Sin Nombre hantavirus (SN) is a recently discovered virus carried by deermice that causes disease with high mortality in humans. Several recent studies have proposed that human disturbance of habitat significantly affects the number of deermice infected with SN. Given unprecedented rates of disturbance and limited understanding of the mechanisms governing variation in SN infection, a thorough study of how disturbance affects SN dynamics is warranted. The central focus of the proposed study is to determine how human disturbance affects SN prevalence in deermice and other reservoirs. To address this issue, a multifaceted research program is proposed that includes empirical and theoretical work. The field data will be used to determine the underlying mechanisms responsible for differences in prevalence. These ground-based data will be used to generate predictive mathematical models of prevalence using aerial and satellite images.
The broader impacts of this study include education, interdisciplinary research and national security. Several undergraduate and graduate students will be trained as part of this research. The project unites scientists from diverse fields (geography, mathematics, ecology, virology). Lastly, the research will yield critical information on the biology of Sin Nombre virus, which is listed as a biological agent of concern for national security.
Rodent Diversity Depresses Incidence of Disease in Deer Mice The central focus of this project was to understand how disturbance and biodiversity impacted host-pathogen interactions. To address this issue, we studied populations of deer mice naturally infected with Sin Nombre (hanta) Virus (the causative agent of hantavirus-cardiopulmonary syndrome in humans). We monitored 6-12 deer mouse populations and measured SNV prevalence in deer mice and other potential hosts from 2004-2010. During this time, deer mouse populations changed in population size from three to nine-fold and the percent of deer mice infected with SNV varied from 0-60%. We found that the incidence of SNV in deer mice was lower at highly disturbed sites and that this result was not consistently density dependent. Lower infection rates at disturbed sites appeared to be a function of the diversity of the nocturnal rodent community. Disturbed sites had a greater number of rodent species with select species that appear to be "Dilution Agents" reducing the incidence of SNV in deer mice. Another factor contributing to lower SNV prevalence at disturbed sites was the decreased persistence of individuals (Lehmer, 2008). That is, animals did not remain on disturbed sites as long as they did on undisturbed sites. We developed several new tools to be used in future studies of hantavirus and other pathogens. We developed an IgM assay for SNV in deer mice. IgM antibodies are the initial antibodies produced in response to infection. The IgM assay allows identification of SNV infections in deer mice at earlier stages than before, although further research is needed to validate this statement. We also generated a model using satellite imagery (Moderate-resolution Imaging Spectroradiometer) to predict deer mice density and the number of infected deer mice. This model can predict the potential risk of hanta virus using satellite images of landscape greenness and thus could be an important tool for public health officials. We developed a mouse surveillance system that allowed us to observe mice to determine the frequency at which mice engaged in behaviors that promoted disease transmission. We have a large data set from this project that has opened up a wide array of mathematical modeling questions. We will provide the data set to biology and math students for future thesis projects. We have presented our results at national scientific meetings as well as to the general public.
