Use this URL to cite or link to this record in EThOS:
Title: Refining baseline estimates of dengue transmissibility and implications for control
Author: Imai, Natsuko
ISNI:       0000 0004 6059 2327
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Access from Institution:
Climate change, globalisation and increased travel, increasing urban populations, overcrowding, continued poverty, and the breakdown of public health infrastructure are among the factors contributing to the 30-fold increase in total dengue incidence in the past 50 years. Consequently, with an estimated 40% of the world's population at risk of infection, dengue is now the world's most important mosquito-borne viral infection. However estimates of dengue transmissibility and burden remain ambiguous. Since the majority of infections are asymptomatic, surveillance systems substantially underestimate true rates of infection. With advances in the development of novel control measures and the recent licensing of the Sanofi Dengvaxia® dengue vaccine, obtaining robust estimates of average dengue transmission intensity is key for estimating both the burden of disease from dengue and the likely impact of interventions. Given the highly spatially heterogeneous nature of dengue transmission, future planning, implementation, and evaluation of control programs are likely to require a spatially targeted approach. Here we collate existing age-stratified seroprevalence and incidence data and develop catalytic models to estimate the burden of dengue as quantified by the force of infection and basic reproduction number. We identified a paucity of serotype-specific age stratified seroprevalence surveys in particular but showed that non-serotype specific data could give robust estimates of baseline transmission. Chapters explore whether estimates derived from different data types are comparable. Using these estimates we mapped the estimated number of dengue cases across the globe at a high spatial resolution allowing us to assess the likely impact of targeted control measures.
Supervisor: Ferguson, Neil M. ; Cauchemez, Simon ; Dorigatti, Ilaria Sponsor: Medical Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral