Detectability of the novel coronavirus (SARS-CoV-2) infection and rates of mortality for COVID-19 in different regions of the Russian Federation

RelevanceLaboratory diagnosis of the novel coronavirus (SARS-CoV-2) infection combined with tracing/quarantine for contacts of infected individuals affects the spread of the SARS-CoV-2 infection and levels of related mortality. At the same time, testing practices for SARS-CoV-2 infection vary in the different regions of the Russian Federation. For example, in the city of St. Petersburg, where mortality rate for COVID-19 is the highest in the Russian Federation on Oct. 25, 2020, every death for COVID-19 corresponds to 15.7 detected cases of COVID-19 in the population, while the corresponding number for the whole of Russia is 58.1, suggesting limited detection of mild and moderate cases of COVID-19 in St. Petersburg. Additionally, while in some regions in Russia, all individuals with respiratory symptoms presenting for medical care are tested for SARS-CoV-2 infection, in a number of other regions in Russia, only certain categories of individuals presenting for medical care with respiratory symptoms were tested for the SARS-CoV-2 infection prior to Oct. 26, 2020.Materials & MethodsMore active testing for SARS-CoV-2 in the population results in increased detectability (i.e. the proportion of detected COVID-19 cases among all cases of SARS-CoV-2 infection in the population) and decreased case-fatality ratio (CFR, the proportion of deaths among reported COVID-19 cases in the population) – this because under more active testing, the number of mild and moderate cases of COVID-19 increases. We used data from the Russian Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing (Rospotrebnadzor) on the number of detected cases and the number of deaths from COVID-19 in the different regions of the Russian Federation to examine the correlation between case-fatality ratios and rates of mortality for COVID-19 in different regions of the Russian Federation.ResultsThe correlation between case-fatality ratios and rates of mortality for COVID-19 in the 85 different regions of the Russian Federation on Oct. 25, 2020 is 0.64 (0.50,0.75). For several regions of the Russian Federation, detectability of SARS-CoV-2 infection is relatively low, while rates of mortality for COVID-19 are relatively high.ConclusionsDetectability of the SARS-CoV-2 infection is one of the factors that affects the levels of mortality from COVID-19 – higher detectability contributes to lower rates of mortality for COVID-19. To increase detectability, one ought to test all individuals with respiratory symptoms seeking medical care for SARS-CoV-2 infection (which is also suggested by the recent recommendations from the Ministry of Health), and to undertake additional measures to increase the volume of testing for SARS-CoV-2. Such measures, in combination with quarantine for infected cases and their close contacts help to mitigate the spread of the SARS-CoV-2 infection and diminish the related mortality.

Estimating and forecasting the spread of COVID-19 in South Korea: A Bayesian SIHR-based dynamic model with non-pharmaceutical interventions

Background: As of May 22, 2020, the total number of confirmed COVID-19 cases is over 5 million worldwide and more than 300 thousand people have lost their lives to the virus. South Korea also experienced a sharp increase in late February, but owing to non-pharmaceutical interventions, the number of confirmed cases has been decreasing since March. In this study, we aimed to investigate the transmission dynamics with these effects as well as forecast the spread of COVID-19 in South Korea, using a flexible statistical model.Methods: We analyzed the COVID-19 data obtained at the Korea Centers for Disease Control and Prevention from Feb 18 to April 30. Using a Bayesian susceptible-infectious-hospitalized-removed (SIHR) dynamic model, we estimated the dynamic transmission rate considering the non-pharmaceutical intervention effects and forecast the confirmed cases.Results: The estimated transmission rate without any control effects was 0.4605 with 95% credible interval (0.4468, 0.4745). During the days with effects between February 26 and March 6, the daily transmission rate decreased by about 89.48% of that of the previous day. With consistent control effects, it remained at 0.1549 with 95% credible interval (0.1497, 0.1602). Based on the estimated transmission rate, the forecast number of COVID-19 infections in South Korea showed an overall decreasing pattern.Conclusions: We considered and estimated the dynamic effects of the non-pharmaceutical interventions on COVID-19 using a Bayesian SIHR-based model. This study shows that non-pharmaceutical interventions including active testing, quarantine and isolation, personal preventive measures, and social distancing are crucial to curb the transmission. Our findings contribute to a better understanding of non-pharmaceutical interventions in COVID-19.

COVID-19 case-fatality rate and demographic and socioeconomic influencers: a worldwide spatial regression analysis based on country-level data

We used the COVID-19 dataset obtained from the Our World in Data website and investigated the associations between COVID-19 CFR and nine country-level indices of 209 countries/territories using the Matern correlation regression model. Spatial dependence among the data was controlled using the latitude and longitude of the centroid of the countries/territories. Stratified analyses were conducted by economic level and COVID-19 testing policy. The average of country/territory-specific COVID-19 CFR is about 2-3% worldwide, which is higher than previously reported at 0.7-1.3%. Statistically significant associations were observed between COVID-19 CFR and population size and proportion of female smokers. The open testing policies are associated with decreased CFR. Strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher stringency index was associated with higher CFR in higher income countries with active testing policies. The statistically significant association between population size and COVID-19 CRF suggests the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in females and COVID-19 CFR might be due to that the proportion of female smokers reflected broadly income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations.

The timing of contact restrictions and pro-active testing balances the socio-economic impact of a lockdown with the control of infections

During the SARS-CoV-2 pandemic, numerous mathematical models have been developed. Reporting artefacts and missing data about asymptomatic spreaders, imply considerable margins of uncertainty for model-based predictions. Epidemiological models can however also be used to investigate the consequences of measures to control the pandemic, reflected in changes to parameter values. We present a SIR-based, SUIR model in which the influence of testing and a reduction of contacts is studied by distinguishing 'Unidentified' and 'Identified' spreaders of infections. The model uses four ordinary differential equations and is kept deliberately simple to investigate general patterns occurring from testing and contact restrictions. The model goes beyond other efforts, by introducing time dependent parameter curves that represent different strategies in controlling the pandemic. Our analysis reveals the effect of 'pro-active' testing for the design of contact restriction measures. By pro-active testing we mean testing beyond those people who show symptoms. The simulations can explain why the timing of contract restrictions and pro-active testing is important. The model can also be used to study the consequence of different strategies to exit from lockdown. Our SUIR model is implemented in Python and is made available through a Juypter Notebooks. This an extensive documentation of the derivation and implementation of the model, as well as transparent and reproducible simulation studies. Our model should contribute to a better understanding of the role of testing and contact restrictions.

Suppressing the impact of the COVID-19 pandemic using controlled testing and isolation

The Corona virus disease 2019 (COVID-19) has significantly affected lives of people around the world. Today, isolation policy is enforced by identifying infected individuals based on symptoms when these appear or by testing people and quarantining those who have been in close contact with infected people. In addition, many countries have imposed complete or partial lock-downs to control the spread of the disease. While this has resulted in some some success in slowing down the spread of the virus, lock-downs as well as widespread quarantine have devastating effects on the economy and social life. Thus, governments are urgently looking for efficient strategies to significantly relax lock-downs, while still controlling the spread of the virus. We argue that this can be done by using active feedback to control testing for infection by actively testing individuals with a high probability of being infected. We develop an active testing strategy to achieve this goal, and demonstrate that it would have tremendous success in controlling the spread of the virus on one million people, using 3,000 tests per day. Our results show up to a 50% reduction in quarantine rate and morbidity rate in typical settings as compared to existing methods.

PRIMARIES AS A NEW COMMUNICATION FORMAT FOR INTERACTION BETWEEN THE RUSSIAN VOTER AND THE PARTY CANDIDATE

The transformation of electoral processes, as well as the introduction of new elements, as a rule, are due to the dynamic development and at the same time the increasing complexity of social relations. One of such manifestations is the active testing party of the mechanism of preliminary intraparty voting to determine the most effective candidates by the United Russia and their subsequent nomination to elected authorities of power. The use of a truly innovative candidate selection mechanism for the Russian Federation, for the first time in which all citizens with active electoral rights could join, was a demonstration of the party’s preparation for participation in the competition for single-mandate constituencies within the framework of the newly returned mixed electoral system in the elections of deputies of the State Duma. In the given conditions, the party declared its readiness to induce its regional organizations to reorient - the main political resource for it should be voter support. The key indirect effect of the use of this tool for the Russian voter was manifested in the expansion of the traditional boundaries of the application of active suffrage. Taking into consideration attention to the emerging practice of both its supporters and critics, as well as attempts to institutionalize, the author analyzed the background of the issue and formulated the advantages and threats brought by the primaries into the Russian electoral process. The basis of the study for the formulation of the problem and the formulation of possible arguments in favor of this procedure were the data of sociological and expert surveys, as well as the existing scientific works of authors who are few in this area of work.