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Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria
BACKGROUND: The serial interval is a fundamentally important quantity in infectious disease epidemiology that has numerous applications to inferring patterns of transmission from case data. Many of these applications are apropos of efforts to eliminate falciparum malaria from locations throughout th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034682/ https://www.ncbi.nlm.nih.gov/pubmed/27660051 http://dx.doi.org/10.1186/s12936-016-1537-6 |
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author | Huber, John H. Johnston, Geoffrey L. Greenhouse, Bryan Smith, David L. Perkins, T. Alex |
author_facet | Huber, John H. Johnston, Geoffrey L. Greenhouse, Bryan Smith, David L. Perkins, T. Alex |
author_sort | Huber, John H. |
collection | PubMed |
description | BACKGROUND: The serial interval is a fundamentally important quantity in infectious disease epidemiology that has numerous applications to inferring patterns of transmission from case data. Many of these applications are apropos of efforts to eliminate falciparum malaria from locations throughout the world, yet the serial interval for this disease is poorly understood quantitatively. METHODS: To obtain a quantitative estimate of the serial interval for falciparum malaria, the sum of the components of the falciparum malaria transmission cycle was taken based on a combination of mathematical models and empirical data. During this process, a number of factors were identified that account for substantial variability in the serial interval across different contexts. RESULTS: Treatment with anti-malarial drugs roughly halves the serial interval due to an abbreviated period of human infectiousness, seasonality results in different serial intervals at different points in the transmission season, and variability in within-host dynamics results in many individuals whose serial intervals do not follow average behaviour. Furthermore, 24.5 % of secondary cases presenting clinically did so prior to the primary cases being identified through active detection of infection. CONCLUSIONS: These results have important implications for epidemiological applications that rely on quantitative estimates of the serial interval of falciparum malaria and other diseases characterized by prolonged infections and complex ecological drivers. |
format | Online Article Text |
id | pubmed-5034682 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50346822016-09-29 Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria Huber, John H. Johnston, Geoffrey L. Greenhouse, Bryan Smith, David L. Perkins, T. Alex Malar J Research BACKGROUND: The serial interval is a fundamentally important quantity in infectious disease epidemiology that has numerous applications to inferring patterns of transmission from case data. Many of these applications are apropos of efforts to eliminate falciparum malaria from locations throughout the world, yet the serial interval for this disease is poorly understood quantitatively. METHODS: To obtain a quantitative estimate of the serial interval for falciparum malaria, the sum of the components of the falciparum malaria transmission cycle was taken based on a combination of mathematical models and empirical data. During this process, a number of factors were identified that account for substantial variability in the serial interval across different contexts. RESULTS: Treatment with anti-malarial drugs roughly halves the serial interval due to an abbreviated period of human infectiousness, seasonality results in different serial intervals at different points in the transmission season, and variability in within-host dynamics results in many individuals whose serial intervals do not follow average behaviour. Furthermore, 24.5 % of secondary cases presenting clinically did so prior to the primary cases being identified through active detection of infection. CONCLUSIONS: These results have important implications for epidemiological applications that rely on quantitative estimates of the serial interval of falciparum malaria and other diseases characterized by prolonged infections and complex ecological drivers. BioMed Central 2016-09-22 /pmc/articles/PMC5034682/ /pubmed/27660051 http://dx.doi.org/10.1186/s12936-016-1537-6 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Huber, John H. Johnston, Geoffrey L. Greenhouse, Bryan Smith, David L. Perkins, T. Alex Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria |
title | Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria |
title_full | Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria |
title_fullStr | Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria |
title_full_unstemmed | Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria |
title_short | Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria |
title_sort | quantitative, model-based estimates of variability in the generation and serial intervals of plasmodium falciparum malaria |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034682/ https://www.ncbi.nlm.nih.gov/pubmed/27660051 http://dx.doi.org/10.1186/s12936-016-1537-6 |
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