using societal values to inform public health policy during the covid 19 pandemic CORD-Papers-2022-06-02 (Version 1)

Title: Using Societal Values to Inform Public Health Policy During the COVID-19 Pandemic: The Role of Health Preference Research
Published: 2021-04-22
Journal: Patient
DOI: 10.1007/s40271-021-00516-0
DOI_URL: http://doi.org/10.1007/s40271-021-00516-0
Author Name: DiSantostefano Rachael L
Author link: https://covid19-data.nist.gov/pid/rest/local/author/disantostefano_rachael_l
Author Name: Terris Prestholt Fern
Author link: https://covid19-data.nist.gov/pid/rest/local/author/terris_prestholt_fern
sha: 2f1b8af49a5e413d87063c2bd14657285beb9409
license: no-cc
license_url: [no creative commons license associated]
source_x: Medline; PMC
source_x_url: https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/
pubmed_id: 33886102
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/33886102
pmcid: PMC8060338
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060338
url: https://www.ncbi.nlm.nih.gov/pubmed/33886102/ https://doi.org/10.1007/s40271-021-00516-0
has_full_text: TRUE
Keywords Extracted from Text Content: COVID-19 discrete-choice Patient SARS-CoV-2 people quarantine-all Singapore [1 liver COVID-19 border discrete-choice patient lockdowns herd coronavirus 2 Poteet globe left lockdown coronavirus disease 2019 COVID-19 vaccines participants Gijsbers patients
Extracted Text Content in Record: First 5000 Characters:Since March 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; coronavirus disease 2019 ) pandemic has had a substantial effect on daily life worldwide. All countries have experienced both significant threats to health and social and economic disruption. COVID-19 infections and resulting morbidity and mortality have overwhelmed health systems, affected in-person learning in schools, and changed how and when individuals can shop and patronize businesses. Global responses to COVID-19 have varied considerably in terms of trade-offs between control measures and keeping business as usual for as long as possible. As the pandemic continues through 2021, the availability and administration of vaccines will again influence policy and control measures. In this special issue of The Patient, we highlight seven empirical COVID-19 health preference research studies to better understand the value of health and health-related policies around the COVID-19 pandemic. Given the rapid evolution of the disease trends and control strategies, each study should be interpreted in the context of the time of collection. Studies in this special issue examine trade-offs in the pandemic relating to early personal restrictions and lockdowns, the allocation of intensive care unit (ICU) beds and ventilators during scarcity, and the acceptance of vaccines with various attributes, including ways that uptake might be maximized. Understanding community preferences can inform government policies in these areas. Using discrete-choice experiments, two preference studies early in the pandemic evaluated various lockdown policies to control the spread of COVID-19 in Singapore and Australia. In April 2020, a study evaluated the acceptability of different potential government control policies depending upon the severity of the local and global spread of COVID-19 in Singapore [1] . Five policies restricted local movement (no gatherings of more than 50 people, school closure, work from home orders, shut down public transportation, lockdown) and four controlled borders (quarantine-restricted countries, quarantine-all countries, no entry-restricted countries, no entry-all countries). The study showed support for restrictions in local movement, which was heavily driven by case fatality rate. The degree of global spread was the most important factor for support of border control policies. Support for different policies varied based on patient characteristics. In May 2020, a study evaluated the acceptability of different COVID-19 control measures in Australia [2] . Attributes included control measures (restriction level, duration of restrictions, tracking of people), burden of disease (number of people infected with disease, total number of deaths), and economic consequences (number of people who lose their job, additional government spending, additional income tax levy for the next three years). Participants demonstrated that policies resulting in a high death toll were less acceptable than those resulting in high economic losses (unemployment, government expenditure, or tax levies). However, lower unemployment and government expenditure were also important. There was heterogeneity of preferences by characteristics. Interestingly, the use of mobile phones and wearables to manage and contain disease spread at the potential expense of privacy were preferred over not using them in this Australian sample. This is consistent with another COVID-19 discrete-choice experiment in Australia demonstrating that acceptance of such tracking via surveillance technology may depend on the context and the state of the pandemic [3] . Another discrete-choice experiment estimated uptake of digital technology for disease tracking at about 60% [4] . However, the use of mobile phones to track individuals may be met with mixed acceptance within and across countries and raises ethical issues [5] . It is not surprising that the severity of the outbreak, in particular COVID-19 deaths, was the most important attribute in accepting restrictions across both studies examining disease control strategies. In addition, heterogeneity of preferences, based on participant characteristics, for different COVID-19 disease control measures was identified in both a survey of more than 7000 people across seven European countries and a preference study in the USA [6, 7] . Understanding this preference heterogeneity can aid in the design of lockdown policies to achieve greater adherence, including tailoring to different populations. Early in the pandemic, countries with the highest infection rates experienced shortages of protective equipment for healthcare workers, ventilators, and ICU beds, requiring many health systems to develop rationing policies and triage to ensure equitable distribution to those with greatest benefit and need [8, 9] . Two discrete-choice experiments evaluated prioritization of ventilators and ICU beds across patients with varying characteristics during shorta
Keywords Extracted from PMC Text: " left participants border COVID-19 discrete-choice SARS-CoV-2 Patient Poteet coronavirus disease 2019 [COVID-19 lockdowns COVID-19 vaccines coronavirus 2 Singapore [1 liver [48–50] COVID-19 's herd people globe [24–28 patient patients lockdown Gijsbers discrete-choice
Extracted PMC Text Content in Record: First 5000 Characters:Since March 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; coronavirus disease 2019 [COVID-19]) pandemic has had a substantial effect on daily life worldwide. All countries have experienced both significant threats to health and social and economic disruption. COVID-19 infections and resulting morbidity and mortality have overwhelmed health systems, affected in-person learning in schools, and changed how and when individuals can shop and patronize businesses. Global responses to COVID-19 have varied considerably in terms of trade-offs between control measures and keeping business as usual for as long as possible. As the pandemic continues through 2021, the availability and administration of vaccines will again influence policy and control measures. In this special issue of The Patient, we highlight seven empirical COVID-19 health preference research studies to better understand the value of health and health-related policies around the COVID-19 pandemic. Given the rapid evolution of the disease trends and control strategies, each study should be interpreted in the context of the time of collection. Studies in this special issue examine trade-offs in the pandemic relating to early personal restrictions and lockdowns, the allocation of intensive care unit (ICU) beds and ventilators during scarcity, and the acceptance of vaccines with various attributes, including ways that uptake might be maximized. Understanding community preferences can inform government policies in these areas. Using discrete-choice experiments, two preference studies early in the pandemic evaluated various lockdown policies to control the spread of COVID-19 in Singapore and Australia. In April 2020, a study evaluated the acceptability of different potential government control policies depending upon the severity of the local and global spread of COVID-19 in Singapore [1]. Five policies restricted local movement (no gatherings of more than 50 people, school closure, work from home orders, shut down public transportation, lockdown) and four controlled borders (quarantine—restricted countries, quarantine—all countries, no entry—restricted countries, no entry—all countries). The study showed support for restrictions in local movement, which was heavily driven by case fatality rate. The degree of global spread was the most important factor for support of border control policies. Support for different policies varied based on patient characteristics. In May 2020, a study evaluated the acceptability of different COVID-19 control measures in Australia [2]. Attributes included control measures (restriction level, duration of restrictions, tracking of people), burden of disease (number of people infected with disease, total number of deaths), and economic consequences (number of people who lose their job, additional government spending, additional income tax levy for the next three years). Participants demonstrated that policies resulting in a high death toll were less acceptable than those resulting in high economic losses (unemployment, government expenditure, or tax levies). However, lower unemployment and government expenditure were also important. There was heterogeneity of preferences by characteristics. Interestingly, the use of mobile phones and wearables to manage and contain disease spread at the potential expense of privacy were preferred over not using them in this Australian sample. This is consistent with another COVID-19 discrete-choice experiment in Australia demonstrating that acceptance of such tracking via surveillance technology may depend on the context and the state of the pandemic [3]. Another discrete-choice experiment estimated uptake of digital technology for disease tracking at about 60% [4]. However, the use of mobile phones to track individuals may be met with mixed acceptance within and across countries and raises ethical issues [5]. It is not surprising that the severity of the outbreak, in particular COVID-19 deaths, was the most important attribute in accepting restrictions across both studies examining disease control strategies. In addition, heterogeneity of preferences, based on participant characteristics, for different COVID-19 disease control measures was identified in both a survey of more than 7000 people across seven European countries and a preference study in the USA [6, 7]. Understanding this preference heterogeneity can aid in the design of lockdown policies to achieve greater adherence, including tailoring to different populations. Early in the pandemic, countries with the highest infection rates experienced shortages of protective equipment for healthcare workers, ventilators, and ICU beds, requiring many health systems to develop rationing policies and triage to ensure equitable distribution to those with greatest benefit and need [8, 9]. Two discrete-choice experiments evaluated prioritization of ventilators and ICU beds across patients with varying characteristics during sho
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