%0 Journal Article
%4 dpi.inpe.br/plutao/2013/05.31.17.15
%2 dpi.inpe.br/plutao/2013/05.31.17.15.17
%@doi 10.4236/abb.2013.44066
%@issn 2156-8456
%@issn 2156-8502
%F lattes: 0271662670324136 3 KifferMontCamaPign:2013:SpApCo
%T A proposed model for understanding human-bacterial interactions: Space-time approach on community <i>Escherichia coli</i> occurrence and resistance phenomenon
%D 2013
%A Kiffer, Carlos R. V.,
%A Monteiro, Antonio Miguel Vieira,
%A Camargo, Eduardo Celso Gerbi,
%A Pignatari, Antonio C. C.,
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Laboratório Especial de Microbiologia Clinica, Department Doenças Infecciosas e Parasitárias, Universidade Federal de São Paulo, São Paulo, Brazil
%@electronicmailaddress
%@electronicmailaddress miguel@dpi.inpe.br
%@electronicmailaddress eduardo@dpi.inpe.br
%B Advances in Bioscience and Biotechnology
%V 4
%N 4
%P 505-508
%K Escherichia coli, antimicrobial agents, microbiome.
%X Due to ecological effect, it is expected that population exposures to antimicrobial drugs may lead to micro- organisms modifications, occasionally leading to re- sistance emergence. The present review was based on previous empirical data and on related literature search for quantitative empirical models exploring the hu- man-bacterial interactions. Our previous studies have shown the emergence of ciprofloxacin resistant (CIP- R) Escherichia coli significantly related to previous specific levels of ciprofloxacin consumption and to urban clusters of CIP-R E. coli. The evidence of sig- nificant spatial clustering of antimicrobial resistance (ciprofloxacin resistance E. coli) reinforces the ecolo- gical effect hypothesis as a major drive in resistance emergence. In other words, human populations sub- mitted to a certain ciprofloxacin or quinolone usage level may affect neighbours within certain geogra- phical areas, not necessarily due to individual antim- icrobial intake, but as a driving pressure over a mo- dified circulating E. coli population. Apparently quan- titative spatial-temporal analytical frameworks may be better for understanding human-bacterial interac- tions based on any of their epiphenomena (antimicro- bial consumption, antimicrobial resistance, geno/phe- notypic characteristics).
%@language en
%3 ABB_2013041113304729.pdf