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Transmission intensity and drug resistance in malaria population dynamics: implications for climate change.

Artzy-Randrup Y, Alonso D, Pascual M - PLoS ONE (2010)

Bottom Line: We then address the implications of warmer temperatures in an East African highland, where, as in other similar regions at the altitudinal edge of malaria's distribution, there has been a pronounced increase of cases from the 1970s to the 1990s.Climate change and drug resistance can interact and need not be considered as alternative explanations for trends in disease incidence in this region.Non-monotonic patterns of treatment failure with transmission intensity similar to those described as the 'valley phenomenon' for Uganda can result from epidemiological dynamics but under poorly understood assumptions.

View Article: PubMed Central - PubMed

Affiliation: Howard Hughes Medical Institute, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America. YArtzy@umich.edu

ABSTRACT
Although the spread of drug resistance and the influence of climate change on malaria are most often considered separately, these factors have the potential to interact through altered levels of transmission intensity. The influence of transmission intensity on the evolution of drug resistance has been addressed in theoretical studies from a population genetics' perspective; less is known however on how epidemiological dynamics at the population level modulates this influence. We ask from a theoretical perspective, whether population dynamics can explain non-trivial, non-monotonic, patterns of treatment failure with transmission intensity, and, if so, under what conditions. We then address the implications of warmer temperatures in an East African highland, where, as in other similar regions at the altitudinal edge of malaria's distribution, there has been a pronounced increase of cases from the 1970s to the 1990s. Our theoretical analyses, with a transmission model that includes different levels of immunity, demonstrate that an increase in transmission beyond a threshold can lead to a decrease in drug resistance, as previously shown, but that a second threshold may occur and lead to the re-establishment of drug resistance. Estimates of the increase in transmission intensity from the 1970s to the 1990s for the Kenyan time series, obtained by fitting the two-stage version of the model with an explicit representation of vector dynamics, suggest that warmer temperatures are likely to have moved the system towards the first threshold, and in so doing, to have promoted the faster spread of drug resistance. Climate change and drug resistance can interact and need not be considered as alternative explanations for trends in disease incidence in this region. Non-monotonic patterns of treatment failure with transmission intensity similar to those described as the 'valley phenomenon' for Uganda can result from epidemiological dynamics but under poorly understood assumptions.

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Related in: MedlinePlus

Fraction of the population in the different immunity classes as a function of vectorial capacity for a simplified three class model (the x-axis is given in log scale).The orange line represents the fraction of hosts in class 1, the green line represents the fraction in class 2 and the blue line represents the fraction in class 3. For low levels of vectorial capacity the majority of the population is in the lowest immunity class, and as vectorial capacity increases, individuals in the population gain higher levels of immunity.
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pone-0013588-g002: Fraction of the population in the different immunity classes as a function of vectorial capacity for a simplified three class model (the x-axis is given in log scale).The orange line represents the fraction of hosts in class 1, the green line represents the fraction in class 2 and the blue line represents the fraction in class 3. For low levels of vectorial capacity the majority of the population is in the lowest immunity class, and as vectorial capacity increases, individuals in the population gain higher levels of immunity.

Mentions: Model simulations show that at high levels of transmission intensity, or vectorial capacity, the general prevalence of infection in the population is higher, and the distribution of individuals tends to be accumulated in the higher immunity classes (see Figure 2). As vectorial capacity increases, individuals are repeatedly bitten, which leads to higher rates of re-infection. The individuals that are rapidly re-infected will stay longer in an infected state. This leads individuals to gain higher levels of immunity, as well as insuring that the immunity they have gained is less likely to be lost. In return, larger fractions of the population exhibit milder clinical symptoms, and the relative drug use is generally lower. It is important to note that as the distribution of hosts leans towards the higher immunity classes, it is only the relative fraction of treated individuals which starts dropping, while the overall drug treatment in the population may continue to increase with the general rise in prevalence. This is in contrast to earlier notions that the decrease in drug pressure in high transmission areas is due to a general decrease in drug use and not a relative one [12], [38].


Transmission intensity and drug resistance in malaria population dynamics: implications for climate change.

Artzy-Randrup Y, Alonso D, Pascual M - PLoS ONE (2010)

Fraction of the population in the different immunity classes as a function of vectorial capacity for a simplified three class model (the x-axis is given in log scale).The orange line represents the fraction of hosts in class 1, the green line represents the fraction in class 2 and the blue line represents the fraction in class 3. For low levels of vectorial capacity the majority of the population is in the lowest immunity class, and as vectorial capacity increases, individuals in the population gain higher levels of immunity.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2965653&req=5

pone-0013588-g002: Fraction of the population in the different immunity classes as a function of vectorial capacity for a simplified three class model (the x-axis is given in log scale).The orange line represents the fraction of hosts in class 1, the green line represents the fraction in class 2 and the blue line represents the fraction in class 3. For low levels of vectorial capacity the majority of the population is in the lowest immunity class, and as vectorial capacity increases, individuals in the population gain higher levels of immunity.
Mentions: Model simulations show that at high levels of transmission intensity, or vectorial capacity, the general prevalence of infection in the population is higher, and the distribution of individuals tends to be accumulated in the higher immunity classes (see Figure 2). As vectorial capacity increases, individuals are repeatedly bitten, which leads to higher rates of re-infection. The individuals that are rapidly re-infected will stay longer in an infected state. This leads individuals to gain higher levels of immunity, as well as insuring that the immunity they have gained is less likely to be lost. In return, larger fractions of the population exhibit milder clinical symptoms, and the relative drug use is generally lower. It is important to note that as the distribution of hosts leans towards the higher immunity classes, it is only the relative fraction of treated individuals which starts dropping, while the overall drug treatment in the population may continue to increase with the general rise in prevalence. This is in contrast to earlier notions that the decrease in drug pressure in high transmission areas is due to a general decrease in drug use and not a relative one [12], [38].

Bottom Line: We then address the implications of warmer temperatures in an East African highland, where, as in other similar regions at the altitudinal edge of malaria's distribution, there has been a pronounced increase of cases from the 1970s to the 1990s.Climate change and drug resistance can interact and need not be considered as alternative explanations for trends in disease incidence in this region.Non-monotonic patterns of treatment failure with transmission intensity similar to those described as the 'valley phenomenon' for Uganda can result from epidemiological dynamics but under poorly understood assumptions.

View Article: PubMed Central - PubMed

Affiliation: Howard Hughes Medical Institute, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America. YArtzy@umich.edu

ABSTRACT
Although the spread of drug resistance and the influence of climate change on malaria are most often considered separately, these factors have the potential to interact through altered levels of transmission intensity. The influence of transmission intensity on the evolution of drug resistance has been addressed in theoretical studies from a population genetics' perspective; less is known however on how epidemiological dynamics at the population level modulates this influence. We ask from a theoretical perspective, whether population dynamics can explain non-trivial, non-monotonic, patterns of treatment failure with transmission intensity, and, if so, under what conditions. We then address the implications of warmer temperatures in an East African highland, where, as in other similar regions at the altitudinal edge of malaria's distribution, there has been a pronounced increase of cases from the 1970s to the 1990s. Our theoretical analyses, with a transmission model that includes different levels of immunity, demonstrate that an increase in transmission beyond a threshold can lead to a decrease in drug resistance, as previously shown, but that a second threshold may occur and lead to the re-establishment of drug resistance. Estimates of the increase in transmission intensity from the 1970s to the 1990s for the Kenyan time series, obtained by fitting the two-stage version of the model with an explicit representation of vector dynamics, suggest that warmer temperatures are likely to have moved the system towards the first threshold, and in so doing, to have promoted the faster spread of drug resistance. Climate change and drug resistance can interact and need not be considered as alternative explanations for trends in disease incidence in this region. Non-monotonic patterns of treatment failure with transmission intensity similar to those described as the 'valley phenomenon' for Uganda can result from epidemiological dynamics but under poorly understood assumptions.

Show MeSH
Related in: MedlinePlus