Spatial statistical analysis of pre-existing mortalities of 20 diseases with COVID-19 mortalities in the continental United States

Mollalo, Abolfazl; Rivera, Kiara M.; Vahabi, Nasim

doi:10.1016/j.scs.2021.102738

Cited by 35 publications

(21 citation statements)

References 45 publications

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“…Global Moran’s I statistic was employed on the model’s residuals to determine whether the residuals are spatially autocorrelated [ 39 , 40 ]. A significant spatial autocorrelation among residuals indicates the model is missing key covariates [ 41 , 42 ].…”

Section: Methodsmentioning

confidence: 99%

Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States

Mollalo

Tatar

2021

IJERPH

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Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribution of vaccination rates, mainly based on the social vulnerability index (SVI). In this study, we compiled a database of the percentage of fully vaccinated people at the county scale across the continental United States as of 29 July 2021, along with SVI data as potential significant covariates. We further employed multiscale geographically weighted regression to model spatial nonstationarity of vaccination rates. Our findings indicated that the model could explain over 79% of the variance of vaccination rate based on Per capita income and Minority (%) (with positive impacts), and Age 17 and younger (%), Mobile homes (%), and Uninsured people (%) (with negative effects). However, the impact of each covariate varied for different counties due to using separate optimal bandwidths. This timely study can serve as a geospatial reference to support public health decision-makers in forming region-specific policies in monitoring vaccination programs from a geographic perspective.

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Section: Methodsmentioning

confidence: 99%

Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States

Mollalo

Tatar

2021

IJERPH

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“…Achieving this will reduce the burden of disease, reduce the pressure on health facilities and human resources, and as a result, hospitalized patients will enjoy better and more efficient services [29]. On the other hand, due to the importance of time in controlling the virus spread and the fact that the widespread implementation of laws and policies is time-consuming, it is necessary to protect society by implementing classified policies from the cities to the national level [52]. According to the study by Ainslie et al, China was able to quickly implement restrictions-reduction strategies, which led to economic recovery [33].…”

Section: • Providing Financial Support For Vulnerable Businessesmentioning

confidence: 99%

Social distance capacity to control the COVID-19 pandemic: A systematic review on time series analysis

Khosravizadeh

Ahadinezhad

Maleki

et al. 2022

JRS

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BACKGROUND: Reducing interpersonal contact has been one of the least expensive and most widely used COVID-19 control strategies. OBJECTIVE: This systematic review has been conducted with the aim of identifying social distancing strategies and policies and their impact on the COVID-19 pandemic. METHODS: In order to compile this systematic review, Google Scholar, PubMed, Scopus, Web of Science, Science Direct, Magiran, SID, and Irandoc databases were searched from the COVID-19 outbreak until March 2021. Keywords included “social”, “physical”, “distance”, “outbreak”, “incidence”, “prevalence”, “spread”, “new case”, “death*”, “mortality*”, “morbidity*” , “covid-19”, “coronavirus”, “sars-cov-2” and “time series*”. The articles were qualitatively evaluated by two researchers using the STROBE tool. Finally, the study data were divided into three conceptual categories by three researchers, who then agreed on one category. The practical suggestions were also categorized in the same way. RESULTS: The policies and strategies adopted to implement social distancing were included in five categories of restrictions, prohibitions, closures, incentives, and punishments. Transportation and travel restrictions, crowded places and schools closure, use of telecommunications and virtual communications, and financial and psychological support to society members were the main policies in this area. CONCLUSION: Rapid and complete vaccination of all people around the world is out of reach, therefore social distancing and the implementation of physical restraints, especially in crowded and densely populated environments, should be done extensively until COVID-19 is eradicated.

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“…In that study, hotspots and high/low-risk areas were detected by using the Getis-Ord Gi* and Local Moran’s I statistic [ 11 , 12 ]. A univariate regression model was developed to quantify the association of COVID-19 mortality with common risk factors [ 13 ] including age [ 14 , 15 ], sex [ 16 , 17 ], co-morbidities [ 18 , 19 ], hospitalization length [ 20 , 21 ] and transfer to an Intensive Care Unit (ICU) [ 16 , 20 ]. Here, a comprehensive spatial-epidemiological dataset linked to other urban data at the census level is offered for further investigation to identify transmission trends and clustering patterns of the COVID-19 incidence in the densely populated city.…”

Section: Objectivementioning

confidence: 99%

A spatial-epidemiological dataset of subjects infected by SARS-CoV-2 during the first wave of the pandemic in Mashhad, second-most populous city in Iran

et al. 2021

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Objective In March 2020, Iran tackled the first national wave of COVID-19 that was particularly felt in Mashhad, Iran’s second-most populous city. Accordingly, we performed a spatio-temporal study in this city to investigate the epidemiological aspects of the disease in an urban area and now wish to release a comprehensive dataset resulting from this study. Data description These data include two data files and a help file. Data file 1: “COVID-19_Patients_Data” contains the patient sex and age + time from symptoms onset to hospital admission; hospitalization time; co-morbidities; manifest symptoms; exposure up to 14 days before admission; disease severity; diagnosis (with or without RT-PCR assay); and outcome (recovery vs. death). The data covers 4000 COVID-19 patients diagnosed between 14 Feb 2020 and 11 May 2020 in Khorasan-Razavi Province. Data file 2: “COVID-19_Spatiotemporal_Data” is a digital map of census tract divisions of Mashhad, the capital of the province, and their population by gender along with the number of COVID-19 cases and deaths including the calculated rates per 100,000 persons. This dataset can be a valuable resource for epidemiologists and health policymakers to identify potential risk factors, control and prevent pandemics, and optimally allocate health resources.

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Spatial statistical analysis of pre-existing mortalities of 20 diseases with COVID-19 mortalities in the continental United States

Cited by 35 publications

References 45 publications

Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States

Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States

Social distance capacity to control the COVID-19 pandemic: A systematic review on time series analysis

A spatial-epidemiological dataset of subjects infected by SARS-CoV-2 during the first wave of the pandemic in Mashhad, second-most populous city in Iran

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