Meta-analysis of data on helminth resistance

Meta-analysis of current knowledge on parasitic helminths, their reproduction, eggs, life cycles, and infection cases. 

Skills that could be learned from this project:

• listing all relevant keywords to use in scientific databases

• literature search using the Web of Science and Scopus databases

• defining inclusion and exclusion criteria

• abstract screening of found papers and original decision based on inclusion criteria

• full read screening to define which papers are going to be used for data extraction (following another list of inclusion criteria)

• data extraction, especially using AI

• actual statistical analysis (meta-analysis).

The project would be led primarily by Viktor Kovalov

Modelling drug resistance in parasitic worms

These project ideas are based on mathematical models of drug resistance evolution in C. elegans; ideas can be modified to fit your interests (see Trubenova 2024: https://www.biorxiv.org/content/10.1101/2024.11.07.620884v2.full.pdf )

• • Investigating the mating system further

    • The effect of the male-female ratio: often the observed ratio in human hosts is not one-to-one. Thus, we could analyse specific ratios or the effect of variability in this ratio.

    • The level of polygamy found in helminth populations, spatial restrictions could limit this.

  • Studying how worm burden affects drug response

    • With increased worm burden, the drug might not reach certain worms as much as others and/or drugs taken up by other worms are not available for the rest, thus decreasing the effective concentration visible. This affects where on the dose-response curve each worm is over time.

    • This project would involve a literature review of available PK and PD data and models for anthelmintic drugs against major helminth species. 

    • This would then be synthesised in a model linking PK to PD and population genetics to simulate the evolution of drug resistance.

Skills that could be learned from any of these projects:

• • Understanding helminth biology, drug resistance

  • Implementing biological aspects in an abstract way (i.e. modelling)

  • Using Python and possibly running code on the cluster (Euler)

  • Finding relevant parameter ranges and defining useful outcome metrics to compare models

The project would be led primarily by Maya Louage