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

Abstract

Climate 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 rain-fall 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 oth-er 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 re-sults suggest maximum temperature as a better predictor of malaria trends than minimum tem-perature or precipitation, particularly in the transition zone. Climate change effects on malaria caseloads seem multi-factorial. For effective malaria control, interventions could be synchronized N. A. B. Klutse et al. 765 with the most important climatic predictors of the disease for greater impact.