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. 2014 Oct 30;8(10):e3288.
doi: 10.1371/journal.pntd.0003288. eCollection 2014 Oct.

Quantifying the contribution of hosts with different parasite concentrations to the transmission of visceral leishmaniasis in Ethiopia

Affiliations

Quantifying the contribution of hosts with different parasite concentrations to the transmission of visceral leishmaniasis in Ethiopia

Ezer Miller et al. PLoS Negl Trop Dis. .

Abstract

Background: An important factor influencing the transmission dynamics of vector-borne diseases is the contribution of hosts with different parasitemia (no. of parasites per ml of blood) to the infected vector population. Today, estimation of this contribution is often impractical since it relies exclusively on limited-scale xenodiagnostic or artificial feeding experiments (i.e., measuring the proportion of vectors that become infected after feeding on infected blood/host).

Methodology: We developed a novel mechanistic model that facilitates the quantification of the contribution of hosts with different parasitemias to the infection of the vectors from data on the distribution of these parasitemias within the host population. We applied the model to an ample data set of Leishmania donovani carriers, the causative agent of visceral leishmaniasis in Ethiopia.

Results: Calculations facilitated by the model quantified the host parasitemias that are mostly responsible for the infection of vector, the sand fly Phlebotomus orientalis. Our findings indicate that a 3.2% of the most infected people were responsible for the infection of between 53% and 79% (mean - 62%) of the infected sand fly vector population.

Significance: Our modeling framework can easily be extended to facilitate the calculation of the contribution of other host groups (such as different host species, hosts with different ages) to the infected vector population. Identifying the hosts that contribute most towards infection of the vectors is crucial for understanding the transmission dynamics, and planning targeted intervention policy of visceral leishmaniasis as well as other vector borne infectious diseases (e.g., West Nile Fever).

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. The infectiousness of blood with different parasite concentrations (parasitemias).
We fitted the model (equation 4) and logistic function (y = 1/(1+exp[-λ1−λ2x])) to two different VBD set of results by maximum likelihood estimation (Nelder-Mead method) of the model parameters λ1 and λ2. The error bars in the proportion of infected vectors (y axis) were calculated as 95% confidence intervals of the respective binomial distribution. The origin in both panels (marked in blue) was taken as a data point, since we assume that a vector cannot be infected by uninfected blood. In red – our model fit, in green – logistic regression (A) The fitting results to data on VL : our model: λ1 = 0.9037, λ2 = 3.58*10−4, logistic regression:λ1 = 0.9434, λ2 = 6.024*10−6 (B) The fitting results to data on Chikungunya : our model: λ1 = 0.8712, λ2 = 3.82*10−5, logistic regression: λ1 = 0.2505, λ2 = 3.0482*10−6. PFU = Plaque-Forming Unit. Note that our model fits all data points within their confidence intervals. However, the logistic function is unable to fit the data points either for low parasitemia values (since it is always different than zero, thus the origin never belongs to its image), or for high parasitemia values (since it always approaches 1 for x→∞, although certain proportion of vectors can never be infected [17], [18], [19]).
Figure 2
Figure 2. The contribution of asymptomatic carriers with different parasitemias to the infected sand fly population.
(A) Division of the infected human population into parasitemia categories. Bars represent the proportion of the different parasitemias among the total infected human population (N = 658). Due to a large sample size (N = 658), the errors were of the order of 1% and hence negligible. (B) The calculated proportions (according to equation 5) of infected sand flies (from all infected sand flies) that were infected by feeding on individuals belonging to different parasitemia categories. Grouped bars represent the proportions of flies infected by biting people that belong to a particular parasitemia category (X axis). Different colored bars represent the proportion of infected sand flies (from all infected sand flies) for three different values of the model parameters, λ1 and λ2: mean, and the two edges of their 95% confidence intervals (the confidence intervals were calculated by parametric bootstrapping on Figure 1A data). Note that for high estimations of λ1 and λ2 (and hence q(n)), the relative contribution of people with low parasitemias to the population of infected sand flies would be larger compared to the case of low λ1 and λ2 (i.e., low q(n)).

References

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