Mapping the growing global burden of dengue to help countries plan for the next decade of dengue control

点击翻译按钮获取中文摘要

Dengue is one of the fastest growing global infectious diseases with an 8-fold increase in reported cases since 2000. Because a large proportion of dengue virus infections are asymptomatic and the quality of disease surveillance is constantly changing, computational models have been central to estimating the global burden of dengue. However, a key limitation of current models is that they do not accurately estimate how this burden changes year-on-year. This prevents model-based burden estimates of dengue having the same impact they do in the fields of HIV, TB and malaria where they are actively used to track progress towards international targets. This year, new goals for reducing the global burden of dengue between 2021-2030 will be set. Data gaps and limitations of current modelling approaches constraint our ability to track country progress, understand how existing interventions are working and suggest how control programmes need to change to meet these new targets.In this fellowship I will develop novel detailed global dengue models that allow a new generation of predictions of the past present and future global burden of dengue to be made. These models can be used to answer three main aims:Aim 1: How has the global growth in dengue burden changed since 2000?By pairing a new global dengue database with geostatistical and mathematical modelling techniques I will generate unbiased burden estimates of the growth in dengue burden 2000-2020.Aim 2: How effective have policy changes to reduce dengue deaths been?Through an analysis of over 4 million individual-level patient records in São Paulo (Brazil) and the Philippines, I will investigate how changes in treatment seeking, diagnosis and clinical management have reduced the risk of dengue death. This will measure the impact of current interventions on mortality and identify where further gains could be made.Aim 3: By how much will dengue burden grow 2021-2030 in each country?By projecting the models from Aim 1 into the future taking into account changes in climate, urbanisation and growing levels of immunity to dengue, robust predictions of dengue burden 2021-2030 can be made. A dengue control feasibility assessment will then identify the specific barriers each country faces in meeting their 2021-2030 targets.This fellowship aims to improve our understanding of how the global burden of dengue is changing at a pivotal time. Aim 1 will focus on developing a new generation of dengue models to estimate past changes in incidence 2000-2020 to understand why we were unable to contain dengue expansion. Aim 2 will answer key questions about the effectiveness of current efforts to reduce dengue deaths. Aim 3 will estimate future growth in dengue incidence allowing countries to decide how to best address this growing problem. All the data, models and predictions will be hosted on a new dedicated website that allows researchers and government officials to explore these estimates in detail and with full transparency. Beyond dengue, these models will also provide fundamental insights into how modern emerging infectious diseases are capable of uncontained global spread and help design new strategies against future pandemics.