A team of researchers from New York University have developed a new system that can foretell the outbreak of dengue fever by simply evaluating the calling behaviour of citizens to a public-health hotline.
The new telephone-based disease surveillance system can predict the spread, along with the intra-city granularity, of dengue fever two to three weeks ahead of time.
Dengue fever is a mosquito-borne virus that infects up to 400,000 people every year.
New York University courant institute of mathematical sciences professor and part of the research team Lakshminarayanan Subramanian said: “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.
“We think our technique can be of use to public-health officials in their fight against the spread of crippling diseases.”
The new telephone-based prediction system is used to measure the number of calls received at a health hotline facility in a bid to foretell the number of dengue cases at a block-by-block level.
The traditional method of collecting disease surveillance data requires a large infrastructure to collect, as well as analyse disease incidence data from all healthcare facilities in a country.
However, the new system has the capability to closely monitor disease activity by simply evaluating the calls of the natives of a country to a public-health hotline.
New York University computer science and engineering doctoral student and a project researcher Nabeel Abdur Rehman 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 don’t have enough resources to allocate to large geographical units.
“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.”
The team of research scientists used more than 300,000 calls to the health hotline, which was established in the aftermath of the 2011 dengue fever outbreaks in a bid to forecast the number of dengue cases across the city and at a block-by-block level over a period of two years.
The researchers then matched their forecast with the actual number of cases reported in public hospitals, which exhibited a high level of accuracy for the model’s predictions that could not only foretell the number of patients to be affected, but also their locations two to three weeks in advance.
Image: A TEM micrograph showing Dengue virus virions (the cluster of dark dots near the centre). Photo: courtesy of CDC per University of South Carolina Biomedical Sciences.