Smart probes for optical imaging of T cells and screening of anti-cancer immunotherapies.

T cells are an essential part of the immune system with crucial roles in adaptive response and the maintenance of tissue homeostasis. Depending on their microenvironment, T cells can be differentiated into multiple states with distinct functions. This myriad of cellular activities have prompted the development of numerous smart probes, ranging from small molecule fluorophores to nanoconstructs with variable molecular architectures and fluorescence emission mechanisms. In this Tutorial Review, we summarize recent efforts in the design, synthesis and application of smart probes for imaging T cells in tumors and inflammation sites by targeting metabolic and enzymatic biomarkers as well as specific surface receptors. Finally, we briefly review current strategies for how smart probes are employed to monitor the response of T cells to anti-cancer immunotherapies. We hope that this Review may help chemists, biologists and immunologists to design the next generation of molecular imaging probes for T cells and anti-cancer immunotherapies.

Impact of the COVID-19 pandemic on travel behavior: A case study of domestic inbound travelers in Jeju, Korea.

This study analyzes a large-scale navigation dataset that captures travel activities of domestic inbound visitors in Jeju, Korea in the first nine months of 2020. A collection of regression models are introduced to quantify the dynamic effects of local and national COVID-19 indicators on their travel behavior. Results suggest that behavior of inbound travelers was jointly affected by pandemic severity locally and remotely. The daily number of new cases in Jeju has a greater impact on reducing travel activities than the national-level daily new cases of COVID-19. The impacts of the pandemic did not diminish over time but produced heterogeneous effects on travels with different trip purposes. Our findings reveal the persistence of COVID-19's effects on travel behavior and the variability in travelers' responses across tourism activities with different levels of perceived health risks. The implications for crisis management and recovery strategies are also discussed.

Nosocomial Outbreak of Coronavirus Disease 2019 by Possible Airborne Transmission Leading to a Superspreading Event.

BACKGROUND: Nosocomial outbreaks with superspreading of coronavirus disease 2019 due to a possible airborne transmission have not been reported. METHODS: Epidemiological analysis, environmental samplings, and whole-genome sequencing (WGS) were performed for a hospital outbreak. RESULTS: A superspreading event that involved 12 patients and 9 healthcare workers (HCWs) occurred within 9 days in 3 of 6 cubicles at an old-fashioned general ward with no air exhaust built within the cubicles. The environmental contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was significantly higher in air grilles (>2 m from patients' heads and not within reach) than on high-touch clinical surfaces (36.4%, 8 of 22 vs 3.4%, 1 of 29, P = .003). Six (66.7%) of 9 contaminated air exhaust grilles were located outside patient cubicles. The clinical attack rate of patients was significantly higher than of HCWs (15.4%, 12 of 78 exposed patients vs 4.6%, 9 of 195 exposed HCWs, P = .005). Moreover, the clinical attack rate of ward-based HCWs was significantly higher than of nonward-based HCWs (8.1%, 7 of 68 vs 1.8%, 2 of 109, P = .045). The episodes (mean ±â€…standard deviation) of patient-care duty assignment in the cubicles was significantly higher among infected ward-based HCWs than among noninfected ward-based HCWs (6.0 ±â€…2.4 vs 3.0 ±â€…2.9, P = .012) during the outbreak period. The outbreak strains belong to SARS-CoV-2 lineage B.1.36.27 (GISAID clade GH) with the unique S-T470N mutation on WGS. CONCLUSIONS: This nosocomial point source superspreading event due to possible airborne transmission demonstrates the need for stringent SARS-CoV-2 screening at admission to healthcare facilities and better architectural design of ventilation systems to prevent such outbreaks. Portable high-efficiency particulate filters were installed in each cubicle to improve ventilation before resumption of clinical service.

Environmental impacts of shifts in energy, emissions, and urban heat island during the COVID-19 lockdown across Pakistan.

Restrictions on human and industrial activities due to the coronavirus (COVID-19) pandemic have resulted in an unprecedented reduction in energy consumption and air pollution around the world. Quantifying these changes in environmental conditions due to government-enforced containment measures provides a unique opportunity to understand the patterns, origins and impacts of air pollutants. During the lockdown in Pakistan, a significant reduction in energy demands and a decline of ∼1786 GWh (gigawatt hours) in electricity generation is reported. We used satellite observational data for nitrogen dioxide (NO2), carbon monoxide (CO), sulphur dioxide (SO2), aerosol optical depth (AOD) and land surface temperature (LST) to explore the associated environmental impacts of shifts in energy demands and emissions across Pakistan. During the strict lockdown period (March 23 to April 15, 2020), we observed a reduction in NO2 emissions by 40% from coal-based power plants followed by 30% in major urban areas compared to the same period in 2019. Also, around 25% decrease in AOD (at 550 nm) thickness in industrial and energy sectors was observed although no major decrease was evident in urban areas. Most of the industrial regions resumed emissions during the 3rd quarter of April 2020 while the urban regions maintained reduced emissions for a longer period. Nonetheless, a gradual increase has been observed since April 16 due to relaxations in lockdown implementations. Restrictions on transportation in the cities resulted in an evident drop in the surface urban heat island (SUHI) effect, particularly in megacities. The changes reported as well as the analytical framework provides a baseline benchmark to assess the sectoral pollution contributions to air quality, especially in the scarcity of ground-based monitoring systems across the country.

Development of the Adjusted Wind Chill Equivalent Temperature (AWCET) for cold mortality assessment across a subtropical city: validation and comparison with a spatially-controlled time-stratified approach.

BACKGROUND: Global warming has reduced the adaptability of the people living in subtropical regions to cope up with cold stress due to lengthening of hot days and shortening of transition period from hot to cold weather. However, existing studies on measuring cold stress are based on biometeorological indices designed for temperate regions. This may overestimate the impact of wind chill on mortality risk in subtropical cities. METHODS: This study developed an Adjusted Wind Chill Equivalent Temperature (AWCET) index. A spatially-controlled time-stratified approach was applied to evaluate the ability of AWCET for estimating cold mortality in subtropical cities, based on a mortality dataset (2008-2012) in Hong Kong. RESULTS: The use of AWCET could indicate increase in all-cause, cardiovascular, respiratory, and cancer-related mortality risk during the days with average temperature < = 1st [11.0 °C], <= 3rd [12.6 °C] and < = 5th [13.4 °C] percentiles. The results were stable and consistent based on both log-linear and curve-linear relationships between AWCET and mortality risk. AWCET was also compared with the New Wind Chill Equivalent Temperature (NWCET) designed for temperate regions, and has found that higher magnitude of mortality risk would be found when using AWCET for assessing all-cause and cause-specific mortality in Hong Kong, for days with average temperature < = 1st, <= 3rd and < = 5th percentiles. CONCLUSIONS: AWCET is validated to be effective to access cold mortality in the context of subtropical cities. The use of AWCET may enhance the cold weather warning system in subtropical cities, as a supplementary tool to help demonstrating small administrative-level perceived temperature with volunteered geographic information.

Spatial variability of excess mortality during prolonged dust events in a high-density city: a time-stratified spatial regression approach.

BACKGROUND: Dust events have long been recognized to be associated with a higher mortality risk. However, no study has investigated how prolonged dust events affect the spatial variability of mortality across districts in a downwind city. METHODS: In this study, we applied a spatial regression approach to estimate the district-level mortality during two extreme dust events in Hong Kong. We compared spatial and non-spatial models to evaluate the ability of each regression to estimate mortality. We also compared prolonged dust events with non-dust events to determine the influences of community factors on mortality across the city. RESULTS: The density of a built environment (estimated by the sky view factor) had positive association with excess mortality in each district, while socioeconomic deprivation contributed by lower income and lower education induced higher mortality impact in each territory planning unit during a prolonged dust event. Based on the model comparison, spatial error modelling with the 1st order of queen contiguity consistently outperformed other models. The high-risk areas with higher increase in mortality were located in an urban high-density environment with higher socioeconomic deprivation. CONCLUSION: Our model design shows the ability to predict spatial variability of mortality risk during an extreme weather event that is not able to be estimated based on traditional time-series analysis or ecological studies. Our spatial protocol can be used for public health surveillance, sustainable planning and disaster preparation when relevant data are available.

Synergetic analysis of springtime air pollution episodes over Gwangju, Korea.

The characteristics of springtime aerosols, including their optical and microphysical properties, were analyzed for the months of March to May of 2009 in Gwangju (35.23°N, 126.84°E), Korea. A high Light Detection and Ranging (LIDAR)-derived aerosol depolarization ratio (δ) of 0.25±0.04 was determined on dust particles during the observation period. The Ångström exponent values of the 440-870nm wavelength pair (Å440-870) and single-scattering albedo at 675nm (Ω675) measured by a CIMEL sun/sky radiometer were 0.77±0.19 and 0.95±0.01, respectively. The elevated dust layers reached a maximum elevation of 4km above sea level. Anthropogenic/smoke particles that originated from highly populated/industrialized regions could be distinguished by their relatively smaller particle size (Å440-870 ranged between 1.33 and 1.36) and higher light-absorbing (Ω675 of 0.92±0.01) characteristics. These aerosols are mostly distributed at altitudes <1.2km. The root-mean-square deviation (RMSD) between the aerosol optical depth (AOD, τ) derived from LIDAR (τLIDAR) and from the CIMEL sun/sky radiometer (τCIMEL) varied with respect to the surface PM10 concentration. The RMSD between τLIDAR and τCIMEL was as low as 13% under lower PM10 concentration levels (<100µg/m3). In contrast, the RMSD between τLIDAR and τCIMEL increased three times (~31%) under high surface PM10 concentration levels (>100µg/m3). These results suggest that the accuracy of τLIDAR is influenced by specific atmospheric conditions, regardless of its uncertainty.

Development of a personal integrated environmental monitoring system.

Environmental pollution in the urban areas of Hong Kong has become a serious public issue but most urban inhabitants have no means of judging their own living environment in terms of dangerous threshold and overall livability. Currently there exist many low-cost sensors such as ultra-violet, temperature and air quality sensors that provide reasonably accurate data quality. In this paper, the development and evaluation of Integrated Environmental Monitoring System (IEMS) are illustrated. This system consists of three components: (i) position determination and sensor data collection for real-time geospatial-based environmental monitoring; (ii) on-site data communication and visualization with the aid of an Android-based application; and (iii) data analysis on a web server. This system has shown to be working well during field tests in a bus journey and a construction site. It provides an effective service platform for collecting environmental data in near real-time, and raises the public awareness of environmental quality in micro-environments.

An AI-empowered indoor digital contact tracing system for COVID-19 outbreaks in residential care homes.

An AI-empowered indoor digital contact-tracing system was developed using a centralized architecture and advanced low-energy Bluetooth technologies for indoor positioning, with careful preservation of privacy and data security. We analyzed the contact pattern data from two RCHs and investigated a COVID-19 outbreak in one study site. To evaluate the effectiveness of the system in containing outbreaks with minimal contacts under quarantine, a simulation study was conducted to compare the impact of different quarantine strategies on outbreak containment within RCHs. The significant difference in contact hours between weekdays and weekends was observed for some pairs of RCH residents and staff during the two-week data collection period. No significant difference between secondary cases and uninfected contacts was observed in a COVID-19 outbreak in terms of their demographics and contact patterns. Simulation results based on the collected contact data indicated that a threshold of accumulative contact hours one or two days prior to diagnosis of the index case could dramatically increase the efficiency of outbreak containment within RCHs by targeted isolation of the close contacts. This study demonstrated the feasibility and efficiency of employing an AI-empowered system in indoor digital contact tracing of outbreaks in RCHs in the post-pandemic era.

Multi-spatiotemporal AOD trends and association with land use changes over the Guangdong-Hong Kong-Macao Greater Bay Area during 2001-2021.

Analyzing long-term variations of aerosol optical depth (AOD) is beneficial for determining high-pollutant-risk areas and formulating mitigation policies. In this study, multi-spatiotemporal trends and periodicity of AOD, as well as the persistence over the Guangdong-Hong Kong-Macao Greater Bay Area from 2001 to 2021, were investigated by the extreme-point symmetric mode decomposition (ESMD), Theil-Sen Median trend analysis and Hurst exponent. The results elucidate that AOD exhibits fluctuant variations during the 21-year period with the year 2012 as the turning point. There is a slight upward tendency (0.009 year-1) in the pre-2012 period but a pronounced downward trend (- 0.03 year-1) in the post-2012 period, suggesting an overall declining trend in the study area. The northern cities in the area present an increasing-stable-decreasing trend of monthly average AOD, whereas other cities have an increasing-fluctuating-decreasing trend over the study period. The decreasing rate in the western parts is higher than that in the eastern parts, like Zhaoqing, Jiangmen and Foshan city. A continuous decline of AOD is dominated over the study area, whereas an anti-persistence tendency is accumulated in the northeastern parts. Additionally, elevated AOD can be observed in unused land, water bodies and construction land, while grassland, cropland and woodland have lower AOD. The decreasing rate is larger when land-use types with high AOD are converted to those with low AOD; otherwise, the decreasing rate is smaller. The results have a great significance for improving the understanding of long-term variations of AOD, as well as providing a scientific basis to formulate environmental protection and mitigation practices.

Current methods for evaluating people's exposure to green space: A scoping review.

People's exposure to green space is a critical link between urban green space and urban residents' health. Since green space may affect human health through multiple pathways regarding diverse human health outcomes, the measurement of people's exposure to green space must be tailored to concrete study contexts and research questions. In this scoping review, we systematically categorized the available green space representations and metrics in the last two decades that can be used to derive people's exposure to green space regarding different research topics. A three-phase systematic review was conducted after a generalized search of relevant research articles from the three most-used publication databases, namely Scopus, the Web of Science, and PubMed. We identified 260 research articles that particularly discuss green space representations and metrics. We further developed a multi-pathway framework to articulate the complicated context issues in green space studies. We categorized the most relevant green space representations and metrics into five groups, including green space indices, the delineation, inventory, and usage of green space, the spatiotemporal evolution of green space, the attributes and components of green space, and the green space landscape and fragmentation. Finally, we discussed the inter-conversion between different green space representations and metrics, the "mobility-turn" in green space studies and how it may affect the derivation of people's exposure to green space, and other potential methodological issues in measuring people's exposure to green space. Our scoping review provides the most comprehensive framework and categories for deriving people's exposure to green space to date, which may strongly support a broad range of studies that concern green space's health effects.

Marine plastic pollution detection and identification by using remote sensing-meta analysis.

The persistent plastic litter, originating from different sources and transported from rivers to oceans, has posed serious biological, ecological, and chemical effects on the marine ecosystem, and is considered a global issue. In the past decade, many studies have identified, monitored, and tracked marine plastic debris in coastal and open ocean areas using remote sensing technologies. Compared to traditional surveying methods, high-resolution (spatial and temporal) multispectral or hyperspectral remote sensing data have been substantially used to monitor floating marine macro litter (FMML). In this systematic review, we present an overview of remote sensing data and techniques for detecting FMML, as well as their challenges and opportunities. We reviewed the studies based on different sensors and platforms, spatial and spectral resolution, ground sampling data, plastic detection methods, and accuracy obtained in detecting marine litter. In addition, this study elaborates the usefulness of high-resolution remote sensing data in Visible (VIS), Near-infrared (NIR), and Short-Wave InfraRed (SWIR) range, along with spectral signatures of plastic, in-situ samples, and spectral indices for automatic detection of FMML. Moreover, the Thermal Infrared (TIR), Synthetic aperture radar (SAR), and Light Detection and Ranging (LiDAR) data were introduced and these were demonstrated that could be used as a supplement dataset for the identification and quantification of FMML.

Association of Molnupiravir and Nirmatrelvir-Ritonavir with reduced mortality and sepsis in hospitalized omicron patients: a territory-wide study.

This study evaluates the association between antivirals (Molnupiravir and Nirmatrelvir-Ritonavir) and all-cause and respiratory mortality and organ dysfunction among high-risk COVID-19 patients during an Omicron outbreak. Two cohorts, Nirmatrelvir-Ritonavir versus control and Molnupiravir versus control, were constructed with inverse probability treatment weighting to balance baseline characteristics. Cox proportional hazards models evaluated the association of their use with all-cause mortality, respiratory mortality, and all-cause sepsis (a composite of circulatory shock, respiratory failure, acute liver injury, coagulopathy, and acute liver impairment). Patients recruited were hospitalized and diagnosed with the COVID-19 Omicron variant between February 22, 2022 and April 15, 2022, and followed up until May 15, 2022. The study included 17,704 patients. There were 4.67 and 22.7 total mortalities per 1000 person-days in the Nirmatrelvir-Ritonavir and control groups respectively before adjustment (weighted incidence rate ratio, - 18.1 [95% CI - 23.0 to - 13.2]; hazard ratio, 0.18 [95% CI, 0.11-0.29]). There were 6.64 and 25.9 total mortalities per 1000 person-days in the Molnupiravir and control groups respectively before adjustment (weighted incidence rate ratio per 1000 person-days, - 19.3 [95% CI - 22.6 to - 15.9]; hazard ratio, 0.23 [95% CI 0.18-0.30]). In all-cause sepsis, there were 13.7 and 35.4 organ dysfunction events per 1000 person-days in the Nirmatrelvir-Ritonavir and control groups respectively before adjustment (weighted incidence rate ratio per 1000 person-days, - 21.7 [95% CI - 26.3 to - 17.1]; hazard ratio, 0.44 [95% CI 0.38-0.52]). There were 23.7 and 40.8 organ dysfunction events in the Molnupiravir and control groups respectively before adjustment (weighted incidence ratio per 1000 person-days, - 17.1 [95% CI, - 20.6 to - 13.6]; hazard ratio, 0.63 [95% CI 0.58-0.69]). Among COVID-19 hospitalized patients, use of either Nirmatrelvir-Ritonavir or Molnupiravir compared with no antiviral use was associated with a significantly lower incidence of 28-days all-cause and respiratory mortality and sepsis.

Analysis of airborne particulate matter (PM2.5) over Hong Kong using remote sensing and GIS.

Airborne fine particulates (PM(2.5); particulate matter with diameter less than 2.5 µm) are receiving increasing attention for their potential toxicities and roles in visibility and health. In this study, we interpreted the behavior of PM(2.5) and its correlation with meteorological parameters in Hong Kong, during 2007-2008. Significant diurnal variations of PM(2.5) concentrations were observed and showed a distinctive bimodal pattern with two marked peaks during the morning and evening rush hour times, due to dense traffic. The study observed higher PM(2.5) concentrations in winter when the northerly and northeasterly winds bring pollutants from the Chinese mainland, whereas southerly monsoon winds from the sea bring fresh air to the city in summer. In addition, higher concentrations of PM(2.5) were observed in rush hours on weekdays compared to weekends, suggesting the influence of anthropogenic activities on fine particulate levels, e.g., traffic-related local PM(2.5) emissions. To understand the spatial pattern of PM(2.5) concentrations in the context of the built-up environment of Hong Kong, we utilized MODerate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Thickness (AOT) 500 m data and visibility data to derive aerosol extinction profile, then converted to aerosol and PM(2.5) vertical profiles. A Geographic Information Systems (GIS) prototype was developed to integrate atmospheric PM(2.5) vertical profiles with 3D GIS data. An example of the query function in GIS prototype is given. The resulting 3D database of PM(2.5) concentrations provides crucial information to air quality regulators and decision makers to comply with air quality standards and in devising control strategies.

Trends in vegetation productivity related to climate change in China's Pearl River Delta.

Climate change will be a powerful stressor on ecosystems and biodiversity in the second half of the 21st century. In this study, we used the satellite-derived Normalized Difference Vegetation Index (NDVI) to examine a 34-year trend along with the response of vegetation to climate indicators surrounding the world's largest megacity: the Pearl River Delta (PRD) of China. An overall increasing trend is observed in vegetation productivity metrics over the study period 1982 to 2015. Increase in winter productivity in both natural ecosystems and croplands is more related to increasing temperatures (r = 0.5-0.78), than to changes in rainfall. For growing season productivity, negative correlations with temperature were observed in cropland regions, and some forests in the northern part of PRD region, suggesting high-temperature stress on crop production and forest vegetation. However, increased winter and spring temperatures provide higher opportunities for cropping in winter. During the decade 1995-2004, vegetation productivity metrics showed a reversal in the upward trend. The geographical and biological complexity of the region under significant climatic and development impacts suggests causative factors would be synergistic. These include our observed decrease in sunshine hours, increasing cloud cover associated with atmospheric aerosols from industrial and urban development, direct pollution effects on plant growth, and exceedance of high temperature growth thresholds.

Assessing the Country-Level Excess All-Cause Mortality and the Impacts of Air Pollution and Human Activity during the COVID-19 Epidemic.

The impact of Coronavirus Disease 2019 (COVID-19) on cause-specific mortality has been investigated on a global scale. However, less is known about the excess all-cause mortality and air pollution-human activity responses. This study estimated the weekly excess all-cause mortality during COVID-19 and evaluated the impacts of air pollution and human activities on mortality variations during the 10th to 52nd weeks of 2020 among sixteen countries. A SARIMA model was adopted to estimate the mortality benchmark based on short-term mortality during 2015-2019 and calculate excess mortality. A quasi-likelihood Poisson-based GAM model was further applied for air pollution/human activity response evaluation, namely ground-level NO2 and PM2.5 and the visit frequencies of parks and workplaces. The findings showed that, compared with COVID-19 mortality (i.e., cause-specific mortality), excess all-cause mortality changed from -26.52% to 373.60% during the 10th to 52nd weeks across the sixteen countries examined, revealing higher excess all-cause mortality than COVID-19 mortality in most countries. For the impact of air pollution and human activities, the average country-level relative risk showed that one unit increase in weekly NO2, PM2.5, park visits and workplace visits was associated with approximately 1.54% increase and 0.19%, 0.23%, and 0.23% decrease in excess all-cause mortality, respectively. Moreover, compared with the impact on COVID-19 mortality, the relative risks of weekly NO2 and PM2.5 were lower, and the relative risks of weekly park and workplace visits were higher for excess all-cause mortality. These results suggest that the estimation based on excess all-cause mortality reduced the potential impact of air pollution and enhanced the influence of human activities compared with the estimation based on COVID-19 mortality.

Sensor technology to monitor health, well-being and movement among healthcare personnel at workplace: a systematic scoping review protocol.

INTRODUCTION: The well-being and health of healthcare personnel is becoming increasingly important in the delivery of high-quality healthcare. The recent developments in technology have provided new opportunities for the objective detection of a wide variety of real-world properties and movement. However, technologies that are used to monitor health, well-being and movement among healthcare personnel have not been fully synthesised. The overall aim of this scoping review is to examine what type of sensor technology is available to monitor the health, well-being and movement of healthcare personnel in healthcare settings. More specifically, we want to explore what types of sensor technology applications, for what purposes and how they have been used to monitor health, well-being and movement among healthcare personnel in different workplace settings. METHODS AND ANALYSIS: This scoping review protocol will follow Arksey and O'Malley's methodology, complemented by the approach of the Joanna Briggs Institute to scoping reviews and guidance for conducting systematic scoping reviews. Peer-reviewed literature will be identified using a search strategy developed by a librarian, and a wide range of electronic datasets of medical, computer and information systems disciplines will be used. Eligibility of the articles will be determined using a two-stage screening process consisting of (1) a title and abstract scan, and (2) a full-text review. Extracted data will be thematically analysed and validated by an expert of sensor technology and a group of nurses as stakeholders. Descriptive statistics will be calculated when necessary. ETHICS AND DISSEMINATION: The results obtained from the review will inform what technology has been used, how it has been used in healthcare settings and what types of technology might still be needed for future innovations. Findings of the scoping review will be published in a peer-reviewed journal. REGISTRATION: This review was submitted in Open Science Framework on 12 December 2020.

Comparing the space-time patterns of high-risk areas in different waves of COVID-19 in Hong Kong.

This study compares the space-time patterns and characteristics of high-risk areas of COVID-19 transmission in Hong Kong between January 23 and April 14 (the first and second waves) and between July 6 and August 29 (the third wave). Using space-time scan statistics and the contact tracing data of individual confirmed cases, we detect the clusters of residences of, and places visited by, both imported and local cases. We also identify the built-environment and demographic characteristics of the high-risk areas during different waves of COVID-19. We find considerable differences in the space-time patterns and characteristics of high-risk residential areas between waves. However, venues and buildings visited by the confirmed cases in different waves have similar characteristics. The results can inform policymakers to target mitigation measures in high-risk areas and at vulnerable groups, and provide guidance to the public to avoid visiting and conducting activities at high-risk places.

Identifying the space-time patterns of COVID-19 risk and their associations with different built environment features in Hong Kong.

Identifying the space-time patterns of areas with a higher risk of transmission and the associated built environment and demographic characteristics during the COVID-19 pandemic is critical for developing targeted intervention measures in response to the pandemic. This study aims to identify areas with a higher risk of COVID-19 transmission in different periods in Hong Kong and analyze the associated built environment and demographic factors using data of individual confirmed cases. We detect statistically significant space-time clusters of COVID-19 at the Large Street Block Group (LSBG) level in Hong Kong between January 23 and April 14, 2020. Two types of high-risk areas are identified (residences of and places visited by confirmed cases) and two types of cases (imported and local cases) are considered. The demographic and built environment features for the identified high-risk areas are further examined. The results indicate that high transport accessibility, dense and high-rise buildings, a higher density of commercial land and higher land-use mix are associated with a higher risk for places visited by confirmed cases. More green spaces, higher median household income, lower commercial land density are linked to a higher risk for the residences of confirmed cases. The results in this study not only can inform policymakers to improve resource allocation and intervention strategies but also can provide guidance to the public to avoid conducting high-risk activities and visiting high-risk places.

Spatial and environmental constraints on natural forest regeneration in the degraded landscape of Hong Kong.

Tropical forests are the main reservoirs for global biodiversity and climate control. As secondary forests are now more widespread than primary forests, understanding their functioning and role in the biosphere is increasingly important. This includes understanding how they achieve stability, how they accumulate species and build biodiversity and how they cycle nutrients and carbon. This study investigates how we can restore tropical secondary forests to resemble high biomass, highly biodiverse and stable ecosystems seen today only in primary, undisturbed forests. The study used historic aerial photographs and recent high-resolution satellite images from 1945 to 2014 to map forest patches with five age categories, from 14-years to over 70-years, in Hong Kong's degraded tropical landscape. A forest inventory comprising 28 quadrats provided a rare opportunity to relate patterns of species composition at different stages during the succession with topographic and soil characteristics. The topographic variables accounted for 15% of the variance in species abundance, and age of forest stands explained 29%. Species richness rapidly increased after the first 15 years, but was lower in old-growth, than in medium age forest. This is attributed to the inability of late-successional species to disperse into the young forests as the natural dispersal agents (birds, mammals) have been lost. Light-loving pioneers which are unable to tolerate the shade of older forests, cannot regenerate in their own shade, therefore species diversity declines after a few decades. For ecosystem restoration in tropical secondary forests, introduction of late-successional species is necessary to assist natural succession, given the absence of native fauna, seed dispersal agents, and the surrounding altered environment. We also show that remote sensing can play a pivotal role in understanding the recovery and functioning of secondary forest regeneration as its contribution to the biosphere is increasingly important.