My work focuses on modelling the population dynamics of soil transmitted helminths and schistosomes. With the recent advent of large-scale donations of anthelminthic drugs from pharmaceutical companies, it is essential to understand the impact of different regimes of mass drug administration on the parasite burden of populations. In particular, how the degree of control or the possibility of elimination depend on whom the drugs are targetted at and how frequently. My work involves analysis of simple mathematica models as well as simulation using age-structured models and stochastic individual (worm) based approaches. Helminths are characterised by a high degree of variability in their distribution among hosts and reproductive behaviour and the techniques of data collection are also prone to error. My aim is to develop Baysian techniques to properly integrate parameter and biological uncertainty into the models and hence give realistic confidence intervals on model output.
Lochen A, Truscott JE, Croucher NJ, 2022, Analysing pneumococcal invasiveness using Bayesian models of pathogen progression rates, Plos Computational Biology, Vol:18, ISSN:1553-734X
et al., 2021, Forecasting the effectiveness of the DeWorm3 trial in interrupting the transmission of soil-transmitted helminths in three study sites in Benin, India and Malawi, Parasites and Vectors, Vol:14, ISSN:1756-3305
et al., 2020, Forecasting the Effectiveness of the DeWorm3 Trial in Interrupting the Transmission of Soil-transmitted Helminths in Three Study Sites in Benin, India and Malawi
et al., 2019, Heterogeneity in transmission parameters of hookworm infection within the baseline data from the TUMIKIA study in Kenya, Parasites and Vectors, Vol:12, ISSN:1756-3305
et al., 2019, Calculating the prevalence of soil-transmitted helminth infection through pooling of stool samples: Choosing and optimizing the pooling strategy, Plos Neglected Tropical Diseases, Vol:13, ISSN:1935-2727