The Role of Temperature for Malaria Transmission in Gongi Kolela District, Amhara Regional State, North West EthiopiaTsegahun Worku Brhanie*
Department of Applied Human Nutrition, Faculty of Chemical and Food Engineering, Bahir Dar University, Ethiopia
- *Corresponding Author:
- Tsegahun Worku Brhanie
Department of Applied Human Nutrition
Faculty of Chemical and Food Engineering
Bahir Dar University, Ethiopia
E-mail: [email protected]
Received date: September 13, 2016; Accepted date: December 08, 2016; Published date: December 15, 2016
Citation: Brhanie TW (2016) The Role of Temperature for Malaria Transmission in Gongi Kolela District, Amhara Regional State, North West Ethiopia. Epidemiology (Sunnyvale) 6:281. doi: 10.4172/2161-1165.1000281
Copyright: © 2016 Brhanie TW. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Background: Malaria is a disease caused by protozoan parasites of the genus Plasmodium and transmitted by the bite of infected female anopheles mosquitoes. Temperature have influential role for malaria transmission. This study was done to see the correlation between positive malaria cases and temperature. Objective: To assess the correlation between positive malaria cases and temperature. Methods: Time series analysis was conducted by using ten years monthly temperature and malaria cases. Simple linear regression and correlation were applied to analyze Correlation between temperature and malaria case by using SPSS version 16.0. Results: Within ten years, malaria transmission was observed throughout the year. Both Plasmodium falciparum and Plasmodium vivax found in the district. Spearman correlation analysis showed that monthly minimum temperature (p=0.034) at one month lag significantly correlated with total positive malaria cases but maximum temperature (p=-0.020) negatively related with total malaria cases. Simple linear regression analysis suggested that monthly maximum temperature (p=0.039) significant factors. Conclusions: From the time series analysis malaria transmission was not periodic. Temperature has association with malaria cases and may effect on the same or next month malaria cases occurrence. The responsible bodies should use temperature for predicting malaria transmission.