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This project was designed as a multi-centric, evidence-driven study to estimate the burden of hospital-acquired infections in public healthcare facilities in Tamil Nadu and to evaluate the effectiveness of structured environmental disinfection interventions. It combines epidemiological research, implementation science, and health systems assessment to generate actionable insights for strengthening infection prevention frameworks. The initiative also aims to establish standardized outcome measures and high-quality data from resource-limited settings, where such evidence has historically been scarce.
Reliable data on the true prevalence and transmission dynamics of HAIs in public hospitals is limited, leading to underreporting and fragmented policy responses. Existing IPC practices are often dependent on continuous behavioral compliance, which is difficult to sustain at scale. In addition, there is a lack of well-powered, methodologically robust interventional studies from India that measure the direct impact of environmental disinfection on infection rates. Without this evidence, healthcare systems face challenges in prioritizing cost-effective and operationally feasible infection control strategies.
The project implements a cluster-randomized interventional study that measures baseline infection rates, evaluates prevailing IPC systems, and introduces a structured environmental disinfection protocol across selected healthcare facilities. By comparing intervention and control settings over a defined period, the study generates high-quality data on the effectiveness, feasibility, and impact of enhanced disinfection practices. The approach shifts the focus from purely behaviour-driven compliance to system-level environmental controls that are more sustainable and scalable in public health settings.
The study follows a rigorously designed research framework that includes baseline IPC assessments, sample size estimation, hospital and ward selection based on defined inclusion criteria, and standardized outcome measurement. Healthcare facilities are randomized into intervention and control arms, with continuous monitoring to ensure fidelity to the implementation plan. Data collection processes are supported by training, consent protocols, and structured surveillance mechanisms, enabling consistent measurement of infection incidence and operational performance across sites.
CDPH provided leadership in research design, epidemiological analysis, implementation planning, and coordination across participating institutions. The organization’s multidisciplinary expertise enabled the integration of public health science, operational research, and real-world health system constraints into a single cohesive program. CDPH also ensured that the project outputs are aligned with policy translation, capacity building, and long-term system strengthening.
Beyond immediate research outputs, the project strengthens surveillance capacity, establishes standardized outcome frameworks for future studies, and promotes sustainable infection control practices that do not rely solely on behavioural change. It represents a critical step toward resilient health systems capable of reducing preventable infections and improving quality of care at scale.
The project generates one of the first large-scale, high-quality evidence bases on the burden of hospital-acquired infections and the effectiveness of environmental disinfection in Indian public healthcare facilities. Its findings support data-driven decision-making for infection prevention policies, improve resource allocation, and contribute to safer hospital environments for patients and healthcare workers. By demonstrating a scalable and cost-effective intervention model, the initiative has the potential to influence national and state-level IPC strategies and serve as a reference for similar settings globally.
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COVID Today was developed by a multidisciplinary group of clinicians, researchers, data scientists, engineers, and student volunteers working under the India COVID Apex Research Team (iCART). Bringing together expertise from leading institutions and global technology organizations, the team combined epidemiological insight with advanced data analytics and robust technical infrastructure.
Dr Mohak Gupta, MBBS, AIIMS Delhi.
Technology and Data-driven Solutions in Healthcare
Saptarshi Mohanta (Rishi), BS-MS, IISER Pune.
Machine Learning, Deep Learning, Data Applications and Analytics
Aditya Garg, B.Tech CSE, VIT Vellore
Content Creation
Abhinav Gupta, CA Inter, B.Com
Simplifying Complex Structures with Technology
Apurva Thakker, B.Tech CSE, BFCET Bathinda
Solving Problems through Technology
Siddharth Jain, Integrated B.Tech-MBA, IIIT Gwalior.
Data Analysis, Machine Learning