Skip to main content

Free Content Spatial synchrony of malaria outbreaks in a highland region of Ethiopia

Download Article:

You have access to the full text article on a website external to Ingenta Connect.

Please click here to view this article on Wiley Online Library.

You may be required to register and activate access on Wiley Online Library before you can obtain the full text. If you have any queries please visit Wiley Online Library

Abstract

To understand the drivers and consequences of malaria in epidemic‐prone regions, it is important to know whether epidemics emerge independently in different areas as a consequence of local contingencies, or whether they are synchronised across larger regions as a result of climatic fluctuations and other broad‐scale drivers. To address this question, we collected historical malaria surveillance data for the Amhara region of Ethiopia and analysed them to assess the consistency of various indicators of malaria risk and determine the dominant spatial and temporal patterns of malaria within the region. We collected data from a total of 49 districts from 1999–2010. Data availability was better for more recent years and more data were available for clinically diagnosed outpatient malaria cases than confirmed malaria cases. Temporal patterns of outpatient malaria case counts were correlated with the proportion of outpatients diagnosed with malaria and confirmed malaria case counts. The proportion of outpatients diagnosed with malaria was spatially clustered, and these cluster locations were generally consistent from year to year. Outpatient malaria cases exhibited spatial synchrony at distances up to 300 km, supporting the hypothesis that regional climatic variability is an important driver of epidemics. Our results suggest that decomposing malaria risk into separate spatial and temporal components may be an effective strategy for modelling and forecasting malaria risk across large areas. They also emphasise both the value and limitations of working with historical surveillance datasets and highlight the importance of enhancing existing surveillance efforts.
No References
No Citations
No Supplementary Data
No Data/Media
No Metrics

Language: English

Document Type: Research Article

Affiliations: 1:  Geographic Information Science Center of Excellence, South Dakota State University, Brookings, SD, USA 2:  Health, Development, and Anti-Malaria Association, Addis Ababa, Ethiopia 3:  United States Agency for International Development, Addis Ababa, Ethiopia

Publication date: 2012-10-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more