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首页> 外文期刊>The American Journal of Tropical Medicine and Hygiene >Risk Assessment of Dengue Transmission in Bangladesh Using a Spatiotemporal Network Model and Climate Data
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Risk Assessment of Dengue Transmission in Bangladesh Using a Spatiotemporal Network Model and Climate Data

机译：使用时空网络模型和气候数据的孟加拉国登革船风险评估

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Vector-borne disease risk assessment is crucial to optimize surveillance, preventative measures (vector control), and resource allocation (medical supplies). High arthropod abundance and host interaction strongly correlate to vector-borne pathogen transmission. Increasing host density and movement increases the possibility of local and long-distance pathogen transmission. Therefore, we developed a risk-assessment framework using climate (average tem-perature and rainfall) and host demographic (host density and movement) data, particularly suitable for regions with unreported or underreported incidence data. This framework consisted of a spatiotemporal network-based approach coupled with a compartmental disease model and nonhomogeneous Gillespie algorithm. The correlation of climate data with vector abundance and host-vector interactions is expressed as vectorial capacity-a parameter that governs the spreading of infection from an infected host to a susceptible one via vectors. As an example, the framework is applied for dengue in Bangladesh. Vectorial capacity is inferred for each week throughout a year using average monthly temperature and rainfall data. Long-distance pathogen transmission is expressed with human movement data in the spatiotemporal network. We have identified the spatiotemporal suitability of dengue spreading in Bangladesh as well as the significant-incidence window and peak-incidence period. Analysis of yearly dengue data variation suggests the possibility of a significant outbreak with a new serotype introduction. The outcome of the framework comprised spatiotemporal suit-ability maps and probabilistic risk maps for spatial infection spreading. This framework is capable of vector-borne disease risk assessment without historical incidence data and can be a useful tool for preparedness with accurate human movement data.
机译：媒介传播疾病风险评估对于优化监测、预防措施（媒介控制）和资源分配（医疗用品）至关重要。节肢动物丰度高和宿主相互作用与媒介传播病原体密切相关。宿主密度和移动的增加增加了病原体局部和远距离传播的可能性。因此，我们利用气候（平均温度和降雨量）和寄主人口统计（寄主密度和移动）数据开发了一个风险评估框架，尤其适用于发病率数据未报告或报告不足的地区。该框架由一个基于时空网络的方法、一个分区疾病模型和非齐次Gillespie算法组成。气候数据与病媒丰度和宿主-病媒相互作用的相关性表示为病媒容量——一个控制感染通过病媒从受感染宿主向易感宿主传播的参数。例如，该框架适用于孟加拉国的登革热。利用月平均气温和降雨量数据推断出一年中每周的矢量容量。病原体的远距离传播是通过时空网络中的人体运动数据来表达的。我们已经确定了登革热在孟加拉国传播的时空适宜性，以及重要的发病窗口和发病高峰期。对每年登革热数据变化的分析表明，随着新血清型的引入，有可能发生重大疫情。该框架的结果包括时空适应能力图和空间感染传播的概率风险图。该框架能够在没有历史发病率数据的情况下进行病媒传播疾病风险评估，并且可以成为一个有用的工具，用于准备准确的人类活动数据。

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