Predicting malaria, encephalitis before they get you

Diseases like malaria and Japanese encephalitis can now be avoided, not by vaccines but through prediction. Scientists from Bangalore-based Centre for Mathematical Modelling and Computer Simulation (C-MMACS) are developing two models that will help predict where mosquitoes with disease-causing germs are prevalent.

Using this information, one may either avoid living in the areas or take measures to eliminate the mosquitoes.

Malaria outbreak depends on two factors—the mosquito population and the exposure of human beings to mosquitoes.

Through these two models, the C-MMACS scientists will be able to tell people where not to go, and take the preventive methods, said C-MMACS scientist, Prashant Goswami, who is heading the research.

The project has been taken up in collaboration with University of Liverpool, UK, and various Centre for Scientific and Industrial Research (CSIR) agencies, including Indian Institute of Chemical Technology (IICT), Hyderabad.

Goswami said he and his team had already developed the first model for short-term prediction that will provide data pertaining to mosquito population in a particular area two days in advance. The second model, which is in the process of being developed, will give similar data two months in advance.

C-MMACS scientists are of the opinion that such predictions, if sent out in form of a bulletin, could help people plan their outings to a particular region, or even help them decide which area they would want to buy a home to settle down in.

The models will be able to predict mosquito population owing to various climatic conditions in a particular area.  “The models are not climate models; they are malaria-focus models. We will be able to predict the population of mosquitoes by measuring rainfall, temperature, humidity, and the number of daylight hours in a day. And when we put it together with human population, we will be able to provide the exposure (to mosquitoes) probability,” said Goswami.

“Currently, there are models that measure the outbreak of malaria, but this will predict it beforehand. Our philosophy is ensuring wellness beforehand rather than going into treatment after being afflicted,” he said.

While the short-term model was developed in collaboration with IICT, Hyderabad, “for the long-term model we collaborated with the University of Liverpool, which we are trying to make suitable for Indian conditions,” Goswami revealed.

Both the models need to be validated before being introduced to large-scale usage, wherein the data can be used by government or private agencies, or even individuals seeking information about mosquito prevalence in a particular area.

“We will check if the models work in various Indian states and then it will be functional. The models ought to be ready in a matter of a few months,” he said.