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Non-healthcare system interventions and COVID-19 daily cases: a multilevel time series analysis
by
Yang, Yanfang
, Lei, Lei
, Liu, Aonan
, Ma, Hao
in
Analysis
/ Biostatistics
/ China
/ Coronaviruses
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 - prevention & control
/ Developing countries
/ Disease control
/ Economic development
/ Economic factors
/ Economic policy
/ Economics
/ Environmental aspects
/ Environmental Health
/ Epidemics
/ Epidemiology
/ Estimates
/ GNI
/ Gross National Income
/ Health aspects
/ Health care
/ Health services
/ Humans
/ Income
/ Income group
/ Interception
/ Intervention
/ LDCs
/ Low income areas
/ Low income groups
/ Maximum likelihood estimates
/ Medicine
/ Medicine & Public Health
/ Medicine, Preventive
/ Methods
/ Multilevel
/ Multilevel Analysis
/ Multilevel model
/ Non-healthcare system interventions
/ Pandemics
/ Per capita
/ Policy implementation
/ Policy making
/ Population density
/ Prevention
/ Preventive health services
/ Public events
/ Public Health
/ Random effects
/ Region
/ Regions
/ SARS-CoV-2
/ Social aspects
/ Socioeconomic development
/ Socioeconomic factors
/ Stratification
/ Time series
/ Travel restrictions
/ Vaccine
/ Variables
2025
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Non-healthcare system interventions and COVID-19 daily cases: a multilevel time series analysis
by
Yang, Yanfang
, Lei, Lei
, Liu, Aonan
, Ma, Hao
in
Analysis
/ Biostatistics
/ China
/ Coronaviruses
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 - prevention & control
/ Developing countries
/ Disease control
/ Economic development
/ Economic factors
/ Economic policy
/ Economics
/ Environmental aspects
/ Environmental Health
/ Epidemics
/ Epidemiology
/ Estimates
/ GNI
/ Gross National Income
/ Health aspects
/ Health care
/ Health services
/ Humans
/ Income
/ Income group
/ Interception
/ Intervention
/ LDCs
/ Low income areas
/ Low income groups
/ Maximum likelihood estimates
/ Medicine
/ Medicine & Public Health
/ Medicine, Preventive
/ Methods
/ Multilevel
/ Multilevel Analysis
/ Multilevel model
/ Non-healthcare system interventions
/ Pandemics
/ Per capita
/ Policy implementation
/ Policy making
/ Population density
/ Prevention
/ Preventive health services
/ Public events
/ Public Health
/ Random effects
/ Region
/ Regions
/ SARS-CoV-2
/ Social aspects
/ Socioeconomic development
/ Socioeconomic factors
/ Stratification
/ Time series
/ Travel restrictions
/ Vaccine
/ Variables
2025
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Non-healthcare system interventions and COVID-19 daily cases: a multilevel time series analysis
by
Yang, Yanfang
, Lei, Lei
, Liu, Aonan
, Ma, Hao
in
Analysis
/ Biostatistics
/ China
/ Coronaviruses
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 - prevention & control
/ Developing countries
/ Disease control
/ Economic development
/ Economic factors
/ Economic policy
/ Economics
/ Environmental aspects
/ Environmental Health
/ Epidemics
/ Epidemiology
/ Estimates
/ GNI
/ Gross National Income
/ Health aspects
/ Health care
/ Health services
/ Humans
/ Income
/ Income group
/ Interception
/ Intervention
/ LDCs
/ Low income areas
/ Low income groups
/ Maximum likelihood estimates
/ Medicine
/ Medicine & Public Health
/ Medicine, Preventive
/ Methods
/ Multilevel
/ Multilevel Analysis
/ Multilevel model
/ Non-healthcare system interventions
/ Pandemics
/ Per capita
/ Policy implementation
/ Policy making
/ Population density
/ Prevention
/ Preventive health services
/ Public events
/ Public Health
/ Random effects
/ Region
/ Regions
/ SARS-CoV-2
/ Social aspects
/ Socioeconomic development
/ Socioeconomic factors
/ Stratification
/ Time series
/ Travel restrictions
/ Vaccine
/ Variables
2025
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Non-healthcare system interventions and COVID-19 daily cases: a multilevel time series analysis
Journal Article
Non-healthcare system interventions and COVID-19 daily cases: a multilevel time series analysis
2025
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Overview
Background
The global COVID-19 pandemic has significantly impacted public health and socio-economic development worldwide. This study aims to investigate the effects of non-healthcare system interventions on the daily new cases of COVID-19 from January 2020 to October 2022.
Methods
With the aid of multilevel approach, we identified income group, region and country as stratification factors that affect the number of COVID-19 daily new cases. Data on COVID-19 cases collected by Johns Hopkins University were used, and policy implementation details were recorded through the Oxford COVID-19 Government Response Tracker dataset. To analyze the effects of national, regional, and income group factors on the number of daily new COVID-19 cases, we implemented three multilevel sequential mixed-effects models and applied restricted maximum likelihood to estimate the variance of random effects.
Results
Our results indicate a correlation between income group and the rise in intercepts of random effects in the multilevel sequential mixed-effects models. High-income countries recorded the highest intercept at 713.26, while low-income countries showed the lowest at -313.79. Under the influence of policies, the implementation of \"Canceling public events\" and \"International travel restrictions\" has been shown to significantly reduce the daily number of new COVID-19 cases. In contrast, \"Restrictions on gatherings\" appear to have the opposite effect, potentially leading to an increase in daily new COVID-19 cases.
Conclusions
In designing epidemic control policies, due consideration should be given to factors such as income group, as well as medical, demographic, and social differences among nations influenced by economic factors. In policy-making, policymakers should pay greater attention to policy implementation and people's responses, in order to maximize the effectiveness and adherence of such policies.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ China
/ COVID-19
/ COVID-19 - prevention & control
/ GNI
/ Humans
/ Income
/ LDCs
/ Maximum likelihood estimates
/ Medicine
/ Methods
/ Non-healthcare system interventions
/ Region
/ Regions
/ Vaccine
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