Likely health outcomes for untreated acute febrile illness in the tropics in decision and economic models; a Delphi survey
Modelling is widely used to inform decisions about management of malaria and acute febrile illnesses. Most models depend on estimates of the probability that untreated patients with malaria or bacterial illnesses will progress to severe disease or death. However, data on these key parameters are lac...
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| Veröffentlicht in: | PloS one 2011-02, Vol.6 (2), p.e17439-e17439 |
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| creator | Lubell, Yoel Staedke, Sarah G Greenwood, Brian M Kamya, Moses R Molyneux, Malcolm Newton, Paul N Reyburn, Hugh Snow, Robert W D'Alessandro, Umberto English, Mike Day, Nick Kremsner, Peter Dondorp, Arjen Mbacham, Wilfred Dorsey, Grant Owusu-Agyei, Seth Maitland, Kathryn Krishna, Sanjeev Newton, Charles Pasvol, Geoffrey Taylor, Terrie von Seidlein, Lorenz White, Nicholas J Binka, Fred Mills, Anne Whitty, Christopher J M |
| description | Modelling is widely used to inform decisions about management of malaria and acute febrile illnesses. Most models depend on estimates of the probability that untreated patients with malaria or bacterial illnesses will progress to severe disease or death. However, data on these key parameters are lacking and assumptions are frequently made based on expert opinion. Widely diverse opinions can lead to conflicting outcomes in models they inform.
A Delphi survey was conducted with malaria experts aiming to reach consensus on key parameters for public health and economic models, relating to the outcome of untreated febrile illnesses. Survey questions were stratified by malaria transmission intensity, patient age, and HIV prevalence. The impact of the variability in opinion on decision models is illustrated with a model previously used to assess the cost-effectiveness of malaria rapid diagnostic tests. Some consensus was reached around the probability that patients from higher transmission settings with untreated malaria would progress to severe disease (median 3%, inter-quartile range (IQR) 1-5%), and the probability that a non-malaria illness required antibiotics in areas of low HIV prevalence (median 20%). Children living in low transmission areas were considered to be at higher risk of progressing to severe malaria (median 30%, IQR 10-58%) than those from higher transmission areas (median 13%, IQR 7-30%). Estimates of the probability of dying from severe malaria were high in all settings (medians 60-73%). However, opinions varied widely for most parameters, and did not converge on resurveying.
This study highlights the uncertainty around potential consequences of untreated malaria and bacterial illnesses. The lack of consensus on most parameters, the wide range of estimates, and the impact of variability in estimates on model outputs, demonstrate the importance of sensitivity analysis for decision models employing expert opinion. Results of such models should be interpreted cautiously. The diversity of expert opinion should be recognised when policy options are debated. |
| doi_str_mv | 10.1371/journal.pone.0017439 |
| format | Article |
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A Delphi survey was conducted with malaria experts aiming to reach consensus on key parameters for public health and economic models, relating to the outcome of untreated febrile illnesses. Survey questions were stratified by malaria transmission intensity, patient age, and HIV prevalence. The impact of the variability in opinion on decision models is illustrated with a model previously used to assess the cost-effectiveness of malaria rapid diagnostic tests. Some consensus was reached around the probability that patients from higher transmission settings with untreated malaria would progress to severe disease (median 3%, inter-quartile range (IQR) 1-5%), and the probability that a non-malaria illness required antibiotics in areas of low HIV prevalence (median 20%). Children living in low transmission areas were considered to be at higher risk of progressing to severe malaria (median 30%, IQR 10-58%) than those from higher transmission areas (median 13%, IQR 7-30%). Estimates of the probability of dying from severe malaria were high in all settings (medians 60-73%). However, opinions varied widely for most parameters, and did not converge on resurveying.
This study highlights the uncertainty around potential consequences of untreated malaria and bacterial illnesses. The lack of consensus on most parameters, the wide range of estimates, and the impact of variability in estimates on model outputs, demonstrate the importance of sensitivity analysis for decision models employing expert opinion. Results of such models should be interpreted cautiously. The diversity of expert opinion should be recognised when policy options are debated.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0017439</identifier><identifier>PMID: 21390277</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acute Disease ; Adolescent ; Adult ; Antibiotics ; Bacteria ; Case management ; Child ; Child, Preschool ; Children ; Collaboration ; Cost analysis ; Critical Illness - economics ; Critical Illness - epidemiology ; Critical Illness - therapy ; Decision analysis ; Decision making ; Decision Support Techniques ; Delphi Technique ; Diagnostic systems ; Diagnostic tests ; Disease Progression ; Disease transmission ; Economic analysis ; Economic aspects ; Economic models ; Epidemiology ; Estimates ; Experts ; Fever - complications ; Fever - diagnosis ; Fever - economics ; Fever - epidemiology ; Health ; Health aspects ; Health visiting ; Hospitals ; Humans ; Hygiene ; Illnesses ; Infant ; Infant, Newborn ; Malaria ; Malaria - diagnosis ; Malaria - economics ; Malaria - epidemiology ; Mathematical models ; Medical research ; Medicine ; Midwifery ; Models, Economic ; Mortality ; Nursing ; Outcome Assessment (Health Care) - methods ; Outcome Assessment (Health Care) - statistics & numerical data ; Parameter estimation ; Patients ; Physicians ; Pneumonia ; Probability ; Prognosis ; Public health ; Sensitivity analysis ; Surveys ; Tropical Climate ; Tropical environments ; Variability ; Vector-borne diseases ; Young Adult</subject><ispartof>PloS one, 2011-02, Vol.6 (2), p.e17439-e17439</ispartof><rights>COPYRIGHT 2011 Public Library of Science</rights><rights>2011 Lubell et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Lubell et al. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c691t-c9ee810dddf3820bcf7627784cbb768be86ec9f0b06d54c3265e5b022b3e2be53</citedby><cites>FETCH-LOGICAL-c691t-c9ee810dddf3820bcf7627784cbb768be86ec9f0b06d54c3265e5b022b3e2be53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3044764/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3044764/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,2096,2915,23847,27905,27906,53772,53774,79349,79350</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21390277$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Snounou, Georges</contributor><creatorcontrib>Lubell, Yoel</creatorcontrib><creatorcontrib>Staedke, Sarah G</creatorcontrib><creatorcontrib>Greenwood, Brian M</creatorcontrib><creatorcontrib>Kamya, Moses R</creatorcontrib><creatorcontrib>Molyneux, Malcolm</creatorcontrib><creatorcontrib>Newton, Paul N</creatorcontrib><creatorcontrib>Reyburn, Hugh</creatorcontrib><creatorcontrib>Snow, Robert W</creatorcontrib><creatorcontrib>D'Alessandro, Umberto</creatorcontrib><creatorcontrib>English, Mike</creatorcontrib><creatorcontrib>Day, Nick</creatorcontrib><creatorcontrib>Kremsner, Peter</creatorcontrib><creatorcontrib>Dondorp, Arjen</creatorcontrib><creatorcontrib>Mbacham, Wilfred</creatorcontrib><creatorcontrib>Dorsey, Grant</creatorcontrib><creatorcontrib>Owusu-Agyei, Seth</creatorcontrib><creatorcontrib>Maitland, Kathryn</creatorcontrib><creatorcontrib>Krishna, Sanjeev</creatorcontrib><creatorcontrib>Newton, Charles</creatorcontrib><creatorcontrib>Pasvol, Geoffrey</creatorcontrib><creatorcontrib>Taylor, Terrie</creatorcontrib><creatorcontrib>von Seidlein, Lorenz</creatorcontrib><creatorcontrib>White, Nicholas J</creatorcontrib><creatorcontrib>Binka, Fred</creatorcontrib><creatorcontrib>Mills, Anne</creatorcontrib><creatorcontrib>Whitty, Christopher J M</creatorcontrib><title>Likely health outcomes for untreated acute febrile illness in the tropics in decision and economic models; a Delphi survey</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Modelling is widely used to inform decisions about management of malaria and acute febrile illnesses. Most models depend on estimates of the probability that untreated patients with malaria or bacterial illnesses will progress to severe disease or death. However, data on these key parameters are lacking and assumptions are frequently made based on expert opinion. Widely diverse opinions can lead to conflicting outcomes in models they inform.
A Delphi survey was conducted with malaria experts aiming to reach consensus on key parameters for public health and economic models, relating to the outcome of untreated febrile illnesses. Survey questions were stratified by malaria transmission intensity, patient age, and HIV prevalence. The impact of the variability in opinion on decision models is illustrated with a model previously used to assess the cost-effectiveness of malaria rapid diagnostic tests. Some consensus was reached around the probability that patients from higher transmission settings with untreated malaria would progress to severe disease (median 3%, inter-quartile range (IQR) 1-5%), and the probability that a non-malaria illness required antibiotics in areas of low HIV prevalence (median 20%). Children living in low transmission areas were considered to be at higher risk of progressing to severe malaria (median 30%, IQR 10-58%) than those from higher transmission areas (median 13%, IQR 7-30%). Estimates of the probability of dying from severe malaria were high in all settings (medians 60-73%). However, opinions varied widely for most parameters, and did not converge on resurveying.
This study highlights the uncertainty around potential consequences of untreated malaria and bacterial illnesses. The lack of consensus on most parameters, the wide range of estimates, and the impact of variability in estimates on model outputs, demonstrate the importance of sensitivity analysis for decision models employing expert opinion. Results of such models should be interpreted cautiously. The diversity of expert opinion should be recognised when policy options are debated.</description><subject>Acute Disease</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Antibiotics</subject><subject>Bacteria</subject><subject>Case management</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Collaboration</subject><subject>Cost analysis</subject><subject>Critical Illness - economics</subject><subject>Critical Illness - epidemiology</subject><subject>Critical Illness - therapy</subject><subject>Decision analysis</subject><subject>Decision making</subject><subject>Decision Support Techniques</subject><subject>Delphi Technique</subject><subject>Diagnostic systems</subject><subject>Diagnostic tests</subject><subject>Disease Progression</subject><subject>Disease transmission</subject><subject>Economic analysis</subject><subject>Economic aspects</subject><subject>Economic models</subject><subject>Epidemiology</subject><subject>Estimates</subject><subject>Experts</subject><subject>Fever - complications</subject><subject>Fever - diagnosis</subject><subject>Fever - economics</subject><subject>Fever - epidemiology</subject><subject>Health</subject><subject>Health aspects</subject><subject>Health visiting</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Hygiene</subject><subject>Illnesses</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Malaria</subject><subject>Malaria - diagnosis</subject><subject>Malaria - economics</subject><subject>Malaria - epidemiology</subject><subject>Mathematical models</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Midwifery</subject><subject>Models, Economic</subject><subject>Mortality</subject><subject>Nursing</subject><subject>Outcome Assessment (Health Care) - methods</subject><subject>Outcome Assessment (Health Care) - statistics & numerical data</subject><subject>Parameter estimation</subject><subject>Patients</subject><subject>Physicians</subject><subject>Pneumonia</subject><subject>Probability</subject><subject>Prognosis</subject><subject>Public health</subject><subject>Sensitivity analysis</subject><subject>Surveys</subject><subject>Tropical Climate</subject><subject>Tropical environments</subject><subject>Variability</subject><subject>Vector-borne diseases</subject><subject>Young 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health outcomes for untreated acute febrile illness in the tropics in decision and economic models; a Delphi survey</title><author>Lubell, Yoel ; Staedke, Sarah G ; Greenwood, Brian M ; Kamya, Moses R ; Molyneux, Malcolm ; Newton, Paul N ; Reyburn, Hugh ; Snow, Robert W ; D'Alessandro, Umberto ; English, Mike ; Day, Nick ; Kremsner, Peter ; Dondorp, Arjen ; Mbacham, Wilfred ; Dorsey, Grant ; Owusu-Agyei, Seth ; Maitland, Kathryn ; Krishna, Sanjeev ; Newton, Charles ; Pasvol, Geoffrey ; Taylor, Terrie ; von Seidlein, Lorenz ; White, Nicholas J ; Binka, Fred ; Mills, Anne ; Whitty, Christopher J M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c691t-c9ee810dddf3820bcf7627784cbb768be86ec9f0b06d54c3265e5b022b3e2be53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Acute 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Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lubell, Yoel</au><au>Staedke, Sarah G</au><au>Greenwood, Brian M</au><au>Kamya, Moses R</au><au>Molyneux, Malcolm</au><au>Newton, Paul N</au><au>Reyburn, Hugh</au><au>Snow, Robert W</au><au>D'Alessandro, Umberto</au><au>English, Mike</au><au>Day, Nick</au><au>Kremsner, Peter</au><au>Dondorp, Arjen</au><au>Mbacham, Wilfred</au><au>Dorsey, Grant</au><au>Owusu-Agyei, Seth</au><au>Maitland, Kathryn</au><au>Krishna, Sanjeev</au><au>Newton, Charles</au><au>Pasvol, Geoffrey</au><au>Taylor, Terrie</au><au>von Seidlein, Lorenz</au><au>White, Nicholas J</au><au>Binka, Fred</au><au>Mills, Anne</au><au>Whitty, Christopher J M</au><au>Snounou, Georges</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Likely health outcomes for untreated acute febrile illness in the tropics in decision and economic models; a Delphi survey</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2011-02-24</date><risdate>2011</risdate><volume>6</volume><issue>2</issue><spage>e17439</spage><epage>e17439</epage><pages>e17439-e17439</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Modelling is widely used to inform decisions about management of malaria and acute febrile illnesses. Most models depend on estimates of the probability that untreated patients with malaria or bacterial illnesses will progress to severe disease or death. However, data on these key parameters are lacking and assumptions are frequently made based on expert opinion. Widely diverse opinions can lead to conflicting outcomes in models they inform.
A Delphi survey was conducted with malaria experts aiming to reach consensus on key parameters for public health and economic models, relating to the outcome of untreated febrile illnesses. Survey questions were stratified by malaria transmission intensity, patient age, and HIV prevalence. The impact of the variability in opinion on decision models is illustrated with a model previously used to assess the cost-effectiveness of malaria rapid diagnostic tests. Some consensus was reached around the probability that patients from higher transmission settings with untreated malaria would progress to severe disease (median 3%, inter-quartile range (IQR) 1-5%), and the probability that a non-malaria illness required antibiotics in areas of low HIV prevalence (median 20%). Children living in low transmission areas were considered to be at higher risk of progressing to severe malaria (median 30%, IQR 10-58%) than those from higher transmission areas (median 13%, IQR 7-30%). Estimates of the probability of dying from severe malaria were high in all settings (medians 60-73%). However, opinions varied widely for most parameters, and did not converge on resurveying.
This study highlights the uncertainty around potential consequences of untreated malaria and bacterial illnesses. The lack of consensus on most parameters, the wide range of estimates, and the impact of variability in estimates on model outputs, demonstrate the importance of sensitivity analysis for decision models employing expert opinion. Results of such models should be interpreted cautiously. The diversity of expert opinion should be recognised when policy options are debated.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21390277</pmid><doi>10.1371/journal.pone.0017439</doi><tpages>e17439</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2011-02, Vol.6 (2), p.e17439-e17439 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1312192494 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Acute Disease Adolescent Adult Antibiotics Bacteria Case management Child Child, Preschool Children Collaboration Cost analysis Critical Illness - economics Critical Illness - epidemiology Critical Illness - therapy Decision analysis Decision making Decision Support Techniques Delphi Technique Diagnostic systems Diagnostic tests Disease Progression Disease transmission Economic analysis Economic aspects Economic models Epidemiology Estimates Experts Fever - complications Fever - diagnosis Fever - economics Fever - epidemiology Health Health aspects Health visiting Hospitals Humans Hygiene Illnesses Infant Infant, Newborn Malaria Malaria - diagnosis Malaria - economics Malaria - epidemiology Mathematical models Medical research Medicine Midwifery Models, Economic Mortality Nursing Outcome Assessment (Health Care) - methods Outcome Assessment (Health Care) - statistics & numerical data Parameter estimation Patients Physicians Pneumonia Probability Prognosis Public health Sensitivity analysis Surveys Tropical Climate Tropical environments Variability Vector-borne diseases Young Adult |
| title | Likely health outcomes for untreated acute febrile illness in the tropics in decision and economic models; a Delphi survey |
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