Environmental Surveillance of Resistance to Antibiotics - ENSURE

Healthcare facility-based wastewater surveillance (WWS) to track antibiotic resistance offers potential to leapfrog traditional surveillance systems that remain episodic in LMICs. Challenges include human resource shortages and demotivation to report data. We aim to demonstrate WWS as a novel approach in AMR surveillance that can be scaled across One health. 

The team lead and primary contact for this application is Dr Geetanjali Kapoor. She is a researcher and the acting head at the primary organisation (CDDEP India).

AMR is a significant threat to global health, particularly in LMICs. The primary cause of AMR is the overuse and misuse of antimicrobials across sectors. Globally, AMR is associated with ∼4.95 million deaths annually, with 36% rise in overall consumption of antimicrobials between 2000 to 2010 (1,2).

Surveillance is a critical intervention for control of AMR since it provides evidence for informing treatment guidelines and policy, at the level of hospital, region and nation. However, surveillance requires diagnostic testing and culturing capabilities, which are poorly implemented in many hospitals, particularly in rural areas, largely because of inadequate resources and human capacity critical for running microbiology laboratories. Currently, surveillance platforms depend on hospital data from individual patients. This is both resource intensive and often not representative of the underlying resistance, since testing is largely limited to sick patients. Furthermore, data are rarely transmitted in usable formats to decision makers to inform response and are therefore not used.

New technologies and approaches are needed to leapfrog older approaches, that have not been scaled up in most LMIC settings. Without this follow-up action, the resources expended on surveillance offer a poor return on investment and are hard to justify.   

The target audience are those who currently make use of surveillance data or for whom these data could improve outcomes. This includes clinicians, public health administrators and policy makers.

The dashboard will be a state of the art data visualisation tool equipped with analytics and predictive models (using AI and ML techniques) to forecast AMR trends, thereby supporting rapid response and planning for future health emergencies. Alongside, we will help to build the capacity of clinicians, public health administrators and policy makers on dashboard interpretation.

A low-cost, low-maintenance, and easy-to-use hospital wastewater-based AMR surveillance tool will be impactful, and available to the state government at zero-cost. It will reduce the surveillance reporting time and allow public health decision makers to monitor and forecast AMR burden in near real-time. The tool will be integrated with the existing disease surveillance system of the State and scaled to other geographies in the country based on interoperability of platforms.

Furthermore, the solution will promote better coordination among various stakeholders including researchers, public health administrators, antibiotics’ manufacturers, and policy makers, for robust data sharing, near real-time analytics, risk forecasting, and rapid response.

We aim to demonstrate the feasibility of a healthcare facility-based WWS as a novel approach to understanding the AMR burden, over routine clinical surveillance. In addition, the solution will also entail development of a low-cost and low-maintenance dashboard, that will grant clinicians, public health administrators and policy makers, with access to the latest AMR data (including antibiograms). In the future, the concept can be decentralised for scale up at community levels.

Sharing the AMR burden in near-real time with clinicians, public health administrators, will help in faster action at the policy level. It will help to ascertain stock outs or wastage of antibiotics and vaccines, strengthen supply logistics, improve vaccination coverage, and reduce morbidity and healthcare costs (including out-of-pocket expenditure).

Since globally, India has among the highest out-of-pocket spending on healthcare, with a preference for private facilities (14), data will be captured from both government and private healthcare facilities, in order to ensure inclusivity. In addition, since the solution will pave way for AMR surveillance in all domains of One Health, future data will better represent the larger population.

In year 1, our primary focus will be to compare the AMR burden estimated from clinical samples with the AMR burden generated from hospital wastewater (sewage treatment plants), for hospitals in Chikaballapur and Bangalore. This activity will start at 6th month after commencement of the study and continue for approximately 24 months.

In year 2, we will include two additional hospitals from the same State. This activity will start at 12th month after commencement of the study and continue for approximately 18 months. In addition, year 2 will be devoted to developing an AMR dashboard to monitor the near real-time relationships between AMR, antimicrobial consumption and climatic factors, and forecast AMR trends, followed by its integration with the existing State level disease surveillance platform.

In year 3, we will identify and devise strategies for scale across to additional hospitals in another State. In addition, community messaging will done in both the States. Throughout the three years, we will also active engage with the relevant Central and State departments, and share interim research findings.

A dedicated team will be assigned the role of monitoring the following indicators, over regular intervals:

1. Relative proportion of antibiotic resistant genes
2. Relative proportion of the pathogens carrying antibiotic resistant genes
3. Relative proportion of antibiotic classes 
4. Prediction of resistance mechanism

The above indicators were also monitored in a recently concluded study by our team (5).

In addition, we will also document the following:

1. Number of wastewater samples collected and tested
2. Number of reports generated for the wastewater samples tested
3. Number of risk alerts generated
4. Number of capacity building exercises for various stakeholders

Our study results will be disseminated through interactions with public health officials and also published in a peer reviewed journal. The message will also be communicated to masses to spread awareness on AMR and its control.

The anticipated challenges and proposed mitigation, are summarized as follows:

1.     Technical: The proposed AMR specific dashboard will be integrated with an existing disease surveillance system. However, if the state does not already have any system in place, our solution will have to be used as a stand-alone dashboard for AMR surveillance. Hence, the solution will be customised accordingly. 

2.     Partnership: For the proposed objectives to be fulfilled, availability of molecular testing laboratories is crucial. This has been considered in our current partnership. However, decision to scale up our solution to another State, will depend on availability of a similar testing facility.  If required, we may support an existing government or non-government testing lab in upgrading their infrastructure to initiate wastewater testing.

3.     Data sharing: Data quality largely depends on level of coordination among health, drugs, municipal and meteorology departments in the State. Restricted or delayed data access may lead to implementation delays. Hence, our team will proactively work towards facilitating smooth engagements with various departments, for data sharing.

4.     Financial: Government interest towards dashboard ownership and fund availability, is critical for solution's sustainability. Hence, we will encourage regular participation from department officials to discuss convergence and sustainability strategies.

Despite its recognition as a global threat, quantifying AMR is difficult owing to challenges on surveillance. Diagnostic testing and culturing capabilities, are poorly implemented in many hospitals, largely because of inadequate resources and human capacity in LMIC settings. In addition, obtaining hospital data from individual patients are not only resource intensive, but often not representative of the underlying resistance, since testing is largely limited to sick patients. Furthermore, data are rarely transmitted in usable formats to decision makers to inform response. 

Our solution will demonstrate the feasibility of a healthcare facility-based WWS as a novel and affordable approach to understanding the AMR burden, over clinical surveillance. Since comparison of AMR profiles between wastewater and clinical samples will be done by metagenomics, funds are required and hence we are applying to the Trinity challenge on AMR. In addition, expert guidance from the Trinity collaborators and mentors, will also aid us in refinement of our solution.  

The new technology and approach are needed to be able to leapfrog older approaches, and scale up AMR surveillance. Without this follow-up action, the resources expended on surveillance offer a poor return on investment and are hard to justify.  

We have put in a lot of thought in assembling a highly skilled team across some of India’s best scientific and health institutions.

Moreover, expert guidance shared by the collaborators and mentors mentioned on the Trinity website, will be highly appreciated. In particular, we have identified Infosys and Clinton Health Access Initiative (CHAI), as our potential mentors for further guidance. Infosys is headquartered in the same city as where we are currently based, and are world renowned as IT giants. CHAI has a long standing and widespread presence in India, and their guidance on stakeholder engagements, project implementation, and scale up, will benefit our work.