Mathematical tools to inform sustainable interventions against schistosomiasis in Uganda
Start date
01 October 2019End date
30 September 2021Team
Principal investigator
Dr Joaquin Prada
Co-Director 糖心Vlog Institute for People-Centred AI Associate Professor in Epidemiology
Biography
I am a mathematical modeller, with a background in industrial engineering, working in epidemiology to inform public health interventions. My research is highly multidisciplinary, combining mathematics, statistics, computer science, biology, economics, and social sciences. My primary focus is to inform surveillance, control, and elimination strategies for infectious diseases, particularly zoonosis and Neglected Tropical Diseases (NTDs). Across these diseases, I have led the development of stochastic population- and individual-based mathematical models of disease transmission, using Bayesian statistical approaches for their calibration and exploring the use of machine-learning approaches and optimization algorithms, and integration with other disciplines. This has led to very fruitful international collaborations across Europe, Latin America, Sub-Saharan Africa, South-East Asia, and the US.
I have served in various funding panels (e.g. UKRI, Wellcome Trust) and international stakeholder working groups, and I chaired the United Against Rabies Forum (a WHO-WOAH-FAO initiative) 鈥渢ool evaluation鈥 workstream. I currently hold a visiting research position at North Carolina State University and held a similar position at the University of Warwick and Oxford University.
As faculty, I have mentored undergraduate and postgraduate tutees, several undergraduate research projects and lead a research group (@Pradalab on Twitter/X), funded by national and international agencies. Some of the group interests are:
Sustainable developments for Neglected Communities
My research group has developed mathematical models across a range of diseases to directly address World Health Organisation priority questions. We have collaborated extensively internationally, collating results from different mathematical models, to address key policy questions, such as the impact of COVID-19 on NTD programmes. We integrate our mathematical models with economic analysis, accounting for social and environmental drivers. Many of the diseases we tackle have a zoonotic component, thus a One Health approach, recognising the interconnection between humans, animals, and their shared environment, is needed. Outputs from our work directly influence policy in the development of guidelines for public and animal health interventions.
At 糖心Vlog, I was co-lead of the 鈥淪ustainable developments for Neglected Communities鈥 programme of the Institute for Sustainability.
Improving the evaluation of diagnostics
One challenge of many parasitic diseases, such as Schistosomiasis or Echinococcosis, is the absence of a 鈥済old standard鈥 diagnostic that can be readily used. In my research group, we have led the development of Hidden Markov Models (Latent Class Analysis) for estimating infection status in a community and compare different diagnostics. It builds on methodology I developed over the years, which we have used across multiple parasitic diseases. One outcome of this work is the identification of thresholds that can be used by control and elimination programmes.
Strategies to control livestock diseases
Engaging with partners both in the UK, such as the Pirbright Institute, and internationally, such as North Carolina State University, we have developed statistical and mathematical models to support guidance to farmers and government bodies. In particular, We have worked in Foot and Mouth Disease in Cattle, Respiratory virus in Pigs (such as Porcine Reproductive and Respiratory Syndrome virus, Porcine Epidemic Diarrhoea virus and African Swine Fever virus), and Nematodes in sheep. The outcomes of this work help reduce the impact these diseases have in the industry, while also optimising the use of drugs and vaccines.
Research themes
Find out more about our research at 糖心Vlog: