IDSP to Big Data
Outbreaks of infectious diseases threaten lives, our health and the economy. In a world where people make multiple contacts at work, home or in leisure activities, outbreaks arise and spread rapidly.
Recent multi-country viral outbreaks such as Ebola and Severe Acute Respiratory Syndrome (SARS) claimed thousands of lives and cost billions of dollars.
Foreseeing an outbreak
When diseases are predictable, theoretically, health systems can be designed to manage them. In India, this does not happen because hospital bed occupancy is high; but planning ensures supplies and drugs.
But in a public health-care system that is already stretched, when new diseases emerge recognition and response are slow and frequently inadequate in the early stages of the outbreak. Once the outbreak has spread and is more widely recognised, all available resources are brought to bear on the outbreak. This results in a gross disruption of services available for routine health care, resulting in unrecognised damage that can impact the structure of the system and delivery of health care well beyond the outbreak.
Efforts in India
Recognising the importance of surveillance, the Ministry of Health and Family Welfare set up an Integrated Disease Surveillance Programme (IDSP) at the National Centre for Disease Control that uses district and State-level systems to report weekly on outbreaks of disease across India.
Efforts have been invested in building the system and trying to increase its capacity to generate actionable data.
Not much progress
But even years after initiation, the bulk of surveillance reports have failed to predict the outbreaks.
Although 40 to 50 outbreaks are reported each week, the most common outbreak reports are of diarrhoeal disease and food poisoning. Media scanning and analysis are a part of the tracking system, but there are lacunae because the IDSP did not report cases of chikungunya in September 2016 in Delhi.
Using data
There has been a great interest in using data that is gathered incidentally to recognise outbreaks early or predict the potential for outbreaks. For example, Google Flu Trends launched in 2008, aggregated Google search queries to provide estimates of influenza trends in 25 countries.
However, it failed to predict the 2013 flu season and was halted in 2015. Analysis showed how big data analytics requires caution and a changing of algorithms over time.
Nonetheless, the use of collated data sources for insights for public good is a key challenge that needs to be overcome to build rapidly responsive collaborations between industry, governments and academia, that share data while protecting individual privacy.
Underutilized in India
The velocity, variety and volume of big data defined by time and location are a resource that is currently underutilised in India because we have not yet built the systems for collaborations for the analysis and the inference we need for public health.
Planning for the use of such networks should be a key strategy in our plans whether it is for infectious disease outbreaks or other emergency situations.