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

登革热是全球增长最快的传染病之一，自2000年以来报告病例增加了8倍。由于很大一部分登革热病毒感染是无症状的，而且疾病监测的质量在不断变化，计算模型一直是估计登革热全球负担的核心。然而，当前模型的一个关键限制是，它们不能准确估计这一负担的逐年变化情况。这使得基于模型的登革热负担估计无法产生与在艾滋病毒、结核病和疟疾领域相同的影响，在这些领域，它们被积极用于跟踪实现国际目标的进展情况。今年，将制定2021-2030年期间减少登革热全球负担的新目标。目前建模方法的数据缺口和局限性限制了我们跟踪国家进展、了解现有干预措施如何发挥作用以及建议控制规划需要如何改变以实现这些新目标的能力。在这项研究中，我将开发新的详细的全球登革热模型，使人们能够对过去、现在和未来的登革热全球负担做出新一代的预测。这些模型可用于回答三个主要目标：目标1：自2000年以来登革热负担的全球增长如何变化？通过将一个新的全球登革热数据库与地质统计学和数学建模技术相结合，我将对2000-2020年登革热负担的增长作出公正的负担估计。目标2：减少登革热死亡的政策变化效果如何？通过对巴西圣保罗和菲律宾400多万个人患者记录的分析，我将调查寻求治疗、诊断和临床管理方面的变化是如何降低登革热死亡风险的。这将衡量当前干预措施对死亡率的影响，并确定可以在哪些方面取得进一步成果。目标3:2021-2030年，每个国家的登革热负担将增长多少？通过将目标1中的模型预测到未来，考虑到气候变化、城市化和登革热免疫水平的提高，可以对2021-2030年的登革热负担做出可靠的预测。然后进行登革热控制可行性评估，确定每个国家在实现2021-2030年目标方面面临的具体障碍。该奖学金旨在提高我们对登革热全球负担如何在关键时刻发生变化的理解。目标1将侧重于开发新一代登革热模型，以估计2000-2020年过去发病率的变化，以了解我们为何无法控制登革热的扩大。目标2将回答有关目前减少登革热死亡的努力是否有效的关键问题。目标3将估计登革热发病率的未来增长，使各国能够决定如何最好地解决这一日益严重的问题。所有的数据、模型和预测都将放在一个新的专门网站上，研究人员和政府官员可以在这个网站上以完全透明的方式详细研究这些估计。除了登革热之外，这些模型还将提供关于现代新发传染病如何能够在全球不受控制地传播的基本见解，并有助于设计针对未来大流行的新战略。

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.