User guide to impact network analysis (INA). RTB User Guide

Abstract

From COVID-19 to emerging crop diseases and exotic pests that threaten natural ecosystems, invasive species are a major problem globally. Invasive populations, such as antibiotic- or pesticide-resistant genotypes or new pathotypes, are also a serious challenge. Desirable populations, such as improved crop varieties and endangered species, also have the potential to spread under the right conditions. Successful seed systems may require both types of management: supporting the spread of new crop varieties and stopping or slowing the spread of seedborne pathogens. One thing all these systems have in common is the need for a network of people and institutions to act together to manage a network of spread and saturation. These people and institutions decide whether and how to invest in interventions to slow or speed biological spread. Impact network analysis (INA) is a framework for evaluating how technologies do or do not successfully manage varieties, species, or populations, in the context of the linked socioeconomic networks of communication and influence, and the biophysical networks of technology implementation and biological spread. The INA package in the R programming environment provides decision support tools for scenario analysis to evaluate the likely outcomes from a range of regional management strategies. These strategies may include investment in surveillance, training, subsidies supporting the management of technology adoption, and improvements to management technologies. The INA framework is designed to provide useful input for decision-making by indirect users (users who may not apply the R package, themselves) as well as direct users who will use the R functions and potentially design new variations on the analyses. A goal of the INA framework development is to support a community of practice for researchers and practitioners who address similar problems, to provide lessons learned across systems that may have traditionally fallen in separate disciplines.