ArticleNature communications2021
Emulator-based Bayesian optimization for efficient multi-objective calibration of an individual-based model of malaria.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- R-package agentBayes: Likelihood-based statistical methods for agent-based models.PLoS computational biology · 2026Article
- Exploring heterogeneity in mosquito exposure and attraction and its implications for malaria transmission.PLoS computational biology · 2026Article
- malariasimple: An R package for fast simulations of malaria transmission.PLoS computational biology · 2026Article
- Global approaches to infectious disease surveillance and modeling.Nature medicine · 2026Review
- Start from the end: Policy exploration to inform effective and consistent interventions applied to COVID-19 in St. Louis.PNAS nexus · 2026Article
- Timing of the fourth dose of RTS,S/AS01 malaria vaccine in perennial settings: a modelling study.Malaria journal · 2026Article
- Combining seasonal malaria chemoprevention with novel therapeutics for malaria prevention: a mathematical modelling study.PLoS computational biology · 2026Article
- Gaussian process emulation for exploring complex infectious disease models.PLoS computational biology · 2025Article
- Rethinking a hybrid malaria chemoprevention delivery strategy for children in sub-perennial settings: a modelling study integrating age- and seasonally-targeted delivery.Malaria journal · 2025Article
- Multitask deep learning for the emulation and calibration of an agent-based malaria transmission model.PLoS computational biology · 2025Article
- Gaussian Process Emulation for Exploring Complex Infectious Disease Models.medRxiv : the preprint server for health sciences · 2025Article
- Public health impact of current and proposed age-expanded perennial malaria chemoprevention: a modelling study.Scientific reports · 2025Article
- Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum and Plasmodium vivax malaria, 2000-22: a spatial and temporal modelling study.Lancet (London, England) · 2025Article
- Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges.Nature communications · 2025Article
- Performance characteristics and potential public health impact of improved pre-erythrocytic malaria vaccines targeting childhood burden.PLOS global public health · 2025Article
- AnophelesModel: An R package to interface mosquito bionomics, human exposure and intervention effects with models of malaria intervention impact.PLoS computational biology · 2024Article
- Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Severe outcomes of malaria in children under time-varying exposure.Nature communications · 2024Article
- Design and selection of drug properties to increase the public health impact of next-generation seasonal malaria chemoprevention: a modelling study.The Lancet. Global health · 2024Article
- Emulator-based Bayesian calibration of the CISNET colorectal cancer models.medRxiv : the preprint server for health sciences · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Individual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose using a Bayesian optimization framework employing Gaussian process or machine learning emulator functions to calibrate a complex malaria transmission simulator. We demonstrate our approach by optimizing over a high-dimensional parameter space with respect to a portfolio of multiple fitting objectives built from datasets capturing the natural history of malaria transmission and disease progression. Our approach quickly outperforms previous calibrations, yielding an improved final goodness of fit. Per-objective parameter importance and sensitivity diagnostics provided by our approach offer epidemiological insights and enhance trust in predictions through greater interpretability.
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