Travelling and COVID-19: A Mathematical Model

Banerjee, Sankha

doi:10.21203/rs.3.rs-26244/v1

Cited by 5 publications

(4 citation statements)

References 37 publications

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“…Meanwhile, high income levels likely increase the mobility and number of contacts, which increases the rate of new cases and deaths ( 16 ). In addition, traveling and population dispersal can aggravate the spread of disease in each region ( 17 , 18 ). Although air travel has clearly been a major driver of the pandemic, intercontinental travel restrictions were less effective between Europe and the USA ( 19 ).…”

Section: Discussionmentioning

confidence: 99%

Evolving trend change during the COVID-19 pandemic

Gao¹,

Zheng

Shi³

et al. 2022

Front. Public Health

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Coronavirus disease (COVID-19) has caused unimaginable damage to public health and socio-economic structures worldwide; thus, an epidemiological depiction of the global evolving trends of this disease is necessary. As of March 31, 2022, the number of cases increased gradually over the four waves of the COVID-19 pandemic, indicating the need for continuous countermeasures. The highest total cases per million and total deaths per million were observed in Europe (240,656.542) and South America (2,912.229), despite these developed countries having higher vaccination rates than other continents, such as Africa. In contrast, the lowest of the above two indices were found in undeveloped African countries, which had the lowest number of vaccinations. These data indicate that the COVID-19 pandemic is positively related to the socio-economic development level; meanwhile, the data suggest that the vaccine currently used in these continents cannot completely prevent the spread of COVID-19. Thus, rethinking the feasibility of a single vaccine to control the disease is needed. Although the number of cases in the fourth wave increased exponentially compared to those of the first wave, ~43.1% of deaths were observed during the first wave. This was not only closely linked to multiple factors, including the inadequate preparation for the initial response to the COVID-19 pandemic, the gradual reduction in the severity of additional variants, and the protection conferred by prior infection and/or vaccination, but this also indicated the change in the main driving dynamic in the fourth wave. Moreover, at least 12 variants were observed globally, showing a clear spatiotemporal profile, which provides the best explanation for the presence of the four waves of the pandemic. Furthermore, there was a clear shift in the trend from multiple variants driving the spread of disease in the early stage of the pandemic to a single Omicron lineage predominating in the fourth wave. These data suggest that the Omicron variant has an advantage in transmissibility over other contemporary co-circulating variants, demonstrating that monitoring new variants is key to reducing further spread. We recommend that public health measures, along with vaccination and testing, are continually implemented to stop the COVID-19 pandemic.

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Section: Discussionmentioning

confidence: 99%

Evolving trend change during the COVID-19 pandemic

Gao¹,

Zheng

Shi³

et al. 2022

Front. Public Health

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“…The value of p can be obtained by substituting the values of m and s from ( 9) and ( 10), respectively, into (11). Further, it can be observed that only three samples are sufficient to get a Gaussian wave.…”

Section: Estimation Of Mean Standard Deviation and The Peak Value Of A Gaussian Wavementioning

confidence: 99%

Mathematical Modeling and Estimation for Next Wave of COVID19 in Poland

Arti

Wiliński

2021

Preprint

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We investigate the problem of mathematical modeling of new corona virus (Covid19) in Poland and tries to predict the upcoming wave. A Gaussian mixture model is proposed to characterize the COVID-19 disease and to predict a new / future wave of COVID-19. This prediction is very much needed to prepare for medical setup and continue with the upcoming program. Specifically, data related to the new confirmed cases of COVID-19 per day are considered, and then we attempt to predict the data and statistical activity. A close match between actual data and analytical data by using the Gaussian mixture model shows that it is a suitable model to present new cases of COVID-19. In addition, it is thought that there are N waves of COVID-19 and that information for each future wave is also present in current and previous waves as well. Using this concept, predictions of a future wave can be made.

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“…The mu variant is also monitored. A few variants of COVID-19 frequency in limited and unrestricted areas have been suggested in studies [7][8][9][10][11][12][13][14][15][16][17][18][19][20]23].…”

Section: Introductionmentioning

confidence: 99%

Probability Calculation of Upcoming Waves of COVID-19 in Poland

Arti

Wiliński

2022

WSB Journal of Business and Finance

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We present the problem of risk estimation/assessment of the new coronavirus (COVID-19) spread in Poland. In the literature, a method is given to explain the COVID-19 disease and try to predict the occurrence of the next wave of COVID-19. A Gaussian composite model is used in literature to identify COVID-19 disease. In this model, however, the prediction of the upcoming waves is dependent primarily on the set of selected samples. For different sets of samples, distinct timings of the upcoming waves are obtained. In this article, we assume that probability is associated with each set of samples, which are used for the prediction of the upcoming waves. By exploring this aspect, it is shown that a better prediction of the upcoming COVID-19 waves can be performed.

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Travelling and COVID-19: A Mathematical Model

Cited by 5 publications

References 37 publications

Evolving trend change during the COVID-19 pandemic

Evolving trend change during the COVID-19 pandemic

Mathematical Modeling and Estimation for Next Wave of COVID19 in Poland

Probability Calculation of Upcoming Waves of COVID-19 in Poland

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