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*Figure 1. Schematic drawing of the Designing Feasible Futures Framework (DF3) Illustrating the initial framing "What can we learn from this pandemic for the next one?"*

## **A Granular Analysis of Snakebite Cases in India and its Spatial Trends**

**Thirumal Reddy Vennam, Prachi Shukla, Khushboo Balani, Jitendra Shah, and Satish Agnihotri** Indian Institute of Technology Bombay, Mumbai, India

India is home to half of the total snakebites and more than half of the snakebite-related deaths in the world. However, it continues to be a low-priority issue for the government. The susceptibility to snakebites has only increased in recent times due to increased urbanization and resultant deforestation. While past analyses have identified the high-burden states, we identified hotspots at the district level for improved targeting of resources and preventive action. We also identified the time periods of peak incidence at the disaggregated levels to feed into the early-warning systems, thereby informing the anti-venom inventory management at local levels. Lastly, we examine the relationship between cropping patterns and the incidence of snakebites. We use the official HMIS database, which provides monthly data from health facilities across the country. Most studies have relied on primary data collection to inform their analysis. The time period of our analysis is FY18- FY20. The unit of analysis is districts and states. We use the univariate Local Indicators of Spatial Autocorrelation (LISA) technique to identify the hotspots of snakebites. Lastly, we present correlational estimates between the nature of crops and the incidence of snakebites to enhance our understanding of the determinants of snakebites. Just 77 districts (out of 703) constituted 52.7% of the snakebite cases in the country between FY18-FY20. LISA analysis identified 63 hotspots (Moran's I = 0.516), with 62 being located in four states Andhra Pradesh, Tamil Nadu, West Bengal, and Maharashtra. The peak months for the incidence of snakebites differ across states, with June to October (cropping season) being the most common time period. While paddy cultivation is usually found to be correlated with a greater incidence of snakebites, we found that cropped areas under coarse grains (millets, sorghum) had a higher correlation [0.48] than cereals (rice, wheat) [0.37]. The HMIS database, despite its limitations, provides monthly data for monitoring the burden of snakebites across districts. Since health is a state subject in India, preventive and curative efforts should be directed towards the identified hotspots by the respective state governments. The limited availability of official data on this issue reiterates the need for investment in data-collection efforts.

#### Introduction

India is home to half of the total snakebites and more than half of the snakebiterelated deaths in the world, yet it continues to be a low-priority issue for the government. The susceptibility to snakebites has only increased in recent times due to an increased urbanisation and resultant deforestation. While past analyses have identified the high-burden states, we identified hotspots at district-level for the improved targeting of resources and preventive action. We also identified the time periods of peak incidence at the disaggregated levels, to feed into the early warning systems, thereby informing the anti-venom inventory management at local levels. Lastly, we examined the relationship between cropping patterns and incidence of snakebites.

*Figure 1. Seasonality of total snakebites (2017-21) (Source: HMIS).*

#### Methodology

We used the official HMIS database, which provides monthly data from health facilities across the country. Most studies have relied on primary data collection to inform their analysis. The time period of our analysis was FY18- FY20. The unit of analysis was districts and states. We used the univariate Local Indicators of Spatial Autocorrelation (LISA) technique to identify the hotspots of snakebites. Lastly, we present correlational estimates between the nature of crops and incidence of snakebites to enhance our understanding of the determinants of snakebites.

*Figure 2. LISA map for total snake bites (2019-20) (Source: HMIS).*

#### Results

Just 77 districts (out of 703) constituted 52.7% of the snakebites cases in the country between FY18 and FY20. The LISA analysis identified 63 hotspots (Moran's I = 0.516), with 62 being located in the four states of Andhra Pradesh, Tamil Nadu, West Bengal and Maharashtra.

The peak months for incidence of snakebites differed across states, with June to October (cropping season) being the most common time-period. While paddy

Cultivation is usually found to be correlated with a greater incidence of snakebites, we found that cropped areas under coarse grains (millet, sorghum) had a higher correlation [0.48] than cereals (rice, wheat) [0.37].

#### Conclusions

The HMIS database, despite its limitations, provides monthly data for monitoring the burden of snakebites across districts. Since health is a state subject in India, the preventive and curative effort should be directed towards the identified hotspots by the respective state governments. The limited availability of official data on this issue reiterates the need for investment in data- collection efforts. The study highlights the need for quality data to better inform anti-venom inventory management.
