Accessibility of Vaccination Centers in COVID-19 Outbreak Control: A GIS-Based Multi-Criteria Decision Making Approach

Optimizing the Selection of Mass Vaccination Sites: Access and Equity Consideration

In the early phases of the COVID-19 pandemic, vaccine accessibility was limited, impacting large metropolitan areas such as Los Angeles County, which has over 10 million residents but only nine initial vaccination sites, which resulted in people experiencing long travel times to get vaccinated. We developed a mixed-integer linear model to optimize site selection, considering equitable access for vulnerable populations. Analyzing 277 zip codes between December 2020 and May 2021, our model incorporated factors such as car ownership, ethnic group disease vulnerability, and the Healthy Places Index, alongside travel times by car and public transit. Our optimized model significantly outperformed actual site allocations for all ethnic groups. We observed that White populations faced longer travel times, likely due to their residences being in more remote, less densely populated areas. Conversely, areas with higher Latino and Black populations, often closer to the city center, benefited from shorter travel times in our model. However, those without cars experienced greater disadvantages. While having many vaccination sites might improve access for those dependent on public transit, that advantage is diminished if people must search among many sites to find a location with available vaccines.

Human Papillomavirus (HPV) Vaccine Coverage and Confidence in Italy: A Nationwide Cross-Sectional Study, the OBVIOUS Project

BACKGROUND

Human Papillomavirus (HPV) vaccination rates are still below the target due to vaccine refusal or delay, lack of knowledge, and logistical challenges. Understanding these barriers is crucial for developing strategies to improve HPV vaccination rates.

METHODS

This cross-sectional study used a questionnaire to investigate social and behavioral factors influencing decision making about the HPV vaccine. The survey was conducted from 11 April to 29 May 2022 and involved 10,000 Italian citizens aged ≥ 18 years. The sample was stratified based on region of residence, gender, and age group.

RESULTS

3160 participants were surveyed about themselves, while 1266 respondents were surveyed about their children's vaccine uptake. Among females aged ≥ 26 years, the national average HPV vaccine uptake was 21.7%, with variations across different regions. In the 18-25 age group, females had a vaccine uptake (80.8%) twice as much as males (38.1%), while vaccine uptake among male and female children aged 9-11 was similar.

CONCLUSIONS

The OBVIOUS study in Italy reveals factors influencing low HPV vaccine uptake, suggesting targeted approaches, tailored information campaigns, heightened awareness of eligibility, promoting early vaccination, addressing low-risk perception among males, addressing safety concerns, and enhancing perceived accessibility to improve vaccine uptake and mitigate health risks.

Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

When COVID-19 spread in China in December 2019, thousands of studies have focused on this pandemic. Each presents a unique perspective that reflects the pandemic's main scientific disciplines. For example, social scientists are concerned with reducing the psychological impact on the human mental state especially during lockdown periods. Computer scientists focus on establishing fast and accurate computerized tools to assist in diagnosing, preventing, and recovering from the disease. Medical scientists and doctors, or the frontliners, are the main heroes who received, treated, and worked with the millions of cases at the expense of their own health. Some of them have continued to work even at the expense of their lives. All these studies enforce the multidisciplinary work where scientists from different academic disciplines (social, environmental, technological, etc.) join forces to produce research for beneficial outcomes during the crisis. One of the many branches is computer science along with its various technologies, including artificial intelligence, Internet of Things, big data, decision support systems (DSS), and many more. Among the most notable DSS utilization is those related to multicriterion decision making (MCDM), which is applied in various applications and across many contexts, including business, social, technological and medical. Owing to its importance in developing proper decision regimens and prevention strategies with precise judgment, it is deemed a noteworthy topic of extensive exploration, especially in the context of COVID-19-related medical applications. The present study is a comprehensive review of COVID-19-related medical case studies with MCDM using a systematic review protocol. PRISMA methodology is utilized to obtain a final set of (n = 35) articles from four major scientific databases (ScienceDirect, IEEE Xplore, Scopus, and Web of Science). The final set of articles is categorized into taxonomy comprising five groups: (1) diagnosis (n = 6), (2) safety (n = 11), (3) hospital (n = 8), (4) treatment (n = 4), and (5) review (n = 3). A bibliographic analysis is also presented on the basis of annual scientific production, country scientific production, co-occurrence, and co-authorship. A comprehensive discussion is also presented to discuss the main challenges, motivations, and recommendations in using MCDM research in COVID-19-related medial case studies. Lastly, we identify critical research gaps with their corresponding solutions and detailed methodologies to serve as a guide for future directions. In conclusion, MCDM can be utilized in the medical field effectively to optimize the resources and make the best choices particularly during pandemics and natural disasters.

Improving the Spatial Accessibility of Community-Level Healthcare Service toward the ‘15-Minute City’ Goal in China

Background: The recent global COVID-19 pandemic serves as another reminder that people in different urban neighborhoods need equal access to basic medical services. This study aims to improve the spatial accessibility of healthcare services toward the ‘15-minute city’ goal. Methods: We chose Zhengzhou, China, as a case study. To improve spatial accessibility, two optimization models of optimal supply-demand allocation (OSD) and the capacitated p-medina problem (CPMP) were used. Spatial accessibility in this study is defined as the walking time from the communities to healthcare centers. Results: For the current status of healthcare services at the community level, the mean travel time is 18.3 min, and 39.6% of residents can access healthcare services within a 15-minute travel time. Population coverage within a 15-minute walking time is significantly lower than the national target of 80%. After redefining the service areas through OSD allocation, the mean travel time was reduced to 16.5 min, and 45.1% of the population could reach services. Furthermore, the 60 newly proposed healthcare centers selected by the CPMP model could potentially increase by 35.0% additional population coverage. The average travel time was reduced to 10 min. Conclusions: Both the redefinition of the service areas and the opening of new service centers are effective ways to improve the spatial accessibility of healthcare services. Two methods of this study have implications for urban planning practices towards the 15-minute city.

Spatial Syndromic Surveillance and COVID-19 in the U.S.: Local Cluster Mapping for Pandemic Preparedness

Maps have become the de facto primary mode of visualizing the COVID-19 pandemic, from identifying local disease and vaccination patterns to understanding global trends. In addition to their widespread utilization for public communication, there have been a variety of advances in spatial methods created for localized operational needs. While broader dissemination of this more granular work is not commonplace due to the protections under Health Insurance Portability and Accountability Act (HIPAA), its role has been foundational to pandemic response for health systems, hospitals, and government agencies. In contrast to the retrospective views provided by the aggregated geographies found in the public domain, or those often utilized for academic research, operational response requires near real-time mapping based on continuously flowing address level data. This paper describes the opportunities and challenges presented in emergent disease mapping using dynamic patient data in the response to COVID-19 for northeast Ohio for the period 2020 to 2022. More specifically it shows how a new clustering tool developed by geographers in the initial phases of the pandemic to handle operational mapping continues to evolve with shifting pandemic needs, including new variant surges, vaccine targeting, and most recently, testing data shortfalls. This paper also demonstrates how the geographic approach applied provides the framework needed for future pandemic preparedness.

Modeling Health Seeking Behavior Based on Location-Based Service Data: A Case Study of Shenzhen, China

Understanding residents’ health seeking behavior is crucial for the planning and utilization of healthcare resources. With the support of emerging location-based service (LBS) data, this study proposes a framework for inferring health seeking trips, measuring observed spatial accessibility to healthcare, and interpreting the determinants of health seeking behavior. Taking Shenzhen, China as a case study, a supply–demand ratio calculation method based on observed data is developed to explore basic patterns of health seeking, while health seeking behavior is described using a spatial analysis framework based on the Huff model. A total of 95,379 health seeking trips were identified, and their analysis revealed obvious differences between observed and potential spatial accessibility. In addition to the traditional distance decay effect and number of doctors, the results showed health seeking behavior to be determined by hospital characteristics such as hospital scale, service quality, and popularity. Furthermore, this study also identified differences in health seeking behavior between subgroups with different ages, incomes, and education levels. The findings highlight the need to incorporate actual health seeking behavior when measuring the spatial accessibility of healthcare and planning healthcare resources. The framework and methods proposed in this study can be applied to other contexts and other types of public facilities.

Assessing the impact of mobility on the incidence of COVID-19 in Dublin City

COVID-19 has had a major impact on the transport systems around the world. Several transport-related policies were implemented in short period of time to contain the spread of the pandemic. These policies had a major influence on travel behavior and people's perception towards the safety of different modes of transport, especially public transport, thus affecting several sustainable mobility initiatives. To build a resilient and sustainable transport system and to rebuild trust in public transport, it is important to understand the role of mobility in the spread of COVID-19 pandemic. The present study investigates the relationship between mobility and reported COVID-19 infections using data from Dublin city. Different modes of transport including traffic volume, bus passengers, pedestrians and cyclists were considered in the study during a forty week period. Multiple scenarios involving two-week lag and three-week lag of mobility data and COVID-19 infections were considered in building statistical models. Results showed that, 36.2% of the reported COVID-19 infections after a two-week lag and 33% of the infections after a three-week lag. Our research examines the links between movements and COVID-19 numbers, but clearly this was not the only reason for increased case numbers as many other events impacted on increased numbers. The study further discusses the policy implications and strategies for ensuring a resilient and sustainable transport system.

Access to the COVID-19 services during the pandemic - a scoping review

Appropriate accessibility to coronavirus disease 2019 (COVID-19) services is essential in the efficient management of the pandemic. Different geospatial methods and approaches have been used to measure accessibility to COVID-19 health-related services. This scoping review aimed to summarize and synthesize the geospatial studies conducted to measure accessibility to COVID-19 healthcare services. Web of Science, Scopus, and PubMed were searched to find relevant studies. From 1113 retrieved unique citations, 26 articles were selected to be reviewed. Most of the studies were conducted in the USA and floating catchment area methods were mostly used to measure the spatial accessibility to COVID-19 services including vaccination centres, Intensive Care Unit beds, hospitals and test sites. More attention is needed to measure the accessibility of COVID-19 services to different types of users especially with combining different non-spatial factors which could lead to better allocation of resources especially in populations with limited resources.

Spatial Analysis of COVID-19 Vaccine Centers Distribution: A Case Study of the City of Jeddah, Saudi Arabia

The COVID-19 pandemic is one of the most devastating public health emergencies in history. In late 2020 and after almost a year from the initial outbreak of the novel coronavirus (SARS-CoV-2), several vaccines were approved and administered in most countries. Saudi Arabia has established COVID-19 vaccination centers in all regions. Various facilities were selected to set up these vaccination centers, including conference and exhibition centers, old airport terminals, pre-existing medical facilities, and primary healthcare centers. Deciding the number and locations of these facilities is a fundamental objective for successful epidemic responses to ensure the delivery of vaccines and other health services to the entire population. This study analyzed the spatial distribution of COVID-19 vaccination centers in Jeddah, a major city in Saudi Arabia, by using GIS tools and methods to provide insight on the effectiveness of the selection and distribution of the COVID-19 vaccination centers in terms of accessibility and coverage. Based on a spatial analysis of vaccine centers’ coverage in 2020 and 2021 in Jeddah presented in this study, coverage deficiency would have been addressed earlier if the applied GIS analysis methods had been used by authorities while gradually increasing the number of vaccination centers. This study recommends that the Ministry of Health in Saudi Arabia evaluated the assigned vaccination centers to include the less-populated regions and to ensure equity and fairness in vaccine distribution. Adding more vaccine centers or reallocating some existing centers in the denser districts to increase the coverage in the uncovered sparse regions in Jeddah is also recommended. The methods applied in this study could be part of a strategic vaccination administration program for future public health emergencies and other vaccination campaigns.