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      Using Urban Landscape Pattern to Understand and Evaluate Infectious Disease Risk: A Case Study of COVID-19 in Wuhan

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          Abstract

          COVID-19 case numbers in 161 sub-districts of Wuhan were investigated based on landscape epidemiology, and their landscape metrics were calculated based on land use/land cover (LULC). Initially, a mediation model verified a partially mediated population role in the relationship between landscape pattern and infection number. Adjusted incidence rate (AIR) and community safety index (CSI), two indicators for infection risk in sub-districts, were 25.82∼63.56 ‱ and 3.00∼15.87 respectively, and central urban sub-districts were at higher infection risk. Geographically weighted regression (GWR) performed better than OLS regression with AICc differences of 7.951∼181.261. The adjusted R 2 in GWR models of class-level index and infection risk were 0.697 to 0.817, while for the landscape-level index they were 0.668 to 0.835. Secondly, 16 key landscape metrics were identified based on GWR, and then a prediction model for infection risk in sub-districts and communities was developed. Using principal component analysis (PCA), development intensity, landscape level, and urban blue-green space were considered to be principal components affecting disease infection risk, explaining 73.1% of the total variance. Cropland (PLAND and LSI), urban land (NP, LPI, and LSI) and unused land (NP) represent development intensity, greatly affecting infection risk in urban areas. Landscape level CONTAG, DIVISION, SHDI, and SHEI represent mobility and connectivity, having a profound impact on infection risk in both urban and suburban areas. Water (PLAND, NP, LPI, and LSI) and woodland (NP, and LSI) represent urban blue-green spaces, and were particularly important for infection risk in suburban areas.

          Based on urban landscape pattern, we proposed a framework to understand and evaluate infection risk. These findings provide a basis for risk evaluation and policy-making of urban infectious disease, which is significant for community management and urban planning for infectious disease worldwide.

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          Most cited references54

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          The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations.

          Reuben M. Baron, David A Kenny (1986)
          In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.
          Article 0 comments Cited 4167 times – based on 0 reviews     Review now
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            Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods.

            David P. MacKinnon, Chondra Lockwood, Jason Henry Williams (2004)
            The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the bias-corrected bootstrap the best method overall.
            Article 0 comments Cited 733 times – based on 0 reviews     Review now
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              Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China

              Yueling Ma, Yadong Zhao, Jiangtao Liu … (2020)
              Meteorological parameters are the important factors influencing the infectious diseases such as severe acute respiratory syndrome (SARS) and influenza. This study aims to explore the association between Corona Virus Disease 2019 (COVID-19) deaths and weather parameters. In this study, we collected the daily death numbers of COVID-19, meteorological parameters and air pollutant data from 20 January 2020 to 29 February 2020 in Wuhan, China. Generalized additive model was applied to explore the effect of temperature, humidity and diurnal temperature range on the daily death counts of COVID-19. There were 2299 COVID-19 death counts in Wuhan during the study period. A positive association with COVID-19 daily death counts was observed for diurnal temperature range (r = 0.44), but negative association for relative humidity (r = −0.32). In addition, one unit increase in diurnal temperature range was only associated with a 2.92% (95% CI: 0.61%, 5.28%) increase in COVID-19 deaths in lag 3. However, both 1 unit increase of temperature and absolute humidity were related to the decreased COVID-19 death in lag 3 and lag 5, with the greatest decrease both in lag 3 [−7.50% (95% CI: −10.99%, −3.88%) and −11.41% (95% CI: −19.68%, −2.29%)]. In summary, this study suggests the temperature variation and humidity may also be important factors affecting the COVID-19 mortality.
              Article 0 comments Cited 373 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Urban For Urban Green
                Journal ID (iso-abbrev): Urban For Urban Green
                Title: Urban Forestry & Urban Greening
                Publisher: Published by Elsevier GmbH.
                ISSN (Print): 1618-8667
                ISSN (Electronic): 1610-8167
                Publication date PMC-release: 2 April 2021
                Publication date (Electronic): 2 April 2021
                Electronic Location Identifier: 127126
                Affiliations
                [a ]Department of Landscape Architecture, College of Horticulture and Forest, Huazhong Agricultural University, No. 1, Shizishan Street Hongshan District, Wuhan, Hubei Province, 430070, China
                [b ]Key Laboratory of Urban Agriculture in Central China, Ministry of Agriculture and Rural Affairs, China
                Author notes
                [* ]Corresponding author at: Department of Landscape Architecture, College of Horticulture and Forest, Huazhong Agricultural University, Hongshan District, Wuhan, 430070, China.
                Article
                Publisher Item ID: S1618-8667(21)00151-5 Publisher ID: 127126
                DOI: 10.1016/j.ufug.2021.127126
                PMC ID: 8017915
                PubMed ID: 33824634
                SO-VID: 7a9ec7c2-cfcb-4fef-a744-296c3eaa2555
                Copyright statement: © 2021 Published by Elsevier GmbH.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 10 June 2020
                Date revision received : 26 February 2021
                Date accepted : 30 March 2021
                Categories
                Subject: Article

                Keywords: landscape pattern,infection risk,landscape metrics,landscape epidemiology,covid-19,wuhan
                Data availability:
                Keywords: landscape pattern, infection risk, landscape metrics, landscape epidemiology, covid-19, wuhan

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