Analysis of the Mexican communication plan to control the Covid-19 epidemic

This chapter uses discourse analysis to study the statements made by two main players of the Mexican government: President Andrés Manuel López Obrador and Hugo López-Gatell, the Undersecretary for Health Prevention and Promotion. This analysis also discusses the ¡Quédate en casa! audiovisual advertisement campaign and its main character: the heroine SuSana Distancia. It suggests that the government's advertisement campaigns failed to promote the importance of health care and joint responsibility among the community;this is reflected in the number of people infected and deaths in Mexico. This study is made up of six parts: the first introduces the importance of a strategic communication plan;the second discusses the frame of reference;the third describes the analysis method and the corpus study configuration;the fourth includes the results;the fifth ponders the analysis;and the sixth includes the conclusions. The main findings are that the Mexican government never had the intention of promoting the use of masks as an essential measure. Two spots taught the population how to wear a mask;however, the discourse of both the Undersecretary and the President was that wearing a mask was not an essential measure to control infections. © Springer Nature Switzerland AG 2023. All rights reserved.

MNLTour: A Web and Mobile Application for Virtual Tour System of Select Tourist Spots Around Manila Using 360-degree Imagery and Virtual Reality Technology

MNLTour is a virtual tour system for selected tourist spots situated within the city of Manila. It utilizes 360-degree images, 2D images, voice recordings, and virtual reality technology to offer an immersive user experience of the virtual environment. The virtual tour system was developed using the Unity3D software and was then integrated into web and mobile applications accessible through web browsers and android smartphones, respectively. MNLTour aims to promote the wonders of Manila city by showcasing some of its historical tourist spots that have been severely affected by the outbreak of the COVID-19 pandemic. The developed web and mobile applications were tested and later evaluated to assess the overall quality of the software in accordance with ISO 9126 standard. The evaluation statements primarily focus on the aspects of functionality, efficiency, usability, effectiveness, and user satisfaction in using the application. Descriptive statistics was used to analyze and summarize the data gathered from the evaluation respondents. The evaluation of the application in both platforms turned out to have admirable evaluation results;hence, it's safe to say that the developed software has an acceptable overall quality. © 2022 IEEE.

A COVID-19-Related Retinopathy Case Report.

The recent outbreak of the severe acute respiratory syndrome coronavirus-2 has been declared a worldwide pandemic by the WHO. Within various multi-organ involvements, several ocular manifestations have been described. We report the case of a patient diagnosed with COVID-19 who presented with a progressive increase of bilateral cotton wool spots over a 1-week period, despite quick and complete recovery of systemic signs of the disease and no ocular symptoms. We followed the evolution of such lesions over a 3-month period. Here, we underline the importance of retinal screening even if no ocular symptom is reported. Furthermore, we demonstrate the essential role of fundus examination as a reflection of systemic vascular changes.

Performances of Dried Blood Spots and Point-of-Care Devices to Identify Virological Failure in HIV-Infected Patients: A Systematic Review and Meta-Analysis.

To broaden access to HIV viral load monitoring (VLM), the use of blood samples from dried blood spots (DBS) or point-of-care (POC) devices, could be of great help in settings where plasma is not easily accessible. The variety of assays available makes the choice complex. This systematic review and meta-analysis aims to estimate the sensitivity and specificity of DBS and POC devices to identify patients in virological failure using World Health Organization (WHO) recommendations (viral load ≥1000 copies/mL), compared with plasma, for the assays currently available. Four databases were searched for articles, and two reviewers independently identified articles reporting sensitivity and specificity of DBS and/or POC to identify patients in virological failure. We excluded articles that used other thresholds as well as articles with a total number of participants below 50 to avoid reporting bias. Heterogeneity and factors associated with assays' performances were assessed by I2 statistics and metaregression. The protocol of this review follows the PRISMA guidelines. Out of 941 articles, 47 were included: 32 DBS evaluations and 16 POC evaluations. Overall, when using DBS, the Abbott RT HIV-1, Roche CAP-CTM, NucliSENS BioMerieux and Aptima assays presented sensitivity and specificity exceeding 85%, but reported results were highly heterogeneous. Factors associated with better performances were high volume of blood and the use of the same assay for DBS and plasma VLM. Regarding the POC devices, SAMBA I, SAMBA II, and GeneXpert devices presented high sensitivity and specificity exceeding 90%, with less heterogeneity. DBS is suitable VLM, but performances can vary greatly depending on the protocols, and should be performed in trained centers. POC is suitable for VLM with less risk of heterogeneity but is more intensive in costs and logistics.

A text data mining approach to the study of emotions triggered by new advertising formats during the COVID-19 pandemic.

Under the influence of the health emergency triggered by the COVID-19 pandemic, many brands changed their communication strategy and included more or less explicit references to the principles of solidarity and fraternity in their TV commercials to boost the confidence and hope of Italian families during the lockdown. The traditional attitudes of the advertising format, which focused on product characteristics, were relegated to the background in order to reinforce the "brand image" through words, signs, hashtags and music that spread empathetic messages to all those who needed to regain hope and trust in a time of extreme emotional fragility. The objective of this paper is to identify the emotions and brand awareness during the lockdown using text mining techniques by measuring customer sentiment expressed on the Twitter social network. Our proposal starts from an unstructured corpus of 20,982 tweets processed with text data mining techniques to identify patterns and trends in people's posts related to specific hashtags and TV ads produced during the COVID-19 pandemic. The innovations in the brand's advertising among consumers seem to have triggered some sense of appreciation and gratitude, as well as a strong sense of belonging that was not present before, as the TV ads were perceived as a disruptive element in consumers' tweets. Although this effect is clearly documented, in this paper we demonstrate its transitory nature, in the sense that the frequency of occurrence of terms associated with an emotional dimension peaks during the weeks of lockdown, and then gradually decreases.

Accelerating Biosafety Capacity Building to Ensure National Biosecurity

Biosafety is an essential part of the national security system, which is related to people's lives and health, the country's longterm stability, and sustainable development, which is the bottom line that must be guaranteed. The international biosafety situation is grim and complex, while domestic biosafety faces challenges. Therefore, biosafety capacity building has become an international hot spot, among which scientific and technological innovation, talent training, and infrastructure platform construction are the top priorities. Although China has achieved strategic results in the rapid identification of pathogens, research, and development of specific vaccines and medicine in fighting against COVID-19 by relying on scientific research, it has shown the urgency for scientific and technological innovation in biosafety. Therefore,China has developed a strategic plan on "promoting the modernization of the national security system and capabilities, resolutely safeguarding national security and social stability" included in the 20th National Congress of the Communist Party of China. Hence, it is suggested to promote biosafety capacity building further to improve China's biosecurity system, protect people's health, ensure national security, and maintain long-term peace and stability by improving the layout of scientific and technological frontiers, promoting the construction of biosafety discipline, training of more special talents, and infrastructure platform construction.

A Bibliometric Analysis of Trending Mobile Teaching and Learning Research from the Social Sciences

With the development of computer and information technology, mobile teaching has enjoyed pride of place among teaching mediums in the past two decades. To visually explore the mobile learning hotspots and trends present in international journals, this study adopted two science mapping tools (CiteSpace and VOSviewer) to first detect and then visualise emerging trends (i.e., hotspots) in the mobile learning literature. A total of 528 mobile learning articles published between 2003 and 2021 that appeared in 21 international educational technology journals indexed in the SSCI database were retrieved for bibliometric analysis. The results show (1) there was a remarkable increase in academic output in this field starting in 2008 that topped out in 2021;(2) co-authorship with academics from diverse countries/regions and institutions was evident;(3) three trending foci in the literature include defining mobile learning, designing learning systems, and exploring mobile learning effectiveness;and (4) the high-frequency co-cited publications focus on the effectiveness of mobile devices via different research methods. This study provides scholars with an accessible summary of the current trends in mobile learning, identifies the active researchers in this field, and reports on which outlets are most relevant for research produced on this topic. In addition, the findings have direct implications for the education and private sectors. Mobile devices are not widely adopted in classroom settings and are often considered a learning tool more suited for out-of-class assignments or practice. Therefore, it is necessary for information technology educators to invest in actively initiating the integration of mobile technology into the classroom. Those in the technology industry should aim to develop mobile devices and relevant educational applications/software that can be utilised not only within the confines of the classroom but also to bridge in-class and out-of-class learning.

Dried blood spot eluates are suitable for testing of SARS-CoV-2 IgG antibodies targeting Spike protein 1 and Nucleocapsid protein.

Dried blood spots (DBS) provide easy handling and are thus a beneficial tool for data collection, e.g. for epidemiological studies. The suitability of DBS for the assessment of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was analyzed with regards to the use in future studies addressing seroprevalence in the population. 121 volunteers gave a venous blood sample and capillary blood samples on two DBS cards (PerkinElmer and Ahlstrom-Munksjö) via self-sampling under supervision. All samples were analyzed using the Anti-SARS-CoV-2 ELISA (IgG) and the Anti-SARS-CoV-2 NCP ELISA (IgG) from EUROIMMUN performed on the EUROIMMUN EUROLabWorkstation ELISA. Correlation coefficients between ELISA results based on the different sampling methods were calculated. Results of DBS analysis for SARS-CoV-2 IgG S1 and NCP highly correlated with the serum values (r = 0.96). In addition, the calculation of the phi coefficient showed no significant difference between the qualitative results of both sampling methods (rφ = 0.98-1.0). Further analysis of DBS eluates after prolonged storage of 6-8 h also showed a high correlation with serum results (r = 0.97 and r = 0.93, respectively). The study results indicate suitability of DBS for the analysis of antibodies against SARS-CoV-2 S1 and NCP. For DBS eluate, a stability of 6-8 h for measurement of SARS-CoV-2 antibodies can be assumed.

An empirical analysis of Delhi's air quality throughout different COVID-19 pandemic waves

Delhi was one of India's COVID-19 hotspots, with significant death rates during the year 2021. This study looked at the link between COVID-19 cases in Delhi, and key meteorological variables. The study found that COVID-19 cases during the second wave (P2-March- May 2021) were much higher than during the first wave (P1-Jan-Feb 2021) in Delhi. During P1 (Jan-Feb 2021) the mean PM2.5, PM10, NO2 and CO concentrations were greater than that of P2 (March-May 2021) while the reverse happened for SO2 and O3. Spearman correlation test indicated that COVID-19 cases maintained a significant positive correlation with the high temperature of P2 (March-May 2021) and high humidity of P1 (Jan-Feb 2021) in line with the accepted notion that COVID-19 transmitted favourably in hot and humid climates. The Multilayer perceptron (MLP) model indicated that COVID-19 spread was supported by air pollutants and climate variables like PM2.5, NO2, RH, and WS in P1(Jan-Feb 2021) and PM2.5 and O3 in P2 (March-May 2021). Owing to chemical coupling, across all six monitoring stations, O3 maintained an inverse relationship with NO2 throughout the COVID-19 phases in Delhi. The city dwellers had health risks also due to PM pollution at varying degrees, indicated by high hazard quotients (HQs), requiring lowering of air pollution concentrations on an urgent basis. [ FROM AUTHOR] Copyright of Journal of Applied & Natural Science is the property of Applied & Natural Science Foundation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Data-Driven COVID-19 Vaccine Development for Janssen

The COVID-19 pandemic has spurred extensive vaccine research worldwide. One crucial part of vaccine development is the phase III clinical trial that assesses the vaccine for safety and efficacy in the prevention of COVID-19. In this work, we enumerate the first successful implementation of using machine learning models to accelerate phase III vaccine trials, working with the single-dose Johnson & Johnson vaccine to predictively select trial sites with naturally high incidence rates ("hotspots"). We develop DELPHI, a novel, accurate, policy-driven machine learning model that serves as the basis of our predictions. During the second half of 2020, the DELPHI-driven site selection identified hotspots with more than 90% accuracy, shortened trial duration by six to eight weeks (approximately 33%), and reduced enrollment by 15,000 (approximately 25%). In turn, this accelerated time to market enabled Janssen's vaccine to receive its emergency use authorization and realize its public health impact earlier than expected. Several geographies identified by DELPHI have since been the first areas to report variants of concern (e.g., Omicron in South Africa), and thus DELPHI's choice of these areas also produced early data on how the vaccine responds to new threats. Johnson & Johnson has also implemented a similar approach across its business including supporting trial site selection for other vaccine programs, modeling surgical procedure demand for its Medical Device unit, and providing guidance on return-to-work programs for its 130,000 employees. Continued application of this methodology can help shorten clinical development and change the economics of drug development by reducing the level of risk and cost associated with investing in novel therapies. This will allow Johnson & Johnson and others to enable more effective delivery of medicines to patients.

Travel route planning method to avoid epidemic hot-spots in the post-epidemic era

The Chinese government adhered to the "dynamic clearance” epidemic prevention strategy from August 2021 to December 7, 2022, during the post-epidemic era (this study started in March 2022 and ended in September 2022). People are gradually resuming their daily routines, and demand for travel is rising again. Nonetheless, the epidemic occasionally breaks out on a smaller scale, causing social concern. As a social reaction, the essential issue is how to avoid COVID-19 hot-spots effectively by offering secure travel options for local residents who tend to travel privately. Two travel route planning models are proposed to avoid COVID-19 hot-spots based on the invalid road sections which are affected by epidemic. Specifically, the static model aims at generating the shortest travel distance after detours, with the constraint of avoiding COVID-19 hot-spots;the dynamic model takes real-time data into account, which includes epidemic risk levels, road grades, and real-time traffic information on road selection. Shenzhen, China, is illustrated as an example of the research area in this paper. To assess the effectiveness and efficiency of the suggested approaches, data regarding the road network, the prevalence of epidemics, and traffic congestion are collected. The experimental results demonstrate that 1) the proposed two route planning models can effectively bypass areas with high levels of epidemic risk. 2) The static route planning model increases the travel distance by 12.24% and 13.03%, while the dynamic route planning model increases the travel distance by 24.33% and 27.69% compared with the conventional shortest route, given the same origin and destination and the same impact radii of the COVID-19 hot-spots (300 and 500 m respectively). When taking detour routes to avoid COVID-19 hot-spots, the average increase in trip distance does not surpass 50%, which is acceptable psychologically for travelers. 3) The static travel route planning model is suitable for the severe epidemic situation for it can strictly avoid the epidemic hot-spots;The dynamic travel route planning model is applicable to the situation where the epidemic situation is relatively mild. Ultimately, the route planning models can be utilized to develop a framework to provide travelers with detour options, which would make a practical difference to ensure travelers' safety during traveling and contribute to preventing the spread of the epidemic. © 2023 The Author(s)

An Analysis of Public Service Satisfaction of Tourists at Scenic Spots: The Case of Xiamen City

The outbreak of the COVID-19 epidemic has greatly hindered the development of the tourism industry. It is urgent for the city to improve the quality of public service in scenic spots, so as to attract more tourists and achieve sustainable development. With a literature review and reference to some guidance, the evaluation indicator system of public service satisfaction of scenic spots was constructed based on the analytic hierarchy process. Then, we distributed two questionnaires to complete the study. The first is the expert questionnaire for the evaluation indicator system. We used YAAHP software to process the questionnaire data and calculated the weight of each indicator, which provided a basis for the following analysis. The second is the questionnaire distributed to tourists of Xiamen. Then, we used the fuzzy comprehensive evaluation method to analyze the satisfaction of public services in scenic spots. The outcomes show that tourists are overall satisfied with the public services of scenic spots in Xiamen. However, there are still some problems, such as lagging information service, inadequate security, and supervision in the scenic spot. Therefore, the city and scenic spots should improve the level of smart tourism service, strengthen the construction of hardware and software facilities, and focus on the protection of tourists' rights and interests. © 2023 by the authors.

A pilot study: Validation of dried blood spots (DBS) to assess SARS-CoV2 IgG antibody immunoassays in underserved minority population.

Underserved, low-income, rural and certain migrant populations have greater risks and higher incidences of Coronavirus disease 2019 (COVID-19) than more privileged populations. Current in-person testing methods have limitations, namely exposure risk, a requirement of accessible transportation to healthcare facilities, and economic barriers. Dried blood spots (DBS) samples are widely used for diagnostics in many infectious diseases including Rabies, HIV, Ebola viruses and newborn screening. Our goal was to determine the accuracy and reliability of measuring COVID-19 IgG in DBS compared to paired plasma samples in a population with known infection status and then apply this method to screen an underserved minority population with high risk for COVID-9 infection (unvaccinated, pregnant, low income, Hispanic women). To optimize the assay, we tested 22 nonpregnant women, 12 with positive prior PCR testing for SARS-CoV2 infection and 10 with negative PCR results. After the assay was optimized, we tested the assay in a vulnerable population with a high risk for infection, who were 52 Hispanic pregnant women without prior PCR testing or vaccination. DBS assay results in both groups showed an agreement of 100% with paired plasma samples. The availability of a DBS assay could enable people who may not have access or transportation to healthcare facilities to use DBS as a COVID-19 testing vehicle.

Emerging trends and hot spots in subacute thyroiditis research from 2001 to 2022: A bibliometric analysis.

Background: Subacute thyroiditis (SAT) is the most prevalent self-limiting thyroid disease that causes pain, accounting for about 5% of all clinical thyroid disorders. Numerous clinically noteworthy results have been published in this area over the last 20 years. However, no article has comprehensively assessed the relevant literature yet. We conducted a bibliometric analysis of SAT to provide light on the dynamic nature of scientific advancement and aid researchers in gaining a global perspective while examining research core themes and hotspots. Methods: SAT-related articles and reviews from 2001 to 2022 were retrieved from the Science Citation Index-Expanded of Web of Science Core Collection (WoSCC). We analyzed current research trends and hotspots in this area using CiteSpace and Vosviewer. Results: A total of 568 studies associated with SAT research were published in 282 academic journals by 2,473 authors in 900 institutions from 61 countries/regions. The United States was a crucial link in inter-country/region collaboration and was the most frequently involved country in international cooperation. The University of Missouri System was the top organization, and Braley-Mullen H. was the most productive researcher. Thyroid published the most papers, with 36 publications. The most co-cited article was "Clinical features and outcome of subacute thyroiditis in an incidence cohort: Olmsted County, Minnesota, study" (by Fatourechi V., 2003). The clustered network and timeline view of keywords showed that the prevalence, diagnosis, and treatment of SAT were the research core themes during the past 20 years. Analysis of keyword bursts indicated that the clinical characteristic and the influence of COVID-19 on SAT appeared to be the current research hotspots. Conclusion: This bibliometric analysis conducted a thorough review of the SAT research. The clinical characteristics and the genetic background of SAT under the influence of COVID-19 are current research hotspots. However, there is still a need for further study and global collaboration. Our findings can aid researchers in understanding the current status of SAT research and immediately pinpoint new directions for further investigation.

The Role of Functional Urban Areas in the Spread of COVID-19 Omicron (Northern Spain).

This study focuses on the space-time patterns of the COVID-19 Omicron wave at a regional scale, using municipal data. We analyze the Basque Country and Cantabria, two adjacent regions in the north of Spain, which between them numbered 491,816 confirmed cases in their 358 municipalities from 15th November 2021 to 31st March 2022. The study seeks to determine the role of functional urban areas (FUAs) in the spread of the Omicron variant of the virus, using ESRI Technology (ArcGIS Pro) and applying intelligence location methods such as 3D-bins and emerging hot spots. Those methods help identify trends and types of problem area, such as hot spots, at municipal level. The results demonstrate that FUAs do not contain an over-concentration of COVID-19 cases, as their location coefficient is under 1.0 in relation to population. Nevertheless, FUAs do have an important role as drivers of spread in the upward curve of the Omicron wave. Significant hot spot patterns are found in 85.0% of FUA area, where 98.9% of FUA cases occur. The distribution of cases shows a spatially stationary linear correlation linked to demographically progressive areas (densely populated, young profile, and with more children per woman) which are well connected by highways and railroads. Based on this research, the proposed GIS methodology can be adapted to other case studies. Considering geo-prevention and WHO Health in All Policies approaches, the research findings reveal spatial patterns that can help policymakers in tackling the pandemic in future waves as society learns to live with the virus.

Visual Analysis of Psychological Resilience Research Based on Web of Science Database.

Background: The importance of psychological resilience that people show in coping with stress and adversity is prominent, but few studies have used rigorous bibliometric tools to analyze the knowledge structure and distribution of psychological resilience research. Objective: The purpose of this study was to sort out and summarize the previous studies on psychological resilience by using bibliometrics. Specifically, the time distribution of psychological resilience research was determined by publication trend, the power distribution was determined by the distribution of countries, authors, institutions and journals, the hot research spots were analyzed according to the results of keyword cluster analysis, and the research frontier was explored according to the results of burst keywords. Methods: CiteSpace5.8.R3 was used to analyze the literatures on psychological resilience collected in Web of Science core Collection database from January 1, 2010, to June 16, 2022. Results: A total of 8462 literatures were included after screening. Research on psychological resilience has been on the rise in recent years. The United States had made a high contribution in this field. Robert H Pietrzak, George A Bonanno, Connor KM and others were highly influential. J Pers Soc Psychol has the highest citation frequency and centrality. The research hot spots focus on five aspects: study on psychological resilience related to COVID-19 pandemic, influencing factors of psychological resilience, psychological resilience related to PTSD, study on psychological resilience of special population, and the molecular biology and genetic basis of psychological resilience. Psychological resilience related to COVID-19 pandemic was the most cutting-edge research aspect. Conclusion: The current situation and trend of psychological resilience research were found in this study, which may be used to identify more hot issues and explore new research directions in this field.

Ultrasound Placental Remodeling Patterns and Pathology Characteristics in Patients with History of Mild SARS-CoV-2 Infection during Pregnancy.

Introduction: This research aims to describe a progressive pattern of ultrasound placental remodeling in patients with a history of SARS-CoV-2 infection during pregnancy. Materials and Methods: This was a longitudinal, cohort study which enrolled 23 pregnant women with a history of former mild SARS-CoV-2 infection during the current pregnancy. Four obstetricians analyzed placental ultrasound images from different gestational ages following COVID infection and identified the presence and degree of remodeling. We assessed the inter-rater agreement and the interclass correlation coefficients. Pathology workup included placental biometry, macroscopic and microscopic examination. Results: Serial ultrasound evaluation of the placental morphology revealed a progressive pattern of placental remodeling starting from 30-32 weeks of gestation towards term, occurring approximately 8-10 weeks after the SARS-CoV-2 infection. Placental changes-the "starry sky" appearance and the "white line" along the basal plate-were identified in all cases. Most placentas presented normal subchorionic perivillous fibrin depositions and focal stem villi perivillous fibrin deposits. Focal calcifications were described in only 13% of the cases. Conclusions: We identified two ultrasound signs of placental remodeling as potential markers of placental viral shedding following mild SARS-CoV-2. The most likely pathology correspondence for the imaging aspect is perivillous and, respectively, massive subchorionic fibrin deposits identified in most cases.

The effects of community-infused problem-oriented policing in crime hot spots based on police data: a randomized controlled trial.

Objectives: This randomized controlled trial (RCT) assessed the effectiveness of a community-infused problem-oriented policing (CPOP) intervention on reducing property/violent crime. Methods: In two mid-Atlantic cities, a total of 102 crime hot spots were randomly assigned to receive CPOP or standard patrol. Analyses examine changes in crime the year before, during, and one year after the intervention. We used hierarchical Poisson regression models. Results: We found no main effects for the CPOP intervention on property and violent crimes in either site. In site B, the violent crime count in low treatment hot spots was 200% higher than controls post-intervention but this likely reflected officers paying less attention to treatment locations with lower levels of crime. Conclusions: Our results suggest that CPOP was not effective in the unusual context of the COVID-19 pandemic and post-George Floyd killing. Given the challenges of implementing CPOP during this unique time, caution is needed in interpreting these findings.

Modified ARCHITECT® serologic assays enable plasma-level performance from dried blood spot samples.

Dried blood spots (DBSs) provide an alternative sample input for serologic testing. We evaluated DBSs for the ARCHITECT® hepatitis B surface antigen (HBsAg) NEXT, hepatitis B e-antigen (HBeAg), anti-hepatitis B core antigen (anti-HBc II), HIV antigen/antibody (Ag/Ab) Combo and AdviseDx SARS-CoV-2 IgG II assays. Assay performance with DBSs was assessed with or without assay modification and compared with on-market assay with plasma samples. DBS stability was also determined. HBsAg NEXT and HIV Ag/Ab Combo assays using DBSs showed sensitivity and specificity comparable to that of on-market assays. Modified HBeAg, anti-HBc II and SARS-CoV-2 IgG II DBS assays achieved performance comparable to on-market assays. Use of DBSs as input for high-throughput serologic assays is expected to have significant implications for improving population surveillance and increasing access to diagnostic testing.

Evaluation of serological assays for SARS-CoV-2 antibody testing from dried blood spots collected from cohorts with prior SARS-CoV-2 infection.

Background: Dried blood spot (DBS) specimens are a useful serosurveillance tool particularly in hard-to-reach populations but their application for detecting SARS-CoV-2 infection is poorly characterised. Objectives: To compare detection of naturally acquired SARS-CoV-2 antibodies in paired DBS and serum specimens using commercially available serological immunoassays. Study Design: Specimens were collected through St Vincent's Hospital observational post COVID-19 cohort study (ADAPT). Laboratory spotted DBS from venepuncture were initially tested on seven assays, a DBS validation completed on three with clinically collected fingerstick DBSs tested on one. Results: Sensitivity for Euroimmun nucleocapsid (NCP) IgG ELISA from laboratory spotted DBS (n=145), Euroimmun spike, IgG ELISA from laboratory spotted DBS (n=161), and Binding Site total antibody ELISA from clinically collected fingerstick DBS (n=391) was 100% (95% CI: 95.8-100%), 100% (95% CI: 95.8-100%) and 92.9% (95% CI: 89.5-95.5%), respectively. Specificity was 66.2% (95% CI: 53.6-77.0%), 96% (95% CI: 88.7-99.1%) and 98.8% (95% CI: 93.3-99.9%), respectively. All three assays' results displayed a strong positive correlation between DBS compared to paired serum. Conclusions: The Binding Site™ spike total antibody and Euroimmun™ spike IgG ELISAs provided good analytical performance, demonstrating that DBS specimens could facilitate specimen collection in the epidemiological surveillance of SARS-CoV-2 infection. This is highly applicable in populations and settings where venepuncture is problematic (including community based regional/remote settings, nursing homes, prisons, and schools).