Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study
Descripción del Articulo
ARUap:idPdleiaasgencoosntfiicrmtethsatsta(lRlhDeaTdsi)nfgolervceolsroarnearveiprruessednisteedacsoerr(eCcOtlyV: ID) are used in low- and middle- income countries (LMICs) to inform treatment decisions. However, to date, it is unclear when this use is cost-effective. Existing analyses are limited to a...
| Autores: | , , , , , , , , , , , , , , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2024 |
| Institución: | Universidad Peruana de Ciencias Aplicadas |
| Repositorio: | UPC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorioacademico.upc.edu.pe:10757/675812 |
| Enlace del recurso: | http://hdl.handle.net/10757/675812 |
| Nivel de acceso: | acceso abierto |
| Materia: | COVID rapid diagnostic tests critical illness |
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Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study |
| title |
Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study |
| spellingShingle |
Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study Bonnet, Gabrielle COVID rapid diagnostic tests critical illness |
| title_short |
Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study |
| title_full |
Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study |
| title_fullStr |
Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study |
| title_full_unstemmed |
Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study |
| title_sort |
Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study |
| author |
Bonnet, Gabrielle |
| author_facet |
Bonnet, Gabrielle Bimba, John Chavula, Chancy Chifamba, Harunavamwe N. Divala, Titus H. Lescano, Andres G. Majam, Mohammed Mbo, Danjuma Suwantika, Auliya A. Tovar, Marco A. Yadav, Pragya Ekwunife, Obinna Mangenah, Collin Ngwira, Lucky G. Corbett, Elizabeth L. Jit, Mark Vassall, Anna |
| author_role |
author |
| author2 |
Bimba, John Chavula, Chancy Chifamba, Harunavamwe N. Divala, Titus H. Lescano, Andres G. Majam, Mohammed Mbo, Danjuma Suwantika, Auliya A. Tovar, Marco A. Yadav, Pragya Ekwunife, Obinna Mangenah, Collin Ngwira, Lucky G. Corbett, Elizabeth L. Jit, Mark Vassall, Anna |
| author2_role |
author author author author author author author author author author author author author author author author |
| dc.contributor.author.fl_str_mv |
Bonnet, Gabrielle Bimba, John Chavula, Chancy Chifamba, Harunavamwe N. Divala, Titus H. Lescano, Andres G. Majam, Mohammed Mbo, Danjuma Suwantika, Auliya A. Tovar, Marco A. Yadav, Pragya Ekwunife, Obinna Mangenah, Collin Ngwira, Lucky G. Corbett, Elizabeth L. Jit, Mark Vassall, Anna |
| dc.subject.es_PE.fl_str_mv |
COVID rapid diagnostic tests critical illness |
| topic |
COVID rapid diagnostic tests critical illness |
| description |
ARUap:idPdleiaasgencoosntfiicrmtethsatsta(lRlhDeaTdsi)nfgolervceolsroarnearveiprruessednisteedacsoerr(eCcOtlyV: ID) are used in low- and middle- income countries (LMICs) to inform treatment decisions. However, to date, it is unclear when this use is cost-effective. Existing analyses are limited to a narrow set of countries and uses. The aim of this study is to assess the cost-effectiveness of COVID RDTs to inform the treatment of patients with severe illness in LMICs, considering real world practice. We assessed the cost-effectiveness of COVID testing across LMICs using a decision tree model, differentiating results by country income level, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) prevalence, and testing scenario (none, RDTs, polymerase chain reaction tests—PCRs and combinations). LMIC experts defined realistic care pathways and treatment options. Using a healthcare provider perspective and net monetary benefit approach, we assessed both intended (COVID symptom alleviation) and unintended (treatment side effects) health and economic impacts for each testing scenario. We included the side effects of corticosteroids, which are often the only available treatment for COVID. Because side effects depend both on the treatment and the patient’s underlying illness (COVID or COVID-like illnesses, such as influenza), we considered the prevalence of COVID-like illnesses in our analyses. We found that SARS-CoV-2 testing of patients with severe COVID-like illness can be cost-effective in all LMICs, though only in some circumstances. High influenza prevalence among suspected COVID cases improves cost-effectiveness, since incorrectly provided corticosteroids may worsen influenza outcomes. In low- and some lower-middle-income countries, only patients with a high index of suspicion for COVID should be tested with RDTs, while other patients should be presumed to not have COVID. In some lower-middleincome and upper-middle-income countries, suspected severe COVID cases should almost always be tested. Further, in these settings, negative test results in patients with a high initial index of suspicion should be confirmed through PCR and, during influenza outbreaks, positive results in patients with a low initial index of suspicion should also be confirmed with a PCR. The use of interleukin-6 receptor blockers, when supported by testing, may also be cost-effective in higher-income LMICs. The cost at which they would be cost-effective in low-income countries ($162 to $406 per treatment course) is below current prices. The primary limitation of our analysis is substantial uncertainty around some of the parameters in our model due to limited data, most notably on current COVID mortality with standard of care, and insufficient evidence on the impact of corticosteroids on patients with severe influenza. |
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2024 |
| dc.date.accessioned.none.fl_str_mv |
2024-09-21T22:45:28Z |
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2024-09-21T22:45:28Z |
| dc.date.issued.fl_str_mv |
2024-07-01 |
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info:eu-repo/semantics/article |
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15491277 |
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10.1371/journal.pmed.1004429 |
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http://hdl.handle.net/10757/675812 |
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PLoS Medicine |
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However, to date, it is unclear when this use is cost-effective. Existing analyses are limited to a narrow set of countries and uses. The aim of this study is to assess the cost-effectiveness of COVID RDTs to inform the treatment of patients with severe illness in LMICs, considering real world practice. We assessed the cost-effectiveness of COVID testing across LMICs using a decision tree model, differentiating results by country income level, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) prevalence, and testing scenario (none, RDTs, polymerase chain reaction tests—PCRs and combinations). LMIC experts defined realistic care pathways and treatment options. Using a healthcare provider perspective and net monetary benefit approach, we assessed both intended (COVID symptom alleviation) and unintended (treatment side effects) health and economic impacts for each testing scenario. We included the side effects of corticosteroids, which are often the only available treatment for COVID. Because side effects depend both on the treatment and the patient’s underlying illness (COVID or COVID-like illnesses, such as influenza), we considered the prevalence of COVID-like illnesses in our analyses. We found that SARS-CoV-2 testing of patients with severe COVID-like illness can be cost-effective in all LMICs, though only in some circumstances. High influenza prevalence among suspected COVID cases improves cost-effectiveness, since incorrectly provided corticosteroids may worsen influenza outcomes. In low- and some lower-middle-income countries, only patients with a high index of suspicion for COVID should be tested with RDTs, while other patients should be presumed to not have COVID. In some lower-middleincome and upper-middle-income countries, suspected severe COVID cases should almost always be tested. Further, in these settings, negative test results in patients with a high initial index of suspicion should be confirmed through PCR and, during influenza outbreaks, positive results in patients with a low initial index of suspicion should also be confirmed with a PCR. The use of interleukin-6 receptor blockers, when supported by testing, may also be cost-effective in higher-income LMICs. The cost at which they would be cost-effective in low-income countries ($162 to $406 per treatment course) is below current prices. The primary limitation of our analysis is substantial uncertainty around some of the parameters in our model due to limited data, most notably on current COVID mortality with standard of care, and insufficient evidence on the impact of corticosteroids on patients with severe influenza.Fogarty International CenterRevisión por paresapplication/flvengPublic Library of Scienceinfo:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Universidad Peruana de Ciencias Aplicadas (UPC)Repositorio Academico - UPCPLoS Medicine217 Julyreponame:UPC-Institucionalinstname:Universidad Peruana de Ciencias Aplicadasinstacron:UPCCOVIDrapid diagnostic testscritical illnessCost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling studyinfo:eu-repo/semantics/article2024-09-21T22:46:19ZTHUMBNAILjournal.pmed.1004429.pdf.jpgjournal.pmed.1004429.pdf.jpgGenerated Thumbnailimage/jpeg109551https://repositorioacademico.upc.edu.pe/bitstream/10757/675812/5/journal.pmed.1004429.pdf.jpg1ece4459e2eed108086cd926ed74fa6eMD55falseTEXTjournal.pmed.1004429.pdf.txtjournal.pmed.1004429.pdf.txtExtracted texttext/plain59091https://repositorioacademico.upc.edu.pe/bitstream/10757/675812/4/journal.pmed.1004429.pdf.txt7b28109057f5cf023dd4f592e87c499aMD54falseORIGINALjournal.pmed.1004429.pdfjournal.pmed.1004429.pdfapplication/pdf1242858https://repositorioacademico.upc.edu.pe/bitstream/10757/675812/3/journal.pmed.1004429.pdf1a69ef2c95f9d1ab620d60c89d73cd09MD53trueLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorioacademico.upc.edu.pe/bitstream/10757/675812/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52falseCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorioacademico.upc.edu.pe/bitstream/10757/675812/1/license_rdf4460e5956bc1d1639be9ae6146a50347MD51false10757/675812oai:repositorioacademico.upc.edu.pe:10757/6758122024-09-22 05:23:14.266Repositorio académico upcupc@openrepository.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 |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).