The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study
Mathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using...
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| Veröffentlicht in: | Epidemiology and infection 2008-03, Vol.136 (3), p.289-298 |
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| creator | TEMIME, L. HEJBLUM, G. SETBON, M. VALLERON, A. J. |
| description | Mathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using antibiotic resistance as a case study, 60 published models were analysed. Their interactions with other scientific fields are reported and their citation impact evaluated, as well as temporal trends. The yearly number of antibiotic resistance modelling publications increased significantly between 1990 and 2006. This rise cannot be explained by the surge of interest in resistance phenomena alone. Moreover, modelling articles are, on average, among the most frequently cited third of articles from the journal in which they were published. The results of this analysis, which might be applicable to other emerging public health problems, demonstrate the growing interest in mathematical modelling approaches to evaluate antibiotic resistance. |
| doi_str_mv | 10.1017/S0950268807009442 |
| format | Article |
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J.</creatorcontrib><title>The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study</title><title>Epidemiology and infection</title><addtitle>Epidemiol. Infect</addtitle><description>Mathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using antibiotic resistance as a case study, 60 published models were analysed. Their interactions with other scientific fields are reported and their citation impact evaluated, as well as temporal trends. The yearly number of antibiotic resistance modelling publications increased significantly between 1990 and 2006. This rise cannot be explained by the surge of interest in resistance phenomena alone. 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The results of this analysis, which might be applicable to other emerging public health problems, demonstrate the growing interest in mathematical modelling approaches to evaluate antibiotic resistance.</description><subject>Anti-Bacterial Agents - therapeutic use</subject><subject>Antibiotic resistance</subject><subject>Antibiotics</subject><subject>Applications</subject><subject>Bacteria</subject><subject>Bacteriology</subject><subject>Bibliographic citations</subject><subject>Biological and medical sciences</subject><subject>Biology</subject><subject>Citation impact</subject><subject>Clinical medicine</subject><subject>Communicable Diseases - drug therapy</subject><subject>Communicable Diseases - epidemiology</subject><subject>Computer Science</subject><subject>Decision making</subject><subject>Disease models</subject><subject>Disease transmission</subject><subject>Drug Resistance, Microbial</subject><subject>Epidemiology</subject><subject>Fundamental and applied biological sciences. 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J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study</atitle><jtitle>Epidemiology and infection</jtitle><addtitle>Epidemiol. Infect</addtitle><date>2008-03-01</date><risdate>2008</risdate><volume>136</volume><issue>3</issue><spage>289</spage><epage>298</epage><pages>289-298</pages><issn>0950-2688</issn><eissn>1469-4409</eissn><coden>EPINEU</coden><abstract>Mathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using antibiotic resistance as a case study, 60 published models were analysed. Their interactions with other scientific fields are reported and their citation impact evaluated, as well as temporal trends. 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| subjects | Anti-Bacterial Agents - therapeutic use Antibiotic resistance Antibiotics Applications Bacteria Bacteriology Bibliographic citations Biological and medical sciences Biology Citation impact Clinical medicine Communicable Diseases - drug therapy Communicable Diseases - epidemiology Computer Science Decision making Disease models Disease transmission Drug Resistance, Microbial Epidemiology Fundamental and applied biological sciences. Psychology General aspects Global Health Humans Industrialized nations Infectious diseases Life Sciences Mathematical models Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Microbiology Modeling and Simulation Models, Statistical Public health Research methodology Review Review Article Santé publique et épidémiologie Staphylococcus infections Statistics |
| title | The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study |
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