Strong effect of socioeconomic levels on the spread and treatment of the 2019 novel coronavirus (COVID-19) in China
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Abstract
Background
Global response to the COVID-19 epidemic presents strengths and weaknesses in national and regional social governance capacities to address public health challenges. The emergence, detection, spread, treatment and containment of infectious diseases shows the considerable political and economic impacts in a highly interconnected world. We aimed to estimate the effects of socioeconomic levels on the spread and treatment of COVID-19 in China. Methods We obtained daily COVID-19 cases at a city level in China. We used migration data from the major cities in Hubei Province, and macroeconomic data at city and province levels. We obtained social management measures in response to COVID-19 outbreak. We assessed the association between measures, migration and COVID-19 spread, and the association between socioeconomic levels and COVID-19 treatment capacity.
Findings
On January 1, 2020, COVID-19 spread that affected by management measures and migration started across China. After Wuhan lockdown, the case number reached peak in 12 days, and COVID-19 outbreak was basically contained in China in four weeks due to intensive measures. Guangdong, Jiangsu and Zhejiang Provinces showed the most excellent COVID-19 treatment capacities. Socioeconomic levels in these provinces ranked top in China. Guangdong achieved the largest decline in severe case rate by 22.1%. Jiangsu had the lowest average rate of severe cases (1.7%) and zero death. Among the regions with top case number, Zhejiang showed the highest rate of cured cases on confirmed cases (96.3%), the lowest average rate of severe cases (7.7%), and one death. The COVID-19 treatment capacities were strongly affected by regional economics and measures on control, detection and treatment.
Interpretation
Socioeconomic levels had strong effect on the spread and treatment of COVID-19 in China. Further investigations are needed on the effectiveness of Chinese measures and the effects of socioeconomic levels on COVID-19 treatment outside China.
Fund
None
Research in context
Evidence before this study
We searched PubMed for articles published in any language up to April 24, 2020, with the search terms “COVID-19 AND (socioeconomic OR measure) AND (spread OR treatment)”. We identified 334 articles. Some researchers are dedicated to debating the effect of social management measures on the spread of COVID-19 epidemic. All previous studies focused on the effect of the individual measure on COVID-19 spread over time. We identified several mathematical modelling studies exploring the effect of management measures, mainly focusing on Wuhan lockdown in China, on COVID-19 spread. However, social management measures not only involve prevention and control of virus spread, but also virus detection and patient treatment. No study used methods that would allow the assessment of effect of several management measures on the spread, detection, and treatment of COVID-19 at various time milestones over the entire course of COVID-19 outbreak. Some scholars advocated that health equity cannot be ignored to contain the global COVID-19 epidemic. They did not provide epidemical and economic data analysis to assess the effect of socioeconomic gradients in health at individual or regional levels. No study estimated the effects of socioeconomic levels on national and regional COVID-19 treatment.
Added value of this study
We found that on January 1, 2020, COVID-19 spread that affected by management measures and migration started across China. After Wuhan lockdown, COVID-19 outbreak was basically contained in China in four weeks due to intensive measures. The intensive measures mainly include movement restriction, wearing masks in public, nationwide joint prevention and control at a community level, four early strategies, and information disclosure. We, for the first time, estimated the effect of socioeconomic levels on spread and treatment of COVID-19 in China. The management measures, including Fangcang shelter hospitals, medical assistance nationwide, and continuously updated diagnosis and treatment plan for COVID-19, greatly improved COVID-19 treatment capacities in China, particularly in Hubei Province. The COVID-19 treatment capacities were strongly affected by regional economics and measures on control, detection and treatment.
Implications of all the available evidence
The Chinese experience provides important insights into how to design effective management strategies of COVID-19 or other epidemic. Further efforts are needed on the effectiveness of Chinese management measures and the effects of socioeconomic levels on COVID-19 treatment outside China.
Article activity feed
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SciScore for 10.1101/2020.04.25.20079400: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Additionally, the limitation of this study lied in data unavailability. For an improved understanding of socioeconomic effect on COVID-19 treatment in China, case reports of severe and dead patients at a city level, including …
SciScore for 10.1101/2020.04.25.20079400: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Additionally, the limitation of this study lied in data unavailability. For an improved understanding of socioeconomic effect on COVID-19 treatment in China, case reports of severe and dead patients at a city level, including gender, age, weight, medical history and length of hospital stay could be added. Socioeconomic factors, e.g., the number of beds, doctors and nurses in intensive care units, the number of key medical resources in all top hospitals, e.g., negative pressure ambulances, Extracorporeal Membrane Oxygenation (ECMO), ventilator and other key treatment equipment at a city level could be supplemented. COVID-19 spread in China was effectively curbed, and the spread to other countries was notably reduced. The effectiveness of these Chinese measures in controlling transmission and treatment of COVID-19 in other countries of the world requires intensive examination. The Chinese experience provides important insights into how to design effective management strategies of COVID-19 or other epidemic outside China.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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