One Health Index Calculator for India Using Empirical Methods for Policy Stewardship: Development and Usability Study.

BACKGROUND

One Health is a collaborative approach that can be used to evaluate and enhance the fields of human, animal, and environmental health and to emphasize their sectoral interconnectedness. Empirical evaluation of the One Health performance of a country in the form of an index, provides direction for actionable interventions such as targeted funding, prioritized resource allocation, rigorous data management, and evidence-based policy decisions. These efforts, along with public engagement and awareness on disease management; environmental degradation, and preparedness toward disease outbreaks, contribute to strengthening global health security. Thus, developing a One Health Index (OHI) calculator for India is a significant step toward evidence-based One Health governance in the context of low-and middle-income countries.

OBJECTIVE

This study aimed to (1) develop a OHI Calculator for India using efficient and user-friendly weighting methods and demonstrate the calculation of the OHI; (2) develop India-specific datasets through secondary data collection from reliable data sources; and (3) determine data gaps for policy stewardship.

METHODS

We proposed a OHI calculator to measure the OHI from an Indian context by adopting the Global One Health Index framework that comprises 3 categories: 13 key indicators, 57 indicators, and 216 subindicators. Secondary data collection was conducted to create a dataset for specific to India from reliable sources. For measuring OHI, we demonstrated two mathematical weighting methods: an efficient expert-based rating using fuzzy extent analysis and a modified entropy-based weightage method.

RESULTS

We demonstrate the step-by-step OHI calculation by determining indicator scores using both fuzzy extent analysis and modified entropy-based weightage method. Through secondary data collection an India-specific dataset was created using reliable sources. For the datasets from India, data for 156/216 subindicators were available, while that for the remaining 60 indicators were unavailable. Further, a pilot correlation analysis was performed between 20 indicator scores and relevant budget allocations for the years 2022-2023, 2023-2024, and 2024-2025. It was found that increases in the budget allocation across consecutive years improved indicator scores or better performance and vice versa.

CONCLUSIONS

The demonstrated OHI calculator has the potential to serve as a governance tool while promoting data transparency and ethical data management. There is a need for a collaborative data federation approach to resolve data gaps, including incomplete, missing, or unavailable data. Further, the correlation analysis between budgetary allocation and performance of indicators provides empirical evidence for policymakers to improve intersectoral communication, multistakeholder engagement, concerted interventions, and informed policy decisions for resource allocation.