# Country-Based COVID-19 DNA Sequence Classification in Relation with International Travel Policy
## 3 Results and Discussion  
Figure 4 displays the accuracy chart of DNA sequence classification for the MLP, CNN, and BiLSTM models. When considering all available sequences, as depicted in Figure 4, it is shown that sequences from Brunei can be distinguished from those of other ASEAN countries with almost perfect accuracy, reaching 98%. Conversely, the three countries with a lower accuracy are Indonesia, Malaysia, and Vietnam. This pattern remains relatively similar when exclusively involving the Delta variant in the dataset for each country, as shown in Figure 4. Therefore, even though the variant is the same, the DNA sequences can still be differentiated based on the country of origin. \begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Model** & **Main Layer: Unit/Filter [Dropout]** & \begin{tabular}{c} **Fully Connected Layer:** \\ **Unit, Activation, Dropout** \\ \end{tabular} & \
\begin{tabular}{c} **Output Layer** \\ **Output Layer** \\ \end{tabular} &
\begin{tabular}{c} **Hyperparameters:** \\ **Optimizer, Learning** \\ **Rate, Batch Size** \\ \end{tabular} \\ \hline MLP & Dense (6 layers): 400, 300, 200, 100, 50, 10 [0.3] & ReLU & Dense (2, softmax) & Adam, 0.001, 1000 \\ CNN & Conv1D (3 layers): 100, 100, 80. & 20, ReLU, 0.5 & Dense (2, softmax) & Adam, 0.001, 1000 \\ BiLSTM & BiLSTM (1 layer): 80 [0.2] & 20, ReLU, 0.5 & Dense (2, softmax) & Adam, 0.001, 1000 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The architectures of the deep-learning models used for country-based COVID-19 DNA sequences classification. Figure 4: Accuracy chart of ‘one-vs-all’ country-based classification using MLP, CNN, and BiLSTM models (**a**) involving all available sequences and (**b**) only involving Delta variant sequences. Regarding the impact of different areas among ASEAN countries, while Brunei exhibits a higher sequence accuracy than Malaysia, for instance, it is noteworthy to consider other classification results depicted in Figure 4. In this figure, the sequence accuracy of Singapore, despite being a small country, is not higher than that of Cambodia and Laos, two countries with larger geographical areas. In future work, it would be intriguing to explore the correlation between a country's size and the diversity of its DNA sequences for generalizing this finding. Table 4 demonstrates the detailed performance metrics for each model, involving Delta variant sequences. The execution time, which measures the time in seconds at which the code is executed for the dataset of each corresponding country, is also calculated. Notably, from Table 4, the execution time of the MLP is relatively faster than that of the CNN or BiLSTM, with a comparable level of accuracy. Hence, the MLP model proves to be suitable in terms of both accuracy and execution time. For further assurance in evaluating the performance of the MLP model, Table 5 shows the classification accuracy resulting from the 10-fold cross-validation technique. It is obvious from Table 5 that the accuracy results are relatively similar to those of the previous scenario where the model was trained without the implementation of cross-validation. We now analyze these classification results in the context of the pandemic situation and the implementation of international travel policy. Initially, we observed the pandemic situation in each country, focusing particularly on the number of cases and deaths accumulated during the period from July to December 2021. Referring to the second dataset from official data collated by Our World in Data [26], as depicted in Figure 5, it appears non-coincidental that Malaysia, one of the countries with a lower accuracy, experienced a severe condition with a notably high number of both accumulated new cases and deaths per million people. In contrast, Cambodia and Laos exhibited relatively lower numbers. While it is premature to conclude that a country with high accuracy, in terms of its DNA sequence, which can be distinguished well from others, tends to undergo a favorable