TY - JOUR

T1 - The COVID-19 quandemic

AU - Rubin, Olivier

AU - King, Carina

AU - von Schreeb, Johan

AU - Morsut, Claudia

AU - Kovács, Gyöngyi

AU - Raju, Emmanuel

N1 - © 2024. The Author(s).

PY - 2024

Y1 - 2024

N2 - BACKGROUND: The terms syndemic and infodemic have both been applied to the COVID-19 pandemic, and emphasize concurrent socio-cultural dynamics that are distinct from the epidemiological outbreak itself. We argue that the COVID-19 pandemic has exposed yet another important socio-political dynamic that can best be captured by the concept of a quandemic - a portmanteau of "quantification" and "pandemic".MAIN TEXT: The use of quantifiable metrics in policymaking and evaluation has increased throughout the last decades, and is driven by a synergetic relationship between increases in supply and advances in demand for data. In most regards this is a welcome development. However, a quandemic, refers to a situation where a small subset of quantifiable metrics dominate policymaking and the public debate, at the expense of more nuanced and multi-disciplinary discourse. We therefore pose that a quandemic reduces a complex pandemic to a few metrics that present an overly simplified picture. During COVID-19, these metrics were different iterations of case numbers, deaths, hospitalizations, diagnostic tests, bed occupancy rates, the R-number and vaccination coverage. These limited metrics came to constitute the internationally recognized benchmarks for effective pandemic management. Based on experience from the Nordic region, we propose four distinct dynamics that characterize a quandemic: 1) A limited number of metrics tend to dominate both political, expert, and public spheres and exhibit a great deal of rigidity over time. 2) These few metrics crowd-out other forms of evidence relevant to pandemic response. 3) The metrics tend to favour certain outcomes of pandemic management, such as reducing hospitalization rates, while not capturing potential adverse effects such as social isolation and loneliness. 4) Finally, the metrics are easily standardized across countries, and give rise to competitive dynamics based on international comparisons and benchmarking.CONCLUSION: A quandemic is not inevitable. While metrics are an indispensable part of evidence-informed policymaking, being attentive to quandemic dynamics also means identifying relevant evidence that might not be captured by these few but dominant metrics. Pandemic responses need to account for and consider multilayered vulnerabilities and risks, including socioeconomic inequities and comorbidities.

AB - BACKGROUND: The terms syndemic and infodemic have both been applied to the COVID-19 pandemic, and emphasize concurrent socio-cultural dynamics that are distinct from the epidemiological outbreak itself. We argue that the COVID-19 pandemic has exposed yet another important socio-political dynamic that can best be captured by the concept of a quandemic - a portmanteau of "quantification" and "pandemic".MAIN TEXT: The use of quantifiable metrics in policymaking and evaluation has increased throughout the last decades, and is driven by a synergetic relationship between increases in supply and advances in demand for data. In most regards this is a welcome development. However, a quandemic, refers to a situation where a small subset of quantifiable metrics dominate policymaking and the public debate, at the expense of more nuanced and multi-disciplinary discourse. We therefore pose that a quandemic reduces a complex pandemic to a few metrics that present an overly simplified picture. During COVID-19, these metrics were different iterations of case numbers, deaths, hospitalizations, diagnostic tests, bed occupancy rates, the R-number and vaccination coverage. These limited metrics came to constitute the internationally recognized benchmarks for effective pandemic management. Based on experience from the Nordic region, we propose four distinct dynamics that characterize a quandemic: 1) A limited number of metrics tend to dominate both political, expert, and public spheres and exhibit a great deal of rigidity over time. 2) These few metrics crowd-out other forms of evidence relevant to pandemic response. 3) The metrics tend to favour certain outcomes of pandemic management, such as reducing hospitalization rates, while not capturing potential adverse effects such as social isolation and loneliness. 4) Finally, the metrics are easily standardized across countries, and give rise to competitive dynamics based on international comparisons and benchmarking.CONCLUSION: A quandemic is not inevitable. While metrics are an indispensable part of evidence-informed policymaking, being attentive to quandemic dynamics also means identifying relevant evidence that might not be captured by these few but dominant metrics. Pandemic responses need to account for and consider multilayered vulnerabilities and risks, including socioeconomic inequities and comorbidities.

U2 - 10.1186/s12992-024-01024-0

DO - 10.1186/s12992-024-01024-0

M3 - Journal article

C2 - 38431647

VL - 20

JO - Globalization and Health

JF - Globalization and Health

SN - 1744-8603

IS - 1

M1 - 19

ER -