| Introduction: Contextual introduction. Body: Explain importance of Digital models for disease tracking. Also write some issues associated with these models. Conclusion: Write a way forward. |
Digital approaches can improve the timeliness and depth of surveillance information. In India Integrated Disease Surveillance Project was started in 2004 and the Integrated Health Information Platform in 2019.The World Health Organization now routinely uses HealthMap, ProMED and similar systems to monitor infectious disease outbreaks, inform clinicians etc.
Importance of Digital models for disease tracking:
- Public health surveillance helps in the identification, collation and analysis of disease occurrence. It is the bedrock of national healthcare architecture.
- Internet-based disease detection and monitoring tools offer real-time surveillance with much greater temporal and spatial resolution compared to traditional surveillance systems. Recent epidemics and the COVID-19 pandemic highlight its importance to support public health prevention and containment measures.
- Digital disease surveillance is less costly and time consuming compared to traditional surveillance.
- Two key advantages- speed and volume may increasingly help health officials spot outbreaks quickly and cheaply.
Issues associated with these models:
- Public health institutions tracking disease occurrence based on data generated by states are the primary disease surveillance arms. But the state’s performance so far has been less optimalas they often function in silos.
- Over the next decade, having adequate skilled personnel in public health surveillancemay be a bigger challenge. For instance, WHO’s International Health Regulations are binding on members.
- At the same time, the huge volume of digital data also comes with sufficient challenges to accuracy and privacy to make it a “double-edged sword’. Digital models are not regulated by a robust personal data protection bill.
- Social media is justifiably notorious for spreading falsehoods, which in the case of infectious diseases can have deadly consequences. Public health depends on trust in public officials, but that trust can quickly erode if a government releases faulty information.
- No automated framework that combines data streams, analyses them in a statistically robust manner, and produces actionable reports in near real-time has been developed.
Digital models are set to bring far-reaching changes in public health surveillance by expanding sources of data collation to the private sector, which is an important component of the overall healthcare system.
