Use of quantitative forecasting methods and error calculation for better adaptability to the application of a mathematical model to determine the speed of spread of a coronavirus infection (COVID-19) in Spain

2020 ◽  
Vol 13 (1) ◽  
pp. 157-175
Author(s):  
G. Sanglier Contreras ◽  
M. Robas Mora ◽  
P. Jimenez Gomez
Keyword(s):  
Mathematical Model ◽  
Error Calculation ◽  
Forecasting Methods ◽  
Coronavirus Infection

APPLICATION OF THE HOLT-WINTERS METHOD FOR FORECASTION HOSPITAL ADMISSIONS IN CITIES

2021 ◽  
Vol 4 (30) ◽  
pp. 22-32
Author(s):  
V. A. Klyapko ◽  
Keyword(s):  
Hospital Admissions ◽  
Analytical Data ◽  
Transportation Of Patients ◽  
Large Cities ◽  
Forecasting Methods ◽  
The Subject ◽  
Coronavirus Infection ◽  
Object Of Study ◽  
The City ◽  
Use Of Models

The current situation of coronavirus infection necessitates the use of models and prediction methods for decision- making in a rapidly changing situation in large cities and towns. Due to the dynamics of the processes, it is necessary to use different models and forecasting methods for the development of the situation. The city of St. Petersburg is the object of study and an analysis of hospitalisation of patients is performed. St. Petersburg was chosen as the subject of the research. The presented research was carried out within the framework of the work "Mathematical modelling of logistic systems in medicine" during the performance of diploma projects on the assignment of St. Petersburg executive authorities in 2021. In the course of the study analytical data are collected, the city districts where the situation with transportation of patients to medical organizations is likely to be difficult to predict are identified, and the methodology of forecasting hospitalization of patients by ambulance cars is considered. In solving the problem of predicting the situation, forecasting methods in the class of polynomial models are used and the effectiveness of using the Holt-Winters method is justified.

Implementation of Genetic-Algorithm-Based Forecasting Model to Power System Problems

2018 ◽  
pp. 140-155
Author(s):  
Sajad Madadi ◽  
Morteza Nazari-Heris ◽  
Behnam Mohammadi-Ivatloo ◽  
Sajjad Tohidi
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Power System ◽  
Load Forecasting ◽  
Wind Farms ◽  
Optimization Method ◽  
Forecasting Model ◽  
Renewable Generation ◽  
Forecasting Methods ◽  
Pool Market

Power system includes many types of markets. Such markets are generally cleared at certain times, whereas market participators have to determine their operational plans before meeting the actual conditions. Therefore, forecasting methods can assist market players. Forecasting methods are applied to forecast electricity demand. The unknown conditions in the power system are increased by integration of renewable generation units. Forecasting methods, which are used for the load forecasting, are updated because the output power of renewable generation units such as wind farms and photovoltaic (PV) panels have more deviation than power demand. The pool market can be introduced as other parameter that is forecasted by market players. In this chapter, the authors investigate a mathematical model for forecasting of wind. Then, the forecasting model is proposed. Genetic algorithm is applied as an optimization method to handle delay associated with wind forecasting.

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

CALCULATION OF THE BASIC AND ADDITIONAL ERRORS OF THE MOISTURE METER OF GRAIN AND GRAIN PRODUCTS

2021 ◽  
Vol 2 (1) ◽  
pp. 29-34
Author(s):  
Parakhat Mailievna Matyakubova ◽  
◽  
Ruslan Raisovich Kuluev
Keyword(s):  
Mathematical Model ◽  
Measuring Transducer ◽  
Basic Error ◽  
Error Calculation ◽  
Moisture Meter ◽  
Grain Products ◽  
The Mathematical Model

Calculation of the basic error of the moisture meter is determined by the error in measuring the frequency. The latter, in turn, consists of the error of the timer-counter when counting the frequency (quantization), the error in determining the coefficients a1and a2of the mathematical model of the measuring transducer during calibration, and the error due to the noise of the comparator-amplifier.Keywords:error, error calculation, measurements, result.

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