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A dynamic model for estimating adult female mortality from ovarian dissection data for the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe
Human and animal trypanosomiasis, spread by tsetse flies (Glossina spp), is a major public health concern in much of sub-Saharan Africa. The basic reproduction number of vector-borne diseases, such as trypanosomiasis, is a function of vector mortality rate. Robust methods for estimating tsetse morta...
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Published in: | PLoS neglected tropical diseases 2017-08, Vol.11 (8), p.e0005813 |
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description | Human and animal trypanosomiasis, spread by tsetse flies (Glossina spp), is a major public health concern in much of sub-Saharan Africa. The basic reproduction number of vector-borne diseases, such as trypanosomiasis, is a function of vector mortality rate. Robust methods for estimating tsetse mortality are thus of interest for understanding population and disease dynamics and for optimal control. Existing methods for estimating mortality in adult tsetse, from ovarian dissection data, often use invalid assumptions of the existence of a stable age distribution, and age-invariant mortality and capture probability. We develop a dynamic model to estimate tsetse mortality from ovarian dissection data in populations where the age distribution is not necessarily stable. The models correspond to several hypotheses about how temperature affects mortality: no temperature dependence (model 1), identical temperature dependence for mature adults and immature stages, i.e., pupae and newly emerged adults (model 2), and differential temperature dependence for mature adults and immature stages (model 3). We fit our models to ovarian dissection data for G. pallidipes collected at Rekomitjie Research Station in the Zambezi Valley in Zimbabwe. We compare model fits to determine the most probable model, given the data, by calculating the Akaike Information Criterion (AIC) for each model. The model that allows for a differential dependence of temperature on mortality for immature stages and mature adults (model 3) performs significantly better than models 1 and 2. All models produce mortality estimates, for mature adults, of approximately 3% per day for mean daily temperatures below 25°C, consistent with those of mark-recapture studies performed in other settings. For temperatures greater than 25°C, mortality among immature classes of tsetse increases substantially, whereas mortality remains roughly constant for mature adults. As a sensitivity analysis, model 3 was simultaneously fit to both the ovarian dissection and trap data; while this fit also produces comparable mortality at temperatures below 25°C, it is not possible to obtain good fits to both data sources simultaneously, highlighting the uncertain correspondence between trap catches and population levels and/or the need for further improvements to our model. The modelling approach employed here could be applied to any substantial time series of age distribution data. |
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The basic reproduction number of vector-borne diseases, such as trypanosomiasis, is a function of vector mortality rate. Robust methods for estimating tsetse mortality are thus of interest for understanding population and disease dynamics and for optimal control. Existing methods for estimating mortality in adult tsetse, from ovarian dissection data, often use invalid assumptions of the existence of a stable age distribution, and age-invariant mortality and capture probability. We develop a dynamic model to estimate tsetse mortality from ovarian dissection data in populations where the age distribution is not necessarily stable. The models correspond to several hypotheses about how temperature affects mortality: no temperature dependence (model 1), identical temperature dependence for mature adults and immature stages, i.e., pupae and newly emerged adults (model 2), and differential temperature dependence for mature adults and immature stages (model 3). We fit our models to ovarian dissection data for G. pallidipes collected at Rekomitjie Research Station in the Zambezi Valley in Zimbabwe. We compare model fits to determine the most probable model, given the data, by calculating the Akaike Information Criterion (AIC) for each model. The model that allows for a differential dependence of temperature on mortality for immature stages and mature adults (model 3) performs significantly better than models 1 and 2. All models produce mortality estimates, for mature adults, of approximately 3% per day for mean daily temperatures below 25°C, consistent with those of mark-recapture studies performed in other settings. For temperatures greater than 25°C, mortality among immature classes of tsetse increases substantially, whereas mortality remains roughly constant for mature adults. As a sensitivity analysis, model 3 was simultaneously fit to both the ovarian dissection and trap data; while this fit also produces comparable mortality at temperatures below 25°C, it is not possible to obtain good fits to both data sources simultaneously, highlighting the uncertain correspondence between trap catches and population levels and/or the need for further improvements to our model. The modelling approach employed here could be applied to any substantial time series of age distribution data.</description><identifier>ISSN: 1935-2735</identifier><identifier>ISSN: 1935-2727</identifier><identifier>EISSN: 1935-2735</identifier><identifier>DOI: 10.1371/journal.pntd.0005813</identifier><identifier>PMID: 28854189</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adults ; Age ; Age composition ; Animals ; Biology and Life Sciences ; Control methods ; Data ; Disease ; Disease control ; Dissection ; Distribution ; Dynamics ; Economic models ; Epidemiology ; Estimates ; Estimation ; Female ; Laboratories ; Medicine and Health Sciences ; Modelling ; Models, Biological ; Mortality ; Mosquitoes ; Optimal control ; Ovaries ; Ovary - physiology ; People and Places ; Population ; Population Dynamics ; Population levels ; Probability theory ; Prognosis ; Public health ; Pupa - growth & development ; Pupa - parasitology ; Pupae ; Seasons ; Sensitivity analysis ; South Africa ; Specimen Handling ; Temperature ; Temperature dependence ; Temperature effects ; Tropical diseases ; Trypanosomiasis ; Tsetse Flies - growth & development ; Tsetse Flies - parasitology ; United States ; Valleys ; Vector-borne diseases ; Zimbabwe</subject><ispartof>PLoS neglected tropical diseases, 2017-08, Vol.11 (8), p.e0005813</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Austen sampled in Zimbabwe. PLoS Negl Trop Dis 11(8): e0005813. https://doi.org/10.1371/journal.pntd.0005813</rights><rights>2017 Ackley, Hargrove 2017 Ackley, Hargrove</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Austen sampled in Zimbabwe. PLoS Negl Trop Dis 11(8): e0005813. https://doi.org/10.1371/journal.pntd.0005813</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c624t-62980fa1f2e2113e8cdc5ffa7dc1de6055f254cce4032e4c143dd86f6ad974943</citedby><cites>FETCH-LOGICAL-c624t-62980fa1f2e2113e8cdc5ffa7dc1de6055f254cce4032e4c143dd86f6ad974943</cites><orcidid>0000-0003-0181-6063</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1939436105/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1939436105?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28854189$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Valenzuela, Jesus G.</contributor><creatorcontrib>Ackley, Sarah F</creatorcontrib><creatorcontrib>Hargrove, John W</creatorcontrib><title>A dynamic model for estimating adult female mortality from ovarian dissection data for the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe</title><title>PLoS neglected tropical diseases</title><addtitle>PLoS Negl Trop Dis</addtitle><description>Human and animal trypanosomiasis, spread by tsetse flies (Glossina spp), is a major public health concern in much of sub-Saharan Africa. The basic reproduction number of vector-borne diseases, such as trypanosomiasis, is a function of vector mortality rate. Robust methods for estimating tsetse mortality are thus of interest for understanding population and disease dynamics and for optimal control. Existing methods for estimating mortality in adult tsetse, from ovarian dissection data, often use invalid assumptions of the existence of a stable age distribution, and age-invariant mortality and capture probability. We develop a dynamic model to estimate tsetse mortality from ovarian dissection data in populations where the age distribution is not necessarily stable. The models correspond to several hypotheses about how temperature affects mortality: no temperature dependence (model 1), identical temperature dependence for mature adults and immature stages, i.e., pupae and newly emerged adults (model 2), and differential temperature dependence for mature adults and immature stages (model 3). We fit our models to ovarian dissection data for G. pallidipes collected at Rekomitjie Research Station in the Zambezi Valley in Zimbabwe. We compare model fits to determine the most probable model, given the data, by calculating the Akaike Information Criterion (AIC) for each model. The model that allows for a differential dependence of temperature on mortality for immature stages and mature adults (model 3) performs significantly better than models 1 and 2. All models produce mortality estimates, for mature adults, of approximately 3% per day for mean daily temperatures below 25°C, consistent with those of mark-recapture studies performed in other settings. For temperatures greater than 25°C, mortality among immature classes of tsetse increases substantially, whereas mortality remains roughly constant for mature adults. As a sensitivity analysis, model 3 was simultaneously fit to both the ovarian dissection and trap data; while this fit also produces comparable mortality at temperatures below 25°C, it is not possible to obtain good fits to both data sources simultaneously, highlighting the uncertain correspondence between trap catches and population levels and/or the need for further improvements to our model. The modelling approach employed here could be applied to any substantial time series of age distribution data.</description><subject>Adults</subject><subject>Age</subject><subject>Age composition</subject><subject>Animals</subject><subject>Biology and Life Sciences</subject><subject>Control methods</subject><subject>Data</subject><subject>Disease</subject><subject>Disease control</subject><subject>Dissection</subject><subject>Distribution</subject><subject>Dynamics</subject><subject>Economic models</subject><subject>Epidemiology</subject><subject>Estimates</subject><subject>Estimation</subject><subject>Female</subject><subject>Laboratories</subject><subject>Medicine and Health Sciences</subject><subject>Modelling</subject><subject>Models, Biological</subject><subject>Mortality</subject><subject>Mosquitoes</subject><subject>Optimal control</subject><subject>Ovaries</subject><subject>Ovary - physiology</subject><subject>People and Places</subject><subject>Population</subject><subject>Population Dynamics</subject><subject>Population levels</subject><subject>Probability theory</subject><subject>Prognosis</subject><subject>Public health</subject><subject>Pupa - growth & development</subject><subject>Pupa - parasitology</subject><subject>Pupae</subject><subject>Seasons</subject><subject>Sensitivity analysis</subject><subject>South Africa</subject><subject>Specimen Handling</subject><subject>Temperature</subject><subject>Temperature dependence</subject><subject>Temperature effects</subject><subject>Tropical diseases</subject><subject>Trypanosomiasis</subject><subject>Tsetse Flies - growth & development</subject><subject>Tsetse Flies - parasitology</subject><subject>United States</subject><subject>Valleys</subject><subject>Vector-borne diseases</subject><subject>Zimbabwe</subject><issn>1935-2735</issn><issn>1935-2727</issn><issn>1935-2735</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkt9qFDEUxgdRbK2-gWhAEG92nWSS-XNTWIrWQsEbvfEmnE1OdlMyyZpkKvsePrDZ7bZ0pUxgQvI7X06-fFX1ltZz2nT0802Yogc33_is53Vdi542z6pTOjRixrpGPH80P6lepXRTmKFQL6sT1veC0344rf4uiN56GK0iY9DoiAmRYMp2hGz9ioCeXCYGR3BYiJjB2bwlJoaRhFuIFjzRNiVU2YYyhQx7ibxGkhOWQYzbkksXUrIeyAacs9puMJHFlDJ6kmDcONTEevLLjktY_sHX1QsDLuGbw_-s-vn1y4-Lb7Pr75dXF4vrmWoZz7OWDX1tgBqGjNIGe6WVMAY6rajGthbCMMGVQl43DLmivNG6b00Leuj4wJuz6v2d7qa0Jw-GJllsK5strUUhru4IHeBGbmKxJW5lACv3CyGuJMRslUM5LLE3uluKoVOcKQ6ma1quOR0MN9D0Rev8cNq0HFEr9DmCOxI93vF2LVfhVgrRtW3LisCng0AMv6fySHK0SaFz4DFM-74561lb72724T_06dsdqFV5XWm9CeVctROVC1Ez0faM7rTmT1Dl01hiEzwaW9aPCj4-KlgjuLxOwU27hKRjkN-BKpZ4RDQPZtBa7kJ-37XchVweQl7K3j028qHoPtXNPzgq-9U</recordid><startdate>20170801</startdate><enddate>20170801</enddate><creator>Ackley, Sarah F</creator><creator>Hargrove, John W</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7SS</scope><scope>7T2</scope><scope>7T7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>H95</scope><scope>H97</scope><scope>K9.</scope><scope>L.G</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-0181-6063</orcidid></search><sort><creationdate>20170801</creationdate><title>A dynamic model for estimating adult female mortality from ovarian dissection data for the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe</title><author>Ackley, Sarah F ; Hargrove, John W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c624t-62980fa1f2e2113e8cdc5ffa7dc1de6055f254cce4032e4c143dd86f6ad974943</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adults</topic><topic>Age</topic><topic>Age composition</topic><topic>Animals</topic><topic>Biology and Life Sciences</topic><topic>Control methods</topic><topic>Data</topic><topic>Disease</topic><topic>Disease control</topic><topic>Dissection</topic><topic>Distribution</topic><topic>Dynamics</topic><topic>Economic models</topic><topic>Epidemiology</topic><topic>Estimates</topic><topic>Estimation</topic><topic>Female</topic><topic>Laboratories</topic><topic>Medicine and Health Sciences</topic><topic>Modelling</topic><topic>Models, Biological</topic><topic>Mortality</topic><topic>Mosquitoes</topic><topic>Optimal control</topic><topic>Ovaries</topic><topic>Ovary - physiology</topic><topic>People and Places</topic><topic>Population</topic><topic>Population Dynamics</topic><topic>Population levels</topic><topic>Probability theory</topic><topic>Prognosis</topic><topic>Public health</topic><topic>Pupa - growth & development</topic><topic>Pupa - parasitology</topic><topic>Pupae</topic><topic>Seasons</topic><topic>Sensitivity analysis</topic><topic>South Africa</topic><topic>Specimen Handling</topic><topic>Temperature</topic><topic>Temperature dependence</topic><topic>Temperature effects</topic><topic>Tropical diseases</topic><topic>Trypanosomiasis</topic><topic>Tsetse Flies - growth & development</topic><topic>Tsetse Flies - parasitology</topic><topic>United States</topic><topic>Valleys</topic><topic>Vector-borne diseases</topic><topic>Zimbabwe</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ackley, Sarah F</creatorcontrib><creatorcontrib>Hargrove, John W</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest - 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The basic reproduction number of vector-borne diseases, such as trypanosomiasis, is a function of vector mortality rate. Robust methods for estimating tsetse mortality are thus of interest for understanding population and disease dynamics and for optimal control. Existing methods for estimating mortality in adult tsetse, from ovarian dissection data, often use invalid assumptions of the existence of a stable age distribution, and age-invariant mortality and capture probability. We develop a dynamic model to estimate tsetse mortality from ovarian dissection data in populations where the age distribution is not necessarily stable. The models correspond to several hypotheses about how temperature affects mortality: no temperature dependence (model 1), identical temperature dependence for mature adults and immature stages, i.e., pupae and newly emerged adults (model 2), and differential temperature dependence for mature adults and immature stages (model 3). We fit our models to ovarian dissection data for G. pallidipes collected at Rekomitjie Research Station in the Zambezi Valley in Zimbabwe. We compare model fits to determine the most probable model, given the data, by calculating the Akaike Information Criterion (AIC) for each model. The model that allows for a differential dependence of temperature on mortality for immature stages and mature adults (model 3) performs significantly better than models 1 and 2. All models produce mortality estimates, for mature adults, of approximately 3% per day for mean daily temperatures below 25°C, consistent with those of mark-recapture studies performed in other settings. For temperatures greater than 25°C, mortality among immature classes of tsetse increases substantially, whereas mortality remains roughly constant for mature adults. As a sensitivity analysis, model 3 was simultaneously fit to both the ovarian dissection and trap data; while this fit also produces comparable mortality at temperatures below 25°C, it is not possible to obtain good fits to both data sources simultaneously, highlighting the uncertain correspondence between trap catches and population levels and/or the need for further improvements to our model. The modelling approach employed here could be applied to any substantial time series of age distribution data.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28854189</pmid><doi>10.1371/journal.pntd.0005813</doi><orcidid>https://orcid.org/0000-0003-0181-6063</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adults Age Age composition Animals Biology and Life Sciences Control methods Data Disease Disease control Dissection Distribution Dynamics Economic models Epidemiology Estimates Estimation Female Laboratories Medicine and Health Sciences Modelling Models, Biological Mortality Mosquitoes Optimal control Ovaries Ovary - physiology People and Places Population Population Dynamics Population levels Probability theory Prognosis Public health Pupa - growth & development Pupa - parasitology Pupae Seasons Sensitivity analysis South Africa Specimen Handling Temperature Temperature dependence Temperature effects Tropical diseases Trypanosomiasis Tsetse Flies - growth & development Tsetse Flies - parasitology United States Valleys Vector-borne diseases Zimbabwe |
title | A dynamic model for estimating adult female mortality from ovarian dissection data for the tsetse fly Glossina pallidipes Austen sampled in Zimbabwe |
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