Ecology of Andes & Choclo Viruses

由西方多种汉坦病毒中的任何一种引起的汉坦病毒心肺综合征 据认为，半球是通过吸入受感染的啮齿动物排泄物而收缩的。在南部和中部 智利，安第斯山脉病毒感染乙齿鼠长尾鼠 (Oligoryzomys longicaudatus)，并导致一种罕见但罕见的疾病 人类感染严重，死亡率高。在巴拿马西部，Choclo 病毒感染啮齿动物 Oligoryzomys fulvescens 会引起常见但通常轻微或不明显的人类感染，感染率低 死亡率。在这两个地区，传播风险似乎受到许多因素的影响 受感染的啮齿动物和易感人群之间有密切接触的机会。我们将集中精力 对其中三个因素进行调查，目的是获得对未来设计至关重要的见解 减少汉坦病毒传播的环境干预措施。 首先，最近在智利和巴拿马进行的调查表明，选定的植被具有感染风险 受感染媒介啮齿动物喜欢的栖息地。在智利，可以通过遥感来预测暴露风险 对全国 2/3 的地区进行卫星图像分析。在巴拿马，一项微观分析表明 家庭周围受感染的啮齿动物与农业活动之间的复杂关系。我们建议重点关注 使用标记重捕获诱捕和无线电遥测技术研究啮齿动物和栖息地随时间变化的空间关系 标记啮齿动物的活动，特别是在家庭周围环境中。其次我们将创建一个 动态模型扩展了我们当前的静态风险分析。新模型将图论应用到领域 收集啮齿动物栖息地偏好和景观内运动的数据，以预测可能的情况 受感染啮齿动物的活动。我们将使用来自与过去不同的站点的数据来测试模型 创建模型。通过量化啮齿动物的病毒载量将提高模型的时间精度 冬季（低传播）和春季（高传播）季节的血液、组织和尿液。最后， 对巴拿马高危人群进行的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.