Ecological Archives E089-129-A1

Anna E. Jolles, Vanessa O. Ezenwa, Rampal S. Etienne, Wendy C. Turner, and Han Olff. 2008. Interactions between macroparasites and microparasites drive infection patterns in free-ranging African buffalo. Ecology 89:2239–2250.

Appendix A. Model sensitivity to parametergamma(recovery rate from worm infection).

Parametergammais the rate at which worm-infected hosts, IW and ICO recover from their worm infections and revert to S and ITB status, respectively. We ran our model with values ofgammabetween 0 and 1, at intervals of 0.1, to assess how our choice ofgammaaffects model output, for models including higher mortality of coinfected individuals (dCO) only, and for models including both elevated dCO and transmission heterogeneity as mechanisms generating observed patterns of worm and TB infection. We examined two components of model output, (i) the relationship between worm prevalence and TB prevalence in the population, at low (0.15), intermediate (0.3), and high (0.6) annual mortality of coinfected individuals (dCO), as shown in the main panels of Fig. 5; and (ii) the difference in TB prevalence between hosts with and without worms, at low, intermediate and high dCO, as shown in the inset panels of Fig. 5. (For this sensitivity analysis we setdelta= 3 as in the model output presented in the main text).

(i) The relationship between herd worm prevalence and TB prevalence changes very little withgamma: At medium dCO the negative slope of the regression of TB prevalence versus worm prevalence gets slightly less steep asgammais increased, while changes ingammahardly affect the regression slope at all when dCO is at the high or low setting. Across the whole range ofgamma, both models produce negative slopes for intermediate and high dCO, and slopes close to 0 for low dCO (Fig. A1).

(ii) In the model including only dCO, TB prevalence in hosts with worms is higher than in worm-free hosts for all levels of dCO (Fig. A2a). In the model including dCO and transmission heterogeneity, TB prevalence in worm-free hosts exceeds TB prevalence in worm-infected hosts when dCO is high, but not when dCO is at the medium or low setting (Fig. A2b). These relationships hold across all levels ofgamma, although the difference in TB prevalence between worm-free and worm-infected hosts is always larger for lower values ofgamma.

FigA1
 
   FIG. A1. Model sensitivity to parameter γ – relationship between herd TB prevalence and herd worm prevalence, (a) in the model including only dCO and (b) in the model including both dCO and transmission heterogeneity. The y-axis shows the negative slope of the regression of herd TB prevalence on herd worm prevalence. Variation ingammahas little effect on the regression slopes for either model.

 

FigA2
 
   FIG. A2. Model sensitivity to parametergamma– TB prevalence according to worm status, (a) in the model including only dCO and (b) in the model including both dCO and transmission heterogeneity. The y-axis shows the difference in TB prevalence (PTB) between worm-infected and worm-free buffalo (PTB(W+) – PTB(W-)). The difference in TB prevalence between worm-infected and worm-free hosts is larger at low valuesgamma. TB prevalence in worm-free hosts only exceeds TB prevalence in worm-infected hosts (yielding negative y) in the model including transmission heterogeneity (b) at high dCO.

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