516 respective carrying capacities, lim t-1 NrðtÞ ¼Kr and lim t-1 NsðtÞ ¼Ks: The preferred habitats serve as a population source for the boundary region. The densities in the boundary region depend on the densities of these source populations and the movement rates into and out of this region. In particular, in the boundary region, the reservoir and spillover population densities are lim t-1 NaðtÞ ¼ pi Kr ¼ Ka and limNbðtÞ ¼ po t-1 pi Ks ¼ Kb; po respectively. As the ratio pi=po increases, so do the population densities in the boundary region, whereas the densities in the preferred habitats will approach their respective carrying capacities. Hence, the total reservoir population density (preferred þ boundary) is Kr þ Ka and the total spillover population density is Ks þ Kb. The equilibrium values for the unique DFE are Sr ¼ Kr, Sa ¼ Ka, Ss ¼ Ks, and Sb ¼ Kb; all of the other equilibrium values are zero. We assume initial densities are less than or equal to their respective carrying capacities, 0rNið0ÞrKi, i ¼ r; s; a; b with Nrð0Þ40 and Nsð0Þ40. Whether the DFE is stable depends on the basic reproduction number for the habitat-based model. We calculate reproduction numbers for each of the preferred habitats and an approximation to the overall basic reproduction number for the habitat-based model (3.4)–(3.6), R0. IfR041, then it is likely that the disease persists in the reservoir and spillover populations. The reproduction numbers can be calculated using the next generation matrix approach (van den Driessche and Watmough, 2002). For the general system (3.4)–(3.6), it is possible to show that the basic reproduction number is a positive root of a fourth degree polynomial but it is difficult to obtain a simple analytical expression for R0. The simplifying assumption di ¼ 0 ¼ gi ; i ¼ a; b; ð4:1Þ leads to an explicit expression for R0 (shown below). This explicit expression is a close approximation to the overall basic reproduction number, if the time spent in the boundary is short relative to the time spent in each of the disease states. This expression is very useful in interpreting the contributions to disease outbreaks by the reservoir and the spillover species and in making comparisons to other reproduction numbers. Assume condition (4.1) holds. First, the reproduction number for the reservoir species (assuming the spillover species is not present) is R r 0 ¼ poKrðbIdrbr þ bPdrgr ÞþpiKaðba1drbr þ ba2drgr Þ : poðdr þ brÞðgr þ brÞbr Second, the reproduction number for the spillover species (assuming the reservoir species is not present) is R s 0 ¼ poKsb Ads þ p iK bb b3ds poðds þ bsÞðg s þ bsÞ : If there are no interspecies interactions so that p i ¼ 0 ¼ po, then Ka ¼ 0 ¼ K b. Each of the reproduction numbers simplifies to well-known reproduction numbers for SEIP or SEAR models (3.1) or (3.3), respectively. In this case, it is straightforward to calculate the enzootic equilibrium for the reservoir host, Sr ¼ Kr R r ; Er ¼ brKr dr þ br 1 1 R r ; Ir ¼ dr g r þ br Author's personal copy ARTICLE IN PRESS Er;P r ¼ gr Ir; ð4:2Þ br whenever the reproduction number for the SEIP model (3.1) is R r ¼ KrðbIdrbr þ bPdrgr Þ 41: ðdr þ brÞðgr þ brÞbr L.J.S. **Allen** et al. / Journal of Theoretical Biology 260 (2009) 510–522 At equilibrium, the proportion of animals that are RNA- or antibody-positive, ðIr þ P rÞ=Kr, is dr 1 1 R r : ð4:3Þ dr þ br To derive an expression for the basic reproduction number for the habitat-based model when (4.1) holds, we first define an expression R c 0 which depends on interspecies or crossover transmission. That is, let the intraspecies transmission parameters be zero, bI ¼ bP ¼ bA ¼ 0 and ba1 ¼ ba2 ¼ bb3 ¼ 0, and the interspecies transmission parameters, bb1 , bb2 , and ba3 , be nonzero. The reproduction number for interspecies pathogen transmission is defined as pidsba3Ka poðgs þ bsÞðds þ bsÞ : R c 0 ¼ p idrK bðb b1br þ b b2g r Þ poðdr þ brÞðg r þ brÞbr Note that R c 0 depends on the ratio p i=po directly and indirectly through the carrying capacities in the overlap region, K b and Ka. The preceding definition can be used to define the basic reproduction number for the habitat-based model (3.4)–(3.6): qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ; þ : ð4:4Þ R0 ¼ 1 2 Rr 0 þ Rs 0 ðR r 0 Rs 0 Þ2 þ 4R c 0 (Derivation of this formula is given in the Appendix.) It follows that R0ZmaxfR r 0 ; Rs0 g; interspecies pathogen transmission increases the basic reproduction number. A similar relationship was shown in a multi-species SI model of McCormack and **Allen** (2007). The local stability of the DFE follows directly from the results of van den Driessche and Watmough (2002). Global stability of the DFE when R0o1 and condition (4.1) holds can be verified by construction of a Liapunov function. The full system (3.4)–(3.6) consists of 16 differential equations which makes it difficult to find an explicit closed form solution for an enzootic equilibrium (EE). However, existence and uniqueness of a positive EE can be verified when R041 and condition (4.1) holds. It is shown, in the Appendix, that the EE for the full system (3.4)–(3.6) is a fixed point of Er ¼ f ðEr; EsÞ and Es ¼ gðEr; EsÞ. Then the existence of a unique positive EE follows by applying a theorem (Hethcote and Thieme, 1985) on existence and uniqueness of a positive fixed point. The following theorem summarizes the preceding results. Theorem 4.1. A basic reproduction number R0 exists for system (3.4)–(3.6) such that if R0o1, the DFE is locally asymptotically stable. If condition (4.1) holds for system (3.4)–(3.6), then (i) R0 has the form given in (4.4), (ii) if R0o1, then the DFE is globally asymptotically stable, and (iii) if R041, then the DFE is unstable and there exists a unique positive enzootic equilibrium. 5. Numerical examples Selection of parameters values is based on estimates from the literature for hantavirus (d i and g i , i ¼ r; s) and on trapping and demographic data for the reservoir species A. montensis and for the spillover species N. lasiurus or O. delator (b i, K i, i ¼ r; s and equilibrium ratios). The reservoir species A. montensis and one spillover species (N. lasiurus) are widely distributed in many of our study sites sampled in **Paraguay**, whereas the other spillover species (O. delator) is less widespread and generally less abundant. We choose carrying capacities of Kr ¼ 100 and Ks ¼ 50 for the reservoir and spillover species in their respective habitats.

Although the values for Kr and Ks are not known, the selected values are close to the estimates for minimal number known alive based on data from the trapping regions. The basic time unit in the model is one year. We assume total number of births per female per year that survive to the adult reproductive stage is six for the reservoir and the spillover species (several litters per year). Assuming an equal sex ratio, for the male population the number of males that survive to reproductive age is br ¼ 3 ¼ bs. Population growth is assumed to satisfy a logistic growth assumption so that for the reservoir and spillover species, drðNrÞ ¼brNr=Kr and dsðNsÞ ¼bsNs=Ks; so that drðKrÞ ¼br and dsðKsÞ ¼bs. We assume an average duration of two weeks for the latent period E and for the spillover infectious stage A, and an average duration of three months for the highly infectious stage for the reservoir species (Bernshtein et al., 1999; Lee et al., 1981; Padula et al., 2004). Hence, dr ¼ 26 ¼ ds, g s ¼ 26, and g r ¼ 4, e.g., 1=26 year two weeks. In addition, da ¼ dr, d b ¼ ds, g a ¼ g r , and g b ¼ g s . Animals enter the boundary region several times per year and stay only a short time. The average length of time in the boundary region is less than the average length of time for the latent period or acute infectious period, 1=por1=d i and 1=por1=g i , i ¼ a; b. In the numerical examples, we let p i ¼ 8 and po ¼ 52 which means, on average, each animal may make eight visits per year to the boundary region, spending about one week in the boundary region. The probability there is a transition from an exposed to an infectious state while in the boundary region is 1/3 (see Eq. (3.7)). Even Table 1 Basic parameter values for the ODE and the CTMC models for the reservoir and the spillover species. Reservoir parameter Value Spillover parameter Value Kr 100 Ks 50 br 3 bs 3 dr 26 ds 26 gr 4 gs 26 da ga 26 4 db gb 26 26 bI 0.075 bA 0.025 bP 0.025 bb3 0.025 ba1 0.075 bb1 0.15 ba2 0.025 0.05 bb2 0.05 b a3 Reservoir Species 30 25 20 15 10 5 P r I r Author's personal copy ARTICLE IN PRESS L.J.S. **Allen** et al. / Journal of Theoretical Biology 260 (2009) 510–522 517 0 0 1 2 3 4 Year though this probability is not small, the basic reproduction number given by (4.4) is a good approximation to the overall basic reproduction number for our parameter values (shown below). The parameter values are reasonable but are chosen for illustrative purposes (a range of values, p i 2½2; 25Š and po 2½26; 364Š, are considered later in this section). These parameter choices give population densities in the boundary region of Ka 15 and K b 8. The transmission parameters b j cannot be estimated directly. Instead, we make some reasonable assumptions about their relationship to disease transmission in the infectious stages, b I and b P . The product b I Kr is the number of infectious contacts that result in infection by a highly infectious reservoir animal per year (at equilibrium). Based on the summary data for proportion of animals RNA- or antibody-positive, 0.25 at site R3B, if we equate formula (4.3) to 0.25 and let br ¼ 3 and dr ¼ 26, this leads to R r ¼ 1:39 (when p i ¼ 0 ¼ po). Thus, the value of b I is chosen so that R r 0 (which is close to Rr ) is between one and two. We assume that the highly infectious stage of the reservoir host (RNA-positive and/or antibody-positive) is three times as infectious as the persistently infectious stage (only antibody-positive), i.e., b I ¼ 3b P (Bernshtein et al., 1999; Lee et al., 1981; Padula et al., 2004). In addition, we assume the transmissibility of the pathogen in the acute infectious stage A of the spillover host is the same as for the persistent stage in the reservoir host, b A ¼ b P. This leads to R s 0 o1. In the boundary region, intraspecific transmissibility remains the same as in the preferred habitats, but interspecies transmissibility is doubled due to aggressive encounters. In particular, b a1 ¼ b I; b a2 ¼ b P; b b3 ¼ b A; ð5:1Þ b b1 ¼ 2b I; b b2 ¼ 2b P; b a3 ¼ 2b A: ð5:2Þ The basic parameter values are given in Table 1. If (4.1) holds and the remaining parameter values are as in Table 1 with p i ¼ 8 and po ¼ 52, we obtain R c 0 o2 10 4 , so that . The approximate reproduction numbers based on the analysis in Section 4 are R r 0 ¼ 1:42; Rs0 ¼ 0:04; and R0 ¼ 1:42: Reservoir Species (Bdry) R0 R r 0 The overall basic reproduction number for the parameters in Table 1 is R0 ¼ 1:38 which is close to the approximation 1.42. The disease persists in the habitat-based model. For the parameter values in Table 1, one sample path of the CTMC model and the solution to the ODE model are graphed for the two infectious stages of the reservoir species (see Fig. 4). Although the pathogen persists, the infection in the spillover population is very low (straight line is the ODE equilibrium value); only sporadic infection occurs in the sample path for the spillover 10 8 6 4 2 P a I a 0 0 1 2 3 4 Fig. 4. Solution to the ODE model (straight lines) and one sample path of the CTMC model (highly variable curves) for the reservoir species in its preferred habitat (Ir and Pr) and in the overlap region (Ia and Pa). The parameter values are given in Table 1 with p i ¼ 8 and po ¼ 52: Initial values are at the equilibrium values given in (4.2), rounded to the nearest integer. Year

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