Globally, more than 90% of all snakebite envenomation (SBE) occur in low resource settings. This neglected tropical disease affects 2.7 million people, with 81,000-138,000 deaths, and approximately 400,000 permanent disabilities annually. Antivenom is a safe, efficacious, time- dependent, and evidence-based treatment, but the availability and timely access to this standard of care is inadequate. It is critical to engage local communities to improve timely access in remote, low resource areas where most SBE morbidity occurs. This proposal will develop and evaluate an innovative multi-modal intervention to improve SBE care, including decentralized antivenom distribution among the existing community healthcare center (CHC) network in the Brazilian Amazon. This novel intervention will integrate (a) advanced geospatial artificial intelligence to create decentralized antivenom distribution models using existing CHCs that optimizes population coverage and time to reach care, (b) a cost-effectiveness evaluation model developed with key stakeholders, and (c) a culturally relevant SBE care package containing education, treatment guidelines, training on antivenom delivery and interfacility care coordination. Using the Consolidated Framework for Implementation Research, we will conduct a formative evaluation of this multi-modal intervention and prepare an implementation strategy for the Brazilian Amazon, as well as prepare to scale up to other low resource locations. Consequently, we will have a standardized approach to use advanced analytics to optimize healthcare delivery in low resource settings that can be used in other countries and with other healthcare interventions.

Start Date: July 2021
End date: March 2023
Grant: #R21TW011944-02

Main topic

This project was divided into three areas of development:

• Aim 1. Develop decentralized antivenom distribution models, optimized by the geographic location of SBEs and CHC facilities in a low-resource area. We will use geostatistical approaches to evaluate the distribution of SBE in the Amazon, describe the estimated travel time to receive antivenom and its association with complications/mortality. With this information, we will develop a geographical artificial intelligence model to identify the optimal locations to distribute antivenom using the CHC network attempting to maximize coverage and minimize the time to care.
• Aim 2. Conduct an economic evaluation of various models of optimized, decentralized antivenom delivery. This economic evaluation aims at
  1. Estimating the net cost per person treated under the proposed decentralized antivenom delivery models,
  2. Identifying the disability-adjusted life-years (DALYs) averted per time reduced to reach SBE appropriate evidence-based care with different models, and
  3. Conducting a model-based cost-effectiveness analysis to compare the difference in cost to the difference in effectiveness of these different antivenom delivery models.
• Aim 3. Conduct a formative evaluation of a culturally relevant SBE care package. With mixed methods and participatory approaches based on the Consolidated Framework for Implementation Research (CFIR) guidelines, a sample of community health centers will be enrolled for our intervention pre-, peri and post implementation evaluation. We will evaluate inner and outer settings, individuals and implementation characteristics, and implementation process indicators.