Location selection of field hospitals amid COVID-19 considering effectiveness and fairness: A case study of Florida.

The world has experienced an unprecedented global health crisis since 2020, the COVID-19 pandemic, which inflicted massive burdens on countries' healthcare systems. During the peaks of the pandemic, the shortages of intensive care unit (ICU) beds illustrated a critical vulnerability in the fight. Many individuals suffering the effects of COVID-19 had difficulty accessing ICU beds due to insufficient capacity. Unfortunately, it has been observed that many hospitals do not have enough ICU beds, and the ones with ICU capacity might not be accessible to all population strata. To remedy this going forward, field hospitals could be established to provide additional capacity in helping emergency health situations such as pandemics; however, location selection is a crucial decision ultimately for this purpose. As such, we consider finding new field hospital locations to serve the demand within certain travel-time thresholds, while accounting for the presence of vulnerable populations. A multi-objective mathematical model is proposed in this paper that maximizes the minimum accessibility and minimizes the travel time by integrating the Enhanced 2-Step Floating Catchment Area (E2SFCA) method and travel-time-constrained capacitated p-median model. This is performed to decide on the locations of field hospitals, while a sensitivity analysis addresses hospital capacity, demand level, and the number of field hospital locations. Four counties in Florida are selected to implement the proposed approach. Findings can be used to identify the ideal location(s) of capacity expansions concerning the fair distribution of field hospitals in terms of accessibility with a specific focus on vulnerable strata of the population.

Identifying areas of potential critical healthcare shortages: A case study of spatial accessibility to ICU beds during the COVID-19 pandemic in Florida.

Healthcare resource availability is potentially associated with COVID-19 mortality, and the potentially uneven geographical distribution of resources is a looming concern in the global pandemic. Given that access to healthcare resources is important to overall population health, assessing COVID-19 patients' access to healthcare resources is needed. This paper aims to examine the temporal variations in the spatial accessibility of the U.S. COVID-19 patients to medical facilities, identify areas that are likely to be overwhelmed by the COVID-19 pandemic, and explore associations of low access areas with their socioeconomic and demographic characteristics. We use a three-step floating catchment area method, spatial statistics, and logistic regression to achieve the goals. Findings of this research in the State of Florida revealed that North Florida, rural areas, and zip codes with more Latino or Hispanic populations are more likely to have lower access than other regions during the COVID-19 pandemic. Our approach can help policymakers identify potentially possible low access areas and establish appropriate policy intervention paying attention to those areas during a pandemic.

Spatial accessibility assessment of COVID-19 patients to healthcare facilities: A case study of Florida.

During the COVID-19 pandemic, healthcare facilities worldwide have been overwhelmed by the amount of coronavirus patients needed to be served. Similarly, the U.S. also experienced a shortage of healthcare resources, which led to a reduction in the efficiency of the whole healthcare system. In order to evaluate this from a transportation perspective, it is critical to understand the extent to which healthcare facilities with intensive care unit (ICU) beds are available in both urban and rural areas. As such, this study aims to assess the spatial accessibility of COVID-19 patients to healthcare facilities in the State of Florida. For this purpose, two methods were used: the two-step floating catchment area (2SFCA) and the enhanced two-step floating catchment area (E2SFCA). These methods were applied to identify the high and low access areas in the entire state. Furthermore, a metric, namely the Accessibility Ratio Difference (ARD), was developed to evaluate the spatial access difference between the models. Results revealed that many areas in the northwest and southern Florida have lower access compared to other locations. The residents in central Florida (e.g., Tampa and Orlando cities) had the highest level of accessibility given their higher access ratios. We also observed that the 2SFCA method overestimates the accessibility in the areas with a lower number of ICU beds due to the "equal access" assumption of the population within the catchment area. The findings of this study can provide valuable insights and information for state officials and decision makers in the field of public health.

Special needs hurricane shelters and the ageing population: development of a methodology and a case study application.

Recent experience of hurricanes, particularly in the southeast United States, has heightened awareness of the multifaceted nature of and the challenges to effective disaster relief planning. One key element of this planning is providing adequate shelter at secure locations for people who evacuate. Some of these individuals will have 'special needs', yet there is little research on the relationship with shelter space. This study designed a geographic information systems-based network optimisation methodology for the siting of special needs hurricane relief shelters, with a focus on the transportation component. It sought to find new locations for shelters that maximise accessibility by vulnerable populations, given capacity constraints, concentrating on the ageing population. The framework was implemented in a medium-sized metropolitan statistical area in the state of Florida where data suggest a possible deficit in special needs shelter space. The study analysed options for increasing special needs shelter capacity, while considering potential uncertainties in transportation network availability.

Using urban commuting data to calculate a spatiotemporal accessibility measure for food environment studies.

Improving spatial access to healthy foods in urban regions is recognized as an important component of reducing the prevalence of chronic illness and achieving better health outcomes. Previously, researchers exploring this domain have calculated accessibility measures derived from the travel cost from home locations to nearby food stores. This approach disregards additional opportunities that present themselves as residents move throughout the city. A time-geographic accessibility measure is utilized to explore how single-occupancy automobile commuting affords access to supermarkets. Results show residents in some TAZs have more access when accounting for their commuting behavior than when measuring access from their home. This finding suggests more nuanced calculations of accessibility are necessary to fully understand which urban populations have greater access to healthy food.

Optimizing hurricane disaster relief goods distribution: model development and application with respect to planning strategies.

Over the last few years, hurricane emergencies have been among the most pervasive major disruptions in the United States, particularly in the south-east region of the country. A key aspect of managing hurricane disasters involves logistical planning to facilitate the distribution and transportation of relief goods to populations in need. This study shows how a variant of the capacitated warehouse location model can be used to manage the flow of goods shipments to people in need. In this application, the model is used with protocols set forth in Florida's Comprehensive Emergency Plan and tested in a smaller city in north Florida. Scenarios explore the effects of alternate goods distribution strategies on the provision of disaster relief. Results show that measures describing people's accessibility to relief goods are affected by the distribution infrastructure used to provide relief, as well as assumptions made regarding the population(s) assumed to be in need of aid.

Analyzing location-based accessibility to dental services: an Ohio case study.

UNLABELLED: Oral health is important to overall health. Therefore, dental services should be available and accessible in order for patients to receive care. OBJECTIVE: This study aims to identify regional inequities in dental provider location and suggest an innovative methodology that could be useful in establishing new dental facilities that are geographically accessible. METHODS: Using a census of dentist locations for the state of Ohio in 1998, geographical accessibility to dental care was analyzed. A geographic information systems (GIS)-based model to evaluate the regional distribution of dentists was developed. In this article, it is applied to estimate the number of new dental facilities needed based on the geographical proximity or distance to nearest dentist or dental facility. Results are interactively displayed and mapped with GIS for visualization. RESULTS: Four hundred thirteen of 1,008 zip codes in Ohio did not have dentists. Using a service standard of S = 5 (all zip codes without dentists must be within 5 miles of a zip code with a dentist), 307 zip codes were not served by dentists. With a standard of S = 10, only 45 zip codes in Ohio were not served by dentists, with only 24 additional offices needed to be located to allow accessibility to a dentist within 10 miles. CONCLUSIONS: Using GIS and geographical techniques to reveal and solve the potential locational inequities in accessibility to dental care, this work links oral health policy with geographical techniques.