Parameter Estimation for a Modified SEIR Model of the COVID-19 Dynamics in the Philippines using Genetic Algorithm

  1. Gabriel Lorenzo I. Santos

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Abstract

The Philippines has been under a series of different levels of community quarantine and this affected the dynamics of the COVID-19 spread in the country. Predicting the trajectory has been an interest of various research groups. To provide a more efficient method to estimate the parameters of the Age-Stratified, Quarantine-modified SEIR model with Nonlinear Incidence Rates (ASQ-SEIR-NLIR) other than the shooting method, a genetic algorithm approach is explored. By defining constraints for each parameter, the algorithm arrived at an acceptable optimal value for each parameter. The experiment is done on two regions of interest: the Philippines (country-level) and Quezon City, Metro Manila (city-level). The ASQ-SEIR-NLIR model, using the parameters generated by the genetic algorithm, is able to produce an average trajectory compared to the actual data, which may be deemed noisy. The dynamics of the COVID-19 spread between Quezon City and average country level is compared, showing that the city population is being exposed to the virus at a much faster rate than the country average and may have more asymptomatics not getting tested than the country average. Given the average trajectory, the peak daily infection projection is way lower at 0.0823% of the country population for the country projection and 0.1494% of the Quezon City population for the city projection, which is below than previous literature estimates of 3-10%.

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    SciScore for 10.1101/2022.05.17.22275187: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    To implement the genetic algorithm and solve the differential equations, Python is primarily used, supported by Python libraries, specifically numpy and scipy.
    Python
    suggested: (IPython, RRID:SCR_001658)
    numpy
    suggested: (NumPy, RRID:SCR_008633)
    It may be addressed by adding more genes representing a specific time interval such as [12] but this modification is not pursued for this experiment because of the limitation of scipy.integrate.odeint solver not accepting array of values as parameter.
    scipy
    suggested: (SciPy, RRID:SCR_008058)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    As mentioned in Section 2.2.1, due to the limitation of scipy.integrate.odeint solver of not accepting a time-varying variable, an average trajectory is achieved. Figure 7 shows the actual daily cases against the predicted daily cases. It is noticeable how the trajectory produced by the ASQ-SEIR-NLIR model passes through the average of the actual data. This observation is valid for both country-level and citylevel. 3.3 Dynamics of COVID-19 Spread: The optimal parameters obtained from the genetic algorithm help describe the dynamics of the spread of COVID-19 at the country-level and at city-level. 3.3.1 Transition from Susceptible to Exposed: The parameters involved in this transition are the transmission or contact rate (β) and quarantine factor (Q), together with the nonlinear incidence rates behavioral factor (α) and disease-resistance factor (ϵ). Both regions of interest show relatively low compliance to minimum health standards yet relatively high disease-resistance rates, which may be attributed to increase vaccination efforts. This implies that there is high level of immunity but the high exposure rate is due to low compliance to minimum health standards. Both regions also differ in terms of contact rate but same quarantine factors. Quezon City has an average βQC = 3.12, which means higher probability of getting exposed to the virus, versus the βPH = 2 average for the whole country. However, the quarantine success spells the difference in terms of the total expected exp...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2022.05.17.22275187v1 on medRxiv