The effect of temperature on mosquito population dynamics of Aedes aegypti: The primary vector of dengue

Hamdan, Nur ’Izzati; Kılıçman, Adem

doi:10.1063/5.0018084

Cited by 4 publications

(6 citation statements)

References 12 publications

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“…For 20˚C, 35˚C, and the temperatures of the three United States cities of interest, these values were estimated from figures. For mosquito lifespan (1/μ v ), we compiled temperature lifespan data on A. aegypti from various studies at temperatures greater than or equal to 15˚C [38][39][40]. We then fit generalized linear models to the data, using the four distributions explored by [14], namely, lognormal, gamma, Weibull, and exponential (see S1 Table for more details).…”

Section: Plos Climatementioning

confidence: 99%

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Changing temperature profiles and the risk of dengue outbreaks

et al. 2023

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As temperatures change worldwide, the pattern and competency of disease vectors will change, altering the global distribution of both the burden of infectious disease and the risk of the emergence of those diseases into new regions. To evaluate the risk of potential summer dengue outbreaks triggered by infected travelers under various climate scenarios, we develop an SEIR-type model, run numerical simulations, and conduct sensitivity analyses under a range of temperature profiles. Our model extends existing theoretical frameworks for studying dengue dynamics by introducing temperature dependence of two key parameters: the mosquito extrinsic incubation period and the lifespan of mosquitoes, which empirical data suggests are both highly temperature dependent. We find that changing temperature significantly alters dengue risk in an inverted U-shape, with temperatures in the range 27-31°C producing the highest risk. As temperatures increase beyond 31°C, the determinants of dengue risk begin to shift from mosquito biting rate and carrying capacity to the duration of the human infectious period, suggesting that changing temperatures not only alter dengue risk but also the potential efficacy of control measures. To illustrate the role of spatial and temporal temperature heterogeneity, we select five US cities where the primary dengue vector, the mosquito Aedes aegypti, has been observed, and which have had dengue cases in the past: Los Angeles, Houston, Miami, Brownsville, and Phoenix. Our analysis suggests that an increase of 3°C leads to an approximate doubling of the risk of dengue in Los Angeles and Houston, but a reduction of risk in Miami, Brownsville, and Phoenix due to extreme heat.

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Section: Plos Climatementioning

confidence: 99%

“…. Model equations for mosquito lifespan over time. Data (points) from [38][39][40]. Models are of the form Link(y) = α 0 + β 1 temperature + β 2 temperature 2 + β 3 temperature 3 .…”

Section: Plos Climatementioning

confidence: 99%

Changing temperature profiles and the risk of dengue outbreaks

et al. 2023

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“…El grupo de variables de precipitaciones pueden hacer caer o elevar la variable Conteo cuando se desestabiliza Tau, si el cambio en precipitaciones es positivo esto ayuda a seguir continuando el ciclo de vida del mosquito para beneficiar la etapa acuática del mosquito, se multiplican los criaderos y tiene el efecto de aumentar Conteo localmente. De igual modo, las variables relacionadas con energía cinética atmosférica o temperatura hacen que el sistema de mosquitos de la ZE se desestabilice si la temperatura ambiental aumenta, esto crea las condiciones propicias que necesita el mosquito para continuar, a veces de forma acelerada (Hamdan & Kilicman, 2020;Johansson et al, 2009;Wu et al, 2009) , su ciclo de vida.…”

Section: Homogeneidad De La Varianza: Prueba De Fligner-killeenunclassified

Dinámica espaciotemporal de la población del mosquito Aedes aegypti (L.) en la zona del Caño Martín Peña en San Juan de Puerto Rico durante los años epidemiológicos 2018–2019; repercusiones a la salud para los residentes de las comunidades aledañas

Padilla-Villanueva¹

2022

Preprint

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The population dynamical system of Ae. aegypti in the premises around the Caño Martín Peña water body was studied (San Juan). Data from 2018 and 2019 were used to count gravid female Ae. aegypti mosquitoes in the study area to determine the seasonality of the vector populations, search for hot and persistent spots, and quantify the risk for arboviral disease outbreak posed to public health inside the study zone. Bayesian statistics provided by a GIS program were used to detect spatiotemporal relationships and develop risk maps for arboviral diseases. A generalized linear regression model controlling for heteroscedasticity was generated to describe the dependent variable versus different meteorological explanatory variables. It was found that the Ae. aegypti population system in the study area behaved persistently and very stably (marginally statistically significant, p < .10), with higher mosquito densities over more densely populated residential areas with less efficient sanitary sewerage. Rising ambient temperature interacts with the dependent variable, making its value higher (p < .001). It is concluded that the State/society should act immediately in the study region to mitigate the present problem of unusually high density of Ae. aegypti mosquitoes, which is currently causing cases of arboviral diseases (p < .01). The use of chaos theory is also encouraged to complement the entomological findings obtained using linear equations and non-linear techniques. In addition, we propose the use of the systemic dependent variable Systemic Tau, a surrogate variable of the dependent variable Count/EpiWeek or fractal variable, to study the population system of Aedes sp. mosquitoes in the ZE at the level of phase space or from the chaos theory.

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“…Various models have been developed to assess the impact of seasonality in environmental conditions on the transmission dynamics of mosquito-borne diseases such as malaria [23, 14] and dengue [17, 24, 20, 25]. Some of these models have delved into mosquito population dynamics under seasonal weather conditions using ordinary differential equation formulations [26, 21, 13, 27, 12] or delay-differential equation systems [28, 29].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Impact of Seasonality on Mosquito Population Dynamics: Insights for Vector Control Strategies

Baafi,

Hurford

2024

Preprint

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Mosquitoes are important vectors for the transmission of some major infectious diseases of humans, i.e., malaria, dengue, West Nile Virus and Zika virus. The burden of these diseases is different for different regions, being highest in tropical and subtropical areas, which have high annual rainfall, warm temperatures, and less pronounced seasonality. The life cycle of mosquitoes consists of four distinct stages: eggs, larvae, pupae, and adults. These life stages have different mortality rates and only adults can reproduce. Seasonal weather may affect the population dynamics of mosquitoes, and the relative abundance of different mosquito stages. We developed a stage-structured model that considers laboratory experiments describing how temperature and rainfall affects the reproduction, maturation and survival of different Anopheles mosquito stages, the species that transmits the parasite that causes malaria. We consider seasonal temperature and rainfall patterns and describe the stage-structured population dynamics of the Anopheles mosquito in Ain Mahbel, Algeria, Cape Town, South Africa, Nairobi, Kenya and Kumasi, Ghana. We find that neglecting seasonality leads to significant overestimation or underestimation of mosquito abundance. We find that depending on the region, mosquito abundance: peaks one, two or four times a year, periods of low abundance are predicted to occur for durations ranging from six months (Ain Mahbel) to not at all (Nairobi); and seasonal patterns of relative abundance of stages are substantially different. The region with warmer temperatures and higher rainfall across the year, Kumasi, Ghana, is predicted to have higher mosquito abundance, which is broadly consistent with reported malaria deaths relative to the other countries considered by our study. Our analysis reveals distinct patterns in mosquito abundance across different months and regions. Control strategies often target one specific life stage, for example, applying larvicides to kill mosquito larvae, or spraying insecticides to kill adult mosquitoes. Our findings suggest that differences in seasonal weather affect mosquito stage structure, and that the best approaches to vector control may differ between regions in timing, duration, and efficacy.

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The effect of temperature on mosquito population dynamics of Aedes aegypti: The primary vector of dengue

Cited by 4 publications

References 12 publications

Changing temperature profiles and the risk of dengue outbreaks

Changing temperature profiles and the risk of dengue outbreaks

Dinámica espaciotemporal de la población del mosquito Aedes aegypti (L.) en la zona del Caño Martín Peña en San Juan de Puerto Rico durante los años epidemiológicos 2018–2019; repercusiones a la salud para los residentes de las comunidades aledañas

Modeling the Impact of Seasonality on Mosquito Population Dynamics: Insights for Vector Control Strategies

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