An individual-based network model to evaluate interventions for controlling pneumococcal transmission
<p>Abstract</p> <p>Background</p> <p><it>Streptococcus pneumoniae </it>is a major cause of morbidity and mortality worldwide, but also a common colonizer of the upper respiratory tract. The emergence and spread of antibiotic resistant pneumococcal strains ha...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2008-06-01
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| Series: | BMC Infectious Diseases |
| Online Access: | http://www.biomedcentral.com/1471-2334/8/83 |
| _version_ | 1828497626965737472 |
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| author | Jansson Andreas Karlsson Diana Normark Birgitta Nilsson Patric |
| author_facet | Jansson Andreas Karlsson Diana Normark Birgitta Nilsson Patric |
| author_sort | Jansson Andreas |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p><it>Streptococcus pneumoniae </it>is a major cause of morbidity and mortality worldwide, but also a common colonizer of the upper respiratory tract. The emergence and spread of antibiotic resistant pneumococcal strains has threatened effective therapy. The long-term effects of measures aiming to limit pneumococcal spread are poorly understood. Computational modeling makes it possible to conduct virtual experiments that are impractical to perform in real life and thereby allows a more full understanding of pneumococcal epidemiology and control efforts.</p> <p>Methods</p> <p>We have developed a contact network model to evaluate the efficacy of interventions aiming to control pneumococcal transmission. Demographic data from Sweden during the mid-2000s were employed. Analyses of the model's parameters were conducted to elucidate key determinants of pneumococcal spread. Also, scenario simulations were performed to assess candidate control measures.</p> <p>Results</p> <p>The model made good predictions of previous findings where a correlation has been found between age and pneumococcal carriage. Of the parameters tested, group size in day-care centers was shown to be one of the most important factors for pneumococcal transmission. Consistent results were generated from the scenario simulations.</p> <p>Conclusion</p> <p>We recommend, based on the model predictions, that strategies to control pneumococcal disease and organism transmission should include reducing the group size in day-care centers.</p> |
| first_indexed | 2024-12-11T12:51:01Z |
| format | Article |
| id | doaj.art-2f21097c55bc4933a85c052b30b64bd4 |
| institution | Directory Open Access Journal |
| issn | 1471-2334 |
| language | English |
| last_indexed | 2024-12-11T12:51:01Z |
| publishDate | 2008-06-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Infectious Diseases |
| spelling | doaj.art-2f21097c55bc4933a85c052b30b64bd42022-12-22T01:06:41ZengBMCBMC Infectious Diseases1471-23342008-06-01818310.1186/1471-2334-8-83An individual-based network model to evaluate interventions for controlling pneumococcal transmissionJansson AndreasKarlsson DianaNormark BirgittaNilsson Patric<p>Abstract</p> <p>Background</p> <p><it>Streptococcus pneumoniae </it>is a major cause of morbidity and mortality worldwide, but also a common colonizer of the upper respiratory tract. The emergence and spread of antibiotic resistant pneumococcal strains has threatened effective therapy. The long-term effects of measures aiming to limit pneumococcal spread are poorly understood. Computational modeling makes it possible to conduct virtual experiments that are impractical to perform in real life and thereby allows a more full understanding of pneumococcal epidemiology and control efforts.</p> <p>Methods</p> <p>We have developed a contact network model to evaluate the efficacy of interventions aiming to control pneumococcal transmission. Demographic data from Sweden during the mid-2000s were employed. Analyses of the model's parameters were conducted to elucidate key determinants of pneumococcal spread. Also, scenario simulations were performed to assess candidate control measures.</p> <p>Results</p> <p>The model made good predictions of previous findings where a correlation has been found between age and pneumococcal carriage. Of the parameters tested, group size in day-care centers was shown to be one of the most important factors for pneumococcal transmission. Consistent results were generated from the scenario simulations.</p> <p>Conclusion</p> <p>We recommend, based on the model predictions, that strategies to control pneumococcal disease and organism transmission should include reducing the group size in day-care centers.</p>http://www.biomedcentral.com/1471-2334/8/83 |
| spellingShingle | Jansson Andreas Karlsson Diana Normark Birgitta Nilsson Patric An individual-based network model to evaluate interventions for controlling pneumococcal transmission BMC Infectious Diseases |
| title | An individual-based network model to evaluate interventions for controlling pneumococcal transmission |
| title_full | An individual-based network model to evaluate interventions for controlling pneumococcal transmission |
| title_fullStr | An individual-based network model to evaluate interventions for controlling pneumococcal transmission |
| title_full_unstemmed | An individual-based network model to evaluate interventions for controlling pneumococcal transmission |
| title_short | An individual-based network model to evaluate interventions for controlling pneumococcal transmission |
| title_sort | individual based network model to evaluate interventions for controlling pneumococcal transmission |
| url | http://www.biomedcentral.com/1471-2334/8/83 |
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