MACE: Mathematical models and economic evaluation for cystic echinococcosis control and elimination
Cystic echinococcosis (CE) is a zoonotic parasitic disease of significant public health concern in many parts of the world. For example, over 5,000 new CE cases are reported in South America every year and a recent study has estimated that more than 150,000 people in Bulgaria, Romania and Turkey might be affected by CE. The burden, extending to include economic impacts, is mostly felt in subsistence livestock keepers and other marginalised rural and peri-urban populations where other health competing threats persist. Under-reporting of the condition is large and the evidence to inform efficient surveillance and control approaches scarce. The large range of surveillance and control measures across all hosts, and their heterogeneous application across geographies further complicates the aggregation and comparison of evidence to assess the performance of control programmes.
This project will inform the most efficient portfolio of surveillance options and interventions towards CE control and elimination, accounting for the varying risks, disease control capacities, and risk preferences across geographies. The project is novel in the joint application of mathematical modelling and economic evaluation at fine spatial resolutions, and in the active elicitation of risk attitudes towards CE and related control measures to formally model their impact on the uptake of interventions and their efficacy.
We target two highly CE endemic areas in the world: south America, where CE control programmes have been operating for decades and the evidence is best to inform our models. The applicants have recently applied state-of-the-art analyses to integrate multiple surveillance sources (e.g. sampling of dogs, passive surveillance, and ultrasound screening on children) in Rio Negro (Argentina) to exhaustively map CE risk. The logical next step, as suggested here, is the integration of the existing risk maps with economic evaluations of the portfolio of interventions (e.g. sheep vaccination) adjusted for risks preferences (e.g. risk aversion, loss aversion). Our second geographical target is Albania where little evidence of CE exists. Here, one of the applicants will conduct a comprehensive survey of the country to collect ultrasound evidence of CE. The survey is planned to start in September 2019. The ultrasound data will then feed the model developed with the Argentinian data, to infer the true magnitude of CE in Albania. As the model contains the economic evaluation component, we will be able to generate multiple disease control scenarios (updated with local costs). Given that risk preferences may be context-specific, we will also elicit risk preferences in Albania.
Our results will inform the ongoing regional control and elimination plan coordinated by the Pan American Health Organization. This plan set up a number of strategic outcomes that our models will be able to operationalize and optimise. We note that two of the applicants are senior members of the South America Initiative for the Control and Elimination of CE that advises countries and PAHO on technical matters. Our results will also contribute additional insight into the true magnitude of CE in south east Europe, contributing thus to WHO’s roadmap plan for CE elimination. We note that two of the applicants are members of WHO’s Informal Working Group on Echinococcosis.
About me: I am a 21 year old Biomedical Scientist with a great interest in data analysis and research. I became interested in statistical and modelling aspect of biology while working on my final year project in bioinformatics where I worked with genomic data to predict the structure and properties of a protein. In my spare time, I like to travel and spend my time surfing in the sun.
What motivated me to do a PhD: I was firstly looking for a project in my interests that could bring wide scale improvements to the lives of a great number of people. I was also looking for a project in which I could contribute with my experience as a biomedical scientist, as well as a project that could help me build upon my skills and help me improve as a researcher. This PhD ticked all the boxes in that aspect.