Do routinely collected hospital data accurately identify whether individuals presenting to emergency departments with gunshot wounds were shot as a result of an assault, an accident, an act of deliberate self-harm, or during legal intervention?In this cross-sectional study of 1227 patients, coding accuracy of firearm injury incidents at 3 level I US trauma centers was assessed using case-level data for 2008 to 2019. The results showed that 28% of all emergency department visits for assault-related firearm injuries were miscoded as firearm accidents in hospital discharge data.These findings suggest that the predominant misclassification problem with firearm injury intent in hospital discharge data is assaults miscoded as accidents, raising questions about studies that have used discharge data to study firearm injury by intent. This cross-sectional study uses case-level electronic health records for 2008 to 2019 from 3 level I US trauma centers to assess intent coding accuracy in hospital data used for firearm injury surveillance. The absence of reliable hospital discharge data regarding the intent of firearm injuries  has been characterized as a glaring gap in the US firearms data infrastructure.To use incident-level information to assess the accuracy of intent coding in hospital data used for firearm injury surveillance.This cross-sectional retrospective medical review study was conducted using case-level data from 3 level I US trauma centers (for 2008-2019) for patients presenting to the emergency department with an incident firearm injury of any severity.Classification of firearm injury intent.International Classification of Diseases, Ninth and Tenth Revision, Clinical Modification (ICD-9-CM and ICD-10-CM) codes for firearm injury intent assigned by medical records coders (in discharge data) and by trauma registrars. Accuracy was assessed using intent-specific sensitivity and positive predictive value (PPV).Researchers reviewed electronic health records for all firearm injuries and compared intent adjudicated by team members (the gold standard) with ICD-10-CM study period , the majority of patients (1090 [88.8%]) were male and 547 (44.6%) were White. The research team adjudicated 837 (68.2%) to be assaults. Of these assault incidents, 234 (28.0%) were ICD coded as unintentional injuries in hospital discharge data. These miscoded patient cases largely accounted for why discharge data had low sensitivity for assaults (66.3%) and low PPV for unintentional injuries (34.3%). Misclassification was substantial even for patient cases described explicitly as assaults in clinical notes (sensitivity of 74.3%), as well as in the ICD-9-CM study period . By contrast, intent coded by trauma registrars differed minimally from researcher-adjudicated intent .Of the 1227 cases of firearm injury incidents seen during the ICD-coded discharge data as a source of firearm injury intent. Based on our observations, researchers and policy makers should be aware that databases drawn from hospital discharge data  cannot be used to reliably count or characterize intent-specific firearm injuries.The findings of this cross-sectional study underscore questions raised by prior work using aggregate count data regarding the accuracy of  Trauma centers are required to maintain a registry of data collected by trauma registrars that, although not a population-based sample of ED visits, had been used to study intent-specific firearm injuries.12We also assessed how trauma registrars coded firearm injury intent. Trauma registrars are allied health professionals who focus exclusively on traumatic injuries and are explicitly charged with recording detailed information about the circumstances that led to the injury, including intent. By contrast, medical records coders are hired for billing purposes to review charts and code diagnoses, procedures, and a nonbillable “external cause of injury” STROBE) reporting guideline.This retrospective cross-sectional study was approved by the Massachusetts General Brigham (MGB) Research Ethics Board and the University of Washington Human Subjects Division, with waiver of informed consent from study participants owing to secondary use of EHR data. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology  codes were used . For October 1, 2015, and all time points afterward, International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes were used .We used data from 3 hospitals: Brigham and Women’s Hospital (BWH) and Massachusetts General Hospital, which belong to a single hospital system (MGB), for 2008 to 2019, and the University of Washington–managed Harborview Medical Center (HMC) for March 20, 2016, to January 31, 2018. Eligible incidents were those in which the medical records coder included a firearm-related e-code in any e-code or diagnosis field. For all records before September 30, 2015, Members of the research team (R.Y. and E.M. for MGB and A.B. for HMC) reviewed the medical record for each eligible patient case. For all incidents that, on review, met our case definition, reviewers assigned an injury intent using a detailed coding manual developed for the project , the wound location, and the activity of the person wounded at the time of the incident. Our coding manual drew on definitions and rules for coding intent from codebooks for the National Violent Death Reporting System,For 111 cases (9.0%), at least 2 study team members coded the same case via review of the medical record. Investigators chose differing intents in 6 cases (4.5%). Disagreements about the intent of an injury were resolved by the project team. For any cases in which the discrepancy was the result of ambiguity in guidance, the coding manual was changed to resolve the ambiguity, and all already-coded cases that might have been affected by the clarification were reviewed and updated. Researcher-adjudicated coding in our final data set reflected the rules specified in the final version of the codebook.Data extracted from the EHR  were linked by medical record number and admission date to trauma registry intent data . At BWH and HMC, the trauma registry included all ED-treated firearm injuries, regardless of severity or admission status. At MGB, cases coded by trauma registrars excluded firearm injury incidents in which the patient was treated in the ED and “released” . The EHR data were also linked to administrative data to retrieve patients’ self-reported (or informant-reported) demographics. Administrative data on self-reported race and ethnicity  were used to illustrate how the burden of intent-specific firearm injury differed depending on who assigned the intent .We calculated intent-specific sensitivity and positive predictive value (PPV) in discharge data and trauma registry data using researcher-adjudicated intent as the gold-standard intent for each patient case. We also assessed the free-text phrases extracted for each case to distinguish incidents in which the medical record contained explicit language indicating intent  from incidents where researcher-adjudicated intent was based only on circumstantial default criteria laid out in the coding manual .ICD-10-CM coded data . We also examined ICD-9-CM coded cases  to assess the extent to which misclassification patterns identified in ICD-10-CM data were present before the explicit change in official intent-related default guidance that accompanied the switch from ICD-9-CM  to ICD-10-CM .2Our primary analyses focused on ICD-10-CM period. Of these individuals, 1090 were male (88.8%) and 136 were female ; 854 (69.6%) were aged 18-39 years and 303 (24.7%) were aged 40 years or older  and the distribution of characteristics closely resembled that of the researcher-adjudicated assault cases.In this cross-sectional study, 1227 patient cases with firearm injury presented at 1 of 3 study sites during the or older . With reICD-coded discharge data, 581 (47.4%) of the 1227 cases were assaults and 432 (35.2%) were unintentional injuries, with less dramatic discrepancies between discharge data and researcher-adjudicated intent for the remaining intent-specific injury types.The research team observed that of the 1227 firearm injury incidents, 837 (68.2%) resulted from assaults, 168 (13.5%) were unintentionally inflicted injuries, 124 (9.9%) were acts of deliberate self-harm, and 43 (3.4%) were legal intervention incidents. For 55 patient cases, it was not possible to identify an intent (4.4%); record review identified credible conflicting information about intent for 19 (34.5%) of these cases . AccordiICD-9-CM data , misclassification of intent by medical coders was substantial . OverallIntent identified by trauma registrars, in contrast, seldom differed from intent assigned by the research team ; for exaICD-10-CM and ICD-9-CM coded discharge data, and among patient cases explicitly described in the medical record as having resulted from an altercation, suggesting a more longstanding and insidious problem than can be attributed to the change in ICD-10-CM injury intent default guidance alone. Nonetheless, firearm injury intent coding would likely improve, albeit to an indeterminate extent, if ICD-10-CM coding instructions defaulted to “assault,” the actuarially most probable intent, and not to “accident” as currently used, especially if coupled with incentives and coding interface modifications that made cases with unambiguous and explicit intent-related language more likely to be coded as noted.In this cross-sectional study of case-level firearm injuries at 3 level I trauma centers, injury intent determined by the research team differed minimally from intent determined by trauma registrars but differed substantially from the intent determined by medical records coders. These findings suggest that the predominant intent-related misclassification problem in discharge data was a tendency to code firearm injuries from assaults as unintentional firearm injuries. This tendency was apparent in ICD-coded intent in hospital discharge data. In that study of 122 pediatric patients presenting to a level I trauma center with a firearm injury, 16 of 28 cases ICD coded as an unintentional injury in hospital discharge data were classified by the research team as assaults.14Our findings are consistent with the only other study of which we are aware to compare researcher-adjudicated intent for firearm injuries to Our secondary finding that intent assigned by trauma registrars and by our research team differed minimally suggests that hospitals with trauma registrars already have a reliable source of intent-related information about firearm injuries, especially if registrars code all firearm injury incidents . This close correspondence also suggests that medical records coders, who are more experienced at coding than are research team members, would likely have little trouble characterizing firearm injury intent accurately if incentives were created for them to do so .ICD-coded discharge data as having suffered an unintentional firearm injury were nearly as likely to be arrested for violent crimes after hospitalization as were patients ICD coded as having suffered assault-related firearm injuries.15Several considerations should be borne in mind when interpreting the results of this cross-sectional study. First, there is no gold standard against which to compare researcher-adjudicated intent. Nevertheless, the close correspondence between intent assigned by the research team and by professional coders trained to record detailed information about traumatic injuries  provides a measure of external validity for our coding rules. Although it is possible that this close agreement resulted from shared coding biases and that other sources of bias are present in the medical records themselves, our finding that many assaults are misclassified as accidents helps explain why a prior study found that patients who were identified in ICD-coding problems in discharge data more generally, 2 observations suggest that this is plausible. First, the predominant misclassification problem we observed in our discharge data (that many assaults are miscoded as accidents) is the principal distortion others have argued pertains to national data. For example, in 2016, half of firearm injuries in discharge data from the Healthcare Cost and Utilization Project Nationwide Emergency Department Sample were ICD coded as unintentional firearm injuries and 43% were coded as assaults, whereas estimates based on more credible sources of intent found that less than 20% were unintentional injuries and more than 70% were assaults.4 Second, misclassification problems in our analyses restricted to ED treat-and-release cases were similar in kind and extent to those among admitted cases, suggesting that intent misclassification is largely independent of injury severity .Second, study data came from 3 hospitals located in urban settings, all of which were level I trauma centers and are thus not representative of US hospitals. Although we do not have individual-level data from other institutions to directly assess whether the error-producing processes we identified at our study sites underlie ICD coded as unintentional injuries in discharge data. One possible explanation is that three-quarters of these cases were coded by medical records coders who almost always ICD code such cases as assaults and one-quarter by coders who, for whatever reason and despite explicit evidence of assault in the narrative, coded these cases as unintentional injuries. It is also possible, although less plausible, that the same coder is accurate three-fourths of the time and defaults to unintentional one-fourth of the time. Future studies that elicit coder-level information about the coding process should try to determine how medical records coder practices foster the misclassifications we have described.Third, our study used case-level but not coder-level data. Thus, although we can document and quantify discrepancies at the patient-incident level, we can only speculate about any coder-level practices underlying these discrepancies. We are unable to determine, for example, why approximately one-quarter of firearm injury cases that were explicitly described as assault-related in the medical record were ICD-coded discharge data to describe aspects of intent-specific firearm injuries, such as how many have occurred, the demographic distribution of the people injured, and the medical costs they engender.25The findings of this cross-sectional study underscore questions raised by prior work about the accuracy of discharge data as a source of firearm injury intent, and by extension, the validity of findings from studies that have used


Food environments are viewed as the interface where individuals interact with the wider food system to procure and/or consume food. Institutional food environment characteristics have been associated with health outcomes including obesity and nutrition-related non-communicable diseases (NR-NCDs) in studies from high-income countries. The objectives of this study were (1) to map and characterise the food-outlets within a Ghanaian university campus; and (2) to assess the healthiness of the food outlets.Data collection was undertaken based on geospatial open-source technologies and the collaborative mapping platform OpenStreetMap using a systematic approach involving three phases: remote mapping, ground-truthing, and food-outlet survey. Spatial analyses were performed using Quantum Geographical Information System (QGIS) and comprised kernel density, buffer, and average nearest neighbour analyses to assess outlet distribution, density, and proximity. A classification system was developed to assess the healthiness of food-outlets within the University foodscape.p < 0.001) of student residence and those within 100 and 500 m from departmental buildings/lecture halls (at 5% level of significance).Food-outlets were unevenly distributed over the University foodscape, with many outlets clustered closer to student residencies. Informal food-outlets were the most frequent food-outlet type. Compared to NCD-healthy food-outlets, NCD-unhealthy food-outlets dominated the foodscape (50.7% vs 39.9%) with 9.4% being NCD-intermediate, suggesting a less-healthy university foodscape. More NCD-unhealthy food outlets than NCD-healthy food outlets clustered around student residences. This difference was statistically significant for food outlets within a 100-m buffer (Further action, including research to ascertain how the features of the University’s food environment have or are influencing students’ dietary behaviours are needed to inform interventions aimed at creating healthier foodscapes in the study University and other campuses and to lead the way towards the creation of healthy food environments at the home, work, and community levels.The online version contains supplementary material available at 10.1186/s12889-022-14266-7. Globally, obesity prevalence tripled between 1975 and 2016 . It has Emerging adults, 18 to 25-year olds, have been found to engage in nutritionally poor and less healthy food behaviours, and especially so in comparison with other age cohorts –8. This The university or school food environment has gained popularity as an important factor shaping young people’s eating habits in studies emanating from high-income countries (HICs) –17. The Nearly 10% of the population in sub-Saharan Africa (SSA) go through tertiary education institutions according to  based onTo identify and map the distribution of food-outlets within the University of Ghana campus.To ascertain the type of food-outlets that make up the University of Ghana food environment.To assess the healthiness of the various food-outlets distributed over the University of Ghana campus.The University of Ghana is the oldest and the largest public university in Ghana, located about 13 km north-east of Accra and with a land size of about 99.3 hectares, including a 23-hectare botanical garden. The University has three campuses, namely Legon (main campus), Korle-Bu and Accra City, which are suburban areas, comprising a total student population size of 39,249 including both undergraduate (85.4%) and graduate (14.6%) students. The majority (97.9%) of the population is Ghanaian, 1.5% of other African nationality and 0.6% of other nationality. The University’s Legon campus has 14 halls of residence  remote mapping (2), ground-truthing, and (3) food-outlet survey. The remote mapping phase included online mapping and online validation. There was an initial update of OpenStreetMap (OSM) based on freely available satellite imagery of the study area to create a vector basemap made up of footprints of building structures and routes. All building structures and routes within the boundary of the University campus were remotely mapped and validated online using the Humanitarian OSM Team’s (HOT) Tasking Manager (Tasking Manager is a web-based interface to coordinate mapping task and edit OSM using map editors such as iD editor) to create a basemap which guided ground-truthing or block-by-block observation –38.The ground-truthing activity involves field verification of building structures and routes mapped during the online remote mapping and validation. All data were obtained through ground-truthing survey and direct observation by the first author, and two research assistants recruited for this study, in collaboration with up to 20 well-trained University of Ghana (UG) YouthMapper volunteers stationed at six different clusters of the University campus . Atlases of the verified basemap were generated and printed using a web-based interface (Fieldpapers.org) for generating A4 field paper maps . FieldPaper sheets (FPS) were used to guide the ground-truthing survey and to directly observe and verify the location and typology of all structures in the study area, with particular interest in residential structures and food outlets. Data were recorded using a questionnaire instrument developed using open source software namely OpenDataKit (ODK)  and OpenVolunteers were trained to follow a standard protocol as follows. First, the shape on the FPS representing the building structure was traced out in pencil. Where there was a new structure, a representative shape was drawn on the FPS. Structures were assigned serial numbers starting with 1 (as a three-digit number—001) for the first structure visited using a naming convention  instruments for restaurants  and storA food outlet classification system was developed given the non-existence of a standard food outlet classification regime for the study country. This was based on the literature , 43, 44 the level of processing of the food options on offer ;whether or not the food options on offer are known risk factors for obesity, hypertension, other cardiovascular or NCDs –48; andwhether or not the food options are known to offer protection against NCDs  –48.As the NEMS concept (employed in the development of the food-outlet survey instrument) enables the capturing of both healthy and unhealthy food options available at eating venues, food outlets were also categorised as either NCD-healthy, NCD-intermediate, or NCD-unhealthy based on:The NCD-unhealthy food outlets category encompassed those that sold no fruit and/or vegetable choices, they offered only ultra-processed foods (UPFs), high-fat, and energy-dense choices that encourage excess calorie intake. NCD-healthy food outlets included outlets that had the highest proportion of food options being FV, other plant-based food options, and low-fat food choices or food option that have been associated with healthy eating , 48. TheGeocoding and a food retail environment spatial distribution analysis were undertaken using Quantum Geographical Information System (QGIS) Desktop software version 3.10.0 with Geographic Resources Analysis Support System (GRASS) software version 7.6.1 and Microsoft Excel Spreadsheet. The density of the various outlets per kilometer square over the University foodscape was assessed. In a nearest-neighbor analysis, the distance between two outlets of the same type was determined. Distance to nearest hub (points) analysis was applied to determine the distance between food outlets and classrooms, and between outlets and students’ residences. Two-sample t-tests were ran in MS Excel Spreadsheet to compare the differences between NCD-healthy and NCD-unhealthy food outlets in terms of their proximity to student residencies. The same statistical analysis was ran to compare the proximity of NCD-health outlets and that of NCD-unhealthy food outlets to departmental buildings/lecture halls.After in-person block-by-block mapping of structures within the within the University boundary, five hundred and fifty-eight (558) structures were identified and mapped. The structures comprised food outlets 138, 24.7%), student hostels/halls , lecture halls/other departmental buildings  , staff accommodation , libraries and bookshops based on the focus of this study. Figure 38, 24.7%banku/kenkey with grounded pepper or vegetable sauces (sold separately), banku/fufu with soup, and beans with gari/fried plantain (red-red). Together with other food service places (standard sit-down and take-out restaurants), they made up over 35% of food-outlets, suggesting a high prevalence of eating-out among students. Convenience stores had the third highest proportion (11.6%) of food-outlets. In addition to other everyday items, the convenience stores stocked mainly water, soft drinks, biscuits, packaged snacks and other confectionery, and instant noodles. Each hall/hostel of residence had a convenience store inhouse. Interestingly, fruit store (Fruit stores + Fruit juice stand + Organic food shop together) ranked eighth, representing 3.62% of food-outlets. Food-outlets that fell under the Supermarket category were not full-service supermarkets and offered ultra-processed/packaged foods and drinks only, with no fresh food products. Figure Out of 138 food outlets 58% were food service places with 42% being food stores. About 27.5% of all food outlets were table-top operations offering mainly water, carbonated/sugar-sweetened drinks and biscuits; bread with omelets (fried egg); or instant noodles. A few table-top vendors sold fruit, roastgroundnuts and/or water, millet porridge and other cooked breakfast cereals (such as oats). This is followed by traditional/local sit-down restaurants serving prepared meals including mainly rice dishes with vegetable salad (sold separately), The distribution of food-outlets was somewhat uneven over the University campus and appeared to be concentrated around the halls/hostels of residence, especially towards the south. There was a limited number of food outlets towards the east where many departmental buildings or lecture halls were located Fig. . These aFood delivery service arrangements appeared to offer the opportunity to bridge the distance gap. The study identified four (4) main third-party delivery companies, including “Delivery on Point”, that operated through dispatch riders (on mopeds and motorbikes) stationed at major food-courts who took phone orders from students, procured the food (as requested by student) and delivered it to them. Through dispatch riders, students could buy food from any food outlet or vendor of choice inasmuch as they could afford the cost of delivery. Other food outlets had their own dispatch riders to deliver telephone orders to students. In addition to this, some standard sit-down and take-out/fastfood restaurants like the Basement Plus, Icy cup, Meluv’s Restaurant were listed on online food ordering and delivery platforms like Swyftlyfefood, Bolt food and Jumia food, which also enabled students to order food from outlets both within and outside the University foodscape.p < 0.001) but not for food outlets within 200- and 500-m buffer as shown in Table Food outlet assessment showed that there were more NCD-unhealthy 50.72%) than NCD-healthy food outlets by nearly 11 percentage points and 9.42% of food outlets being NCD-intermediate. Figure 0.72% thaRegarding distance between departments and food outlets, 46%, 64% and 94% of NCD-unhealthy food outlets were respectively within 100, 200, and 500 m buffer of departmental buildings/lecture halls Figs. A, B, C, This study used Geographic Information System (GIS) to characterise the foodscape in the University of Ghana campus. This is the only study to use GIS methods to characterise the features of the food environment within a Ghanaian university community context. The study identified a total of 138 food-outlets in the University foodscape, which were unevenly distributed. Table-top operations ranked the single-largest food-outlet type (27.53%), although all restaurant types , standard sit-down (16%) and take-out restaurants (15%)) put together constituted nearly half of all food-outlets identified. A little over 50% of food-outlets were NCD-unhealthy, about 10 percentage points more common than NCD-healthy food-outlet availability over the foodscape. More food-outlets were clustered around student residences with limited availability of food-outlets around departmental buildings and lecture halls. The kernel-density analysis confirmed that NCD-unhealthy food-outlets also clustered closer to student residences, creating/suggesting an unhealthy food environment. These results suggest that the University foodscape appears to be less healthy by making more unhealthy food options easily accessible (closer) to students.2 less BMI among a non-university adult population. It could be postulated from systematic review evidence [Food service places dominated the campus foodscape, making up about two-fifths of all outlets identified. This suggests a high eating-out among students in this campus. That is, the prevailing characteristics of the University foodscape may be a materialised reflection of students’ longstanding preferences. Qualitative research among UK and Bangladeshi students have suggested that academic demands on time (among students in this university ) and theevidence  that theThe study identified that food-outlets were not evenly spread over the university foodscape. This is consistent with qualitative findings from students in our study university  and a noAlthough the observed prevalence of informal food-outlets may not be expected in a highly regulated and ‘elite’ community like the study area, there may be cultural and normative underpinnings to this finding. It may encourage frequent ultra-processed food (UPF) consumption and lead to unhealthy dietary habit formation over time —includin2 [Another important finding from our analysis showed a higher proportion over 50%) of NCD-unhealthy food outlets than NCD-healthy food-outlets available within the University foodscape. These outlets including traditional sit-down and take-out restaurants, convenience stores and table-top vendors offered energy-dense meals, deep-fried (fatty) foods, SSBs and other UPFs, and operated for long hours. A similar pattern of distribution between healthy and unhealthy food-outlets have been reported in both high- and low-income countries (Bodor et al., 2010 ; Maimait0% of NCDMost studies characterising the food environment have focused on a limited selection of food-outlet types. This study included all food-outlet types available within the study area. Another strength of this study is the use of a robust classification instrument to categorise all available food-outlets as NCD-healthy, NCD-intermediate or NCD-unhealthy based on relevant research , 56, 87.Despite the strengths, this study had limitations. There was bad satellite imagery in sections of the study area during the online mapping and validation to create the study’s basemap. A few of the tasks on the University of Ghana campus HOT Tasking Manager appeared invisible because there was cloud cover obstruction. Those parts could not be digitised and some structures may have been missed at the online mapping stage. However, such structures would have been captured during structure verification/ground-truthing, highlighting the rationale for employing a systematic approach involving the combination of block-by-block observation, respondent reports, and a GPS in this study to capture the characteristics of the food environment.A second limitation could be the geographical inaccessibility encountered during the ground-truthing exercise. Access into some residential areas like the Vice Chancellor’s area and the University Guest Houses, were not allowed for security reasons. As this could mean some outlets missing from the maps, its impact on the study’s findings would be negligible, given that students were not allowed access into these areas.In close relation to the above, the study may not have captured all outlets within the university foodscape given that some food vendors were mobile. This includes vendors who ported FV, pastries, ice creams, and snacks on their heads; or carted ice cream, SSBs, and pastries on bicycles to various points of the foodscape. However, the mobile food vendors constituted a small proportion of food resources in the study community to make a significant difference to the findings reported here.Another limitation could be issues encountered during the upload of fieldpaper sheets to Fieldpaper.org after ground-truthing. Images of some updated fieldpaper sheets captured using the Samsung Galaxy S5 and Alcatel-3 V phone cameras could not be uploaded to Fieldpapers.org. Those parts of the map were therefore manually updated online with information captured on the fieldpapers during structure verification using the individual fieldpaper codes. This may have affected the accuracy of the point location for the structures entered manually. Although this was the case for an insignificant number of the structures identified and mapped, the findings of the study should be interpreted in the light of this and the foregoing limitations.Many food items become unhealthy when consumed beyond recommended levels. Thus some of the food items used as markers of healthiness may become risks to personal health if not consumed in the most appropriate and recommended manner . TherefoThis study set out to identify the features of a university food environment and to assess the healthiness of the food-outlets within the campus foodscape. The campus foodscape offers a variety of food resources but an imbalance in the distribution of the food-outlets was identified. However, there was a robust food delivery system with some food service places listed on online food ordering and delivery platforms. Nearly half of the food resources qualified as NCD-unhealthy food outlets which clustered around student halls/hostels of residence, suggesting a less healthy food university environment. Overall, our findings have important implications for further research and policy interventions towards identifying environmental risk factors associated with unhealthy food behaviours, overweight/obesity, NCDs, and other health outcomes among university students in Ghana during term-time. Another distinctive contribution of this study is the provision of evidence on how remotely mapped data in a collaborative mapping approach can be combined with direct observation and other survey methods to produce data that provides useful insights into relationships between people and location characteristics. This would provide methodological guidance to other investigators, particularly, under-resourced researchers.Additional file 1. Appendix 1.Typology of food-outlets identified in the University foodscape.


We report two cases of ectopic bone formation in the head and neck following treatment with recombinant human bone morphogenetic protein-2 (rhBMP-2). Surgical pathologic data, laryngoscopy imaging, CT imaging, and patient medical history were obtained. First, we report osseous metaplasia in the vocal fold in a 67-year-old male following mandibular dental implants with rhBMP-2; second, a case of severe bony overgrowth of the larynx and fusion to the anterior cervical spine (ACS) in a 73-year-old male following multiple anterior cervical discectomies and fusions with rhBMP-2. Ectopic bone formation following rhBMP-2 has been previously reported. Adverse events like local swelling and edema leading to dysphagia and even airway obstruction after cervical spine application of rhBMP-2 have also been widely reported. Due to the uncommon nature of abnormal bony growth in soft tissue areas of the head and neck and the previously documented adverse effects of rhBMP-2 use, especially in the cervical spine, we consider the two unusual case presentations of ectopic bony formation highly likely to be linked with rhBMP-2. We urge awareness of the adverse effects caused by rhBMP-2, and urge caution in dosing. It is also currently approved for tibial nonunion and maxillary sinus augmentation ,2. WhileIn this report, we introduce two unusual late complications after rhBMP-2 application in the head and neck, both involving laryngeal ectopic bone formation or osseous metaplasia. We also review existing literature regarding adverse events after therapeutic rhBMP-2 application.2.The institutional review board considered this retrospective study exempt from review. Patient medical history and clinical data were obtained for both cases through review of the medical records. The patients were both treated by the authors for their laryngological complaints. For case 1, medical history, laryngoscopy images, and surgical pathologic data were obtained. For case 2, medical history and CT scan images were obtained. Operative information was recorded from the surgeon’s operation notes. Expert reads from the clinical pathologist and radiologist were obtained from patient charts. Both patients’ course of treatment and pertinent surgeries were traced and followed to the present time.3.3.1.3.1.1.2 laser was used in conjunction with microlaryngeal instruments to remove the vocal fold lesion. The excised tissue was sent for standard pathologic examination  procedures with rhBMP-2. This group had significant complications associated with cervical inflammation and soft tissue edema causing higher rates of tracheotomies, unplanned post-surgical intubations, dysphagia or dyspnea, and respiratory failure relative to a control group who underwent the same procedure without rhBMP-2 . ZadeganHeterotopic or ectopic bone formation, which can cause spinal compression and unintended fusions, has also been associated with rhBMP-2. In the spine, this is likely caused by leakage of rhBMP-2 from the implant site, with increased risk if the implant is close to the dura mater ,21. In 2Adverse events of rhBMP-2 application may be related to their dosing, which lacks consensus and varies by application type and site. Given their short half-lives, BMPs must be present in high enough doses for effective osteoinduction . HoweverAdverse effects of rhBMP-2 use may be explained at the cellular level, where BMP-2 has been shown to induce inflammatory cytokines, activate osteoclasts, and induce adipogenesis and bone cyst formation ,31. BrieBMP-2 also acts as both a tumor suppressor and oncogenic factor, and endogenous BMP has been shown to be increased in cancers and metaplastic bone formation . Previou5.Based on the two cases presented, and previous evidence of complications reported in the literature, we remind clinicians that rhBMP-2 therapies pose a risk for ectopic bone formation especially in the cervical spine and head and neck region. Additional adverse events like dysphagia, wound complications, and severe edema that can lead to respiratory obstruction are widely reported in the literature. Clinicians should be mindful of the potential for difficult airway management during general anesthesia after rhBMP-2 administration. Patients treated with rhBMP-2 should be closely monitored for complications, and dosing should be carefully considered.


In the West, recent decades have demonstrated an epidemiological trend towards esophago-gastric adenocarcinomas (EGAC), with considerable associated mortality. Historically, chemotherapy has represented the sole systemic treatment option in the advanced EGAC setting, in addition to complementing the role of surgery and radiotherapy in the case of localized disease. Immune checkpoint inhibitors (ICIs) represent a novel systemic therapeutic choice and have revolutionized the management of other malignancies, including melanoma and renal cell carcinomas. This article considers the rationale for ICIs in EGAC, reviews the evidence supporting their role in the current standard of care in EGAC, and briefly considers ongoing trials and future directions for the ICI class in EGAC. Adenocarcinoma of the esophago-gastric junction and lower esophagus, together with gastric adenocarcinoma, contribute significantly to cancer-related mortality and account for approximately one million deaths worldwide each year . There aThe immune system plays an under-appreciated role in the progression and evolution of cancer as well as being an important variable in how cancers respond to treatment (or not) ,5. The in = 794 patients) that investigated the impact of adjuvant nivolumab, an anti-PD-1 monoclonal antibody, in patients with gastro-esophageal cancer [As shown in l cancer . All patl cancer .A number of studies looking at immunotherapy in the perioperative setting for gastric/GEJ cancers are currently underway. Interim results from DANTE were presented at the American Society of Clinical Oncology (ASCO) 2022 meeting . A phasen = 240) randomized phase 2 study, and unlike Checkmate-577 includes only patients with EGAC histology who are high risk with an R1 resection  or positive lymph nodes post neoadjuvant chemotherapy, as per European and North American standard of care guidelines, followed by surgery. Patients will either receive the chemotherapy they had pre-operatively or the ICI combination  [A number of other studies in the peri-operative setting have not yet reported. EORTC VESTIGE, like CHECKMATE-577, evaluates post-operative ICI—in this case ipilimumab (an anti-CTLA-4 antibody) and nivolumab—in patients who did not have a pathological complete response following pre-operative treatment. It is a relatively large ( 1 year) .KEYNOTE-585 is a somewhat more traditionally designed phase III study of patients with previously untreated, localized, resectable gastric/GEJ adenocarcinoma in whom perioperative chemotherapy is indicated. The study randomizes patients to receive pembrolizumab or placebo in combination with chemotherapy . Some haFinally, the role of immunotherapy has been firmly established in the advanced/metastatic setting in tumors that are microsatellite instability-high or mismatch repair deficient (MSI-H/dMMR). In 2017, the FDA granted its first tissue-agnostic approval for the use of pembrolizumab in the presence MSI-H/dMMR. Operable MSI-H gastric cancer has been identified as being less chemotherapy-sensitive, and so the use of neoadjuvant IO strategies to improve tumor downstaging is a rational choice requiring investigation. The NEONIPIGA Phase II study was recently reported, and in this trial the use of neoadjuvant ipilimumab (1 mg/kg every 6 weeks) with nivolumab 240 mg every 2 weeks for two cycles, followed by surgery then nivolumab 480 mg every four weeks for 9 cycles [The first clinical trials suggesting efficacy for ICI in EGAC were for monotherapy in the advanced disease setting . Pembroln = 160 patients with advanced esophago-gastric cancer [Combined CTLA-4 and PD-1 blockade has a strong immunological rationale ,41 in adc cancer . The addc cancer . Anotherc cancer .p = 0.0560). Pembrolizumab did improve overall survival in patients with a CPS ≥ 10, with a median OS of 9.3 months in the pembrolizumab arm in comparison with 6.7 months in the chemotherapy arm ; p = 0.0074). Histopathological stratification also demonstrated improved median OS to 8.2 months in esophageal squamous cell carcinoma (ESCC), in comparison with the adenocarcinoma population; however, the study did not meet the coprimary end point. A caveat of interpreting these results is that the authors flag that the study was insufficiently powered to statistically analyze significant differences between patients with a PD-L1 ≥ 10 in either SCC or adenocarcinoma. These early studies were the first to indicate the importance of PD-L1 as a marker of efficacy in esophagogastric cancers, and that PD-L1 CPS was a better scoring system to use in adenocarcinoma histologies, whereas the tumor proportion score (TPS) was satisfactory for squamous carcinomas.KEYNOTE-181 evaluated pembrolizumab in a slightly earlier disease setting in patients who had received one previous line of chemotherapy . PatientPrompted by the success of utilising single agent ICI in later line settings in KEYNOTE 181, in addition to benefits noted in other tumour types combining the ICI class with systemic chemotherapy, KEYNOTE 590 was undertaken. It was a randomised study in patients who had untreated advanced esophageal cancer and received either pembrolizumab with chemotherapy or chemotherapy alone . The chen = 1581 patients were randomized, with approximately 60% having tumors expressing PD-L1 with CPS ≥ 5. Most (76%) patients were non-Asian and most (70%) had gastric cancer. The primary endpoints were OS and PFS in patients with PD-L1 CPS ≥ 5. Once the primary endpoints were met in this enriched population, it was possible to evaluate the secondary endpoints of OS in patients with PD-L1 ≥ 1 and in all randomized patients. The response rate in the CPS PD-L1 ≥ 5 population were higher in those patients who received nivolumab . This translated into a median increase in PFS of 1.7 months and increase in OS of 3.3 months. As a result of these data, the US FDA approved Nivolumab in all comers, but giving category 1 evidence to those with gastro-esophageal adenocarcinoma with PD-L1 CPS ≥ 5 in comparison to category 2B evidence for those with PD-L1 CPS ≥ 1. In comparison, the EMA has only afforded regulatory approval in patients with CPS ≥ 5. At the European Society for Medical Oncology (ESMO) Congress in 2021, the Checkmate-649 data were updated to include the ipilimumab and nivolumab arm [CHECKMATE-649 and ATTRACTION 4 both evaluated the combination of Nivolumab and chemotherapy for untreated metastatic esophagogastric adenocarcinoma ,28. CHECumab arm . Whilst p = 0.0007). In the final analysis, median overall survival in the nivolumab with chemotherapy arm was 17.45 months vs. 17.15 months in the placebo plus chemotherapy group . At face value, overall survival data was negative with similar survival curve in both arms. However, two thirds of those enrolled in ATTRACTION-4 went on to receive further chemotherapy, with 27% in the chemotherapy arm receiving later immune checkpoint inhibitor therapy. This raises the possibility that later lines of therapy may have influenced overall survival data.ATTRACTION-4 was of a similar design to CHECKMATE 649, except it was primarily (or exclusively) in Asian patients and did not limit enrolment or assessment relative to PDL1 CPS . PatientOrient-16 evaluated sintilimab, a fully human IgG4 monoclonal antibody targeting PD-1, in combination with oxaliplatin-based chemotherapy in the first-line treatment of gastric or junctional tumours . There wn = 37) in which pembrolizumab was added to the combination of trastuzumab and chemotherapy in patients with untreated metastatic HER2-positive EGAC [Up to 30% of esophago-gastric adenocarcinomas have ERBB-2 (or HER2) oncogenic amplifications, which have been successfully clinically targeted with a combination of systemic chemotherapy and anti-HER2 therapy in the form of trastuzumab for almost a decade, as demonstrated by the ToGA trial. Preclinical and clinical data had demonstrated that trastuzumab increases HER2 internalization and cross presentation by dendritic cells which ultimately stimulates HER2 specific T cell responses. Trastuzumab had also been shown to have significant effects on the immune microenvironment by upregulating PD-1 and PD-L1 expression, inducing TIL expression and modulating MHC class II expression. Therefore, combining an ICI with trastuzumab and chemotherapy in a HER2 positive population of patients was an intriguing prospect. The initial study was a small single arm, phase II study , T-cell immunoglobulin and mucin containing-domain-3 (TIM-3) and T-cell immunoreceptor with immunoglobulin and immunoreceptor with tyrosine-based inhibitory motif domains (TIGIT) inhibitors. It is unclear, as yet, which of these compounds, if any, will find a niche. Anti-LAG-3 antibodies, such as relatimab , and antThe ICI drug class has dramatically altered the outlook and treatment paradigm of many cancers over the past decade. In the past two years, ICIs have demonstrated efficacy in EGAC and are now an integral part of the standard treatment paradigm for both operable and inoperable disease. There are, however, many questions, and the coming years will hopefully see a refinement of the approach. The role of PDL1 needs to be clarified or combined with other biomarkers to improve its predictive value. New techniques, such as circulating DNA in the post operative period, need to be married with evolving treatments to improve patient selection and maximize benefit. Newer immune modalities, either novel (or novelly combined) ICIs, cell-based approaches such as CAR-T, or tumor-infiltrating lymphocyte (TIL) therapies, offer hope of a radically different approach. The clinical studies summarized in this article have certainly established a role for ICI agents in this disease, and set a marker to be surpassed. Whilst newer drugs and strategies may achieve this independently, it is likely that the treatments will need to be integrated rather than supplanted. ICIs also present a new toxicity profile, that in combination with existing modalities demonstrate a not unexpected increase in adverse events. This is important to acknowledge moving forward, given it is unlikely that the standard of care chemotherapy and radiation dose and schedules we are currently using are optimal for anti-tumor immune effects. We can undoubtedly do a better job of incorporating immune-based approaches into the standard of care. This is especially challenging in the perioperative or first line metastatic setting. At the least, recent trials have shown that immune-based approaches have a role. We will, in time, discover how central this role is, and learn how to better select those most likely to derive benefit.


There is a male sex disadvantage in morbidity and mortality due to COVID-19. Proposed explanations to this disparity include gender-related health behaviors, differential distribution of comorbidities and biological sex differences. In this study, we investigated the association between sex and risk of severe COVID-19 while adjusting for comorbidities, socioeconomic factors, as well as unmeasured factors shared by cohabitants which are often left unadjusted. We conducted a total-population-based cohort study  based on individual-level register data. Cox models was used to estimate the associations between sex and risk for severe COVID-19. We additionally used a within-household design and conditional Cox models aiming to account for unmeasured factors shared by cohabitants. A secondary aim was to compare the risk of COVID-19 related secondary outcomes between men and women hospitalized due to COVID-19 using logistic regression. Men were at higher risk for hospitalization , ICU admission  and death  due to COVID-19, based on fully adjusted models. However, the effect of sex varied significantly across age groups: Among people in their 50s, men had > four times higher risk of COVID-19 death. The within-household design did not provide any further explanation to the sex disparity. Among patients hospitalized due to COVID-19, men had an increased risk for viral pneumonia, acute respiratory distress syndrome, acute respiratory insufficiency, acute kidney injury, and sepsis which persisted in fully adjusted models. Recognition of the combined effect of sex and age on COVID-19 outcomes has implications for policy strategies to reduce the adverse effects of the disease.The online version contains supplementary material available at 10.1007/s10654-022-00919-9. Since the outbreak of Coronavirus disease 2019 (COVID-19) caused by the virus SARS-CoV-2 detected in November 2019 and declared a pandemic by the World Health Organization in March 2020, a growing body of evidence reveals male sex as an important risk factor for severe COVID-19 outcomes. Globally, men are overrepresented among hospitalizations, intensive care unit (ICU) admissions and deaths due to COVID-19, despite similar infection rates between sexes. However,Apart from old age and male sex, comorbidities, including widespread cardiovascular and endocrine diseases, are known risk factors for severe COVID-19. As the pNumerous studies have indicated that male sex is a significant risk factor for severe COVID-19. Many studies are based on large, aggregated data with limited ability to adjust for important confounders, whereas other studies are smaller, hospital-based, and often suffer from selection bias and limited generalizability. Therefore, the main aim of this large population-based cohort study was to examine the sex disparity in the risk of hospitalization, ICU admission and death due to COVID-19 by utilizing the ability to link several health and administrative registers containing individual-level data on COVID-19 outcomes, as well as important comorbidities and socioeconomic factors. To analyze the sex disparity in severe COVID-19 outcomes further, we additionally used a within-household design in a subpopulation of the cohort aiming to adjust for unobserved factors shared by individuals living in the same household. This includes housing-related living conditions such as many social, economic and lifestyle related factors which are often shared by cohabitants to a large extent but are often left unadjusted despite being a potential source of omitted variable bias. The within-household design also partly accounts for SARS-CoV-2 exposure since much of the virus transmission occurs within households. A secondary aim of this study was to compare the risk of severe secondary outcomes related to COVID-19 between men and women hospitalized due to COVID-19.We conducted a population-based prospective cohort study to examine the association between sex and risk for severe outcomes in COVID-19 defined as hospitalization, ICU admission or death due to COVID-19. The eligible study population was defined as all individuals aged 18 and older who were living in the region of greater Stockholm, Sweden, on March 1, 2020 . The region of greater Stockholm represents more than one fifth of the entire population in Sweden. Five individuals with missing information on date of death were excluded resulting in a final study population of 1,854,661 individuals.Through the unique personal identity number assigned to all Swedish citizens and residents intending to stay at least one year in Sweden, we were We further analyzed a cohabitation cohort to compare the risk of severe COVID-19 outcomes between men and women living within the same household. This comparison controlled for unknown and unmeasured factors shared among individuals living in the same household that might confound the association between sex and risk of severe COVID-19. Individuals living together evidently share the same housing-related living conditions, as well as many other social, economic and lifestyle related factors to a large extent. Further, since much of the transmission of SARS-CoV-2 occur within households, individuals living together have a similar risk of SARS-CoV-2 exposure. To create our cohabiting cohort, we started with the 1,854,661 individuals included in the population-based cohort and proceeded to exclude 4,173 individuals (< 1%) with missing information on household-id, and 564,842 individuals (30%) who were not living together with another adult person of the opposite sex. Among the 1,285,646 individuals that remained, we only included the oldest opposite-sexed pair of individuals living within the same household, with a maximum age difference of 5 years. In this step, 526,714 individuals (28%) were excluded, which resulted in a cohabiting cohort consisting of 758,932 individuals.We considered three main COVID-19 related outcomes in this study: hospitalization, ICU admission and death due to COVID-19.We derived information on hospitalizations due to COVID-19 from the Stockholm Regional Healthcare Data Warehouse  which provides information on all admissions to hospital as well as all healthcare visits in primary and secondary care . Each recAdmissions to ICU were identified from the Swedish Intensive Care Registry (SIR), a national quality register for intensive care in Sweden including all ICUs in the region of greater Stockholm., 24 We dData on deaths due to COVID-19 was retrieved from the cause of death register (CDR) held by the Swedish National Board of Health and Welfare. The CDR has nationwide coverage and contains information from death records including the underlying and contributory causes of death coded according to the ICD. We definTo assess the robustness of our results, we also used a more inclusive definition of COVID-19 related hospitalizations. This definition held that COVID-19 could be registered as either a primary or a secondary diagnosis. We also performed a similar robustness check regarding COVID-19 related deaths, using a more restrictive definition that held that COVID-19 had to be an underlying cause of death.Several comorbid conditions or history of diseases are associated with an increased risk for severe COVID-19 outcomes. Thus, we attained information on disease history, including possible comorbidities, for all study participants by searching recorded diagnoses in the VAL-database for the following diseases with ICD codes within parentheses; essential hypertension (I10.9), ischemic heart diseases (I20-25), heart failure (I50), stroke (I60-63), chronic obstructive pulmonary disease (COPD) (J44), asthma (J45), type 2 diabetes (E11), obesity (E66), chronic kidney disease (N18), chronic liver disease (K70), and cancer (C00-C97). We described those having an aforementioned disease recorded as a primary or secondary diagnosis on at least one consultation in primary or secondary care or during hospitalization from five years prior study entry until end of study period as having a comorbidity. For cases identified with COVID-19, only diagnoses recorded before the first COVID-19 diagnosis were considered.We derived data on educational attainment and disposable household income from the Longitudinal integrated database for health insurance and labor market studies (LISA) maintained by Statistics Sweden. Highest A second aim of this study was to compare outcomes in terms of diagnoses associated with severe illness due to COVID-19 between men and women hospitalized with COVID-19 as a main diagnosis. The following diagnoses were considered with ICD-10 codes within parentheses: viral pneumonia , acute respiratory distress syndrome (ARDS) (J80.9), acute respiratory insufficiency (J96.0), acute kidney injury (N17), acute hepatic injury , acute cardiac injury (I21), sepsis (R65.1), septic shock , pulmonary embolism (I26), cerebral infarct (I63), embolism and thrombosis . To be defined as a clinical outcome of COVID-19, the diagnosis had to be diagnosed during a hospital episode with COVID-19 as the main diagnosis. Cases with sequential admissions with a readmission within one day of the previous discharge were considered as one hospital episode to account for transfer of patients within and between hospitals.We used Cox proportional hazard regression models to estimate hazard ratios (HRs) with 95% confidence internals (CIs) for the risk of severe outcomes in COVID-19 associated with sex, using time after the start of follow-up in days as the underlying time scale. We adjusted all models for age using restricted cubic splines with 5 knots and then sequentially added other potential confounders including comorbidities and socioeconomic factors. We also tested for interactions between age and sex on COVID-19 outcomes and estimated separate HRs for men compared to women for different age groups . The proportional hazards assumption was assessed graphically using log–log plots and tested based on Schoenfeld residuals. To further examine whether the effect of sex varied during follow-up, we split the follow-up time between the first and second wave of the pandemic  and included an interaction term between sex and time-period in our models.We repeated the main analyses in the cohabitation cohort, using a standard Cox proportional hazards model, with partially and fully adjusted models as described above. To account for unobserved characteristics shared by men and women living in the same household, we performed corresponding analyses using conditional Cox models, stratified by household id. This approach allows each pair of cohabitants to have an individual baseline hazard function, while at the same time allowing it to vary between pairs. An attenuation of an estimate suggests that household-related factors contribute to the association, while the persistence of an estimate suggests that the association between sex and risk for severe COVID-19 is independent from factors shared within households.We used multivariate logistic regression to explore if outcomes, in terms of diagnoses associated with severe COVID-19, differed between men and women hospitalized due to COVID-19. All tests were 2-sided and p < 0.05 was considered statistically significant. All analyses were conducted using Stata Statistical Software: Release 14 .The study population consisted of 1,854,661 individuals, representing the whole adult population of Stockholm County, who were followed for hospitalizations and ICU admissions due to COVID-19 between March 1, 2020 and May 16, 2021 with an average follow-up time of 432 days. During 2,192,925 person-years under observation, 16,475 hospitalizations and 1,974 ICU admissions occurred. The study cohort was also followed for deaths due to COVID-19 between March 1, 2020 and December 31, 2021, with an average follow up time of 302 days amounting to a total of 1,531,833 person-years under observation. During this period 3,281 deaths due to COVID-19 occurred. Table In Table Generally, we found no evidence that sex in models with hospitalizations and deaths related to covid-19 violated the proportional hazards assumption. However, in models with covid-19 related ICU admissions as the outcome, sex seemed to violate the proportional hazards assumption. This was addressed in sensitivity models including an interaction term between sex and time-period. Expectedly, there were no statistically significant interactions between sex and time-period  for covid-19 related hospitalizations and deaths, and the HRs for sex were essentially the same during the two time-periods. For covid-19 related ICU admissions, the effect of male sex was slightly lower during the second wave  compared to the first wave . To assess the robustness of our results, we estimated all our models using a more inclusive definition of COVID-19 related hospitalizations. Reassuringly, our results using this definition of COVID-19 related hospitalization were similar with one exception; women at reproductive age (18–40 years) had an increased risk for hospitalization related to COVID-19 compared to men of the same age (S1 Table). However, this was solely explained by pregnant women receiving pregnancy and delivery-related health care as the main diagnosis and COVID-19 registered as a secondary diagnosis, which means that the difference in the results likely reflects intensive testing and reporting among this otherwise generally healthy female population. We also In Table In Table In this large population-based study, we have observed a substantial male sex disadvantage in severe morbidity and mortality due to COVID-19. In general, men’s excess risk was most pronounced among middle aged people (50–59 years), in particular for the risk of COVID-19 related death. Adjusting for several important comorbidities and socioeconomic factors did not attenuate the observed associations. Further, adjusting for unobserved factors shared by individuals in the same household in a conditional Cox analysis did not provide any further explanation to the sex disparity in severe COVID-19 outcomes. In addition, among patients hospitalized due to COVID-19, men had an increased risk for complications associated with COVID-19 such as viral pneumonia, acute respiratory distress syndrome, acute respiratory insufficiency, acute kidney injury, and sepsis.Our finding that men are at higher risk of severe COVID-19 infection and death compared to women, and that the increased relative risk varies across age-groups is consistent with previous studies., 19 The Gender-related differences in occupations, health-behaviors and attitudes have also been suggested to partly explain men’s increased risk for COVID-19 outcomes. However,The observed sex disparity in COVID-19 outcomes could be a consequence of several biological sex differences, such as sex steroid hormone levels, sex chromosomes, differential genetic expression, and differences in the immune function, whereof some may interact with age. Sex sterTLR7 have been identified in young men with severe or fatal outcomes in COVID-19, without any known predisposing risk factors.[TLR7 variants in men with unexplained severe COVID-19, whereas none were identified among the mildly or asymptomatically infected men.[ACE2 gene is also coded on the X-chromosome and has been found to be regulated by estrogens.[ACE2 expression and regulation may in part explain differences in COVID-19 outcomes.[Women may also benefit from having two X-chromosomes that encode a large number of immune-related genes., 42 As c factors., 48 A sucted men. Angiotenstrogens.ACE2 has outcomes., 52.Severe COVID-19 is associated with a state of dysregulated immune responses associated with excessive production of inflammatory cytokines and chemokines, inflammatory cell infiltration in the lungs, a so-called cytokine storm, causing lung injury and respiratory distress, together with lymphopenia. Deaths due to COVID-19 usually result from acute respiratory distress syndrome, acute respiratory failure, coagulopathy, organ failure and septic shock. We foundA major strength of this study is the total population-based setting with complete coverage of COVID-19 related hospitalizations and deaths, why this study is not subjected to selection bias. Another important strength is the use of administrative register data on socioeconomic factors. For example, these included information on housing arrangements that enabled the novel use of within-household comparisons to address unknown and unmeasured confounders shared by cohabitants in the study of sex disparities in severe COVID-19 outcomes. Further, the unique Stockholm Regional Healthcare Data Warehouse, which contains information on hospitalizations as well as data from primary and secondary care, improved our capability to identify individuals with important comorbidities, compared to using only hospital-based data.There are also limitations to consider. This is an observational study, and as such we cannot determine the causal relationships that underlies the male sex disadvantage in morbidity and mortality due to COVID-19. This study could have been subjected to surveillance bias as men generally receive more specialist inpatient care, which could increase the chance of being detected with COVID-19 in health registers. To minimize this issue, we defined COVID-19 hospitalizations based on main diagnosis only. The accuracy of COVID-19 diagnoses in Swedish health and cause of death registers is presumably high but have not been formally validated. Sensitivity of hospital diagnoses as a measure of severe COVID-19 morbidity among older patients may be an issue since age discrimination in access to care has occurred. AlthoughOur results confirm that men have an excess risk of hospitalization, ICU admission and death due to COVID-19. This sex disparity varies across age groups and is most pronounced among middle aged men compared to women of the same age. Further, among hospitalized COVID-19 patients, men are more likely to be diagnosed with COVID-19 related complications. Different explanations have been suggested to explain men’s vulnerability to COVID-19, including gender related health behaviors, differential distribution of comorbidities and biological sex differences such as sex steroid hormones, genetic constitution, or differential gene expression. The reason for men’s excessive risk is likely multifactorial with a complex interplay between several factors. In this study we adjusted for multiple confounders, including important comorbidities, socioeconomic factors as well as unmeasured household-related factors. These adjustments had no substantial impact on men’s excess risk of severe COVID-19 outcomes. Thus, our results motivate a focus in future studies on biological mechanisms that influence the immune response towards SARS-CoV-2 to help explain women’s advantage in COVID-19. This study also highlights the importance to consider the combined effect of age and sex when defining those at highest risk of severe COVID-19 outcomes.Below is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2


Optimizing specimen collection methods to achieve the most reliable SARS-CoV-2 detection for a given diagnostic sensitivity would improve testing and minimize COVID-19 outbreaks. From September 2020 to April 2021, we performed a household-transmission study in which participants self-collected specimens every morning and evening throughout acute SARS-CoV-2 infection. Seventy mildly symptomatic participants collected saliva, and of those, 29 also collected nasal swab specimens. Viral load was quantified in 1,194 saliva and 661 nasal swab specimens using a high-analytical-sensitivity reverse transcription-quantitative PCR (RT-qPCR) assay. Viral loads in both saliva and nasal swab specimens were significantly higher in morning-collected specimens than in evening-collected specimens after symptom onset. This aspect of the biology of SARS-CoV-2 infection has implications for diagnostic testing. We infer that morning collection would have resulted in significantly improved detection and that this advantage would be most pronounced for tests with low to moderate analytical sensitivity. Collecting specimens for COVID-19 testing in the morning offers a simple and low-cost improvement to clinical diagnostic sensitivity of low- to moderate-analytical-sensitivity tests.IMPORTANCE Our findings suggest that collecting saliva and nasal swab specimens in the morning immediately after waking yields higher SARS-CoV-2 viral loads than collection later in the day. The higher viral loads from morning specimen collection are predicted to significantly improve detection of SARS-CoV-2 in symptomatic individuals, particularly when using moderate- to low-analytical-sensitivity COVID-19 diagnostic tests, such as rapid antigen tests. Although vaccination has substantially reduced hospitalizations and death from COVID-19, limited vaccine uptake and availability and the potential for breakthrough infections  support the continued necessity for diagnostic testing and subsequent isolation of infected individuals . OptimizNasopharyngeal swab, anterior nares swab, midturbinate swab, oropharyngeal swab, buccal swab, gingival crevicular fluid, sputum, tracheal aspirate, and saliva have all been utilized and compared as diagnostic specimens for the detection of SARS-CoV-2 infection. Work done by many groups –5, inclu–7 copies/mL) (4 to 105 copies/mL of specimen) or low analytical sensitivity (LOD of 105 to 108 copies/mL of specimen) are being increasingly used, particularly for at-home and rapid screening testing and in areas of the world with limited laboratory capacity  . Tests wcapacity –16.How specimens are collected can also affect the detectability of SARS-CoV-2 in a specimen. Because SARS-CoV-2, like other pathogens, may exhibit circadian rhythms to replication kinetics , 18, we We conducted a COVID-19 household transmission study .Saliva and nasal swab viral load profiles from most individuals  revealed a pattern of higher viral loads in specimens collected in the morning than in those collected in the evening. In specimens from some individuals , fluctuations in both SARS-CoV-2 and human N1  and human RNase P , this comparison would be skewed by participants who contributed more specimens and biased by sampling at different stages of the infection. To minimize these potential biases, the time of each specimen collection was aligned relative to the date of symptom onset for that participant before plotting both individual viral load datapoints  and the average of log-transformed viral load values  values between successive time points by calculating differences in TC , saliva specimens collected in the morning typically exhibited a negative difference in TC values relative to their preceding evening specimens, whereas evening specimens consistently had a positive difference in TC values relative to their preceding morning specimens. This indicates that throughout the course of symptomatic infection, morning specimens typically result in relatively lower TC values  than evening specimens.The averaged salivary viral load during each collection time point visually suggests higher viral loads in specimens collected in the morning than in the evening during both the presymptomatic and symptomatic phases of infection. This pattern was less apparent in the averaged nasal swab viral loads but can be seen when comparing the es in CT  and B. OTC values, specimens were binned by infection stage: prior to symptom onset and in 4-day intervals relative to symptom onset. The 4-day interval was selected to capture reasonable resolution for infection stage while also providing sufficient measurements to observe potential differences. Significantly higher morning viral loads were not observed prior to symptom onset in either specimen type in the limited number of specimens collected during this period. However, significantly higher viral loads  were observed in saliva specimens collected in the morning for the first 16 days of symptomatic infection  in morning nasal swab specimens from day 4 to day 16 of symptomatic infection . As LOD increases, fewer pairs are predicted to have detectable virus in either the morning or evening specimen; for this reason, confidence intervals widen as the LOD increases, which results in decreased power to detect significant differences in detection by assays with higher LODs. Additionally, assays with lower LODs are able to reliably detect lower viral concentrations, decreasing the impact of fluctuations in viral load from morning to evening sampling on detection.For saliva specimens, the advantage of morning sampling was statistically significant in all but two comparisons ; the twoMorning sampling with nasal swab specimens also exhibited an advantage over evening sampling after 4 days from symptom onset, for all LODs . In the Similarly, when viral loads are declining, one may expect the earlier time point within a pair of successively collected specimens to exhibit improved detection. We assessed whether this effect was responsible for the improved performance of morning sampling over evening sampling when pairs of successively collected morning-to-evening specimens were compared by performing an equivalent analysis of pairs of successively collected evening-to-morning specimens . Even with evening-to-morning pairing, morning sampling exhibited an advantage over evening sampling for all comparisons with saliva and nearly all comparisons with nasal swabs. In the three of 12 comparisons where morning sampling with nasal swabs did not exhibit an advantage, two comparisons had equivalent detection by morning or evening sampling, and in the third comparison evening sampling exhibited only a nonsignificant advantage of less than 2% over morning sampling.This supports that the advantage of morning sampling over evening sampling for both saliva and nasal swabs was robust to whether the morning specimen is collected prior to or following the evening specimen. These results suggest that collecting saliva or nasal swab specimens for SARS-CoV-2 testing in the morning, immediately after waking, can significantly improve detection of symptomatic, infected individuals.In this study, we quantitatively measured SARS-CoV-2 viral load with high frequency (twice per day) longitudinally through the course of mild COVID-19 infection in saliva for 70 individuals and in nasal swabs for 29 individuals. From these measurements, we identified a pattern of higher viral loads in saliva and nasal swab specimens collected in the morning after waking than in those collected in the evening. Although similar observations have been reported for nasopharyngeal swabs , 21, earRNase P target in saliva and nasal swab specimens collected in the morning . Human salivary production decreases overnight , a circadian rhythm in viral replication may also contribute. Regulation and responsiveness of the immune system have been linked to circadian rhythms , based on the quantitatively measured viral loads. A direct comparison with a specific test is needed to test real-world efficacy.This study is subject to five main limitations. First, we had a limited number of specimens collected prior to the onset of symptoms, limiting our ability to discern a difference in detectability with morning or evening specimens during the presymptomatic phase of infection. Second, this study was performed prior to the dominance of the Delta and Omicron variants of SARS-CoV-2, which may exhibit different viral load kinetics. Host factors, including vaccination status, may also influence viral load kinetics; nearly all individuals in this cohort were unvaccinated. Third, specimens were self-collected without supervision and thus may have had a different quality from those collected by a health care professional. However, many COVID-19 diagnostics in use utilize self-collected specimens, and measurements of the human Participants were recruited for participation in a COVID-19 household transmission study as previously described , at home twice per day (after waking up and before going to bed), per manufacturer’s guidelines . One participant self-collected both anterior nares nasal swab and saliva specimen in Nest viral transport medium (VTM) , and three individuals collected their nasal swab specimens in VTM and their saliva specimens in the Spectrum SDNA-1000 saliva collection kit. Participants were instructed not to ingest anything, smoke, or brush their teeth for at least 30 min prior to collection. For nasal swab collection, participants were asked to gently blow their noses before swabbing (four complete rotations with gentle pressure in each nostril) with sterile flocked swabs. A parent/guardian assisted minors with collection. At collection, participants recorded the date and time and any symptoms experienced in the previous 12 h. Specimens collected between 4 a.m. and 12 p.m. were defined as morning; specimens collected between 3 p.m. and 3 a.m. were defined as evening .Between September 2020 and April 2021, 72 participants from 39 households in southern California had acute SARS-CoV-2 infection. Of these, 2 never reported experiencing symptoms and were not included in subsequent analyses where viral loads are aligned with date of symptom onset. Of the 70 symptomatic individuals from 37 households included in the analyses , all 70 Individuals were enrolled at various stages of infection. Of the 70 infected, symptomatic individuals, 58 were positive for SARS-CoV-2 in the first saliva or saliva and nasal swab specimen collected upon enrollment while 12 were initially negative but became positive while enrolled in the study; of these 12 individuals, 7 were collecting both saliva and nasal swabs, and the viral loads and symptoms of these individuals have been previously reported . Of the The mean age of the saliva cohort was 32.8 years , and the mean age was 33.9 years  among those collecting both saliva and nasal swabs. Health conditions and medications that may have impacted viral load kinetics are provided for individual participants in the supplemental material. No participants required hospitalization. At the time of these participants’ enrollment in the study (September 2020 to April 2021), vaccines were either unavailable or limited to priority groups. Only one individual  reported receiving a COVID-19 vaccine .N1 and N2 genes, as well as a human RNase P control. N1 gene TC values were converted to viral load using an equation derived from a standard curve of heat-inactivated SARS-CoV-2 particles spiked into human specimen matrix validated previously by independent RT-double differential PCR (ddPCR) measurement (Specimen processing was performed as previously described . Brieflysurement .TC from sequential specimens were calculated in Microsoft Excel (TC values, the Wilcoxon matched-pair signed-rank test was performed using GraphPad (Initial processing was performed in Python v3.8.2, with calculation of log-transformed averages . Data weft Excel  to D. Plft Excel . For comGraphPad . An uppeGraphPad .https://data.caltech.edu/records/20049.The data underlying the results presented in the study are available at CaltechDATA at


Countries worldwide are focusing to mitigate the ongoing SARS-CoV-2 pandemic by employing public health measures. Laboratories have a key role in the control of SARS-CoV-2 transmission. Serology for SARS-CoV-2 is of critical importance to support diagnosis, define the epidemiological framework and evaluate immune responses to natural infection and vaccine administration.The aim of this study was the assessment of the actual capability among laboratories involved in sero-epidemiological studies on COVID-19 in EU/EEA and EU enlargement countries to detect SARS-CoV-2 antibodies through an external quality assessment (EQA) based on proficiency testing.The EQA panels were composed of eight different, pooled human serum samples , addressing sensitivity and specificity of detection. The panels and two EU human SARS-CoV-2 serological standards were sent to 56 laboratories in 30 countries.The overall performance of laboratories within this EQA indicated a robust ability to establish past SARS-CoV-2 infections via detection of anti-SARS-CoV-2 antibodies, with 53 of 55 laboratories using at least one test that characterised all EQA samples correctly. IgM-specific test methods provided most incorrect sample characterisations (24/208), while test methods detecting total immunoglobulin (0/119) and neutralising antibodies (2/230) performed the best. The semiquantitative assays used by the EQA participants also showed a robust performance in relation to the standards.Our EQA showed a high capability across European reference laboratories for reliable diagnostics for SARS-CoV-2 antibody responses. Serological tests that provide robust and reliable detection of anti-SARS-CoV-2 antibodies are available. What did you want to address in this study?Robust serological test systems to detect antibodies against SARS-CoV-2 in human serum samples are important to establish whether past infections occurred and to assess the extent of immunity in the population. We want to enable laboratories and countries employing public health measures to assess the quality and robustness of different serological tests that are being used in European expert laboratories. What have we learnt from this study?The majority of laboratories (53 of 55) used at least one serological test that was able to characterise all the serum samples correctly. The performance of serological assays varied for different types of antibodies.What are the implications of your findings for public health?Our study showed a high capability across European reference laboratories for reliable diagnostics for SARS-CoV-2 antibody responses. Aside from assessing the total share of people with immunity in the population, reliable serological diagnostics are also important to guide public health actions by helping to estimate the proportion of asymptomatic cases.Countries worldwide are focusing to mitigate the ongoing coronavirus disease COVID-19) pandemic 9 pandemi, the detThe vast impact of the COVID-19 pandemic on public health, economies and societies drives the rapid development of numerous serological assays by laboratories and commercial entities . These tHere, we describe the set-up and results of such an EQA of detection of SARS-CoV-2 antibodies among European expert laboratories that are members of the European Centre for Disease Prevention and Control (ECDC) COVID-19 and influenza laboratory networks, laboratories involved in sero-epidemiological studies on COVID-19 in the European Union and European Economic Area (EU/EEA) and EU-enlargement countries and/or members of the Emerging Viral Diseases-Expert Laboratory Network (EVD-LabNet). The proficiency panel comprised different isotypes of SARS-CoV-2 antibodies. In addition, laboratories also received two human SARS-CoV-2 serological standards produced and described by the Joint Research Centre (JRC), EURM-017 and EURM-018 ,12, to aIn December 2020 and January 2021, European expert laboratories that are members of the ECDC COVID-19 and influenza laboratory networks, laboratories involved in sero-epidemiological studies on COVID-19 in EU/EEA and EU-enlargement countries and/or members of the Emerging Viral Diseases-Expert Laboratory Network (EVD-LabNet) were invited to participate this EQA study. Registration was closed on 2 February 2021.Fifty-four laboratories received one EQA panel and two JRC standards between 22 February and 5 March 2021, one laboratory registered later and received the packages on 24 March 2021. The online submission form to submit EQA results was open until 8 April 2021.The EQA panels were composed of eight different, fully characterised, pooled human serum samples and addressed both sensitivity and specificity of detection. Five samples contained anti-SARS-CoV-2 antibodies, while three samples did not . Anti-SAThe freeze-dried equivalent of 0.2 mL pooled anonymised sera was prepared for each panel sample . SamplesThe standards EURM-017 and EURM-018 were produced and shipped by JRC. Product information on the materials is publicly available ,12.Supplementary Table S1). Based on this characterisation, the final composition of the EQA panels was defined  COVID-19 reference laboratories at INMI and RIVM, using a wide variety of serological tests , and at 4 °C once the material was reconstituted; original material of the JRC standards frozen (acceptable range: −20 °C to −80 °C), and at 4 °C once the material was thawed. Laboratories were informed that the provided standards contained anti-SARS-CoV-2 antibodies, as they received the product information sheet alongside the EQA panel.The testing instructions provided a link to the online result submission platform. In the online submission form, laboratories were asked to give detailed information on each of the tests that they performed on the EQA panel and JRC standards, including the type of detectable antibodies. Since a the majority of serological tests only require small volumes, multiple different tests could be performed. For each method, the laboratories had to indicate whether they detected anti-SARS-CoV-2 antibodies in the EQA samples, the specific result of the test and how they interpreted the outcome of the test. Because laboratories had to submit their results per specific test used, the EQA outcomes could be analysed on individual test level, as well as on laboratory level (multiple tests per laboratory). There was no minimum or maximum limit for how many tests could be assessed with the EQA panels and submitted in the online submission form. Supplementary Table S2 lists the commercial and in-house tests assessed by EQA participants) were used by 55 laboratories resulting in a submission of results of 162 tests.For the purposes of this EQA, the panel outcomes with an individual test submitted by a laboratory were referred to as a ‘test’, i.e. in total, results of 162 tests were submitted by 55 laboratories  . Tests tData were collected and analysed in Microsoft Excel  and GraphPad Prism 9 software for Windows version 9.1.0 . Performance of specific tests was analysed by comparison of the amount of correct vs false results, either grouped by assay type or by isotypes of detectable antibodies, using two-sided Yates’ corrected chi-squared test. Results with a p value ≤ 0.05 were considered statistically significant. Furthermore, Spearman’s rank correlation test was used to assess correlation of EQA performance as fraction of correct results, with sample input volume as specified by the EQA participants.Fifty-six laboratories registered to participate in the EQA. In total, 55 laboratories from 30 countries, namely 27 of 30 EU/EEA countries and three of seven EU pre-accession countries, reported individual panel results representing 162 tests , while oThirty-six of 55 laboratories characterised all EQA samples correctly with all tests they assessed, while 17 additional laboratories used at least one test that identified all EQA samples correctly . Only twOverall, false-negative results occurred less frequently than false-positive results , Table 2Supplementary Table S2). Overall, 3.5%  of reported results using commercial assays and 2.6% (6/231) using in-house assays were incorrect. Of all 162 tests used by participants, 75 (46.3%) were ELISA-based, 43 (26.5%) were CLIA/chemiluminescent microparticle immunoassay (CMIA)/electrochemiluminescent immunoassay (ECLIA) tests and 22 (13.6%) VNTs. The remaining 22 (13.6%) included, among other types of tests, LFA, plaque reduction neutralisation test (PRNT), protein micro-array and immunofluorescence assay/enzyme-linked fluorescence assay.In total, 41 commercial assays and 12 in-house assays were used by the EQA participants  and six commercial assays  correctly characterised all EQA samples in all laboratories that assessed these assays . None ofFour qualitative assays in this EQA had been previously used to characterise the JRC standards as positive, both EURM-017  and EURMLaboratories were asked to specify the exact  results of each test they used to assess how semiquantitative assays performed across different laboratories in comparison to the reference product information available for the two JRC standards. The vast majority of laboratories used the advised volume of 200 µL sterile water to reconstitute the EQA samples (51/55 laboratories) as well as the storage advice for both the EQA panels (54/55 laboratories) and the JRC standards (50/55 laboratories). We did not see any influence of these parameters on test performance. Although sample input volume for the different tests ranged from 1 µL to 170 µL, it did not correlate with the fraction of correct results by test .Considering antibodies directed to different antigenic proteins targeted in the serological assays, the majority of the assays used (n = 27) was based on the spike (S) protein, including recombinant full S or its specific domains . Fifteen assays used both N and S proteins, while six targeted the anti-N response only. In addition, 18 assays used whole live virus isolates for VNT/PRNT, while for three in-house assays, the viral antigen was not reported. No influence of the target protein on test results was observed.The overall performance of laboratories within this EQA indicated a robust ability to establish whether past SARS-CoV-2 infections occurred via detection of anti-SARS-CoV-2 antibodies. All except two laboratories used at least one assay that identified all samples correctly as SARS-CoV-2 antibody positive or negative.Supplementary Table S1). Furthermore, eight of 14 IgM-specific assays resulted in one or more false-positive test results. Several studies have shown that in general, IgM assays have a lower sensitivity and specificity than IgG or total IgG assays [IgM-specific assays showed the most incorrect characterisations of the EQA samples. In particular, sample G (IgA+/IgG+/IgM+(low)) was missed by four of five laboratories that used the same commercial IgM-only assay (Euroimmun – Anti-SARS-CoV-2 NCP ELISA IgM) and by two additional assays that should have been able to detect the presence of IgM antibodies based on their technical specifications . The remaining 20 laboratories were able to identify sample G correctly using 11 different assays. Indeed, this sample was characterised by the two reference laboratories to have IgM levels below the detection limit of some assays (find the detailed results listed in G assays . Hence iG assays -19. IndeSupplementary Table S1). If this was the case, specificity test performance would probably be further reduced in periods of high prevalence of co-circulating seasonal coronaviruses.Correct characterisation of the three specificity samples  was more problematic than of the sensitivity samples. Variable test performance for specificity samples has been reported before ,21. A liAs expected, the absolute titres obtained with the various virus neutralisation assays varied between laboratories as underlying protocols can vary extensively  and this gold standard serology method is mostly used as a research tool in the virology field. A recent European study showed that indeed a substantial heterogeneity exists in neutralising antibody testing approaches, resulting in almost 100-fold differences in raw neutralising titres. However, a direct comparison was possible through harmonisation by the use of a standard defined in IU/mL, which reduced the inter-laboratory variability ca 10-fold . AnotherThe characterisation of the JRC standards with the semiquantitative binding assays by the EQA participants was in range with the standards product information, indicating a robust performance of these semiquantitative assays across different laboratories. The qualitative assays that were used to define the JRC standards performed similarly in the EQA as well.Notably, all samples used in this study were obtained from patients with natural SARS-CoV-2 infections. We did not include samples from vaccinated individuals. For future sero-epidemiological surveillance studies, the capacity of serological tests to differentiate between antibodies derived from natural infections and antibodies induced by vaccination is desirable. This can be achieved by using serological tests with different antigenic targets, i.e. anti-N  and anti-S detection, to determine the level of natural immunity in the study population and assess the risk of vaccination not being sufficient to protect against a potentially increasing burden on the healthcare system. EQA programmes including also sera from vaccinated people would be of great interest to expand the evaluation of the accuracy of different tests during the next phases of the pandemic when vaccination campaigns are consolidated in most countries worldwide.Proficiency testing in EQA schemes allows to compare the accuracy of different tests and the performance of different laboratories based on the same material. Although the number of study participants (n = 55) and moreover the total number of performed tests (n = 162) was sufficient to gain valuable insights into the quality of serological SARS-CoV-2 assays, the abundance, availability and variety of different SARS-CoV-2 assays used by the participants, limits the number of results obtained per specific assay by different laboratories and therefore the statistical power and confidence in the results. It would be desirable to perform additional follow-up studies. The wide variety in tests used and general lack of routine incorporation of international standards in SARS-CoV-2 serology prevents comparisons of immune responses across laboratories, thereby hampering standardised cross-border sero-epidemiological surveillance and the wide implementation of immunoassays to identify correlates of protection against SARS-CoV-2, e.g. in the context of vaccination policies or the EU Digital COVID Certificate Regulation .Nevertheless, proficiency testing is important for individual laboratories. The results of an EQA allow laboratories to identify potential problems and improve the reliability of their diagnosis. Interestingly, one laboratory repeated their tests upon receipt of their EQA results which included three false negative results using two different assays. In this second attempt, the results were correct. This laboratory indicated insufficient homogenisation of the samples as a potential explanation for the observed discrepancies.A general capability for reliable, harmonised and standardised characterisation of the main immunological markers of a previous SARS-CoV-2 infection or vaccination against SARS-CoV-2 is crucial to increase the overall utility of serology testing. Potential inconsistent test performance and the absence of a rationale to use quantitative antibody assays due to the, yet, undetermined correlates of protection of antibody levels, currently limits the overall usefulness of serology. Participation in EQAs may help to improve implementation of diagnostic tests. Our EQA showed a high capability across European reference laboratories for reliable diagnostics for SARS-CoV-2 antibody responses. Serological tests that provide robust and reliable detection of anti-SARS-CoV-2 antibodies are available. However, the use of standards is necessary for meaningful quantitative measurements to increase the overall use of serology testing, including the evaluation of antibody waning and possible reactivity against more relevant virus variants with immunological escape potential in the prospective of a more ‘personalised’ approach to vaccination strategies. This is particularly relevant given that serology is no longer restricted to reference laboratories. Numerous laboratories non specialised in microbiology are performing serological tests using a wide panel of commercial assays. In order to maintain serological test quality, it would also be advisable to implement EQAs at national level, including schemes to evaluate and distinguish natural immunity and vaccination response.