Spatial Transmission Research Articles

Temporal and spatial aerosol transmission from the exhalation of an infected person in an office environment

The paper reports office test chamber experiments with an exposed breathing thermal manikin (6 L/min) and an infected exhalation simulator (6 L/min) connected with a thermal dummy. The motivation was to investigate effects of different protection methods at workstation when an infected person is working in the room. The protection methods were room air purifier, personal air purifier, FFP2-mask, and workstation partition panels. The objective was to measure temporal and spatial concentration characteristics at the exposed breathing zone. The exhale of infected model was aerosolized by using a Blaustein atomizer (BLAM), syringe pump and paraffin oil (0.6 mL/h). The concentrations were measured with TSI optical particle sizers. The ventilation method was mixing ventilation from a perforated duct. The indoor air change was 1.7 1/h (ACH). The experimental set-up was carried out at 6 workstations around the infected person. The temporal and spatial evolution was measured from zero concentration to steady concentration level. The results indicate that the room air purifier and the facemask can efficiently reduce exposure whereas the personal air purifier had a moderate reduction. The partition panels had only a minor effect on exposure. The lowest exposure was found when the individuals were sitting at the same side far from each other.

Population Flow and Epidemic Spread: Direct Impact and Spatial Spillover Effect

Based on population migration data from Baidu and the spatial Durbin model, this paper examines the impact of population mobility on the spatial transmission of COVID-19 and provides a basis for forecasting epidemic transmission and guiding public health intervention plans from the perspectives of population mobility and geographical space. The results show that epidemic spreading displays a clear spatial pattern that includes not only spreading from Wuhan to the surrounding areas but also secondary transmission in the Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta regions through population flows. The epidemic degree in each area is directly affected by the number of population inflows from Wuhan and indirectly affected by the spatial spillover effect from other areas. Due to the lack of strict restrictions on population flows, the spatial spillover effect in areas outside Hubei gradually strengthened after the closure of Wuhan and exceeded the direct effect, and the intensity of population flows within Wuhan had a significant impact on the spread of the epidemic. Without considering the spatial spillover effect, the model will overestimate the impact of population inflows in Wuhan on the local epidemic and underestimate the total effect of regional patterns on epidemic transmission.

Understanding the transmission of African swine fever in wild boars of South Korea: A simulation study for parameter estimation.

Since the introduction of African swine fever (ASF) to Georgia in 2007, the disease has spread to many other countries including South Korea. Initial detection of ASF from wild boars (WB) in South Korea was reported in early October 2019. Since then, more than a thousand WB samples collected from the northern part of the country have been confirmed as ASF positive (2.9% of ASF positivity among WB samples collected until June 2020), indicating that the disease is endemic in the WB populations. To control the disease, multiple layers of fence-lines have been erected. Nevertheless, outbreaks continuously occurred across the fence, requiring a better understanding of the spatial transmission mechanism of ASF in WBs. Hence, we developed a novel ASF transmission model to estimate ecological and epidemiological parameters related to the spread of the disease in the WB population of South Korea. The results showed that roads and rivers were effective to prevent the spread, reducing the transmission rate to approximately 37% on average. Only a limited level of reduction was indicated via fence-lines, implying erection of fences might be considered as a temporary measure to delay the spread. This study also revealed that the probability of ASF transmission to adjacent habitats considerably decreased with increasing distance, supporting the slow spatial transmission speed reported from other European countries. Considering that elucidation of ASF dynamics in WB is crucial to mitigate the impact of the disease, we believe this study provides some useful ecological and epidemiological implications to control the disease in future.

The role of fuel prices in spatial price transmission between horticultural markets: empirical analysis from a developing country

This article aims to analyze how fuel prices impact spatial price transmission between two Chilean horticultural wholesale markets. We implement a regime-dependent VECM where price transmission parameters depend on dynamics imposed by a stationary exogenous variable (fuel price). We identified two price transmission regimes characterized by different equilibrium relationships and short-run adjustment processes. This implies that fuel prices affect price transmission elasticities and intermarket adjustment speeds. Our results show increasing marketing costs as farm to market distance grows. This impact depends on each product’s attributes. Highlights This article analyzes the effect of fuel prices on the price transmission mechanism between the most relevant Chilean horticultural wholesale markets. A regime-dependent Vector Error Correction Model where price transmission parameters depend on fuel price was implemented. Clear evidence of the role played by fuel prices for in horizontal price transmission between the wholesale markets considered in this study was found. This situation supports the idea that regardless of quantities traded in regional markets, the major effect of price adjustment is a result of the high demand, distances and market concentration of a central market. This impact depends on each product’s attributes.

High Spatial Resolution Neutron Transmission Imaging Using a Superconducting Two-Dimensional Detector

Neutron imaging is one of the most powerful tools for nondestructive inspection owing to the unique characteristics of neutron beams, such as high permeability for many heavy metals, high sensitivity for certain light elements, and isotope selectivity owing to a specific nuclear reaction between an isotope and neutrons. In this study, we employed a superconducting detector, current-biased kinetic-inductance detector (CB-KID) for neutron imaging using a pulsed neutron source. We employed the delay-line method, and high spatial resolution imaging with only four reading channels was achieved. We also performed wavelength-resolved neutron imaging by the time-of-flight method for the pulsed neutron source. We obtained the neutron transmission images of a Gd–Al alloy sample, inside which single crystals of GdAl <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_3$</tex-math></inline-formula> were grown, using the delay-line CB-KID. Single crystals were well imaged, in both shapes and distributions, throughout the Al–Gd alloy. We identified Gd nuclei via neutron transmissions that exhibited characteristic suppression above the neutron wavelength of 0.03 nm. In addition, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{155}$</tex-math></inline-formula> Gd resonance dip, a dip structure of the transmission caused by the nuclear reaction between an isotope and neutrons, was observed even when the number of events was summed over a limited area of 15 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> m × 12 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> m. Gd selective imaging was performed using the resonance dip of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{155}$</tex-math></inline-formula> Gd, and it showed clear Gd distribution even with a limited neutron wavelength range of 1 pm.

SCMA-MIMO system with adaptation to the channel state

Sparse code multiple access (SCMA) is one of the promising implementations of non-orthogonal multiple access (NOMA) methods. SCMA provides high spectral efficiency and a large number of network resources. We describe a communication system with SCMA, space-time block coding (STBC), multiple input multiple output (MIMO) technology, and orthogonal frequency division multiplexing (OFDM). The architecture of such systems, including algorithms of formation and processing of signals is considered. A method for adapting signals to the state of the spatial channel transmission based on information about the matrix of channel coefficients is proposed. The application of such adaptation allows to compensate the influence of the channel and to reduce the probability of bit errors. We consider the bit error rate (BER) performance of the communication system in different channel models and show the effectiveness of the proposed methods.

High Spatial Resolution Tomographic Gamma Scanning Reconstruction With Improved MLEM Iterative Algorithm Based on Split Bregman Total Variation Regularization

High spatial resolution tomographic gamma scanning (TGS) reconstruction is very important for the radioassay of drummed low-level radioactive waste. High spatial resolution means that the divided voxels are finer. Due to the large size of the drum, the traditional image reconstruction method based on complete samples takes a long time to scan. To limit the scanning time of the drum, sparse sampling is required. The maximum likelihood expectation maximization (MLEM) is widely used in TGS image reconstruction from projection data, but for high spatial resolution TGS imaging, its quality is insufficient to accurately describe the media boundary and determine radioactivity. The improved MLEM algorithm based on total variation (TV) regularization, such as the MLEM- TV minimization (TVM) algorithm, has been applied to reconstruct high spatial resolution TGS images. The split Bregman algorithm can quickly solve the partial differential equations of TV regularization. In this work, the split Bregman anisotropic TV (SBATV) and the split Bregman isotropic TV (SBITV) are the first time adopted to improve the iterative process of the MLEM algorithm, which are MLEM- SBATV and MLEM- SBITV. Experimental results show that both the MLEM- SBATV algorithm and the MLEM- SBITV algorithm can accurately reconstruct high spatial resolution TGS transmission images with sparse sampling. The MLEM- SBITV algorithm performs better in reconstructing the TGS emission images from sparse sampling than the traditional MLEM, MLEM- TVM, and MLEM- SBATV algorithms, increasing radionuclide positioning and radioactivity reconstruction accuracy.

Spatial Characteristics and Regional Transmission Analysis of PM2.5 Pollution in Northeast China, 2016-2020.

Northeast China is an essential industrial development base in China and the regional air quality is severely affected by PM2.5 pollution. In this paper, spatial autocorrelation, trajectory clustering, hotspot analysis, PSCF and CWT analysis are used to explore the spatial pollution characteristics of PM2.5 and determine the atmospheric regional transmission pattern for 40 cities in Northeast China from 2016 to 2020. Analysis of PM2.5 concentration characteristics in the northeast indicates that the annual average value and total exceedance days of PM2.5 concentration in Northeast China showed a U-shaped change, with the lowest annual average PM2.5 concentration (31 μg/m3) in 2018, decreasing by 12.1% year-on-year, and the hourly PM2.5 concentration exploding during the epidemic lockdown period in 2020. A stable PM2.5 pollution band emerges spatially from the southwest to Northeast China. Spatially, the PM2.5 in Northeast China has a high degree of autocorrelation and a south-hot–north-cool characteristic, with all hotspots concentrated in the most polluted Liaoning province, which exhibits the H–H cluster pattern and hotspot per year. Analysis of the air mass trajectories, potential source contributions and concentration weight trajectories in Northeast China indicates that more than 74% of the air mass trajectories were transmitted to each other between the three heavily polluted cities, with the highest mean value of PM2.5 pollution trajectories reaching 222.4 μg/m3, and the contribution of daily average PM2.5 concentrations exceeding 60 μg/m3 within Northeast China. Pollution of PM2.5 throughout the Northeast is mainly influenced by short-range intra-regional transport, with long-range transport between regions also being an essential factor; organized integration is the only fundamental solution to air pollution.

Woody plant encroachment and the ecology of vector‐borne diseases

Abstract Vector‐borne diseases (VBDs) impact human and animal health globally, and their ecology and transmission are affected by human‐caused ecosystem and biome transitions. Woody plant encroachment (WPE), a top driver of biome and land cover transitions in grasslands and savannas of the world, greatly changes abiotic conditions, vegetation and animal populations and communities. Although these effects mirror mechanisms by which other ecosystem and land cover changes influence VBD ecology, few studies have evaluated if WPE expands distributions and increases the transmission of VBDs. We develop a conceptual framework for WPE effects on VBDs by synthesizing key literature on these topics and on impacts of land cover change on diseases broadly. We also present examples of WPE systems from two continents illustrating documented and likely effects on VBD systems, and we outline a prospectus for future research evaluating such effects. This synthesis highlights the potential for WPE to increase the transmission of VBDs world‐wide. WPE's effects on landscape composition, local vegetation, abiotic conditions, and vector and host resources, interactions and population and community processes, likely impact VBD distributions, transmission and health outcomes. Much additional research is needed on topics like the effects of WPE management on health risks associated with VBDs. Synthesis and applications. Woody plant encroachment (WPE) is drastically changing grasslands and savannas world‐wide. Its well‐documented influences on abiotic conditions (e.g. temperature and humidity), vegetation and wildlife are having previously underappreciated effects on the ecology of vector‐borne diseases, likely increasing spatial distributions and transmission of diseases. Management to reduce WPE is ongoing in much of the world due to its degradation of ecosystem services like biodiversity, livestock production and water quality and quantity. The ecosystem disservice of elevated disease risk in humans, wildlife and domestic animals should be an additional consideration when making land management and policy decisions related to WPE.

Construction of Space Quantum Information System Based on Satellite Recognition

Satellite identification is a form of space quantum information, which refers to the use of artificial earth satellites as the transmitting station between earth communication stations to perform satellite identification to construct a space quantum information system. However, at this stage, a single form of identification cannot meet the needs of various aspects such as the development of the information society. And mobile broadband services. Based on this, this paper has carried out research on the construction of space quantum information system based on satellite recognition. This paper firstly introduces the research significance of space quantum information transmission based on satellite identification, and then analyzes the research status of space information system based on satellite identification and the research status of space quantum information system based on satellite identification at home and abroad. Aiming at the problem of asymmetrical transmission of space information, this paper proposes, a spatial asymmetric transmission scheme based on layered modulation and network coding, and in view of the low communication quality caused by the influence of weather and surrounding environment on the space-based communication channel, this paper proposes an adaptive transmission scheme of spatial information based on satellite cooperation. The survey results show that under the MNC strategy and the traditional zero-padded strategy, the end-to-end bit error rate performance of S2 is not much different. As the signal-to-noise ratio continues to increase to 30dB, the two are basically the same. In the whole range of k value, the access probability of the MNC strategy is equal to a constant 0.67 and remains unchanged. When k=1, under the OUS scheme, it shows that the two source nodes have the same probability of accessing the channel, and the access probability is 50%, which is 16.7% lower than that of the MNC scheme.

A Bayesian Nonparametric Analysis of the 2003 Outbreak of Highly Pathogenic Avian Influenza in the Netherlands

Abstract Infectious diseases on farms pose both public and animal health risks, so understanding how they spread between farms is crucial for developing disease control strategies to prevent future outbreaks. We develop novel Bayesian nonparametric methodology to fit spatial stochastic transmission models in which the infection rate between any two farms is a function that depends on the distance between them, but without assuming a specified parametric form. Making nonparametric inference in this context is challenging since the likelihood function of the observed data is intractable because the underlying transmission process is unobserved. We adopt a fully Bayesian approach by assigning a transformed Gaussian process prior distribution to the infection rate function, and then develop an efficient data augmentation Markov Chain Monte Carlo algorithm to perform Bayesian inference. We use the posterior predictive distribution to simulate the effect of different disease control methods and their economic impact. We analyse a large outbreak of avian influenza in the Netherlands and infer the between-farm infection rate, as well as the unknown infection status of farms which were pre-emptively culled. We use our results to analyse ring-culling strategies, and conclude that although effective, ring-culling has limited impact in high-density areas.

Spatiotemporal differentiation of coupling coordination degree between economic development and water environment and its influencing factors using GWR in China's province

Rapid economic growth and social development in China have led to serious water pollution problems and water resource shortages, limiting the sustainable and coordinated development that could support both the socio-economy and water environment (WE). However, the spatial heterogeneity and evolutionary characteristics of the coordination between economic development (ED) and WE have not been adequately explored in China's provinces. In this study, we use the spatial global (local) autocorrelation and geographically weighted regression (GWR) model to explore the relationship between ED and WE subsystems and its influencing factors in China's provinces from 2010 to 2019. The main results are as follows, (a) The coupling coordination degree (CCD) between the two subsystems in southern China is higher than that of northern China. Transitional development areas have gradually spread to the middle of China, and there has been an increase trend in the number of moderate and high coordination provinces. (b) The ED-led (WE lags behind ED) type is mainly concentrated in central and eastern China, and the WE-led (ED lags behind WE) type is concentrated in the northeastern and western regions. The areas with synchronous development are relatively small in number and are mainly concentrated in east coastal China. (c) There is an obvious spatial dependence of the coordination between ED and WE from the perspective of global correlation, but this dependence is weakened with increasing geographical distance. The local mode of agglomeration shows a trend towards the evolution of high-high clustering in the eastern region. (d) The GWR analysis indicates that the factors of population density, energy consumption, fixed investment, and research and development (R&D) expenditure significantly influence the coordination between ED and WE. Fixed investment and R&D expenditure are mainly positive driving factors, while the impacts of population density and energy consumption vary among different regions as time evolves. Changes in driving force in a region can extend spatial effects to adjacent regions through the spatial transmission mechanism. Finally, we close the paper by recommending the different policy implications according to the GWR results.

Modelling Representative Population Mobility for COVID-19 Spatial Transmission in South Africa.

The COVID-19 pandemic starting in the first half of 2020 has changed the lives of everyone across the world. Reduced mobility was essential due to it being the largest impact possible against the spread of the little understood SARS-CoV-2 virus. To understand the spread, a comprehension of human mobility patterns is needed. The use of mobility data in modelling is thus essential to capture the intrinsic spread through the population. It is necessary to determine to what extent mobility data sources convey the same message of mobility within a region. This paper compares different mobility data sources by constructing spatial weight matrices at a variety of spatial resolutions and further compares the results through hierarchical clustering. We consider four methods for constructing spatial weight matrices representing mobility between spatial units, taking into account distance between spatial units as well as spatial covariates. This provides insight for the user into which data provides what type of information and in what situations a particular data source is most useful.

Tracing and tracking the emergence, epidemiology and dispersal of dengue virus to Africa during the 20th century

The four mosquito-borne dengue virus serotypes (DENV1–DENV4) cause a high burden of disease throughout the tropical and sub-tropical regions of the world. Nevertheless, their precise epidemiological history in Africa, including when and where they originated and were distributed during the 20th century, remains unclear stressing the need for One Health focused research. Accordingly, we conducted a time-scaled molecular epidemiological reconstruction using publicly available and newly sequenced dengue virus genomes of African origin representing all four serotypes to deduce the most likely temporal and spatial transmission routes of each DENV serotype from their ancestral regions to, within and from Africa.Our analyses suggest that during the 20th century, serotypes DENV1–DENV3 were introduced to Africa from South East Asia on multiple occasions. The earliest evidence recorded indicates introduction of DENV2 during the early-1940s and of DENV1 during the mid-1940s to Western Africa from South East Asia. The analysis also implies an early introduction of DENV4 during the mid-1940s to Western Africa, alongside DENV1, probably originating in South East Asia. Establishment of DENV3 in Africa appears to have occurred later in the 1960s, apparently originating from South East Asia. However, with the re-establishment of DENV in the Americas, following the cessation of the PAHO mosquito control programme during the mid-20th century, evidence of introductions of DENV1 and DENV2 from the Americas to Western Africa was also observed. The data also identify intra-regional circulation of DENV, but also inter-regional dispersal of all four serotypes within Africa, which has led to a high degree of geographical overlap among serotypes. It is also noteworthy that DENV from both Eastern and Western Africa, have been introduced into Central Africa but there is no support for the converse relationship. For serotypes DENV1–DENV3, we observed probable exports from within established African DENV clusters (≥2 sequences) primarily to Eastern and Southern Asia.Collectively, our findings support the view that all DENV serotypes, apart from DENV4, have been introduced on multiple occasions to Africa, primarily originating from South East Asia, and subsequently to neighbouring regions within Africa.

The current burden of Japanese encephalitis and the estimated impacts of vaccination: Combining estimates of the spatial distribution and transmission intensity of a zoonotic pathogen.

Japanese encephalitis virus (JEV) is a major cause of neurological disability in Asia and causes thousands of severe encephalitis cases and deaths each year. Although Japanese encephalitis (JE) is a WHO reportable disease, cases and deaths are significantly underreported and the true burden of the disease is not well understood in most endemic countries. Here, we first conducted a spatial analysis of the risk factors associated with JE to identify the areas suitable for sustained JEV transmission and the size of the population living in at-risk areas. We then estimated the force of infection (FOI) for JE-endemic countries from age-specific incidence data. Estimates of the susceptible population size and the current FOI were then used to estimate the JE burden from 2010 to 2019, as well as the impact of vaccination. Overall, 1,543.1 million (range: 1,292.6-2,019.9 million) people were estimated to live in areas suitable for endemic JEV transmission, which represents only 37.7% (range: 31.6-53.5%) of the over four billion people living in countries with endemic JEV transmission. Based on the baseline number of people at risk of infection, there were an estimated 56,847 (95% CI: 18,003-184,525) JE cases and 20,642 (95% CI: 2,252-77,204) deaths in 2019. Estimated incidence declined from 81,258 (95% CI: 25,437-273,640) cases and 29,520 (95% CI: 3,334-112,498) deaths in 2010, largely due to increases in vaccination coverage which have prevented an estimated 314,793 (95% CI: 94,566-1,049,645) cases and 114,946 (95% CI: 11,421-431,224) deaths over the past decade. India had the largest estimated JE burden in 2019, followed by Bangladesh and China. From 2010-2019, we estimate that vaccination had the largest absolute impact in China, with 204,734 (95% CI: 74,419-664,871) cases and 74,893 (95% CI: 8,989-286,239) deaths prevented, while Taiwan (91.2%) and Malaysia (80.1%) had the largest percent reductions in JE burden due to vaccination. Our estimates of the size of at-risk populations and current JE incidence highlight countries where increasing vaccination coverage could have the largest impact on reducing their JE burden.

Investigating the Impact of Trade Disruptions on Price Transmission in Commodity Markets: An Application of Threshold Cointegration

Threshold cointegration is introduced as an econometric technique to model the impact of trade disruptions on spatial price transmission in commodity markets so that market participants and policy makers can understand the global impact of trade disruptions on prices. The threshold cointegration technique that is employed is flexible in that it allows the number of thresholds and their location to be determined endogenously and the threshold variable to be exogenous to the system. We innovate on the threshold cointegration technique by selecting a measure of trade disruptions as the threshold variable. This innovation can be used for any commodity market that is spatially connected due to arbitrage; however, to illustrate its usefulness we apply the technique to trade disruptions for canola traded between Canada and China using weekly data between 2014 and 2019 and find that canola trade disruptions between Canada and China impacted global price transmission and resulted in market fragmentation.

How does internet development affect energy-saving and emission reduction? Evidence from China

With the development of information technology and its innovative applications in the field of environmental protection, the role of the internet in energy conservation and emission reduction has become increasingly prominent. Based on panel data from 30 provinces from 2006 to 2017 and 196 cities from 2011 to 2018 in China, this study utilizes the SBM (Slack-Based Measure) model to evaluate energy saving and emission reduction efficiency. The OLS, Spatial Durbin model, threshold model, mediating effect model, and DID (Difference in Difference) model are employed to study the direct effect, spatial spillover effect, nonlinear relationship, transmission mechanism, and policy effect of internet development on energy saving and emission reduction efficiency. The empirical results indicate that internet development has significantly promoted energy saving and emission reduction efficiency. This conclusion still holds after a series of robustness tests, including IV estimation, and the substitution of dependent and independent variables. The gradual DID model based on the quasi natural experiment of “Broadband China” further proves the causal relationship between internet development and energy saving and emission reduction efficiency. Internet development can improve the latter through technological progress, energy structure, human capital, and openness. Interestingly, the impact of internet development on the energy saving and emission reduction efficiency of adjacent areas also has a significantly positive spatial spillover effect, which still exists under the spatial weight matrix of different distances. There is also solid evidence that the impact of internet development on energy saving and emission reduction efficiency is non-linear under different levels of technological progress, energy structure, human capital, and openness.

Spectrometer‐free Optical Hydrogen Sensing Based on Fano‐like Spatial Distribution of Transmission in a Metal−Insulator−Metal Plasmonic Doppler Grating

AbstractOptical nanosensors are promising for hydrogen sensing because they are small, free from spark generation, and feasible for remote optical readout. Conventional optical nanosensors require broadband excitation and spectrometers, rendering the devices bulky and complex. An alternative is spatial intensity‐based optical sensing, which only requires an imaging system and a smartly designed platform to report the spatial distribution of analytical optical signals. Here, a spatial intensity‐based hydrogen sensing platform is presented based on Fano‐like spatial distribution of the transmission in a Pd‐Al2O3‐Au metal‐insulator‐metal plasmonic Doppler grating (MIM‐PDG). The MIM‐PDG manifests the Fano resonance as an asymmetric spatial transmission intensity profile. The absorption of hydrogen changes the spatial Fano‐like transmission profiles, which can be analyzed with a “spatial” Fano resonance model and the extracted Fano resonance parameters can be used to establish analytical calibration lines. While gratings sensitive to hydrogen absorption are suitable for hydrogen sensing, hydrogen insensitive gratings are also found, which provide an unperturbed reference signal and may find applications in nanophotonic devices that require a stable optical response under fluctuating hydrogen atmosphere. The MIM‐PDG platform is a spectrometer‐free and intensity‐based optical sensor that requires only an imaging system, making it promising for cellphone‐based optical sensing applications.

Spatial Price Dynamics and Asymmetric Price Transmission in Skim Milk Powder International Trade: Evidence from Export Prices for New Zealand and Ireland

A fast-changing global landscape highlights the importance of understanding spatial price dynamics in key international markets such as China, especially in the era of COVID-19 pandemic with international food trade and food system experiencing an unprecedented challenge. Nowadays, New Zealand’s dominant position in China’s dairy import market is being challenged by European Union (EU) dairy exporters leading to intensified market competition. Using monthly export data of skim milk powder (SMP), we applied threshold cointegration models along with asymmetric error correction models to examine spatial price dynamics and price transmissions of New Zealand and Ireland in Chinese and global markets. We found that New Zealand’s export prices retain their leadership position in China, Ireland’s export prices are well more aligned with those in international markets. In terms of own-country price transmission, Ireland’s relatively symmetric and swift adjustments were found to contrast with New Zealand’s SMP export prices, which displayed more asymmetric price transmissions.

Spatial analysis of COVID-19 outbreak to assess the effectiveness of social restriction policy in dealing with the pandemic in Jakarta

Coronavirus disease 2019 (COVID-19) has been spread globally and brought health and socioeconomic issues. Jakarta tried to accommodate health and economic interests through the Large-Scale Social Restriction (LSSR) policy that should be assessed. This study aims to (1) visualize the spatial patterns of confirmed Covid-19 cases and the locations of potential risk of transmission, and (2) determine the spatial processes underlying the spatial patterns of Covid-19 cases. The emerging hot spot analysis and space-time scan statistic were employed to analyze the dynamic of infected cases and transmission risk. A Geographical Weighted Regression (GWR) model was developed to define factors that influence the spatial transmission. The result shows that spatial transmission keeps continuing, despite a decline in the aggregate pandemic curve during LSSR implementation. This was likely affected by settlements types and population density distribution, and transportation networks. Spatial analysis supports the aggregate pandemic curve to increase the pandemic surveillance effectiveness.