Prevalence Rate and Contributory Factors of Malaria in the Amenfi West District, Ghana
Esther Love Darkoh *
Department of Theoretical and Applied Biology, College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
John Aseidu Larbi
Department of Theoretical and Applied Biology, College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
*Author to whom correspondence should be addressed.
Abstract
Aims: To determine the prevalence rate and some contributory factors of malaria in the Amenfi West District of Ghana. This study investigated the prevalence and determinants in predicting malaria status in the Amenfi West District.
Place and Duration of Study: Asankrangwa Catholic Hospital in the Amenfi West District of the Western Region, Ghana between March 2016 and November 2016.
Methodology: A purposive sampling technique was used to select 240 patients of both sexes aged 0- 81 years old at Asankrangwa District Hospital. Venous blood was collected and presence of malaria parasites was observed microscopically on thick smears. Demographic data such as age, sex and the type of malaria control method(s) used were retrieved from patients. All data was recorded and analyzed using SPSS (version 23) statistical software. Categorical data was compared using Pearson’s Chi- Square test set at a significant level of 5%. For parasite density, factor effects were examined using Mann-Whitney and Kruskal-Wallis tests where appropriate to investigate statistical differences at 95% confidence interval. Regression analysis was also employed to model the presence (positive) or absence (negative) of malaria in a patient.
Results: Overall malaria prevalence was 27.9% (67/240). Parasite density (P = 0.048) and prevalence (P = 0.000) differed significantly based on age with younger persons recording higher values. Difference in prevalence rate was also found among the blood group types (P = 0.041) but no statistical difference was recorded in relation to parasite density (P = 0.329). Moreover, the logistic regression analysis showed that blood group (P = 0.029), type of malaria control used (P = 0.019), hemoglobin level (P = 0.002) and age (P= 0.002) are statistically significant in determining the malaria status (positive/negative) of an individual; For instance, use of treated nets or being in an older age group decreased a person’s odds of experiencing malaria.
Conclusion: It is therefore suggested that, much emphasis on the use of ITNs should be focused on younger children since they are more vulnerable to malaria infection.
Keywords: Malaria, parasitemia, seasonality, binary logistic regression, Ghana