# Partially versus Purely Data-Driven Approaches in SARS-CoV-2 Prediction
## 4 Results
### Exponential Regression Model Results  
In this model, all dependent variables are transformed into log scale before applying the regression model. An exponential trend model is computed for the sum of confirmed, new, and death cases (actual and forecast) given day of date. The confidence level is taken at 95%, so the model is significant at \(p\leq 0.05\); the results of applying the exponential regression model for US, Jordan, and Italy are shown in Table 3.  
As shown in Table 3, the lowest SSE value is recorded in Jordan's death cases, which is very similar to the result of the linear regression model; this shows that the death cases in Jordan are varying at a very low random rate. Figure 9 shows the constant exponential line for death cases in Jordan. MSE shows the different between the predicted and actual values. The exponential regression model outperforms the linear regression model, as exhibited by the low MSE rates recorded in all confirmed, new, and death cases in the three selected countries.  
R-squared is maximum in the US, Jordan, and Italy confirmed cases, respectively. This shows that the time variable is a very good predictable variable for the confirmed cases more than new and death cases. For example, 75% of the confirmed cases in the US can be predicted using the independent variable (time).  
\(p\) value \(<0.05\) indicates that the overall model is significant. The result shows significant models in all countries confirmed, death, and new cases, except the death cases model in Jordan, which means the model cannot be taken. However, the null hypothesis that assumes that there is no relation between time and death cases in Jordan is taken.  
Table 4 lists the prediction numbers for confirmed, new, and death cases using the generated exponential regression models. The table shows the prediction number for 24 August 2020, and the date of first future zero cases.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Country** & **Italy** & **Jordan** & **US** \\ \hline \multirow{3}{*}{**Confirmed Cases**} & **Prediction (done on 24 August 2020)** & 247,984 & 1401 & 4,061,952 \\  & **First zero** & Not Applicable & Not Applicable & Not Applicable \\ \hline \multirow{3}{*}{**New Cases**} & **Prediction** & 1197 & 18 & 38,221 \\  & **First Zero** & 26 July 2020 & Not Applicable & Not Applicable \\ \hline \multirow{3}{*}{**Death cases**} & **Prediction** & 119 & Zero & Zero \\  & **First Zero** & Not Applicable & Zero Since 2 nd & \\ \cline{1-1}  & **First Zero** & Not Applicable & May 2020 & 12 th July 2020 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Future Prediction Numbers using Exponential Regression Models for Italy, Jordan, and US.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Country** & \multicolumn{3}{c}{**Italy**} & \multicolumn{3}{c}{**Jordan**} & \multicolumn{3}{c}{**US**} \\ \hline Model & \multicolumn{6}{c}{Forecast Indicator Day of Date + intercept()} \\ Formula & & & & & & & & \\ \hline \multirow{2}{*}{\begin{tabular}{c} SES (sum \\ squared \\ error): \\ MSE (mean \\ squared \\ error): \\ R-Squared: \\ Standard \\ error: \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} New \\ Cases \\ \end{tabular} } & Death & Confirmed & New & Death & Cases & Death & Confirmed & New & Death \\  & Cases & Cases & Cases & Cases & Cases & Cases \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} SES (sum \\ squared \\ error): \\ MSE (mean \\ squared \\ error): \\ R-Squared: \\ Standard \\ error: \\ error: \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} 1240.22 \\ 1240.  
Figure 11: Exponential Regression Models for (**a**) Confirmed Cases; (**b**) Death Cases; (**c**) and New Cases in Jordan.  
Figure 12: Exponential Regression Models for (**a**) Confirmed Cases; (**b**) Death Cases; and (**c**) New Cases in Italy.