Battling superbugs with Big Data
Antibiotics that once cured ailments across the spectrum are now turning into a potential source of prolonged illness, disability and death. The world is transitioning to a post-antibiotic era where common infections and minor injuries will begin to kill, thanks to increasing antibiotic resistance (ABR). In 2015, such resistance was identified as the cause for about 23,000 deaths annually in the US and about 25,000 such deaths in Europe. While accurate data on the incidence of antibiotic resistance in India is unavailable, the highest number of deaths caused by resistant pathogens passed on to newly born babies from mothers or the environment—approximately 58,000—was in our region.
Though ABR in certain cases occurs through the natural evolution of resistance in bacterial pathogens, the rising consumption of antibiotics is a major contributor. Topping this, the New Delhi metallo-beta-lactamase (NDM) enzyme, which makes bacteria resistant to beta-lactam antibiotics, is now present globally. This indicates free movement of ABR across boundaries, with serious consequences. This is nowhere as stark as in India. Our large population is often blamed for the widespread dissemination of a higher number of resistant pathogens, commonly called superbugs. However, it is the interplay of domestic factors such as a weak public health system, cheap antibiotics available in the market, and their unregulated use, that has created ideal conditions for superbugs.
Prescription of antibiotics for a variety of diarrhoeal and respiratory infections despite their limited curative potential has exacerbated the situation. Poor regulation of pharmacies and licensing out several pharmacies to a single pharmacist introduces a large number of unqualified personnel into the supply chain. New virtual marketplaces have made the entire drug distribution process an opportunity for unchecked financial gains by irresponsible actors. The lack of awareness among patients regarding the appropriate use of antibiotics has led to self-medication and non-adherence to the prescribed course of antibiotics, further intensifying the problem.
The dramatic increase in prevalence of superbugs and the dearth of new antibiotics in the market is a warning signal for India. The absence of a good statistical model to show the relationship between antibiotic consumption and associated resistance makes it difficult to frame usage guidelines for these antibiotics. This in large measure explains the absence of any great success even post the Chennai declaration of 2012. To meet the obligations of this declaration, the National Programme on Containment of Antimicrobial Resistance was launched under the 12th Five-year Plan. A core objective was the generation of quality data from 30 laboratories on antimicrobial resistance of pathogens posing a grave public health risk. Though meant to be completed within 2017, only 10 labs have so far been brought within the data-gathering exercise.
Tackling the superbug problem requires massive data collection and analysis. Well-designed studies and indicator surveys providing general insight into the situation are critical to begin with. While studies can provide a clearer picture of the prescribed doses of antibiotics and their pattern of use (including the why, when, where, and for what relating to antibiotic consumption), indicator surveys can attempt to identify the health outcomes emerging from the use of such antibiotics for different ailments. Frequently repeated surveys, with their range expanded to track geographic and demographic representative data, are a policy imperative if India wants to build comprehensive indicators of ABR.
But tracking the data is not in itself of great use unless the health departments of the Central and state governments work in coordination with nodal bodies in the technology space to develop an information-sharing grid. The grid should also have smart data-mining solutions built into it. The virtuous loop of integration of data from various public and privately operated hospitals, pharmacies, and drug procurement services across the country, data analytics to track the correlation between antibiotic consumption and induced drug resistance, and robust information sharing with the public and health authorities is the right approach moving forward. Molecular biologists should be consulted for their insights on the genetic and molecular mechanisms responsible for such resistance.
ABR can be handled successfully once efforts are directed to establish efficient data-mining techniques and a team of specialists is trained to translate this research into useful clinical practice. The database created can certainly help in unravelling the hidden relations between antibiotic use and its associated resistance. Access to this online database can help physicians track ABR patterns; predict health outcomes; and prescribe drugs suitable for patient needs. It will not only help in improving clinical outcomes but also facilitate the deployment of computational and statistical models to accurately predict epidemics. This can aid local health bodies in issuing warnings and controlling the outbreak of infection. The scope of research can be expanded further with new hospitals, clinics and pharmacies joining the network. Big Data and analytics promise a significant step towards personalized medicine. India, sitting at the cusp of a digital revolution, is well placed to integrate such solutions with public health management and address the ABR problem.
Shruti Sharma is a research intern with Carnegie India.