How effective are interventions to reduce attacks on people from large carnivores? A systematic review protocol.

BACKGROUND

Instances of attacks from large carnivores that lead to human injury or death are increasingly reported worldwide. Ensuring human safety when people and carnivores co-occur is central to minimizing human suffering but is also essential to support sustainable carnivore conservation. Various interventions are available intended to alter either the behavior of large carnivores or people, in order to reduce the likelihood of a risky encounter and an attack. Collated evidence on best practices is still lacking, and this protocol outlines a systematic review of evidence for intervention effectiveness to reduce the risk or severity of direct attacks on humans by large carnivores. Specifically, the review seeks to answer the question: How effective are evaluated interventions in reducing large carnivore attacks on people?

METHODS

The bibliographic databases Zoological Record, BIOSIS Citation Index, and Scopus will be searched using a predefined search string. Grey literature will be requested through professional networks, contacts with relevant organizations, and searching selected websites. All returned titles and abstracts will be manually screened using Rayyan.ai. For inclusion, studies should describe the Population, Intervention, Comparator, and Outcome (PICO) of the review research question and be written in English, Spanish, or Swedish. Review papers will be excluded. All records of data coding and extraction are documented in a purposely developed, and priorly piloted, data sheet. Critical appraisal of study validity will be done according to the Collaboration for Environmental Evidence Critical Appraisal Tool prototype version 0.3. Review outcomes will be synthesized in a narrative, and if possible, a quantitative synthesis. The narrative synthesis will describe in text the carnivore population (species, location), context (target object, intervention model), as well as the design and reported results of each study. The quantitative synthesis will include a summary statistic, preferably logarithmic risk ratio, calculated for each original study. A forest plot will be created to visualize study outcomes, as well as judgments of critical appraisal. Provided that enough data is available and that it complies with its assumptions, a meta-regression analysis will be undertaken using metafor package for R software.