4-month malaria epidemic warning for North India
American scientists have found a novel way to forecast malaria epidemics in northwest India, 4 months before they break out, in findings that could help govts prepare much better than with the present, 1-month forecasts. Charu Sudan Kasturi reports.Updated: Mar 04, 2013 01:16 IST
Changes in sea surface temperatures in the South Atlantic Ocean could help predict malaria epidemics in north-west India well before actual outbreaks, scientists have found, potentially handing public health officials more time to tackle the parasitic disease that strikes 9 million Indians every year.
Lower July temperatures in the tropical South Atlantic are associated with malaria epidemics in Delhi, Rajasthan, Punjab and Haryana 4-months before actual outbreaks that typically occur in October or November, the scientists at the University of Michigan Ann Arbor have found. Their research was published on Sunday in reputed journal Nature Climate Change.
“The climate link we have uncovered can be used as an indicator of malaria risk,” said ecologist Mercedes Pascaul, who headed the team. “We hope these findings can be used as part of an early warning system.”
The probability of malaria epidemics is currently calculated largely by looking at monsoon-season rainfall totals to predict the likelihood of breeding sites for the Anopheles mosquito that carries the malaria parasite. This typically gives public health officials just a one-month head-start over actual outbreaks – often not enough time.
Pascaul and her colleagues analyzed malaria incidence records from India’s northwest states from 1985 to 2006, and then used statistical and computerized climate models to examine any associations between sea surface temperatures and malaria epidemics.
They found that colder-than-usual July temperatures of the sea in the tropical South Atlantic, just west of Africa coincided with increases in both monsoon rainfall and in malaria incidence in northwest India in 9 out of 11 epidemic years. Their model also predicted the non-epidemic years accurately.