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Co-infections determine patterns of mortality in a population exposed to parasite infection.

Woolhouse ME, Thumbi SM, Jennings A, Chase-Topping M, Callaby R, Kiara H, Oosthuizen MC, Mbole-Kariuki MN, Conradie I, Handel IG, Poole EJ, Njiiri E, Collins NE, Murray G, Tapio M, Auguet OT, Weir W, Morrison WI, Kruuk LE, Bronsvoort BM, Hanotte O, Coetzer K, Toye PG - Sci Adv (2015)

Bottom Line: Using infections with Theileria parva (a tick-borne protozoan, related to Plasmodium) in indigenous African cattle [where it causes East Coast fever (ECF)] as a model system, we obtain the first quantitative estimate of the effects of heterologous reactivity for any parasitic disease.In individual calves, concurrent co-infection with less pathogenic species of Theileria resulted in an 89% reduction in mortality associated with T. parva infection.Across our study population, this corresponds to a net reduction in mortality due to ECF of greater than 40%.

View Article: PubMed Central - PubMed

Affiliation: Centre for Immunity, Infection and Evolution, University of Edinburgh, Ashworth Laboratories, Kings Buildings, West Mains Road, Edinburgh EH9 3JT, UK.

ABSTRACT
Many individual hosts are infected with multiple parasite species, and this may increase or decrease the pathogenicity of the infections. This phenomenon is termed heterologous reactivity and is potentially an important determinant of both patterns of morbidity and mortality and of the impact of disease control measures at the population level. Using infections with Theileria parva (a tick-borne protozoan, related to Plasmodium) in indigenous African cattle [where it causes East Coast fever (ECF)] as a model system, we obtain the first quantitative estimate of the effects of heterologous reactivity for any parasitic disease. In individual calves, concurrent co-infection with less pathogenic species of Theileria resulted in an 89% reduction in mortality associated with T. parva infection. Across our study population, this corresponds to a net reduction in mortality due to ECF of greater than 40%. Using a mathematical model, we demonstrate that this degree of heterologous protection provides a unifying explanation for apparently disparate epidemiological patterns: variable disease-induced mortality rates, age-mortality profiles, weak correlations between the incidence of infection and disease (known as endemic stability), and poor efficacy of interventions that reduce exposure to multiple parasite species. These findings can be generalized to many other infectious diseases, including human malaria, and illustrate how co-infections can play a key role in determining population-level patterns of morbidity and mortality due to parasite infections.

No MeSH data available.


Related in: MedlinePlus

Sensitivity analysis of mathematical model.Sensitivity analysis of model-predicted, age-related changes in the case fatality rate (CF) for different values of the force of infection with LPT (ΛL) and the rate of clearance of LPT infections (σL). ΛL and σL are varied as indicated, baseline and other parameter values as in Table 3, and high ΛL indicates 2× the baseline and low σL corresponds to a value of zero. CF is constant with age in the absence of heterologous protection by LPT.
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Figure 4: Sensitivity analysis of mathematical model.Sensitivity analysis of model-predicted, age-related changes in the case fatality rate (CF) for different values of the force of infection with LPT (ΛL) and the rate of clearance of LPT infections (σL). ΛL and σL are varied as indicated, baseline and other parameter values as in Table 3, and high ΛL indicates 2× the baseline and low σL corresponds to a value of zero. CF is constant with age in the absence of heterologous protection by LPT.

Mentions: Consistent with the field data (Fig. 2A), the model predicts a constant value for the rate of infection with T. parva, but marked age-related decreases in both CF and CL (Fig. 2B), more so if the force of infection with LPT (ΛL) is high and/or if the rate of clearance of LPT infections (σL) is low (Fig. 4). In the absence of heterologous protection, the model predicts constant CF and CL with age (Fig. 4).


Co-infections determine patterns of mortality in a population exposed to parasite infection.

Woolhouse ME, Thumbi SM, Jennings A, Chase-Topping M, Callaby R, Kiara H, Oosthuizen MC, Mbole-Kariuki MN, Conradie I, Handel IG, Poole EJ, Njiiri E, Collins NE, Murray G, Tapio M, Auguet OT, Weir W, Morrison WI, Kruuk LE, Bronsvoort BM, Hanotte O, Coetzer K, Toye PG - Sci Adv (2015)

Sensitivity analysis of mathematical model.Sensitivity analysis of model-predicted, age-related changes in the case fatality rate (CF) for different values of the force of infection with LPT (ΛL) and the rate of clearance of LPT infections (σL). ΛL and σL are varied as indicated, baseline and other parameter values as in Table 3, and high ΛL indicates 2× the baseline and low σL corresponds to a value of zero. CF is constant with age in the absence of heterologous protection by LPT.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4643819&req=5

Figure 4: Sensitivity analysis of mathematical model.Sensitivity analysis of model-predicted, age-related changes in the case fatality rate (CF) for different values of the force of infection with LPT (ΛL) and the rate of clearance of LPT infections (σL). ΛL and σL are varied as indicated, baseline and other parameter values as in Table 3, and high ΛL indicates 2× the baseline and low σL corresponds to a value of zero. CF is constant with age in the absence of heterologous protection by LPT.
Mentions: Consistent with the field data (Fig. 2A), the model predicts a constant value for the rate of infection with T. parva, but marked age-related decreases in both CF and CL (Fig. 2B), more so if the force of infection with LPT (ΛL) is high and/or if the rate of clearance of LPT infections (σL) is low (Fig. 4). In the absence of heterologous protection, the model predicts constant CF and CL with age (Fig. 4).

Bottom Line: Using infections with Theileria parva (a tick-borne protozoan, related to Plasmodium) in indigenous African cattle [where it causes East Coast fever (ECF)] as a model system, we obtain the first quantitative estimate of the effects of heterologous reactivity for any parasitic disease.In individual calves, concurrent co-infection with less pathogenic species of Theileria resulted in an 89% reduction in mortality associated with T. parva infection.Across our study population, this corresponds to a net reduction in mortality due to ECF of greater than 40%.

View Article: PubMed Central - PubMed

Affiliation: Centre for Immunity, Infection and Evolution, University of Edinburgh, Ashworth Laboratories, Kings Buildings, West Mains Road, Edinburgh EH9 3JT, UK.

ABSTRACT
Many individual hosts are infected with multiple parasite species, and this may increase or decrease the pathogenicity of the infections. This phenomenon is termed heterologous reactivity and is potentially an important determinant of both patterns of morbidity and mortality and of the impact of disease control measures at the population level. Using infections with Theileria parva (a tick-borne protozoan, related to Plasmodium) in indigenous African cattle [where it causes East Coast fever (ECF)] as a model system, we obtain the first quantitative estimate of the effects of heterologous reactivity for any parasitic disease. In individual calves, concurrent co-infection with less pathogenic species of Theileria resulted in an 89% reduction in mortality associated with T. parva infection. Across our study population, this corresponds to a net reduction in mortality due to ECF of greater than 40%. Using a mathematical model, we demonstrate that this degree of heterologous protection provides a unifying explanation for apparently disparate epidemiological patterns: variable disease-induced mortality rates, age-mortality profiles, weak correlations between the incidence of infection and disease (known as endemic stability), and poor efficacy of interventions that reduce exposure to multiple parasite species. These findings can be generalized to many other infectious diseases, including human malaria, and illustrate how co-infections can play a key role in determining population-level patterns of morbidity and mortality due to parasite infections.

No MeSH data available.


Related in: MedlinePlus