“Extreme remedies are very appropriate for extreme diseases”, said Hippocrates, the father of Western medicine. ‘Kala-azar’, or visceral leishmaniasis is one such extreme disease in our country that is endemic mainly to Bihar, Jharkhand, Bengal and Uttar Pradesh. With an estimated 16 crore people at the risk of developing this infection, combating kala-azar needs extreme measures. Now, a group of interdisciplinary researchers consisting of mathematicians, statisticians and ecological researchers from the CSIR-National Chemical Laboratory, Pune, Adamas University, Kolkata, Sultan Qaboos University, Oman and Indian Statistical Institute, Kolkata, have come together to develop a strategy to eliminate this disease from the country.
Kala-azar is the second most common disease spread by insects, after malaria. It is caused by leishmanial group of protozoans (a particular type of parasitic microorganisms) spread by the bites of infected female phlebotomine sand flies. Characterized by greyish-black discolouration of the skin, this deadly tropical disease is aptly called ‘kala-azar’, meaning ‘black fever’. Though the government aims to eliminate kala-azar by 2017, there is a need for well-developed strategies at all levels to make this a reality.
Controlling kala-azar requires community efforts and efficient programmes targeted to control or eliminate the spread of sand flies. Since sand flies are usually found in rural areas in the temperature range of 15–38 °C, along with heavy rainfall, high humidity, abundant vegetation and stagnant water, measures to control them depend largely on the region, season and temperature variations. Spraying insecticides to kill sand flies and using an insecticide-treated bed net prevents the spread of the infection to a great extent. Also, infected patients are treated with an array of drugs.
The researchers of the study propose a mathematical model that can monitor the temporal dynamics of the spread of visceral leishmaniasis in human and vector (sand flies) populations. The model takes the numbers of people living in a particular area, the number of reservoirs in the area and an estimated sand fly population with its biting rates, as inputs. Based on a set of mathematical equations, the model then divides each of the above input parameters as - susceptible, infected and recovered number of people, susceptible and infected number of sand flies and susceptible and infected number of reservoirs. These parameters help in better understanding the severity of the disease in a given area.
In addition, the model also helps in curbing the progress of the infection and controlling the population of sand flies. Based on ‘optimal control theory’, the model analyses three combinations of control measures aimed at disease control-effectiveness as well as cost-effectiveness. In the first combination, the spray of insecticides and drug-based treatment of infected individuals are considered. The second combination of strategies is based on insecticide-treated bed net, spray of insecticides and drug based treatment. The third one involves the use of treated bed nets and spray of insecticides. The proposed mathematical model was verified with real disease data from South Sudan.
The researchers found that the combination of drug-based treatment of infected individuals and spray of insecticides was the most optimal, in terms of cost and effectiveness, and in controlling the disease as compared to the others. “Our aim was to identify which control strategy or combinations will be more effective based on these three approaches. These may also vary based on the country, region or severity of the disease. Hence, one needs to use suitable parameters to simulate our model and get the predictions about the optimal control strategies specific to that region so that a particular intervention strategy or combinations can be applied to control the effect of the disease on the populations, either for short or long periods of time”, says Dr. Ram Rup Sarkar, Principal Scientist, CSIR- National Chemical Laboratory, who was involved in this research.
This model has demonstrated that optimal control of kala-azar is possible by implementing intervention strategies at different time points of the infection in population. Studies like this highlight the cost benefit of different strategies and help predict the best one based on the outcomes. They also help decision makers, who are often faced by the challenge of resource allocation, in choosing plausible alternative strategies.