Unified population register as a source of conducting socio-demographic analysis

The article deals with the analysis of demographic characteristics based on data from unified population register. The role of population registers, which are considered the most important sources of population data, is examined. The possibility of a wider use of the data of the unified population register in socio-demographic research is studied. Demographic characteristics are analyzed in the context of the COVID-19 pandemic based on data from individuals integrated into a single registry for experimental assessment. Experience shows that although data from population registers are currently used in demographic research, there is no approach to using data from other government registers. One of the main features of conducting demographic analysis using data collected in different state registers is the presence of a single identification number for each person. In the study, the information on individuals is presented by hypothetical data taken from two separate registers (population registers and health registers). A dataset on 1,000 individuals was combined into a single register. In this dataset, personal data and information about health of the population were collected. The dataset includes each person's PIN, gender, age, position, number of family members, nationality, chronic diseases including diabetes, bronchial asthma, COVID-19 infection, death from COVID-19, recovery from COVID-19. The obtained results show that the creation of a single integrated register based on the population register — electronic demography system — requires an increase in the number of available statistical indicators, integration of various state registers for a more detailed analysis. This will allow processing data and performing statistical analysis more thoroughly and for a longer period of time.

Epitope-specific antibody responses differentiate COVID-19 outcomes and variants of concern

BACKGROUNDThe role of humoral immunity in COVID-19 is not fully understood, owing, in large part, to the complexity of antibodies produced in response to the SARS-CoV-2 infection. There is a pressing need for serology tests to assess patient-specific antibody response and predict clinical outcome.METHODSUsing SARS-CoV-2 proteome and peptide microarrays, we screened 146 COVID-19 patients' plasma samples to identify antigens and epitopes. This enabled us to develop a master epitope array and an epitope-specific agglutination assay to gauge antibody responses systematically and with high resolution.RESULTSWe identified linear epitopes from the spike (S) and nucleocapsid (N) proteins and showed that the epitopes enabled higher resolution antibody profiling than the S or N protein antigen. Specifically, we found that antibody responses to the S-811-825, S-881-895, and N-156-170 epitopes negatively or positively correlated with clinical severity or patient survival. Moreover, we found that the P681H and S235F mutations associated with the coronavirus variant of concern B.1.1.7 altered the specificity of the corresponding epitopes.CONCLUSIONEpitope-resolved antibody testing not only affords a high-resolution alternative to conventional immunoassays to delineate the complex humoral immunity to SARS-CoV-2 and differentiate between neutralizing and non-neutralizing antibodies, but it also may potentially be used to predict clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants of concern in both the peptide array and latex agglutination formats.FUNDINGOntario Research Fund (ORF) COVID-19 Rapid Research Fund, Toronto COVID-19 Action Fund, Western University, Lawson Health Research Institute, London Health Sciences Foundation, and Academic Medical Organization of Southwestern Ontario (AMOSO) Innovation Fund.

Rapid and accurate agglutination-based testing for SARS-CoV-2 antibodies

We have developed a rapid, accurate, and cost-effective serologic test for SARS-CoV-2 virus, which caused the COVID-19 pandemic, on the basis of antibody-dependent agglutination of antigen-coated latex particles. When validated using plasma samples that are positive or negative for SARS-CoV-2, the agglutination assay detected antibodies against the receptor-binding domain of the spike (S-RBD) or the nucleocapsid protein of SARS-CoV-2 with 100% specificity and ∼98% sensitivity. Furthermore, we found that the strength of the S-RBD antibody response measured by the agglutination assay correlated with the efficiency of the plasma in blocking RBD binding to the angiotensin-converting enzyme 2 in a surrogate neutralization assay, suggesting that the agglutination assay might be used to identify individuals with virus-neutralizing antibodies. Intriguingly, we found that >92% of patients had detectable antibodies on the day of a positive viral RNA test, suggesting that the agglutination antibody test might complement RNA testing for the diagnosis of SARS-CoV-2 infection.

Graph modelling for tracking the COVID-19 pandemic spread

The modelling is widely used in determining the best strategies for the mitigation of the impact of infectious diseases. Currently, the modelling of a complex system such as the spread of COVID-19 infection is among the topical issues. The aim of this article is graph-based modelling of the COVID-19 infection spread. The article investigates the studies related to the modelling of COVID-19 pandemic and analyses the factors affecting the spread of the disease and its main characteristics. We propose a conceptual model of COVID-19 epidemic by considering the social distance, the duration of contact with an infected person and their location-based demographic characteristics. Based on the hypothetical scenario of the spread of the virus, a graph model of the process are developed starting from the first confirmed infection case to human-to-human transmission of the virus and visualized by considering the epidemiological characteristics of COVID-19. The application of graph for the pandemic modelling allows for considering multiple factors affecting the epidemiological process and conducting numerical experiments. The advantage of this approach is justified with the fact that it enables the reverse analysis the spread as a result of the dynamic record of detected cases of the infection in the model. This approach allows for to determining undetected cases of infection based on the social distance and duration of contact and eliminating the uncertainty significantly. Note that social, economic, demographic factors, the population density, mental values and etc. affect the increase in number of cases of infection and hence, the research was not able to consider all factors. In future research will analyze multiple factors impacting the number of infections and their use in the models will be considered.

MCDM approach for weighted ranking of candidates in e-voting

The aim of the study is the application of multi-criteria evaluation methods for ranking of candidates in e-voting. Due to the potential to enhance the electoral efficiency in e-voting multiple criteria, such as personality traits, activity and reputation in social media, opinion followers on election area and so on for the selection of qualified personnel can be considered. In this case, the number of criteria excesses in the decision-making stage directed us to the use of a multi-criteria decision making model (MCDM). This paper proposes MCDM for weighted ranking of candidates in e-voting. Criteria for the candidates’ ranking and selection are determined and each voter uses the linguistic scales for the ranking of each candidate. Candidates’ ranking is evaluated according to all criteria. In a numerical study, it is provided the candidates’ evaluation on the base of selected criteria and ranked according to the importance of criteria. To assess the importance of the criteria and to evaluate the suitability of the candidates for each of the criteria, the voters use linguistic variables. In practice, the proposed model can use different evaluation scales for the selection of candidates in e-voting. The proposed model allows selecting a candidate with the competencies based on the criteria set out in the e-voting process and making more effective decisions.

MCDM for Candidate Selection in E-Voting

E-voting is one of the most important components of e-democracy and forms the basis of a democratic governance system. Voting results always lead to a broad debate in terms of candidate selection and whether the candidate elected to a position is suitable for that position. At present, the selection of qualified personnel and their appointment to responsible positions in public administration is one of the topical issues. In this article is proposed an MCDM for selection of candidates in e-voting. Criteria for the candidates' selection are determined and the relation of each candidate to other candidates is assessed using a binary matrix. Candidate rating is calculated according to all criteria. A numerical experiment is provided for candidate evaluation on the base of the selected criteria and ranked according to the importance of the criteria. The proposed model allows selecting a candidate with competencies based on the criteria set out in the e-voting process and making more effective decisions.

E-services evaluation criteria: the case of Azerbaijan

[full article in English] The development of evaluation and effective public administration mechanisms are crucial for providing effective e-government services. The article explores the international expertise in the field of the e-service evaluation process. The organization and provision of e-services in government entities, as well as the evaluation regarding the organization and functioning of information systems, are carried out by the “ASAN service” system in Azerbaijan. The evaluation of the organization and functioning of e-services is conducted by considering three determined criteria: the level of digitalization and relevance, the level of information openness and accessibility, and the level of convenience of use. The evaluation process of e-services allows for improving the level of services and the development of feedback mechanisms; currently, much attention is attributed to the development of citizen-centered services.