New York | Researchers, including those of Indian-origin, have developed a system that can accurately forecast the outbreak of dengue fever two to three weeks ahead of time, by simply analysing the calling behaviour of citizens to a public-health hotline.
Thousands of lives are lost every year in developing countries for failing to detect epidemics early because of the lack of real-time data on reported cases, said Lakshminarayanan Subramanian from New York University (NYU) in the US. We think our technique can be of use to public-health officials in their fight against the spread of crippling diseases, said Subramanian.
The telephone-based disease surveillance system can forecast two to three weeks ahead of time and with intra-city granularity, the outbreak of dengue fever, a mosquito-borne virus that infects up to 400,000 people each year. The system measures the number of calls received at a health hotline facility to forecast the number of dengue cases at a block-by-block level, researchers said.
Instead of allocating a large work force to collect block-by-block level data on disease incidences, we crowdsource these data using citizen enquiries and feedbacks, said Umar Saif, chairman of the Punjab Information Technology Board, which implemented the system in Pakistan. This makes health hotlines ideal for resource- constrained environments in developing countries, said Saif.
Huge infrastructure is required to collect and analyse disease surveillance data traditionally from all healthcare facilities in a country. The primary appeal for this system is its capability to closely monitor disease activity by merely analysing citizen calls on a public-health hotline, researchers said. Early warning systems in the past only generate alerts of disease outbreaks on a city or state level.
Alerts are often of little significance given that governments do not have enough resources to allocate to large geographical units said Nabeel Abdur Rehman from NYU. Our goal was to develop a system that could pinpoint the location inside a city where disease activity has increased so the government could perform targeted containment of a disease, said Rehman.
Researchers including Shankar Kalyanaraman from NYU used more than 300,000 calls to the health hotline, set up in the aftermath of the 2011 outbreaks, to forecast the number of dengue cases across the city and at a block-by-block level over a period of two years.
They then matched their predictions with the actual number of cases reported in public hospitals. The results showed a high level of accuracy for the model’s predictions: the system not only flagged an outbreak, but also made an accurate forecast of both the number of patients and their locations two to three weeks ahead of time.
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