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Geographic access to COVID-19 healthcare in Brazil using a balanced float catchment area approach.

ABSTRACT: The rapid spread of COVID-19 across the world has raised concerns about the responsiveness of cities and healthcare systems during pandemics. Recent studies try to model how the number of COVID-19 infections will likely grow and impact the demand for hospitalization services at national and regional levels. However, less attention has been paid to the geographic access to COVID-19 healthcare services and to hospitals' response capacity at the local level, particularly in urban areas in the Global South. This paper shows how transport accessibility analysis can provide actionable information to help improve healthcare coverage and responsiveness. It analyzes accessibility to COVID-19 healthcare at high spatial resolution in the 20 largest cities of Brazil. Using network-distance metrics, we estimate the vulnerable population living in areas with poor access to healthcare facilities that could either screen or hospitalize COVID-19 patients. We then use a new balanced floating catchment area (BFCA) indicator to estimate spatial, income, and racial inequalities in access to hospitals with intensive care unit (ICU) beds and mechanical ventilators while taking into account congestion effects. Based on this analysis, we identify substantial social and spatial inequalities in access to health services during the pandemic. The availability of ICU equipment varies considerably between cities, and it is substantially lower among black and poor communities. The study maps territorial inequalities in healthcare access and reflects on different policy lessons that can be learned for other countries based on the Brazilian case.

SUBMITTER: Pereira RHM

PROVIDER: S-EPMC7879934 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Geographic access to COVID-19 healthcare in Brazil using a balanced float catchment area approach.

Pereira Rafael H M RHM Braga Carlos Kauê Vieira CKV Servo Luciana Mendes LM Serra Bernardo B Amaral Pedro P Gouveia Nelson N Paez Antonio A

Social science & medicine (1982) 20210212

The rapid spread of COVID-19 across the world has raised concerns about the responsiveness of cities and healthcare systems during pandemics. Recent studies try to model how the number of COVID-19 infections will likely grow and impact the demand for hospitalization services at national and regional levels. However, less attention has been paid to the geographic access to COVID-19 healthcare services and to hospitals' response capacity at the local level, particularly in urban areas in the Globa ...[more]

PMID: 33609968

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Project description:It is widely accepted that healthcare-seeking behaviour is neither limited to nor terminated by access to one single healthcare provider. Yet the sequential conceptualisation of healthcare-seeking processes has not diffused into quantitative research, which continues to analyse healthcare access as a "one-off" event. The ensuing lack of understanding healthcare behaviour is problematic in light of the immense burden of premature death especially in low- and middle-income countries. This paper presents an alternative approach. Based on a novel survey instrument, we analyse original survey data from rural India and China that contain 119 unique healthcare pathways among 637 respondents. We offer three applications of how such sequential data can be analysed to enhance our understanding of people's health behaviour. First, descriptive analysis of sequential data enables more a comprehensive representation of people's health behaviours, for example the time spent in various healthcare activities, common healthcare pathways across different groups, or shifts in healthcare provider access during a typical illness. Second, by analysing the effect of mobile technology on healthcare-seeking process characteristics, we demonstrate that conventional, sequence-insensitive indicators are potentially inconsistent and misleading approximations when compared to a more precise, sequence-sensitive measure. Third, we describe how sequential data enable transparent and flexible evaluations of people's healthcare behaviour. The example of a sequence-insensitive evaluation suggests that household wealth has no statistical link to an illustrative "ideal" form of public healthcare utilisation. In contrast, sequence-sensitive evaluations demonstrate that household wealth is associated with an increased likelihood of bypassing referral processes and approaching unregulated and costly informal and private practitioners before accessing a public clinic. Sequential data therefore do not only reveal otherwise neglected locational idiosyncrasies, but they also yield deeper insights into the drivers of people's health behaviours compared to a conventional approach to "access to healthcare."

Project description:BackgroundThere are only limited studies on access to COVID-19 vaccines and identifying the most appropriate health centres for performing vaccination in metropolitan areas. This study aimed to measure potential spatial access to COVID-19 vaccination centres in Mashhad, the second-most populous city in Iran.MethodsThe 2021 age structure of the urban census tracts was integrated into the enhanced two-step floating catchment area model to improve accuracy. The model was developed based on three different access scenarios: only public hospitals, only public healthcare centres and both (either hospitals or healthcare centres) as potential vaccination facilities. The weighted decision-matrix and analytic hierarchy process, based on four criteria (i.e. service area, accessibility index, capacity of vaccination centres and distance to main roads), were used to choose potential vaccination centres looking for the highest suitability for residents. Global Moran's index (GMI) was used to measure the spatial autocorrelation of the accessibility index in different scenarios and the proposed model.ResultsThere were 26 public hospitals and 271 public healthcare centres in the study area. Although the exclusive use of public healthcare centres for vaccination can provide the highest accessibility in the eastern and north-eastern parts of the study area, our findings indicate that including both public hospitals and public healthcare centres provide high accessibility to vaccination in central urban part. Therefore, a combination of public hospitals and public healthcare centres is recommended for efficient vaccination coverage. The value of GMI for the proposed model (accessibility to selected vaccination centres) was calculated as 0.53 (Z = 162.42, P < 0.01). Both GMI and Z-score values decreased in the proposed model, suggesting an enhancement in accessibility to COVID-19 vaccination services.ConclusionsThe periphery and poor areas of the city had the least access to COVID-19 vaccination centres. Measuring spatial access to COVID-19 vaccination centres can provide valuable insights for urban public health decision-makers. Our model, coupled with geographical information systems, provides more efficient vaccination coverage by identifying the most suitable healthcare centres, which is of special importance when only few centres are available.

Dataset Information

Geographic access to COVID-19 healthcare in Brazil using a balanced float catchment area approach.

Publications

Geographic access to COVID-19 healthcare in Brazil using a balanced float catchment area approach.

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