论文信息 - Logistic growth model and modeling of factors for community case transmission.

Logistic growth model and modeling of factors for community case transmission.

In this article, we analyze the spread of cases resulting from community transmission of COVID-19 in Senegal in order to identify statistical associations. The identification and knowledge of the factors associated with this community transmission can be a decision support tool to limit the spread of the disease. We estimate parameters and evaluate the growth factor, community rate, weekly increase and daily difference, and make forecasting to help on how to find concrete actions to control the situation.

Babacar Mbaye Ndiaye | Massamba Diouf | B. Ndiaye | M. Diouf

[1] B. Ndiaye,et al. Analysis of the COVID-19 pandemic by SIR model and machine learning technics for forecasting , 2020, 2004.01574.

[2] Diaraf Seck,et al. Comparative prediction of confirmed cases with COVID-19 pandemic by machine learning, deterministic and stochastic SIR models , 2020, 2004.13489.

[3] Jianhong Wu,et al. Richards model revisited: validation by and application to infection dynamics. , 2012, Journal of theoretical biology.

[4] S. Sarr,et al. Impact of contamination factors on the COVID-19 evolution in Senegal , 2020, 2006.16326.

[5] Diaraf Seck,et al. Visualization and machine learning for forecasting of COVID-19 in Senegal , 2020, 2008.03135.

[6] Fred Brauer,et al. Mathematical epidemiology: Past, present, and future , 2017, Infectious Disease Modelling.

[7] Gerardo Chowell,et al. Is West Africa Approaching a Catastrophic Phase or is the 2014 Ebola Epidemic Slowing Down? Different Models Yield Different Answers for Liberia , 2014, PLoS currents.