Performance of COVID-19 case-based surveillance system in FCT, Nigeria, March 2020 -January 2021.

INTRODUCTION: The emergence of novel SARS-CoV-2 has caused a pandemic of Coronavirus Disease 19 (COVID-19) which has spread exponentially worldwide. A robust surveillance system is essential for correct estimation of the disease burden and containment of the pandemic. We evaluated the performance of COVID-19 case-based surveillance system in FCT, Nigeria and assessed its key attributes. METHODS: We used a cross-sectional study design, comprising a survey, key informant interview, record review and secondary data analysis. A self-administered, semi-structured questionnaire was administered to key stakeholders to assess the attributes and process of operation of the surveillance system using CDC's Updated Guidelines for Evaluation of Public Health Surveillance System 2001. Data collected alongside surveillance data from March 2020 to January 2021 were analyzed and summarized using descriptive statistics. RESULTS: Out of 69,338 suspected cases, 12,595 tested positive with RT-PCR with a positive predictive value (PPV) of 18%. Healthcare workers were identified as high-risk group with a prevalence of 23.5%. About 82% respondents perceived the system to be simple, 85.5% posited that the system was flexible and easily accommodates changes, 71.4% reported that the system was acceptable and expressed willingness to continue participation. Representativeness of the system was 93%, stability 40%, data quality 56.2% and timeliness 45.5%, estimated result turnaround time (TAT) was suboptimal. CONCLUSION: The system was found to be useful, simple, flexible, sensitive, acceptable, with good representativeness but the stability, data quality and timeliness was poor. The system meets initial surveillance objectives but rapid expansion of sample collection and testing sites, improvement of TAT, sustainable funding, improvement of electronic database, continuous provision of logistics, supplies and additional trainings are needed to address identified weaknesses, optimize the system performance and meet increasing need of case detection in the wake of rapidly spreading pandemic. More risk-group persons should be tested to improve surveillance effectiveness.

A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19.

The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel framework that intelligently combines machine learning models and the Internet of Things (IoT) technology specifically to combat COVID-19 in smart cities. The purpose of the study is to promote the interoperability of machine learning algorithms with IoT technology by interacting with a population and its environment to curtail the COVID-19 pandemic. Furthermore, the study also investigates and discusses some solution frameworks, which can generate, capture, store, and analyze data using machine learning algorithms. These algorithms can detect, prevent, and trace the spread of COVID-19 and provide a better understanding of the disease in smart cities. Similarly, the study outlined case studies on the application of machine learning to help fight against COVID-19 in hospitals worldwide. The framework proposed in the study is a comprehensive presentation on the major components needed to integrate the machine learning approach with other AI-based solutions. Finally, the machine learning framework presented in this study has the potential to help national healthcare systems in curtailing the COVID-19 pandemic in smart cities. In addition, the proposed framework is poised as a pointer for generating research interests that would yield outcomes capable of been integrated to form an improved framework.

Humoral immunological kinetics of severe acute respiratory syndrome coronavirus 2 infection and diagnostic performance of serological assays for coronavirus disease 2019: an analysis of global reports.

As the coronavirus disease 2019 (COVID-19) pandemic continues to rise and second waves are reported in some countries, serological test kits and strips are being considered to scale up an adequate laboratory response. This study provides an update on the kinetics of humoral immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and performance characteristics of serological protocols (lateral flow assay [LFA], chemiluminescence immunoassay [CLIA] and ELISA) used for evaluations of recent and past SARS-CoV-2 infection. A thorough and comprehensive review of suitable and eligible full-text articles was performed on PubMed, Scopus, Web of Science, Wordometer and medRxiv from 10 January to 16 July 2020. These articles were searched using the Medical Subject Headings terms 'COVID-19', 'Serological assay', 'Laboratory Diagnosis', 'Performance characteristics', 'POCT', 'LFA', 'CLIA', 'ELISA' and 'SARS-CoV-2'. Data from original research articles on SARS-CoV-2 antibody detection ≥second day postinfection were included in this study. In total, there were 7938 published articles on humoral immune response and laboratory diagnosis of COVID-19. Of these, 74 were included in this study. The detection, peak and decline period of blood anti-SARS-CoV-2 IgM, IgG and total antibodies for point-of-care testing (POCT), ELISA and CLIA vary widely. The most promising of these assays for POCT detected anti-SARS-CoV-2 at day 3 postinfection and peaked on the 15th day; ELISA products detected anti-SARS-CoV-2 IgM and IgG at days 2 and 6 then peaked on the eighth day; and the most promising CLIA product detected anti-SARS-CoV-2 at day 1 and peaked on the 30th day. The most promising LFA, ELISA and CLIA that had the best performance characteristics were those targeting total SARS-CoV-2 antibodies followed by those targeting anti-SARS-CoV-2 IgG then IgM. Essentially, the CLIA-based SARS-CoV-2 tests had the best performance characteristics, followed by ELISA then POCT. Given the varied performance characteristics of all the serological assays, there is a need to continuously improve their detection thresholds, as well as to monitor and re-evaluate their performances to assure their significance and applicability for COVID-19 clinical and epidemiological purposes.

Understanding the implications of SARS-CoV-2 re-infections on immune response milieu, laboratory tests and control measures against COVID-19.

Several months after the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), cases of re-infection after recovery were reported. The extent and duration of protective immunity after SARS-CoV-2 infection is not fully understood. As such, the possibility of re-infection with SARS-CoV-2. Furthermore, cases of re-infection were mainly due to different variants or mutant SARS-CoV-2. Following the fast and pandemic-scale spread of COVID-19, mutations in SARS-CoV-2 have raised new diagnostic challenges which include the redesign of the oligonucleotide sequences used in RT-PCR assays to avoid potential primer-sample mismatches, and decrease sensitivities. Since the initial wave of the pandemic, some regions had experienced fresh outbreaks, predisposing people to be susceptible to SARS-CoV-2 re-infection. Hence, this article sought to offer detailed biology of SARS-CoV-2 re-infections and their implications on immune response milieu, diagnostic laboratory tests and control measures against COVID-19.

Leveraging on the genomics and immunopathology of SARS-CoV-2 for vaccines development: prospects and challenges.

The incidence and case-fatality rates (CFRs) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, the etiological agent for Coronavirus Disease 2019 (COVID-19), have been rising unabated. Even though the entire world has been implementing infection prevention and control measures, the pandemic continues to spread. It has been widely accepted that preventive vaccination strategies are the public health measures for countering this pandemic. This study critically reviews the latest scientific advancement in genomics, replication pattern, pathogenesis, and immunopathology of SARS-CoV-2 infection and how these concepts could be used in the development of vaccines. We also offer a detailed discussion on the anticipated potency, efficacy, safety, and pharmaco-economic issues that are and will be associated with candidate COVID-19 vaccines.

Mathematical modeling for infectious viral disease: The COVID-19 perspective.

In this study, we examined various forms of mathematical models that are relevant for the containment, risk analysis, and features of COVID-19. Greater emphasis was laid on the extension of the Susceptible-Infectious-Recovered (SIR) models for policy relevance in the time of COVID-19. These mathematical models play a significant role in the understanding of COVID-19 transmission mechanisms, structures, and features. Considering that the disease has spread sporadically around the world, causing large scale socioeconomic disruption unwitnessed in contemporary ages since World War II, researchers, stakeholders, government, and the society at large are actively engaged in finding ways to reduce the rate of infection until a cure or vaccination procedure is established. We advanced argument for the various forms of the mathematical model of epidemics and highlighted their relevance in the containment of COVID-19 at the present time. Mathematical models address the need for understanding the transmission dynamics and other significant factors of the disease that would aid policymakers to make accurate decisions and reduce the rate of transmission of the disease.

Roles and challenges of coordinated public health laboratory response against COVID-19 pandemic in Africa.

As the incidence of Coronavirus Disease 19 (COVID-19) continues to rise, many countries have been seeking for medical assistance such as donation or procurement of laboratory test kits and strips. These consumables are largely intended for use in the laboratory investigations of COVID-19 cases, suspected contacts, asymptomatic persons and in discharging cured persons. Thus, this article was instigated to update and remind healthcare providers and policymakers (especially those in developing countries) on the principles of sample collections, storage, transportation, laboratory protocols and networks needed for appropriate public health response against COVID-19 pandemic in Africa and other developing countries. In addition, this article presents challenges that hinder adequate COVID-19 laboratory response and discuss some possible solutions that could ameliorate these constrains.

Exploring the genetics, ecology of SARS-COV-2 and climatic factors as possible control strategies against COVID-19

The world has been thrown into pandemonium due to the recent Coronavirus Disease-19 (COVID-19) pandemic. Early available clinical data have indicated that geriatric persons cum those with comorbidity such as cardiovascular, metabolic and immunological disorders suffered severe form of COVID-19. All countries and territories of the world are currently exploring available strategies to control the pandemic with the hope to significantly minimize its morbidity and mortality rate. This present study critically reviewed available and latest research progress on the genetics and ecology of SARS-CoV-2, as well as the influence of climatic factors on the spread of COVID-19, and thus, discussed how these concepts could be harnessed for COVID-19 control and further scientific advancements in resolving the pandemic.