The Impact of Health Policies and Sociodemographic Factors on Doubling Time of the COVID-19 Pandemic in Mexico

. The doubling time is the best indicator of the course of the current COVID-19 pandemic. The aim of the present investigation was to determine the impact of policies and several sociodemographic factors on the COVID-19 doubling time in Mexico. . A retrospective longitudinal study was carried out ac...

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Bibliographic Details
Published in:International journal of environmental research and public health 2021-02, Vol.18 (5), p.2354
Main Authors: Díaz-Castro, Lina, Cabello-Rangel, Héctor, Hoffman, Kurt
Format: Article
Language:English
Subjects:
Coefficients
Coronaviruses
Correlation analysis
COVID-19
COVID-19 - epidemiology
COVID-19 - transmission
Data models
Disease transmission
Health Policy
Humans
Life expectancy
Longitudinal Studies
Mexico - epidemiology
Mobility
Pandemics
Per capita
Population
Population Density
Population number
Poverty
Propagation
Public health
Retrospective Studies
Severe acute respiratory syndrome coronavirus 2
Sociodemographics
Socioeconomic Factors
Variables
Velocity
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Summary:. The doubling time is the best indicator of the course of the current COVID-19 pandemic. The aim of the present investigation was to determine the impact of policies and several sociodemographic factors on the COVID-19 doubling time in Mexico. . A retrospective longitudinal study was carried out across March-August, 2020. Policies issued by each of the 32 Mexican states during each week of this period were classified according to the University of Oxford Coronavirus Government Response Tracker (OxCGRT), and the doubling time of COVID-19 cases was calculated. Additionally, variables such as population size and density, poverty and mobility were included. A panel data model was applied to measure the effect of these variables on doubling time. . States with larger population sizes issued a larger number of policies. Delay in the issuance of policies was associated with accelerated propagation. The policy index (coefficient 0.60, < 0.01) and the income per capita (coefficient 3.36, < 0.01) had a positive effect on doubling time; by contrast, the population density (coefficient -0.012, < 0.05), the mobility in parks (coefficient -1.10, < 0.01) and the residential mobility (coefficient -4.14, < 0.01) had a negative effect. . Health policies had an effect on slowing the pandemic's propagation, but population density and mobility played a fundamental role. Therefore, it is necessary to implement policies that consider these variables.
ISSN:1660-4601
1661-7827
1660-4601
DOI:10.3390/ijerph18052354