The impact of climate on Leptospirosis in São Paulo, Brazil

Abstract In this work, we correlate the daily number of human leptospirosis cases with several climatic factors. We used a negative binomial model that considers hospital daily admissions due to leptospirosis as the dependent variable, and the climatic variables of daily precipitation pattern, and m...
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Autor*in:	Coelho, Micheline S. Z. S. [verfasserIn] Massad, Eduardo

Format:	Artikel
Sprache:	Englisch

Erschienen:	2011

Schlagwörter:	Leptospirosis Negative binomial regression Hospital admission Climate

Anmerkung:	© ISB 2011

Übergeordnetes Werk:	Enthalten in: International journal of biometeorology - Springer-Verlag, 1961, 56(2011), 2 vom: 03. März, Seite 233-241
Übergeordnetes Werk:	volume:56 ; year:2011 ; number:2 ; day:03 ; month:03 ; pages:233-241

Links:	Volltext

DOI / URN:	10.1007/s00484-011-0419-4

Katalog-ID:	OLC2106904231

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title_sort	the impact of climate on leptospirosis in são paulo, brazil
title_auth	The impact of climate on Leptospirosis in São Paulo, Brazil
abstract	Abstract In this work, we correlate the daily number of human leptospirosis cases with several climatic factors. We used a negative binomial model that considers hospital daily admissions due to leptospirosis as the dependent variable, and the climatic variables of daily precipitation pattern, and maximum and minimum temperature as independent variables. We calculated the monthly leptospirosis admission probabilities from the precipitation and maximum temperature variables. The month of February showed the highest probability, although values were also high during the spring months. The month of February also showed the highest number of hospital admissions. Another interesting result is that, for every 20 mm precipitation, there was an average increase of 31.5% in hospital admissions. Additionally, the relative risk of leptospirosis varied from 1.1 to 2.0 when the precipitation varied from 20 to 140 mm. © ISB 2011
abstractGer	Abstract In this work, we correlate the daily number of human leptospirosis cases with several climatic factors. We used a negative binomial model that considers hospital daily admissions due to leptospirosis as the dependent variable, and the climatic variables of daily precipitation pattern, and maximum and minimum temperature as independent variables. We calculated the monthly leptospirosis admission probabilities from the precipitation and maximum temperature variables. The month of February showed the highest probability, although values were also high during the spring months. The month of February also showed the highest number of hospital admissions. Another interesting result is that, for every 20 mm precipitation, there was an average increase of 31.5% in hospital admissions. Additionally, the relative risk of leptospirosis varied from 1.1 to 2.0 when the precipitation varied from 20 to 140 mm. © ISB 2011
abstract_unstemmed	Abstract In this work, we correlate the daily number of human leptospirosis cases with several climatic factors. We used a negative binomial model that considers hospital daily admissions due to leptospirosis as the dependent variable, and the climatic variables of daily precipitation pattern, and maximum and minimum temperature as independent variables. We calculated the monthly leptospirosis admission probabilities from the precipitation and maximum temperature variables. The month of February showed the highest probability, although values were also high during the spring months. The month of February also showed the highest number of hospital admissions. Another interesting result is that, for every 20 mm precipitation, there was an average increase of 31.5% in hospital admissions. Additionally, the relative risk of leptospirosis varied from 1.1 to 2.0 when the precipitation varied from 20 to 140 mm. © ISB 2011
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mediatype_str_mv	n
isOA_txt	false
hochschulschrift_bool	false
doi_str	10.1007/s00484-011-0419-4
up_date	2024-07-04T08:22:08.320Z
_version_	1803635998925520896
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The impact of climate on Leptospirosis in São Paulo, Brazil

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