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. 2021 Jul 2;9(7):728.
doi: 10.3390/vaccines9070728.

COVID-19 Pandemic Development in Jordan-Short-Term and Long-Term Forecasting

Tareq Hussein  1   2 , Mahmoud H Hammad  1 , Pak Lun Fung  2 , Marwan Al-Kloub  3 , Issam Odeh  4 , Martha A Zaidan  2   5 , Darren Wraith  6
Affiliations

COVID-19 Pandemic Development in Jordan-Short-Term and Long-Term Forecasting

Tareq Hussein et al. Vaccines (Basel). .

Abstract

In this study, we proposed three simple approaches to forecast COVID-19 reported cases in a Middle Eastern society (Jordan). The first approach was a short-term forecast (STF) model based on a linear forecast model using the previous days as a learning data-base for forecasting. The second approach was a long-term forecast (LTF) model based on a mathematical formula that best described the current pandemic situation in Jordan. Both approaches can be seen as complementary: the STF can cope with sudden daily changes in the pandemic whereas the LTF can be utilized to predict the upcoming waves' occurrence and strength. As such, the third approach was a hybrid forecast (HF) model merging both the STF and the LTF models. The HF was shown to be an efficient forecast model with excellent accuracy. It is evident that the decision to enforce the curfew at an early stage followed by the planned lockdown has been effective in eliminating a serious wave in April 2020. Vaccination has been effective in combating COVID-19 by reducing infection rates. Based on the forecasting results, there is some possibility that Jordan may face a third wave of the pandemic during the Summer of 2021.

Keywords: linear forecast; public immunity; vaccination; white-box model.

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Conflict of interest statement

The author declares no conflict of interest.

Figures

Figure 1
Figure 1
Daily reported cases of positive qPCR tests, recovered, and death since the first case was reported in Jordan (14 March 2020).
Figure 2
Figure 2
Cumulative reported cases of positive qPCR tests, recovered, and death since the first case was reported in Jordan (14 March 2020).
Figure 3
Figure 3
(a) Number of daily and cumulative qPCR tests performed in Jordan since the first case was reported (14 March 2020). (b) Daily and cumulative percentage of the positive qPCR cases out of the performed tests.
Figure 4
Figure 4
Daily percentage of the positive qPCR cases out of the performed tests and cumulative vaccination (at least once).
Figure 5
Figure 5
A scheme showing the short-term forecast (STF) model.
Figure 6
Figure 6
A scheme showing the long-term forecast (LTF) model.
Figure 7
Figure 7
A scheme showing the hybrid forecast (HF) model.
Figure 8
Figure 8
Short-term forecast (STF) models (Equation (1)) for the COVID-19 pandemic in Jordan based on the positive qPCR cases out of the performed daily tests (as percentage out of the total qPCR daily tests): (a,b) previous 5 days learning, (c,d) previous 10 days learning, (e,f) previous 20 days learning, (g,h) previous 40 days learning. The left panel is the time-series of the percentage of the daily positive qPCR tests percentage and the right panel is the corresponding scatter plots between the forecasted and the reported daily positive qPCR tests percentage. Legend of the left panel: (dots) reported and (line) forecasted.
Figure 9
Figure 9
Long-term forecast (LTF) model (Equation (2)) for the COVID-19 pandemic in Jordan based on the positive qPCR cases out of the performed daily tests (as percentage out of the total qPCR daily tests). Legend: (dots) reported and (line) forecasted.
Figure 10
Figure 10
Hybrid forecast (HF) model: (a) is the time-series of the pandemic and (b) is the scatter plot between the predicted and the reported percentage of the daily positive qPCR daily testes.
See this image and copyright information in PMC

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