The spread of the COVID-19 pandemic was spatially heterogeneous around the world; the transmission of the disease is driven by complex spatial and temporal variations in socioenvironmental factors. Spatial tools are useful in supporting COVID-19 control programs. A substantive review of the merits of the methodological approaches used to understand the spatial epidemiology of the disease is hardly undertaken. In this study, we reviewed the methodological approaches used to identify the spatial and spatiotemporal variations of COVID-19 and the socioeconomic, demographic and climatic drivers of such variations. We conducted a systematic literature search of spatial studies of COVID-19 published in English from Embase, Scopus, Medline, and Web of Science databases from 1 January 2019 to 7 September 2021. Methodological quality assessments were also performed using the Joanna Briggs Institute (JBI) risk of bias tool. A total of 154 studies met the inclusion criteria that used frequentist (85%) and Bayesian (15%) modelling approaches to identify spatial clusters and the associated risk factors. Bayesian models in the studies incorporated various spatial, temporal and spatiotemporal effects into the modelling schemes. This review highlighted the need for more local-level advanced Bayesian spatiotemporal modelling through the multi-level framework for COVID-19 prevention and control strategies.

/pdf/methods-used-in-the-spatial-and-spatiotemporal-analysis-of-2oo1a75v.pdf

Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review

Urban green and blue spaces (UGBS) have the potential to improve public health and wellbeing, address health inequities, and provide co-benefits for the environment, economy, and society. To achieve these ambitions, researchers should engage with communities, practitioners, and policy makers in a virtuous circle of research, policy, implementation, and active citizenship using the principles of co-design, co-implementation, co-evaluation, and co-translation. This Viewpoint provides an integrated perspective on the challenges that hinder the delivery of health-enhancing UGBS and recommendations to address them. Our recommendations include: strengthening the evidence beyond cross-sectional research designs, strengthening the evidence base on UGBS intervention approaches, evaluating the effects on diverse population groups and communities, addressing inequities in the distribution and quality of UGBS, accelerating research on blue space, providing evidence for environmental effects, incorporating co-design approaches, developing innovative modelling methods, fostering whole-system evidence, harnessing political drivers, creating collaborations for sustainable UGBS action, and advancing evidence in low-income and middle-income countries. The full potential of UGBS as public health, social, economic, and environmental assets is yet to be realised. Acting on the research and translation recommendations will aid in addressing these challenges in collaboration with research, policy, practice, and communities. 

Advancing urban green and blue space contributions to public health.

Many people visited urban parks during the COVID-19 pandemic to reduce the negative effects of lack of physical activity, social isolation, anxiety, and depression. It is unclear whether all parks are robust against the pandemic, helping people sustain healthy daily living through the diverse activities within them. Nevertheless, few studies have identified the specific relationship between park visits and the COVID-19 pandemic. Therefore, this study aims to demonstrate how physical features such as type, functionality, and access influenced daily visiting to parks during the pandemic, using mobile phone data at a micro level. This study first classified urban parks as point-type parks with an area of less than 1 ha, plane-type parks with 1 ha or more, and line-type parks with elongated shapes, while measuring accessibility to residential, employment, transportation, and auxiliary facilities within the park. The study employed the multi-level regression model with random intercept to investigate the effects of differing park visits, focusing on Goyang city, South Korea. Our analysis results identified that easy access from home was more important than the park size during the pandemic. If we look at the types of parks, the use of both plane- and point-type parks increased more than that of line-type parks. However, line-type parks near homes, along with shopping and sports facilities, were found to be more robust to the pandemic. These findings can be informative to provide specific guidelines to fulfill the enhanced role of parks in sustaining public health during an infectious disease pandemic that may strike again.

https://www.mdpi.com/1660-4601/19/10/6062/pdf?version=1652772560

Are All Urban Parks Robust to the COVID-19 Pandemic? Focusing on Type, Functionality, and Accessibility

By the end of 2021, the Omicron variant of coronavirus disease 2019 had become the dominant cause of a worldwide pandemic crisis. This demands a deeper analysis to support policy makers in creating interventions that not only protect people from the pandemic but also remedy its negative effects on the economy. Thus, this study investigated people’s mobility changes through the relationship between spatiotemporal population density and urban facilities. Results showed that places related to daily services, restaurants, commercial areas, and offices experienced decreased visits, with the highest decline belonging to commercial facilities. Visits to health care and production facilities were stable on weekdays but increased on holidays. Educational institutions’ visits decreased on weekdays but increased on holidays. People’s visits to residential housing and open spaces increased, with the rise in residential housing visits being more substantial. The results also confirmed that policy interventions (e.g., declaration of emergency and upgrade of restriction level) have a great impact on people’s mobility in the short term. The findings would seem to indicate that visit patterns at service and restaurant places decreased least during the pandemic. The analysis outcomes suggest that policy makers should pay more attention to risk perception enhancement as a long-term measure. Furthermore, the study clarified the population density of each facility type in a time series. Improving model performance would be promising for tracking and predicting the spread of future pandemics. 

Changes in mobility amid the COVID-19 pandemic in Sapporo City, Japan: An investigation through the relationship between spatiotemporal population density and urban facilities

On 30 January 2020, the World Health Organization (WHO) declared the current novel coronavirus disease 2019 (COVID-19) as a public health emergency of international concern and later characterized it as a pandemic. New data show that excess body mass and vitamin D deficiency might be related to the disease severity and mortality. The aim of this study was to evaluate whether latitude, as a proxy of sunlight exposure and Vitamin D synthesis, and prevalent obesity among European populations, is related to COVID-19 spread and severity. European COVID-19 data (incidence and fatality), including information on the prevalence of obesity, social distancing, and others were obtained by the "Our World in Data" website on 17 April 2021. Adjusted analysis showed that higher COVID-19 incidence and fatality were pictured in countries being in higher latitude, both during the whole period, as well as, during the time period 1 November 2020-31 March 2021. Higher incidence and fatality of COVID-19 were observed where the prevalence of overweight/obesity was higher during the whole time period, whereas during the time period 1 November 2020-31 March 2021, only COVID-19 incidence was higher but not a fatality. The present results provide insights for targeted interventions and preventive strategies against COVID-19. 

/pdf/covid-19-mortality-in-europe-by-latitude-and-obesity-status-2bj1pjjr.pdf

COVID-19 Mortality in Europe, by Latitude and Obesity Status: A Geo-Spatial Analysis in 40 Countries

Background: On January 21, 2020, the World Health Organization reported the first case of severe acute respiratory syndrome coronavirus 2, which rapidly evolved to the COVID-19 pandemic. Since then, the virus has also rapidly spread among Latin American, Caribbean, and African countries.
Objective: The first aim of this study is to identify new emerging COVID-19 clusters over time and space (from January 21 to mid-May 2020) in Latin American, Caribbean, and African regions, using a prospective space–time scan measurement approach. The second aim is to assess the impact of real-time population mobility patterns between January 21 and May 18, 2020, under the implemented government interventions, measurements, and policy restrictions on COVID-19 spread among those regions and worldwide.
Methods: We created a global COVID-19 database, of 218 countries and territories, merging the World Health Organization daily case reports with other measures such as population density and country income levels for January 21 to May 18, 2020. A score of government policy interventions was created for low, intermediate, high, and very high interventions. The population’s mobility patterns at the country level were
obtained from Google community mobility reports. The prospective space–time scan statistic method was applied in five time periods between January and May 2020, and a regression mixed model analysis was used.
Results: We found that COVID-19 emerging clusters within these five periods of time increased from 7 emerging clusters to 28 by mid-May 2020. We also detected various increasing and decreasing relative risk estimates of COVID-19 spread among Latin American, Caribbean, and African countries within the period of analysis. Globally, population mobility to parks and similar leisure areas during at least a minimum of implemented intermediate-level control policies (when compared to low-level control policies) was related to accelerated COVID-19 spread. Results were almost consistent when regional stratified analysis was applied. In addition, worldwide population mobility due to working during high implemented control policies and very high implemented control policies, when compared to low-level control policies, was related to positive COVID-19 spread.
Conclusions: The prospective space–time scan is an approach that low-income and middle-income countries could use to detect emerging clusters in a timely manner and implement specific control policies and interventions to slow down COVID-19 transmission. In addition, real-time population mobility obtained from crowdsourced digital data could be useful for current and future targeted public health and mitigation policies at a global and regional level.

/pdf/estimating-the-covid-19-spread-through-real-time-population-3fzbsy8zt6.pdf

Estimating the COVID-19 spread through real-time population mobility patterns: surveillance in Low- and Middle- income countries.

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Estimating the COVID-19 spread through real-time population mobility patterns: surveillance in Low- and Middle- income countries.