Health Intelligence Pilot
PREVENTIVE WATER–HEALTH INTELLIGENCE LABORATORY
Establishment of a Continuous Drinking-Water Surveillance, Microbial Genomics, GIS and Predictive Health Intelligence Platform for Haridwar and Rishikesh
Proposed Budget: ₹15.02 Crore [₹4.253 Cr (Non-recurring) + ₹10.620 Cr (Recurring) + ₹0.14873 Cr (Contingency)]
The facility is conceived as a continuously operating institutional research platform — not a one-time project.
PILOT LIVE: RHIP — 3 wards assessed · significant contamination found · IIT Roorkee–UCT initiative since June 2026
1. Executive Summary
This proposal seeks to establish a Preventive Water–Health Intelligence Laboratory using urban Haridwar as the initial demonstration landscape. The facility will integrate drinking-water chemistry, heavy-metal surveillance, environmental microbiology, molecular diagnostics, microbial genomics, GIS, population exposure assessment and predictive modelling.
The central objective is to move beyond periodic water-quality testing toward a continuously learning system that can identify persistent and emerging contamination hotspots, characterize their biological signatures, estimate population exposure and generate evidence for preventive intervention.
The Roorkee Health Intelligence Pilot (RHIP) provided the initial proof of concept. IITRoorkee and Ullas Charitable Trust (UCT) collaborated upon the project which inculcated thorough geographically structured water surveillance. RHIP demonstrated the feasibility of linking water-quality findings with spatial intelligence and identified heavy-metal contamination in sampled water sources. It also highlighted the need for dedicated laboratory capacity to support timely, standardised and longitudinal surveillance. The laboratory and surveillance programme will be implemented through two complementary cost components:
NON-RECURRING (₹4.253 CRORE) Initial capital investment for establishment of the dedicated Water–Health Intelligence Laboratory, including core laboratory infrastructure, analytical equipment, cold-chain systems, field surveillance and GIS/AI-enabled systems required for operational readiness.
RECURRING (₹10.620 CRORE) Operational expenditure for the 36-month- Haridwar (Urban + Semi-Urban ) and Rishikesh (Urban + Semi-Urban) surveillance programme, covering sample collection, testing, consumables, field operations, data management and programme implementation.
CONTINGENCY & UNFORESEEN COSTS (₹ 0.14873 CRORE) Provision for unforeseen operational requirements, price variation, additional sampling/testing, minor equipment or field requirements, logistics and other implementation contingencies.
2. Problems to be Addressed
| Problem | Gap / consequence |
|---|---|
| Fragmented surveillance | Chemical, microbiological, spatial and health information are generally generated in separate streams, limiting integrated risk assessment. |
| Limited spatial resolution | Periodic sampling may miss neighbourhood-scale contamination and differences between groundwater, municipal supply and public/household sources. |
| Insufficient microbial resolution | Routine indicator testing detects contamination but provides limited information on microbial communities, priority pathogens, virulence and antimicrobial-resistance signatures. |
| Weak exposure linkage | Contamination concentration alone does not describe population risk; source, water use, population density, sanitation and vulnerability also matter. |
| Limited water–health integration | Disease signals are rarely analysed together with temporally and spatially resolved water-quality information. |
| Reactive rather than predictive monitoring | Most programmes report present conditions rather than predicting where risk is likely to increase. |
| One-time project limitation | Snapshot surveys do not reveal persistent versus seasonal hotspots or allow models to improve with new evidence. |
| Limited translation to prevention | Data need to be converted into targeted sampling, source investigation, intervention and post-intervention verification. |
3. Phases of the project: Over 36 months’ time period
Phase 01 – Setting up of laboratory → Phase 02 – Haridwar (Urban) → Phase 03 – Haridwar (Semi-Urban) → Phase 04 – GIS mapping of secondary disease data → Preventive Water–Health Intelligence Dashboard → Phase 05 – Rishikesh (Urban) → Phase 06 – Rishikesh (Semi-Urban) → Phase 07 – GIS mapping of secondary disease data → Preventive Water–Health Intelligence Dashboard
4. Long-Term Vision
The laboratory will function as a permanent institutional platform in Indian Institute of Technology, Roorkee (IITR). Haridwar will provide the initial urban and semi urban as the test bed, but the infrastructure, methods, data architecture and models will be expanded to Rishikesh urban and semi-urban regions, followed by other regions of Uttarakhand and India.
Operating cycle: SURVEILLANCE → DATA INTEGRATION → HOTSPOT DETECTION → MOLECULAR INVESTIGATION → EXPOSURE ASSESSMENT → RISK PREDICTION → PREVENTIVE ACTION → VERIFICATION → MODEL UPDATE
5. Laboratory Architecture
| Laboratory unit | Core capability |
|---|---|
| A. Water Quality & Sample Processing | Physicochemical parameters, filtration, sample preparation, QA/QC |
| B. Heavy-Metal Analysis | Priority metals/metalloids using ICP-OES; digestion and trace-analysis workflow |
| C. Environmental Microbiology | Indicator organisms, culture-based analysis, membrane filtration and microbial enumeration |
| D. Molecular & Genomic Surveillance | DNA extraction, qPCR, pathogen assays, environmental DNA and preparation for outsourced/in-house sequencing |
| E. GIS, Bioinformatics & AI | Spatial database, exposure modelling, metagenomic analysis, predictive modelling and dashboard development |
| F. Field Surveillance | Georeferenced sampling, portable water-quality measurements and cold-chain transport |
6. Phase-I Equipment and Capital Budget
| Component | Major equipment / scope | Budget |
|---|---|---|
| 1. Water quality & sample processing | Multiparameter water-quality meter; UV-Vis spectrophotometer; Calorimeter | ₹7.5 L |
| 2. Heavy-metal analysis | ICP-MS; microwave digestion system; fume hood; gas and sample introduction accessories | ₹326 L |
| 3. Environmental microbiology | Class II A2 biosafety cabinet; autoclave; BOD incubator; microbiological incubators; refrigerated centrifuge; microscope; colony counter; shaker; membrane filtration system | ₹39.8 L |
| 4. Molecular biology | 96-well real-time PCR system; conventional PCR; NanoDrop spectrophotometer; Qubit fluorometer; gel electrophoresis system; gel documentation system; PCR workstation; microcentrifuge; UPS and accessories. | ₹49.3 L |
| 5. Cold chain & preservation | -20°C laboratory freezer; laboratory freezers | ₹2.7 L |
Phase-I estimated capital requirement: ₹4.253 Cr.
7. Structured Sampling Approach:
| Component | Haridwar (Urban) | Haridwar (Semi- Urban) | Rishikesh (Urban) | Rishikesh (Semi Urban) |
|---|---|---|---|---|
| 1.Localities | 24 | 54 | 33 | 7 |
| 2.Proposed samples/Locality | 25 | 25 | 5 | 25 |
| 3. Samples/round | 600 | 1350 | 825 | 175 |
| 4. Recurring cost/sample | ₹1000 | ₹1000 | ₹1000 | ₹1000 |
| 5. Programme samples (36 months) | 21,600 | 48,600 | 29,700 | 6,300 |
| 6. Recurring requirement | ₹2.16 Cr | ₹4.860 Cr | ₹2.970 Cr | ₹0.630 Cr |
| 7. Next Generation Sequencing | 100 samples in total | |||
| 8. Next Generation Cost/Sample | ₹8000 | |||
| 9. Next Generation sequencing requirement | ₹8.00 Lakh | |||
| 10. Total programme requirement | ₹10.620 Cr | |||
Contingency & Unforeseen Costs (1%): ₹0. 14873 Cr Phase (II – VII ) estimated capital requirement: ₹15.02173 Cr = ~ ₹ 15.02 Cr
8. Why These Equipment Are Needed
| Equipment / system | Strategic justification |
|---|---|
| ICP-MS | Provides high-sensitivity, multi-element detection of priority heavy metals and trace contaminants, enabling comprehensive in-house environmental exposure assessment. |
| Microwave digestion | Standardizes sample preparation for elemental analysis and enables expansion to other environmental matrices. |
| qPCR | Provides rapid, quantitative detection of priority microbial/pathogen and source-tracking markers. |
| Class II A2 BSC | Supports safe handling of environmental microbiological samples and minimizes contamination during molecular workflows. |
| −20°C storage | Enables short- and long-term preservation of DNA, microbial isolates, environmental samples and selected reference materials for repeat testing and future molecular analyses. |
| Field instrumentation | Allows spatially resolved screening and improves sampling decisions before expensive laboratory analyses. |
| GPU workstation + storage | Supports metagenomic data processing, machine learning, spatial modelling and long-term data retention. |
| Filtration/sample processing | Critical for low-biomass environmental DNA recovery and reproducible microbiological analysis. |
9. Initial Consumables and Recurring Cost Structure
| Recurring category | Examples |
|---|---|
| Molecular biology | DNA extraction kits, qPCR master mixes, primers/probes, controls, tubes/plates, electrophoresis reagents |
| Microbiology | Culture media, membrane filters, sterile bottles, plates, reference materials and microbial controls |
| Elemental analysis | High-purity acids, elemental standards, internal standards, digestion consumables and certified reference materials |
| Field surveillance | Sterile sampling bottles, filters, gloves, labels/barcodes, transport media, coolants and temperature loggers |
| Quality assurance | Blanks, duplicates, spikes, calibration standards, control materials and instrument validation |
| General laboratory | Pipette tips, tubes, PPE, cryovials, chemical/biohazard waste supplies and cleaning materials |
A recurring annual operating budget should be planned separately for field sampling, consumables, instrument AMC/calibration, outsourced sequencing and specialized analyses. The capital purchase alone will not sustain a continuous intelligence platform.
10. Core KPIs
| KPI | Three-year / ongoing target |
|---|---|
| 1. Spatial coverage | ≥250 georeferenced water sources/points established during the initial baseline; expand thereafter. |
| 2. Continuous surveillance | At least four seasonal sampling campaigns per year during baseline, followed by annual longitudinal surveillance. |
| 3. Analytical capability | Routine physicochemical and priority heavy-metal surveillance established with documented QA/QC. |
| 4. Microbial surveillance | Routine microbial indicators plus targeted molecular assays for priority waterborne hazards. |
| 5. Genomic intelligence | Genomic characterization of representative, high-risk and emerging-hotspot samples; annual dataset expansion. |
| 6. GIS integration | 100% of research samples linked to spatial coordinates, source metadata and sampling time. |
| 7. Hotspot intelligence | Persistent, seasonal and emerging contamination hotspots identified and tracked over time. |
| 8. Predictive model | Water-associated health-risk prediction model developed, temporally/spatially validated and reported with uncertainty. |
| 9. Preventive action | High-priority alerts translated into documented investigation, targeted sampling or intervention recommendations. |
| 10. Platform sustainability | Annual growth in datasets, research projects, collaborations, trained researchers and external funding. |
11. Expected Outcomes
| Outcome | Deliverable |
|---|---|
| Urban Drinking-Water Atlas | Continuously updated GIS atlas of sources, chemistry, microbial indicators and risk zones. |
| Heavy-Metal Risk Map | Spatial and seasonal distribution of priority metals/metalloids with exceedance and uncertainty information. |
| Microbial Water Atlas | Distribution of indicator organisms, priority pathogens and microbial community signatures. |
| Environmental Genomic Repository | Longitudinal microbial, pathogen, virulence and AMR dataset. |
| Exposure-Risk Map | Identification of population groups and locations potentially exposed to water hazards. |
| Water–Health Association Model | Quantitative assessment of spatial and temporal relationships between water hazards and aggregated health indicators. |
| Preventive Risk Model | Prediction of emerging water-associated health risk rather than only current contamination. |
| Early-Warning Dashboard | Prioritized zones for confirmatory sampling, investigation and preventive action. |
| Intervention Verification | Measurement of whether interventions reduce environmental and predicted health risk. |
| Institutional platform | Permanent capability for future water, environmental microbiology, genomics, GIS/AI and public-health projects. |
13. Three-Year Development Pathway
| Stage / Phase | Timeline | Geography | Key Activities & Purpose |
|---|---|---|---|
| Stage 01 — Establish | M1–M6 | Roorkee, District Haridwar | Facility establishment; procurement & installation; SOPs, QA/QC, sample logistics, GIS/database, staff training and pilot testing |
| Stage 02 — Generate Evidence- Urban Surveillance | M7–M14 | Haridwar (Urban-24 wards) | Urban Water-quality surveillance, laboratory testing, GIS-spatial mapping and environmental risk assessment; operationalize and validate the RHIP framework |
| Stage 03 – Semi urban expansion | M15–M22 | Haridwar (Semi-Urban- 54 wards) | Semi-urban contamination profile, seasonal trends, GIS-spatial mapping, risk assessment and expanded surveillance database |
| Stage 04 -Intelligence + Rishikesh Expansion | M23–M30 | Haridwar + Rishikesh (Urban: 33 Wards + Semi Urban: 7 wards) | Haridwar: Health-data integration → Disease & water-risk mapping → Dashboard development → Risk prioritisation + Rishikesh: Urban & semi-urban water surveillance → GIS mapping → Contamination profiling |
| Stage 05 – Model Integration & Refinement | M31–M34 | Haridwar + Rishikesh | Rishikesh health-data integration → Water–health association → Dashboard expansion → Comparative risk analysis → Model refinement |
| Stage 06 – Consolidation & Scale-Up | M35–M36 | Haridwar + Rishikesh | Integrated Water–Health Intelligence System → Model validation → Intervention framework → SOPs & replication framework → Scale-up recommendations |
14. Data and Governance Principles
- All samples will carry standardized identifiers, GPS coordinates, source metadata, date/time and analytical batch information.
- QA/QC, calibration, blanks, duplicates, spikes and reference materials will be incorporated into routine workflows.
- Health information will be handled only in aggregated/de-identified form and subject to appropriate institutional and ethical permissions.
- Genomic detection will be interpreted as environmental surveillance evidence and not automatically as proof of clinical causation.
- Predictive models will be validated across time and/or geography and will report uncertainty and model limitations.
- Raw data, processed datasets, metadata, model versions and intervention records will be retained to support reproducibility.
15. Institutional Value
- Creates a distinctive interdisciplinary research facility at the interface of environmental biotechnology, microbial genomics, GIS, AI and public health.
- Provides a permanent platform for PhD, M.Tech and project training.
- Creates a longitudinal dataset that becomes more valuable with every sampling cycle.
- Supports competitive proposals to national agencies, public-health programmes, environmental agencies and industry.
- Enables collaborations with municipal water authorities, hospitals, diagnostic laboratories and environmental monitoring agencies.
- Provides a scalable framework that can be transferred from Haridwar to other urban, semi urban and rural regions.
16. Final Institutional Outcome
The principal outcome will not be a completed Haridwar water-quality survey. The principal outcome will be the establishment of a continuously operating Water–Health Intelligence Laboratory whose evidence base, analytical capability and predictive models improve every year.
In practical terms, the platform should progressively answer five questions:
- WHERE is the hazard?
- WHAT is the hazard?
- WHO is exposed?
- WHERE is health risk increasing?
- WHAT preventive action should be prioritized?
This creates a closed-loop system from surveillance to prevention.