A Prototype for Interpretation of Sars-Cov-2 Tests Using Artificial Vision

Covid-19 has been declared a pandemic by the World Health Organization in March 2020, so science has been trying to help mitigate its effects from its various fields of study. Machine learning methods can play an important role in identifying test results that reveal whether an individual has the disease. This degree work presents a prototype based on computer vision and machine learning techniques to automatically detect SARS-CoV-2 serology tests. The goal of the prototype is to identify and classify the serology test cassette result by Immunoglobulin G and Immunoglobulin M indicators that are flagged after a test reaction time which is approximately 15 minutes. The results in the identification performed by the prototype are promising and ease its analysis, reducing the errors in the identification of the test and the interpretation of the results. The result is a prototype that allows to perform, simplify and improve the tasks of health professionals, which they must perform daily in the triage area. © 2022 IEEE.

The Role of Serology Testing in the Context of Immunization Policies for COVID-19 in Latin American Countries.

This review aims to explore the role and value of serology testing in the context of COVID-19 immunization policies in Latin American countries and the barriers and challenges to the adequate use and uptake of this tool. It builds on a review of the academic literature, evidence, and existing policies, and includes a multistage process of discussion and feedback by a group of five experts. Regional and country-level evidence and resources from five focus countries-Argentina, Brazil, Chile, Colombia, and Mexico-were collected and analyzed. This review contains an overview of (1) the impact of the SARS-CoV-2 pandemic, the variants of concern and current testing strategies, (2) the introduction of COVID-19 vaccination, (3) the potential use of serology testing to support immunization initiatives, (4) the current frameworks for the use of serology testing in the region, and (5) the barriers and challenges to implementing serology testing in the context of COVID-19 immunization policies, including a discussion on the potential actions required to address these barriers and facilitate the uptake of this strategy in the region. Stakeholders can use elements of this document to guide timely decision-making, raise awareness, and inspire further studies.

COVID-19 Antibody Tests: An Overview.

Novel coronavirus (nCoV) first emerged in Hubei province of China in December 2019. The virus initially known as 2019-nCoV was renamed to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses. The associated disease is known as coronavirus disease 2019 (COVID-19). As the COVID-19 pandemic has unfolded, interest has grown in antibody testing as a way to measure how far the infection has spread and to identify individuals who may be immune. Molecular diagnostic tests like polymerase chain reaction are developed rapidly, however they are not able to fulfill all the requirements of an epidemic reaction. Hence, to complement molecular diagnostic tests, serology tests emerged as a vital aspect of the overall response by confirming the presence of antibodies during the early stage of the infection. Antibody tests help in assessing herd immunity, data about the ongoing phase of infection, identifying potential donors for convalescent plasma therapy, etc. This review currently focuses on giving an overview about the antibody tests in SARS-CoV-2 infections.

Estimation of Covid-19 prevalence from serology tests: A partial identification approach.

We propose a partial identification method for estimating disease prevalence from serology studies. Our data are results from antibody tests in some population sample, where the test parameters, such as the true/false positive rates, are unknown. Our method scans the entire parameter space, and rejects parameter values using the joint data density as the test statistic. The proposed method is conservative for marginal inference, in general, but its key advantage over more standard approaches is that it is valid in finite samples even when the underlying model is not point identified. Moreover, our method requires only independence of serology test results, and does not rely on asymptotic arguments, normality assumptions, or other approximations. We use recent Covid-19 serology studies in the US, and show that the parameter confidence set is generally wide, and cannot support definite conclusions. Specifically, recent serology studies from California suggest a prevalence anywhere in the range 0%-2% (at the time of study), and are therefore inconclusive. However, this range could be narrowed down to 0.7%-1.5% if the actual false positive rate of the antibody test was indeed near its empirical estimate ( ∼ 0.5%). In another study from New York state, Covid-19 prevalence is confidently estimated in the range 13%-17% in mid-April of 2020, which also suggests significant geographic variation in Covid-19 exposure across the US. Combining all datasets yields a 5%-8% prevalence range. Our results overall suggest that serology testing on a massive scale can give crucial information for future policy design, even when such tests are imperfect and their parameters unknown.

COVID toes: where do we stand with the current evidence?

BACKGROUND: Numerous of cases of chilblains have been observed, mainly in young subjects with no or mild symptoms compatible with COVID-19. The pathophysiology of these lesions is still widely debated and an association with SARS-CoV-2 infection remains unconfirmed. OBJECTIVES: This paper focus on the unresolved issues about these COVID toes and in particular whether or not they are associated with COVID-19. ARGUMENTS: The temporal link between the outbreak of chilblains and the COVID-19 pandemic is a first suggests a link between the two events. Positive anti-SARS-CoV/SARS-CoV-2 immunostaining on skin biopsy of chilblains seem to confirm the presence of the virus in the lesions, but lack specificity and must be interpreted with caution. Conversely, RT-PCR and anti-SARS-CoV-2 serology were negative in the majority of patients with chilblains. Therefore, SARS-CoV-2 infection can be excluded, with relative certainty, even after accounting for possible lower immunization in mild/asymptomatic patients and for some differences in sensitivity/specificity between the tests used. Some authors hypothesize that chilblains could be the cutaneous expression of a strong type I interferon (IFN-I) response. High production of IFN-I is suggested to be associated with early viral control and may suppress antibody response. However, the absence of other cutaneous or extracutaneous symptoms as observed in other interferonopathies raises unanswered questions. To date, a direct link between chilblains and COVID-19 still seems impossible to confirm. A more indirect association due to lifestyle changes induced by lockdown is a possible explanation. Improvement of chilblains when protective measures were adopted and after lifting of lockdown, support this hypothesis. CONCLUSION: Conflicting current evidence highlights the need for systematic and repeated testing of larger numbers of patients and the need for valid follow-up data that take into consideration epidemic curves and evolution of lockdown measures.

Diagnosis of COVID-19 for controlling the pandemic: A review of the state-of-the-art.

To date, health organizations and countries around the world are struggling to completely control the spread of the coronavirus disease 2019 (COVID-19). Scientists and researchers are developing tests for the rapid detection of individuals who may carry the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), while striving to find a suitable vaccine to immunize healthy individuals. As there are clinically reported cases of asymptomatic carriers of SARS-CoV-2, fast and accurate diagnosis plays an important role in the control and further prevention of this disease. Herein, we present recent technologies and techniques that have been implemented for the diagnosis of COVID-19. We summarize the methods created by different research institutes as well as the commercial devices and kits developed by companies for the detection of SARS-CoV-2. The description of the existing methods is followed by highlighting their advantages and challenges. Finally, we propose some promising techniques that could potentially be applied to the detection of SARS-CoV-2, and tracing the asymptomatic carriers of COVID-19 rapidly and accurately in the early stages of infection, based on reviewing the research studies on the detection of similar infectious viruses, especially severe acute respiratory syndrome (SARS) coronavirus, and Middle East respiratory syndrome (MERS) coronavirus.

COVID-19 Antibody Tests: A Valuable Public Health Tool with Limited Relevance to Individuals.

Antibody tests for detecting past infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have many uses for public health decision making, but demand has largely come from individual consumers. This review focuses on the individual relevance of antibody tests: their accuracy in detecting prior infection, what past SARS-CoV-2 infection can currently infer about future immunity or possible medical sequelae, and the potential future importance of antibody tests for vaccine selection and medical screening. Given uncertainty about the antibody tests (quality, accuracy level, positive predictive value) and what those tests might indicate immunologically (durability of antibodies and necessity for protection from reinfection), seropositive test results should not be used to inform individual decision making, and antibody testing should remain a tool of public health at this time.