scholarly journals Mathematical Modeling Based Study and Prediction of COVID-19 Epidemic Dissemination Under the Impact of Lockdown in India

2020 ◽  
Vol 8 ◽  
Author(s):  
Vipin Tiwari ◽  
Namrata Deyal ◽  
Nandan S. Bisht
Keyword(s):  
Mathematical Modeling ◽  
The Impact

Mathematical modeling of the impact of a pulse seismic source on geological media

2020 ◽  
Author(s):  
E. A. Efimov ◽  
V. M. Sadovskii ◽  
O. V. Sadovskaya
Keyword(s):  
Mathematical Modeling ◽  
Seismic Source ◽  
The Impact

scholarly journals The impact of super-spreader cities, highways, and intensive care availability in the early stages of the COVID-19 epidemic in Brazil

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Miguel A. L. Nicolelis ◽  
Rafael L. G. Raimundo ◽  
Pedro S. Peixoto ◽  
Cecilia S. Andreazzi
Keyword(s):  
Mathematical Modeling ◽  
Intensive Care ◽  
Road Traffic ◽  
Geographic Spread ◽  
Boomerang Effect ◽  
Entry Points ◽  
Entire Country ◽  
Major Factors ◽  
The Impact ◽  
Care Availability

AbstractAlthough international airports served as main entry points for SARS-CoV-2, the factors driving the uneven geographic spread of COVID-19 cases and deaths in Brazil remain mostly unknown. Here we show that three major factors influenced the early macro-geographical dynamics of COVID-19 in Brazil. Mathematical modeling revealed that the “super-spreading city” of São Paulo initially accounted for more than 85% of the case spread in the entire country. By adding only 16 other spreading cities, we accounted for 98–99% of the cases reported during the first 3 months of the pandemic in Brazil. Moreover, 26 federal highways accounted for about 30% of SARS-CoV-2’s case spread. As cases increased in the Brazilian interior, the distribution of COVID-19 deaths began to correlate with the allocation of the country’s intensive care units (ICUs), which is heavily weighted towards state capitals. Thus, severely ill patients living in the countryside had to be transported to state capitals to access ICU beds, creating a “boomerang effect” that contributed to skew the distribution of COVID-19 deaths. Therefore, if (i) a lockdown had been imposed earlier on in spreader-capitals, (ii) mandatory road traffic restrictions had been enforced, and (iii) a more equitable geographic distribution of ICU beds existed, the impact of COVID-19 in Brazil would be significantly lower.

scholarly journals Mathematical Modeling of the Spread of Alcoholism Among Colombian College Students

2020 ◽  
Vol 16 (32) ◽  
pp. 195-223
Author(s):  
Edgardo Pérez
Keyword(s):  
Mathematical Modeling ◽  
College Students ◽  
Mathematical Model ◽  
Drinking Behavior ◽  
Preventive Measure ◽  
Nonlinear Mathematical Model ◽  
Consumption Behavior ◽  
Existence And Stability ◽  
Drugs And Crime ◽  
The Impact

In this paper, we present a nonlinear mathematical model, describing the spread of high-risk alcohol consumption behavior among college students in Colombia. We proved the existence and stability of the alcohol-free and drinking state equilibrium by means of Lyapunov function and LaSalle’s invariance principle. Also, we apply optimal control to study the impact of a preventive measure on the spread of drinking behavior among college students. Finally, we use numerical simulations and available data provided by the United Nations Office on Drugs and Crime (UNODC) and the Colombian Ministry of Justice to validate the obtained mathematical model.

scholarly journals Mathematical modeling of the SARS-CoV-2 epidemic in Qatar and its impact on the national response to COVID-19

2020 ◽  
Author(s):  
Houssein H. Ayoub ◽  
Hiam Chemaitelly ◽  
Shaheen Seedat ◽  
Monia Makhoul ◽  
Zaina Al Kanaani ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Acute Care ◽  
Hospital Admissions ◽  
Deterministic Model ◽  
Infection Prevalence ◽  
Care Hospital ◽  
Healthcare Needs ◽  
National Response ◽  
The Impact ◽  
Second Wave

AbstractBackgroundMathematical modeling constitutes an important tool for planning robust responses to epidemics. This study was conducted to guide the Qatari national response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. The study investigated the time course of the epidemic, forecasted healthcare needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions.MethodsAn age-structured deterministic model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression throughout the population.ResultsThe enforced social and physical distancing interventions flattened the epidemic curve, reducing the peaks for incidence, prevalence, acute-care hospitalization, and intensive care unit (ICU) hospitalizations by 87%, 86%, 76%, and 78%, respectively. The daily number of new infections was predicted to peak at 12,750 on May 23, and active-infection prevalence was predicted to peak at 3.2% on May 25. Daily acute-care and ICU-care hospital admissions and occupancy were forecast accurately and precisely. By October 15, 2020, the basic reproduction number R0 had varied between 1.07-2.78, and 50.8% of the population were estimated to have been infected (1.43 million infections). The proportion of actual infections diagnosed was estimated at 11.6%. Applying the concept of Rt tuning, gradual easing of restrictions was rationalized and justified to start on June 15, 2020, when Rt declined to 0.7, to buffer the increased interpersonal contact with easing of restrictions and to minimize the risk of a second wave. No second wave has materialized as of October 15, 2020, five months after the epidemic peak.ConclusionsUse of modeling and forecasting to guide the national response proved to be a successful strategy, reducing the toll of the epidemic to a manageable level for the healthcare system.

The Students–Professors Problem—The Reversal Error and Beyond

2021 ◽  
pp. 1-37
Author(s):  
Uffe Thomas Jankvist ◽  
Mogens Niss
Keyword(s):  
Mathematical Modeling ◽  
Mixed Methods ◽  
Empirical Study ◽  
Secondary Students ◽  
Mixed Methods Design ◽  
Problem Statement ◽  
Upper Secondary ◽  
Reversal Error ◽  
The Impact ◽  
Error Types

Abstract This paper first introduces and reviews the existing research on the well-known “students–professors (S/P) problem”, which was first formulated in 1979. Next, it presents an empirical study of Danish upper secondary students’ answers to two mathematical modeling versions of the S/P-problem; a mathematization version (296 students), and a de-mathematization version (658 students). Besides reproducing several previously reported findings, e.g., the so-called reversal error, the study identifies new error types not previously reported in the literature. The mathematical modeling perspective adopted, along with a mixed-methods design, give rise to new potential explanations of the reversal error as well as explanations of the new error types. Our study shows that interpreting the linguistic formulation of the S/P-problem statement is not only related to language but is intrinsically of a mathematical – and cognitive – nature as well. Altogether, there is still more to be said about the S/P-problem forty years after its emergence. The impact sheet to this article can be accessed at 10.6084/m9.figshare.16610104.

scholarly journals Mathematical modeling of the impact of forest fires on buildings and structures

2018 ◽  
Vol 209 ◽  
pp. 00021
Author(s):  
Valeriy Perminov ◽  
Victoria Marzaeva
Keyword(s):  
Mathematical Modeling ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Behavior ◽  
Fire Intensity ◽  
Physical Mechanisms ◽  
Important Concern ◽  
Fire Initiation ◽  
The Impact ◽  
Fundamental Physical

The protection of buildings and structures in a community from destruction by forest fires is a very important concern. This paper addresses the development of a mathematical model for fires in the wildland-urban intermix. The forest fire is a very complicated phenomenon. At present, fire services can forecast the danger rating of, or the specific weather elements relating to, forest fire. There is need to understand and predict forest fire initiation, behavior and impact of fire on the buildings and constructions. This paper’s purposes are the improvement of knowledge on the fundamental physical mechanisms that control forest fire behavior. The mathematical modeling of forest fires actions on buildings and structures has been carried out to study the effects of fire intensity and wind speed on possibility of ignition of buildings.

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