Understanding the link between malaria risk and climate

Paaijmans, Krijn P.; Read, Andrew F.; Thomas, Matthew B.

doi:10.1073/pnas.0903423106

Cited by 384 publications

(409 citation statements)

References 63 publications

(75 reference statements)

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“…Numerous mathematical models have been designed and used to assess the impact of climate change and seasonality on the transmission dynamics of mosquito-borne diseases, such as malaria (Agusto et al 2015;Ebi et al 2005;Jaenisch and Patz 2002;Mordecai et al 2012;Paaijmans et al 2009), dengue (Chen et al 2010;Hales et al 2002;Pham et al 2011;Wu et al 2009;Yang et al 2011), chikungunya (Fischer et al 2013;Meason and Paterson 2014) and WNv (Abdelrazec et al 2015;Wang et al 2011). For instance, such models allow for the determination of parameters, or variables, that influences the life-cycle of the mosquitoes (Ahumada et al 2004;Cailly et al 2012;Tran et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Mathematical assessment of the role of temperature and rainfall on mosquito population dynamics

Abdelrazec

Gumel

2016

J. Math. Biol.

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A new stage-structured model for the population dynamics of the mosquito (a major vector for numerous vector-borne diseases), which takes the form of a deterministic system of non-autonomous nonlinear differential equations, is designed and used to study the effect of variability in temperature and rainfall on mosquito abundance in a community. Two functional forms of eggs oviposition rate, namely the Verhulst-Pearl logistic and Maynard-Smith-Slatkin functions, are used. Rigorous analysis of the autonomous version of the model shows that, for any of the oviposition functions considered, the trivial equilibrium of the model is locally-and globally-asymptotically stable if a certain vectorial threshold quantity is less than unity. Conditions for the existence and global asymptotic stability of the non-trivial equilibrium solutions of the model are also derived. The model is shown to undergo a Hopf bifurcation under certain conditions (and that increased density-dependent competition in larval mortality reduces the likelihood of such bifurcation). The analyses reveal that the Maynard-Smith-Slatkin oviposition function sustains more oscillations than the Verhulst-Pearl logistic function (hence, it is more suited, from ecological viewpoint, for modeling the egg oviposition process). The non-autonomous model is shown to have a globally-asymptotically stable trivial periodic solution, for each of the oviposition functions, when the associated reproduction threshold is less than unity. Furthermore, this model, in the absence of density-dependent mortality rate for larvae, has a unique and globally-asymptotically stable periodic solution under certain conditions. Numerical simulations of the non-autonomous model, using mosquito surveillance and weather data from the Peel region of Ontario, Canada, show a peak mosquito abundance for temperature and rainfall values in the range [20−25] • C and [15-35] mm, respectively. These ranges are recorded in the Peel region between July and August (hence, this study suggests that anti-mosquito control effects should be intensified during this period).

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Section: Introductionmentioning

confidence: 99%

Mathematical assessment of the role of temperature and rainfall on mosquito population dynamics

Abdelrazec

Gumel

2016

J. Math. Biol.

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“…Inclusion of these temperatures in analyses including constant treatments only does not change the results (not shown). Incidence of host extinction was measured as the proportion of times the host population, arcsine square-root transformed, was found to be extinct across the four main sampling days (6,13,20,27) of the experiment. Analyses investigating host extinction excluded populations in constant environments as extinctions were only observed in constant environments of 358C.…”

Section: (D) Statistical Analysis (I) Host Populationsmentioning

confidence: 99%

“…This was achieved by taking the residuals over the entire dataset from a generalized linear model with a binomial error structure, with extinction as the response variable and number of Paramecium from which extinction was estimated (number on slide) as the explanatory variable. Mean residual extinction was calculated across the four main sampling days (6,13,20,27) of the experiment. We then took the mean of the residuals across sampling days 6, 13, 20 and 27 as a measure of extinction.…”

Section: (D) Statistical Analysis (I) Host Populationsmentioning

confidence: 99%

“…This work highlights that both differences in mean and variance are important to consider when trying to understand how variation in environment influences the behaviour of natural systems. Recent theoretical analyses of Plasmodium dynamics [13] and a single generation study of its development in mosquitoes [23] advocate strongly that environmental variation is a key determinant for parasite epidemiology. However, experimental demonstration of the influence of a variable versus constant environment for long-term host -parasite dynamics is not yet established.…”

Section: Introductionmentioning

confidence: 99%

“…owing to tolerance of certain organisms to frost. The inclusion of temporal environmental variation in epidemiological models has proved critical for accurate retrospective prediction of epidemics in the field [13] and for describing factors that influence spatial and temporal differences in parasite prevalence [14 -16]. Even limited exposure to a stressful environment can modify host resistance traits [17 -19] and experimental studies on non-parasite systems show that population dynamics are strongly influenced by fluctuation between permissive and restrictive environmental states [20 -22].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Temporal variation in temperature determines disease spread and maintenance inParameciummicrocosm populations

2011

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The environment is rarely constant and organisms are exposed to temporal and spatial variations that impact their life histories and inter-species interactions. It is important to understand how such variations affect epidemiological dynamics in host-parasite systems. We explored effects of temporal variation in temperature on experimental microcosm populations of the ciliate Paramecium caudatum and its bacterial parasite Holospora undulata. Infected and uninfected populations of two P. caudatum genotypes were created and four constant temperature treatments (268C, 288C, 308C and 328C) compared with four variable treatments with the same mean temperatures. Variable temperature treatments were achieved by alternating populations between permissive (238C) and restrictive (358C) conditions daily over 30 days. Variable conditions and high temperatures caused greater declines in Paramecium populations, greater fluctuations in population size and higher incidence of extinction. The additional effect of parasite infection was additive and enhanced the negative effects of the variable environment and higher temperatures by up to 50 per cent. The variable environment and high temperatures also caused a decrease in parasite prevalence (up to 40%) and an increase in extinction (absence of detection) (up to 30%). The host genotypes responded similarly to the different environmental stresses and their effect on parasite traits were generally in the same direction. This work provides, to our knowledge, the first experimental demonstration that epidemiological dynamics are influenced by environmental variation. We also emphasize the need to consider environmental variance, as well as means, when trying to understand, or predict population dynamics or range.

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Environmental Determinants of Malaria Transmission Around the Koka Reservoir in Ethiopia

Endo

Eltahir

2018

GeoHealth

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New dam construction is known to exacerbate malaria transmission in Africa as the vectors of malaria—Anopheles mosquitoes—use bodies of water as breeding sites. Precise environmental mechanisms of how reservoirs exacerbate malaria transmission are yet to be identified. Understanding of these mechanisms should lead to a better assessment of the impacts of dam construction and to new prevention strategies. Combining extensive multiyear field surveys around the Koka Reservoir in Ethiopia and rigorous model development and simulation studies, environmental mechanisms of malaria transmission around the reservoir were examined. Most comprehensive and detailed malaria transmission model, Hydrology, Entomology, and Malaria Transmission Simulator, was applied to a village adjacent to the reservoir. Significant contributions to the dynamics of malaria transmission are shaped by wind profile, marginal pools, temperature, and shoreline locations. Wind speed and wind direction influence Anopheles populations and malaria transmission during the major and secondary mosquito seasons. During the secondary mosquito season, a noticeable influence was also attributed to marginal pools. Temperature was found to play an important role, not so much in Anopheles population dynamics, but in malaria transmission dynamics. Change in shoreline locations drives malaria transmission dynamics, with closer shoreline locations to the village making malaria transmission more likely. Identified environmental mechanisms help in predicting malaria transmission seasons and in developing village relocation strategies upon dam construction to minimize the risk of malaria.

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Understanding the link between malaria risk and climate

Cited by 384 publications

References 63 publications

Mathematical assessment of the role of temperature and rainfall on mosquito population dynamics

Mathematical assessment of the role of temperature and rainfall on mosquito population dynamics

Temporal variation in temperature determines disease spread and maintenance inParameciummicrocosm populations

Environmental Determinants of Malaria Transmission Around the Koka Reservoir in Ethiopia

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