Abstract
Insecticide spraying of housing units is an important control measure for vector-borne infections such as Chagas disease. As vectors may invade both from other infested houses and sylvatic areas and as the effectiveness of insecticide wears off over time, the dynamics of (re)infestations can be approximated by \({ SIRS}\)-type models with a reservoir, where housing units are treated as hosts, and insecticide spraying corresponds to removal of hosts. Here, we investigate three ODE-based models of this type. We describe a dual-rate effect where an initially very high spraying rate can push the system into a region of the state space with low endemic levels of infestation that can be maintained in the long run at relatively moderate cost, while in the absence of an aggressive initial intervention the same average cost would only allow a much less significant reduction in long-term infestation levels. We determine some sufficient and some necessary conditions under which this effect occurs and show that it is robust in models that incorporate some heterogeneity in the relevant properties of housing units.
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Notes
We use the term “reservoir” here for a source of (re)infestation of susceptible domestic units at a fixed rate. To avoid possible confusion with the use of the term “animal reservoir” in studies of human infection by disease agents, we will write “(sylvatic) reservoir.”
It was in fact called a “hysteresis-like effect” in Oduro (2016).
Here “strictly” has a different meaning than in Definition 3.1, and in the multidimensional case “monotone” needs to be interpreted as “monotone in each variable.”
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Acknowledgements
We are greatly indebted to former Ohio University student William Clark for helping us with preliminary simulations and pointing out the strange shape of the curves for the cost at equilibrium level that led to this study of the dual-rate effect. We also thank Sofia Ocaña-Mayorga, Anita G. Villacis, and Cesar Yumiseva of the Center for Research on Health in Latin America (CISeAL) for sharing valuable insights on Chagas disease transmission. Special thanks are due to the referees and the editor for valuable comments. They greatly helped us in improving the manuscript and pointed us to promising directions of future research. This work received financial support to MG from Pontifical Catholic University of Ecuador (K13063 and L13254) http://www.puce.edu.ec, Children’s Heartlink USA http://www.childrensheartlink.org/ Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health (DMID/NIADID/NIH) [AI077896-01] and Fogarty International Center, Global Infectious Disease Training Grant (TW008261-01A1).
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Appendix
Appendix
1.1 Calculating \(I^*\) for the Basic Model with \(c > 0\)
At an equilibrium,
From the second line, we have
Substituting (29) into the first line of (28) and simplifying give a quadratic equation:
The only solution of (30) with \(I^* \ge 0\) is:
1.2 Proof of Inequality (22)
For \(r_1=\frac{w(\beta m-c)}{w+c}\), we have \(\frac{wm}{w+r_1}-\frac{r_1w}{\beta (w+r_1)}-\frac{c}{\beta } = 0\).
Recall that
Let \(T(r)=\frac{wm}{w+r}-\frac{rw}{\beta (w+r)}-\frac{c}{\beta }\) and \(P(r)=\frac{wcm}{\beta (w+r)}\). Then,
Now,
We have
From (31), we obtain
so that
Therefore, in view of (32),
Replace \(r_1\) by \(\frac{w(\beta m-c)}{w+c}\) and let
Notice that for positive \(\beta , c, m, w\) the following inequalities are all equivalent:
Thus, \(A > 0\) if, and only if, \(m > \frac{c}{\beta }\).
Also,
It follows that
Now, it suffices to show that when m is sufficiently large relative to the ratio \(\frac{c}{\beta }\), the inequality
holds so that
In order to prove (33), it suffices to find some constant \(B> 0\) such that \(A \ge B\) for all sufficiently large m.
Here, we will show that
for all \(m\ge \frac{c}{\beta }+1=\frac{c+\beta }{\beta }\).
For the first inequality in (34), notice that the following are all equivalent for any \(\beta , w, c\ge 0\):
For the second inequality in (34), assume \(\frac{c}{\beta }+1\le m\). Then,
and the result follows by taking square roots of both sides and subtracting \(\frac{c}{\beta }\).
1.3 Proof of Theorem 3.6
Assume \(\gamma =\frac{c}{\beta }\). Then,
We show that for \(\gamma > m\) and any \(r_2 > r_1 \ge 0\):
By substituting the last line of (35) into the right-hand side of (36), canceling the positive factor 2mw and cross multiplying with the positive denominators, we see that it suffices to show
Canceling some common terms gives
After rearranging terms, we obtain
If \(\gamma > m\), the first term in the square brackets is nonnegative. Next, we will show that
Consider the following expression, which is always positive for \(r_2>r_1\):
By expanding the products inside each of the main factors in the first line of (38) and rearranging terms, we obtain:
By rewriting the first two lines of (39) as a difference of two squares and factoring out some terms in the third, we obtain
Now, (37) follows from (40) by moving the negative terms to the right and taking square roots.
1.4 The Cost Function Increases When \(\beta = 0\)
When we set \(\beta = 0\) in the basic model, we obtain a system of linear DEs
At equilibrium,
Substitute \(R^{*}=\frac{rI^{*}}{w}\) into the first line of (41) and solve for \(I^{*}\) to get
Thus, we can estimate the derivative of the cost function as follows:
1.5 Proof of Proposition 3.8(a)
We consider any function of the form
where \(c, d > 0\) are constants such that
The first derivative of f wrt h behaves as follows:
Let us calculate the second derivative of f wrt h.
The last inequality follows from (43).
Thus, \(f'(0) > 0\) and \(f'\) decreases throughout \([0, \infty )\). Now, it follows from the last part of (44) that \(f'(h) > 0\) throughout \([0, \infty )\). Proposition 3.8(a) follows by observing that the function \(\frac{I^*(r_i, c_i)}{2\beta _{ii}}\) is of the form (42) with
so that (43) holds.
1.6 Proof of Proposition 3.8(c)
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Oduro, B., Grijalva, M.J. & Just, W. Models of Disease Vector Control: When Can Aggressive Initial Intervention Lower Long-Term Cost?. Bull Math Biol 80, 788–824 (2018). https://doi.org/10.1007/s11538-018-0401-y
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DOI: https://doi.org/10.1007/s11538-018-0401-y