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. 2006 May;43(3):623-30.
doi: 10.1603/0022-2585(2006)43[623:rbhvav]2.0.co;2.

Relationships between host viremia and vector susceptibility for arboviruses

Cynthia C Lord  1 , C Roxanne Rutledge, Walter J Tabachnick
Affiliations

Relationships between host viremia and vector susceptibility for arboviruses

Cynthia C Lord et al. J Med Entomol. 2006 May.

Abstract

Using a threshold model where a minimum level of host viremia is necessary to infect vectors affects our assessment of the relative importance of different host species in the transmission and spread of these pathogens. Other models may be more accurate descriptions of the relationship between host viremia and vector infection. Under the threshold model, the intensity and duration of the viremia above the threshold level is critical in determining the potential numbers of infected mosquitoes. A probabilistic model relating host viremia to the probability distribution of virions in the mosquito bloodmeal shows that the threshold model will underestimate the significance of hosts with low viremias. A probabilistic model that includes avian mortality shows that the maximum number of mosquitoes is infected by feeding on hosts whose viremia peaks just below the lethal level. The relationship between host viremia and vector infection is complex, and there is little experimental information to determine the most accurate model for different arthropod-vector-host systems. Until there is more information, the ability to distinguish the relative importance of different hosts in infecting vectors will remain problematic. Relying on assumptions with little support may result in erroneous conclusions about the importance of different hosts.

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Figures

Fig. 1
Fig. 1
Possible shapes for the relationship between host viremia and the probability of infection of a mosquito. Solid line, threshold; see equation 1 in the text, with vT = 5 (log PFU/ml). Dashed line, sigmoidal; see equation 9 in the text. Dotted line, exponential; P(inf) = exp(−0.4v). Parameter values were chosen simply for illustration to demonstrate some possible shapes for the relationship.
Fig. 2
Fig. 2
Theoretical distributions of virions per bloodmeal and the resulting probability of infection. (a) Normal probability distribution with mean z̄ and standard deviation √z; see equation in the text. (b) Probability of infection given the distribution in (a) and the number of virions required to infect a mosquito; the full equation is given in the text.
Fig. 3
Fig. 3
Probabilistic model with bird mortality. (a) Viremia over time. Three possible patterns are shown, designated by the theoretical peak viremia, vp. See text for equations. Species 1, vp = 5; species 2, vp = 8; species 3, vp = 10. In all cases, the birds die when v ≥8. (b) Probability of mosquito infection at different viremias. This curve is based on the model shown in Fig. 2b but is formulated mathematically using equation 9 in the text for convenience. (c) Probability of mosquito infection over the time course of bird viremia.
Fig. 4
Fig. 4
Results from model I. (a) Number of infected mosquitoes produced from one infected bird assuming that the duration of infectiousness increases with the level of viremia. The surface shows the number of infected mosquitoes given different levels of constant viremia in the host and different thresholds required for mosquito infection. (b) The same surface but when the duration of infectiousness decreases with the level of viremia. See text for details and equations.
Fig. 5
Fig. 5
Results from model II. If a threshold model (dotted line) is assumed, but the true curve follows model II, the number of infected mosquitoes produced will be underestimated (the area under each curve to the left of the dotted line). This underestimate increases when fewer virions are required to infect a mosquito or if the threshold under model I is assumed to be higher.
Fig. 6
Fig. 6
Results from model III. The maximum number of infected mosquitoes is produced when the theoretical peak viremia is just below the lethal level.
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