathway.2 and a maximal gradient of 105 mm Hg. Aortic regurgitation was graded to be moderately severe (grade III/IV). The left ventricular systolic function was reduced, with an ejection fraction of 35%. His ECG showed normal sinus rhythm with no pre-excitation  conduction. Recording and interpreting a 12-lead electrocardiogram after cardiac surgery and intervention is important to find disturbances in AV conduction or previously concealed accessory pathways.•Full pre-excitation can mask a high-degree AV block. In such patients, pacemaker therapy has to be considered.•The conductive properties of an accessory pathway cannot be automatically classified as benign, even if the conduction in the pathway is only intermittent.These cases elucidate the importance of recording and interpreting 12-lead ECG after cardiac surgery or other invasive valvular procedures that might affect AV conduction or facilitate conduction in an AP. Our report is the first one to show persistent unmasking of pre-excitation after aortic valve surgery. The patients presenting with pre-excitation should be assessed by noninvasive or invasive methods, in order to characterize the risk of developing malignant arrhythmias or AV block.


People residing in regional and remote areas and from low socio-economic backgrounds already face significant health and lifestyle challenges associated with disadvantage. It is time to invest in injury prevention interventions for these populations, as well as upstream policy strategies to minimize any further preventable loss of life.Injuries are a leading cause of harm for children. This study explores the impact of determinants of health on children (0–19 years) injury-related mortality ). Cause of death data from the Australian Bureau of Statistics were sourced for children in Australia between 1 July 2007 to 30 June 2017. Fifteen injury categories  were used. Burden and trends by injury mechanism were explored. A total of 5153 children died; with road traffic incidents , intentional self-harm (2.46) and drowning (0.72) being the leading mechanisms. Female fatality rates in very remote areas (8.73) were nine times higher than in major cities . Fatality rates increased with remoteness; very remote areas recording an injury-related fatality rated six times  that of major city residents. Accidental poisoning and intentional self-harm fatalities were more likely in high IRSAD areas, while road traffic fatalities were more likely in low and mid socio-economic areas (X Globally, injuries are a leading cause of mortality and morbidity for children and adolescents. In 2017, the Global Burden of Disease study estimated 4.48 million injury deaths globally, an increase of 5.3% since 1990 [Understanding and preventing injuries is complex as they may be intentional or unintentional, be due to a range of mechanisms such as road transport, falls, drowning, burns, poisoning, interpersonal violence and suicide, impact all ages and require a range of strategies to prevent them from occurring ,2,3,4. AInjury risk is impacted by external factors including determinants of health. Determinants of health, referred to as the causes of the causes , are theGeographical remoteness and socio-economic status are determinants which impact health, including injury ,11. PoorChildren and adolescents experience significant fatal and non-fatal burden due to injuries  and are While fatal child injury rates are declining, there are clear variations based on socioeconomic inequalities . TherefoThis study reports a total population analysis of injury-related mortality among children and adolescents aged 0–19 years (henceforth referred to as children) in Australia between 1 January 2007 and 30 June 2017 (a period of 10 years), with a particular focus on determinants of health—namely remoteness and IRSAD of the child’s residential location.Cause of Death Unit Record File data were sourced from the Australian Bureau of Statistics (ABS). Data are provided to approved applicants only, but similar publicly available data to the Cause of Death data release collated by the ABS annually are provided . VariablAll deaths that had a primary cause of death injury ICD-10-AM  code werThis study examines injury-related deaths that were registered and who died between 1 January 2007 and 31 December 2017; noting that particularly for 2017, this would represent an approximate under-numeration of 6% (this proportion is based on the proportion of people who died within a given year but whose death was not registered until the following year). This particularly impacts those deaths which occur later in the year i.e., November and December. As such, trends over time are explored on Australian financial years 1 July to 30 June, from 1 July 2007 to 30 June 2017.Fifteen categories of injury mechanism were collated using the ICD-10 codes. Due to small numbers of cases, the mechanisms of ‘overexertion, strenuous and repetitive movements’ (X50) and ‘contact with venomous animals and plants’ (X20-29) were grouped into ‘Other’. The coding structure for the categories is described in The impact of determinants of health on child injury risk was explored by remoteness and IRSAD. The remoteness of the child’s residential location was calculated by matching the nine digit statistical local area (SLA) code to the corresponding Australian Standard Geographical Classification (ASGC) category  .The nine-digit SLA was also used to code the victim’s residential location to the corresponding decile on the index of socio-economic advantage and disadvantage (IRSAD). IRSAD aligns the statistical local area with a decile ranking (1–10), with areas ranked 1 being the most disadvantaged. Victims’ residential postcode current IRSAD was used as a proxy for their familial socio-economic status . IRSAD iTemporal trends over time in fatal injury mechanism were explored using the linear calculation in Microsoft Excel 365 Build: 13426.20274). Crude rates and relative risk (RR) with a 95% confidence interval (CI) were used to calculate the impact of remoteness of residential location on injury-related fatalities. Crude rates per 100,000 population were calculated for all children 0–19 years, by sex and by age group , using the population from June of each year 26.20274. and 2016Univariate and chi-square analyses  were usThis study received ethics approval from the James Cook University Human Research Ethics Committee (H6136). Due to ethical constraints associated with reporting small numbers, small cell counts less than five (and their associated percentages) are reported as not presented (NP).2 = 0.72)  .The highest rates of fatal injury were seen in the 15–19 years age group with an average rate across the study period of 22.23 per 100,000, compared with the lowest rate of 2.63 per 100,000 among the 5–9 years age group. Crude injury-fatality rates are declining among 15–19-year-olds, with stagnant rates among 0–4-year-olds and 5–9-year-olds, with a slight upturn in rates among 10–14-year-olds .n = 3487). Males were overrepresented in all age groups, rising from 59.1% of all injury-related fatalities in the 0–4 years age group, to 71.8% of all fatalities in the 15–19 years age group.Males accounted for 67.7% of all fatalities (n = 1970) of the overall injury-related fatality burden, followed by intentional self-harm  and drowning . The overrepresentation of males was most pronounced in injury-related fatalities as a result of falls  and electrocution, radiation and extreme temperatures . When calculated as crude fatality rates, road traffic and other land transport incidents recorded a fatality rate of 3.39 per 100,000 population, compared to 2.46 for intentional self-harm and 0.72/100,000 population for drowning  the rate of major city residents .Males recorded higher rates of fatal injury than females across all remoteness classifications, with the highest rates seen in very remote areas . When compared to major cities, the relative risk of an injury-related fatality was six higher in very remote areas for males  and nine times higher for females . Rates of injury-related fatalities were highest for 15–19-year-olds across all remoteness classification, ranging from 17.11 fatalities per 100,000 residents in major cities, to a rate of 102.33 in very remote areas .Across the five remoteness classification categories, road traffic and other land transport incidents (2.45) and intentional self-harm (2.12) recorded the highest rates of fatal injury in areas classified as major cities. This pattern continued across all remoteness classifications, with the exception of very remote areas, where the rate of injury-related fatalities associated with intentional self-harm (16.97) overtook that of road traffic and other land transport (14.39). The highest RR of injury-related fatality was for electrocution, radiation and extreme temperatures, with an 18 times  higher risk of dying from this injury mechanism in a very remote area than in a major city. .When compared to females, a proportionately higher number of males in the 0–4 years age group died from road transport and other land transport injuries in major cities (57.1%), rising to 79.3% for the 15–19 years age group in very remote areas. When compared to males, a proportionately higher number of females aged 10–14 years died due to road transport related injuries in very remote areas (62.5%). For intentional self-harm related fatalities, sex differences were most pronounced among 15–19-year-olds in inner regional areas, where males accounted for 73.1% of fatalities. Sex differences for drowning were most pronounced in major cities for the 15–19 years age group, with males accounting for 90.9% of all drowning-related fatalities.2 = 0.6734). . .2 = 1.86; p = 0.395).  and among males (67.7%). Males accounted for a higher proportion of injury-related fatalities than females across all IRSAD deciles. A higher proportion of female injury-related fatalities occurred among high IRSAD deciles (20.0%) than males (18.4%), however sex by IRSAD decile did not have a statistically significant impact on injury-related fatalities (X 0.395). 2 = 28.58; p < 0.001) . There was a statistically significant difference in injury-related fatalities for age group by IRSAD. Older children (15–19-year-olds) were more likely to die from injury-related incidents in areas classified as high IRSAD, whereas children (0–4 years) were more likely to die from injury-related incidents if residing in low IRSAD areas (X< 0.001) .2 = 69.05; p < 0.001) were found for proportion of injury mechanism by IRSAD for road traffic and other land transport (more likely in low and mid IRSAD deciles), accidental poisoning (high IRSAD), and intentional self-harm (low and mid IRSAD)  and mid IRSAD (40.7%). In areas classified as high IRSAD, intentional self-harm accounted for the highest proportion of injury-related deaths (32.4%). Statistically significant differences (Xd IRSAD) .When exploring sex differences by injury mechanism, age and IRSAD decile, 15–19-year-old males accounted for a significantly higher proportion of drowning-related deaths in low , mid (89.2%) and high (90.9%) IRSAD deciles. Females aged 0–4 years old accounted for 71.4% of burn-related deaths in high IRSAD deciles. A higher proportion of males aged 15–19 years of age died from intentional self-harm in low IRSAD deciles  compared to mid  and high IRSAD deciles .Injury is a leading, yet preventable cause of death among children. This study has explored the impact of determinants of health, namely remoteness of residential location and IRSAD of residential location on injury-related fatalities among 0–19-year-olds in Australia. This study reports the injury-related fatalities of 5153 children aged 0–19 years, with the highest rates occurring among adolescents 15–19 years . The highest rates of injury-related fatalities being due to the mechanisms of road traffic and other land transport (3.39), intentional self-harm (2.46) and drowning (0.72). Rates of injury-related fatality increased as remoteness increased, with six times the risk of an injury-related fatality for children aged 0–19 years in very remote areas of Australia when compared to those residing in major cities. Males and 15–19-year-olds recorded the highest rates of injury-related fatality across all remoteness classifications and age bands, with the highest rate seen among 15–19-year-olds in very remote areas .Variations in fatal injury risk also exist based on the socio-economic advantage or disadvantage of where children live. While sex did not significantly impact injury-related fatalities when examined by IRSAD decile, significant differences were seen by age band and injury mechanism. Fatal injury risk was most pronounced in low IRSAD areas for very young children (0–4 years of age) and in high IRSAD areas for 15–19-year-olds. Road transport and other land transport injury-related fatalities and intentional self-harm fatalities were significantly more likely in low and mid IRSAD deciles, while accidental poisoning-related fatalities were significantly more likely in high IRSAD deciles. We now focus our discussion on the three leading injury mechanisms identified in the study being road traffic and other land-based transport, intentional self-harm and drowning. We then look to the future with respect to preventative efforts, while also focusing on the opportunity that the new National Injury Prevention Plan provides.n = 1970, 38%) across the study period. High rates were seen across all remoteness classifications, with the fatality risk associated with this mechanism six times higher  in very remote areas when compared to major cities. Similarly, road traffic injuries were significantly more likely in areas classified as low  and mid  IRSAD deciles. Road surfaces are generally of poorer quality in regional and remote Australia [Road traffic and other land-based transport incidents accounted for the largest number of fatalities , a rate that is eight times  that of the fatality rate in major cities. Adolescence is a period of high risk for suicide, due to multiple stressors, mood disorders and development phase ,52. ThouLike most other injury mechanisms explored, this study identified that the risk of an intentional self-harm-related fatality was significantly higher for residents of low and mid IRSAD deciles. The published literature has also identified this increased intentional self-harm risk in areas of socio-economic disadvantage ,57. GiveThis study found drowning to be the third leading cause of injury-related fatalities among children in Australia. Like other injury mechanisms, rates increased as remoteness increased, aside from a slightly higher rate in inner regional  than outer regional (1.41), with a four times  greater risk of drowning in very remote areas than in major cities. Similarly, a higher proportion of drowning occur in areas of low and mid socio-economic status, with just 17.2% of drowning deaths occurring in high socio-economic areas. This is in keeping with other studies into drowning which have identified significantly higher rates of drowning as rurality increases ,60 and iA range of upstream factors also impact drowning risk, with less pools, seasonal facilities and a lack of instructors impacting ability to learn to swim in regional and remote areas , and theGreater investment is clearly needed in primary prevention measures to reduce injury-related mortality and morbidity in regional and remote Australia and among areas of socio-economic disadvantage . This wiThe existence of the new National Injury Prevention Strategy 2020–2030 , which iPreventing injury-related harm is vital to the nation’s addressing many of the child and adolescent health targets outlined in the Sustainable Development Goals ,24. MoreThis study adds to the limited literature exploring the impact of injury related fatality among children aged 0–19 years in Australia by determinants of health, namely remoteness and socio-economic status of residential location at a total population level. The study uses a nationally validated data source and is likely to have consistency and accuracy with respect to the identification of cause of death. Where population data were available, this study uses rates to explore risk of injury-related fatalities per 100,000 residents.There are, however, some limitations associated with this study. This study explores fatalities only, and further research is needed to explore the full burden of injury-related morbidity. Population data by IRSAD decile are not publicly available in Australia and therefore we were unable to calculate fatality rates by IRSAD. Assumption made regarding population distribution across the all-age population grouped IRSAD deciles holding true for children aged 0–19 years may not be correct. As such, the chi square tests of significance should be interpreted with caution. As remoteness and IRSAD are calculated at the statistical local area level, this limits any individual advantage or disadvantage which may occur within a statistical local area. For example, in an area considered to be low IRSAD, it is possible that there are households which would be considered high within the IRSAD classification. With respect to remoteness, some of the statistical areas are quite large, potentially spanning several remoteness classifications, however in this study, they have been assigned to a single remoteness classification. This study has explored the impact of determinants of health, namely the geographical remoteness of residence and socio-economic status of residential area on injury-related fatalities among children aged 0–19 years in Australia. This study identified road traffic and other land transport injuries, intentional self-harm and drowning to be the three leading causes of death, with fatality rates increasing as remoteness increased. For most injury mechanisms examined that there was a disproportionate burden among low and middle IRSAD deciles except for intentional self-harm and accidental poisoning related deaths, which were significantly higher in high IRSAD areas. The findings of this study suggest injury prevention strategies for young people in Australia should consider these determinants of health. People residing in regional and remote areas and from low socio-economic backgrounds already face significant health and lifestyle challenges associated with disadvantage. It is time to invest in these populations to minimize any further preventable loss of life.