Assessment of Patterns of Climate Variables and Malaria Cases in Two Ecological Zones of Ghana

dc.contributor.authorKlutse, N.A.B.
dc.contributor.authorAboagye-Antwi, F.
dc.contributor.authorOwusu, K.
dc.contributor.authorNtiamoa-Baidu, Y.
dc.date.accessioned2022-09-02T09:18:48Z
dc.date.available2022-09-02T09:18:48Z
dc.date.issued2014
dc.descriptionResearch Articleen_US
dc.description.abstractClimate change is projected to impact human health, particularly incidence of water related and vector borne diseases, such as malaria. A better understanding of the relationship between rainfall patterns and malaria cases is thus required for effective climate change adaptation strategies involving planning and implementation of appropriate disease control interventions. We analyzed climatic data and reported cases of malaria spanning a period of eight years (2001 to 2008) from two ecological zones in Ghana (Ejura and Winneba in the transition and coastal savannah zones respectively) to determine the association between malaria cases, and temperature and rainfall patterns and the potential effects of climate change on malaria epidemiological trends. Monthly peaks of malaria caseloads lagged behind monthly rainfall peaks. Correlation between malaria caseloads and rainfall intensity, and minimum temperature were generally weak at both sites. Lag correlations of up to four months yielded better agreement between the variables, especially at Ejura where a two-month lag between malaria caseloads and rainfall was significantly high but negatively correlated (r = −0.72; p value < 0.05). Mean monthly maximum temperature and monthly malaria caseloads at Ejura showed a strong negative correlation at zero month lag (r = −0.70, p value < 0.05), with a similar, but weaker relationship at Winneba, (r = −0.51). On the other hand, a positive significant correlation (r = 0.68, p value < 0.05) between malaria caseloads and maximum temperature was observed for Ejura at a four-month lag, while Winneba showed a strong correlation (r = 0.70; p value < 0.05) between the parameters at a two-month lag. The results suggest maximum temperature as a better predictor of malaria trends than minimum temperature or precipitation, particularly in the transition zone. Climate change effects on malaria caseloads seem multi-factorial. For effective malaria control, interventions could be synchronizeden_US
dc.identifier.citationHow to cite this paper: Klutse, N.A.B., Aboagye-Antwi, F., Owusu, K. and Ntiamoa-Baidu, Y. (2014) Assessment of Patterns of Climate Variables and Malaria Cases in Two Ecological Zones of Ghana. Open Journal of Ecology, 4, 764-775. http://dx.doi.org/10.4236/oje.2014.412065en_US
dc.identifier.otherhttp://www.scirp.org/journal/oje http://dx.doi.org/10.4236/oje.2014.412065
dc.identifier.urihttp://localhost:8080/handle/123456789/38290
dc.language.isoenen_US
dc.publisherOpen Journal of Ecologyen_US
dc.subjectMalariaen_US
dc.subjectTemperatureen_US
dc.subjectClimate Changeen_US
dc.subjectEcological Zoneen_US
dc.subjectRainfallen_US
dc.titleAssessment of Patterns of Climate Variables and Malaria Cases in Two Ecological Zones of Ghanaen_US
dc.typeArticleen_US

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