Literature DB >> 9051921

Temperature thresholds and statistical modelling of larval Wuchereria bancrofti (Filariidea:Onchocercidae) developmental rates.

F Lardeux1, J Cheffort.   

Abstract

Developmental rates for Wuchereria bancrofti larvae maturing in the vector Aedes polynesiensis were estimated by analysing stage-frequency data consisting of counts of larval stages in mosquitoes reared at 20, 22.5, 25, 27.5, 30 and 32 degrees C. Base temperatures (i.e. low temperature thresholds) for W. bancrofti development were estimated by the x-intercept method and the model of Lactin et al. (1995). Resulting values were similar with both methods and were approximately 12.5 degrees C for microfilariae (mf) in thorax, approximately 17 degrees C for L1, 15.5 degrees C for L2 and 16.5 degrees C for L3. Upper thresholds estimated by the Lactin et al. model were 29.3 degrees C for mf, 29.1 degrees C for L1, 32.2 degrees C for L2 and 31.5 degrees C for L3. In addition, an original method was devised for computing the L3 upper threshold, by modelling L3 length shrinkage with temperature. It gave a value of 31.4 degrees C. At 32 degrees C, L2 and L3 stages exhibited altered morphology, larvae being shorter and wider than expected. The model of Lactin et al. described adequately the non-linear relationship between developmental rate and temperature, but a linear degree-day approach may be applied for temperatures below 27-28 degrees C.

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Year:  1997        PMID: 9051921     DOI: 10.1017/s0031182096008359

Source DB:  PubMed          Journal:  Parasitology        ISSN: 0031-1820            Impact factor:   3.234


  10 in total

1.  Developmental models for estimating ecological responses to environmental variability: structural, parametric, and experimental issues.

Authors:  Julia L Moore; Justin V Remais
Journal:  Acta Biotheor       Date:  2014-01-20       Impact factor: 1.774

Review 2.  Rethinking vector immunology: the role of environmental temperature in shaping resistance.

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3.  Cautioning the use of degree-day models for climate change projections in the presence of parametric uncertainty.

Authors:  Julia L Moore; Song Liang; Adam Akullian; Justin V Remais
Journal:  Ecol Appl       Date:  2012-12       Impact factor: 4.657

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Authors:  Hannah Slater; Edwin Michael
Journal:  PLoS One       Date:  2012-02-16       Impact factor: 3.240

5.  Mapping, bayesian geostatistical analysis and spatial prediction of lymphatic filariasis prevalence in Africa.

Authors:  Hannah Slater; Edwin Michael
Journal:  PLoS One       Date:  2013-08-12       Impact factor: 3.240

6.  Modelling co-infection with malaria and lymphatic filariasis.

Authors:  Hannah C Slater; Manoj Gambhir; Paul E Parham; Edwin Michael
Journal:  PLoS Comput Biol       Date:  2013-06-13       Impact factor: 4.475

7.  Mapping the geographical distribution of lymphatic filariasis in Zambia.

Authors:  Enala T Mwase; Anna-Sofie Stensgaard; Mutale Nsakashalo-Senkwe; Likezo Mubila; James Mwansa; Peter Songolo; Sheila T Shawa; Paul E Simonsen
Journal:  PLoS Negl Trop Dis       Date:  2014-02-20

8.  Spatio-temporal distribution of dengue and lymphatic filariasis vectors along an altitudinal transect in Central Nepal.

Authors:  Meghnath Dhimal; Ishan Gautam; Aljoscha Kreß; Ruth Müller; Ulrich Kuch
Journal:  PLoS Negl Trop Dis       Date:  2014-07-31

9.  Environmental suitability for lymphatic filariasis in Nigeria.

Authors:  Obiora A Eneanya; Jorge Cano; Ilaria Dorigatti; Ifeoma Anagbogu; Chukwu Okoronkwo; Tini Garske; Christl A Donnelly
Journal:  Parasit Vectors       Date:  2018-09-17       Impact factor: 3.876

10.  The global distribution and transmission limits of lymphatic filariasis: past and present.

Authors:  Jorge Cano; Maria P Rebollo; Nick Golding; Rachel L Pullan; Thomas Crellen; Anna Soler; Louise A Kelly-Hope; Steve W Lindsay; Simon I Hay; Moses J Bockarie; Simon J Brooker
Journal:  Parasit Vectors       Date:  2014-10-11       Impact factor: 3.876

  10 in total

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