Verification and preparation
1. Establish the existence of an outbreak: IT systems like automated surveillance and real-time dashboards help detect unusual increases in cases and trigger early alerts.
2. Verify the diagnosis: Laboratory Information Management Systems (LIMS) and teleconsultation tools enable accurate and rapid confirmation of the disease.
3. Prepare for field work: Mobile apps, GIS mapping, and digital data collection tools assist in planning logistics and organizing field investigation teams.
Describe the outbreak
4. Construct a working case definition: Shared online documents and digital collaboration platforms ensure consistent and updated case definitions across all investigators.
5. Find cases systematically & record information: Digital data collection tools and EMR integration allow efficient case finding, data entry, and tracking with minimal errors.
6. Perform descriptive epidemiology: Data analysis and visualization software (e.g., R, Power BI) produce epidemic curves, maps, and summary tables instantly.
Hypothesis and testing
7. Develop hypothesis: Data mining and statistical software (e.g., R, Python) help identify potential exposure patterns and formulate preliminary hypotheses.
8. Analytical studies to test hypotheses: Advanced analytics programs (e.g., R, Python, SPSS) are used to compare data between groups and test associations statistically.
9. Special studies (e.g., environmental, laboratory): Internet of Things (IoT) sensors and bioinformatics tools link environmental and genetic data to understand sources and transmission pathways.
Response and action
10. Implementation of control measures and follow-up: IT supports communication of interventions via alerts and tracks the effectiveness of control measures through dashboards.
11. Communication – including outbreak report: Digital reporting platforms and dashboards enable timely sharing of findings and outbreak updates with stakeholders and the public.