Pattern Of Spread Research Articles

Evolving patterns of metastatic spread, treatment, and outcome for patients with oligometastatic colorectal cancer

IntroductionThe assessment and management of oligometastatic colorectal cancer has evolved over the last two decades. We aimed to examine trends in the presentation, management and outcomes of patients presenting with liver-only disease, given recent changed standards for baseline imaging, and evolving definitions of resectability. Patients with lung-only disease can provide a contemporaneous control group. MethodsProspectively maintained data from the multi-site Treatment of Recurrent and Advanced Colorectal Cancer Registry were reviewed over three consecutive periods; 2009–2013, 2014–2018, and 2019–2023. Survival outcomes were determined by Kaplan-Meier method. ResultsOf 4613 patients with metastatic colorectal cancer, median age was 66 years (interquartile range 56–76), and 2356 (51 %) patients had a single metastatic site. Compared to the earlier periods, patients diagnosed in 2019–2023, were younger, had better ECOG scores and were more likely to have three or more metastatic sites. The proportion of patients with liver-only metastases decreased over the three consecutive periods, from 32.0 % (n = 462), to 27.0 % (n = 498) to 25.9 % (n = 33), p < 0.001, however the proportion of liver-only metastases patients undergoing resection increased from 41.5 to 59.3 %, p < 0.001. The incidence and resection rate of lung-only metastases was unchanged over time. ConclusionThe increasing number of metastatic sites and reduced number of patients with liver-only metastases is potentially explained by the increased use of FDG-PET imaging at baseline. The increased proportion of patients with liver-only disease undergoing resection may be explained by advancement in surgical techniques, improvements in systemic therapies and the evolving definition of resectable disease. SynopsisThe pattern and treatment of metastatic colorectal cancer has evolved over the last two decades. This study examines the trends in presentation management and outcomes of patients with metastatic colorectal cancer using a multi-site database.

Investigation of landscape risk factors for the recent spread of varroa mite (Varroa destructor) in European honeybee (Apis mellifera) colonies in New South Wales, Australia.

In June 2022, an exotic pest of the European honeybee (Apis mellifera), the varroa mite (Varroa destructor), was detected in surveillance hives at the Port of Newcastle, New South Wales (NSW). Previously, Australia remained the only continent free of the varroa mite. In September 2023, the National Management Group decided to shift the focus of the response from eradication to management. It is estimated that the establishment of varroa mite in Australia could lead to more than $70 million in losses each year due to greatly reduced pollination services. Currently, there are no reported studies on the epidemiology of varroa mite in NSW because it is such a recent outbreak, and there is little knowledge of the factors associated with the presence of V. destructor in the Australian context. We sourced publicly available varroa mite outbreak reports from June 22 to December 19, 2022, to determine if urbanization, land use, and distance from the incursion site are associated with the detection of varroa mite infestation in European honeybee colonies in NSW. The outcome investigated was epidemic day, relative to the first detected premises (June 22, 2022). The study population was comprised of 107 premises, which were declared varroa-infested. The median epidemic day was day 37 (July 29, 2022), and a bimodal distribution was observed from the epidemic curve, which was reflective of an intermittent source pattern of spread. We found that premises were detected to be infected with varroa mite earlier in urban areas [median epidemic day 25 (July 17, 2022)] compared to rural areas [median epidemic day 37.5 (July 29, 2022)]. Infected premises located in areas without cropping, forests, and irrigation were detected earlier in the outbreak [median epidemic days 23.5 (July 15, 2022), 30 (July 22, 2022), and 15 (July 7, 2022), respectively] compared to areas with cropping, forests, and irrigation [median epidemic days 50 (August 11, 2022), 43 (August 4, 2022), and 47 (August 8, 2022), respectively]. We also found that distance from the incursion site was not significantly correlated with epidemic day. Urbanization and land use are potential factors for the recent spread of varroa mite in European honeybee colonies in NSW. This knowledge is essential to managing the current varroa mite outbreak and preventing future mass varroa mite spread events.

Transcriptomic Profiling of Primary Prostate Cancers and Nonlocalized Disease on Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography: A Multicenter Retrospective Study.

To characterize the relationship between Decipher genomic classifier scores and prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT)-based metastatic spread. We identified patients from four institutions who underwent PSMA PET/CT scans pretreatment for primary staging or postradical prostatectomy (RP) for suspected recurrence and had Decipher transcriptomic data available from biopsy or RP specimens. PSMA PET/CT-based patterns of spread were classified as localized (miT + N0M0) or nonlocalized (miN1M0 or miM1a-c). We calculated the association between Decipher scores and the risk of nonlocalized disease on PSMA PET/CT using multivariable logistic regression for pretreatment patients and multivariable Cox regression for post-RP patients. We also compared select transcriptomic signatures between patients with localized and nonlocalized diseases. Five hundred eighty-six patients were included (pretreatment: n = 329; post-RP: n = 257). Higher Decipher scores were associated with nonlocalized disease on PSMA PET/CT both pretreatment (odds ratio, 1.18 [95% CI, 1.03 to 1.36] per 0.1 increase in Decipher score, P = .02) and post-RP (hazard ratio, 1.15 [95% CI, 1.05 to 1.27] per 0.1 increase in Decipher score, P = .003). In the pretreatment setting, nonlocalized disease was associated with higher rates of TP53 mutations and lower rates of PAM50 luminal A subtype compared with localized disease. In the post-RP setting, overexpression of signatures related to metabolism, DNA repair, and androgen receptor signaling were associated with higher rates of nonlocalized disease. Higher Decipher scores were associated with nonlocalized disease identified on PSMA PET/CT both pretreatment and post-RP. There were several transcriptomic differences between localized and nonlocalized diseases in both settings.

The Spread Pattern of New Practice in Liver Transplantation in the United States.

Introducing new liver transplantation (LT) practices, like unconventional donor use, incurs higher costs, making evaluation of their prognostic justification crucial. This study reexamines the spread pattern of new LT practices and its prognosis across the United States. The study investigated the spread pattern of new practices using the UNOS database (2014-2023). Practices included LT for hepatitis B/C (HBV/HCV) nonviremic recipients with viremic donors, LT for COVID-19-positive recipients, and LT using onsite machine perfusion (OMP). One year post-LT patient and graft survival were also evaluated. LTs using HBV/HCV donors were common in the East, while LTs for COVID-19 recipients and those using OMP started predominantly in California, Arizona, Texas, and the Northeast. K-means cluster analysis identified three adoption groups: facilities with rapid, slow, and minimal adoption rates. Rapid adoption occurred mainly in high-volume centers, followed by a gradual increase in middle-volume centers, with little increase in low-volume centers. The current spread patterns did not significantly affect patient survival. Specifically, for LTs with HCV donors or COVID-19 recipients, patient and graft survivals in the rapid-increasing group was comparable to others. In LTs involving OMP, the rapid- or slow-increasing groups tended to have better patient survival (p=0.05) and significantly improved graft survival rates (p=0.02). Facilities adopting new practices often overlap across different practices. Our analysis revealed three distinct adoption groups across all practices, correlating the adoption aggressiveness with LT volume in centers. Aggressive adoption of new practices did not compromise patient and graft survivals, supporting the current strategy. Understanding historical trends could predict the rise in future LT cases with new practices, aiding in resource distribution.

Instabilities and self–organization in spatiotemporal epidemic dynamics driven by nonlinearity and noise

Theoretical analysis of epidemic dynamics has attracted significant attention in the aftermath of the COVID–19 pandemic. In this article, we study dynamic instabilities in a spatiotemporal compartmental epidemic model represented by a stochastic system of coupled partial differential equations (SPDE). Saturation effects in infection spread–anchored in physical considerations–lead to strong nonlinearities in the SPDE. Our goal is to study the onset of dynamic, Turing–type instabilities, and the concomitant emergence of steady–state patterns under the interplay between three critical model parameters–the saturation parameter, the noise intensity, and the transmission rate. Employing a second–order perturbation analysis to investigate stability, we uncover both diffusion–driven and noise–induced instabilities and corresponding self–organized distinct patterns of infection spread in the steady state. We also analyze the effects of the saturation parameter and the transmission rate on the instabilities and the pattern formation. In summary, our results indicate that the nuanced interplay between the three parameters considered has a profound effect on the emergence of dynamical instabilities and therefore on pattern formation in the steady state. Moreover, due to the central role played by the Turing phenomenon in pattern formation in a variety of biological dynamic systems, the results are expected to have broader significance beyond epidemic dynamics.

A review of dengue transmission and dengue therapy among people

Dengue fever is a significant threat to global health, caused by the dengue virus and transmitted mainly by Aedes mosquitoes. It is crucial to understand the transmission dynamics of the virus to develop effective control and prevention strategies. Epidemiological studies have provided valuable insights into outbreaks' spread patterns, risk factors, and nature. These are essential for targeted interventions such as vector control, reducing human-mosquito contact, and community-based preventive measures. At the same time, there is a pressing need to develop effective therapies to alleviate the disease burden and reduce mortality associated with dengue outbreaks. Current therapeutic research focuses on antiviral treatments, supportive care strategies, and vaccine development to combat the diverse clinical manifestations of dengue. To address the multifaceted challenges of dengue, there must be a concerted effort toward developing robust preventive measures, innovative therapies, and enhanced diagnostic tools. A comprehensive understanding of its transmission dynamics coupled with effective therapeutic interventions is pivotal in pursuing dengue control and mitigation, as it poses a formidable global health challenge.

Study on Temporal and Spatial Distribution of Landslides in the Upper Reaches of the Yellow River

The geological structure of the upper reaches of the Yellow River is complex, especially in the Sigouxia-Laganxia section. It has always been a high-incidence area of landslide disasters, which poses a threat to the safe operation of the upper reaches of the Yellow River. In this study, based on the high-precision remote sensing image data, the spatial distribution of each landslide was obtained by superimposing the remote sensing image and the 1:50,000 digital elevation model (DEM). Some typical landslides were selected for detailed field investigation and field verification. The results show that the remote sensing image characteristics of landslides in the upper reaches of the Yellow River are obvious. Through remote sensing interpretation and field investigation, a total of 508 landslides of various types were found, including 24 giant landslides. The spatial spreading patterns of landslides mainly include six types: dumb-bell shape, rectangle, saddle type, long arc shape, triangle, and side-by-side shape. The length and width of the landslide deposit are mainly concentrated at 550–1500 m and 600–1500 m, and the average elevation of the sliding body is mainly concentrated between 2000 and 2800 m. The average slope of the landslide is mainly distributed between 15–20°. Giant landslides are mainly distributed in the Jianzha basin area, surrounded by the Jishishan fault and the Lajishan fault in the West Qinling Mountains. The spatial distribution characteristics of giant landslides have obvious regional differences due to different factors such as lithologic differences and riverside erosion. The research results are of great significance for the early identification, prevention, and mitigation of landslide disasters in the upper reaches of the Yellow River.

Navigating the labyrinth of peritoneal and extraperitoneal anatomy: abdominal spread made easy with a case based review.

Essential to understanding disease spread in abdomen is to separate the peritoneum from the extraperitoneum. These areas have distinct anatomy with well-define separate pathways. The peritoneum is comprised of connected recesses that are potential spaces, normally not imaged except when containing excess fluid or air. Peritoneal recesses are formed by the opposing peritoneal surfaces and subdivided by the attachments of the ligaments and mesenteries to the parietal peritoneum. Disease flows within the recesses by changes in abdominal pressure. This forms a distinct spread pattern. The extraperitoneum is traditionally stratified by the renal fascia into the anterior and posterior pararenal spaces and the perirenal space. The fascia contains and directs spread from the contained organs with the compartments. Each space has a unique spread pattern defined by the containing fascia. The extraperitoneum is connected to the mesenteries and ligaments forming the subperitoneal space. This space interconnects the extraperitoneum with the mesenteries allowing for the normal continuum of blood vessels, lymphatics, and nerves but also forms the pathways for bidirectional spread of disease.

Data-Driven Wildfire Spread Modeling of European Wildfires Using a Spatiotemporal Graph Neural Network

Wildfire spread models are an essential tool for mitigating catastrophic effects associated with wildfires. However, current operational models suffer from significant limitations regarding accuracy and transferability. Recent advances in the availability and capability of Earth observation data and artificial intelligence offer new perspectives for data-driven modeling approaches with the potential to overcome the existing limitations. Therefore, this study developed a data-driven Deep Learning wildfire spread modeling approach based on a comprehensive dataset of European wildfires and a Spatiotemporal Graph Neural Network, which was applied to this modeling problem for the first time. A country-scale model was developed on an individual wildfire time series in Portugal while a second continental-scale model was developed with wildfires from the entire Mediterranean region. While neither model was able to predict the daily spread of European wildfires with sufficient accuracy (weighted macro-mean IoU: Portugal model 0.37; Mediterranean model 0.36), the continental model was able to learn the generalized patterns of wildfire spread, achieving similar performances in various fire-prone Mediterranean countries, indicating an increased capacity in terms of transferability. Furthermore, we found that the spatial and temporal dimensions of wildfires significantly influence model performance. Inadequate reference data quality most likely contributed to the low overall performances, highlighting the current limitations of data-driven wildfire spread models.

Dynamics of endemic human coronavirus and SARS-CoV-2 in a hospital of Madrid, Spain. Retrospective study from June 2020 to July 2023.

An observational and retrospective study was carried out to analyse HCoV positivity from a multiplex PCR respiratory panel and RT-PCR for SARS-CoV-2 in respiratory samples from 1 June 2020 to 31 July 2023 at the Príncipe de Asturias University Hospital (HUPA) in Alcalá de Henares, Madrid, Spain. Out of 2802 respiratory panels, 1258 (44.8%) turned out positive. HCoV was detected in 114 (4%) cases (range 0-23; median 1.5; IQR 0-3.75) with positivity rates ranging from 0% to 14%. All four variants of HCoV circulated, and OC-43 was the most common in 62.3% of cases. After the onset of the pandemic, the HCoV season was delayed 22 weeks, with a peak positivity of 9% in the summer of 2021, showing an inverse relationship with the alpha and delta waves of SARS-CoV-2. In the two subsequent autumn-winter seasons, HCoV positivity increased (11-14%) with a reduction in the summer of 2022 and 2023 following the emergence of the omicron variant and the relaxation of social distancing measures. The seasonal spread pattern of endemic HCoV might be returning to normal in our region and likely in other temperate zones of the northern hemisphere after 3 years of the pandemic.

Infection patterns in simple and complex contagion processes on networks.

Contagion processes, representing the spread of infectious diseases, information, or social behaviors, are often schematized as taking place on networks, which encode for instance the interactions between individuals. The impact of the network structure on spreading process has been widely investigated, but not the reverse question: do different processes unfolding on a given network lead to different infection patterns? How do the infection patterns depend on a model's parameters or on the nature of the contagion processes? Here we address this issue by investigating the infection patterns for a variety of models. In simple contagion processes, where contagion events involve one connection at a time, we find that the infection patterns are extremely robust across models and parameters. In complex contagion models instead, in which multiple interactions are needed for a contagion event, non-trivial dependencies on models parameters emerge, as the infection pattern depends on the interplay between pairwise and group contagions. In models involving threshold mechanisms moreover, slight parameter changes can significantly impact the spreading paths. Our results show that it is possible to study crucial features of a spread from schematized models, and inform us on the variations between spreading patterns in processes of different nature.

Fire in the rainforest: A 3200‐year history of fire in a West Kalimantan, Indonesia, tropical rainforest

AbstractDespite its perceived historical rarity, fire is an important disturbance in tropical rainforests. Very large rainforest fires have been observed multiple times in recent decades, often during years of strong El Niño‐Southern Oscillation droughts. Fire in rainforest has major short‐term consequences for humans and wildlife by converting forest to fire‐prone fern, shrub, and grass, but the long‐term effects remain to be seen. Borneo's indigenous groups have been using fire to clear land for centuries, yet the prevalence and spatial patterns of premodern fire across forest types in Borneo are not well understood. This research set out to reconstruct fire in a 1500‐ha primary rainforest spanning 800 m of elevation in Indonesian Borneo with the goal of elucidating the role humans have played in rainforest fire. We found that humans played an important role in the occurrence of fire in recent centuries. Evidence of fire—charcoal &gt;2 mm—is more abundant in forest types where humans would be more likely to live and/or practice swidden agriculture. However, pyrogenic material is ubiquitous across the study area, showing that all forest types have experienced fire. A set of 50 radiocarbon dates showed that in lowland areas—where human‐caused fire is most likely—fire occurred throughout the last 3200 years, peaking 1300–1600 ce. The upland areas lacked evidence of fire before 1250 ce but otherwise had a similar pattern to the lowlands. The period of high fire coincides with regional demographic changes as well as regional droughts documented elsewhere in Southeast Asia. In upland areas, fires likely burned only under regional drought when fires could more easily spread upslope. Although forest plot studies at this site show little structural evidence of past fires, tree diversity is lower than expected in the most burned areas (alluvial benches). Thus, our results suggest that land clearance was a major source of fire, but the current intact state of these rainforests indicates that they were largely resilient to fires and land use hundreds of years ago. Recent fires mirror patterns of fire spread that occurred hundreds of years ago, though their severity and extent are likely much greater.

Association of lung cancer-associated cachexia with the metastatic spread to pleura.

12095 Background: Cancer-associated cachexia (CAC), a major contributor to mortality in patients with non-small cell lung cancer (NSCLC), is characterized by alterations in body composition. Here, we explore the associations between body composition changes and the pattern of lung cancer metastatic spread. Methods: Computer tomography (CT) images from cancer diagnosis and recurrence were used to quantify subcutaneous and visceral adipose tissue (SAT, VAT) and skeletal muscle (SKM) tissue areas at the 3rd lumbar vertebrae level, using an DAFS AI-based software, Voronoi Analytics, in 101 NSCLC pts, who relapsed after surgical treatment of the primary tumor at the Medical University of Gdansk Hospital. The decrease in SKM, SAT and VAT of more than 5% or 10% at cancer relapse was compared with the pattern of cancer recurrence. Results: The median time to recurrence after primary tumor resection was 1.6 years (0.4–6.4 years). There were 38% local or regional recurrences, 59% distant recurrences, and 13% second primary lung cancers. Among the cases with distant recurrence, there were 19% brain recurrences, 22% pleural metastases, 34% lung metastases, 17% bone metastases, and 11% cases of liver relapse. More than one site of distant recurrence occurred in 51 (50%) of patients. Loss of &gt; 5% of SKM, SAT and VAT occurred in 61%, 33% and 41% respectively. Loss of &gt;5% or &gt;10% of SKM was associated with the pleural metastases at the time of cancer recurrence, ( P &lt; 0.001). Median muscle loss was –11.6% for patients with pleural relapse and –5.3 % for patients with other metastatic locations ( P &lt; 0.001). There were no significant associations between other body composition changes and the pattern of recurrences, tumor histology or age. Conclusions: NSCLC relapse to the pleura after surgical treatment of the primary tumor, appears to be associated with a decrease in the skeletal muscle compartment. This finding may inform the design of the future studies aiming to investigate molecular correlates of sarcopenia and cancer-associated cachexia.

Staging and Restaging Pediatric Abdominal and Pelvic Tumors: A Practical Guide.

The most common abdominal malignancies diagnosed in the pediatric population include neuroblastoma, Wilms tumor, hepatoblastoma, lymphoma, germ cell tumor, and rhabdomyosarcoma. There are distinctive imaging findings and patterns of spread for each of these tumors that radiologists must know for diagnosis and staging and for monitoring the patient's response to treatment. The multidisciplinary treatment group that includes oncologists, surgeons, and radiation oncologists relies heavily on imaging evaluation to identify the best treatment course and prognostication of imaging findings, such as the image-defined risk factors for neuroblastomas, the PRETreatment EXtent of Disease staging system for hepatoblastoma, and the Ann Arbor staging system for lymphomas. It is imperative for radiologists to be able to correctly indicate the best imaging methods for diagnosis, staging, and restaging of each of these most prevalent tumors to avoid inconclusive or unnecessary examinations. The authors review in a practical manner the most updated key points in diagnosing and staging disease and assessing response to treatment of the most common pediatric abdominal tumors. ©RSNA, 2024 Supplemental material is available for this article.

1960년대 한-일 대중음악에 나타나는 비틀즈의 영향을 통한, 대중음악의 수용의미 분석 - 1960년대 양국 밴드 음악의 비교를 중심으로

Since the Beatles’ arrival in New York on February 7 th , 1964 was broadcast, they have shaken up not only the United States but also the world’s popular music market. Korea and Japan, which were strongly influenced by American pop culture at the time, were also influenced by British-style band music including the Beatles. Based on this cultural phenomenon that Korea and Japan experienced simultaneously in the 1960s, this study examined the patterns of cultural spread in the Anglo-American region between the two nations via a comparison of the music of the two countries at the time. This study compared Korean and Japanese 60s popular music in terms of melodies and harmonies that were influenced by British-style band music represented by the Beatles. As a result, the band music of both countries exhibited similarities and differences in musical aspects. A common factor is that the band music of both countries follows the Beatles’ band formation and arrangement method; however, differences were also observed. In the case of Korean bands, excluding their adapted songs, the musical influence of the Beatles is not easy to find. Korean band Add4’s songs were made using pentatonic scales, which give the feeling of Korean folk music. The band Keyboys wrote songs in the trot genre. In the case of Japan, other examples can be found. The band The Spiders and The Dynamites used music as similar to the Beatles as possible, thereby reflecting the Beatles’ melodic and harmonic characteristics as much as possible. Jackey Yoshikawa and the Blue Comets showed enka tendencies. Based on our results, Korea’s 1960s band music localized new English-American music and accepted it in a compromise manner. Japanese band music also attempted to localize, but attempted to copy the trend of English-American music represented by the Beatles. It was confirmed that attempts had also been made. Based on these differences in cultural acceptance between the two countries, the patterns of cultural transmission at the time in the Anglo-American world can be summarized as follows. 1. The public’s level of exposure to Anglo-American culture was different in the two countries. 2. The music production companies of the two countries had different approaches to the newly forming English-American music. Thereafter, Korean and Japanese popular music in the 70s and 80s took different paths. This difference can be viewed as the result of the two countries’ different acceptance of Anglo-American music from the 50s, 60s, and 70s, which are considered a time of differentiation in Anglo-American popular music genres such as rock, rock‘n’roll, and R&amp;B. The occurrence of the phenomenon of cultural acceptance influencing later generations of music is believed to be repeating with the birth of K-pop. Accordingly, the formation of modern K-pop and its differences from J-pop can be considered as future research tasks.

Machine learning provides insights for spatially explicit pest management strategies by integrating information on population connectivity and habitat use in a key agricultural pest.

Insect pests have garnered increasing interest because of anthropogenic global change, and their sustainable management requires knowledge of population habitat use and spread patterns. To enhance this knowledge for the prevalent tea pest Empoasca onukii, we utilized a random forest algorithm and a bivariate map to develop and integrate models of its habitat suitability and genetic connectivity across China. Our modeling revealed heterogeneous spatial patterns in suitability and connectivity despite the common key environmental predictor of isothermality. Analyses indicated that tea cultivation in areas surrounding the Tibetan Plateau and the southern tip of China may be at low risk of population outbreaks because of their predicted low suitability and connectivity. However, regions along the middle and lower reaches of the Yangtze River should consider the high abundance and high recolonization potential of E. onukii, and thus the importance of control measures. Our results also emphasized the need to prevent dispersal from outside regions in the areas north of the Yangtze River and highlighted the effectiveness of internal management efforts in southwestern China and along the southeastern coast. Further projections under future conditions suggested the potential for increased abundance and spread in regions north of the Yangtze River and the southern tip of China, and indicated the importance of long-term monitoring efforts in these areas. These findings highlighted the significance of combining information on habitat use and spread patterns for spatially explicit pest management planning. In addition, the approaches we used have potential applications in the management of other pest systems and the conservation of endangered biological resources. © 2024 Society of Chemical Industry.

Exploring the urban arbovirus landscape in Rio de Janeiro, Brazil: transmission dynamics and patterns of disease spread

This study focuses on urban arboviruses, specifically dengue (DENV), chikungunya (CHIKV), and Zika (ZIKV), which pose a significant public health challenge in Rio de Janeiro state, Southeast Brazil. In our research, we highlight critical findings on the transmission dynamics of these arboviruses in Rio de Janeiro, identifying distinct patterns of disease spread. By combining genomic data with case reports from the Brazilian Ministry of Health, we have analysed the phylogenetics, prevalence and spatial distribution of these endemic viruses within the state. Our results revealed sustained DENV transmission primarily in the northern part of the state, a significant ZIKV epidemic in 2016 affecting all mesoregions, and two major CHIKV outbreaks in 2018 and 2019, predominantly impacting the northern and southern areas. Our analysis suggests an inverse relationship between arboviral case incidence and urban density, with less populous regions experiencing higher transmission rates, potentially attributed to a complex interplay of factors such as the efficacy of vector control measures, environmental conditions, local immunity levels, and human mobility. Furthermore, our investigation unveiled distinct age and gender trends among affected individuals. Notably, dengue cases were predominantly observed in young adults aged 32, while chikungunya cases were more prevalent among individuals over 41. In contrast, cases of ZIKV were concentrated around the 33-year age group. Intriguingly, females accounted for nearly 60% of the cases, suggesting a potential gender-based difference in infection rates. Our findings underscore the complexity of arbovirus transmission and the need for interventions tailored to different geographical mesoregions. Enhanced surveillance and genomic sequencing will be essential for a deeper, more nuanced understanding of regional arbovirus dynamics. Identifying potential blind spots within the state will be pivotal for developing and implementing more effective public health strategies, specifically designed to address the unique challenges posed by these viruses throughout the state. This study was supported by the National Institutes of Health USA grant U01 AI151698 for the United World Arbovirus Research Network (UWARN) and the CRP-ICGEB RESEARCH GRANT 2020 Project CRP/BRA20-03.

Analisis Penyebaran Hoax Di Media Sosial Dan Dampaknya Terhadap Masyarakat

The spread of hoaxes on social media has become a serious problem in society. This research aims to analyze the factors that cause the spread of hoaxes, the characteristics of hoax content, a well as their impact on society. The research method used is the study of literature and content analysis from various online news sources. The results showed that the main factors of the spread of hoaxes were lack of digital literacy., economic motivation, and political polarization. Hoax content generally spreads quickly, has sensational titles, and contains inaccurate information. The impact of hoaxes on society includes confusion, social conflict, and a decline in public trust. This research concludes that comprehensive efforts from the government, media, and the public are needed to overcome the hoax problem. This research aims to analyze the causes, patterns of spread, and the impact of hoaxes on social media on the community. The research methods used are literature studies and content analysis from various trusted sources. Patterns of spreading hoaxes generally utilize sicial media algorithms to achieve a wide reach quickly. The negative impact of hoaxes on society is very diverse, ranging from triggering social confilcts, affecting public opinion, to threatening political stability and national security. This shows the urgency of handing hoaxes comprehensively, involving the role of government, social media platforms, and the public.

Biogeographic patterns of daily wildfire spread and extremes across North America

IntroductionClimate change is predicted to increase the frequency of extreme single-day fire spread events, with major ecological and social implications. In contrast with well-documented spatio-temporal patterns of wildfire ignitions and perimeters, daily progression remains poorly understood across continental spatial scales, particularly for extreme single-day events (“blow ups”). Here, we characterize daily wildfire spread across North America, including occurrence of extreme single-day events, duration and seasonality of fire and extremes, and ecoregional climatic niches of fire in terms of Actual Evapotranspiration (AET) and Climatic Water Deficit (CWD) annual climate normals.MethodsRemotely sensed daily progression of 9,636 wildfires ≥400 ha was used to characterize ecoregional patterns of fire growth, extreme single-day events, duration, and seasonality. To explore occurrence, extent, and impacts of single-day extremes among ecoregions, we considered complementary ecoregional and continental extreme thresholds (Ecoregional or Continental Mean Daily Area Burned + 2SD). Ecoregional spread rates were regressed against AET and CWD to explore climatic influence on spread.ResultsWe found three-fold differences in mean Daily Area Burned among 10 North American ecoregions, ranging from 260 ha day−1 in the Marine West Coast Forests to 751 ha day−1 in Mediterranean California. Ecoregional extreme thresholds ranged from 3,829 ha day−1 to 16,626 ha day−1, relative to a continental threshold of 7,173 ha day−1. The ~3% of events classified as extreme cumulatively account for 16–55% of total area burned among ecoregions. We observed four-fold differences in mean fire duration, ranging from 2.7 days in the Great Plains to 10.5 days in Northwestern Forested Mountains. Regions with shorter fire durations also had greater daily area burned, suggesting a paradigm of fast-growing short-duration fires in some regions and slow-growing long-duration fires elsewhere. CWD had a weak positive relationship with spread rate and extreme thresholds, and there was no pattern for AET.DiscussionRegions with shorter fire durations had greater daily area burned, suggesting a paradigm of fast-growing short-duration fires in some regions and slow-growing long-duration fires elsewhere. Although climatic conditions can set the stage for ignition and influence vegetation and fuels, finer-scale mechanisms likely drive variation in daily spread. Daily fire progression offers valuable insights into the regional and seasonal distributions of extreme single-day spread events, and how these events shape net fire effects.

REGRESSION OF SURVIVAL DAGUM 3 PARAMETER LINK FUNCTION IN HIV/AIDS PATIENTS IN EAST JAVA

AIDS (Acquired Immuno Deficiency Syndrome) is is a symptom of blood cell disease which results in decreased immunity in humans. HIV/AIDS causes a decline in economic productivity, health, and environmental fields, so it needs treatment to reduce the spread of the disease in East Java. The spread of the HIV/AIDS virus is growing rapidly both in terms of region and pattern of spread. Therefore, it is necessary to have policies from the government to prevent the spread of HIV/AIDS through mathematical modeling to determine the actual and comprehensive factors that influence HIV/AIDS care. policies needed to handle and reduce HIV/AIDS in East Java. This study aims to determine the factors that influence the care of people with HIV/AIDS with Survival Regression modeling Dagum 3 Parameter link function. This model uses parameter estimation with a Bayesian analysis approach with the results that the factors that significantly influence the length of HIV/AIDS care in East Java are marital status (X5), absolute CD4 levels (X7), Suffering Stage (X8), Functional State (X9), and Therapy adherence (X10). These results indicate that marital status and condition characteristics of HIV/AIDS sufferers are important information in the socialization program for reducing HIV/AIDS in East Java.