Literature DB >> 27063735

Mosquito breeding site water temperature observations and simulations towards improved vector-borne disease models for Africa.

Ernest O Asare1, Adrian M Tompkins, Leonard K Amekudzi, Volker Ermert, Robert Redl.   

Abstract

An energy budget model is developed to predict water temperature of typical mosquito larval developmental habitats. It assumes a homogeneous mixed water column driven by empirically derived fluxes. The model shows good agreement at both hourly and daily time scales with 10-min temporal resolution observed water temperatures, monitored between June and November 2013 within a peri-urban area of Kumasi, Ghana. There was a close match between larvae development times calculated using either the model-derived or observed water temperatures. The water temperature scheme represents a significant improvement over assuming the water temperature to be equal to air temperature. The energy budget model requires observed minimum and maximum temperatures, information that is generally available from weather stations. Our results show that hourly variations in water temperature are important for the simulation of aquatic-stage development times. By contrast, we found that larval development is insensitive to sub-hourly variations. Modelling suggests that in addition to water temperature, accurate estimation of degree-day development time is very important to correctly predict the larvae development times. The results highlight the potential of the model to predict water temperature of temporary bodies of surface water. Our study represents an important contribution towards the improvement of weatherdriven dynamical disease models, including those designed for malaria early forecasting systems.

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Year:  2016        PMID: 27063735     DOI: 10.4081/gh.2016.391

Source DB:  PubMed          Journal:  Geospat Health        ISSN: 1827-1987            Impact factor:   1.212


  4 in total

Review 1.  Mathematical modeling of climate change and malaria transmission dynamics: a historical review.

Authors:  Steffen E Eikenberry; Abba B Gumel
Journal:  J Math Biol       Date:  2018-04-24       Impact factor: 2.259

2.  Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors.

Authors:  Muhammad Haris Mazher; Javed Iqbal; Muhammad Ahsan Mahboob; Iqra Atif
Journal:  Iran J Public Health       Date:  2018-09       Impact factor: 1.429

3.  Modelled and observed mean and seasonal relationships between climate, population density and malaria indicators in Cameroon.

Authors:  Amelie D Mbouna; Adrian M Tompkins; Andre Lenouo; Ernest O Asare; Edmund I Yamba; Clement Tchawoua
Journal:  Malar J       Date:  2019-11-10       Impact factor: 2.979

4.  Mapping Aedes aegypti (Diptera: Culicidae) and Aedes albopictus Vector Mosquito Distribution in Brownsville, TX.

Authors:  Mark H Myer; Chelsea M Fizer; Kenneth R Mcpherson; Anne C Neale; Andrew N Pilant; Arturo Rodriguez; Pai-Yei Whung; John M Johnston
Journal:  J Med Entomol       Date:  2020-01-09       Impact factor: 2.278

  4 in total

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