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Spatio-temporal malaria transmission patterns in Navrongo demographic surveillance site, northern Ghana

Kasasa, Simon and Asoala, Victor and Gosoniu, Laura and Anto, Francis and Adjuik, Martin and Tindana, Cletus and Smith, Thomas and Owusu-Agyei, Seth and Vounatsou, Penelope. (2013) Spatio-temporal malaria transmission patterns in Navrongo demographic surveillance site, northern Ghana. Malaria journal, Vol. 12 , 63.

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Abstract

The relationship between entomological measures of malaria transmission intensity and mortality remains uncertain. This is partly because transmission is heterogeneous even within small geographical areas. Studying this relationship requires high resolution, spatially structured, longitudinal entomological data. Geostatistical models that have been used to analyse the spatio-temporal heterogeneity have not considered the uncertainty in both sporozoite rate (SR) and mosquito density data. This study analysed data from Kassena-Nankana districts in northern Ghana to obtain small area estimates of malaria transmission rates allowing for this uncertainty.; Independent Bayesian geostatistical models for sporozoite rate and mosquito density were fitted to produce explicit entomological inoculation rate (EIR) estimates for small areas and short time periods, controlling for environmental factors.; Mosquitoes were trapped from 2,803 unique locations for three years using mainly CDC light traps. Anopheles gambiae constituted 52%, the rest were Anopheles funestus. Mean biting rates for An. funestus and An. gambiae were 32 and 33 respectively. Most bites occurred in September, the wettest month. The sporozoite rates were higher in the dry periods of the last two years compared with the wet period. The annual EIR varied from 1,132 to 157 infective bites. Monthly EIR varied between zero and 388 infective bites. Spatial correlation for SR was lower than that of mosquito densities.; This study confirms the presence of spatio-temporal heterogeneity in malaria transmission within a small geographical area. Spatial variance was stronger than temporal especially in the SR. The estimated EIR will be used in mortality analysis for the area.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Infectious Disease Modelling > Infectious Disease Modelling (Smith)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Biostatistics > Bayesian Modelling and Analysis (Vounatsou)
UniBasel Contributors:Smith, Thomas A. and Vounatsou, Penelope
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:BioMed Central
ISSN:1475-2875
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:31 Dec 2015 10:53
Deposited On:13 Sep 2013 07:50

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