Measuring "Fearonomic Effects" in Valuing Therapies: An Application to COVID-19 in China.
Identifieur interne : 000119 ( Main/Exploration ); précédent : 000118; suivant : 000120Measuring "Fearonomic Effects" in Valuing Therapies: An Application to COVID-19 in China.
Auteurs : Siyu Ma [États-Unis] ; David D. Kim [États-Unis] ; Joshua T. Cohen [États-Unis] ; Peter J. Neumann [États-Unis]Source :
- Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research [ 1524-4733 ] ; 2020.
Descripteurs français
- KwdFr :
- MESH :
- Wicri :
- geographic : République populaire de Chine.
English descriptors
- KwdEn :
- MESH :
- geographic : China.
- economics : Coronavirus Infections, Pandemics, Pneumonia, Viral.
- Betacoronavirus, COVID-19, Checklist, Databases, Factual, Fear, Health Policy, Humans, Models, Economic, SARS-CoV-2.
Abstract
OBJECTIVES
To develop a checklist that helps quantify the economic impact associated with fear of contagion and to illustrate how one might use the checklist by presenting a case study featuring China during the coronavirus disease 2019 (COVID-19) outbreak.
METHODS
Based on "fearonomic effects," a qualitative framework that conceptualizes the direct and indirect economic effects caused by the fear of contagion, we created a checklist to facilitate empirical estimation. As a case study, we first identified relevant sectors affected by China's lockdown policies implemented just before the Lunar New Year (LNY) week. To quantify the immediate impact, we then estimated the projected spending levels in 2020 in the absence of COVID-19 and compared these projections with actual spending during the LNY week. Data sources used include Chinese and global websites. To characterize uncertainty, we reported upper and lower bound estimates and calculated midpoints for each range.
RESULTS
The COVID-19 epidemic is estimated to cost China's economy $283 billion ($196-369 billion), that is, ¥2.0 trillion renminbi (¥1.4-¥2.6 trillion), during the LNY week. Reduced restaurant and movie theater business ($106 [$103-$109] billion, 37.5% [36.4%-38.5%]) and reduced public transportation utilization ($96 [$13-$179] billion dollars, 33.9% [4.6%-63.3%]) explain most of this loss, followed by travel restrictions and the resulting loss of hotel business and tourism ($80.36 billion, 28.4%).
CONCLUSION
Our checklist can help quantify the immediate and near-term impact of COVID-19 on a country's economy. It can also help researchers and policy makers consider the broader economic and social consequences when valuing future vaccines and treatments.
DOI: 10.1016/j.jval.2020.06.002
PubMed: 33127009
PubMed Central: PMC7384788
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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<term>Checklist (MeSH)</term>
<term>China (MeSH)</term>
<term>Coronavirus Infections (economics)</term>
<term>Databases, Factual (MeSH)</term>
<term>Fear (MeSH)</term>
<term>Health Policy (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Models, Economic (MeSH)</term>
<term>Pandemics (economics)</term>
<term>Pneumonia, Viral (economics)</term>
<term>SARS-CoV-2 (MeSH)</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Bases de données factuelles (MeSH)</term>
<term>Betacoronavirus (MeSH)</term>
<term>Chine (MeSH)</term>
<term>Humains (MeSH)</term>
<term>Infections à coronavirus (économie)</term>
<term>Liste de contrôle (MeSH)</term>
<term>Modèles économiques (MeSH)</term>
<term>Pandémies (économie)</term>
<term>Peur (MeSH)</term>
<term>Pneumopathie virale (économie)</term>
<term>Politique de santé (MeSH)</term>
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<keywords scheme="MESH" type="geographic" xml:lang="en"><term>China</term>
</keywords>
<keywords scheme="MESH" qualifier="economics" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pandemics</term>
<term>Pneumonia, Viral</term>
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<term>COVID-19</term>
<term>Checklist</term>
<term>Databases, Factual</term>
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<term>Health Policy</term>
<term>Humans</term>
<term>Models, Economic</term>
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<term>Betacoronavirus</term>
<term>Chine</term>
<term>Humains</term>
<term>Liste de contrôle</term>
<term>Modèles économiques</term>
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<front><div type="abstract" xml:lang="en"><p><b>OBJECTIVES</b>
</p>
<p>To develop a checklist that helps quantify the economic impact associated with fear of contagion and to illustrate how one might use the checklist by presenting a case study featuring China during the coronavirus disease 2019 (COVID-19) outbreak.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>Based on "fearonomic effects," a qualitative framework that conceptualizes the direct and indirect economic effects caused by the fear of contagion, we created a checklist to facilitate empirical estimation. As a case study, we first identified relevant sectors affected by China's lockdown policies implemented just before the Lunar New Year (LNY) week. To quantify the immediate impact, we then estimated the projected spending levels in 2020 in the absence of COVID-19 and compared these projections with actual spending during the LNY week. Data sources used include Chinese and global websites. To characterize uncertainty, we reported upper and lower bound estimates and calculated midpoints for each range.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>The COVID-19 epidemic is estimated to cost China's economy $283 billion ($196-369 billion), that is, ¥2.0 trillion renminbi (¥1.4-¥2.6 trillion), during the LNY week. Reduced restaurant and movie theater business ($106 [$103-$109] billion, 37.5% [36.4%-38.5%]) and reduced public transportation utilization ($96 [$13-$179] billion dollars, 33.9% [4.6%-63.3%]) explain most of this loss, followed by travel restrictions and the resulting loss of hotel business and tourism ($80.36 billion, 28.4%).</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSION</b>
</p>
<p>Our checklist can help quantify the immediate and near-term impact of COVID-19 on a country's economy. It can also help researchers and policy makers consider the broader economic and social consequences when valuing future vaccines and treatments.</p>
</div>
</front>
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<Abstract><AbstractText Label="OBJECTIVES">To develop a checklist that helps quantify the economic impact associated with fear of contagion and to illustrate how one might use the checklist by presenting a case study featuring China during the coronavirus disease 2019 (COVID-19) outbreak.</AbstractText>
<AbstractText Label="METHODS">Based on "fearonomic effects," a qualitative framework that conceptualizes the direct and indirect economic effects caused by the fear of contagion, we created a checklist to facilitate empirical estimation. As a case study, we first identified relevant sectors affected by China's lockdown policies implemented just before the Lunar New Year (LNY) week. To quantify the immediate impact, we then estimated the projected spending levels in 2020 in the absence of COVID-19 and compared these projections with actual spending during the LNY week. Data sources used include Chinese and global websites. To characterize uncertainty, we reported upper and lower bound estimates and calculated midpoints for each range.</AbstractText>
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