scholarly journals Epidemiological forecast of COVID-19 in Kazakhstan

2020 ◽  
Vol 4 (39) ◽  
pp. 49-53
Author(s):  
Bakhytkul Mustafina ◽  
◽  
Aiman Mussina ◽  
Anel Serikbayeva ◽  
Erdos Baranbayev ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Coronavirus Infection

Currently, the epidemic situation in Kazakhstan is stable.The main reason for this is a correctly calculated epidemic forecast. This article provides a forecast of the epidemic situation in Kazakhstan using a mathematical model. The model is used to analyze the epidemic situation between Kazakhstan and other countries. In addition, the article discusses the ways and consequences of eliminating the epidemic. The developed model is used to describe how the upcoming epidemic situation is developing. In other words, the article analyzes and evaluates the epidemic caused by coronavirus infection in Kazakhstan using a mathematical model

MATHEMATICAL MODEL TO PREDICT SEVERITY OF CORONAVIRUS INFECTION AND MAIN ANTI-EPIDEMIC MEASURES IN UKRAINE

2020 ◽  
pp. 57-65
Author(s):  
K. A. Kryvonos ◽  
V. S. Maslova ◽  
V. M. Sharapov ◽  
S. M. Vorobyov
Keyword(s):  
Mathematical Model ◽  
Platelet Count ◽  
Elderly Patients ◽  
Erythrocyte Sedimentation Rate ◽  
Sedimentation Rate ◽  
Regression Equations ◽  
Middle Aged ◽  
Erythrocyte Sedimentation ◽  
Coronavirus Infection ◽  
D Dimer

Currently, the epidemic situation regarding the incidence of coronavirus infection COVID−19 in Ukraine continues to be tense. In order to in−depth study of the problem of clinical features, treatment and prevention of this disease, as well as the development of a mathematical model for predicting the severity of its course, 30 patients aged 18 to 85 years were examined. Among the patients there were young and middle−aged people as well as elderly patients with chronic diseases, namely obesity, hypertension, diabetes. The diagnosis of coronavirus infection was confirmed in all the patients by molecular genetic method, i.e. SARS−CoV−2 RNA was isolated, and in 10 patients − IgM + IgG to SARS was determined by immunochromatographic analysis. With COVID−19, young and middle−aged patients have a fairly mild course with a decrease in platelet count by 7 %, erythrocyte sedimentation rate by 48 %, prothrombin by 14 % and D−dimer by 31 %. The construction of regression equations based on trend lines revealed that in elderly patients after treatment there was a further decrease in the level of D−dimer (20 %), an increase in platelet count (30 %), a decrease in white blood cell count (26 %), neutrophils (38 %), increase in lymphocyte levels by 3 times, decrease in erythrocyte sedimentation rate (by 10 %) and prothrombin parameters (by 15 %). Based on cluster and regression analysis, coefficients were calculated for each prognostic function. It was found that the linear dependence and statistically significant effect on the course of COVID−19 in all patients have leukocytes, erythrocyte sedimentation rate and D−dimer. In order to prevent the spread of coronavirus infection in Ukraine COVID−19 in this March, quarantine was introduced throughout the country, which is being extended to this day. There is no doubt about the importance of recommendations for improving anti−epidemic measures to prevent coronavirus infection throughout Ukraine. Key words: coronavirus infection, COVID−19, clinical blood counts, disease prognosis, anti−epidemic measures in Ukraine.

MODELS OF STIMULATING THE WORK OF MEDICAL PERSONNEL IN THE CONTEXT OF THE PANDEMIC OF THE NEW CORONAVIRUS INFECTION COVID-19

2021 ◽  
Vol 1 (10) ◽  
pp. 133-148
Author(s):  
Evgeny V. Kostyrin ◽  
Keyword(s):  
Mathematical Model ◽  
Financial Incentives ◽  
Medical Personnel ◽  
Health Department ◽  
Comprehensive System ◽  
Practical Implementation ◽  
Average Salary ◽  
Work Related ◽  
Coronavirus Infection ◽  
Incentive Payments

Models of stimulating the work of medical personnel in the conditions of the pandemic of the new coronavirus infection COVID-19 have been developed, namely: a model of stimulating the work of doctors and secondary medical personnel in the conditions of working in the “red zone”, diagnosing patients, post-COVID rehabilitation of patients and work related to vaccination of the population. A comprehensive system of staff motivation in the fight against COVID-19 has also been developed, including a comprehensive economic and mathematical model of financial incentives for doctors and nursing staff and tools for the practical implementation of the developed models using algorithms and software based on MS Excel spreadsheets. The practical implementation of the developed comprehensive system of stimulating the work of medical personnel was carried out on the example of a medical and preventive institution under the structural subordination of the Moscow Health Department, on the basis of which work on the prevention, vaccination and treatment of a new coronavirus infection COVID-19 was organized. The application of a comprehensive economic and mathematical model of stimulating the work of medical personnel in practice allowed, in addition to guaranteed federal and regional surcharges for work under COVID-19, to provide average incentive payments per medical worker in the amount of 58,318.20 rubles per month, which made it possible to increase the average salary of doctors during the spread of COVID-19 by almost 45%, excluding federal and regional surcharges.

USING AIR EXCHANGE TO REDUCE THE PROBABILITY OF THE SPREAD OF THE CORONAVIRUS INFECTION

2020 ◽  
pp. 59-65
Author(s):  
В. Н. Мелькумов ◽  
Г. А. Кузнецова ◽  
А. В. Панин ◽  
М. Я. Панов
Keyword(s):  
Mathematical Model ◽  
General Solution ◽  
Infectious Diseases ◽  
Medical Institution ◽  
Airborne Transmission ◽  
Infected People ◽  
Medical Institutions ◽  
Coronavirus Infection ◽  
The Mathematical Model ◽  
Air Exchange

Постановка задачи. Процессы вентиляции оказывают значительное влияние на распространение инфекций, передающихся воздушно-капельным путем. Необходимо использовать воздухообмен для снижения вероятности распространения подобных инфекций. Результаты. С использованием схемы воздушной передачи инфекционных заболеваний Уэллса-Райли разработана математическая модель распространения коронавирусной инфекции в лечебном учреждении, состоящем из группы сообщающихся помещений, в которых постоянно находятся и перемещаются как здоровые, так и инфицированные люди. Математическая модель позволяет учитывать перемещение людей по помещениям и оседание квантов генерации инфекции больным человеком при циркуляции воздуха. Получено общее решение математической модели, позволяющее рассчитать концентрацию квантов генерации инфекции в помещениях при функционировании лечебного учреждения. Выводы. Разработанная математическая модель лечебного учреждения позволяет глубже понять возможности распространения коронавирусной инфекции и учесть эти риски при проектировании лечебных учреждений. Statement of the problem. Ventilation processes have a significant impact on the spread of airborne infections. It is necessary to use air exchange to reduce the likelihood of spreading such infections. Results. Using the Wells - Riley model of airborne transmission of infectious diseases, a mathematical model has been developed for the spread of the coronavirus infection in a medical institution consisting of a group of communicating rooms in which both healthy and infected people are constantly located and moved. The mathematical model makes it possible to take into account the movement of people around the premises and the settling of quanta of the generation of infection by a sick person when air moves. The general solution of the mathematical model is obtained, which allows one to calculate the concentration of quanta of generation of infection in the premises during the operation of a medical institution. Conclusions. The developed mathematical model of a medical institution provides a deeper understanding of the possibilities of the spread of the coronavirus infection and taking these risks into account when designing medical institutions.

scholarly journals Stability Analysis of a Mathematical Model in Inflammatory Response System Due to SARS Coronavirus Infection

2020 ◽  
Vol 17 (2) ◽  
pp. 280-292
Author(s):  
Ario Wiraya
Keyword(s):  
Mathematical Model ◽  
Inflammatory Response ◽  
Equilibrium Point ◽  
Reproduction Number ◽  
Asymptotically Stable ◽  
Response System ◽  
Coronavirus Infection ◽  
Disease Free ◽  
The Basic Reproduction Number ◽  
Inflammatory Response System

Severe Acute Respiratory Syndrome (SARS) Coronavirus infection in a human body indicated by cytokine response due to an inflammation. The purpose of this research is to construct and analyze a mathematical model of interaction between inflammatory pro-response and anti-response cytokine to predict the dynamic on inflammatory response system, so that the treatment can be optimized. The results obtained in this research describe some dynamics which happen on the cytokines, i.e. the disease-free equilibrium point is asymptotically stable when the basic reproduction number is less than one. In this condition, a patient with initial concentrations of the cytokines around the disease-free equilibrium point will be free of viral infection. The infection equilibrium point is asymptotically stable when the basic reproduction number is greater than one. In this condition, a patient with initial concentrations of the cytokines around the infection equilibrium point will be infected by the virus. Probability of a patient being free of viral infection can increase if the production rate of the cytokines are decreased or the degradation rate of the cytokines are increased.

Some epidemiological aspects of the new coronavirus infection (COVID-19) in Rostov region

2020 ◽  
Vol 18 (3) ◽  
pp. 21-29
Author(s):  
A.R. Litovko ◽  
◽  
T.I. Tverdokhlebova ◽  
E.V. Kovalev ◽  
G.V. Karpushchenko ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Key Words ◽  
Rights Protection ◽  
Human Wellbeing ◽  
Rostov Region ◽  
Consumer Rights ◽  
Coronavirus Infection ◽  
The Government ◽  
Spread Of Infection ◽  
Epidemiological Situation

Material and methods. We evaluated the incidence of COVID-19 in Rostov region. The data was obtained from the Rostov Department of the Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing, Center of Hygiene and Epidemiology of Rostov region, and Rostov Research Institute of Microbiology and Parasitology. In addition to that, we monitored the information on the official websites of the Government of Rostov region and regional COVID-19 headquarters. The SEIR analytical platform was used to build a mathematical model for predicting the spread of infection in Rostov region. Results. We have evaluated the epidemiological situation of COVID-19 in Rostov region and analyzed the effectiveness of preventive and anti-epidemic measures with the possibility of predicting the development of the epidemic process in the region. Key words: coronavirus infection, prognosis, anti-epidemic measures, epidemiological situation, COVID-19

scholarly journals Fractional Riccati equation to model the dynamics of COVID-19 coronovirus infection

2021 ◽  
Vol 2094 (3) ◽  
pp. 032042
Author(s):  
D A Tverdyi ◽  
R I Parovik
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Riccati Equation ◽  
Russian Federation ◽  
Variable Coefficients ◽  
Variable Order ◽  
Modified Newton Method ◽  
Coronavirus Infection ◽  
The Russian Federation ◽  
The Republic

Abstract The article proposes a mathematical model based on the fractional Riccati equation to describe the dynamics of COVID-19 coronavirus infection in the Republic of Uzbekistan and the Russian Federation. The model fractional Riccati equation is an equation with variable coefficients and a derivative of a fractional variable order of the Gerasimov-Caputo type. The solution to the model Riccati equation is given using the modified Newton method. The obtained model curves are compared with the experimental data of COVID-19 coronavirus infection in the Republic of Uzbekistan and the Russian Federation. It is shown that with a suitable choice of parameters in the mathematical model, the calculated curves give results close to real experimental data.

scholarly journals USING AIR EXCHANGE TO REDUCE THE PROBABILITY OF SPREADING CORONAVIRUS INFECTION

2021 ◽  
pp. 14-20
Author(s):  
V. N. Melkumov ◽  
G. A. Kuznetsova ◽  
A. V. Panin ◽  
M. Ya. Panov
Keyword(s):  
Mathematical Model ◽  
General Solution ◽  
Infectious Diseases ◽  
Medical Institution ◽  
Airborne Transmission ◽  
Infected People ◽  
Medical Institutions ◽  
Coronavirus Infection ◽  
The Mathematical Model ◽  
Air Exchange

Statement of the problem. Ventilation processes have a significant impact on the spread of airborne infections. It is necessary to use air exchange to reduce the likelihood of spreading such infections. Mathematical model. Using the Wells - Riley model of airborne transmission of infectious diseases, a mathematical model has been developed for the spread of coronavirus infection in a medical institution, consisting of a group of communicating rooms in which both healthy and infected people are constantly located and moved. The mathematical model makes it possible to take into account the movement of people around the premises and the settling of quanta of the generation of infection by a sick person when air moves. Results. The general solution of the mathematical model is obtained, which allows calculating the concentration of quanta of generation of infection in the premises during the operation of a medical institution.Conclusions. The developed mathematical model of a medical institution allows a deeper understanding of the possibilities of the spread of coronavirus infection and taking these risks into account when designing medical institutions.

scholarly journals Epidemiological situation of a new coronavirus infection (COVID-19) in the Rostov region: analysis and forecast

2020 ◽  
Vol 11 (3) ◽  
pp. 69-78
Author(s):  
E. V. Kovalev ◽  
T. I. Tverdokhlebova ◽  
G. V. Karpushenko ◽  
E. G. Erganova ◽  
V. V. Agafonova ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Consumer Protection ◽  
The Internet ◽  
Human Welfare ◽  
Rostov Region ◽  
Regional Headquarters ◽  
Coronavirus Infection ◽  
The Government ◽  
Spread Of Infection ◽  
Epidemiological Situation

Objective: monitoring, analysis and forecast of the spread of new coronavirus infection (COVID-19) in the Rostov region.Materials and methods: analysis of data on the incidence of COVID-19 in the Rostov region, obtained on the basis of agencies: Department of the Federal service for supervision of consumer protection and human welfare in the Rostov region, Center of hygiene and epidemiology in Rostov region, Rostov research Institute of Microbiology and Parasitology, as well as the monitoring of information on the Internet sites of the Government of the Rostov region and the regional headquarters for the fight against the spread of COVID-19. Application of the SEIR analytical platform to build a mathematical model for predicting the spread of infection in the Rostov region.Results: the article presents an analysis of the epidemiological situation for the incidence of COVID-19 in the Rostov region, analyzes the effectiveness of preventive and anti-epidemic measures with the ability to predict the development of the epidemiological process in the region.

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