Contagion Source Detection in Epidemic and Infodemic Outbreaks: Mathematical Analysis and Network Algorithms

This monograph provides an overview of the mathematical theories and computational algorithm design for contagion source detection in large networks. By leveraging network centrality as a tool for statistical inference, we can accurately identify the source of contagions, trace their spread, and predict future trajectories. This approach provides fundamental insights into surveillance capability and asymptotic behavior of contagion spreading in networks. Mathematical theory and computational algorithms are vital to understanding contagion dynamics, improving surveillance capabilities, and developing effective strategies to prevent the spread of infectious diseases and misinformation.Comment: Suggested Citation: Chee Wei Tan and Pei-Duo Yu (2023), "Contagion Source Detection in Epidemic and Infodemic Outbreaks: Mathematical Analysis and Network Algorithms", Foundations and Trends in Networking: Vol. 13: No. 2-3, pp 107-251. http://dx.doi.org/10.1561/130000006

Confirmation of Itersonilia perplexans infecting pyrethrum (Tanacetum cinerariifolium) in Australia

Pyrethrum (Tanacetum cinerariifolium (Trevir.) Sch. Bip.) is grown to extract pyrethrins which are active ingredients for insecticides (Greenhill 2007). The Australian pyrethrum industry supplies over 50% of the world market. Surveys of Tasmanian crops in spring 2013, detected the presence of a fungus putatively identified as Itersonilia perplexans Derx. on foliage in 54 of 86 surveyed fields (Hay et al. 2015). This fungus was associated with necrotic leaf tips often spreading to encompass whole leaves. However, pathogenicity to pyrethrum was not confirmed. To isolate, tissue was excised from foliar lesions, surface sterilised using 0.4% NaClO, placed onto 2% water agar and incubated at 20°C for 5 days. Colonies were pure-cultured by hyphal-tip transfer onto potato-dextrose agar. Eleven isolates were cultured onto yeast mold agar (YMA) for 14 days at 15°C in the dark (Horita and Yasuoka 2002). Colonies were slow growing (1.9 to 2.3 mm/day) white to buff on both surfaces, with a darker center visible on lower surfaces. Mycelia were straight and hyaline with clamp connections at the septa. Squares transferred from the edge of YMA colonies onto microscope slides produced ballistoconidia that were aseptate, granular and lunate, kidney or lemon-shaped after 24 h. Ballistoconidia lengths and widths (n = 50/isolate) ranged from 14.6 to 20.4 µm and 10.0 to 13.6 µm. Chlamydospores were not observed. These observations were consistent with descriptions of I. perplexans (Koike and Tjosvold 2001; Liu et al. 2015). All 11 isolates were sequenced across the internal transcribed spacer (ITS) region of rDNA (ITS; primers V9G/ITS4; de Hoog and van den Ende 1998; White et al. 1990), and large (LSU; primers LROR/LR7; Rehner and Samuels 1995), and small (SSU; NS1/NS4; White et al. 1990) subunits of rDNA (Genbank accession nos. KU563626 to KU563658). The ITS (673 bp), SSU (1,047 bp) and LSU (1,318 bp) differed by 3, 1 and 0 bp, respectively, across isolates. Maximum parsimony and maximum likelihood analyses of a concatenated 3 loci alignment with Cystofilobasidiales representatives (Liu et al. 2015) placed all isolates and the I. perplexans ex-neotype strain CBS 363.85 within a single monophyletic clade with 100% bootstrap support. Two representative isolates are stored at the Plant Pathology Herbarium (accession nos. BRIP 57986 and 57987). Leaves of 46-day-old pyrethrum plants (n = 45), generated from surface sterilised seed, were inoculated with a 1.5 × 105 ballistoconidia/ml suspension (equal mix of eight isolates) and maintained between 10 and 22°C under a 12-h photoperiod for 14 days. Brown necrotic leaf tips, consistent with reported field symptoms were observed on 71% of plants and I. perplexans was recovered from 69% of symptomatic plants. For flower inoculations, pyrethrum plants were removed from fields as vegetative plants in spring and maintained in a greenhouse set at 20:14°C and 14:10 h day:night. Open flowers (10 per plant) were dipped into a 1.2 × 104 ballistoconidia/ml suspension mix of three isolates. Brown withered ray florets were observed on 10/12 plants 18 days post-inoculation, matching those described in petal blight of chrysanthemum (McRitchie et al. 1973). I. perplexans was re-isolated from 11/12 inoculated plants and 1 control plant (of 12) which exhibited the same symptoms. In both experiments, I. perplexans was identified based on its distinctive morphology. This confirms the pathogenicity of I. perplexans to both pyrethrum leaves and flowers

DeepTrace: Learning to Optimize Contact Tracing in Epidemic Networks with Graph Neural Networks

The goal of digital contact tracing is to diminish the spread of an epidemic or pandemic by detecting and mitigating public health emergencies using digital technologies. Since the start of the COVID-$19$ pandemic, a wide variety of mobile digital apps have been deployed to identify people exposed to the SARS-CoV-2 coronavirus and to stop onward transmission. Tracing sources of spreading (i.e., backward contact tracing), as has been used in Japan and Australia, has proven crucial as going backwards can pick up infections that might otherwise be missed at superspreading events. How should robust backward contact tracing automated by mobile computing and network analytics be designed? In this paper, we formulate the forward and backward contact tracing problem for epidemic source inference as maximum-likelihood (ML) estimation subject to subgraph sampling. Besides its restricted case (inspired by the seminal work of Zaman and Shah in 2011) when the full infection topology is known, the general problem is more challenging due to its sheer combinatorial complexity, problem scale and the fact that the full infection topology is rarely accurately known. We propose a Graph Neural Network (GNN) framework, named DeepTrace, to compute the ML estimator by leveraging the likelihood structure to configure the training set with topological features of smaller epidemic networks as training sets. We demonstrate that the performance of our GNN approach improves over prior heuristics in the literature and serves as a basis to design robust contact tracing analytics to combat pandemics

Novel species of Cercospora and Pseudocercospora (Capnodiales, Mycosphaerellaceae) from Australia

Novel species of Cercospora and Pseudocercospora are described from Australian native plant species. These taxa are Cercospora ischaemi sp. nov. on Ischaemum australe (Poaceae); Pseudocercospora airliensis sp. nov. on Polyalthia nitidissima (Annonaceae); Pseudocercospora proiphydis sp. nov. on Proiphys amboinensis (Amaryllidaceae); and Pseudocercospora jagerae sp. nov. on Jagera pseudorhus var. pseudorhus (Sapindaceae). These species were characterised by morphology and an analysis of partial nucleotide sequence data for the three gene loci, ITS, LSU and EF-1α. Recent divergence of closely related Australian species of Pseudocercospora on native plants is proposed

Novel species of Cercospora and Pseudocercospora (Capnodiales, Mycosphaerellaceae) from Australia

Novel species of Cercospora and Pseudocercospora are described from Australian native plant species. These taxa are Cercospora ischaemi sp. nov. on Ischaemum australe (Poaceae); Pseudocercospora airliensis sp. nov. on Polyalthia nitidissima (Annonaceae); Pseudocercospora proiphydis sp. nov. on Proiphys amboinensis (Amaryllidaceae); and Pseudocercospora jagerae sp. nov. on Jagera pseudorhus var. pseudorhus (Sapindaceae). These species were characterised by morphology and an analysis of partial nucleotide sequence data for the three gene loci, ITS, LSU and EF-1α. Recent divergence of closely related Australian species of Pseudocercospora on native plants is proposed

Chitosan oligosaccharide as a plant immune inducer on the Passiflora spp. (passion fruit) CMV disease

Cucumber mosaic virus (CMV), one of the main viruses, is responsible for Passiflora spp. (passion fruit) virus diseases, which negatively affect its planting, cultivation, and commercial quality. In this study, a laboratory anti-CMV activity screening model for Passiflora spp. CMV disease was first established. Then, the effects of different antiviral agents of chitosan oligosaccharide (COS), dufulin (DFL), and ningnanmycin (Ning) on CMV virulence rate in Passiflora spp. were determined. The virulence rate and anti-CMV activity in Passiflora spp. treated with COS were 50% and 45.48%, respectively, which were even better than those of DFL (66.67% and 27.30%, respectively) and Ning (83.30% and 9.17%, respectively). Field trials test results showed COS revealed better average control efficiency (47.35%) against Passiflora spp. CMV disease than those of DFL (40.93%) and Ning (33.82%), indicating that COS is effective in the control of the Passiflora spp. CMV disease. Meanwhile, the nutritional quality test results showed that COS could increase the contents of soluble solids, titratable acids, vitamin C, and soluble proteins in Passiflora spp. fruits as well as enhance the polyphenol oxidase (PPO), superoxide dismutase (SOD), and peroxidase (POD) activity in the leaves of Passiflora spp. seedlings. In addition, the combined transcriptome and proteome analysis results showed that COS mainly acted on the Brassinosteroids (BRs) cell signaling pathway, one of plant hormone signal transduction pathway, in Passiflora spp., thus activating the up-regulated expression of TCH4 and CYCD3 genes to improve the resistance to CMV disease. Therefore, our study results demonstrated that COS could be used as a potential plant immune inducer to control the Passiflora spp. CMV disease in the future

How E-Servqual Affects Customer\u27s Online Purchase Intention?

With the boom of Internet, Internet has become one of the consumers’ online shopping channels. However, there is different in online shopping situation is because of consumers in different cultures and countries have different online shopping behavior is worth to discuss. This study is to explore the Internet users’ online shopping situation in developing country, Malaysia, and 118 questionnaire respondents were collected. Statistical analysis software SPSS 17.0 and AMOS 6.0 were used to analyze the impact on e-service quality, satisfaction, trust, and purchase intention. The model fit of this study was in an acceptable level, and this indicates that the theoretical model of this study supports the description of e-service quality for e-retailers that online shopping situation will be effected by trust and satisfaction. The result of this study will be available for those who interested in developing a transnational e-retailer as a reference, as well as academic research on cross-cultural comparative analysis