alexa Model for Rainfall and Malaria Cases in Yilmana Densa District, North West Ethiopia | OMICS International | Abstract
ISSN: 2161-1165

Epidemiology: Open Access
Open Access

Like us on:

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Model for Rainfall and Malaria Cases in Yilmana Densa District, North West Ethiopia

Tsegahun Worku Brhanie*

School of Public Health, College of Medicine and Health Sciences, Bahir Dar University, Ethiopia

*Corresponding Author:
Tsegahun Worku Brhanie
School of Public Health, College of Medicine and Health Sciences
Bahir Dar University, Ethiopia
Tel: +251918041869
E-mail: [email protected]

Received date: August 02, 2016; Accepted date: September 09, 2016; Published date: September 16, 2016

Citation: Brhanie TW (2016) Model for Rainfall and Malaria Cases in Yilmana Densa District, North West Ethiopia. Epidemiology (Sunnyvale) 6:262. doi:10.4172/2161-1165.1000262

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.

Abstract

Background: Malaria is the major public health problem in Ethiopia. Rain fall amount and distribution have impact for malaria transmission. Objective: To assess the relationship between positive malaria cases and Rainfall within ten year’s periodic trends of malaria transmission. Method: Retrospective study design was conducted by using ten years monthly rainfall and positive malaria cases. Simple linear regression, correlation were applied to analyze association. SPSS version 16.0 was used for analysis. Result: A slight variation of malaria transmission was observed in the last ten years and the transmission was non periodic. Among Plasmodium species, P. falciparum was highly prevalent. From spearman correlation analysis monthly minimum rainfall (p=0.022) at one month lag was significantly correlated with total positive malaria cases. Simple linear regression analysis suggested that monthly rainfall (p=0.001) at one month lag was significant meteorological factor. Multiple linear regressions analysis also showed that, rainfall had significantly (p<0.001) correlated at the same time with positive malaria cases by stepwise regression. Conclusion: From this finding, malaria transmission was not seasonal. Rainfall has association with malaria cases and may effect on the same or next month malaria cases occurrence. Rainfall seems best malaria predictor, since strongly correlated with malaria cases.

Keywords

Recommended Conferences

Annual meet on Epidemiology and Public Health

Yokohama, Japan
Share This Page
 
Top