## 6 Novel mHealth Predictive Outbreak for COVID-19 (mPOC) Algorithm and IoMT Protocol
### PEI Construct  
The Predictive Exposure Index (PEI) is also a recursive index primarily influenced by environmental and behavioral factors. In the initial stage, the algorithm collects information from the user regarding their household members, occupations, and other factors that impact their typical behaviors, as depicted in Equation (2).  
During the IoMT stage, the algorithm monitors the user's physiological changes and captures environmental sounds, analyzing the rate at which they are changing, particularly in relation to DRI-related parameters.  
In the PRAaS stage, PEI is actively updated by receiving location details from GPS and mobile networks, tracking the user's current location, movement, and intended final destination. The system regularly sends PEI updates to the Outbreak Tracking Center (OTC) and receives real-time updates from the Public Health Broadcasting Agencies and OTC. The DRI and PEI updates are translated into audio warnings for the users, indicating the risk level of their destination. Furthermore, users at the destination are informed about the risk rating of impending arrivals, showcasing the predictive nature of the system. The calculation of future PEI values involves considering both current DRI and PEI values in a recursive manner, as outlined in Equation (2). These dependencies, along with user behavior and movements, are presented in Table 3. As mentioned, the PEI/DRI calculation results are converted into audio and video signals, which users receive as health and location risk alerts and notifications (Table 3).  
Upon initializing the mPOC application, PEI starts with a user-specific initial value. Based on Equation (2) and the user's movements, PEI is updated with new values. For instance, if the user remains stationary at home, the PEI value will remain low, and this information will be conveyed to the OTC. As the user ventures out of their residence, the PEI value may change depending on the risk factors associated with the trajectory or destination (for instance, going to a high-risk area will increase the PEI value). The DRI also continuously senses physiological parameters and updates its values accordingly. These two indices trigger appropriate light and audio notifications on the smartphone running the mPOC application to alert the user accordingly. Figure 3 shows the flowchart of the system and the three stages.  
\[PEI\left[i+1\right]=F(DRI\left[i\right],hh,OTC,Im,PEI\left[i\right]) \tag{2}\]  
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Location** & **Location** & **PEI** & **DRI** & **PEI** & **Alert** \\
**(Now)** & **(Next)** & **(Now)** & & **(Next)** & **(Light-Audio)** \\ \hline Home & LRL & \(\uparrow\) & \(\uparrow\) & \(\approx\) & A/LRA \\ \hline Home & MRL & \(\downarrow\) & \(\downarrow\) & \(\approx\) & A/MRA \\ \hline Home & MRL & \(\uparrow\) & \(\downarrow\) & \(\uparrow\uparrow\) & A/MRA \\ \hline Home & MRL & \(\downarrow\) & \(\uparrow\) & \(\approx\) & R/MRA \\ \hline Home & MRL & \(\uparrow\) & \(\uparrow\) & \(\uparrow\uparrow\) & R/MRA \\ \hline Home & HRL & \(\downarrow\) & \(\downarrow\) & \(\approx\) & A/HRA \\ \hline Home & HRL & \(\uparrow\) & \(\downarrow\) & \(\uparrow\uparrow\) & A/HRA \\ \hline Home & HRL & \(\downarrow\) & \(\uparrow\) & \(\approx\) & R/HRA \\ \hline Home & HRL & \(\uparrow\) & \(\uparrow\) & \(\uparrow\uparrow\) & R/HRA \\ \hline MR & LRL & \(\uparrow\) & \(\downarrow\) & \(\uparrow\uparrow\uparrow\) & R/VHRA \\ \hline HR & LRL & \(\uparrow\) & \(\downarrow\) & \(\uparrow\uparrow\uparrow\) & R/VHRA \\ \hline \hline \end{tabular}  
* \(\uparrow\uparrow\): Higher (e.g., 3 to 8); \(\uparrow\uparrow\uparrow\): Highest (e.g., 1 to 10); \(\approx\): Remain; DRI Color Codes: Green (G), Yellow (Y), Amber (A), Red (R); PEI: Audio Codes: Silent (S), Low Risk Alert (LRA), Medium Risk Alert (MRA), High Risk Alert (MRA), Very High Risk Alert (VHRA).  
\end{table}
Table 3: _Cont._hh_: household data, _lm_: location and movement.