Selected article for: "lag time and time point"

Author: REZKI, M.
Title: Estimating the total size of coronavirus epidemic in Algeria via different approaches
  • Cord-id: ld77bjpv
  • Document date: 2020_8_1
  • ID: ld77bjpv
    Snippet: In this paper, several techniques and models proposed the spread of coronavirus (Covid-19) and determines approximately the final number of coronavirus infected cases as well as infection point (peak time) in Algeria. To see the goodness of the predicting techniques, a comparative study was done by calculating error indicators such as Root-Mean-Square Error (RMSE) and the sum of squared estimate of errors (SSE). The main technique used in this study is the logistic growth regression model widely
    Document: In this paper, several techniques and models proposed the spread of coronavirus (Covid-19) and determines approximately the final number of coronavirus infected cases as well as infection point (peak time) in Algeria. To see the goodness of the predicting techniques, a comparative study was done by calculating error indicators such as Root-Mean-Square Error (RMSE) and the sum of squared estimate of errors (SSE). The main technique used in this study is the logistic growth regression model widely used in epidemiology. The results only relate to the two months from the beginning of the epidemic in Algeria, which should be readjusted by integrating the new data over time, because hazardous parameters like possible relaxations (decrease of vigilance or laxity of society) can affect these results and generally cause a time lag in the curve. Hence, a re-estimation of the curves is always requested.

    Search related documents:
    Co phrase search for related documents
    • logistic model and low degree: 1, 2, 3