Urban environments and COVID-19 in three Eastern states of the United States

Lee, Whanhee; Kim, Honghyok; Choi, Hayon Michelle; Heo, Seulkee; Fong, Kelvin C.; Yang, Jooyeon; Park, Chaerin; Kim, Ho; Bell, Michelle L.

doi:10.1016/j.scitotenv.2021.146334

Cited by 63 publications

(62 citation statements)

References 37 publications

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“…Compared to Whites, the death rate is 30 to 1, but it has been concluded that the impact is practically significant due to the overall low probability in cases and deaths countrywide. Our research findings are consistent with studies done by [ 16 ] and [ 21 ] which suggest that POC positive cases and death rates were higher in some states but not for the overall country. Specifically, in the District of Columbia, the death rate of Blacks was five times higher than the White ethnic group, while in Michigan, their death rate was three times higher than the White ethnic group [ 21 ].…”

Section: Discussionsupporting

confidence: 93%

An analysis of the impact of policies and political affiliation on racial disparities in COVID-19 infections and deaths in the USA

Hamilton

Hamilton²,

Soneye

et al. 2021

Int J Data Sci Anal

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This research aimed to quantify the racial disparities of COVID-19 for primarily positive tests and deaths across the US and territories individually and collectively. The first research hypothesis investigated whether positive cases and death rates were higher for people of color (POC) than the White ethnic group. The second hypothesis examined whether there is a significant difference in confirmed positive cases and death rates between ethnic groups across the US and territories. The third hypothesis investigated if political party control and governmental policies affected the number of cases and death proportion rates across ethnic groups. The research findings suggest that POC positive cases and death rates were higher in some states. Black ethnic groups were dying at a high rate in the southeastern states, the District of Columbia, and in Maryland. Specifically, in the District of Columbia, the death rate is five times higher than the White ethnic group. For Latinx ethnic groups, the high cases and death rates have mostly occurred in western states, including Texas. The Latinx ethnic group accounted for half the total deaths in Texas and California. The Latinx ethnic group death rate is higher than the White ethnic group in four states: Texas, California, New Mexico, and the District of Columbia. The research findings also show that the rate of deaths and cases per ethnic group for policies and political factors were significant except for the mask mandate policy. Based on the analyzed data, mask mandates were not a factor in the cases or death rates of any ethnic group. Each state’s policies for bars, curfews, public schools, and travel—along with legislative party control—had the most influences across ethnic groups. The research results for the death rates and number of cases due to these implemented policies varied between ethnic groups.

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Section: Discussionsupporting

confidence: 93%

An analysis of the impact of policies and political affiliation on racial disparities in COVID-19 infections and deaths in the USA

Hamilton

Hamilton²,

Soneye

et al. 2021

Int J Data Sci Anal

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“…These findings contrast with studies in the USA showing that overcrowding at the county or zip code area level is positively associated, and education negatively associated, with COVID-19 incidence. 18 , 19 However, we caution against forming conclusions from these results. Variations in testing by subcity area socioeconomic status (and overcrowding) are likely to have affected our findings, as socioeconomic status has been shown to be associated with testing.…”

Section: Discussionmentioning

confidence: 87%

The effect of population mobility on COVID-19 incidence in 314 Latin American cities: a longitudinal ecological study with mobile phone location data

Kephart

Delclòs‐Alió

Rodrı́guez

et al. 2021

The Lancet Digital Health

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Background Little is known about the effect of changes in mobility at the subcity level on subsequent COVID-19 incidence, which is particularly relevant in Latin America, where substantial barriers prevent COVID-19 vaccine access and non-pharmaceutical interventions are essential to mitigation efforts. We aimed to examine the longitudinal associations between population mobility and COVID-19 incidence at the subcity level across a large number of Latin American cities. Methods In this longitudinal ecological study, we compiled aggregated mobile phone location data, daily confirmed COVID-19 cases, and features of urban and social environments to analyse population mobility and COVID-19 incidence at the subcity level among cities with more than 100 000 inhabitants in Argentina, Brazil, Colombia, Guatemala, and Mexico, from March 2 to Aug 29, 2020. Spatially aggregated mobile phone data were provided by the UN Development Programme in Latin America and the Caribbean and Grandata; confirmed COVID-19 cases were from national government reports and population and socioeconomic factors were from the latest national census in each country. We used mixed-effects negative binomial regression for a time-series analysis, to examine longitudinal associations between weekly mobility changes from baseline (prepandemic week of March 2–9, 2020) and subsequent COVID-19 incidence (lagged by 1–6 weeks) at the subcity level, adjusting for urban environmental and socioeconomic factors (time-invariant educational attainment, residential overcrowding, population density [all at the subcity level], and country). Findings We included 1031 subcity areas, representing 314 Latin American cities, in Argentina (107 subcity areas), Brazil (416), Colombia (82), Guatemala (20), and Mexico (406). In the main adjusted model, we observed an incidence rate ratio (IRR) of 2·35 (95% CI 2·12–2·60) for COVID-19 incidence per log unit increase in the mobility ratio ( vs baseline) during the previous week. Thus, 10% lower weekly mobility was associated with 8·6% (95% CI 7·6–9·6) lower incidence of COVID-19 in the following week. This association gradually weakened as the lag between mobility and COVID-19 incidence increased and was not different from null at a 6-week lag. Interpretation Reduced population movement within a subcity area is associated with a subsequent decrease in COVID-19 incidence among residents of that subcity area. Policies that reduce population mobility at the subcity level might be an effective COVID-19 mitigation strategy, although they should be combined with strategies that mitigate any adverse social and economic consequences of reduced mobility for the most vulnerable groups. Funding Wellcome Trust. Translation For the Spanish translation of the abstract see Supplementary Materials section.

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“…Research indicates that the risk of disease spread and deaths are influenced by several characteristics, such as socio-demographic factors [ 5 ], behavioral traits [ 6 ], and pre-existing health conditions [ 7 ]. However, the risk factors impacting the spread and severity of COVID-19 infections are inconsistent across studies, and they vary from place to place [ 8 , 9 ]. Therefore, studies focused on the local-level transmission of this disease are necessary for identifying the main drivers of disease spread that are suitable to contain the current pandemic in this specific region.…”

Section: Introductionmentioning

confidence: 99%

District-Level Risk Factors for COVID-19 Incidence and Mortality in Nepal

Lamichhane

Shrestha

Kim

2022

IJERPH

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The recent global pandemic of the novel coronavirus disease 2019 (COVID-19) is affecting the entire population of Nepal, and the outcome of the epidemic varies from place to place. A district-level analysis was conducted to identify socio-demographic risk factors that drive the large variations in COVID-19 mortality and related health outcomes, as of 22 January 2021. Data on COVID-19 extracted from relevant reports and websites of the Ministry of Health and Population of Nepal, and the National Population and Housing Census and the Nepal Demographic and Health Survey were the main data sources for the district-level socio-demographic characteristics. We calculated the COVID-19 incidence, recovered cases, and deaths per 100,000 population, then estimated the associations with the risk factors using regression models. COVID-19 outcomes were positively associated with population density. A higher incidence of COVID-19 was associated with districts with a higher percentage of overcrowded households and without access to handwashing facilities. Adult literacy rate was negatively associated with the COVID-19 incidence. Increased mortality was significantly associated with a higher obesity prevalence in women and a higher smoking prevalence in men. Access to health care facilities reduced mortality. Population density was the most important driver behind the large variations in COVID-19 outcomes. This study identifies critical risk factors of COVID-19 outcomes, including population density, crowding, education, and hand hygiene, and these factors should be considered to address inequities in the burden of COVID-19 across districts.

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Urban environments and COVID-19 in three Eastern states of the United States

Cited by 63 publications

References 37 publications

An analysis of the impact of policies and political affiliation on racial disparities in COVID-19 infections and deaths in the USA

An analysis of the impact of policies and political affiliation on racial disparities in COVID-19 infections and deaths in the USA

The effect of population mobility on COVID-19 incidence in 314 Latin American cities: a longitudinal ecological study with mobile phone location data

District-Level Risk Factors for COVID-19 Incidence and Mortality in Nepal

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