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Find video protocols related to scientific articles indexed in Pubmed.
Descriptive spatial analysis of the cholera epidemic 2008-2009 in Harare, Zimbabwe: a secondary data analysis.
Trans. R. Soc. Trop. Med. Hyg.
PUBLISHED: 04-15-2010
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This ecological study describes the cholera epidemic in Harare during 2008-2009 and identifies patterns that may explain transmission. Rates ratios of cholera cases by suburb were calculated by a univariate regression Poisson model and then, through an Empirical Bayes modelling, smoothed rate ratios were estimated and represented geographically. Mbare and southwest suburbs of Harare presented higher rate ratios. Suburbs attack rates ranged from 1.2 (95% Cl = 0.7-1.6) cases per 1000 people in Tynwald to 90.3 (95% Cl = 82.8-98.2) in Hopley. The identification of this spatial pattern in the spread, characterised by low risk in low density residential housing, and a higher risk in high density south west suburbs and Mbare, could be used to advocate for improving water and sanitation conditions and specific preparedness measures in the most affected areas.
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Elevation and cholera: an epidemiological spatial analysis of the cholera epidemic in Harare, Zimbabwe, 2008-2009.
BMC Public Health
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In highly populated African urban areas where access to clean water is a challenge, water source contamination is one of the most cited risk factors in a cholera epidemic. During the rainy season, where there is either no sewage disposal or working sewer system, runoff of rains follows the slopes and gets into the lower parts of towns where shallow wells could easily become contaminated by excretes. In cholera endemic areas, spatial information about topographical elevation could help to guide preventive interventions. This study aims to analyze the association between topographic elevation and the distribution of cholera cases in Harare during the cholera epidemic in 2008 and 2009.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.