Dr Victor Alegana
Early Career Research Fellow
Dr Victor Alegana is an Early Career Research Fellow at the KEMRI- Wellcome Trust Research Programme. He has a PhD in Geography and Masters degree in applied Geographic Information Systems and Remote Sensing both from the University of Southampton, UK. He has a keen interest in use of routine health data and application of spatial-statistical data science to public health problems in low- and middle-income countries. This include broad areas of population health particularly on spatial epidemiology (disease burden estimation), health care access, delivery of health interventions, and monitoring Sustainable Development Goals related to vulnerable populations.
Broad research areas
- In using applied data science to investigate public health problems related to infectious diseases in low- and middle-income countries. Victor is currently investigating ways of improving the use of routine data for estimating disease burden in East Africa.
- Delivery of healthcare in low-resource settings including access, health systems and health interventions.
Recent and current projects
- Mapping for malaria elimination: Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence.
- Equity delivery: Distribution and delivery of healthcare in low-and middle income countries
- Healthcare utilisation for fever treatment: Using Bayesian IRT models to estimate treatment burden in low-resource settings.
- SDG indicators and nationally representative survey data: Investigation precision in public health data-science.
National and sub-national variation in patterns of febrile case management in sub-Saharan Africa
Alegana VA. et al, (2018), Nature Communications, 9
Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence.
Alegana VA. et al, (2016), Scientific reports, 6
Fine resolution mapping of population age-structures for health and development applications
Alegana VA. et al, (2015), Journal of The Royal Society Interface, 12, 20150073 - 20150073
Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models
Alegana VA. et al, (2013), Spatial and Spatio-temporal Epidemiology, 7, 25 - 36
Spatial modelling of healthcare utilisation for treatment of fever in Namibia
Alegana VA. et al, (2012), International Journal of Health Geographics, 11, 6 - 6
Routine data for malaria morbidity estimation in Africa: challenges and prospects
Alegana VA. et al, (2020), BMC Medicine, 18
Bayesian Spatiotemporal Modeling of Routinely Collected Data to Assess the Effect of Health Programs in Malaria Incidence During Pregnancy in Burkina Faso.
Rouamba T. et al, (2020), Scientific reports, 10
Estimating hospital catchments from in-patient admission records: a spatial statistical approach applied to malaria.
Alegana VA. et al, (2020), Scientific reports, 10
A spatial database of health facilities managed by the public health sector in sub Saharan Africa
Maina J. et al, (2019), Scientific Data, 6
A spatial regression model for the disaggregation of areal unit based data to high-resolution grids with application to vaccination coverage mapping.
Utazi CE. et al, (2019), Statistical methods in medical research, 28, 3226 - 3241