The Irish economy has recovered at an impressive pace from the economic and financial crisis that lasted from 2008–12. Nonetheless, as a small open economy with some lingering vulnerabilities from the recent crisis, the economy remains heavily exposed to potential adverse shocks. In this paper, we explore the possible impact of external shocks on the Irish economy. We model the shocks in a two-stage process: first using NiGEM to estimate the impact on Ireland's key trading partners and the broader international environment and then examining the effect of these changes in the COSMO model of the Irish economy. The paper focusses on three relevant risks facing the economy: the potential for a hard Brexit, an increase in interest rates and a depreciation of the sterling euro exchange rate. Using this two-step approach allows us to demonstrate the transmission of external shocks to the Irish economy. The results help to quantify the potential impact on future growth, the labour market, public finances and the financial system of some key risks materialising.

The prevalence of schistosome infections in intermediate host snails varies with snail age. The relationship between age and prevalence, the age—prevalence curve, is complex and may vary in space and time, and among parasite—host species. Field studies show that the shape of the age—prevalence curve may be seasonally variable, and that at some times there may be a decline in prevalence among older snails. This paper attempts to explain these observations in terms of the underlying epidemiological processes. A discrete-time version of Muench's catalytic model for age-dependent infection is developed. Model simulations were carried out using life-history and epidemiological parameters derived from studies of Schistosoma haematobium—Bulinus globusus in Zimbabwe. Analysis of model behaviour identifies aspects of the schistosome— snail interaction that affect the shape of the age—prevalence curve. The following features can result in a decline in prevalence among older snails. (1) A decrease in the survival rate of patent infected snails with age. (2) A decrease in the force of infection with age. (3) A high rate of loss of infection. (4) A heterogeneity in the snail population such that the probability of infection is correlated with snail fecundity. (This would occur if there existed a spatial correlation between force of infection and fecundity, or if there were a correlation between fecundity and susceptibility.) The evidence for the occurrence of these features in the field is assessed. Survival rate is related more closely to the duration of patent infection than to age per se. The evidence for age-dependent force of infection is equivocal. Significant loss-of-infection rates have yet to be demonstrated. Heterogeneities in force of infection and fecundity have been reported and, for the Zimbabwe data, this mechanism can explain seasonally in the age—prevalence curve as a function of known seasonal variation in the force of infection and snail fecundity.