Of lice and math: using models to understand and control populations of head lice

TL;DR

This study develops a biological and computational model of head lice populations to evaluate the effectiveness of various treatment strategies, highlighting the importance of treatment timing and application methods.

Contribution

The paper introduces a novel model combining biology and simulations to analyze head lice control strategies, including systematic and non-systematic treatments.

Findings

Systematic treatments are more effective than non-systematic ones.

Timing of treatment initiation significantly impacts control success.

A single contagion parameter can replicate real infestation dynamics.

Abstract

In this paper we use detailed data about the biology of the head louse (pediculus humanus capitis) to build a model of the evolution of head lice colonies. Using theory and computer simulations, we show that the model can be used to assess the impact of the various strategies usually applied to eradicate head lice, both conscious (treatments) and unconscious (grooming). In the case of treatments, we study the difference in performance that arises when they are applied in systematic and non-systematic ways. Using some reasonable simplifying assumptions (as random mixing of human groups and the same mobility for all life stages of head lice other than eggs) we model the contagion of pediculosis using only one additional parameter. It is shown that this parameter can be tuned to obtain collective infestations whose variables are compatible with what is given in the literature on real infestations. We analyze two scenarios: one where group members begin treatment when a similar number of lice are present in each head, and another where there is one individual who starts treatment with a much larger threshold ('superspreader'). For both cases we assess the impact of several collective strategies of treatment.