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

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dc.contributor.authorAmekudzi, L.K.
dc.contributor.authorTompkins, Adrian M.
dc.contributor.authorAsare, Ernest O.
dc.contributor.authorErmert, Volker
dc.contributor.authorRedl, Robert
dc.date.accessioned2020-02-21T11:16:48Z
dc.date.accessioned2023-04-19T01:51:56Z
dc.date.available2020-02-21T11:16:48Z
dc.date.available2023-04-19T01:51:56Z
dc.date.issued2015-02-18
dc.descriptionThis article is published in Geospatial Health and alsom available at doi:10.4081/gh.2016.391en_US
dc.description.abstractAbstract An energy budget model is developed to predict the 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, an 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 weather-driven dynamical disease models, including those designed for malaria early forecasting systems.en_US
dc.description.sponsorshipKNUSTen_US
dc.identifier.citationGeospatial Health, 10.4081en_US
dc.identifier.uri10.4081/gh.2016.391
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/12052
dc.language.isoenen_US
dc.publisherGeospatial Healthen_US
dc.subjectWater temperatureen_US
dc.subjectEnergy balance modelen_US
dc.subjectLarvae development time.en_US
dc.titleMosquito breeding site water temperature observations and simulations towards improved vector-borne disease models for Africaen_US
dc.typeArticleen_US
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