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Environ Sci Technol ; 43(4): 993-9, 2009 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-19320148

RESUMO

Diarrheal illness is a leading cause of child mortality in developing nations. Previous longitudinal studies have attempted to identify the factors that contribute to child mortality, but few have examined the determinants of diarrheal illness at a country level. Here we demonstrate the use of Classification and Regression Trees (CART) to predict diarrheal illness from a 192-country data set of country-level attributes and compare the performance of CART with a linear regression model. The CART model identifies improvements in rural sanitation as the most important spending priority for reducing diarrheal illness. We estimate that reducing unmet rural sanitation need worldwide by 65% would save the equivalent of 1.2 million lives annually.


Assuntos
Efeitos Psicossociais da Doença , Diarreia/economia , Diarreia/epidemiologia , Inteligência Artificial , Criança , Diarreia/mortalidade , Geografia , Saúde Global , Humanos , Modelos Lineares , Modelos Estatísticos , População Rural , Saneamento
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