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Spinned Poisson distribution with health management application
Consider a data collection setup during a spread of an infectious disease. Examples include severe acute respiratory syndrome (SARS) or influenza A virus H3N2. The health management in such scenarios quickly removes the infected cases before the data collection is completed. The estimate of the inci...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer US
2011
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7087638/ https://www.ncbi.nlm.nih.gov/pubmed/21519931 http://dx.doi.org/10.1007/s10729-011-9157-8 |
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author | Shanmugam, Ramalingam |
author_facet | Shanmugam, Ramalingam |
author_sort | Shanmugam, Ramalingam |
collection | PubMed |
description | Consider a data collection setup during a spread of an infectious disease. Examples include severe acute respiratory syndrome (SARS) or influenza A virus H3N2. The health management in such scenarios quickly removes the infected cases before the data collection is completed. The estimate of the incidence rate or the chance for anyone to be immune requires using a correct probability distribution. The usual Poisson distribution is inappropriate because of the impact of removing infected cases on the incidence rate as well as observing a new case. An appropriate new probability distribution is derived and is named as spinned Poisson distribution. The statistical properties of the spinned Poisson distribution are developed and illustrated using infectious smallpox incidence in Abakaliki, Nigeria. |
format | Online Article Text |
id | pubmed-7087638 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-70876382020-03-23 Spinned Poisson distribution with health management application Shanmugam, Ramalingam Health Care Manag Sci Article Consider a data collection setup during a spread of an infectious disease. Examples include severe acute respiratory syndrome (SARS) or influenza A virus H3N2. The health management in such scenarios quickly removes the infected cases before the data collection is completed. The estimate of the incidence rate or the chance for anyone to be immune requires using a correct probability distribution. The usual Poisson distribution is inappropriate because of the impact of removing infected cases on the incidence rate as well as observing a new case. An appropriate new probability distribution is derived and is named as spinned Poisson distribution. The statistical properties of the spinned Poisson distribution are developed and illustrated using infectious smallpox incidence in Abakaliki, Nigeria. Springer US 2011-04-26 2011 /pmc/articles/PMC7087638/ /pubmed/21519931 http://dx.doi.org/10.1007/s10729-011-9157-8 Text en © Springer Science+Business Media, LLC 2011 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Shanmugam, Ramalingam Spinned Poisson distribution with health management application |
title | Spinned Poisson distribution with health management application |
title_full | Spinned Poisson distribution with health management application |
title_fullStr | Spinned Poisson distribution with health management application |
title_full_unstemmed | Spinned Poisson distribution with health management application |
title_short | Spinned Poisson distribution with health management application |
title_sort | spinned poisson distribution with health management application |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7087638/ https://www.ncbi.nlm.nih.gov/pubmed/21519931 http://dx.doi.org/10.1007/s10729-011-9157-8 |
work_keys_str_mv | AT shanmugamramalingam spinnedpoissondistributionwithhealthmanagementapplication |