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Determination of the processes driving the acquisition of immunity to malaria using a mathematical transmission model.

Filipe JA, Riley EM, Drakeley CJ, Sutherland CJ, Ghani AC - PLoS Comput. Biol. (2007)

Bottom Line: The results were compared to age patterns of parasite prevalence and clinical disease in endemic settings in northeastern Tanzania and The Gambia.Two types of immune function were required to reproduce the epidemiological age-prevalence curves seen in the empirical data; a form of clinical immunity that reduces susceptibility to clinical disease and develops with age and exposure (with half-life of the order of five years or more) and a form of anti-parasite immunity which results in more rapid clearance of parasitaemia, is acquired later in life and is longer lasting (half-life of >20 y).The development of anti-parasite immunity better reproduced observed epidemiological patterns if it was dominated by age-dependent physiological processes rather than by the magnitude of exposure (provided some exposure occurs).

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.

ABSTRACT
Acquisition of partially protective immunity is a dominant feature of the epidemiology of malaria among exposed individuals. The processes that determine the acquisition of immunity to clinical disease and to asymptomatic carriage of malaria parasites are poorly understood, in part because of a lack of validated immunological markers of protection. Using mathematical models, we seek to better understand the processes that determine observed epidemiological patterns. We have developed an age-structured mathematical model of malaria transmission in which acquired immunity can act in three ways ("immunity functions"): reducing the probability of clinical disease, speeding the clearance of parasites, and increasing tolerance to subpatent infections. Each immunity function was allowed to vary in efficacy depending on both age and malaria transmission intensity. The results were compared to age patterns of parasite prevalence and clinical disease in endemic settings in northeastern Tanzania and The Gambia. Two types of immune function were required to reproduce the epidemiological age-prevalence curves seen in the empirical data; a form of clinical immunity that reduces susceptibility to clinical disease and develops with age and exposure (with half-life of the order of five years or more) and a form of anti-parasite immunity which results in more rapid clearance of parasitaemia, is acquired later in life and is longer lasting (half-life of >20 y). The development of anti-parasite immunity better reproduced observed epidemiological patterns if it was dominated by age-dependent physiological processes rather than by the magnitude of exposure (provided some exposure occurs). Tolerance to subpatent infections was not required to explain the empirical data. The model comprising immunity to clinical disease which develops early in life and is exposure-dependent, and anti-parasite immunity which develops later in life and is not dependent on the magnitude of exposure, appears to best reproduce the pattern of parasite prevalence and clinical disease by age in different malaria transmission settings. Understanding the effector mechanisms underlying these two immune functions will assist in the design of transmission-reducing interventions against malaria.

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Schematic Illustration of the Full Transmission Model for Humans and Mosquitoes (without Explicit Ageing in Humans)States are shown in circles, and subscripts denote the population (H = humans, M = mosquitoes): susceptible SH/SM, latent infection EH/EM, infected with symptomatic disease (severe and clinical cases) DH, asymptomatic patent infection AH, infected with undetectable (subpatent) parasite density UH, infectious mosquitoes IM. ΛH /ΛM is the force of infection on the human and mosquito populations, respectively, 1/h is the mean latent period in humans, 1/g the mean latent period in mosquitoes, φ is the proportion of human infections that develop disease, f the proportion of symptomatic cases that receive effective drug treatment, rT the rate of recovery on treatment, rD the rate of recovery without treatment, rA the rate at which asymptomatic infections become subpatent, and rU the rate at which subpatent infections are cleared. The coloured circles denote the stages at which acquired immunity can have an effect (modifying φ, rA, and rU). The parameters and their values are described in Table 1.
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pcbi-0030255-g006: Schematic Illustration of the Full Transmission Model for Humans and Mosquitoes (without Explicit Ageing in Humans)States are shown in circles, and subscripts denote the population (H = humans, M = mosquitoes): susceptible SH/SM, latent infection EH/EM, infected with symptomatic disease (severe and clinical cases) DH, asymptomatic patent infection AH, infected with undetectable (subpatent) parasite density UH, infectious mosquitoes IM. ΛH /ΛM is the force of infection on the human and mosquito populations, respectively, 1/h is the mean latent period in humans, 1/g the mean latent period in mosquitoes, φ is the proportion of human infections that develop disease, f the proportion of symptomatic cases that receive effective drug treatment, rT the rate of recovery on treatment, rD the rate of recovery without treatment, rA the rate at which asymptomatic infections become subpatent, and rU the rate at which subpatent infections are cleared. The coloured circles denote the stages at which acquired immunity can have an effect (modifying φ, rA, and rU). The parameters and their values are described in Table 1.

Mentions: We model a human population with continuous age structure in which individuals of a given age can be in one of the following states: susceptible or not infected (SH), latent infection (EH), infected with symptomatic disease (including severe and clinical cases) (DH), asymptomatic with detectable parasites (AH), and asymptomatic infection with undetectable (subpatent) parasite density (UH). The main distinction between states DH and AH is that individuals in state AH do not prompt treatment that leads to a change in infection state. The state UH is included to account for the fact that measured parasitemia often decays with age, while highly sensitive parasite detection techniques suggest parasitemia continues increasing with age nearing 100% in highly endemic areas [37]. In tandem, we consider a mosquito population whose individuals can be susceptible (SM), exposed (latent) (EM), or infectious (IM). Figure 6 shows the transitions between states in each population (without displaying ageing). Susceptible humans move to latent infection at rate Λ, the force of infection on the human population. Individuals remain in this state for a mean duration 1/h (the mean latent period). A proportion φ develop disease whilst the remainder (1−φ) move to the asymptomatic infection category. A proportion f of symptomatic cases (DH) receive effective drug treatment and recover at rate rT, while the remaining cases recover naturally without treatment at rate rD. If clinical treatment or natural recovery is fully successful at removing parasites (with probability φ), the host returns to the susceptible state and otherwise moves to the asymptomatic state. Asymptomatic infections become subpatent at rate rA, and these subpatent infections are cleared at rate rU with individuals returning to the susceptible state. Those in the asymptomatic state may additionally develop disease through superinfection at rate φΛ. Each human infection state, namely DH, AH, and UH, has a specific level of infectivity (transmission of mature gametocytes) to biting mosquitoes. The full equations for this model and further parameter definitions are given in Protocol S1.


Determination of the processes driving the acquisition of immunity to malaria using a mathematical transmission model.

Filipe JA, Riley EM, Drakeley CJ, Sutherland CJ, Ghani AC - PLoS Comput. Biol. (2007)

Schematic Illustration of the Full Transmission Model for Humans and Mosquitoes (without Explicit Ageing in Humans)States are shown in circles, and subscripts denote the population (H = humans, M = mosquitoes): susceptible SH/SM, latent infection EH/EM, infected with symptomatic disease (severe and clinical cases) DH, asymptomatic patent infection AH, infected with undetectable (subpatent) parasite density UH, infectious mosquitoes IM. ΛH /ΛM is the force of infection on the human and mosquito populations, respectively, 1/h is the mean latent period in humans, 1/g the mean latent period in mosquitoes, φ is the proportion of human infections that develop disease, f the proportion of symptomatic cases that receive effective drug treatment, rT the rate of recovery on treatment, rD the rate of recovery without treatment, rA the rate at which asymptomatic infections become subpatent, and rU the rate at which subpatent infections are cleared. The coloured circles denote the stages at which acquired immunity can have an effect (modifying φ, rA, and rU). The parameters and their values are described in Table 1.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2230683&req=5

pcbi-0030255-g006: Schematic Illustration of the Full Transmission Model for Humans and Mosquitoes (without Explicit Ageing in Humans)States are shown in circles, and subscripts denote the population (H = humans, M = mosquitoes): susceptible SH/SM, latent infection EH/EM, infected with symptomatic disease (severe and clinical cases) DH, asymptomatic patent infection AH, infected with undetectable (subpatent) parasite density UH, infectious mosquitoes IM. ΛH /ΛM is the force of infection on the human and mosquito populations, respectively, 1/h is the mean latent period in humans, 1/g the mean latent period in mosquitoes, φ is the proportion of human infections that develop disease, f the proportion of symptomatic cases that receive effective drug treatment, rT the rate of recovery on treatment, rD the rate of recovery without treatment, rA the rate at which asymptomatic infections become subpatent, and rU the rate at which subpatent infections are cleared. The coloured circles denote the stages at which acquired immunity can have an effect (modifying φ, rA, and rU). The parameters and their values are described in Table 1.
Mentions: We model a human population with continuous age structure in which individuals of a given age can be in one of the following states: susceptible or not infected (SH), latent infection (EH), infected with symptomatic disease (including severe and clinical cases) (DH), asymptomatic with detectable parasites (AH), and asymptomatic infection with undetectable (subpatent) parasite density (UH). The main distinction between states DH and AH is that individuals in state AH do not prompt treatment that leads to a change in infection state. The state UH is included to account for the fact that measured parasitemia often decays with age, while highly sensitive parasite detection techniques suggest parasitemia continues increasing with age nearing 100% in highly endemic areas [37]. In tandem, we consider a mosquito population whose individuals can be susceptible (SM), exposed (latent) (EM), or infectious (IM). Figure 6 shows the transitions between states in each population (without displaying ageing). Susceptible humans move to latent infection at rate Λ, the force of infection on the human population. Individuals remain in this state for a mean duration 1/h (the mean latent period). A proportion φ develop disease whilst the remainder (1−φ) move to the asymptomatic infection category. A proportion f of symptomatic cases (DH) receive effective drug treatment and recover at rate rT, while the remaining cases recover naturally without treatment at rate rD. If clinical treatment or natural recovery is fully successful at removing parasites (with probability φ), the host returns to the susceptible state and otherwise moves to the asymptomatic state. Asymptomatic infections become subpatent at rate rA, and these subpatent infections are cleared at rate rU with individuals returning to the susceptible state. Those in the asymptomatic state may additionally develop disease through superinfection at rate φΛ. Each human infection state, namely DH, AH, and UH, has a specific level of infectivity (transmission of mature gametocytes) to biting mosquitoes. The full equations for this model and further parameter definitions are given in Protocol S1.

Bottom Line: The results were compared to age patterns of parasite prevalence and clinical disease in endemic settings in northeastern Tanzania and The Gambia.Two types of immune function were required to reproduce the epidemiological age-prevalence curves seen in the empirical data; a form of clinical immunity that reduces susceptibility to clinical disease and develops with age and exposure (with half-life of the order of five years or more) and a form of anti-parasite immunity which results in more rapid clearance of parasitaemia, is acquired later in life and is longer lasting (half-life of >20 y).The development of anti-parasite immunity better reproduced observed epidemiological patterns if it was dominated by age-dependent physiological processes rather than by the magnitude of exposure (provided some exposure occurs).

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.

ABSTRACT
Acquisition of partially protective immunity is a dominant feature of the epidemiology of malaria among exposed individuals. The processes that determine the acquisition of immunity to clinical disease and to asymptomatic carriage of malaria parasites are poorly understood, in part because of a lack of validated immunological markers of protection. Using mathematical models, we seek to better understand the processes that determine observed epidemiological patterns. We have developed an age-structured mathematical model of malaria transmission in which acquired immunity can act in three ways ("immunity functions"): reducing the probability of clinical disease, speeding the clearance of parasites, and increasing tolerance to subpatent infections. Each immunity function was allowed to vary in efficacy depending on both age and malaria transmission intensity. The results were compared to age patterns of parasite prevalence and clinical disease in endemic settings in northeastern Tanzania and The Gambia. Two types of immune function were required to reproduce the epidemiological age-prevalence curves seen in the empirical data; a form of clinical immunity that reduces susceptibility to clinical disease and develops with age and exposure (with half-life of the order of five years or more) and a form of anti-parasite immunity which results in more rapid clearance of parasitaemia, is acquired later in life and is longer lasting (half-life of >20 y). The development of anti-parasite immunity better reproduced observed epidemiological patterns if it was dominated by age-dependent physiological processes rather than by the magnitude of exposure (provided some exposure occurs). Tolerance to subpatent infections was not required to explain the empirical data. The model comprising immunity to clinical disease which develops early in life and is exposure-dependent, and anti-parasite immunity which develops later in life and is not dependent on the magnitude of exposure, appears to best reproduce the pattern of parasite prevalence and clinical disease by age in different malaria transmission settings. Understanding the effector mechanisms underlying these two immune functions will assist in the design of transmission-reducing interventions against malaria.

Show MeSH
Related in: MedlinePlus