dynamAedes: a unified modelling framework for invasive Aedes mosquitoes

Re, Daniele Da; Bortel, Wim Van; Reuss, Friederike; Müller, Ruth; Boyer, Sébastien; Montarsi, Fabrizio; Ciocchetta, Silvia; Arnoldi, Daniele; Marini, Giancarlo; Rizzoli, Annapaola; L’Ambert, Grégory; Lacour, Guillaume; Koenraadt, Constantianus J. M.; Vanwambeke, Sophie; Marcantonio, Matteo

doi:10.1186/s13071-022-05414-4

Cited by 11 publications

(11 citation statements)

References 130 publications

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“…This is likely due to the fact that during the rainy season, BG-GAT has to compete with the large number of larval breeding habitats present in the study localities, as shown by Wat'senga et al [12]. In Kinshasa, temperature is not a limiting factor in the development of both Aedes species [18], although temperature and humidity play critical roles in the population dynamics of both species by impacting Aedes mortality and, hence, pathogen transmission [19]. The differences in densities between the dry and rainy seasons seem to be the result of the rainfall and the presence of water-containing larval habitats.…”

Section: Discussionmentioning

confidence: 75%

“…Larval source management is one of the key interventions, whereas adult Aedes control strategies are primarily considered for outbreak control. However, the epidemiological impact of adult vector control is uncertain (see e.g., [18]). In Kinshasa, adult vector control methods should target mosquitoes outdoors due to the marked exophagic and exophilic behavior of the two vector species Ae.…”

Section: Discussionmentioning

confidence: 99%

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Behavior of Adult Aedes aegypti and Aedes albopictus in Kinshasa, DRC, and the Implications for Control

et al. 2023

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Yellow fever and chikungunya outbreaks—and a few dengue cases—have been reported in the Democratic Republic of the Congo (DRC) in recent years. However, little is known about the ecology and behavior of the adult disease vector species, Aedes aegypti and Aedes albopictus, in DRC. Preliminary studies showed important differences in Aedes behavior in DRC and Latin-American sites. Therefore, this study aimed to assess the host-seeking and resting behaviors of female Ae. aegypti and Ae. albopictus, and their densities in four communes of Kinshasa (Kalamu, Lingwala, Mont Ngafula and Ndjili). Two cross-sectional surveys were carried out, one in the dry season (July 2019) and one in the rainy season (February 2020). We used three different adult vector collection methods: BG-Sentinel 2, BG-GAT, and prokopack. Both Aedes species were clearly exophagic, exophilic, and sought breeding sites outdoors. The adult house index for Ae. aegypti exceeded 55% in all communes except Lingwala, where it was only 27%. The Adult Breteau Index (ABI) for Ae. aegypti was 190.77 mosquitoes per 100 houses inspected in the rainy season and 6.03 in the dry season. For Ae. albopictus, the ABI was 11.79 and 3.52 in the rainy and dry seasons, respectively. Aedes aegypti showed unimodal host-seeking activity between 6 h and 21 h. The exophagic and exophilic behaviors of both species point to the need to target adult mosquitoes outdoors when implementing vector control.

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Section: Discussionmentioning

confidence: 75%

Section: Discussionmentioning

confidence: 99%

Behavior of Adult Aedes aegypti and Aedes albopictus in Kinshasa, DRC, and the Implications for Control

et al. 2023

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“…Unlike correlative models, process-based models are usually independent of geographical observations of the taxa under investigation. These typically express biological (or other) processes by a mathematical equation (e.g., ordinal differential equation or matrix population models) relating an indicator of the process (e.g., a lifehistory trait such as the number of offspring) to different factors affecting its performance (e.g., environmental conditions) (Da Re et al, 2022;Kearney et al, 2010). For instance, Larter et al (2017) showed how a single plant functional trait (xylem resistance to cavitation) displayed a strong statistical relationship with its species distribution in relation to aridity across the climatic range of the species.…”

Section: Discussionmentioning

confidence: 99%

Towards causal relationships for modelling species distribution

Da Re,

Tordoni,

Lenoir

et al. 2023

Journal of Biogeography

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AimUnderstanding the processes underlying the distribution of species through space and time is fundamental in several research fields spanning from ecology to spatial epidemiology. Correlative species distribution models rely on the niche concept to infer or explain the distribution of species, though often focusing only on the abiotic component of the niche (e.g. temperature, precipitation), without clear causal links to the biology of the species under investigation. This might result in an oversimplification of the complex niche hypervolume, resulting in a single model formula whose estimates and predictions lack ecological realism.LocationNot applicable.Time PeriodNot applicable.Major Taxa StudiedVirtual species.Materials and MethodsWe believe that a causal perspective associated with a finer definition of the modelling target is necessary to develop more ecologically realistic outputs. Here, we propose to infer the geographical distribution of a species by applying the modelling relation approach, a causal conceptual framework developed by the theoretical biologist Robert Rosen, which can be formalized through structural equation modelling.ResultsOur findings suggest that building a model relying on a strong conceptual basis improves the stability of the estimated model's coefficients, without necessarily increasing the predictive accuracy metrics of the model.Main ConclusionsIncluding causal processes underlying the spatial distribution of species into an inferential formal system highlights the methodological steps where uncertainty can arise and results in model outputs which are tightly linked to the ecology of the target species.

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“…Unlike correlative models, process-based models are usually independent of geographical observations of the taxa under investigation. These typically express biological (or other) processes by a mathematical equation (e.g., ordinal differential equation or matrix population models) relating an indicator of the process (e.g., a life history trait such as the number of offsprings) to different factors affecting its performance (e.g., environmental conditions) (Kearney et al, 2010;Da Re et al, 2022). For instance, Larter et al (2017) showed how a single plant functional trait (xylem resistance to cavitation) displayed a strong statistical relationship with its species distribution in relation to aridity across the climatic range of the species.…”

Section: Discussionmentioning

confidence: 99%

Towards causal relationships for modelling species distribution

Da Re,

Tordoni,

Lenoir

et al. 2023

Preprint

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1. Understanding the processes underlying the distribution of species through space and time is fundamental in several research fields spanning from ecology to spatial epidemiology. Correlative species distribution models (SDMs) involve popular statistical tools to infer species geographical distribution thanks to spatiotemporally explicit observations of species occurrences coupled with a set of environmental predictors. 2. So-called SDMs rely on the niche concept to infer or explain the distribution of species, though often focusing only on the abiotic component of the niche (e.g., temperature, precipitation), without clear causal links to the biology of species under investigation. This might result in an over-simplification of the complex niche hypervolume, resulting in a single model formula whose estimates and predictions lack ecological realism. 3. We believe that a causal perspective associated with a finer definition of the modelling target is necessary to develop ecologically more realistic outputs. Here, we propose to infer the geographical distribution of a species by applying the modelling relation approach, a causal conceptual framework developed by the theoretical biologist Robert Rosen, which can be formalized through structural equation modelling (SEM). 4. Implementing the modelling relation into SDMs would improve the inclusion of the causal processes underlying the spatial distribution of species into an inferential formal system, potentially highlighting the methodological steps where uncertainty arises and eventually resulting in model outputs which are tightly linked to the ecology of the target species.

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dynamAedes: a unified modelling framework for invasive Aedes mosquitoes

Cited by 11 publications

References 130 publications

Behavior of Adult Aedes aegypti and Aedes albopictus in Kinshasa, DRC, and the Implications for Control

Behavior of Adult Aedes aegypti and Aedes albopictus in Kinshasa, DRC, and the Implications for Control

Towards causal relationships for modelling species distribution

Towards causal relationships for modelling species distribution

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