Revisando los métodos de agregación de unidades espaciales: MAUP, algoritmos y un breve ejemplo

Vela, Hada Melissa Sáenz

doi:10.24201/edu.v31i2.1592

Cited by 2 publications

(1 citation statement)

References 36 publications

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“…We believe that the lack of visual correlation of call rates with socioeconomic information is due to the imprecision of the unit used for call rates (municipality or neighbourhood) as the unit for socioeconomic information was the census section. Therefore, we have suffered the modifiable area unit problem or ecological fallacy ( 23 ).…”

Section: Discussionmentioning

confidence: 99%

Assessing the social impacts of the COVID-19 crisis using phone helplines. The case of the Balearic Islands, Spain

Ramos Monserrat,

Ramón Molinas,

Fuster Truyol

et al. 2024

Front. Public Health

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BackgroundCrises and health policies to tackle them can increase health inequalities. We explored the scope and usefulness of helplines set up during the COVID-19 crisis and characterised the vulnerability of their users. This study explored the geographic and socioeconomic effects of the telephone helplines set up by the Balearic Islands Government and aimed to characterise the vulnerability of their users.MethodsTelephonic survey combined with a geographical analysis of a sample of calls made between 15th of March and 30th of June of 2020 to five helplines: COVID-19 general information; psychological, social (minimum vital income), labour (temporary employment regulation), and housing (rental assistance) helps. The questionnaire included sociodemographic and housing characteristics, type of problem, and if it was solved or not. We used multinomial regression to explore factors associated with having solved the problem. We calculated the standardised rate of calls by municipality using Chi-squared and z-test to test differences.Results1,321 interviews from 2,678 selected (231 excluded, 608 untraceable, and 518 refusals). 63.8% of women, 48.7% were born in another country. They had no internet at home in 3.1%, only on the phone in 17.3%. The 23.5% had no income at home. The Problem was solved in 25.4%, and partly in 30.9%. Factors associated with not solving the problem were not having income at home (p = 0.021), labour (p = 0.008), economic (p = 0.000) or housing (p = 0.000) problems. People from 55 of 67 municipalities did at least one call. The highest rates of calls were from coastal tourist municipalities.ConclusionHelplines reached most of the territory of the Balearic Islands and were used mainly in tourist municipalities. It probably has not been helpful for families with more significant deprivation. Digital inequalities have emerged.

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Section: Discussionmentioning

confidence: 99%