My research focuses on using data-driven approaches and modeling techniques to predict the geographic distribution of mosquito-borne diseases. Currently my work revolves around two main areas:
1. Building, maintaining and updating a global dengue incidence database (opendengue.org)
2. Generating global risk maps for dengue, zika, chikungunya and yellow fever, by fitting a machine learning model to global disease occurrence data and leveraging similarities among them
As a member of the Dengue Mapping and Modelling Group at LSHTM, led by Dr Oliver Brady, I actively collaborate with modellers, epidemiologists and public health experts, including the WHO Global Arbovirus Initiative.
1. Building, maintaining and updating a global dengue incidence database (opendengue.org)
2. Generating global risk maps for dengue, zika, chikungunya and yellow fever, by fitting a machine learning model to global disease occurrence data and leveraging similarities among them
As a member of the Dengue Mapping and Modelling Group at LSHTM, led by Dr Oliver Brady, I actively collaborate with modellers, epidemiologists and public health experts, including the WHO Global Arbovirus Initiative.
Affiliations
Department of Infectious Disease Epidemiology and Dynamics
Faculty of Epidemiology and Population Health
Centres
Centre for Mathematical Modelling of Infectious Diseases
Teaching
I teach on MSc modules including Epidemiology of Infectious Diseases and Modelling and Dynamics of Infectious Diseases, as well as short courses on infectious disease modelling and spatial analysis in R (ISAIR).
Research
Research Area
Modelling
Epidemiology
GIS/Spatial analysis
Vector control
Disease and Health Conditions
Dengue
Zika
Yellow fever
Malaria
Selected Publications
A systematic review of the data, methods and environmental covariates used to map<i>Aedes</i>-borne arbovirus transmission risk
2023
Cold Spring Harbor Laboratory
Decreased birth weight after prenatal exposure to wildfires on the eastern coast of Korea in 2000
2022
Epidemiology and health
Modeling the early temporal dynamics of viral load in respiratory tract specimens of COVID-19 patients in Incheon, the Republic of Korea.
2021
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES