Effect of Vaccination against SARS-CoV-2 on Long COVID-19: A Narrative Review.

Vaccines against SARS-CoV-2 have saved millions of lives and played an important role in containing the COVID-19 pandemic. Vaccination against SARS-CoV-2 is also associated with reduced disease severity and, perhaps, with COVID-19 symptom burden. In this narrative review, we present, in a clinically relevant question-and-answer manner, the evidence regarding the association between vaccination against SARS-CoV-2 and long COVID-19. We discuss how the mechanism of action of vaccines could interplay with the pathophysiology of post-COVID-19 condition. Furthermore, we describe how specific factors, such as the number of vaccine doses and the type of SARS-CoV-2 variants, may affect post-COVID-19 condition. We also discuss the role of timing for vaccination in relation to the onset of long COVID-19 symptoms, as it seems to affect the frequency and severity of the condition. Additionally, we describe the potential modifying effect of age, as well as the association of type and level of immune response with long COVID-19. We also describe how system-specific long COVID-19 sequelae, namely neurocognitive-psychologic symptoms and cardiovascular pathology, could be altered by vaccination. Last, we address the question of whether seasonal influenza vaccination has a meaningful impact on the frequency of long COVID-19.

Non-Communicable Diseases: The Invisible Epidemic.

Historically, communicable diseases, such as HIV/AIDS, viral hepatitis, malaria, poliomyelitis, tuberculosis, influenza and, more recently, the coronavirus disease 2019, have been at the center of global health concerns and initiatives, as they are transmitted from one person to another with a variety of ways, easily spread across national borders, and threaten the lives of millions of people all over the globe [...].

Performance of Antigen Detection Tests for SARS-CoV-2: A Systematic Review and Meta-Analysis.

Coronavirus disease 2019 (COVID-19) initiated global health care challenges such as the necessity for new diagnostic tests. Diagnosis by real-time PCR remains the gold-standard method, yet economical and technical issues prohibit its use in points of care (POC) or for repetitive tests in populations. A lot of effort has been exerted in developing, using, and validating antigen-based tests (ATs). Since individual studies focus on few methodological aspects of ATs, a comparison of different tests is needed. Herein, we perform a systematic review and meta-analysis of data from articles in PubMed, medRxiv and bioRxiv. The bivariate method for meta-analysis of diagnostic tests pooling sensitivities and specificities was used. Most of the AT types for SARS-CoV-2 were lateral flow immunoassays (LFIA), fluorescence immunoassays (FIA), and chemiluminescence enzyme immunoassays (CLEIA). We identified 235 articles containing data from 220,049 individuals. All ATs using nasopharyngeal samples show better performance than those with throat saliva (72% compared to 40%). Moreover, the rapid methods LFIA and FIA show about 10% lower sensitivity compared to the laboratory-based CLEIA method (72% compared to 82%). In addition, rapid ATs show higher sensitivity in symptomatic patients compared to asymptomatic patients, suggesting that viral load is a crucial parameter for ATs performed in POCs. Finally, all methods perform with very high specificity, reaching around 99%. LFIA tests, though with moderate sensitivity, appear as the most attractive method for use in POCs and for performing seroprevalence studies.

Effect of vaccination on SARS-CoV-2 reinfection risk: a case-control study in the Republic of Cyprus.

OBJECTIVES: We explored the effectiveness of COVID-19 vaccines in preventing reinfection in the Republic of Cyprus. STUDY DESIGN: This was a matched case-control study (1:2). METHODS: Cases were adults with a first episode of SARS-CoV-2 infection in 2020 and a second episode (i.e. reinfection) between June and August 2021. Controls were adults with only one infection episode in 2020 (i.e. not reinfected). Matching was performed by age, gender, and week of diagnosis for the first episode. The reinfection date of a case was applied to the matched controls for estimating full or partial vaccination status. Cases and controls were classified as unvaccinated, partially vaccinated (i.e. vaccination series not completed or final dose received ≤14 days before the reinfection date), or fully vaccinated (i.e. final dose received >14 days before the reinfection date). Conditional logistic regression was performed to calculate odds ratios and 95% confidence intervals for full or partial vaccination, against no vaccination, between controls and cases. RESULTS: This study showed that controls were more likely to be vaccinated (odds ratio for full vaccination: 5.51, 95% confidence interval: 2.43-12.49) than cases. CONCLUSIONS: This finding answers a pressing question of the public and supports the offer of vaccination to people with previous SARS-CoV-2 infection.

Emerging Zoonotic Infections, Social Processes and Their Measurement and Enhanced Surveillance to Improve Zoonotic Epidemic Responses: A "Big Events" Perspective.

Zoonotic epidemics and pandemics have become frequent. From HIV/AIDS through COVID-19, they demonstrate that pandemics are social processes as well as health occurrences. The roots of these pandemics lie in changes in the socioeconomic interface between humanity and non-human host species that facilitate interspecies transmission. The degree to which zoonoses spread has been increased by the greater speed and extent of modern transportation and trade. Pre-existing sociopolitical and economic structures and conflicts in societies also affect pathogen propagation. As an epidemic develops, it can itself become a social and political factor, and change and interact with pre-existing sociobehavioral norms and institutional structures. This paper uses a "Big Events" approach to frame these processes. Based on this framework, we discuss how social readiness surveys implemented both before and during an outbreak might help public health predict how overall systems might react to an epidemic and/or to disease control measures, and thus might inform interventions to mitigate potential adverse outcomes or possibly preventing outbreaks from developing into epidemics. We conclude by considering what "pathways measures", in addition to those we and others have already developed, might usefully be developed and validated to assist outbreak and epidemic disease responses.

Circulating IgG Levels in SARS-CoV-2 Convalescent Individuals in Cyprus.

Long-term persistence and the heterogeneity of humoral response to SARS-CoV-2 have not yet been thoroughly investigated. The aim of this work is to study the production of circulating immunoglobulin class G (IgG) antibodies against SARS-CoV-2 in individuals with past infection in Cyprus. Individuals of the general population, with or without previous SARS-CoV-2 infection, were invited to visit the Biobank at the Center of Excellence in Biobanking and Biomedical Research of the University of Cyprus. Serum IgG antibodies were measured using the SARS-CoV-2 IgG and the SARS-CoV-2 IgG II Quant assays of Abbott Laboratories. Antibody responses to SARS-CoV-2 were also evaluated against participants' demographic and clinical data. All statistical analyses were conducted in Stata 16. The median levels of receptor binding domain (RBD)-specific IgG in 969 unvaccinated individuals, who were reportedly infected between November 2020 and September 2021, were 432.1 arbitrary units (AI)/mL (interquartile range-IQR: 182.4-1147.3). Higher antibody levels were observed in older participants, males, and those who reportedly developed symptoms or were hospitalized. The RBD-specific IgG levels peaked at three months post symptom onset and subsequently decreased up to month six, with a slower decay thereafter. IgG response to the RBD of SARS-CoV-2 is bi-phasic with considerable titer variability. Levels of IgG are significantly associated with several parameters, including age, gender, and severity of symptoms.

Gaps in Knowledge About SARS-CoV-2 & COVID-19 Among University Students Are Associated With Negative Attitudes Toward People With COVID-19: A Cross-Sectional Study in Cyprus.

University students represent a highly active group in terms of their social activity in the community and in the propagation of information on social media. We aimed to map the knowledge, attitudes, and perceptions of University students in Cyprus about severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and Coronavirus disease 2019 (COVID-19) to guide targeted future measures and information campaigns. We used a cross-sectional online survey targeting all students in conventional, not distance-learning, programs in five major universities in the Republic of Cyprus. Students were invited to participate through the respective Studies and Student Welfare Office of each institution. The survey was made available in English and Greek on REDCap. Participation was voluntary and anonymous. The questionnaire was developed based on a consensus to cover the main factual information directed by official channels toward the general public in Cyprus at the time of the survey. In addition to sociodemographic information (N = 8), the self-administered questionnaire consisted of 19 questions, assessing the knowledge regarding the characteristics of SARS-CoV-2 and COVID-19, infection prevention and control measures (N = 10), perceptions related to COVID-19, for instance, whether strict travel measures are necessary (N = 4), and attitudes toward a hypothetical person infected (N = 2). Furthermore, participants were asked to provide their own assessment of their knowledge about COVID-19 and specifically with regard to the main symptoms and ways of transmission (N = 3). The number of students who completed the survey was 3,641 (41% studying Health/Life Sciences). Amongst them, 68.8% responded correctly to at least 60% of knowledge-related questions. Misconceptions were identified in 30%. Only 29.1% expressed a positive attitude toward a hypothetical person with COVID-19 without projecting judgment (9.2%) or blame (38%). Odds of expressing a positive attitude increased by 18% (95% CI 13-24%; p < 0.001) per unit increase in knowledge. Postgraduate level education was predictive of better knowledge (odds ratio (OR) 1.81; 95% CI 1.34-2.46; p < 0.001 among doctoral students] and positive attitude [OR 1.35; 95% CI 1.01-1.80; p = 0.04). In this study, we show that specific knowledge gaps and misconceptions exist among University students about SARS-CoV-2 and COVID-19 and their prevalence is associated with negative attitudes toward people with COVID-19. Our findings highlight the integrated nature of knowledge and attitude and suggest that improvements to the former could contribute to improvements in the latter.

Effect of public health interventions during the first epidemic wave of COVID-19 in Cyprus: a modelling study.

BACKGROUND: Cyprus addressed the first wave of SARS CoV-2 (COVID-19) by implementing non-pharmaceutical interventions (NPIs). The aims of this study were: a) to estimate epidemiological parameters of this wave including infection attack ratio, infection fatality ratio, and case ascertainment ratio, b) to assess the impact of public health interventions and examine what would have happened if those interventions had not been implemented. METHODS: A dynamic, stochastic, individual-based Susceptible-Exposed-Infected-Recovered (SEIR) model was developed to simulate COVID-19 transmission and progression in the population of the Republic of Cyprus. The model was fitted to the observed trends in COVID-19 deaths and intensive care unit (ICU) bed use. RESULTS: By May 8th, 2020, the infection attack ratio was 0.31% (95% Credible Interval [CrI]: 0.15, 0.54%), the infection fatality ratio was 0.71% (95% CrI: 0.44, 1.61%), and the case ascertainment ratio was 33.2% (95% CrI: 19.7, 68.7%). If Cyprus had not implemented any public health measure, the healthcare system would have been overwhelmed by April 14th. The interventions averted 715 (95% CrI: 339, 1235) deaths. If Cyprus had only increased ICU beds, without any social distancing measure, the healthcare system would have been overwhelmed by April 19th. CONCLUSIONS: The decision of the Cypriot authorities to launch early NPIs limited the burden of the first wave of COVID-19. The findings of these analyses could help address the next waves of COVID-19 in Cyprus and other similar settings.

The Procoagulant Effect of COVID-19 on the Thrombotic Risk of Patients with Hip Fractures Due to Enhanced Clot Strength and Fibrinolysis Shutdown.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) in patients with hip fractures is associated with increased incidence of venous thromboembolism (VTE). The purpose of this study was to evaluate the hemostatic alterations of COVID-19 that are associated with a higher thrombotic risk using rotational thromboelastometry (ROTEM). METHODS: A retrospective observational study was performed including 20 COVID-19 patients with hip fractures. To compare the coagulopathy of patients with mild COVID-19 and hip fractures with the coagulopathy associated with each of these two conditions separately, we used two previously recruited groups of patients; 198 hip fracture patients without COVID-19 and 21 COVID-19 patients without hip fractures. The demographics, clinical parameters, conventional coagulation parameters and ROTEM findings of the three groups were analyzed and compared. RESULTS: COVID-19 hip fracture patients had higher amplitude of clot firmness at 10 min (p < 0.001), higher alpha angle (p < 0.001), higher lysis index at 60 min (p < 0.001), and shorter clot formation time (p < 0.001) than non-COVID-19 hip fracture patients, indicating increased clot strength and impaired fibrinolysis due to COVID-19. The value of lysis index at 60 min (99%) in COVID-19 patients with hip fractures was consistent with fibrinolysis shut down. Multivariable linear regression analysis further confirmed that COVID-19 resulted in increased amplitude of clot firmness at 10 min (p < 0.001), increased maximum clot firmness (p < 0.001), increased lysis index at 60 min (p < 0.001) and increased alpha angle (p < 0.001), but significantly shortened clot formation time (p < 0.001). DISCUSSION: The higher thrombotic risk in COVID-19 patients with hip fractures is characterized by increased clot strength and fibrinolysis shutdown, as shown by ROTEM findings. Further prospective studies are warranted to evaluate the need for modification of thromboprophylaxis to balance the hemostatic derangements of COVID-19 patients with hip fractures.

Pitfalls and perils of survival analysis under incorrect assumptions: the case of COVID-19 data. / Escollos y peligros del análisis de supervivencia bajo supuestos incorrectos: el caso de los datos de COVID-19

Non-parametric survival analysis has become a very popular statistical method in current medical research. However, resorting to survival analysis when its fundamental assumptions are not fulfilled can severely bias the results. Currently, hundreds of clinical studies are using survival methods to investigate factors potentially associated with the prognosis of coronavirus disease 2019 (COVID-19) and test new preventive and therapeutic strategies. In the pandemic era, it is more critical than ever to base decision-making on evidence and rely on solid statistical methods, but this is not always the case. Serious methodological errors have been identified in recent seminal studies about COVID-19: One reporting outcomes of patients treated with remdesivir and another one on the epidemiology, clinical course, and outcomes of critically ill patients. High-quality evidence is essential to inform clinicians about optimal COVID-19 therapies and policymakers about the true effect of preventive measures aiming to tackle the pandemic. Though timely evidence is needed, we should encourage the appropriate application of survival analysis methods and careful peer-review to avoid publishing flawed results, which could affect decision-making. In this paper, we recapitulate the basic assumptions underlying non-parametric survival analysis and frequent errors in its application and discuss how to handle data on COVID-19.

El análisis de supervivencia no paramétrico se ha convertido en un método estadístico muy popular en la investigación médica actual. Sin embargo, recurrir al análisis de supervivencia cuando no se cumplen sus supuestos fundamentales puede sesgar gravemente los resultados. Actualmente, cientos de estudios clínicos están utilizando métodos de supervivencia para investigar factores potencialmente asociados con el pronóstico de la enfermedad por coronavirus 2019 (COVID-19) y probar nuevas estrategias preventivas y terapéuticas. En la era de la pandemia, es más importante que nunca basar la toma de decisiones en pruebas y confiar en métodos estadísticos sólidos, pero no siempre es así. Se han identificado errores metodológicos graves en estudios seminales recientes sobre COVID-19: uno que informa los resultados de los pacientes tratados con remdesivir y otro sobre la epidemiología, el curso clínico y los resultados de los pacientes en estado crítico. La evidencia de alta calidad es esencial para informar a los médicos sobre las terapias COVID-19 óptimas y a los legisladores sobre el verdadero efecto de las medidas preventivas destinadas a abordar la pandemia. Aunque se necesita evidencia oportuna, debemos fomentar la aplicación adecuada de métodos de análisis de supervivencia y una revisión cuidadosa por pares para evitar la publicación de resultados defectuosos, que podrían afectar la toma de decisiones. En este artículo, recapitulamos los supuestos básicos que subyacen al análisis de supervivencia no paramétrico y los errores frecuentes en su aplicación y discutimos cómo manejar los datos sobre COVID-19.

Beyond the physical risk: Psychosocial impact and coping in healthcare professionals during the COVID-19 pandemic.

AIMS AND OBJECTIVES: This study aimed to examine the psychosocial impact and identify risk factors for poor psychosocial outcomes in healthcare professionals during the Coronavirus disease 2019 (COVID-19) pandemic in Cyprus. BACKGROUND: Healthcare professionals are in the forefront of the COVID-19 pandemic facing an unprecedented global health crisis, which can have consequences on their psychosocial health. There is a need to identify risk factors for poor psychosocial outcomes to inform the design of tailored psychological interventions. DESIGN: Cross-sectional online study. METHODS: A total of 1071 healthcare professionals completed self-report questionnaires. Measures included sociodemographic information, COVID-19-related characteristics, quality of life (Brief World Health Organization Quality of Life; WHOQOL-Bref), anxiety (Generalized Anxiety Disorder-7; GAD-7), depression (Patient Health Questionnaire-8; PHQ-8), occupational burnout (Copenhagen Burnout Inventory; CBI), and coping (Brief Coping Orientation to Problems Experienced; Brief COPE). This article follows the STROBE reporting guidelines. RESULTS: The prevalence of moderate to severe anxiety and clinically significant depression was 27.6% and 26.8%, respectively. Significant risk factors for poor psychological outcomes included being female, being a nurse or doctor (vs non-medical professional), working in frontline units (inpatient, intensive care), perceptions of inadequate workplace preparation to deal with the pandemic, and using avoidance coping. Depression and occupational burnout were significant risk factors for poor quality of life. CONCLUSION: The findings suggest several individual, psychosocial, and organisational risk factors for the adverse psychological outcomes observed in healthcare professionals during the COVID-19 pandemic. RELEVANCE TO CLINICAL PRACTICE: This study highlights the urgent need for screening for anxiety and depression and psychological interventions to combat an imminent mental health crisis in healthcare professionals during the COVID-19 pandemic. Pandemic response protocols and public health initiatives aiming to improve and prevent mental health problems in healthcare professionals during the current and future health crises, need to account for the various factors at play.

Big Events theory and measures may help explain emerging long-term effects of current crises.

Big Events are periods during which abnormal large-scale events like war, economic collapse, revolts, or pandemics disrupt daily life and expectations about the future. They can lead to rapid change in health-related norms, beliefs, social networks and behavioural practices. The world is undergoing such Big Events through the interaction of COVID-19, a large economic downturn, massive social unrest in many countries, and ever-worsening effects of global climate change. Previous research, mainly on HIV/AIDS, suggests that the health effects of Big Events can be profound, but are contingent: Sometimes Big Events led to enormous outbreaks of HIV and associated diseases and conditions such as injection drug use, sex trading, and tuberculosis, but in other circumstances, Big Events did not do so. This paper discusses and presents hypotheses about pathways through which the current Big Events might lead to better or worse short and long term outcomes for various health conditions and diseases; considers how pre-existing societal conditions and changing 'pathway' variables can influence the impact of Big Events; discusses how to measure these pathways; and suggests ways in which research and surveillance might be conducted to improve human capacity to prevent or mitigate the effects of Big Events on human health.

Modeling the first wave of Covid-19 pandemic in the Republic of Cyprus.

We present different data analytic methodologies that have been applied in order to understand the evolution of the first wave of the Coronavirus disease 2019 in the Republic of Cyprus and the effect of different intervention measures that have been taken by the government. Change point detection has been used in order to estimate the number and locations of changes in the behaviour of the collected data. Count time series methods have been employed to provide short term projections and a number of various compartmental models have been fitted to the data providing with long term projections on the pandemic's evolution and allowing for the estimation of the effective reproduction number.

Use of wearable sensors to assess compliance of asthmatic children in response to lockdown measures for the COVID-19 epidemic.

Between March and April 2020, Cyprus and Greece health authorities enforced three escalated levels of public health interventions to control the COVID-19 pandemic. We quantified compliance of 108 asthmatic schoolchildren (53 from Cyprus, 55 from Greece, mean age 9.7 years) from both countries to intervention levels, using wearable sensors to continuously track personal location and physical activity. Changes in 'fraction time spent at home' and 'total steps/day' were assessed with a mixed-effects model adjusting for confounders. We observed significant mean increases in 'fraction time spent at home' in Cyprus and Greece, during each intervention level by 41.4% and 14.3% (level 1), 48.7% and 23.1% (level 2) and 45.2% and 32.0% (level 3), respectively. Physical activity in Cyprus and Greece demonstrated significant mean decreases by - 2,531 and - 1,191 (level 1), - 3,638 and - 2,337 (level 2) and - 3,644 and - 1,961 (level 3) total steps/day, respectively. Significant independent effects of weekends and age were found on 'fraction time spent at home'. Similarly, weekends, age, humidity and gender had an independent effect on physical activity. We suggest that wearable technology provides objective, continuous, real-time location and activity data making possible to inform in a timely manner public health officials on compliance to various tiers of public health interventions during a pandemic.

SARS-CoV-2 Molecular Transmission Clusters and Containment Measures in Ten European Regions during the First Pandemic Wave.

BACKGROUND: The spatiotemporal profiling of molecular transmission clusters (MTCs) using viral genomic data can effectively identify transmission networks in order to inform public health actions targeting SARS-CoV-2 spread. METHODS: We used whole genome SARS-CoV-2 sequences derived from ten European regions belonging to eight countries to perform phylogenetic and phylodynamic analysis. We developed dedicated bioinformatics pipelines to identify regional MTCs and to assess demographic factors potentially associated with their formation. RESULTS: The total number and the scale of MTCs varied from small household clusters identified in all regions, to a super-spreading event found in Uusimaa-FI. Specific age groups were more likely to belong to MTCs in different regions. The clustered sequences referring to the age groups 50-100 years old (y.o.) were increased in all regions two weeks after the establishment of the lockdown, while those referring to the age group 0-19 y.o. decreased only in those regions where schools' closure was combined with a lockdown. CONCLUSIONS: The spatiotemporal profiling of the SARS-CoV-2 MTCs can be a useful tool to monitor the effectiveness of the interventions and to reveal cryptic transmissions that have not been identified through contact tracing.

Trends of Online Search of COVID-19 Related Terms in Cyprus.

Knowledge of trends in web searches provides useful information for various purposes, including responses to public health emergencies. This work aims to analyze the popularity of internet search queries for Coronavirus Disease 2019 (COVID-19) and COVID-19 symptoms in Cyprus. Query data for the term Coronavirus were retrieved from Google Trends website between 19 January and 30 June 2020. The study focused on Cyprus and the four most populated cities: Nicosia, Limassol, Larnaca, and Paphos. COVID-19 symptoms including fever, cough, sore throat, shortness of breath, and myalgia were considered in the analysis. Daily and weekly search volumes were described, and their correlation with the evolution of the COVID-19 pandemic and important announcements or events were examined. Three periods of interest peaks were identified in Cyprus. The highest interest in COVID-19-related terms was found in the city of Paphos. The most popular symptoms were fever and cough, and the symptom with the highest increase in popularity was myalgia. At the beginning of the pandemic, the search volume of COVID-19 grew substantially when governments, major organizations, and high-profile figures, globally and locally, made important announcements regarding COVID-19. Health authorities in Cyprus and elsewhere could benefit from constantly monitoring the online interest of the population in order to get timely information that could be used in public health planning and response.

Effect of early application of social distancing interventions on COVID-19 mortality over the first pandemic wave: An analysis of longitudinal data from 37 countries.

OBJECTIVES: To estimate the effect of early application of social distancing interventions on Covid-19 cumulative mortality during the first pandemic wave. METHODS: Ecological longitudinal study using multivariable negative binomial regression for panel data. Daily numbers of Covid-19 cases and deaths, and data on social distancing interventions, for the 37 member countries of the Organization for Economic Cooperation and Development (OECD) were analysed. RESULTS: Covid-19 cumulative mortality over the first pandemic wave varied widely across countries (range, 4.16 to 855 deaths per million population). On average, one-day delay in application of mass gatherings ban was associated with an adjusted increase in Covid-19 cumulative mortality by 6.97% (95% CI, 3.45 to 10.5), whilst a one-day delay in school closures was associated with an increase of 4.37% (95% CI, 1.58 to 7.17) over the study period. We estimated that if each country had enacted both interventions one week earlier, Covid-19 cumulative mortality could have been reduced by an average of 44.1% (95% CI, 20.2 to 67.9). CONCLUSIONS: Early application of mass gatherings ban and school closures in outbreak epicentres was associated with an important reduction in Covid-19 cumulative mortality during the first pandemic wave. These findings may support policy decision making.

Extensive Testing and Public Health Interventions for the Control of COVID-19 in the Republic of Cyprus between March and May 2020.

Coronavirus disease 2019 (COVID-19) has significantly affected the well-being of individuals worldwide. We herein describe the epidemiology of COVID-19 in the Republic of Cyprus during the first epidemic wave (9 March-3 May 2020). We analyzed surveillance data from laboratory-confirmed cases, including targeted testing and population screening. Statistical analyses included logistic regression. During the surveillance period, 64,136 tests (7322.3 per 100,000) were performed, 873 COVID-19 cases were diagnosed, and 20 deaths were reported (2.3%). Health-care workers (HCWs) represented 21.4% of cases. Overall, 19.1% of cases received hospital care and 3.7% required admission to Intensive Care Units. Male sex (adjusted Odds Ratio (aOR): 3.04; 95% Confidence Interval (CI): 1.97-4.69), increasing age (aOR: 1.56; 95%CI: 1.36-1.79), symptoms at diagnosis (aOR: 6.05; 95%CI: 3.18-11.50), and underlying health conditions (aOR: 2.08; 95%CI: 1.31-3.31) were associated with hospitalization. For recovered cases, the median time from first to last second negative test was 21 days. Overall, 119 primary cases reported 616 close contacts, yielding a pooled secondary attack rate of 12% (95%CI: 9.6-14.8%). Three population-based screening projects, and two projects targeting employees and HCWs, involving 25,496 people, revealed 60 positive individuals (0.2%). Early implementation of interventions with targeted and expanded testing facilitated prompt outbreak control on the island.

Antibody Tests in Detecting SARS-CoV-2 Infection: A Meta-Analysis.

The emergence of Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 made imperative the need for diagnostic tests that can identify the infection. Although Nucleic Acid Test (NAT) is considered to be the gold standard, serological tests based on antibodies could be very helpful. However, individual studies are usually inconclusive, thus, a comparison of different tests is needed. We performed a systematic review and meta-analysis in PubMed, medRxiv and bioRxiv. We used the bivariate method for meta-analysis of diagnostic tests pooling sensitivities and specificities. We evaluated IgM and IgG tests based on Enzyme-linked immunosorbent assay (ELISA), Chemiluminescence Enzyme Immunoassays (CLIA), Fluorescence Immunoassays (FIA), and the Lateral Flow Immunoassays (LFIA). We identified 38 studies containing data from 7848 individuals. Tests using the S antigen are more sensitive than N antigen-based tests. IgG tests perform better compared to IgM ones and show better sensitivity when the samples were taken longer after the onset of symptoms. Moreover, a combined IgG/IgM test seems to be a better choice in terms of sensitivity than measuring either antibody alone. All methods yield high specificity with some of them (ELISA and LFIA) reaching levels around 99%. ELISA- and CLIA-based methods perform better in terms of sensitivity (90%-94%) followed by LFIA and FIA with sensitivities ranging from 80% to 89%. ELISA tests could be a safer choice at this stage of the pandemic. LFIA tests are more attractive for large seroprevalence studies but show lower sensitivity, and this should be taken into account when designing and performing seroprevalence studies.