Ecology of Andes & Choclo Viruses

汉他病毒心肺综合征由西方国家的任何一种汉他病毒引起 被认为是通过吸入受感染的啮齿动物排泄物而收缩的。南部和中部 在智利，安第斯山脉病毒感染了sigmodontine啮齿类动物长尾寡鼠，并导致罕见的，但 严重的人类感染，死亡率高。在巴拿马西部，Choclo病毒感染啮齿动物 Oligoryzomys fulvescens和引起一种常见的，但通常是轻度或不明显的人类感染， 死亡率在这两个地区，传播风险似乎受到许多因素的影响， 受感染的啮齿类动物和易感人群之间的密切接触机会。呢我们一起来 对其中三个因素进行调查，目标是获得对未来设计至关重要的见解 采取环境干预措施，减少汉坦病毒的传播。 首先，最近在智利和巴拿马进行的调查发现，感染风险与选定的植被有关 受感染的啮齿动物喜欢的栖息地。在智利，可通过遥感预测接触风险 卫星图像分析覆盖了全国三分之二的地区在巴拿马，一项微观分析表明， 感染的啮齿动物与农业活动之间的复杂关系。我们建议将重点 啮齿动物和栖息地之间的空间关系，随着时间的推移，使用标记重捕诱捕和无线电遥测 以标记啮齿动物的运动，特别是在近室内环境中。其次，我们将创建一个 动态模型，扩展了我们目前对风险的静态分析。新模型将图论应用于领域 收集啮齿动物栖息地偏好和景观内运动的数据，以预测 受感染的啮齿动物的移动。我们将使用来自不同地点的数据来测试该模型， 创建模型。通过对啮齿动物体内病毒载量的定量分析，可以提高模型的时间精度 血液、组织和尿液在冬季（低传播）和春季（高传播）。最后， 对巴拿马高危人群进行的一系列血清调查将量化对人类感染的影响 与啮齿动物密度和运动的时空变化有关。

Hantavirus cardiopulmonary syndrome resulting from any of a number of hantaviruses in the western hemisphere is thought to be contracted through inhalation of infected rodent excreta. In southern and central Chile, the Andes virus infects the sigmodontine rodent Oligoryzomys longicaudatus, and causes a rare but severe human infection with high mortality. In western Panama, the Choclo virus infects the rodent Oligoryzomys fulvescens and causes a common but usually mild or inapparent human infection with a low mortality rate. In both regions the risk of transmission appears to be influenced by many factors increasing the opportunity for close contact between infected rodents and susceptible humans. We will focus our investigations on three of these factors, with the goal of gaining insights critical for the design of future environmental interventions to decrease hantavirus transmission. First, recent investigations in Chile and Panama have associated risk of infection with selected vegetation habitats favored by the infected vector rodents. In Chile exposure risk can be predicted by remote sensing with satellite imagery analysis over 2/3 of the country. In Panama a micro scale analysis has suggested complex relationships between peridomestic infected rodents and agricultural activities. We propose to focus on spatial relationships between rodents and habitats over time, using mark-recapture trapping and radiotelemetry to mark rodent movements, particularly in peridomestic environments. Second we will create a dynamic model that extends our current static analysis of risk. The new model will apply graph theory to field collected data of rodent habitat preferences and movements within the landscape to predict the likely movement of infected rodents. We will test the model using data from sites different from those used to create the model. The temporal precision of the model will be improved by quantitating viral load in rodent blood, tissue and urine in the winter (low transmission) and spring (high transmission) seasons. Finally, serial serosurveys of at-risk human populations in Panama will quantify the impact on human infection associated with spatial-temporal variations in rodent density and movement.