DOI: 10.5061/dryad.5hqbzkhcn
title: Eco-evolutionary dynamics of anthelmintic resistance in soil-transmitted helminths

description: Anthelmintic resistance (AR) of helminth parasites against the most widely
 available drugs is an ongoing concern for both human and
 livestock-infecting species. Indeed, there has been substantial evidence
 of AR in livestock but less in humans, which may be due to a variety of
 reasons. In this paper, we develop an eco-evolutionary model that couples
 the life cycle of these parasites with their underlying evolution in a
 single biallelic genetic locus that confers resistance to treatment drugs.
 We determine the critical treatment frequency needed to effectively
 eliminate the population, for a fixed drug efficacy (without evolution)
 and use this to classify three qualitative distinct behaviors of the
 eco-evolutionary model. Then, we describe how aspects of the life cycle
 influence which qualitative outcome is achieved and the spread of the
 resistance allele, comparing across human- and livestock- infecting
 species. For all but one species, we find that lower fecundity rates and
 lower contact rates speed the spread of resistance, while lower larval
 death slows it down. The life cycle parameters of Ancylostoma duodenale
 and Ostertagia circumcincta are associated with the fastest and slowest
 spread of resistance, respectively. We discuss the mechanistic reason for
 these results.
description: # Eco-evolutionary dynamics of anthelmintic resistance in soil-transmitted
 helminths These data are
 created as a output of an eco-evolutionary model detailed in the
 manuscript. We ran a number of different model parameterizations and
 report the ecological dynamics (growth, rescue, or decline coded as 1, 2,
 and 3). Both Mathematica and R code include the same eco-evolutionary
 model and includes parameter values for all six helminth species. ##
 Description of the data and file structure File list: main_figures.R
 SI_mathematica.nb SI_mathematica.pdf 50grid_treatment.csv
 50grid_treatment_res3.csv 50grid_parasite.csv 50grid_parasite_res.csv
 50grid_parasite_mul.csv 50grid_parasite_mul_res.csv 50grid_host_v2.csv
 50grid_host_v2_1_res.csv 50grid_host_subset.csv
 50grid_host_subset_res3.csv There are two sets of code. The Mathematica
 code (provided as SI_mathematica.nb and SI_mathematica.pdf) reproduces
 Figure 2 of the critical time between pulses as it depends on drug
 efficacy. The R code (main_figures.R) reproduces figures 3-8 and
 supplemental figures. Figures 3-5 require the datasets with
 "50grid" in the file name, which have been produced using the
 Mathematica code to categorize the ecological dynamics where the output is
 stored with the "res" suffix in a single column (growth, rescue,
 or decline coded as 1, 2, and 3 respectively). The variables in the
 "50grid" datasets refer to the 10 parameters in the model. These
 variables are: p = coverage of the population, i.e. the fraction of the
 population treated with drugs. freq = the frequency of drug treatment in
 number of times per year. mu_a = adult worm death rate in deaths per day.
 lambda_eff = reproduction rate in eggs per day. N = host population
 density in hosts per m^2. beta_eff = contact rate per host in m^2 per day.
 mu_l = larval death rate in deaths per day mu_h = host death rate in
 deaths per day. mu_BB = drug efficacy against worms of genotype BB, i.e.
 the fraction of worms that don't survive treatment, ranging from 0 to
 1. mu_AB = drug efficacy against worms of genotype AB, i.e. the fraction
 of worms that don't survive treatment, ranging from 0 to 1. mu_AA =
 drug efficacy against worms of genotype AA, i.e. the fraction of worms
 that don't survive treatment, ranging from 0 to 1. In
 "50grid_treatment.csv" file the values of frequency (freq) and
 coverage (p) are manipulated. The results are in
 "50grid_treatment_res3.csv". In "50grid_parasite.csv"
 file the values of adult death rate (mu_a) and egg production rate
 (lambda_eff) are manipulated. The results are in
 "50grid_parasite_res.csv". In
 "50grid_parasite_mul.csv" file the values of larval death rate
 (mu_l) and egg production rate (lambda_eff) are manipulated. The results
 are in "50grid_parasite_mul_res.csv". In
 "50grid_host_v2.csv" file the values of contact rate (beta_eff)
 and host density (N) are manipulated. The results are in
 "50grid_host_v2_1_res.csv". In
 "50grid_host_subset.csv" file the values of contact rate
 (beta_eff) and host density (N) are manipulated, but over a smaller range
 of contact rates. The results are in
 "50grid_host_subset_res3.csv". The additional parameters host
 death rate (mu-h), drug susceptibility of genotype BB (mu_BB), death rate
 of genotype AB (mu_AB), and death rate of genotype AA (mu_AA) are held
 constant. ## Sharing/Access information All data was produced from our
 model. ## Code/Software We suggest running the Mathematica code first and
 then the R code. The R code will call the "grid" datasets in the
 "Grids" folder to create figures 3-5. R version 4.1.1 was used
 and the following packages were loaded: cowplot, deSolve, ggplot2, ggpubr,
 gridExtra, viridis.