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.
Links
Where it is published
- DOI doi.org/10.17632/ndmv9373st.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Applied mathematics · Earth & Environmental Science · Engineering · Epidemiology · Humanities · Life Sciences · Mathematics & Statistics · Medicine & Health · Public health · Social Science
- Inferred from text
- Simulation 75% · Tabular 65%
Provenance · 1 source records, 17 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/ndmv9373st.1 | 4 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4202 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Epidemiology'] |
| concepts[field].anzsrc:group:4206 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Public Health'] |
| concepts[field].anzsrc:group:4901 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Applied Mathematics'] |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:mathematics-statistics | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:tabular | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |