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.