Overcoming COVID-19 in China despite shortcomings of the public health system : what can we learn? / Mei Mei Wang and Steffen Fleßa

Background and objective: The COVID-19 pandemic started in Wuhan, China, in December 2019. Although there are some doubts about the reporting of cases and deaths in China, it seems that this country was able to control the epidemic more effectively than many other countries. In this paper, we would like to analyze the measures taken in China and compare them with other countries in order to find out what they can learn from China. Methods: We develop a system dynamics model of the COVID-19 pandemic in Wuhan. Based on a number of simulations we analyze the impact of changing parameters, such as contact rates, on the development of a second wave. Results: Although China's health care system seems to be poorly financed and inefficient, the epidemic was brought under control in a comparably short period of time and no second wave was experienced in Wuhan until today. The measures to contain the epidemic do not differ from what was implemented in other countries, but China applied them very early and rigorously. For instance, the consequent implementation of health codes and contact-tracking technology contributed to contain the disease and effectively prevented the second and third waves. Conclusions: China's success in fighting COVID-19 is based on a very strict implementation of a set of measures, including digital management. While other countries discuss relaxing the lock-down at a rate of 50 per 100,000 inhabitants, China started local lock-downs at a rate of 3 per 100,000. We call for a public debate whether this policy would be feasible for more liberal countries as well..

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:11

Enthalten in:

Health economics review - 11(2021), 1 vom: Dez., Artikel-ID 25, Seite 1-18

Sprache:

Englisch

Beteiligte Personen:

Wang, Mei Mei [VerfasserIn]
Fleßa, Steffen, 1966- [VerfasserIn]

Links:

link.springer.com [kostenfrei]
doi.org [kostenfrei]
hdl.handle.net [kostenfrei]

Themen:

COVID-19
Contact-tracking technology
Health care system
Health codes
System dynamics model

doi:

10.1186/s13561-021-00319-x

Weitere IDs:

10419/285215

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

1763753964