Here we evaluate how a reduction in sampling frequency influences our ability to detect fluctuations in abundance of deer mice, Peromyscus maniculatus; the infection dynamics of a directly transmitted zoonotic virus, SNV (Bunyaviridae: Hantavirus; an agent of hantavirus pulmonary syndrome [HPS] that causes severe morbidity and mortality in humans); and implications this may have to interpretation of human exposure risk. Populations of hosts that are capable of high levels of fecundity, such as deer mice, can exhibit extreme changes in abundance over brief periods (Krebs 1966, 1996, Singleton 1989). The use of infrequent sampling (i.e., seasonal or semiannual) to monitor population abundance of small mammals, such as deer mice, is common (e.g., Saitoh et al. 1999, Strann et al. 2002, Flowerdew et al. 2004, Larsen et al. 2007). In some instances studies using infrequent sampling of small mammals also extend to examination of wildlife (e.g., Cavanagh et al. 2004) or zoonotic pathogens (e.g., Carver et al. 2008) among individuals comprising reservoir populations, such as for hantaviruses in their rodent hosts (Biggs et al. 2000a, 2000b, Escutenaire et al. 2000, Olsson et al. 2003, Pearce-Duvet et al. 2006).

Potentially, the frequency of sampling necessary to describe dynamics of deer mouse populations may differ from the frequency needed to describe dynamics of SNV infection. For example, bi-monthly trapping of deer mice may adequately detect their population fluctuations [due to an approximate 1–2-month lag between the birth of pups and first detection by trapping (King et al. 1963, Kirkland and Layne 1989)], whereas a monthly trapping interval may be necessary to detect the dynamics of SNV transmission [due to a 2–4-week time interval between infection and detection of SNV IgG antibody in deer mice (Botten et al. 2000, 2002)]. Accordingly, it is possible that the sampling interval that is adequate to quantify deer mouse population demographics may be longer than what is necessary to capture dynamics of SNV infection. If the frequency of sampling does not adequately capture both deer mouse population demographics and SNV dynamics, it could lead to erroneous conclusions about host–pathogen relationships and, by extension, sub-optimal management and health interventions.

We used the minimum number of individuals known to be alive (MNA) during a 3-day trapping session as an index of population abundance for each month (cf. Krebs 1966). The minimum number of deer mice antibody positive to SNV (MNI), during each trap session, was calculated in the same way as MNA for grids 11 and 12. Estimated standing prevalence (ESP) of deer mice for a given month was calculated by dividing MNI by MNA (Mills et al. 1999a). Less frequent sampling (e.g, bi-annual or annual), and consequently a lack of recaptures, precluded the use of more complex population estimates of deer mouse abundance and the number of deer mice infected. Because hantaviruses cause chronic (likely life-time) infection in their hosts, antibody is considered a marker of infection (Mills et al. 1999a). We consider antibody-positive deer mice to be actively infected and likely infectious (shedding infectious virus).

Across all three grids, a reduction in the frequency of sampling (even bi-monthly sampling) of deer mice resulted in an underestimation of monthly MNA by at least 10% (Table 1). The underestimation of monthly MNA grew to 13%–20% when the sampling frequency was reduced beyond bi-monthly. Monthly MNI of deer mice at grid 11 was also underestimated as the frequency of sampling was reduced, but by only a small amount, compared to MNA (Table 1). Monthly MNI was never underestimated at grid 12, due to a high frequency of months where no infected deer mice were detected (Fig. 1, Table 1).

Values of ESP from less frequent sampling tended to overestimate measures of ESP from monthly sampling (Table 2, Fig. 2). Overestimation of ESP resulted from relatively stable MNI values, but a smaller MNA values (i.e., the numerator was relatively constant, but the denominator was generally smaller; Table 1) when sampling frequency was less than monthly. This pattern was particularly evident at quarterly, semiannual, and annual sampling intervals (Fig. 2c–h), especially when ESP was >0.15. These overestimates were only statistically significant, however, for monthly estimates at grid 11 (Table 2), which produced a higher number of infected mice throughout the study.

On the basis of monthly sampling, the highest annual MNA of deer mice was recorded most frequently between August and October and least frequently between April and June (Table 3). The most common months for which lows in MNA were observed were less consistent among trapping grids (Table 3). We did not detect any infection in deer mice in one of the 14 years of this study at grid 11, and 4 of the 14 years at grid 12. The maximum annual MNI was most frequently observed between March and June at grids 11 and 12, but annual highs in MNI were also observed in other months, including winter (Table 3). Lows in MNI (often zero) were recorded more frequently in the autumn and winter months, although annual lows in MNI were often recorded in other months as well (Table 3). Maximum annual ESP was also observed in many months, including winter (Table 3). The highest annual ESP, at both grids, was most commonly observed in May or June (Table 3). Similar to MNI, lows in ESP were frequently observed across most months, but were most common in autumn and winter (Table 3).

When sampling frequency was reduced, fewer annual highs and lows in MNA were detected (Table 4). Similarly, the percentage of highs detected in annual MNI and ESP also declined with less frequent sampling (Tables 3 and ​and4).4). The capacity to detect annual lows in MNI and ESP, however, remained high, regardless of reduced sampling frequency, reflecting a relatively high number of months in which no infected deer mice were captured (Tables 3 and ​and44).

Overestimation of high levels of ESP is of direct interest and application to human HPS exposure risk. Human incidence of HPS in Montana is not detected when ESP of deer mice, from monthly sampling, is below 10% (Madhav et al. 2007), suggesting that investment in public health awareness programs or interventions are best targeted when deer mouse ESP exceeds this value. This study demonstrates that if this knowledge were currently applied to direct health awareness programs or interventions under a less frequent sampling regime (such as would be the case with semiannual and annual sampling frequencies), values of deer mouse ESP exceeding 10% would be overestimated and would result in premature investment in public health campaigns or interventions. Conversely, intervention when it may not be necessary is far superior, in terms of public health, to inaction. Of course, less frequent sampling is also likely to delay detection of epizootic conditions.

Resources to invest in host–pathogen monitoring programs are likely limited in many instances. As such, short-term studies, with limited spatial replication, which seek general information about host abundance and pathogen dynamics over time, should be interpreted with caution. We observed substantial fluctuations in deer mouse MNA, MNI, and ESP over 14 years, a feature characteristic of highly fecund animals (Krebs 1966, 1996, Singleton 1989, Carver et al. 2008). However, SNV dynamics did not always reflect deer mouse abundance on the same grid and were not always similar between grids. These findings support those of Douglass et al. (2001), who found large spatial and temporal variation in MNA (near 0 to over 120 per 100-trap grid) and MNI (0 to over 60) among 18 grids in Montana. Despite the variable nature of SNV over time, prevalence among deer mouse populations tends to peak in spring, across disparate geographic locations and variable habitat types (Douglass et al. 2001, Mills et al. 1999b and references therein). While it was not the specific focus of this study, understanding processes driving population fluctuations of deer mice (e.g., survival and dispersal) would likely contribute to a better understanding of the dynamics of infection (Douglass et al. 2007, Madhav et al. 2007, Lonner et al. 2008, Luis et al. 2010). Our results indicate that to capture natural variation in deer mouse abundance and dynamics of SNV, surveys need to be spatially replicated and of long duration (Douglass et al. 2001). We intentionally based our less frequent sampling, particularly semiannual and annual sampling, on prior knowledge of deer mouse abundance and SNV dynamics at our grids. We acknowledge that someone establishing a new sampling regime would not have the benefit of this prior knowledge, likely resulting in the detection of fewer annual minima and maxima of MNA, MNI, and ESP. Investigations, with limited resources, that aim to understand spatial variation in host populations and risk of zoonotic pathogen exposure (without a priori knowledge of host–pathogen dynamics) should first seek to understand annual variation in infection and then target spatial surveys during seasons when infection is at a maxima. In such cases, investigators should keep in mind that estimates of high infection prevalence are likely to be inflated. As a corollary, estimates of high infection prevalence could be improved by increasing sampling frequency during periods (epizootics) where ESP exceeds 10%.

In this study, underestimation of deer mouse abundance is important in understanding SNV infection dynamics, because this inflates estimates of ESP. In general, determining the sampling interval to adequately estimate host abundance is likely to depend on the developmental rate of juveniles and the duration and magnitude of natural population fluctuations (Krebs and Myers 1974). For example, there is a 1–2-month lag between the birth of pups and first detection of deer mice by trapping (King et al. 1963, Kirkland and Layne 1989). We have trapped deer mice monthly and this appears to have been a reasonable frequency to capture abundance and follow temporal fluctuations in their abundance, a conclusion also supported by Parmenter et al. (1999). Naturally, the ability to document fluctuations in population abundance and to investigate processes that underlie fluctuations (e.g., survival and recruitment) diminishes as the frequency of sampling decreases (Krebs and Myers 1974). Similar to our findings, that sampling less frequently than monthly leads to underestimates of MNA, attempts to model temporal fluctuations in deer mouse population abundance, using a range of predictors (e.g., temperature, precipitation, survival, and maturation), have also required a monthly sampling to acquire any level of accuracy (Yaffee et al. 2008, Luis et al. 2010). Further, accurate estimation of population demographic parameters [i.e., survival, recruitment (Krebs and Myers 1974), and dispersal (Lonner et al. 2008, Waltee et al. 2009)], all necessary to understand disease dynamics (Keeling and Rohani 2008), require frequent sampling. Understanding the dynamics of SNV among deer mice would greatly benefit from investigations, based on frequent sampling, which link environmental determinants of deer mouse abundance (Luis et al. 2010) and infection.