Identification of Spatial Clusters of COVID-19 in Yogyakarta using Moran’s Index

Various studies on the spreading pattern of COVID-19 were carried out because, every day, there are always new progresses from scientists about this virus, including its unique characteristics in each region with different geographical conditions. The objective of this research is to find the spatial distribution pattern of COVID-19 and to identify the climate parameters influencing it in the Yogyakarta. This study used Moran's Index in analyzing COVID-19 distribution pattern. The results of the analysis show that out of 5 regencies/cities in Yogyakarta, Sleman Regency has the highest average spread of COVID-19 or an average infection rate of 1.09, followed by Bantul with 0.75. Kulonprogo is the regency with the lowest number of cases. The result of Moran's index of 0.32 means that there are correlation between cases.The correlation between temperature and infection rate is R2 = 0.05, while the correlation between humidity and infection rate is R2 = 0.003. The spread of COVID-19 in Yogyakarta is more influenced by mobility or interactions between infected and uninfected individuals.

Staging tau pathology with tau PET in Alzheimer’s disease: a longitudinal study

A biological research framework to define Alzheimer’ disease with dichotomized biomarker measurement was proposed by National Institute on Aging–Alzheimer’s Association (NIA–AA). However, it cannot characterize the hierarchy spreading pattern of tau pathology. To reflect in vivo tau progression using biomarker, we constructed a refined topographic 18F-AV-1451 tau PET staging scheme with longitudinal clinical validation. Seven hundred and thirty-four participants with baseline 18F-AV-1451 tau PET (baseline age 73.9 ± 7.7 years, 375 female) were stratified into five stages by a topographic PET staging scheme. Cognitive trajectories and clinical progression were compared across stages with or without further dichotomy of amyloid status, using linear mixed-effect models and Cox proportional hazard models. Significant cognitive decline was first observed in stage 1 when tau levels only increased in transentorhinal regions. Rates of cognitive decline and clinical progression accelerated from stage 2 to stage 3 and stage 4. Higher stages were also associated with greater CSF phosphorylated tau and total tau concentrations from stage 1. Abnormal tau accumulation did not appear with normal β-amyloid in neocortical regions but prompt cognitive decline by interacting with β-amyloid in temporal regions. Highly accumulated tau in temporal regions independently led to cognitive deterioration. Topographic PET staging scheme have potentials in early diagnosis, predicting disease progression, and studying disease mechanism. Characteristic tau spreading pattern in Alzheimer’s disease could be illustrated with biomarker measurement under NIA–AA framework. Clinical–neuroimaging–neuropathological studies in other cohorts are needed to validate these findings.

Exploring public awareness and spreading pattern analysis of COVID-19 outbreak in Bangladesh

Background: The highly transmissible coronavirus disease 2019 (COVID-19) has plagued the worldwide population with a continuous upward thrust of the death toll, which might be related to insufficient knowledge, attitudes, and behavioral (KAB) score, and public awareness. Objective: The current research sought to explore public awareness in terms of knowledge, attitudes, and behavioral responses toward COVID-19 and analyze its spreading pattern during the embryonic phase in Bangladesh. Methods: From March 19 to April 15 of 2020, seventeen planned questions were answered by the Bangladeshi respondents recruited through a simple snowball sampling technique. Informed consent from each participant was taken in the survey. Results: Out of the total participants (n = 1861), 34.65% were female, and 40.83% had an education level up to Junior School Certificate (JSC). Among all the demographic variables, the highest average knowledge, attitudes and behaviors scores (mean ± SD) were reported for 18- 30 years age group (4.07 ± 1.01 out of 5; 95% confidence interval, [CI] = 4.01-4.13; p< 0.001), above 50 years age group (1.70 ± 0.64 out of 3; 95% CI = 1.59-1.80; p< 0.001), and bachelor or higher degree group (2.64 ± 0.83 out of 4; 95% CI = 2.57-2.70, p< 0.001), respectively. It was clearly depicted that the obtained knowledge score was associated with poor attitudes and behaviors. Conclusion: Education on basic health sciences as well as overwhelming campaign and publicity must be pointed at enhancing KAB scores towards COVID-19 in Bangladesh. Bangladesh Journal of Medical Science Vol.20(5) 2021 p.108-117

10-Months Study Regarding the COVID-19 Spreading in Romanian Counties

The paper analyzes the evolution of COVID-19 cases in Romanian counties over a period of 10 months, to highlight possible similarities that may contribute to a better understanding of the spreading pattern. The study uses the numbers of active cases for each county in Romania, as well as Bucharest and the whole country, reported daily by the Romanian Ministry of Health (https://datelazi.ro) between April 2nd, 2020 and January 25th, 2021. We compared the disease’s evolution in Suceava county (the first outbreak of spread) with other counties in Romania in order to highlight the gaps between them. We calculated the cross-correlations between counties, interpreted as time series. The recorded lags varied between 1–15 days, the most counties having a lag of 6–7 days compared with Suceava. Therefore, on long term there are no important discrepancies between the regions in Romania regarding the evolution of the disease, which shows that the intervention efforts of the medical staff were uniform in efficiency. The existence of a lag of only one day between Suceava and the whole country shows that on long term, even in this county the situation is not very discrepant, belonging to the general evolution.

Modeling the interplay between epidemics and regional socio-economics

In this study we present a dynamical agent-based model to investigate the interplay between the socio-economy of and SEIRS-type epidemic spreading over a geographical area, divided to smaller area districts and further to smallest area cells. The model treats the populations of cells and authorities of districts as agents, such that the former can reduce their economic activity and the latter can recommend economic activity reduction both with the overall goal to slow down the epidemic spreading. The agents make decisions with the aim of attaining as high social positions as possible relative to other agents. They evaluate their social positions based on the local and regional infection rates, compliance to the authorities’ regulations, regional drops in economic activity, and the efforts they make to mitigate the spread of epidemic. We find that the willingness of populations to comply with authorities’ recommendations has the most drastic effect to the spreading of epidemic: periodic waves spread almost unimpeded in non-compliant populations, while in compliant ones the spread is minimal with a chaotic spreading pattern and significantly lower infection rates. Health and economic concerns of agents turned out to have lesser roles, the former increasing their efforts and the latter decreasing them.

Reconstructing Diffusion Model for Virality Detection in News Spread Networks

In today's competitive world, organizations take advantage of widely-available data to promote their products and increase their revenue. This is achieved by identifying the reader's preference for news genre and patterns in news spread network. Spreading news over the internet seems to be a continuous process which eventually triggers the evolution of temporal networks. This temporal network comprises of nodes and edges, where node corresponds to published articles and similar articles are connected via edges. The main focus of this article is to reconstruct a susceptible-infected (SI) diffusion model to discover the spreading pattern of news articles for virality detection. For experimental analysis, a dataset of news articles from four domains (business, technology, entertainment, and health) is considered and the articles' rate of diffusion is inferred and compared. This will help to build a recommendation system, i.e. recommending a particular domain for advertisement and marketing. Hence, it will assist to build strategies for effective product endorsement for sustainable profitability.