| dc.description.abstract | Vector-borne diseases such as malaria and filariasis are public health problems that affect the socioeconomic status of all developing countries. Malaria is a serious disease globally, for instance, according to year 2019 and 2020 global malaria data; there were 227 million and 241 million malaria cases respectively, and approximately 627,000 deaths. In year 2020 about 95% of malaria cases and 96% of malaria deaths occurred in Africa. Mosquitoes are the main causes of malaria but there are several spices such as Aedes, Culex and Anopheles that transmit various diseases. Anopheles
is the main vector for malaria which needs to be controlled in order to minimize the spread of malaria. Use of mosquito repellents is one of the ways used to prevent bites from the A. gambiae. In the market there are several repellents that are used in prevention of mosquito bites but they have negative effects such as allergy and dermatitis to the users. Therefore, the current study seeks to formulate an eco-friendly and non-toxic A. gambiae repellent for control of malaria. The plant samples were collected from Mugui village, Tharaka South Sub-County, Tharaka constituency in Tharaka Nithi County. The samples were hydro-distilled using a Clevenger apparatus to obtain the essential oils, and experimental tests done in a repellent testing chamber. The essential oils were then analyzed using Gas Chromatography-Mass Selective detector instrument (GC-MSD) to determine their chemical composition. The most abundance compounds in the essential oils were terpenoids: 1, 8-Cineole, β-Myrcene,β-Pinene. A blend of O. suave and O. americanum mixed in the ratio of 1:1 was more potent repellent (100.00±0.00) against A. gambiae suggesting that this may be due to additive or synergistic effects of individual constituents. The most potent single essential oil was O. americanum while Eucalyptus citriodora was the least potent.
The values of repellence action were determined over control at a p-value of 0.05 and 0.01 by one-way Analysis of Variances (ANOVA) and separated using Student Newman-Keels at P≤0.05 using SAS software. | en_US |
