Quick Start =========== Epidemic Model -------------- .. code-block:: python from episia import epi # Run SEIR model model = epi.seir( N=1_000_000, I0=10, E0=50, beta=0.35, sigma=1/5.2, gamma=1/14 ) result = model.run() print(result) # Plot results result.plot().show() Biostatistics ------------- .. code-block:: python from episia import epi # Calculate risk ratio rr = epi.risk_ratio(a=40, b=10, c=20, d=30) print(rr) # Output: Risk Ratio: 2.667 (1.514-4.696) # Confidence interval for proportion prop = epi.proportion_ci(k=45, n=100) print(prop) # Output: Proportion: 0.4500 (0.354-0.549) # Diagnostic test evaluation diag = epi.diagnostic_test_2x2(tp=80, fp=20, fn=10, tn=90) print(f"Sensitivity: {diag.sensitivity:.3f}") print(f"Specificity: {diag.specificity:.3f}") DHIS2 Integration ----------------- .. code-block:: python from episia.dhis2 import DHIS2Client # Connect to DHIS2 demo instance client = DHIS2Client( url = "https://play.dhis2.org/40.2.2", username = "admin", password = "district", ) # Fetch surveillance data ds = client.to_dataset( data_element = "FTRrcoaog83", # Malaria cases period = "LAST_52_WEEKS", org_unit = "ImspTQPwCqd", # Sierra Leone ) print(f"Loaded {ds.total_cases} cases") print(f"Date range: {ds.date_range}") # Generate epidemic curve ds.to_timeseries_result().plot().show() Reporting --------- .. code-block:: python from episia import epi # Generate report from model result report = epi.report( result, title="SEIR Model - Burkina Faso 2024", author="Dr. Ouedraogo" ) # Export in multiple formats report.save_html("report.html") report.save_markdown("report.md") report.save_json("report.json") More Examples ------------- See the `Examples directory `_ for more detailed examples.