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Seasonal associations of climatic drivers and malaria in the highlands of Ethiopia

Overview of attention for article published in Parasites & Vectors, June 2015
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Title
Seasonal associations of climatic drivers and malaria in the highlands of Ethiopia
Published in
Parasites & Vectors, June 2015
DOI 10.1186/s13071-015-0954-7
Pubmed ID
Authors

Alemayehu Midekisa, Belay Beyene, Abere Mihretie, Estifanos Bayabil, Michael C. Wimberly

Abstract

The impacts of interannual climate fluctuations on vector-borne diseases, especially malaria, have received considerable attention in the scientific literature. These effects can be significant in semi-arid and high-elevation areas such as the highlands of East Africa because cooler temperature and seasonally dry conditions limit malaria transmission. Many previous studies have examined short-term lagged effects of climate on malaria (weeks to months), but fewer have explored the possibility of longer-term seasonal effects. This study assessed the interannual variability of malaria occurrence from 2001 to 2009 in the Amhara region of Ethiopia. We tested for associations of climate variables summarized during the dry (January-April), early transition (May-June), and wet (July-September) seasons with malaria incidence in the early peak (May-July) and late peak (September-December) epidemic seasons using generalized linear models. Climate variables influenced land surface temperature (LST), rainfall, actual evapotranspiration (ET), and the enhanced vegetation index (EVI). We found that both early and late peak malaria incidence had the strongest associations with meteorological conditions in the preceding dry and early transition seasons. Temperature had the strongest influence in the wetter western districts, whereas moisture variables had the strongest influence in the drier eastern districts. We also found a significant correlation between malaria incidence in the early and the subsquent late peak malaria seasons, and the addition of early peak malaria incidence as a predictor substantially improved models of late peak season malaria in both of the study sub-regions. These findings suggest that climatic effects on malaria prior to the main rainy season can carry over through the rainy season and affect the probability of malaria epidemics during the late malaria peak. The results also emphasize the value of combining environmental monitoring with epidemiological surveillance to develop forecasts of malaria outbreaks, as well as the need for spatially stratified approaches that reflect the differential effects of climatic variations in the different sub-regions.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Ethiopia 1 <1%
Unknown 140 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 30 21%
Researcher 20 14%
Student > Ph. D. Student 19 13%
Student > Bachelor 15 11%
Student > Doctoral Student 6 4%
Other 14 10%
Unknown 38 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 13%
Medicine and Dentistry 16 11%
Environmental Science 13 9%
Nursing and Health Professions 10 7%
Biochemistry, Genetics and Molecular Biology 8 6%
Other 34 24%
Unknown 43 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 July 2015.
All research outputs
#15,339,713
of 22,816,807 outputs
Outputs from Parasites & Vectors
#3,382
of 5,461 outputs
Outputs of similar age
#154,226
of 264,035 outputs
Outputs of similar age from Parasites & Vectors
#77
of 120 outputs
Altmetric has tracked 22,816,807 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,461 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,035 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.