Territorial Strategy of Medical Units for Addressing the First Wave of the COVID-19 Pandemic in the Metropolitan Area of Mexico City: Analysis of Mobility, Accessibility and Marginalization

Abstract

Background. The COVID-19 pandemic has caused an exponential increase in the demand for medical care worldwide. In Mexico, the COVID Medical Units (CMUs) conversion strategy was implemented. Objective. To evaluate the CMU coverage strategy in the Mexico City Metropolitan Area (MCMA) by territory. Materials. The CMU directory was used, as were COVID-19 infection and mobility statistics and Mexican 2020 census information at the urban geographic area scale. The degree of urban marginalization by geographic area was also considered. Method. Using descriptive statistics and the calculation of a CMU accessibility index, population aggregates were counted based on coverage radii. In addition, two regression models are proposed to explain (1) the territorial and temporal trend of COVID-19 infections in the MCMA and (2) the mobility of the COVID-infected population visiting medical units. Results. The findings of the evaluation of the CMU strategy were (1) in the MCMA, COVID-19 followed a pattern of contagion from the urban center to the periphery; (2) given the growth in the number of cases and the overload of medical units, the population traveled greater distances to seek medical care; (3) after the CMU strategy was evaluated at the territory level, it was found that 9 out of 10 inhabitants had a CMU located approximately 7 km away; and (4) at the metropolitan level, the lowest level of accessibility to the CMU was recorded for the population with the highest levels of marginalization, i.e., those residing in the urban periphery.

Spatial scales of COVID-19 transmission in Mexico

“…mission (i.e., communities in which it is assumed that infection spreads via contacts within a relatively homogeneously mixing population [51]). Accounting for spatial heterogeneity is Growth rate (reported cases) known to be important for assessing strategies for interventions [2], especially in areas that have marked differences in urban and rural areas [52]. Using this algorithm, we identify 16 communities before the first cases of COVID-19 were detected in Mexico (Fig.…”

Comparative Analysis of Age, Sex, and Viral Load in Outpatients during the Four Waves of SARS-CoV-2 in A Mexican Medium-Sized City

“…Combined with poor crisis management, disregard for scientific information, and negligent policies by the national highest authorities, adverse effects are exerted on the design of policy responses [22]. In addition, health services are insufficient, and accessibility to medical units is not equal for different sectors of the population [23,24]. The current health policies discourage mass sampling [25], preferring to focus on the corrective treatment of severe cases.…”

The Impacts of COVID-19 on Real Estate Market Dynamics: A Systematic Literature Review of Emerging Trends

“…On the one hand, in 2020, this caused huge losses due to the forced stop periods; on the other hand, it led to a strong impulse to experiment with important technological and organizational changes destined to consolidate over time and still visible today (following the declaration of the end of the health emergency made official on 5 May 2023 by the World Health Organization [9]). In fact, an important role was assumed by the consequences of the measures aimed at containing the infection spread, including those on territorial mobility, especially during the first pandemic phase in 2020 [10][11][12]. In this sense, the impact of the pandemic on migratory flows is closely linked both to the direct effect of the restrictions on international mobility, implemented to counter the fast-spreading virus, and to the negative influence of the climate of uncertainty that has hindered migratory projects.…”