Biology subjects

Simard, F.

Publications and source records attributed to Simard, F..

8 recordsLinked to original sources

bioRxiv2026

Aedes vittatus in Haiti: continued expansion across the Caribbean and implications for the Americas

BackgroundAedes vittatus, an emerging invasive species and arboviral vector with high ecological plasticity and dispersal capacity, is expanding in the Caribbean, being detected in the Dominican Republic, Cuba, and Jamaica and recently in Yucatan, Mexico. ObjectivesThis study aimed to provide evidence of the establishment of Ae. vittatus in Haiti. MethodsLarval surveys were done across 12 localities around Cap-Haitien, in the North-East department of Haiti, the specimens were identified morphologically and confirmed by COI DNA barcoding. FindingsWe report, for the first time, the detection of the invasive vector Aedes (Fredwardsius) vittatus in Haiti, confirmed morphologically and molecularly, and being established in half of the municipalities sampled. Phylogenetic analyses group Haitian specimens with Caribbean and American populations, closely related to Mexico, indicating regional expansion. Main conclusionGiven its role as a vector of chikungunya, dengue, Zika and yellow fever, strengthened entomological surveillance and early detection in North America and the Caribbean are urgently needed.

ecology↗

bioRxiv2025

Green cities and the risk for vector-borne disease transmission for humans and animals: a scoping review

BackgroundGreening cities is a nature-based strategy for sustainable urban development that integrates natural elements like plants or water bodies, to mitigate climate change impacts and enhance human well-being. However, urban green infrastructures (UGIs) can influence the distribution of disease vectors, potentially affecting vector-borne diseases (VBDs). UGIs may provide new suitable environments for urban vectors, while also creating opportunities to mitigate VBD risks through predation, competition, and dilution effects. This article examined the relationships between UGIs, vectors, and associated pathogens, impacting both human and animal health, highlighting knowledge gaps and identifying research priorities to support VBD risk mitigation measures and to guide smart urban planning and design. MethodsA systematic literature search was conducted following PRISMA guidelines in three databases (Pubmed, Scopus, Web of Science). Selected articles involved (i) any aspect of a urban vector system, (ii) in UGIs, and (iii) statistical analysis of the effects of UGIs on VBD risk. Methods employed to characterize UGIs and VBDs were described and the identified impacts were summarized by vector group. ResultsAmong the 98 articles reviewed, most addressed mosquito-pathogen systems (66), tick-pathogen systems (29), and few other vector-borne pathogen systems (3), with studies often confined to a single city or several cities within the same country and focused on one vector group. Urban vegetation generally appeared to heighten the risk of tick-borne diseases. In contrast, the influence of UGIs on the risk of mosquito-borne diseases varied depending on the vector system and on the environmental and climatic context. The diversity of indicators used to assess UGIs and VBD risks may affect the observed impact on VBD risk. ConclusionGiven the increasing popularity of urban greening, it is crucial to investigate its potential implications for public health, and thereby urban planning decisions. However, the lack of standardized protocols complicates the accurate assessment of the effects of UGIs on the risk for VBD emergence and transmission and consequently, on potential mitigation measures.

ecology↗

bioRxiv2022

Insecticide resistance and biting behaviour of malaria vectors in rural West-Africa : a data mining study to adress their fine-scale spatiotemporal heterogeneity, drivers, and predictability

AO_SCPLOWBSTRACTC_SCPLOWInsecticide resistance and behavioural adaptation of malaria mosquitoes affect the efficacy of long-lasting insecticide nets - currently the main tool for malaria vector control. To develop and deploy complementary, efficient and cost-effective control interventions, a good understanding of the drivers of these physiological and behavioural traits is needed. In this data-mining exercise, we modelled a set of indicators of physiological resistance to insecticide (prevalence of three target-site mutations) and behavioural resistance phenotypes (early- and late-biting, exophagy) of anopheles mosquitoes in two rural areas of West-Africa, located in Burkina Faso and Cote dIvoire. To this aim, we used mosquito field collections along with heterogeneous, multi-source and multi-scale environmental data. The objectives were i) to assess the small-scale spatial and temporal heterogeneity of physiological resistance to insecticide and behavioural resistance phenotypes, ii) to better understand their drivers, and iii) to assess their spatio-temporal predictability, at scales that are consistent with operational action. The explanatory variables covered a wide range of potential environmental determinants of vector resistance to insecticide or behavioural resistance phenotypes : vector control, human availability and nocturnal behaviour, macro and micro-climatic conditions, landscape, etc. The resulting models revealed many statistically significant associations, although their predictive powers were overall weak. We interpreted and discussed these associations in light of several topics of interest, such as : respective contribution of public health and agriculture in the selection of physiological resistances, biological costs associated with physiological resistances, biological mechanisms underlying biting behaviour, and impact of micro-climatic conditions on the time or place of biting. To our knowledge, our work is the first modeling insecticide resistance and feeding behaviour of malaria vectors at such fine spatial scale with such a large dataset of both mosquito and environmental data.

ecology↗

bioRxiv2021

Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso

BackgroundImproving the knowledge and understanding of the environmental determinants of malaria vectors abundances at fine spatiotemporal scales is essential to design locally tailored vector control intervention. This work aimed at exploring the environmental tenets of human-biting activity in the main malaria vectors (Anopheles gambiae s.s., Anopheles coluzzii and Anopheles funestus) in the health district of Diebougou, rural Burkina Faso. MethodsAnopheles human-biting activity was monitored in 27 villages during 15 months (in 2017-2018), and environmental variables (meteorological and landscape) were extracted from high resolution satellite imagery. A two-step data-driven modeling study was then carried-out. Correlation coefficients between the biting rates of each vector species and the environmental variables taken at various temporal lags and spatial distances from the biting events were first calculated. Then, multivariate machine-learning models were generated and interpreted to i) pinpoint primary and secondary environmental drivers of variation in the biting rates of each species and ii) identify complex associations between the environmental conditions and the biting rates. ResultsMeteorological and landscape variables were often significantly correlated with the vectors biting rates. Many nonlinear associations and thresholds were unveiled by the multivariate models, both for meteorological and landscape variables. From these results, several aspects of the bio-ecology of the main malaria vectors were precised or hypothesized for the Diebougou area, including breeding sites typologies, development and survival rates in relation to weather, flight ranges from breeding sites, dispersal related to landscape openness. ConclusionsUsing high resolution data in an interpretable machine-learning modeling framework proved to be an efficient way to enhance the knowledge of the complex links between the environment and the malaria vectors at a local scale. More broadly, the emerging field of interpretable machine-learning has significant potential to help improving our understanding of the complex processes leading to malaria transmission.

ecology↗

bioRxiv2018

A new species in the Anopheles gambiae complex reveals new evolutionary relationships between vector and non-vector species

Complexes of closely related species provide key insights about the rapid and independent evolution of adaptive traits. Here, we described and studied a presumably new species in the Anopheles gambiae complex, Anopheles fontenillei, recently discovered in the forested areas of Gabon, Central Africa. Our analysis placed the new taxon in the phylogenetic tree of the An. gambiae complex, revealing important introgression events with other members of the complex. In particular, we detected recent introgression with An. gambiae and An. coluzzii of genes directly involved in vectorial capacity. Moreover, genome analysis of the new species also allowed us to resolve the evolutionary history of inversion 3La. Overall, Anopheles fontenillei has implemented our understanding about the relationship of species within the gambiaecomplex and provides insight into the evolution of vectorial capacity traits, relevant for the successful control of malaria in Africa.

evolutionary biology↗

bioRxiv2018

Natural Wolbachia infections are common in the major malaria vectors in Central Africa

During the last decade, the endosymbiont bacterium Wolbachia has emerged as a biological tool for vector disease control. However, for long time, it was believed that Wolbachia was absent in natural populations of Anopheles. The recent discovery that species within the Anopheles gambiae complex hosts Wolbachia in natural conditions has opened new opportunities for malaria control research in Africa. Here, we investigated the prevalence and diversity of Wolbachia infection in 25 African Anopheles species in Gabon (Central Africa). Our results revealed the presence of Wolbachia in 16 of these species, including the major malaria vectors in this area. The infection prevalence varied greatly among species, confirming that sample size is a key factor to detect the infection. Moreover, our sequencing and phylogenetic analyses showed the important diversity of Wolbachia strains that infect Anopheles. Co-evolutionary analysis unveiled patterns of Wolbachia transmission within Anopheles species, suggesting that past independent acquisition events were followed by co-cladogenesis. The large diversity of Wolbachia strains that infect natural populations of Anopheles offers a promising opportunity to select suitable phenotypes for suppressing Plasmodium transmission and/or manipulating Anopheles reproduction, which in turn could be used to reduce the malaria burden in Africa.

ecology↗

bioRxiv2017

Field evidence for manipulation of mosquito host selection by the human malaria parasite, Plasmodium falciparum

Whether the malaria parasite Plasmodium falciparum can manipulate mosquito host choice in ways that enhance parasite transmission toward humans is unknown. We assessed the influence of P. falciparum on the blood-feeding behaviour of three of its major vectors (Anopheles coluzzii, An. gambiae and An. arabiensis) in Burkina Faso. Host preference assays using odour-baited traps revealed no effect of infection on mosquito long-range anthropophily. However, the identification of the blood meal origin of mosquitoes showed that females carrying sporozoites, the mature transmissible stage of the parasite, displayed a 24% increase in anthropophagy compared to both females harbouring oocysts, the parasite immature stage, and uninfected individuals. Using a mathematical model, we further showed that this increased anthropophagy in infectious females resulted in a > 250% increase in parasite transmission potential, everything else being equal. This important epidemiological consequence highlights the importance of vector control tools targeting infectious females.

evolutionary biology↗

bioRxiv2017

Can malaria parasites manipulate the odour-mediated host preference of their mosquito vectors?

Malaria parasites can manipulate mosquito feeding behaviours such as motivation and avidity to feed on vertebrate hosts in ways that increase parasite transmission. However, in natural conditions, not all vertebrate blood-sources are suitable hosts for the parasite. Whether malaria parasites can manipulate mosquito host choice in ways that enhance parasite transmission toward suitable hosts and/or reduce mosquito attraction to unsuitable hosts (i.e. specific manipulation) is unknown. To address this question, we experimentally infected three species of mosquito vectors (Anopheles coluzzii, Anopheles gambiae, and Anopheles arabiensis) with wild isolates of the human malaria parasite Plasmodium falciparum, and examined the effects of immature (oocyst) and mature (sporozoite) infections on mosquito behavioural responses (activation rate and odour choice) to combinations of calf odour, human odour and outdoor air using a dual-port olfactometer. Regardless of parasite developmental stage and mosquito species, P. falciparum infection did not alter mosquito activation rate or their choice for human odours. The overall expression pattern of host choice of all three mosquito species was consistent with a high degree of anthropophily, with both infected and uninfected individuals showing higher attraction toward human odour over calf odour, human odour over outdoor air, and outdoor air over calf odour. Our results suggests that, in this system, the parasite may not be able to manipulate the early long-range behavioural steps involved in the mosquito host-feeding process, including initiation of host-seeking and host orientation. Future studies examining mosquito host-feeding behaviours at a shorter range (i.e. the \"at-host\" foraging activities) are required to test whether malaria parasites can modify their mosquito host choice to enhance transmission toward suitable hosts and/or reduce biting on unsuitable hosts.

evolutionary biology↗