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

Miller E, Warburg A, Novikov I, Hailu A, Volf P, Seblova V, Huppert A - PLoS Negl Trop Dis (2014)

Bottom Line: 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.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).

View Article: PubMed Central - PubMed

Affiliation: The Kuvin Center for the Study of Infectious & Tropical Diseases, Department of Microbiology & Molecular Genetics, The Institute of Medical Research, Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel; The Biostatistics Unit, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel.

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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Related in: MedlinePlus

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)).
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pntd-0003288-g002: 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)).

Mentions: From a cohort of 4,695 volunteers, 86% were kDNA-PCR negative (i.e. without parasites, in their blood, n = 4,037) while 14% (n = 658) were kDNA PCR positive indicating the presence of Leishmania parasites in their blood, rendering them potentially infectious to biting sand flies. The distribution of parasite concentrations in the infected population (14%, n = 658) is presented in Figure 2A. Figure 2A indicates that most infected individuals had very low parasitemias (∼70% had between 1–10 parasites per ml, n = 458), while very few had high parasitemias (3.2% had above 1,000 parasites per ml, n = 21).


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

Miller E, Warburg A, Novikov I, Hailu A, Volf P, Seblova V, Huppert A - PLoS Negl Trop Dis (2014)

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)).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4214667&req=5

pntd-0003288-g002: 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)).
Mentions: From a cohort of 4,695 volunteers, 86% were kDNA-PCR negative (i.e. without parasites, in their blood, n = 4,037) while 14% (n = 658) were kDNA PCR positive indicating the presence of Leishmania parasites in their blood, rendering them potentially infectious to biting sand flies. The distribution of parasite concentrations in the infected population (14%, n = 658) is presented in Figure 2A. Figure 2A indicates that most infected individuals had very low parasitemias (∼70% had between 1–10 parasites per ml, n = 458), while very few had high parasitemias (3.2% had above 1,000 parasites per ml, n = 21).

Bottom Line: 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.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).

View Article: PubMed Central - PubMed

Affiliation: The Kuvin Center for the Study of Infectious & Tropical Diseases, Department of Microbiology & Molecular Genetics, The Institute of Medical Research, Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel; The Biostatistics Unit, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel.

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).

Show MeSH
Related in: MedlinePlus