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Data · dataset · 2026

Synthetic dataset and simulation code for 'A Mathematical Model for the Transmission of COVID-19 in Mindanao: Epidemic Prevention and Control Measures'

Listed in Teesside University Research Data Repository

This deposit contains the complete synthetic dataset and the simulation code used to generate all numerical results reported in the related manuscript "A Mathematical Model for the Transmission of COVID-19 in Mindanao: Epidemic Prevention and Control Measures" (submitted to the Journal of Theoretical Biology).

Description

The manuscript formulates a nine-compartment deterministic ODE model for COVID-19 transmission in Mindanao, Philippines, with compartments susceptible (S), exposed (E), symptomatic infectious (I_s), asymptomatic infectious (I_a), isolated (Q), untested symptomatic (U_s), untested asymptomatic (U_a), hospitalized (H), and recovered (R), and force of infection lambda = beta*(I_s + theta*I_a)/N. Three intervention scenarios are simulated over a 300-day horizon: Scenario 1 (baseline, no control, R0 = 2.07), Scenario 2 (relaxed measures, Re = 1.44), and Scenario 3 (strict local-government prevention and control measures, Re = 0.86).

Because officially disaggregated daily case series for Mindanao were not publicly available for the study period, all parameter values are synthetic/calibrated so that the baseline scenario reproduces an unmitigated reproduction number consistent with early COVID-19 estimates. The calibration anchors are the July 26, 2020 situation reports of the Philippine Department of Health (DOH) and the World Health Organization (WHO), tabulated in data/calibration_anchors_DOH_WHO_2020-07-26.csv.

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Contents: - data/scenario1_baseline_timeseries.csv, scenario2_relaxed_measures_timeseries.csv, scenario3_strict_lgu_timeseries.csv: daily compartment values, days 0-300 - data/model_parameters.csv: parameter values for all scenarios (Table 1 of the manuscript) - data/initial_conditions.csv: seeding of the epidemic - data/calibration_anchors_DOH_WHO_2020-07-26.csv: DOH/WHO situation-report anchor values - code/simulate_covid19_mindanao.py: Python script that reproduces all CSVs and figures - figures/fig1_baseline.png and fig2_scenarios.png: the manuscript figures as regenerated by the code - README.md: full documentation, column definitions, and verification table Funding: Research Office of Central Mindanao University.

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Simulation 75% · Tabular 65%
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