Only a few cases of acute disseminated encephalomyelitis (ADEM) following coronavirus disease 19 (COVID-19) vaccination have been described since the beginning of the vaccination campaign.Here we report the first case of central nervous system (CNS) demyelination with systemic inflammatory findings on whole body 19-fluorodeoxyglucose positron emission tomography with computed tomography (FDG-PET/CT) following the ChAdOx1 nCoV-19 vaccine.Clinicians should stay aware of potential new adverse events after immunization. Since the beginning of the pandemic, vaccines were produced in record time. Real-world studies indicated an excellent safety profile. Despite these studies, the scientific community must stay aware of rare but severe complications and report them. This allows more accuracy of the real-world safety profile of the vaccine. We can take appropriate measures, as we did with the AztraZaneca vaccine ChAdOx1 nCoV-19) and its thromboembolic complications  nCoV-19 . Acute dA previously healthy 49-year-old female received her first dose of ChAdOx1 nCoV-19 vaccine. She experienced mild flu-like symptoms during the following 48 h. One week later, the patient presented another episode of flu-like symptoms with fever, fatigue, neck pain, followed over the next few days by rapidly progressive sensitive symptoms including paresthesia in both legs, up to the chest, Lhermitte's phenomenon and sphincter dysfunction. In April, the patient came to the neurological consultation at another hospital. During the examination a hypoesthesia with a thoracic (Th) 8 level was noticed with a sensory ataxia. A full spine magnetic resonance imaging (MRI) was normal but somatosensory evoked potentials (SSEPs) showed abnormal conduction above the sensory decussation in the lower brainstem. Four weeks later, the patient came to our neurological outpatient clinic. Her symptoms had worsened with sensory symptoms now involving her hands, worsening sensory ataxia and of sphincter dysfunction. Her neurological examination showed normal strength, hypoesthesia to all modalities with a Th 8 level, absent plantar response, impaired tandem walking and the presence of a Romberg sign.An MRI of the brain was obtained and revealed large, ill-defined T2 fluid attenuated inversion recovery (FLAIR) hyperintensities of periventricular and deep white matter, along with smaller lesions infratentorially , part1. Based on the exclusion of CNS infection or other autoimmune disorders, the diagnosis of atypical ADEM was made. The patient was treated with an intravenous course of methylprednisolone (1 g/day for 5 days). Her condition stabilized and she was transferred to a rehabilitation center.Three weeks after discharge, she was readmitted because of a clinical deterioration. Neurological evaluation showed a new paraparesis, evaluated at 2/5 in the right leg and 3/5 in the left leg, complete loss of pallesthesia up to the iliac crests, a sensory Th 5 level, and a severe sensory ataxia requiring walking aids.Six weeks afterwards, on July 14, an MRI showed an increase in the number and size of spinal cord lesions and the appearance of new foci of contrast enhancement , part 3.Because of the atypical course of the disease, the diagnosis of ADEM was reconsidered. Whole body fluorodeoxyglucose positron emission tomography with computed tomography (FDG-PET/CT) was obtained with the aim of excluding systemic inflammation, namely sarcoidosis despite negative biological markers. Results revealed increased glucose uptake not only in the spinal cord but also in the thyroid, the thoracic aorta walls and the lumbar spinous processes .She did not have any complaints about osteo-articular or vascular systems. Further thyroid testing with echography, hormone levels and autoantibodies were normal. She received IV rituximab (1 g and another after 15 days) and another course of IV methylprednisolone (1 g/day for 5 days). Over the next 2 months, she progressively improved. At last follow-up, strength in her right and left lower limbs was evaluated at 3+/5 and 4+/5, respectively, the sensory level had dropped to the level of Th12 and she could take a few steps without aid. Another MRI showed stability or regression of most lesions.On repeat whole body FDG-PET/CT (13 weeks after the first one), thyroid uptake had disappeared but other regions' abnormal uptake had decreased and new areas of increased uptake had appeared at the level of the scapular and pelvic girdles, ischiatic and great trochanters.This case report raises two important points: the association between ChAdOx1 nCoV-19 and ADEM and the meaning of incidental findings in the FDG PET-CT.A review of the SARS-CoV-2 vaccine and ADEM literature showed 13 reported cases of ADEM following the administration of a COVID-19 vaccine, which are summarized in In comparison to prior cases except maybe one who had a pseudo relapse , our patAlso, the MRI evolution of the lesions is atypical for several reasons: the sub-acute evolution (longer than 3 months), the discordance between brain and spinal cord lesions in terms of how they evolved and their aspects, and the limited resolution on the last MRI after 7 months of follow-up. As some studies have described, some lesions could take up to 18 months to disappear  or persiIt is the first reported case of post-ChAdOx1 nCoV-19 vaccination ADEM in which FDG-PET/CT was performed. The observed pulmonary nodules' hypercaption were very small (<5 mm) with a reduction of the glucose uptake at the FDG-PET/CT control. A basic control will be performed at one year with a CT.The increased glucose uptake observed in the thyroid on the first FDG-PET/CT is difficult to interpret in our clinical setting. Mild FDG uptake by the thyroid is likely physiological and a normal variant but moderate-to-intense diffuse uptake is usually associated with elevated TSH, thyroiditis, hyperthyroidism or Graves' disease . One intThe increased uptake of the thoracic aorta and the lumbar spinous processes interspaces associated with the increased uptake of the scapular and pelvic girdles, ischiatic and great trochanters in the second FDG-PET/CT raised the question of polymyalgia rheumatic associated with a giant cell arteritis (PMR-GCA) diagnosis. Again, in our case we did not have any clinical correlation and our patient is substantially younger (40 years old) than the median age (70 years old) of diagnosis for this PMR-GCA entity . We did We report the first case of post-ChAdOx1 nCoV-19 vaccination atypical ADEM with incidental findings on the FDG-PET/CT consistent with a large-vessel vasculitis, in particular GCA given the hypermetabolism of scapular and pelvic girdles and typical of polymyalgia rheumatica. Their relevance remains debatable at this stage given the lack of corresponding symptoms. Clinicians should stay aware of potential new adverse events after immunization.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The studies involving human participants were reviewed and approved by Comité d'Ethique de l'Hopital Erasme—CUB. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.LB wrote the first draft of the manuscript. VL, SG, MC, and VO-I wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This editorial is to highlight current issues of heart failure management during COVID-19 pandemic. Heart failure is a significant health burden that affects all societies. More than one in ten people over the age of 75 will develop heart failure, and the overall incidence of heart failure in women and men aged 55 years and above is 29% and 33%, respectively, in their lifetime . Acute hThe pandemic of coronavirus disease 2019 (COVID‐19) has become one of the greatest challenges to the public health around the globe. At the time of the writing, there were 281 million confirmed cases of COVID-19 globally, with 5.4 million COVID-19 related deaths. COVID-19 mainly affects the respiratory system, but it also has severe impact on cardiovascular and metabolic systems, resulting in multiple organ failure . In patiThe mechanisms by which COVID-19 leads to cardiac injuries are yet to be delineated, and the long-term impact of COVID-19 on cardiac function and survival remains to be seen. It is likely that systemic and myocardial inflammation following COVID-19 infection is the main cause of myocardial injuries, such as elevated plasma troponin levels, angina or ST elevation on ECG. Only a small portion of patients with angina or ST elevation after COVID-19 infection have clinically significant stenosis on coronary angiogram . The incInvestigation and treatment of precipitating factors for AHF is essential. Acute coronary syndrome, severe hypertension, arrhythmias, mechanical catastrophes, such as ruptured ventricular septum, acute valvular regurgitation, or pulmonary embolism, must be identified and treated . CardiogHemodynamic and fluid management in patients with AHF and COVID-19 is critically important. Hypovolemia is common in critical COVID-19 patients due to reduced oral intake or increased fluid loss, or both . PatientDevices, such as non-invasive ventilation or temporary mechanical circulatory support devices, can also provide symptomatic relief for AHF. In patients with severe pulmonary congestion, early application of non-invasive ventilation significantly improves oxygenation and haemodynamic instability in comparison with conventional oxygen therapy , 13. ThiThe management of heart failure in the setting of COVID-19 has additional challenges. First, delayed care or reluctance of patients to seek medical attention due to self-isolation after contracting COVID-19, or fears of COVID-19 contamination in a clinical setting, may result in progression of stable chronic heart failure to advanced or decompensated heart failure, which can be difficult to manage in a community setting. Patient’s fears of contracting COVID-19 in outpatient clinics or in hospitals are understandable. Frontline healthcare workers may contract COVID-19 from community or from patients presented to the clinics or hospitals. Many hospitals admit COVID-19 and non-COVID-19 patients from the same sites and truly isolating COVID-19 from the non-COVID-19 patients is not always possible . In addiIn response to this dilemma, in many countries, the usual patterns of care for heart failure in the primary care setting have changed, by extensive use of telehealth or video consultations, with reduced in‐person outpatient visits to minimise the risk of contracting COVID-19 for both patients and health care workers , 16. TelFigure While the COVID-19 pandemic has forced some government organisations and healthcare providers to use more telehealth for the care of heart failure patients, integration of this model of care into day-to-day heart failure management in a post-pandemic era remains a work in progress. Several studies that conducted in a non-pandemic environment have shown that telemonitoring of heart failure patients was feasible, and telemonitoring and telephone support can reduce mortality and heart failure‐related hospitalisations , 16. It The use of some of the heart failure medications in the setting of COVID-19 infection needs further discussion. There have been some concerns about the use of angiotensin converting enzyme inhibitors (ACEI) or angiotensin-2 receptor blockers (ARBs) in patients contracted with COVID-19. These concerns were largely based on the ability of COVID-19 virus to bind angiotensin-converting enzyme 2 (ACE2) receptors that are present on the surface of myocytes. There was a believe that the use of ACEI and ARBs may upregulate the ACE2 receptors, which in turn may enhance the myocardial uptake of the COVID-19 virus and the detrimental effect on the heart. However, the interplay between the ACE2 receptors and ACEI or ARBs remains poorly understood, with no clear evidence from available animal or human studies that ACEIs or ARBs lead to over expression of ACE2 receptors in the myocytes. Preliminary observations on patients hospitalized with COVID-19 showed that treatment with ACEI/ARB for hypertension during admission did not change the mortality rate . ACEI/ARHeart failure represents one of the most common cardiovascular conditions associated with significant morbidity and mortality. COVID-19 pandemic has made the care for patients with heart failure even more complex. Pre-existing cardiac conditions, such as heart failure, arrhythmia or coronary artery disease, elevate the risk of morbidity and mortality of COVID-19, and COVID-19 itself is associated with serious cardiovascular complications in those with or without a history of cardiac disease. While the traditional pharmacological and non-pharmacological therapies to heart failure remain unchanged in the era of COVID-19 pandemic, new models of cardiovascular health services, such as telehealth, need to be continued or refined to minimise the risk of viral transmission in patients and healthcare providers, and to optimize the outcomes of patients with heart failure.


A fiber-optic biosensing platform based on ultra-narrowband cladding mode resonances was developed on a high-reflectivity fiber Bragg grating (FBG) for targeting biomolecular detection. The multiple cladding modes with a high sensitivity to the refractive index (RI) were excited in the FBG by coupling between the forward-propagating guided core mode of the multimode fiber and the backward-propagating guided cladding mode of the FBG without any damage to the fiber structure or any change to the standard FBG manufacturing process. The full width at half maximum and the Q-factor of the typical cladding mode resonance operation of the proposed sensor are 80 pm and 19,270, respectively, which are better than those of most fiber-optic biosensors reported to date. In addition, the FBG sensor demonstrated a high sensitivity in protein detection and a high selectivity in serum sample assays. The sensitivity of this sensor was further increased simply by coating it with graphene oxide (GO) sheets on the sensing surface without using a signal amplification strategy. Furthermore, an ultra-low limit of detection (LOD) of 32 pM was obtained by the GO-coated FBG sensor for IgG detection. The proposed FBG sensor provides a competitive fiber-optic platform for biomolecular detection. It has a great potential for applications in label-free biosensing. At present, the development of label-free fiber-optic biosensors is expanding at a faster than expected pace ,2. A labFiber gratings are other types of commonly used fiber biosensing devices, such as etched or side-polished fiber Bragg gratings (FBGs), long-period fiber Bragg gratings (LPG), and tilted fiber Bragg gratings (TFBG) ,21,22. FMotivated by the realization of low-cost and high-performance fiber-optic biochemical monitoring, we proposed a high-reflectivity FBG biosensor based on ultra-narrowband cladding mode resonances in this paper. The transmission spectrum of the sensing structure shows a dense comb-like resonance due to the coupling between the forward-propagating guided core mode of the multimode fiber (MMF) and the backward-propagating guided cladding mode of the FBG. The narrow-band resonance possesses the narrow full width at half maximum (FWHM). This leads to a high Q-factor. The resonant wavelengths of cladding modes are sensitive to the RI and exhibits high stability in the blank buffer sample. As a typical demonstration, the FBG sensor was functionalized with anti-IgG for the detection of IgG at different concentrations and achieved the excellent limit of detection (LOD). The specificity of the FBG sensor was also verified by detecting IgG in serum. After that, we chose the graphene oxide (GO) sheet as the sensitizing material of our proposed FBG sensor to further improve the sensitivity. The GO film as a high RI film leads to enhanced evanescent waves. Its functional group promotes the bio-functionalization of the sensor through covalent bonding. Finally, the GO-coated FBG sensor achieves a high sensitivity and an ultra-low LOD, which is an order of magnitude lower than that of an uncoated FBG sensor. The aim of this work is to demonstrate an FBG as a label-free sensing platform as a proof of concept. It features simplicity, low cost, and high performance compared to the currently reported optical fiber configuration.GO dispersion was purchased from Nanjing XFNANO Materials Tech Co., Ltd. ; (3-Aminopropyl) triethoxysilane (APTES) was purchased from Tokyo Chemical Industry Co., Ltd. ; 1-(3-Dimethylamino-propyl)-3-ethylcarbodiimide hydrochloride (EDC) and N-Hydroxysuccinimide (NHS) were purchased from Saan Chemical Technology Co., Ltd. ; immunoglobulin G (IgG) from rabbit serum, anti-rabbit IgG antibody produced in goat, rabbit serum, and phosphate buffer solution  were purchased from Sangon Biotech Co., Ltd. ; and bovine serum albumin (BSA), glutaraldehyde, and other chemicals were purchased from Sigma-Aldrich Trading Co., Ltd. . All of the reagents were of analytical grade and could be used without further purification. All proteins were dissolved into PBS before use.2SO4: H2O) at 80 °C for 30 min. Subsequently, the sensing probe was mixed with 5% APTES in acetone and further incubated for 30 min. The sensing probe was further reacted in 25% glutaraldehyde at 80 °C for 30 min. After glutaraldehyde fixation and cleaning, the sensing probe was placed in anti-IgG solution (0.1 mg/mL) for 60 min. Thereafter, the sensing probe was soaked in BSA solution (1 mg/mL) as a blocking reagent for 15 min. In each case, the sensing probe was cleaned and dried with deionized water and N2 in turn.The sensing probe was first cleaned using piranha solution  overnight, and the GO sheet was self-assembled on the sensing surface. Subsequently, the sensing probe was reacted in NHS/EDC (0.5/0.5 M) mixed solution at 4 °C for 20 min. Anti-IgG solution (0.1 mg/mL) was injected onto the sensing probe for 60 min to attach the sensing probe. Finally, the sensing probe was soaked in BSA solution (1 mg/mL) for 15 min. In each case, the sensing probe was cleaned and dried with deionized water and NThe schematic overview of the FBG sensor is shown in The experimental transmission spectra of the FBG sensor in different RI environments, obtained by using the sensing system described in For the optical sensors that use the resonance dip as the sensing signal, the Q-factor associated with the FWHM is very important for the sensing resolution. The FWHMs of resonance dips at short wavelengths are significantly affected by the RI of the surrounding medium. However, the RI of the surrounding medium has little effect on the FWHMs of resonance dips at long wavelengths. The difference in FWHM is less than 5 pm between 1.33 and 1.47 for the surrounding medium. The FWHM of the resonance dips within 1535–1545 nm does not exceed 80 pm Although some resonance dips have FWHM as narrow as 50 pm, we still use 80 pm as a performance indicator for our sensor. We chose the resonance dip at 1541.6 nm as the test dip, as shown in Before conducting biochemical sensing, we investigated the stability of the FBG sensor and the error in the dip detection. We placed the sensor probe in the PBS buffer and monitored the spectra for 50 min (the spectra were recorded every 2 min). The experimental data were collected using a computer program developed by LabVIEW. A total of 25 sets of spectral data results were obtained and plotted, as shown in In order to test the biosensing capabilities of our sensors, the FBG sensors were applied for the detection of bioreceptor-analyte complexes such as anti-IgG/IgG. We injected rabbit IgG samples at different concentrations, and the samples would then flow over the sensing surface modified with goat anti-rabbit IgG. The resonant wavelength shift around 1541.6 nm was used as the sensor response. The wavelength shifts were recorded in real-time when the IgG was bound to anti-IgG during the test. The specific binding responses were stabilized within 10 min, indicating the successful binding of IgG to anti-IgG at the sensing surface. After one round of IgG testing, we injected urea into the flow cell to regenerate the sensing surface. Thereafter, we proceeded to the next sample test. Following the above procedure, we successively assayed the IgG samples at the concentrations of 670 nM, 335 nM, 134 nM, 66.7 nM, 13.4 nM, 3.35 nM, and 0.667 nM. The result is shown in In addition, in order to evaluate the specificity of our sensor for samples with complex compositions, we also used the sensor to detect IgG in diluted rabbit serum. In this experiment, we chose a serum concentration of 1 percent, which corresponds to the linear calibration range of the sensor. The response of the sensor to the rabbit serum was approximately 38 pm, corresponding to a concentration of 417 nM. This means that the concentration of IgG in the serum is predicted to be about 6.3 mg/mL which ranges from 5 to 12 mg/mL for normal rabbit serum. This result confirms that our sensor has good accuracy and high selectivity to IgG when thousands of other proteins are present in the serum.To achieve a higher sensitivity in label-free biosensing, the FBG sensor was designed with an overlay to tune the evanescent field on the cladding surface. In our work, GO sheets were selected to coat the cladding as an HRI material. This could enable the formation of a uniform thin layer on the fiber surface via dip-coating deposition method. The use of GO film-based HRI coatings leads to a reorganization of the cladding mode. It allows higher-order cladding modes to propagate over the overlayer. This leads to a larger shift of the corresponding resonance wavelengths and a higher contribution of their evanescent waves. In addition, GO exhibits good biocompatibility and high affinity for specific biomolecules due to hydrophilic oxygen containing functional groups . The carWe investigated the interaction of the GO layer with the evanescent field by simulation, as shown in n21)2−1] . Here, EWe performed a functionalization of the GO-coated FBG sensor and applied it to the detection of IgG at different concentrations. The responses with and without GO-coating at each concentration of the FBG sensor are compared in r are shown as error bars in In order to verify the reproducibility of our experimental results, the sensing chip was regenerated in high-concentration urea (8M) for 5 min. Each measurement at a given concentration was repeated three times. Variabilities of wavelength responses among the same concentration of IgG injections (n = 3) are estimated by relative errors (EWe demonstrate a high-reflectivity FBG biosensor based on ultra-narrowband cladding mode resonances. The proposed sensor is fabricated using the common fiber fusion splicing and fiber grating photo-inscription technologies. The FWHM of the typical cladding mode of the proposed sensor is 80 pm. Its Q-factor is as high as 19,270. Therefore, it is better than most optical fiber biosensors reported so far, including fiber interferometers, fiber grating sensors, and fiber SPR sensors. The sensor demonstrates a sensitive response to protein detection and a high selectivity in serum samples with complex protein composition. The thin layer of GO was introduced to achieve an improvement in sensitivity. Moreover, its high RI character effectively enhanced the excitation of the evanescent field. Without using signal amplification by functionalized gold nanoparticles or second antibodies, an ultra-low LOD of 32 pM was obtained by the GO-coated FBG sensor from IgG detection. This proves that our sensor shows a great potential for applications in highly sensitive and label-free biochemical sensing. In addition, the fabrication of the proposed high-reflectivity FBG biosensor involves only the standard FBG fabrication process and the optical fiber fusion technology. This ensures cost-effective mass production.


The transmission dynamics and burden of SARS-CoV-2 in many regions of the world is still largely unknown due to the scarcity of epidemiological analyses and lack of testing to assess the prevalence of disease. In this work, we develop a quantitative framework based on excess mortality data to reconstruct SARS-CoV-2 transmission dynamics and assess the level of underreporting in infections and deaths. Using weekly all-cause mortality data from Iran, we are able to show a strong agreement between our attack rate estimates and seroprevalence measurements in each province and find significant heterogeneity in the level of exposure across the country with 11 provinces reaching near 100% attack rates. Despite having a young population, our analysis reveals that incorporating limited access to medical services in our model, coupled with undercounting of COVID-19-related deaths, leads to estimates of infection fatality rate in most provinces of Iran that are comparable to high-income countries. Testing capacity continues to limit detection of COVID-19 infections and impacts reliability of mortality estimates. Here, the authors develop a statistical model to estimate COVID-19 attributable deaths using all-cause mortality data from Iran and estimate that around half of these deaths have been reported. An alternative approach to measuring the burden of COVID-19 is to monitor changes in all-cause mortality trends with respect to baseline levels based on historic trends . While excess mortality during the current pandemic may not exactly match the true number of COVID-19-related deaths due to various reasons such as disruptions in treatment for other fatal diseases and socio-economic disparities in health care in different regions of a country, several works have shown that a significant portion of excess deaths in many countries are directly attributable to COVID-1911. This enables us to use excess mortality as a proxy for estimating the number of infections and fatalities from COVID-19 and correct for under-reporting of cases and deaths that may arise due to limited testing from suspected cases and uncertainty in the number of fatalities attributable to COVID-1913.Assessing the true burden of COVID-19 requires a comprehensive surveillance system to monitor outbreaks and a large capacity for diagnostic testing. However, this is particularly challenging for many low- and middle-income countries due to limited diagnostic capacities and access to healthcare18. It was also one of the first countries to experience a second wave of infection after the relaxation of non-pharmaceutical interventions (NPIs) in July 202019. By the end of year 2021, the country experienced three additional waves, two of which were driven by the Alpha and Delta variants of SARS-CoV-2, in May and September 2021. Despite a recent increase in the number of daily administered vaccine doses, Iran had a very slow start on its immunisation programme with only ~3% of the population being fully vaccinated by the end of July 2021, during the surge in cases with the Delta variant20. Because the Ministry of Health and Medical Education (MoHME) of Iran stopped releasing province-level data on the number of confirmed COVID-19 cases and deaths from 2020-03-22, the transmission dynamics across the country have remained largely unknown. One way to estimate the number of infections and account for under-reporting of cases is by converting deaths attributable to COVID-19 to infections using a population-weighted infection fatality ratio (IFR) estimate , taking into account the demographics of the population of interest21. However, such estimation of attack rates can be inaccurate or misleading if it does not take into account the impact of limited access to health care in municipalities with low socioeconomic status, uneven adoption of pharmaceutical and non-pharmaceutical intervention in different areas, and the increased chance of re-infection over time. In particular, it is clear from the SARS-CoV-2 epidemics arounds the world during 2020 and 2021 that the demand for intensive care beds and mechanical ventilators can place a severe strain on health systems. This has likely more profound consequences for low-income settings where the availability and quality of healthcare and related resources is typically limited22. Neglecting to account for these factors can result in an overestimate of SARS-CoV-2 attack rates and underestimation its potential for continued transmission, with immediate implications for assessments of the potential burden of SARS-CoV-2 variants of concern such as Omicron in a population.Iran was among the first countries outside mainland China to report a large outbreak of SARS-CoV-2 in February and March 2020 and also acted as a major source for its spread in several countries in the Middle East and elsewhereIn this work, we use the newly updated province-level age-stratified weekly all-cause mortality data from the National Organization for Civil Registration (NOCR) of Iran and develop a mathematical framework to fully reconstruct the Iranian epidemic with the aim to estimate the attack rate, number of daily hospital admissions, deaths, and re-infection rates of SARS-CoV-2 across the country.23. Furthermore, during the first two waves of the Iranian epidemic, the excess mortality was roughly 2.5 times higher than reported COVID-19 fatalities. However, this dropped to 2.1 at the later stages suggesting that the testing capacity of the country to record infections and deaths gradually improved over time, but not to the extent to fully capture the majority of COVID-19-related deaths. This is also in agreement with statements from the Iranian health officials suggesting that Iran’s COVID-19-related deaths could be twice the official numbers and also previous studies showing elevated levels of under-reporting of COVID-19 fatalities in Iran, particularly in the early stages of the pandemic15. We also find that the cumulative nationwide excess deaths by 2021-10-22 is 259,641  which is nearly twice the 125,000 reported COVID-19 deaths at the time.We obtain age-stratified weekly all-cause mortality data from NOCR and apply a statistical model to calculate the weekly excess mortality for all 31 provinces and across 17 age-groups during the Iranian epidemic (see Methods section). Figure 14. As the epidemic progressed, the timing of the peak excess mortality between different provinces were more simultaneous , and that Iran fully vaccinated roughly 5 times the population size of individuals aged 75 and above by 2021-09-07, it is likely that the drop in excess mortality in the older age-groups before and during the fifth wave is due to their high vaccination coverage.We also carry out a similar analysis to estimate the temporal pattern of COVID-19 fatalities for different age-groups Fig. . We find25, we attribute the mean excess mortality during the pandemic period to COVID-19. This enables us to reconstruct the SARS-CoV-2 transmission dynamics across the country and infer the population fatality rate (PFR), IFR, and attack rate per province (see Methods section). We first estimate the national and provincial attack rates of SARS-CoV-2 under two different sets of assumptions of the IFR by age relationship and select the better-fitting model by comparing the modelled seroprevalence estimates to data  herd-immunity to be reached after the fifth wave.Using our transmission model, we also calculate the cumulative attack rate by 2021-10-22 for each province Fig. . Our res33. International comparisons of COVID-19 death tolls have subsequently relied on excess mortality due to under-reporting of COVID-19 deaths in many parts of the world2. This study is the first to formally explore the suitability of excess mortality as a proxy for estimating under-reporting of COVID-19 infections and deaths, confirming the information contained within reliable excess mortality statistics through the broad agreement with representative seroprevalence estimates. Additionally, this analysis lends further support to evidence that IFR patterns estimated in high income countries may underestimate the IFR in settings with stretched healthcare capacity27, as experienced in many provinces in Iran at periods during the pandemic35. Even though in some provinces we find that the transmission model with a lower estimated IFR provides a better fit to seroprevalence estimates, such a model offers a poor fit across most provinces and often results in epidemiologically unrealistic outcomes such that the modelled transmission dynamics outruns the pool of susceptible individuals. We also note that while some factors such as misidentification of baseline all-cause mortality and deaths attributable to COVID-19, particularly in the younger age-groups with fewer COVID-19-related deaths, can contribute to varied attack rates in some provinces, other factors such as nonrepresentative serosurveys, varied time to seroreversion using different assays, and uncertainty in inferring the true contact matrix between different age-groups within the population can impact the inferred attack rates37. Absence of accurate vaccination data could be another potential source of bias that may influence our modelled attack rates in some provinces, particularly in provinces that experienced high transmission levels due to Delta during the last wave. For instance, if we overestimate the level of protection from vaccines, more individuals need to be infected in a given wave in order to produce an epidemic that correctly matches the observed mortality. Similarly, if more vaccines are distributed to younger individuals than we currently assume in the model, it could lead to an artificial increase in the IFR with those highest at risk not being protected.Since the start of the pandemic, the global heterogeneity in COVID-19 reporting systems globally has resulted in substantial debate about the true extent to which COVID-19 has spread in each country38. This threshold does not represent the point at which the outbreak immediately stops, but rather the point where, on average, fewer secondary infections are produced. During unmitigated outbreaks with such reproduction numbers, the attack rate can reach as high as 90%40. Similarly, during unmitigated outbreaks with variants of concerns such as the Delta variant with increased reproduction numbers compared to the ancestral SARS-CoV-2 virus, the attack rate can reach even higher levels41. While the duration of antibody responses after coronavirus infection over longer timescales remains largely unknown, recent surveillance data and comparative studies have shown that re-infection with SARS-CoV-2 is possible after 3–6 months, and that older age-groups have a much lower protection against reinfection43. Previous studies on human coronaviruses and SARS-CoV have also shown that protective immunity typically starts declining after 5–8 months post infection46. Our findings of high attack rates in several provinces show that herd immunity through natural infection has not been achieved in the population even after nearly 20 months since the start of the Iranian epidemic. This is likely due to substantial reduction in protection against repeat infection over time either due to waning immunity, increased chance of re-infection with variants of concern, or a combination of both. We note that while systematic biases such as identifying the baseline level of all-cause mortality and overestimation of deaths attributable to COVID-19, particularly in the younger age-groups, can contribute to increased attack rates in some provinces, other factors such as heterogeneities in immune protection, limited access to health care in municipalities with low socioeconomic status, and uneven adoption of public health intervention in different regions can also contribute to varied attack rates across the country.Prior to the emergence of the variants of concern, the basic reproduction number of the SARS-CoV-2 virus was estimated to be around 2.8 which corresponds to a herd immunity threshold of about 64%15. Therefore, in order to avoid biasing our expected mortality estimates from years prior to the pandemic, we exclude mortality data during autumn 2019 (from 2019-09-23 to 2019-12-21) from the calculation of background mortality as it may shift the baseline mortality upwards and, hence, result in the underestimation of excess mortality during the pandemic years in autumn 2020 and 2021. We calculate the expected mortality using a linear regression model that accounts for seasonality and trend, previously developed to track excess mortality across more than 100 countries and territories around the world1. As a robustness test, we also calculate expected mortality with the same model under the assumption of an over-dispersed Poisson to see if different methods of calculating excess mortality yields significantly different results. We find that the estimated excess mortality using both methods are virtually identical over time across all provinces  (from 2015-03-15 to 2019-09-22 in Common Era) to calculate background mortality. We find significant levels of excess mortality during several weeks (mostly concentrated in weeks 35 to 45) of autumn 2019 prior to the start of the COVID-19 pandemic  based sampling scheme, which estimates the epidemic start date, R0 and the time varying reproduction number, Rt, using a series of pseudo-random walk parameters, which alter transmission every 2-weeks, given by:f(x) = 2.exp(x)/(1 + exp(x)), i.e., twice the inverse logit function. Each parameter is introduced two weeks after the previous parameter, serving to capture changes in transmission every two weeks. The last change in transmission, ρn, is maintained for the last 4 weeks prior to the current day to reflect our inability to estimate the effect size of this parameter due to the approximate 21-day delay between infection and death22. The MCMC sampling scheme includes adaptive tuning of the proposal implemented during sampling using the Johnstone-Chang optimisation algorithm48. All parameter inference results are based on 100,000 iterations, 10,000 of which are discarded as burn-in. MCMC chains are checked for convergence using standard Gelman-Rubin diagnostics49.We use a previously published age-structured COVID-19 transmission model50. The effective number of general hospital beds and intensive care beds were sourced from the Iran statistical yearbook published in 1396 in Solar Hijri calendar51. At the time of writing, MoHME has not published subnational daily vaccination data prior to 2021-10-26, nor the proportion of which vaccines are administered. As a result, we used multiple data sources to approximate the roll of vaccines subnationally. From 2021-10-26, MoHME started to release the total number of first and second vaccine doses subnationally, which we use in combination with national vaccination data52 to infer the daily vaccination rate per province. A mix of vaccine types have been administered in Iran, with 80% of the population vaccinated with Sinopharm, 10% with AZ and the remaining 10% either Sputkink-V (1.5%) and CoViran Barekat (8.5%). Due to the mix of vaccine types with uncertain efficacy estimates, particularly related to Delta, we use vaccine efficacy estimates for first and second dose efficacy sourced from estimates for the Sinopharm vaccine and other inactivated whole virus vaccine platforms (Table gisaid.org), lagged by 14 days to reflect the delay from administering vaccine to protection being conferred.Each model fit used province-specific demography, with the population size in 5-year age bands sourced from the Statistical Center of Iran53 and conduct model comparison between the two references through comparison against province level estimated seroprevalence data16, with seroprevalence assumed to be described by a Binomial distribution. Lastly, to explore if IFR is changing over time, we explore the ratio of model inferred hospitalisations and observed daily hospitalisations against time using a mixed-effects model, controlling for variation between provinces using a random intercept and slope with respect to time.Imposing a single IFR across the whole country may lead to biased attack rate estimates as it does not account for various factors such healthcare capacity or demographics of each province. To avoid this, we assume that the IFR in each province is dependent on the demographics of the province, such that provinces with older populations have, on average, higher IFRs. The model also tracks the number of people who require a general hospital bed or an ICU bed so that if there is a bed shortage during an epidemic peak in a given province then the mortality outcomes for individuals who do not receive a bed will increase. We explore three sets of model assumptions, which scan across the likely range of parameter estimates for key model parameters that impact the inferred attack rate. These parameters relate to the assumed number of general and ICU hospital beds available, the change in hospitalisation related to the Delta variant and the level of immune escape conferred by the Delta variant relative to previous infection by the Alpha variant and the original wild type strains. Here, the level immune escape only refers to immunity from previous infection, which acts by making a proportion of people who would have been protected against reinfection by the same variant susceptible to infection with Delta. With regards to immunity from vaccination, we assume that the impact of Delta is to reduce the level of protection conferred by the vaccines. These ranges are described in Table 15, 53, where L is the total number of age-groups, αi is the age-stratified IFR for age-group i, σi is its standard error, and wi is the proportion of individuals within age-group i in the population. Unlike IFR estimates based on our transmission model which takes into account the impact of various factors such as province-level demographics, impact of healthcare capacity constraints on increased mortality rates, and increased chance of hospitalisation with Delta the population-weighted IFR only accounts for the province-level demographics which enables us to assess the influence of other factors on increasing IFR.To assess the impact of healthcare capacity constraints on increasing the mortality from COVID-19, we also calculate the mean population-weighted IFRFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Reporting Summary


Paediatric and adult psychiatric emergency department (ED) visits decreased during the initial COVID-19 outbreak. Long-term consequences of the COVID-19 pandemic will include increases in mental healthcare needs, especially among vulnerable groups such as children and adolescents.This study examined changes in the number of overall and diagnosis-specific mental health ED visits among patients aged <18 years following the onset of the COVID-19 pandemic in Madrid, Spain.Using clinical records from all psychiatric ED visits at a major teaching hospital between October 2018 and April 2021, we conducted interrupted time-series analyses and compared trends before and after the day of the first ED COVID-19 case (1st March 2020).A total of 663 patients were included. In March 2020, there was a marked initial decrease of -12.8  less monthly mental health ED visits. After April 2020, there was a subsequent increasing trend of 3.4  additional monthly mental health ED visits.After the onset of the COVID-19 pandemic, there was an increase in paediatric psychiatric ED visits, especially due to suicide-related reasons. These data reinforce the crucial role of the ED in the management of acute mental health problems among youth and highlight the need for renovated efforts to enhance access to care outside of and during acute crises during the pandemic and its aftermath. The COVID-19 pandemic is having a substantial negative mental health impact on the population across the globe , 3, 4. IEmergency Departments are an important pathway to care for children and adolescents with mental health problems , especiaRecent evidence indicates sustained negative mental health outcomes among children and adolescents during the first year of the COVID-19 pandemic . HoweverWe used electronic health records to extract the monthly numbers of total and diagnosis-specific mental health ED visits among patients aged <18 years, between October 2018 and April 2021, to La Paz University Hospital, a large teaching hospital providing acute and emergency care to a catchment area of around 525,000 people in Madrid, Spain, one of the largest global pandemic hotspots during Spring 2020.Diagnoses were exacted from ED clinical records and were grouped into the following DSM-5 diagnostic categories: Depressive disorders, anxiety disorders, schizophrenia spectrum and other psychotic disorders and eating disorders. Given the prevalence of suicide-related phenomena as a main complaint in ED, we added them as a specific category, including suicidal ideation or suicide attempt .Of the total of 663 patients included, 67.5% were females. The mean age was 15 years and two months. The most prevalent diagnostic category was suicide-related phenomena, which accounted for 43.2% of ED visits, followed by depressive disorders (21.0%), anxiety disorders (19.2%), schizophrenia spectrum and other psychotic disorders (6.6%), and eating disorders (2.5%).We conducted interrupted time-series analyses  to quantInterrupted time-series analyses indicated that mental health ED visits among patients aged <18 years remained overall stable between October 2018 and February 2020 . In March 2020, there was a marked initial decrease of -12.8  monthly mental health ED visits. After April 2020, there was a subsequent increasing trend of 3.4  additional monthly mental health ED visits. The difference in trends before and after March 2020 was of 3.2  additional monthly mental health ED visits.Diagnostic-specific analyses suggested that overall increases in mental health ED visits were driven by increases in suicide-related phenomena . Following the initial pandemic outbreak, we also detected increases in anxiety  and depressive disorders  – though for the latter the wide confidence intervals are also compatible with decreasing trends. There were hardly any differences in eating disorders  and schizophrenia spectrum and other psychotic disorders . Mental health ED visits among children and adolescents decreased sharply shortly after the initial COVID-19 outbreak, and subsequently increased over the following months - with over three more monthly mental health ED visits between April 2020 and April 2021. Other studies reported a similar trend, with a decrease in mental health visits to ED during lockdown compared to the year before, followed by an increase in the reopening months .Furthermore, during the post-lockdown period, there was an increase in diagnoses of suicidal behavior  and, to We identified a sustained increase in child and adolescent mental health ED requirements during the months following the initial pandemic onset. These findings highlight the importance of strengthening child and adolescent mental healthcare provision in the context of the ongoing pandemic and its aftermath. Particular emphasis should be placed in ensuring access to interventions to prevent suicide and suicidal behaviors, as the most salient increase in child and adolescent mental health ED visits corresponded to suicide-related consultations. Similar increases in youth ED visits or hospital admissions due to suicide attempts during the initial months of the pandemic period were seen in Turkey , the UniMost evidence-based suicide prevention interventions for youth, such as the Safety Planning Intervention or dialectical-behavioral therapy ,28, can Our study has limitations that should be considered. As with most studies based on electronic healthcare records, our study is limited by potential errors in the transcription of clinical information. However, we used broad, easy-to-detect diagnostic categories, and there is no reason to believe that presence of such errors may have varied over the study period. Also, by focusing solely on ED visits, we are underestimating the actual increase in mental health needs brought about by the pandemic, as we could only detect the most severe cases , includiEven though the study center’s catchment area is a large, highly heterogeneous area with over half a million inhabitants, our results may not be representative of the entire population of the region of Madrid. Our data, however, remain valid to estimate the increase in pediatric psychiatric emergency needs, and we hope that it promotes further analysis of this issue in larger populations.In conclusion, shortly after the onset of the COVID-19 pandemic, there was an increase in pediatric psychiatric ED visits, especially due to suicide-related reasons. These data reinforce the crucial role of the ED in the management of acute mental health problems among youth and highlight the need for renovated efforts to enhance access to care outside of and during acute crises during the pandemic and its aftermath.


Chi-square and independent t-test were used to compare baseline characteristics and Kaplan–Meier curves and Cox models were used for survival analysis. Results: Patients with NAFLD-HCC were more likely to be diagnosed due to symptoms rather than through screening, and at an older age, compared with non-NAFLD HCC. The median survival rates were lower in NAFLD-HCC (17.2 months) than in those with non-NAFLD-HCC (23.5 months). Conclusion: There is a rise in the number of HCC cases in patients with NAFLD, and this has significant implications for hepatologists as they are presented with more advanced diseases and have poorer outcomes. Future studies on HCC will need to identify this group earlier in order to have an impact on the HCC survival rate.Background: Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent liver disease in Australia and is recognised to play a role in the development of hepatocellular carcinoma (HCC). There are no clear guidelines regarding screening for HCC in NAFLD. The aim of this retrospective study was to compare the characteristics and survival rates of NAFLD-HCC to patients with non-NAFLD-HCC to help guide future research in this area. Methods: A total of 152 HCC patients with either NAFLD ( Hepatocellular carcinoma (HCC) is the seventh most common cancer and the second leading cause of cancer deaths worldwide . It accoWhile the incidence of HCC in the presence of NAFLD cirrhosis is considered to be lower than that of viral hepatitis (2.6% versus 4.0%) , the ris®), hospital electronic medical records  and clinical patient folders . Missing data were obtained from medical correspondence from independent health providers, including general practitioners, pathology and radiological services. All patients were aged 18 years or over, with a diagnosis of HCC made according to the American Association of the Study of the Liver (AASLD) clinical, radiological and/or histological criteria [All cases of HCC diagnosed over the period between January 2010 and December 2016 from the HCC database were reviewed for evidence of the metabolic syndrome and NAFLD. Data were retrospectively collected from three independent locations: electronic HCC database  was diagnosed according to AASLD practice guidance for NAFLD ,13: by eBaseline data included patient the following demographics: age at diagnosis, gender, ethnicity (self-reported); features of the metabolic syndrome: body mass index (BMI), hypertension; presence or absence of cirrhosis and degree of decompensation (Child–Pugh stage). The presence of type 2 diabetes and hyperlipidaemia was also recorded. The tumour characteristics included: the date and method of HCC diagnosis , Barcelona Clinic Liver Cancer (BCLC) staging, size of largest lesion at diagnosis, initial management and overall survival (months). In addition, therapy for HCC  received was noted, including treatment response measured via mRECIST criteria , and oveBaseline data on metabolic syndrome was collected as close to the time of diagnosis of HCC as possible, including high BMI, type 2 diabetes, hyperlipidaemia and hypertension. The presence of hypertension was confirmed via clinician notes on the EMR, or the presence of anti-hypertensive agents recorded in medication charts. BMI data were available in approximately 70% of the patients. Alcohol intake was assessed as number of standard drinks per day, with greater than four standard drinks per day or fourteen standard drinks per week considered consistent with alcoholic liver disease . The preEthics approval was obtained by the Eastern Health Office for Research and Ethics local reference number LR25/2017.2) and independent t-test were carried out to compare baseline characteristics. Overall survival time from diagnosis was the primary study endpoint, which was expressed as both a mean and median. Univariate and multivariable Cox logistic regression analysis was used to determine predictors of overall survival. The Kaplan–Meier survival analysis was used to plot overall survival as a function of time, which excluded patients which failed to undergo follow-up. Cox models were also used for survival analysis. p values < 0.05 were considered statistically significant.Continuous variables were expressed as a mean with a 95% confidence interval (CI). Categorical variables were summarised as a percentage. Chi-squared , with 8% of patients being of Asian ethnicity. In the non-NAFLD cohort, a higher proportion of those with Asian descent (24%) was observed, reflecting mainly patients with HBV-related liver disease. Other aetiologies of liver disease in the non-NAFLD population included predominately alcoholic liver disease (30%), Hepatitis B (23%), Hepatitis C (16%) and a mixture of Hepatitis C and alcoholic liver disease (25%), as shown in p = 0.12). In those with cirrhosis, the distribution of the Child–Pugh stage was not significantly different between the two groups. NAFLD-HCC was more likely to present due to symptoms (p = 0.046) with a trend towards larger tumours (p = 0.20). Despite this, both cohorts had similar distributions of BCLC stages, with the majority in both groups presenting with BCLC-C disease; however, there were more advanced diseases (BCLC D) in the NAFLD cohort.A higher proportion of NAFLD-HCC patients were not cirrhotic at baseline; however, most did have cirrhosis (81%) and the prevalence of cirrhosis between NAFLD and non-NAFLD patients (90%) was not statistically different (p = 0.004) with the majority undergoing surgical resection. This is compared to a predominance of drug-eluting bead transarterial chemoembolization (DEB-TACE) (47%) in the non-NAFLD patients versus NAFLD-HCC (17% p < 0.001). Nearly one-third (31%) of NAFLD-HCC patients in the study cohort received best supportive care only, compared with only 17% in the non-NAFLD-HCC group (p < 0.001). Only one patient in the NAFLD-HCC group received a liver transplant, compared to five patients in the non-NAFLD group following initial treatment  of the patients. From January 2000 to December 2016, 84 (58%) patients had died, with deaths equally distributed among the NAFLD group (56%) and the non-NAFLD group (58%). The proportion of liver-related deaths in both groups were also equal to 88%. Patients with NAFLD had a median survival time of 17.2 months, compared with 23.5 months in those with non-NAFLD-related HCC. There was no significant difference in the overall survival between NAFLD and non-NAFLD cohorts at four years on Kaplan–Meier survival analysis . None ofp < 0.001). In contrast, male sex was associated with improved overall survival . Age at diagnosis and hypertension remained predictive on multivariate analysis of poorer survival, while male sex was consistently associated with improved survival. Type 2 diabetes and hyperlipidaemia were not examined in the univariate and multivariate analyses as they are confounded with the diagnosis of NAFLD.On univariate Cox regression analysis, higher BMI, hypertension and increased age at diagnosis were associated with reduced overall survival with hypertension having the strongest association  and male (67%) . This stThe metabolic syndrome has increasingly been associated with HCC, but the exact relationship remains unclear. The increased BMI of the NAFLD-HCC group may increase the risk of malignancy by placing the body into a chronic inflammatory state via the release of pro-inflammatory cytokines such as interleukin-6 (IL-6) and tumour necrosis factor alpha (TNF-α) . These iNAFLD-HCC was demonstrated to have similar four-year survival to HCC with other underlying liver diseases  which isNAFLD-HCC is likely to become an even larger subset of patients with HCC in Australia, especially as HBV and HCV treatments and their uptake improves in the era of direct-acting antiviral therapy. Future management strategies for this increasing group of HCC patients needs to be developed to improve outcomes. NAFLD is often silent and overlooked, even in the presence of early cirrhosis, and raising awareness on the risk of HCC in these patients is needed. However, the focus should remain on those with NAFLD cirrhosis, as our data and the data from the United Kingdom have shown this is the highest risk group for HCC development ,23. HoweMost HCC screening programs utilize liver ultrasound as the main tool, which is not always practical for patients with a higher BMI, and this may need to be addressed in the future . The comThere are several limitations to this study. Firstly, the data were retrospectively collected with unavoidable missing data and inability to conduct patient follow-up. The presence of diabetes mellitus as a baseline characteristic was not reported in this study due to incomplete data, but has been shown in other studies as a relative risk of 2.31 for HCC development . LikewisIn conclusion, this is the first study in an Australian population to analyse the different characteristics and survival rates between NAFLD-HCC and non-NAFLD-HCC. NAFLD HCC outcomes may be improved by better surveillance and identification of risk factors to focus screening on the highest risk group in this increasing population with HCC. This study provides informative data for future prospective analyses regarding the role of metabolic risk factors in HCC development and prognosis.


On August 4, 2020, a massive explosion struck the Beirut Harbor in Lebanon. Approximately 220 people were killed and around 7,000 were injured, of which 12% were hospitalized. Despite being weakened by economic crisis and increasing numbers of coronavirus disease 2019 (COVID-19) cases, the national health care system responded promptly. Within a day, international health care assistance in the form of International Emergency Medical Teams (I-EMTs) started arriving. Previous studies have found that I-EMTs have arrived late and have not been adapted to the context and dominating health care needs. The aim of this study was to document the organization, type, activity, and timing of I-EMTs deployed to Beirut and to discuss their relevance in relation to medical needs.Data on all deployed I-EMTs were retrieved from all available sources, including internet searches, I-EMT contacts, and from the World Health Organization (WHO) EMT coordination cell (EMT CC) in Lebanon. The WHO EMT classification was used to categorize deployed teams. Information on characteristics, timing, and activities was retrieved and systematically assessed.Nine I-EMTs were deployed to Beirut following the explosion. Five were equivalent to EMT Type 2 , out of which three were military. The first EMT Type 2 arrived within 24 hours, while the last EMT set up one month after the explosion. Four civilian I-EMTs provided non-clinical support as EMT Specialized Care Teams. A majority of the I-EMTs were focused on trauma care. Three of the four I-EMT Specialized Care Teams were rapidly re-tasked to support COVID-19 care in public hospitals.A majority of the deployed I-EMT Type 2 were military and focused on trauma care rather than the normal burden of disease including COVID-19. Re-tasking of EMTs requires flexible EMTs. To be better adapted, the I-EMT response should be guided by a systematic assessment of both health care capacities in the affected country as well as the varying health effects of hazards before deployment. Several health facilities were destroyed and an estimated 500 hospital beds out of 13,000 in the country were lost. The Lebanese health system was already weakened by the 2019 economic collapse and increasing numbers of coronavirus disease 2019 (COVID-19) patients. However, the national response was prompt, impressive, and largely sufficient. Reportedly within the first two days, 8,643 injured sought care at 42 hospitals located within 88.2km of the Port of Beirut. In addition, international health care assistance started arriving within days of the explosion.On August 4, 2020, a storage containing 2,750 tons of ammonium nitrate exploded in the Port of Beirut, Lebanon. The blast killed around 220 people, injured more than 7,000 people, and approximately 300,000 people became homeless. To address these shortcomings, the World Health Organization  and partners launched the Emergency Medical Team (EMT) initiative in 2013. Following guidelines on classification and standards, agencies can apply to be WHO EMT classified. The EMT initiative also includes an EMT coordination cell (EMT CC) that aims to support the Ministry of Health in the affected country to ensure that international EMTs are an asset for the national emergency operation center.Previous studies have shown that international health care assistance after disasters has arrived late and has been ill-adapted to medical needs. International agencies have not been sufficiently coordinated, accountability has been questioned, and lack of data has made it impossible to fully evaluate their performance.To improve international health care response to disasters, studies on recent deployments are needed. To date, the international health care assistance in Beirut has not been documented nor assessed. The aim of this study was to document the organization, type, activity, and timing of international EMTs (I-EMTs) deployed to Beirut following the explosion on August 4, 2020 and to discuss their relevance in relation to medical needs.This observational study compiles data collected from September 1, 2020 through February 3, 2021. No individual patient medical or personal data were included and most of the information collected was from open online sources or reports from the I-EMT Type 2s to the WHO EMT CC. Based on the EMT initiative ambition of transparency and accountability, retrieved information was treated as open source. No ethical concerns were identified that outweighed the study aim and consequently ethical review board permission was not deemed necessary. Any type of document or study written in English, related to the I-EMT response in Beirut 2020, and containing information on I-EMT type, activities, and deployment timing was included.Data were obtained based on the methodology of previous studies on I-EMT deployments.Secondary data made available by the WHO EMT CC in Beirut;Internet searches  using the search words “emergency medical team,” “foreign medical team,” “field hospital,” “explosion Beirut,” “Beirut blast,” “military field hospital,” “lessons learned,” “healthcare”;Key websites of deployed I-EMTs, the United Nations Office for the Coordination of Humanitarian Affairs  Beirut Port Explosions Situation Reports, the WHO Beirut Blast Situation Reports, and the United Nations Population Fund  Situation Reports on Beirut Port Explosion;Secondary data provided by a team from the Beirut Arab University  on the available foreign medical capabilities in Beirut ; andDirect contact with the I-EMTs requesting data on their deployment.The data sources in this study were: regardless if the agency was WHO EMT classified or not:An EMT Type 1 (EMT-1) is a facility providing out-patient care,An EMT Type 2 (EMT-2) offers in-patient and surgical care, andAn EMT Type 3 (EMT-3) offers advanced referral in-patient care.Specialized Care Teams offer specialized care  but do not offer a facility structure.Each I-EMT was classified as being either a governmental (civilian or military) or nongovernmental organization (NGO). The country of origin was noted. Type was defined using the EMT classification system,Reported capacities  were noted as well as the date of arrival, days required for set-up, and time of departure from Beirut. Data were entered into a Microsoft Excel database .To ensure maximum consistency, data were triangulated and when inconsistent, they were validated using information from I-EMT staff and the WHO EMT CC. One of the authors (Johan von Schreeb) served as a WHO EMT coordinator in Lebanon and visited all I-EMTs. He held weekly I-EMT coordination meetings where the I-EMTs  participated. His observations and official meeting reports were part of the material for the study. The WHO EMT CC also repeatedly contacted all international field hospitals (I-EMT-2) for data on activities.Nine I-EMTs were deployed to Beirut, of which five were field hospitals EMT-2s) focused on surgical trauma care. Of these five, three were military ; one governmental ; and one was from the Iranian Red Crescent . The EMERCOM EMT is WHO classified (EMT-2). For reported capacities of the I-EMT-2s and their medical equipment, see Table s focusedIn addition, four I-EMTs equivalent to Specialized Care Teams were deployed initially to assess health care needs. The teams arrived from Poland , Switzerland , the United Kingdom , and the United States . All Specialized Care Teams were civilian: two NGOs and two governmental. The PCPM EMT, the UK-EMT, and the SDC are WHO EMT classified, while Samaritan’s Purse is in the process of classification.The Qatari army donated two structures that were erected outside two destroyed hospitals with space for approximately 100 hospitals beds as well as medical equipment.Availability of data on the I-EMT-2 activities varied. The EMERCOM hospital reported around 1,000 consultations without further specification. The Iranian RC field hospital provided mainly out-patient consultations (OPCs); no specific data were made available to the WHO EMT CC. Reportedly, some 300-400 OPCs were done until the structure was donated to local health authorities one month after arrival. The Jordanian field hospital offered OPCs but did not report activities. During a visit by the WHO EMT CC two weeks after the blast, this hospital had not admitted patients nor performed any major explosion-related trauma surgery. Data from the Moroccan military field hospital reported both OPCs and surgeries. The Italian field hospital had 32 beds and intensive care unit (ICU) capacity, but admissions to the facility remained low. A total of 1,100 OPCs and 1,300 polymerase chain reaction (PCR)-tests for COVID-19 were reported, but no data were available on specific activities. During two visits by the WHO EMT CC, daily activities were limited to a few OPCs of mainly non-communicable diseases. All OPC patients were PCR tested for COVID-19 prior to entering the I-EMT-2s. If they tested positive for COVID-19, they were referred to a public hospital. See Table The I-EMT Specialized Care Teams deployed to support local agencies and hospitals and did not report specific activities. Based on identified needs, three I-EMT Specialized Care Teams were re-tasked by the WHO EMT CC to provide technical support for COVID-19 care at six public hospitals.The two prefabricated structures set up by the Qatari army did not have running water nor toilets. When visited by the WHO EMT CC a month after the blast, the structures had not been used for clinical practice.The timing of the I-EMTs varied Figure . The majThe SDC and the team from Samaritan’s Purse stayed for approximately one month. The PCPM stayed until the beginning of November 2020. The UK-EMT supported COVID-19 care at four public hospitals in Lebanon until March 2021.The structures that the Qatari army donated were erected two weeks after the blast. Three hospitals were destroyed in Beirut , while remaining hospitals were intact. Primary health care was needed as almost 40% of primary care facilities in the affected area were damaged in the blast. Previous studies and guidelines have emphasized the need for multi-disciplinary EMT capacities in order to also cover the normal burden of disease. However, most of the I-EMT-2s in Beirut did not expose such capacity. At the time of the blast, few COVID-19 cases were hospitalized in Lebanon, something that changed in the following months. None of the I-EMT-2s accepted nor could adapt their services to include care for COVID-19 patients, despite requests from the WHO EMT CC.A majority of I-EMTs were focused on providing trauma care, though these needs had already been met by the national health system. The well-developed  Lebanese health care has significant experience in treating explosion- and conflict-injured. The explosion mainly generated minor injuries that could be managed ambulatory; only around 12% of the injured needed hospitalization.Most of the deployed I-EMT-2s were military. Military field hospitals have resources to rapidly deploy to disasters where national health care is strained. In Beirut, the Moroccan military field hospital provided health care corresponding to the normal burden of disease in Lebanon. This hospital was also located close to the most affected area and rendered positive appreciation from the local community. The Jordanian field hospital was mainly trauma oriented and located within a military zone, which hindered easy access for the general population. The Italian field hospital arrived to provide trauma care, but the hospital remained largely empty, its resources were not optimally used. This suggests that military field hospital deployment must be agile and adapted to medical needs and available capacities. and the EMT initiative emphasizes transparency. Still, non-reporting is known in previous studies. None of the I-EMT-2s in Beirut reported their activities to the WHO EMT CC. After several attempts by the EMT CC and months after the blast, two of the EMT-2s provided basic data on their activities. Data could not be verified nor validated, making interpretation difficult. The activities reported remained low compared to reported capacities. The EMT Specialized Care Teams adhered to EMT standards and attended weekly EMT CC meetings where they reported their non-clinical activities. For future EMT deployments, it is essential to ensure systematic reporting mechanisms and that this remains a EMT core standard.A significant lack of reporting made it difficult to perform an in-depth analysis of the I-EMT-2s activities in relation to medical needs. A minimum data set for EMT reporting is availableAs in previous studies, the I-EMT data available were limited, which made an in-depth analysis of the I-EMT activities impossible. Moreover, the quality of data was not possible to validate. Data were only presented that were made available to the EMT CC. The lack of self-reported data risks introducing selection bias. To balance this, WHO visited and met with staff as well as observed activities at all five I-EMT-2 facilities. The deployed international field hospitals are invited to share ideas on improving future I-EMT data sharing and responses.The international health care response to the Beirut blast was significant and mainly focused on trauma care, while the need for such care was limited when the five field hospitals (EMT-2s) arrived. A majority of the EMT-2s were military. The four other EMTs were adapted to support the existing health system; three of them were re-purposed to support COVID-19 care at public hospitals. Availability of data remains an obstacle to assess EMT activities and suggests improvements.