US Center for Disease Control and Prevention (CDC), Dengue Branch, San Juan, Puerto Rico.
PLoS Negl Trop Dis. 2024 Mar 1;18(3):e0011143. doi: 10.1371/journal.pntd.0011143. eCollection 2024 Mar.
Dengue viruses (DENV) are endemic in the US territories of Puerto Rico, American Samoa, and the US Virgin Islands, with focal outbreaks also reported in the states of Florida and Hawaii. However, little is known about the intensity of dengue virus transmission over time and how dengue viruses have shaped the level of immunity in these populations, despite the importance of understanding how and why levels of immunity against dengue may change over time. These changes need to be considered when responding to future outbreaks and enacting dengue management strategies, such as guiding vaccine deployment. We used catalytic models fitted to case surveillance data stratified by age from the ArboNET national arboviral surveillance system to reconstruct the history of recent dengue virus transmission in Puerto Rico, American Samoa, US Virgin Islands, Florida, Hawaii, and Guam. We estimated average annual transmission intensity (i.e., force of infection) of DENV between 2010 and 2019 and the level of seroprevalence by age group in each population. We compared models and found that assuming all reported cases are secondary infections generally fit the surveillance data better than assuming all cases are primary infections. Using the secondary case model, we found that force of infection was highly heterogeneous between jurisdictions and over time within jurisdictions, ranging from 0.00008 (95% CrI: 0.00002-0.0004) in Florida to 0.08 (95% CrI: 0.044-0.14) in American Samoa during the 2010-2019 period. For early 2020, we estimated that seropositivity in 10 year-olds ranged from 0.09% (0.02%-0.54%) in Florida to 56.3% (43.7%-69.3%) in American Samoa. In the absence of serological data, age-specific case notification data collected through routine surveillance combined with mathematical modeling are powerful tools to monitor arbovirus circulation, estimate the level of population immunity, and design dengue management strategies.
登革热病毒(DENV)在美国的波多黎各、美属萨摩亚和美属维尔京群岛等地流行,佛罗里达州和夏威夷也报告了局部暴发。然而,尽管了解免疫力水平随时间变化的方式和原因对于理解如何以及为何免疫力水平可能随时间而变化非常重要,但对于登革热病毒传播的强度以及登革热病毒如何塑造这些人群的免疫水平,人们知之甚少。在应对未来暴发和实施登革热管理策略(如指导疫苗部署)时,需要考虑这些变化。我们使用基于 ArboNET 国家虫媒病毒监测系统按年龄分层的病例监测数据拟合催化模型,重建了 2010 年至 2019 年期间波多黎各、美属萨摩亚、美属维尔京群岛、佛罗里达州、夏威夷和关岛最近登革热病毒传播的历史。我们估计了每个人群中 2010 年至 2019 年期间的平均年传播强度(即感染率)和按年龄组划分的血清流行率。我们比较了模型,发现假设所有报告的病例都是继发感染通常比假设所有病例都是原发感染更符合监测数据。使用继发感染模型,我们发现各司法管辖区之间以及各司法管辖区内的感染率随时间变化高度异质,从佛罗里达州的 0.00008(95%置信区间:0.00002-0.0004)到美属萨摩亚的 0.08(95%置信区间:0.044-0.14)。在 2010-2019 年期间,对于 2020 年初,我们估计 10 岁儿童的血清阳性率从佛罗里达州的 0.09%(0.02%-0.54%)到美属萨摩亚的 56.3%(43.7%-69.3%)不等。在没有血清学数据的情况下,通过常规监测收集的特定年龄的病例报告数据与数学建模相结合,是监测虫媒病毒传播、估计人群免疫力水平以及设计登革热管理策略的有力工具。