Literature DB >> 17853610

Modeling and biological control of mosquitoes.

Cynthia C Lord1.   

Abstract

Models can be useful at many different levels when considering complex issues such as biological control of mosquitoes. At an early stage, exploratory models are valuable in exploring the characteristics of an ideal biological control agent and for guidance in data collection. When more data are available, models can be used to explore alternative control strategies and the likelihood of success. There are few modeling studies that explicitly consider biological control in mosquitoes; however, there have been many theoretical studies of biological control in other insect systems and of mosquitoes and mosquito-borne diseases in general. Examples are used here to illustrate important aspects of designing, using and interpreting models. The stability properties of a model are valuable in assessing the potential of a biological control agent, but may not be relevant to a mosquito population with frequent environmental perturbations. The time scale and goal of proposed control strategies are important considerations when analyzing a model. The underlying biology of the mosquito host and the biological control agent must be carefully considered when deciding what to include in a model. Factors such as density dependent population growth in the host, the searching efficiency and aggregation of a natural enemy, and the resource base of both have been shown to influence the stability and dynamics of the interaction. Including existing mosquito control practices into a model is useful if biological control is proposed for locations with current insecticidal control. The development of Integrated Pest Management (IPM) strategies can be enhanced using modeling techniques, as a wide variety of options can be simulated and examined. Models can also be valuable in comparing alternate routes of disease transmission and to investigate the level of control needed to reduce transmission.

Mesh:

Year:  2007        PMID: 17853610      PMCID: PMC2771413          DOI: 10.2987/8756-971X(2007)23[252:MABCOM]2.0.CO;2

Source DB:  PubMed          Journal:  J Am Mosq Control Assoc        ISSN: 8756-971X            Impact factor:   0.917


  68 in total

1.  Epidemiological uses of a population model for the tick Rhipicephalus appendiculatus.

Authors:  S Randolph
Journal:  Trop Med Int Health       Date:  1999-09       Impact factor: 2.622

2.  Incidence from coincidence: patterns of tick infestations on rodents facilitate transmission of tick-borne encephalitis virus.

Authors:  S E Randolph; D Miklisová; J Lysy; D J Rogers; M Labuda
Journal:  Parasitology       Date:  1999-02       Impact factor: 3.234

Review 3.  The role of mathematical modeling in evidence-based malaria control.

Authors:  F Ellis McKenzie; Ebrahim M Samba
Journal:  Am J Trop Med Hyg       Date:  2004-08       Impact factor: 2.345

4.  Efficient transmission of Borrelia burgdorferi between cofeeding Ixodes ricinus ticks (Acari: Ixodidae).

Authors:  L Gern; O Rais
Journal:  J Med Entomol       Date:  1996-01       Impact factor: 2.278

5.  A novel mode of arbovirus transmission involving a nonviremic host.

Authors:  L D Jones; C R Davies; G M Steele; P A Nuttall
Journal:  Science       Date:  1987-08-14       Impact factor: 47.728

6.  Dynamic model comparing the bionomics of two isolated Culex tarsalis (Diptera: Culicidae) populations: model development.

Authors:  J N Eisenberg; W K Reisen; R C Spear
Journal:  J Med Entomol       Date:  1995-03       Impact factor: 2.278

7.  A simulation model of the epidemiology of urban dengue fever: literature analysis, model development, preliminary validation, and samples of simulation results.

Authors:  D A Focks; E Daniels; D G Haile; J E Keesling
Journal:  Am J Trop Med Hyg       Date:  1995-11       Impact factor: 2.345

8.  Transmission of Crimean-Congo hemorrhagic fever virus in two species of Hyalomma ticks from infected adults to cofeeding immature forms.

Authors:  S W Gordon; K J Linthicum; J R Moulton
Journal:  Am J Trop Med Hyg       Date:  1993-04       Impact factor: 2.345

9.  A general model for the African trypanosomiases.

Authors:  D J Rogers
Journal:  Parasitology       Date:  1988-08       Impact factor: 3.234

10.  The risk and dynamics of onchocerciasis recrudescence after cessation of vector control.

Authors:  A P Plaisier; G J van Oortmarssen; J Remme; E S Alley; J D Habbema
Journal:  Bull World Health Organ       Date:  1991       Impact factor: 9.408

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  5 in total

1.  Multiscale analysis for a vector-borne epidemic model.

Authors:  Max O Souza
Journal:  J Math Biol       Date:  2013-04-02       Impact factor: 2.259

2.  Can Horton hear the whos? The importance of scale in mosquito-borne disease.

Authors:  C C Lord; B W Alto; S L Anderson; C R Connelly; J F Day; S L Richards; C T Smartt; W J Tabachnick
Journal:  J Med Entomol       Date:  2014-03       Impact factor: 2.278

3.  An age-structured extension to the vectorial capacity model.

Authors:  Vasiliy N Novoseltsev; Anatoli I Michalski; Janna A Novoseltseva; Anatoliy I Yashin; James R Carey; Alicia M Ellis
Journal:  PLoS One       Date:  2012-06-19       Impact factor: 3.240

Review 4.  Modeling transmission dynamics and control of vector-borne neglected tropical diseases.

Authors:  Paula M Luz; Claudio J Struchiner; Alison P Galvani
Journal:  PLoS Negl Trop Dis       Date:  2010-10-26

5.  Complementarity of empirical and process-based approaches to modelling mosquito population dynamics with Aedes albopictus as an example-Application to the development of an operational mapping tool of vector populations.

Authors:  Annelise Tran; Morgan Mangeas; Marie Demarchi; Emmanuel Roux; Pascal Degenne; Marion Haramboure; Gilbert Le Goff; David Damiens; Louis-Clément Gouagna; Vincent Herbreteau; Jean-Sébastien Dehecq
Journal:  PLoS One       Date:  2020-01-17       Impact factor: 3.240

  5 in total

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