Xiaomeng Ma

Background: Allergic and type 2 (T2) inflammatory biomarkers are increasingly used to predict outcomes and guide treatment in asthma and COPD. The objective of this cross-sectional study was to determine the prevalence of allergic sensitisation and T2 biomarkers and their clinical associations among patients with diagnoses of asthma and/or COPD in NOVELTY, a large multinational, observational study. Methods: Participants were enrolled from primary/specialist care, stratified by physician-assigned diagnosis and severity. We assessed fractional exhaled nitric oxide (≥25 ppb), blood eosinophils (≥300 cells·µL ⁻¹ ) and allergen-specific IgE sensitisation (≥0.35 kU·L ⁻¹ to any of 11 aeroallergens). Associations between biomarkers and clinical outcomes were examined using descriptive statistics and multivariable regression models adjusted for age, sex, body mass index and smoking status. Results: Data for all biomarkers were available for 4352 participants (asthma: n=2194; asthma+COPD: n=633; COPD: n=1525). Overall, 63% participants had at least one positive biomarker (asthma: 77%; asthma+COPD: 60%; COPD: 45%); only 8%, 4% and 1% of participants, respectively, were positive for all three biomarkers. Women and current smokers were more likely to be triple-negative. Among participants with asthma, having more positive biomarkers was associated with more severe physician-assessed disease, lower lung function and exacerbations. By contrast, in COPD, having no positive biomarkers was associated with more severe physician-assessed disease and lower lung function. Conclusions: Allergic and T2 biomarkers are highly prevalent in asthma and asthma+COPD but less frequent in COPD. Their patterns show distinct associations, sometimes with opposite trends, across diagnostic groups, suggesting distinct underlying mechanisms that differ.

Background: Social determinants of health (SDoH), such as socioeconomics and neighborhoods, strongly influence health outcomes. However, the current state of standardized SDoH data in electronic health records (EHRs) is lacking, a significant barrier to research and care quality.Methods: We conducted a PubMed search using “SDOH” and “EHR” Medical Subject Headings terms, analyzing included articles across five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.Results: Of 685 articles identified, 324 underwent full review. Key findings include implementation of tailored screening instruments, census and claims data linkage for contextual SDoH profiles, NLP systems extracting SDoH from notes, associations between SDoH and healthcare utilization and chronic disease control, and integrated care management programs. However, variability across data sources, tools, and outcomes underscores the need for standardization.Discussion: Despite progress in identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical for SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately, widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Background Social determinants of health (SDoH) like socioeconomics and neighborhoods strongly influence outcomes, yet standardized SDoH data is lacking in electronic health records (EHR), limiting research and care quality. Methods We searched PubMed using keywords “SDOH” and “EHR”, underwent title/abstract and full-text screening. Included records were analyzed under five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions. Results We identified 685 articles, of which 324 underwent full review. Key findings include tailored screening instruments implemented across settings, census and claims data linkage providing contextual SDoH profiles, rule-based and neural network systems extracting SDoH from notes using NLP, connections found between SDoH data and healthcare utilization/chronic disease control, and integrated care management programs executed. However, considerable variability persists across data sources, tools, and outcomes. Discussion Despite progress identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical to fulfill the potential of SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Background Complete reporting of seroepidemiologic studies (e.g. sampling and measurement methods, immunoassay characteristics) are critical to their interpretation, comparison, and utility in evidence synthesis. The Reporting of Seroepidemiologic studies—SARS_JCoV_J2 (ROSES-S) guideline is a reporting checklist that aims to improve the quality and transparency of reporting in SARS-CoV-2 seroepidemiological studies. While the synthesis of seroepidemiologic studies played a crucial role in public health decision-making during the COVID-19 pandemic, adherence of SARS-CoV-2 seroepidemiologic studies to the ROSES-S guideline has not yet been evaluated. Objectives To evaluate the completeness of SARS-CoV-2 seroepidemiologic study reporting over the first two years of the COVID-19 pandemic by assessing adherence to the ROSES-S reporting guideline, determine whether publication of the ROSES-S guideline was associated with changes in reporting completeness, and identify study characteristics associated with reporting completeness. Methods A stratified random sample of SARS-CoV-2 seroepidemiologic studies from the SeroTracker living systematic review database was evaluated for adherence to the ROSES-S guideline. We categorized study adherence to each reporting item in the guideline as “reported”, “not reported”, or “not applicable”. For each reporting item we calculated the percentage of studies that were adherent. We also calculated the median and interquartile range (IQR) adherence across all items and by item domain. Piecewise and multivariable beta regression analyses were used to determine whether publication date of the ROSES-S guideline was associated with changes in the overall adherence scores and to identify study characteristics associated with overall adherence scores. Results 199 studies were included and analyzed. The median adherence to reporting items was 48.1% (IQR 40.0%–55.2%) per study. Adherence to reporting items ranged from 8.8% to 72.7% per study. The laboratory methods domain (e.g. description of testing algorithm) had the lowest median adherence (33.3% [IQR 25.0%–41.7%%]), while the discussion domain had the highest median adherence (75.0% [IQR 50.0%–100.0%])). There were no significant changes in reporting adherence to ROSES-S before and after guideline publication. Article publication source (pConclusions The completeness of reporting in SARS-CoV-2 seroepidemiologic studies was suboptimal, especially in laboratory methods, and was associated with key study characteristics. Publication of the ROSES-S guideline was not associated with changes in reporting practices. Given that reporting is necessary to improve the standardization and utility of seroprevalence data in evidence synthesis, authors should improve adherence to the ROSES-S guideline with support from stakeholders.

Background: Many serological assays to detect SARS-CoV-2 antibodies were developed during the COVID-19 pandemic. Differences in the detection mechanism of SARS-CoV-2 serological assays limited the comparability of seroprevalence estimates for populations being tested. Methods: We conducted a systematic review and meta-analysis of serological assays used in SARS-CoV-2 population seroprevalence surveys, searching for published articles, preprints, institutional sources, and grey literature between 1 January 2020, and 19 November 2021. We described features of all identified assays and mapped performance metrics by the manufacturers, third-party head-to-head, and independent group evaluations. We compared the reported assay performance by evaluation source with a mixed-effect beta regression model. A simulation was run to quantify how biased assay performance affects population seroprevalence estimates with test adjustment. Results: Among 1807 included serosurveys, 192 distinctive commercial assays and 380 self-developed assays were identified. According to manufacturers, 28.6% of all commercial assays met WHO criteria for emergency use (sensitivity [Sn.] >= 90.0%, specificity [Sp.] >= 97.0%). However, manufacturers overstated the absolute values of Sn. of commercial assays by 1.0% [0.1, 1.4%] and 3.3% [2.7, 3.4%], and Sp. by 0.9% [0.9, 0.9%] and 0.2% [−0.1, 0.4%] compared to third-party and independent evaluations, respectively. Reported performance data was not sufficient to support a similar analysis for self-developed assays. Simulations indicate that inaccurate Sn. and Sp. can bias seroprevalence estimates adjusted for assay performance; the error level changes with the background seroprevalence. Conclusions: The Sn. and Sp. of the serological assay are not fixed properties, but varying features depending on the testing population. To achieve precise population estimates and to ensure the comparability of seroprevalence, serosurveys should select assays with high performance validated not only by their manufacturers and adjust seroprevalence estimates based on assured performance data. More investigation should be directed to consolidating the performance of self-developed assays.

Background: Our understanding of the global scale of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection remains incomplete: Routine surveillance data underestimate infection and cannot infer on population immunity; there is a predominance of asymptomatic infections, and uneven access to diagnostics. We meta-analyzed SARS-CoV-2 seroprevalence studies, standardized to those described in the World Health Organization’s Unity protocol (WHO Unity) for general population seroepidemiological studies, to estimate the extent of population infection and seropositivity to the virus 2 years into the pandemic. Methods and findings: We conducted a systematic review and meta-analysis, searching MEDLINE, Embase, Web of Science, preprints, and grey literature for SARS-CoV-2 seroprevalence published between January 1, 2020 and May 20, 2022. The review protocol is registered with PROSPERO (CRD42020183634). We included general population cross-sectional and cohort studies meeting an assay quality threshold (90% sensitivity, 97% specificity; exceptions for humanitarian settings). We excluded studies with an unclear or closed population sample frame. Eligible studies—those aligned with the WHO Unity protocol—were extracted and critically appraised in duplicate, with risk of bias evaluated using a modified Joanna Briggs Institute checklist. We meta-analyzed seroprevalence by country and month, pooling to estimate regional and global seroprevalence over time; compared seroprevalence from infection to confirmed cases to estimate underascertainment; meta-analyzed differences in seroprevalence between demographic subgroups such as age and sex; and identified national factors associated with seroprevalence using meta-regression. We identified 513 full texts reporting 965 distinct seroprevalence studies (41% low- and middle-income countries [LMICs]) sampling 5,346,069 participants between January 2020 and April 2022, including 459 low/moderate risk of bias studies with national/subnational scope in further analysis. By September 2021, global SARS-CoV-2 seroprevalence from infection or vaccination was 59.2%, 95% CI [56.1% to 62.2%]. Overall seroprevalence rose steeply in 2021 due to infection in some regions (e.g., 26.6% [24.6 to 28.8] to 86.7% [84.6% to 88.5%] in Africa in December 2021) and vaccination and infection in others (e.g., 9.6% [8.3% to 11.0%] in June 2020 to 95.9% [92.6% to 97.8%] in December 2021, in European high-income countries [HICs]). After the emergence of Omicron in March 2022, infection-induced seroprevalence rose to 47.9% [41.0% to 54.9%] in Europe HIC and 33.7% [31.6% to 36.0%] in Americas HIC. In 2021 Quarter Three (July to September), median seroprevalence to cumulative incidence ratios ranged from around 2:1 in the Americas and Europe HICs to over 100:1 in Africa (LMICs). Children 0 to 9 years and adults 60+ were at lower risk of seropositivity than adults 20 to 29 (p < 0.001 and p = 0.005, respectively). In a multivariable model using prevaccination data, stringent public health and social measures were associated with lower seroprevalence (p = 0.02). The main limitations of our methodology include that some estimates were driven by certain countries or populations being overrepresented. Conclusions: In this study, we observed that global seroprevalence has risen considerably over time and with regional variation; however, over one-third of the global population are seronegative to the SARS-CoV-2 virus. Our estimates of infections based on seroprevalence far exceed reported Coronavirus Disease 2019 (COVID-19) cases. Quality and standardized seroprevalence studies are essential to inform COVID-19 response, particularly in resource-limited regions.

Background Many SARS-CoV-2 serological assays were rapidly developed during the COVID-19 pandemic. However, differences in detection mechanism limit the comparability of assay outputs. Methods As part of the SeroTracker global living systematic review of SARS-CoV-2 seroprevalence studies, we collated serological assays used in serosurveys between January 1, 2020 and November 19, 2021. We mapped performance metrics to the manufacturer, third-party head-to-head, and independent group evaluations, comparing the assay performance data using a mixed-effect beta regression model. Results Among 1807 serosurveys, 192 distinctive commercial assays and 380 self-developed assays were identified. According to manufacturers, 28.6% of all commercial assays met WHO criteria for emergency use (sensitivity [Sn.] >= 90.0%, specificity [Sp.] >= 97.0%). Third-party and independent evaluations indicated that manufacturers overstated the Sn. of their assays by 5.4% and 2.8%, and Sp. by 6.3% and 1.2%. We found in simulations that inaccurate Sn. and Sp. can substantially bias seroprevalence estimates corrected for assay performance. Conclusions The Sn. and Sp. of the serological assay are not fixed properties, but varying features depending on testing population. To achieve precise population estimates and to ensure comparability, serosurveys should select assays with strong, independently validated performance and adjust seroprevalence estimates based on assured performance data.

Background We aimed to systematically review the magnitude and duration of the protective effectiveness of prior infection (PE) and hybrid immunity (HE) against Omicron infection and severe disease. Methods We searched pre-print and peer-reviewed electronic databases for controlled studies from January 1, 2020, to June 1, 2022. Risk of bias (RoB) was assessed using the Risk of Bias In Non-Randomized Studies of Interventions (ROBINS-I)-Tool. We used random-effects meta-regression to estimate the magnitude of protection at 1-month intervals and the average change in protection since the last vaccine dose or infection from 3 months to 6 or 12 months. We compared our estimates of PE and HE to previously published estimates of the magnitude and durability of vaccine effectiveness (VE) against Omicron. Findings Eleven studies of prior infection and 15 studies of hybrid immunity were included. For prior infection, there were 97 estimates (27 at moderate RoB and 70 at serious RoB), with the longest follow up at 15 months. PE against hospitalization or severe disease was 82.5% [71.8-89.7%] at 3 months, and 74.6% [63.1-83.5%] at 12 months. PE against reinfection was 65.2% [52.9-75.9%] at 3 months, and 24.7% [16.4-35.5%] at 12 months. For HE, there were 153 estimates (78 at moderate RoB and 75 at serious RoB), with the longest follow up at 11 months for primary series vaccination and 4 months for first booster vaccination. Against hospitalization or severe disease, HE involving either primary series vaccination or first booster vaccination was consistently >95% for the available follow up. Against reinfection, HE involving primary series vaccination was 69.0% [58.9-77.5%] at 3 months after the most recent infection or vaccination, and 41.8% [31.5-52.8%] at 12 months, while HE involving first booster vaccination was 68.6% [58.8-76.9%] at 3 months, and 46.5% [36.0-57.3%] at 6 months. Against hospitalization or severe disease at 6 months, hybrid immunity with first booster vaccination (effectiveness 95.3% [81.9-98.9%]) or with primary series alone (96.5% [90.2-98.8%]) provided significantly greater protection than prior infection alone (80.1% [70.3-87.2%]), first booster vaccination alone (76.7% [72.5-80.4%]), or primary series alone (64.6% [54.5-73.6%]). Results for protection against reinfection were similar. Interpretation Prior infection and hybrid immunity both provided greater and more sustained protection against Omicron than vaccination alone. All protection estimates waned quickly against infection but remained high for hospitalisation or severe disease. Individuals with hybrid immunity had the highest magnitude and durability of protection against all outcomes, reinforcing the global imperative for vaccination. Funding WHO COVID-19 Solidarity Response Fund Evidence before this study The global emergence and rapid spread of Omicron (B.1.1.529) variant of concern, characterized by their ability to escape immunity, has required scientists and policymakers to reassess the population protection against Omicron infection and severe disease. So far, few systematic reviews have incorporated data on Omicron, and none have examined the protection against Omicron conferred by hybrid immunity (i.e. the immunity gained from the combination of vaccination and prior infection) which is now widespread globally. While one preprint has recently reported protection from prior infection over time, no systematic review has systematically compared the magnitude and duration of vaccination, prior infection, and hybrid immunity. A large single-country study has reported that protection from either infection or hybrid immunity against Omicron infection wanes to low levels at 15 months, but is relatively stable against severe disease. Added value of this study Prior infection and hybrid immunity both provided greater and more sustained protection against Omicron than vaccination alone. Individuals with hybrid immunity had the highest magnitude and durability of protection against all outcomes; protection against severe disease remained above 95% until the end of available follow-up at 11 months after hybrid immunity with primary series and 4 months after hybrid immunity with booster vaccination, and was sustained at these high levels of protection in projections to 12 months and 6 months, respectively. Implications of all the available evidence These results may serve to tailor guidance on the optimal number and timing of vaccinations. At the public health level, these findings can be combined with data on local infection prevalence, vaccination rates, and their timing. In settings with high seroprevalence, limited resources, and competing health priorities, it may be reasonable to focus on achieving high coverage rates with primary series among individuals who are at higher risk of poor outcome, as this will provide a high level of protection against severe disease for at least one year among those with prior infection. Furthermore, given the waning protection for both infection-and vaccine induced immunity against infection or reinfection, mass vaccination could be timed for roll-out prior to periods of expected increased incidence, such as the winter season. At the individual level, these results can be combined with knowledge of a person’s infection and vaccination history. A six-month delay in booster may be justified after the last infection or vaccination for individuals with a known prior infection and full primary series vaccination. Further follow-up of the protective effectiveness of hybrid immunity against hospitalization or severe disease for all vaccines is needed to clarify how much waning of protection might occur with longer duration since the last infection or vaccination. Producing estimates of protection for new variant-containing vaccines will be crucial for COVID-19 vaccine policy and decision-making bodies. Policy makers considering the use and timing of vaccinations should include the local extent of past infection, the protection conferred by prior infection or hybrid immunity, and the duration of this protection as key considerations to inform their decision-making.

Introduction Estimating COVID-19 cumulative incidence in Africa remains problematic due to challenges in contact tracing, routine surveillance systems and laboratory testing capacities and strategies. We undertook a meta-analysis of population-based seroprevalence studies to estimate SARS-CoV-2 seroprevalence in Africa to inform evidence-based decision making on public health and social measures (PHSM) and vaccine strategy. Methods We searched for seroprevalence studies conducted in Africa published 1 January 2020–30 December 2021 in Medline, Embase, Web of Science and Europe PMC (preprints), grey literature, media releases and early results from WHO Unity studies. All studies were screened, extracted, assessed for risk of bias and evaluated for alignment with the WHO Unity seroprevalence protocol. We conducted descriptive analyses of seroprevalence and meta-analysed seroprevalence differences by demographic groups, place and time. We estimated the extent of undetected infections by comparing seroprevalence and cumulative incidence of confirmed cases reported to WHO.PROSPERO: CRD42020183634. Results We identified 56 full texts or early results, reporting 153 distinct seroprevalence studies in Africa. Of these, 97 (63%) were low/moderate risk of bias studies. SARS-CoV-2 seroprevalence rose from 3.0% (95% CI 1.0% to 9.2%) in April–June 2020 to 65.1% (95% CI 56.3% to 73.0%) in July–September 2021. The ratios of seroprevalence from infection to cumulative incidence of confirmed cases was large (overall: 100:1, ranging from 18:1 to 954:1) and steady over time. Seroprevalence was highly heterogeneous both within countries—urban versus rural (lower seroprevalence for rural geographic areas), children versus adults (children aged 0–9 years had the lowest seroprevalence)—and between countries and African subregions. Conclusion We report high seroprevalence in Africa suggesting greater population exposure to SARS-CoV-2 and potential protection against COVID-19 severe disease than indicated by surveillance data. As seroprevalence was heterogeneous, targeted PHSM and vaccination strategies need to be tailored to local epidemiological situations.