Introduction
Hong Kong (HK) has witnessed waves of COVID-19 surges since the beginning of the pandemic. As HK is still struggling with the most recent surge of cases, the debate over whether HK should adopt mainland China’s “zero-COVID” strategy or a “living with COVID” approach is also happening among academic, public health, social, and political communities.[1] However, one thing for sure is that in this one of the most unequal cities in the world, people of ethnic and racial minorities, mainly foreign domestic workers (FDWs), who have already been under tremendous pressure, are exposed to relatively higher risk than others.[2] As research has already shown, marginalized racial and ethnic groups (Filipinos, Indonesians, etc.) were more likely to report high fear and perceive coronavirus as a major threat.[3] In terms of FDWs in particular, the FDWs have suffered more difficulties in both home countries and Hong Kong; namely, they have faced travel restrictions and lockdowns posed by their home countries, and in Hong Kong, they have had worsening working conditions and have often been deprived of employment rights and entitlements.[4]
Risk Environment Model & racialized risk environments
Instead of focusing on one particular ethnic minority group or one particular aspect of risk assessment, like the population density of their living environment, this study adopts the conceptual framework of “risk environment” that was initially proposed by Tim Rhodes to understand and reduce drug-related harm.[5] Rhodes defines the risk environment as “the place––whether social or physical––in which various factors interact to increase the chances of drug-related harm.”[6] And he delineates the model with two types of environment––micro and macro environments––and four levels of environmental influences––physical, social, economic, and policy.[7] Therefore, the Risk Environment Model is a holistic way to measure the overall COVID risk that is and would be exposed to ethnic and racial minorities in HK.
To measure the “racialized risk environments”[8] of COVID, in which ethnic and racial minorities in HK are living, we need to focus on the geodemographics of racial and ethnic minorities in relation to the locations of probable/confirmed COVID cases that have been recorded, the accessibility to local medical resources, the accessibility to specimen packs collection and -distribution sites, and the degree of the implementation of COVID-related policies locally.
Research questions
My guiding question is to what extent ethnic and racial minorities, represented by the Indonesian and Filipino communities in this study, are more exposed to COVID risk? There are four sub-questions that this study chose to answer. First, to what extent is the overall social environment that most Indonesians and Filipinos live in more susceptible to COVID transmission, namely dense housing units, more people, more extended families? Second, is there a positive correlation between the Indonesian and Filipino population and the low-income population, indicating their weaker abilities to afford medical and other resources? Third, are COVID-related medical resources, namely, clinics/hospitals and vaccination sites, relatively less accessible to the Indonesian and Filipino population, and if so, to what extent? Fourth, in terms of the government intervention in COVID risk management, to what extent do specimen distribution/collection points reach to people who have been notified to do compulsory testing, and how about racial and ethnic population-dense places?
Results
I generated home ranges for 25%, 50%, and 75% of the kernel density of all COVID cases on top of the Indonesian and Filipino density map.
In the center of HK, a large chunk of the Indonesian and Filipino densely populated area is within the 25% home range. The upper part of the Indonesian and Filipino densely populated area on the HK island falls within the 50% and 75% home ranges. However, other regions with relatively significant Indonesian and Filipino density are not within these home ranges. Therefore, the Indonesian and Filipino population living at the city’s center have been exposed to substantial COVID risk.
Having narrowed down our focus to these two areas with relatively high Indonesian and Filipino density and COVID rate, we turn to the four maps to the end of the ETL for physical influences, which visualize the minimum distance between various medical facilities and the centroid in each LTPU. Clinics/hospitals, community, and private vaccination centers are all relatively easily accessible in these two areas. However, the southeast part of HK island, with a significant density of Filipinos and Indonesians, does not have clinics/hospitals or private vaccination centers close to the centroid. Although these areas are not covered by the home ranges of the COVID cases kernel density, they are very close to them, so people living there are also exposed to high risk. Another thing worth mentioning is that many Filipinos and Indonesians live there on the small islands at the bottom of the maps and the large island at the bottom left, and the medical facilities there are just scarce. Even though there have been no COVID surges in these remote areas, given the high transmission of COVID, people living there without sufficient medical resources are also living in potential danger.
Regarding policy influences, I calculated the 1000-m service area of all specimen pack collection/distribution sites and visualized them along with the distribution of testing notices issued by the government. Then I calculated the density of buffers per LTPU. Like the physical influences, the southeast part of HK island and the large island at the bottom left, both of which have a relatively high Filipino and Indonesian density, are not sufficiently covered by the service area of specimen pack collection/distribution sites.
[1] Alice Fung and David Rising, “Xi urges Hong Kong to get control as COVID-19 cases surge,” Associated Press, Feb 16, 2022, https://apnews.com/article/coronavirus-pandemic-health-beijing-xi-jinping-hong-kong-6700d6a93c19f47ebb0a0ec7b9e0e413.
[2] Ian Cheung, “Who Is Responsible for Hong Kong’s Invisible Migrant Workers?” Center for Strategic & International Studies, https://www.csis.org/npfp/who-responsible-hong-kongs-invisible-migrant-workers, accessed Dec 5, 2021.
John Kang, “Study Reveals 95% of Filipino, Indonesian Helpers In Hong Kong Exploited Or Forced Labor,” Forbes, last modified Mar 18, 2016, https://www.forbes.com/sites/johnkang/2016/03/18/study-reveals-95-of-filipino-indonesian-helpers-in-hong-kong-exploited-or-forced-labor/?sh=6ab59d897f0d, accessed Feb 28, 2021.
[3] Michael Niño, Casey Harris, Grant Drawve, and Kevin M. Fitzpatrick, “Race and ethnicity, gender, and age on perceived threats and fear of COVID-19: Evidence from two national data sources,” in SSM - Population Health 13 (2021): 4-6.
[4] Wong Mei Ling May, “The impacts of Covid-19 on foreign domestic workers in Hong Kong,” in Asian Journal of Business Ethics 10, no. 2 (2021): 360-5.
[5] Tim Rhodes, “The ‘risk environment’: a framework for understanding and reducing drug-related harm,” in International Journal of Drug Policy13 (2002): 85-94.
[6] Ibid, 88.
[7] Ibid, 89.
[8] This term comes from Critical Race Theory. See E. Bonilla-Silva, White Supremacy and Racism in the Post-Civil Rights Era (Boulder: Lynne Rienner Publishers, 2001). For the term’s application in Geographical Science, see Hannah L.F. Cooper et al. “Racialized risk environments in a large sample of people who inject drugs in the United States,” in International Journal of Drug Policy 27 (2016): 43-55.
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