. 114 Downloads. Abstract Human cases of hantavirus pulmonary syndrome caused by Sin Nombre virus are the endpoint of complex ecological cascade from weather conditions, population dynamics of deer mice, to prevalence of SNV in deer mice. Using population trajectories from the literature and mathematical modeling, we analyze the time lag between deer mouse population peaks and peaks in SNV antibody prevalence in deer mice. Because the virus is not transmitted vertically, rapid population growth can lead initially to reduced prevalence, but the resulting higher population size may later increase contact rates and generate increased prevalence. Incorporating these factors, the predicted time lag ranges from 0 to 18 months, and takes on larger values when host population size varies with a longer period or higher amplitude, when mean prevalence is low and when transmission is frequency-dependent.

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Population size variation due to variation in birth rates rather than death rates also increases the lag. Predicting future human outbreaks of hantavirus pulmonary syndrome may require taking these effects into account.

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Abstract Because recent studies have not demonstrated a strong relationship between rodent density and Sin Nombre virus (SNV) seroprevalence, there is speculation that seroprevalence may be related to other factors, including habitat quality and food availability. We evaluated densities of deer mice ( Peromyscus maniculatus), plant cover and biomass, and terrestrial arthropod biomass at 2 sites in the southwestern United States to identify factors that may affect the seroprevalence rate of SNV within a rodent population. Seroprevalence differed significantly between years. Although interaction of deer-mouse density, plant cover and biomass, and arthropod biomass was not a strong predictor of seroprevalence ( R 2 = 0.64, P = 0.04), we observed a significant contribution to a repeated-measures model by deer-mouse density ( P = 0.02).

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Our data suggest that as rodent density increases, so does the seroprevalence rate within that population. Although not significantly correlated, we observed the lowest levels of arthropod biomass when seroprevalence was highest.

Based on our results, evaluating changes in habitat quality and incorporating measurement of local ecological variables with studies of fluctuations in rodent density may aid in predicting human outbreaks of hantavirus disease. Comparison of ecological variables We recorded a higher density of deer mice at Chinle (range, 4.5–10.6 animals/ha) than Gallup (1.3–6.1 animals/ha) each year of sampling. Biomass of terrestrial arthropods was 2–2.5 times higher at Chinle than at Gallup in 1994 and 1995 and similar between the 2 sites in 1996 and 1997. In 1998, arthropod biomass was 2 times greater at Gallup compared with Chinle. Plant cover was highest in 1997 and 1998 for Chinle and Gallup. Plant biomass was greatest in 1995 and 1996 at Chinle but lowest during those 2 years at Gallup. Using seroprevalence as the response variable, we tested for a linear relationship between seroprevalence and ecological variables by developing a repeated-measures ANCOVA model.

The site × year and deer-mouse density covariates contributed ( P = 0.01, P = 0.02, respectively) to the overall model when combining all covariates (multiple R 2 = 0.64, d.f. = 13, 21, P = 0.04; ). We further analyzed each individual covariate using the same main and repeated factors. Again, deer-mouse density contributed to the model (multiple R 2 = 0.50, d.f. = 10, 24, P = 0.04; ). To further examine possible relationships between seroprevalence and remaining variables, we developed a plot of the supersmoothed data from each web and year from both sites. Although supersmoothing may result in an exaggeration of an effect, its use can depict general patterns of interactions between measured variables.

We observed that seroprevalence tended to be lower when deer-mouse density was low and arthropod biomass was moderate to high. Additionally, arthropod biomass was lowest and deer-mouse density moderate when seroprevalence reached the highest levels. Scatter plot of the supersmoothed data of each variable data set from each web for each year of sampling. Each variable is represented by a corresponding letter: D, deer-mouse density; A, arthropod biomass; C, plant cover; B, plant biomass; seroprevalence is represented by the solid line Discussion We found a lower level of understory plant cover and higher densities of deer mice at the Chinle site than at the Gallup site. Deer mice are more common on sparsely vegetated sites and areas of open soil surface, which may be related to their consumption of seeds. In addition to the lower plant cover, the Chinle site also had a higher arthropod biomass than did the Gallup site. Higher biomass of arthropods may increase food availability and therefore contribute to higher deer-mice densities at the Chinle site.

Our data demonstrate a significant interaction between SNV seroprevalence and deer-mouse density, which is contrary to recent studies (;; ). The fact that we observed an interaction between population density and seroprevalence may be due to the length of our study compared with other efforts (5 years versus 1–2 years). Future studies should incorporate a combination of frequent within-year rodent sampling (once every 1–2 months) over several years to account for variation in environmental factors, such as precipitation, plant growth, and production of arthropods and seeds. Our study indicated that when arthropod biomass was relatively high, seroprevalence was low, and that when arthropod biomass was low, seroprevalence was high. The fact that we did not observe a statistical relationship between these variables may have been due to the large annual variability in seroprevalence reflected in our model. However, our results support the idea that when food availability is low, animals competing for limited resources are more frequently in physical contact and therefore more likely to spread SNV throughout the population. Our data indicate that rodent density may be the primary driver for seroprevalence but also suggests that food availability (as indicated by arthropod biomass) may contribute to the seroprevalence rate within a rodent population.

Future studies should include more frequent within-year sampling and evaluation of the interaction of variables, such as use and availability of specific food source (both seeds and arthropods), quality of habitat, environmental stressors (sudden alterations in resource allocations, such as food supply), and individual animal health. Incorporating data on ecological variables with estimated predictions of rodent densities may ultimately provide a valuable tool to recognize when and where human outbreaks of hantavirus may occur. Acknowledgments We thank D. Pacheco, and S. Cross for their extremely hard work in the field and assisting with sample processing and T.

Foxx for her initial involvement in this project. Additional personnel who assisted in this study were L.

Payne, and T. Gonzales for reviewing the manuscript, H. Dson importer for poser. Hinojosa for manuscript editing, and V.

Lancaster for assistance in statistical analysis. We also thank R. Parmenter and T. Yates, Biology Department of the University of New Mexico, for providing assistance in the web design. Finally, we owe special thanks to H. Shorty, Navajo Division of Health, Navajo Nation, for initial training of our team in proper handling procedures and his assistance in study site selection on the Navajo Nation and to the families that granted us access to our Gallup study site. This study was supported by Public Health Service grant RO1-A1-36336.

Literature Cited.