Gender, Mobility, and Covid-19: The Case of Belgium

Abstract

Studies have shown that women are disadvantaged when facing infectious disease outbreaks. This study uses descriptive data analysis, causality, and VAR modeling to verify this hypothesis in the case of COVID-19 in Belgium in relation to people's mobility. The results confirm this women's disadvantage hypothesis, in particular among the working-age population in Belgium. This disadvantage is explained by women's greater mobility during the pandemic. Despite the restrictions on nonessential travel imposed by Belgian authorities, women use public transportation more often than men to travel for work and family reasons and are thus more likely to be exposed to the virus. Therefore, it is necessary that the health, economic, and social response provided by the Belgian authorities correct this inequality.

Human mobility behavior in COVID-19: A systematic literature review and bibliometric analysis

“… Ref. : Button et al, 2020 , Pantelaki et al, 2020 , Schippl and Truffer, 2020 ; Assoumou Ella, 2020 , Bucsky, 2020 , Cochran, 2020 , Scorrano and Danielis, 2020 ; Air Transport Sub-theme 1. Aviation’s recovery flight plan Keywords: Airport Service; Forecast of Air Flow; Market Recovery; Operational Efficiency; Future Tourism Demand; Importation Risk; Exportation Risk; Complex Networks.…”

The relationship of social vulnerability and travel behavior with COVID-19 in Metro Manila, Philippines

“…Moreover, the female population (Gender, r = 0.514) appears to have the strongest correlation to this risk. Women tend to travel more for household errands, and usually use public transportation which results to added risk of infection ( Assoumou Ella, 2021 ). These factors contribute to making women more vulnerable to the risk of infection.…”

“…Various technological companies have provided anonymized mobility data to support pandemic response and recovery. Since then, literature utilizing such data to understand travel behavior and mobility changes due to COVID-19 has been growing ( Assoumou Ella, 2021 ; Hasselwander et al, 2021 ; Iio et al, 2021 ; Bucsky, 2020 ; Lou et al, 2020 ; Paez, 2020 ). This study recognizes the data's limitations in reflecting mobility by sociodemographic; nonetheless, travel data are relevant variables for evaluating the impact of the pandemic on the travel behavior of the population, and in considering the role of transportation in spreading the pandemic.…”

“…There is also a difference in mobility behavior between male and female commuters. While men travel more for work and more women are staying at home ( Pinchoff et al, 2021 ), women use public transport more often increasing their risk of exposure to the virus ( Assoumou Ella, 2021 ). Likewise, the older age group faces a significant risk of developing severe illness if they contract COVID-19 because of physiological changes as a result of ageing and any possible comorbidity ( World Health Organization, 2020a ).…”

“…Furthermore, vulnerable populations, such as low-income households, tend to reside in overcrowded structures, increasing their susceptibility to infection. While current literature describes changes in travel behavior for different socioeconomic groups, majority of the studies were either conducted in the United States ( Coleman et al, 2021 ; Lou et al, 2020 ; Almagro et al, 2021 ; Coven and Gupta, 2020 ; Iio et al, 2021 ; Roy and Kar, 2020; Huang et al, 2020 ; Sy et al, 2020 ; Weill et al, 2020), or other developed countries in Europe (Manzira et al, 2022; Assoumou Ella, 2021 ; Politis et al, 2021 ; van der Kloof and Kensmil, 2020 ). Very few studies have focused on developing economies ( Kartal et al, 2021 ; Pinchoff et al, 2021 ), and even less for Asian countries ( Fraiberger et al, 2020 ).…”