Mapping disease with big data

Mapping disease with big data

Mapping disease with 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, live in close-built environments that are changing global ecology, and where travel is frequent, 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.

When diseases are predictable, theoretically, health systems can be designed to manage them. For example, if hospitals know the seasonality of influenza, pneumonia or diarrhoea, they can plan for the surge in admissions, ensuring that beds and staff are available when needed. 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 (especially if there is political pressure), 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.

Read Also:
Will Business Intelligence (BI) Ever Be Consumerized?

In a country with 1.3 billion people, with a marked inequity in health care, dense urban populations, multiple contact with domestic and wild animals, frequent internal migration, a large diaspora, international air links and a warm climate, we are uniquely positioned to be most at threat from indigenous and imported infectious diseases.

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. But even years after initiation, the bulk of surveillance reports continue to be syndromic, with less than a third of outbreaks laboratory confirmed. 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 even when reports filled the columns of national newspapers.

Read Also:
How Big Data Is Improving Health, Security, and Saving Money for Agencies

 



Chief Data Officer Europe
20 Feb

15% off with code CDO7W17

Read Also:
Trust in data and analytics is a non-negotiable priority
Predictive Analytics Innovation summit San Diego
22 Feb

$200 off with code DATA200

Read Also:
Will Business Intelligence (BI) Ever Be Consumerized?
Read Also:
Will Business Intelligence (BI) Ever Be Consumerized?
Big Data Paris 2017
6 Mar
Big Data Paris 2017

15% off with code BDP17-7WDATA

Read Also:
5 Ways to Avoid Common Pitfalls in Large-Scale Analytics Projects

Leave a Reply

Your email address will not be published. Required fields are marked *