Understanding Social Immunity in Ants: A Markovian Approach to Collective Cleaning Strategies

Understanding social immunity mechanisms in ant colonies remains crucial to comprehending the evolution of defense strategies in eusocial organisms. This study assumes the absence of the role of memory in the ants' defense strategy, considering that they can make a new exploration of collective cleaning behaviors. We investigate how worker interactions and previous behaviors influence the evolution of social immunity strategies in response to the presence of pathogens and vulnerable colony members. In this context, with the application of Markov transition models it was possible to describe changes in cleaning behavior over time influenced by the presence of vulnerable members and treatment with an entomopathogenic fungus. We found a significant effect on ant behavior when exposed to \it{Metarhizium anisopliae} when a fungus garden fragment and one larva were present. Our findings confirm a link between prophylactic cleaning and the presence of vulnerable members. Remarkably, distinct behaviors and transition times vary among treatments, revealing workers' adaptability to threats. Allogrooming shows adaptive changes when exposed to pathogens, potentially affecting pathogen transmission. In addition, our study elucidates the intricate interaction between internal and external factors shaping worker behavior. The influence of environmental context on decision-making principles emerges, emphasizing the importance of both intrinsic colony organization and external threats. By using a Markov model to understand ant hygiene behavior, we offer insights into social immunity mechanisms in eusocial organisms. Deciphering collective cleaning strategies can aid in understanding disease dynamics and decision-making processes in complex societies.