Journal articles on the topic 'Epidemic event extraction'
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Lejeune, Gaël, Romain Brixtel, Antoine Doucet, and Nadine Lucas. "Multilingual event extraction for epidemic detection." Artificial Intelligence in Medicine 65, no. 2 (October 2015): 131–43. http://dx.doi.org/10.1016/j.artmed.2015.06.005.
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Han, Xuehua, Juanle Wang, Min Zhang, and Xiaojie Wang. "Using Social Media to Mine and Analyze Public Opinion Related to COVID-19 in China." International Journal of Environmental Research and Public Health 17, no. 8 (April 17, 2020): 2788. http://dx.doi.org/10.3390/ijerph17082788.
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The outbreak of Corona Virus Disease 2019 (COVID-19) is a grave global public health emergency. Nowadays, social media has become the main channel through which the public can obtain information and express their opinions and feelings. This study explored public opinion in the early stages of COVID-19 in China by analyzing Sina-Weibo (a Twitter-like microblogging system in China) texts in terms of space, time, and content. Temporal changes within one-hour intervals and the spatial distribution of COVID-19-related Weibo texts were analyzed. Based on the latent Dirichlet allocation model and the random forest algorithm, a topic extraction and classification model was developed to hierarchically identify seven COVID-19-relevant topics and 13 sub-topics from Weibo texts. The results indicate that the number of Weibo texts varied over time for different topics and sub-topics corresponding with the different developmental stages of the event. The spatial distribution of COVID-19-relevant Weibo was mainly concentrated in Wuhan, Beijing-Tianjin-Hebei, the Yangtze River Delta, the Pearl River Delta, and the Chengdu-Chongqing urban agglomeration. There is a synchronization between frequent daily discussions on Weibo and the trend of the COVID-19 outbreak in the real world. Public response is very sensitive to the epidemic and significant social events, especially in urban agglomerations with convenient transportation and a large population. The timely dissemination and updating of epidemic-related information and the popularization of such information by the government can contribute to stabilizing public sentiments. However, the surge of public demand and the hysteresis of social support demonstrated that the allocation of medical resources was under enormous pressure in the early stage of the epidemic. It is suggested that the government should strengthen the response in terms of public opinion and epidemic prevention and exert control in key epidemic areas, urban agglomerations, and transboundary areas at the province level. In controlling the crisis, accurate response countermeasures should be formulated following public help demands. The findings can help government and emergency agencies to better understand the public opinion and sentiments towards COVID-19, to accelerate emergency responses, and to support post-disaster management.
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Saba, Djamel, Abdelkader Hadidi, Omar Cheikhrouhou, Monia Hamdi, and Habib Hamam. "Development of an Ontology-Based Solution to Reduce the Spread of Viruses." Applied Sciences 12, no. 22 (November 21, 2022): 11839. http://dx.doi.org/10.3390/app122211839.
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With the sudden emergence of many dangerous viruses in recent years and with their rapid transmission and danger to individuals, most countries have adopted several strategies, such as closure and social distancing, to control the spread of the virus in the population. In parallel with all these precautions, scientific laboratories are working on developing the appropriate vaccine, which in many cases takes many years. Until then, it is necessary to resort to many solutions, including solutions that rely on information technologies and artificial intelligence (AI). In this context, this paper proposes a new solution based on the ontology and rules of intelligent reasoning. Initially, the virus environment is analyzed, followed by the extraction and editing of the main elements of the ontology using the “Protégé” software. In the last step, the proposed solution is tested, by choosing the city of Adrar in southwestern Algeria, which was particularly affected by COVID-19. Three scenarios were shown for different cases. The efficiency of the proposed solution was confirmed through the instructions it provides in the event of symptoms appearing in a person. In addition, this solution helps the competent authorities know the location and extent of the epidemic by informing the local communities.
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Abdelkoui, Feriel, and Mohamed-Khireddine Kholladi. "Extracting Criminal-Related Events from Arabic Tweets." Journal of Information Technology Research 10, no. 3 (July 2017): 34–47. http://dx.doi.org/10.4018/jitr.2017070103.
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Recently, Twitter as one of social networks has been considered as a rich source of spatio-temporal information and significant revenue for mining data. Event detection from tweets can help to predict more serious real-world events. Such as: criminal events, natural hazards, and the spread of epidemics. Etc. This paper deals with event-based extraction for criminal incidents from Arabic tweets. It presents a framework that supports automated extraction of spatial and temporal information from tweets. The proposed approach is based on combining various indicators, including the names of places and temporal expressions that appear in the tweet message, related tweeting time, and additional locations from the user's profile. The effectiveness of the system was evaluated in term of recall, precision and f-measure.
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Libin, Pieter J. K., Lander Willem, Timothy Verstraeten, Andrea Torneri, Joris Vanderlocht, and Niel Hens. "Assessing the feasibility and effectiveness of household-pooled universal testing to control COVID-19 epidemics." PLOS Computational Biology 17, no. 3 (March 9, 2021): e1008688. http://dx.doi.org/10.1371/journal.pcbi.1008688.
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Outbreaks of SARS-CoV-2 are threatening the health care systems of several countries around the world. The initial control of SARS-CoV-2 epidemics relied on non-pharmaceutical interventions, such as social distancing, teleworking, mouth masks and contact tracing. However, as pre-symptomatic transmission remains an important driver of the epidemic, contact tracing efforts struggle to fully control SARS-CoV-2 epidemics. Therefore, in this work, we investigate to what extent the use of universal testing, i.e., an approach in which we screen the entire population, can be utilized to mitigate this epidemic. To this end, we rely on PCR test pooling of individuals that belong to the same households, to allow for a universal testing procedure that is feasible with the limited testing capacity. We evaluate two isolation strategies: on the one handpool isolation, where we isolate all individuals that belong to a positive PCR test pool, and on the other handindividual isolation, where we determine which of the individuals that belong to the positive PCR pool are positive, through an additional testing step. We evaluate this universal testing approach in theSTRIDEindividual-based epidemiological model in the context of the Belgian COVID-19 epidemic. As the organisation of universal testing will be challenging, we discuss the different aspects related to sample extraction and PCR testing, to demonstrate the feasibility of universal testing when a decentralized testing approach is used. We show through simulation, that weekly universal testing is able to control the epidemic, even when many of the contact reductions are relieved. Finally, our model shows that the use of universal testing in combination with stringent contact reductions could be considered as a strategy to eradicate the virus.
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Pisano, Carlo. "Strategies for Post-COVID Cities: An Insight to Paris En Commun and Milano 2020." Sustainability 12, no. 15 (July 22, 2020): 5883. http://dx.doi.org/10.3390/su12155883.
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In recent times, many infectious diseases have been spreading at an increasing scale and frequency. There is a common agreement in the literature that our cities should be prepared in the future to react promptly to epidemics, but the way in which this preparedness should be shaped is still an open question. This study aims to introduce a series of factors that should be taken into consideration in building a working framework to define and evaluate strategies for post-COVID cities. Through the use of the mutual learning methodology, this contribution draws on the concept of the epidemic prevention area (EPA) proposed by a research team at the School of Architecture, Southeast University (SEU) in China together with the UNESCO Chair in Cultural Resource Management, as an urban responding system to the COVID-19 epidemic, extracting its main factors and comparing them with two European post-COVID urban strategies: The Paris en Commun and Milano 2020. Research findings highlight that three factors—decentralization of facilities, hierarchization of the transport system and public services, and redundancy of public and semipublic functions—appeared to be particularly relevant in post-COVID cities, to promptly face future epidemic events, while improving their quality, equity, and resilience.
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Adamson, Rebecca. "Vulnerabilities of Women in Extractive Industries." ANTYAJAA: Indian Journal of Women and Social Change 2, no. 1 (June 2017): 24–31. http://dx.doi.org/10.1177/2455632717714134.
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Perhaps it should not be surprising that sex crimes, the sex trade and anti-woman violence, have become major and predictable by-products of oil, gas and mining extraction operations. After all, mining and drilling camps attract hundreds, even thousands of mostly male workers, typically housed in makeshift ‘man camps’. It is a global epidemic. This article looks at the market trends among investors who look at social performance as well as financial performance. It includes a case study on the difference in financial performance between the oil, gas and mining companies that uphold Indigenous peoples’ rights and those companies that do not. The results indicate that for the extractive industry and its investors, doing what is right and doing what pays are one and the same when it comes to Indigenous peoples’ rights. This article proposes that it would be the same for women’s rights and that as governments increasingly prove incapable or unwilling to protect women, we need to turn to the market and make our voices heard. What is needed are the metrics and analytical tools for assessing the impact and financial risks a company can incur, when it fails to recognize women’s rights.
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Omoniwa, D. O., C. N. Chinyere, E. R. Agusi, N. Mkpuma2, J. S. Oyetunde, O. E. Igah, J. Adole, A. M. Adidu-Omoniwa, and C. A. Meseko. "Serological and molecular investigation of canine influenza virus in Plateau State, Nigeria." Sokoto Journal of Veterinary Sciences 20, no. 3 (October 17, 2022): 212–15. http://dx.doi.org/10.4314/sokjvs.v20i3.8.
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Canine influenza is a highly contagious respiratory infection of dogs caused by the Influenza A Virus (IAV), characterized by cough, sneeze, nasal secretions, and inappetence. Infections can be mild, severe or fatal. Aquatic birds constitute a natural reservoir for IAV, which is transmitted to terrestrial birds, including poultry. IAV has also emerged in other mammalian species, including humans, swine, horses, and dogs. IAV epidemics in dogs are a recent development. Commonly detected Canine Influenza Virus (CIV) strains are A/H3N2 and A/H3N8 from avian and equine influenza, respectively. Nigeria’s agro-ecology witnessed widespread circulation of avian influenza since 2006, and recent outbreaks of equine influenza in 2018/2019 raise the possibility of inter-species transmission to dogs. To investigate canine Influenza in Plateau State, we collected 113 nasal swabs and 270 sera samples from dogs in clinics, live dog markets, and during dog vaccination campaigns. After extracting nucleic acid with the Qiagen kit, RT-PCR analysed swabs for the Influenza A matrix gene. Sera samples were screened by Enzyme-Linked Immunosorbent Assay before subtyping a cross-section for H3 antibody by Hemagglutination Inhibition. No matrix gene was amplified from extracted nucleic acid from the nasal swabs. Though few sera were reactive to influenza A nucleoprotein, none was positive for influenza A/H3. The H3N8 strain of equine influenza virus first caused an epidemic in dogs in 1999 in the United States. Subsequently, avian-origin H3N2 CIV emerged in dogs in China and South Korea in 2005. Past CIV epidemics arose from a single cross-species transmission of H3N8 subtype from a mammalian intermediate host and the H3N2 subtype from an avian reservoir. Even though this limited investigation did not detect CIV in Plateau State, the potential remains because of the persistent circulation of avian, swine, and equine Influenza in Nigeria, which requires more extensive virological and serological surveillance.
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Park, Chulmin, Won-Bok Kim, Sung-Yeon Cho, Eun-Jee Oh, Hyeyoung Lee, Kyungjoon Kang, Yoonsuk Lee, and Dong-Gun Lee. "A Simple Method for the Design and Development of Flavivirus NS1 Recombinant Proteins Using an In Silico Approach." BioMed Research International 2020 (February 13, 2020): 1–13. http://dx.doi.org/10.1155/2020/3865707.
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Even in countries that are currently not facing a flavivirus epidemic, the spread of mosquito-borne flaviviruses presents an increasing public threat, owing to climate change, international travel, and other factors. Many of these countries lack the resources (viral strains, clinical specimens, etc.) needed for the research that could help cope with the threat imposed by flaviviruses, and therefore, an alternative approach is needed. Using an in silico approach to global databases, we aimed to design and develop flavivirus NS1 recombinant proteins with due consideration towards antigenic variation. NS1 genes analyzed in this study included a total of 6,823 sequences, from Dengue virus (DENV), Japanese encephalitis virus (JEV), West Nile virus (WNV), Zika virus (ZIKV), and Yellow fever virus (YKV). We extracted and analyzed 316 DENV NS1 sequence types (STs), 59 JEV STs, 75 WNV STs, 30 YFV STs, and 43 ZIKV STs using a simple algorithm based on phylogenetic analysis. STs were reclassified according to the variation of the major epitope by MHC II binding. 78 DENV epitope type (EpT), 29 JEV EpTs, 29 WNV EpTs, 12 YFV EpTs, and 5 ZIKV EpTs were extracted according to their major epitopes. Also, frequency results showed that there were dominant EpTs in all flavivirus. Fifteen STs were selected and purified for the expression of recombinant antigen in Escherichia coli by sodium dodecyl sulfate extraction. Our study details a novel in silico approach for the development of flavivirus diagnostics, including a simple way to screen the important peptide regions.
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Gagarina, G. Yu, L. S. Arkhipova, and D. A. Sizova. "Labour Productivity as Indicator of Regional Economy Efficiency." Vestnik of the Plekhanov Russian University of Economics, no. 6 (December 22, 2021): 83–92. http://dx.doi.org/10.21686/2413-2829-2021-6-83-92.
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The interrelation of labour productivity and economic situation in regions of the Russian Federation is really acute in current conditions, when such destructive factors as sanctions, inflation, instability on global markets due to coronavirus epidemic take place. Therefore, the key goal of the research is to estimate labour productivity in regions as a factor of economy efficiency. Among methods of research it is possible to mention comparative analysis of the indicator, typology of regions by a number of parameters in order to identify regional differentiation. It is assumed that the highest labour productivity is typical of raw-materials regions, which specialize on extraction and export of mineral resources. However, we should take into account that natural and climatic factors in this group of regions increase labour costs and therefore, cut labour productivity. The authors show that in regions with conventional specialization on manufacturing industry (when the raw-materials sector retains a certain importance) the said indicator demonstrates a high value, even in spite of some unfavorable trends on labour market. The authors used the following materials and research findings for preparing the article: results of deep interviews of employment service workers in the Ryazan region conducted in 2021 within the frames of the research ‘Digitalization of Labour Market and Employment in Russia: Trends and Mechanisms of Development’; materials of expert discussions and surveys of employment service heads in regions of the Central Federal District within the frames of the research ‘Organizational and Finance Mechanisms to Support Population Employment in 2021-2023, which Aims at Unemployment Reduction’
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Krapp, Fiorella, Catherine Amaro, Karen Ocampo, Lizeth Astocondor, Noemi Hinostroza, Maribel Riveros, and Coralith Garcia. "1189. A Comprehensive Characterization of the Emerging Carbapenem-Resistant Klebsiella pneumoniae Clinical Isolates From a Public Hospital in Lima, Peru." Open Forum Infectious Diseases 5, suppl_1 (November 2018): S359—S360. http://dx.doi.org/10.1093/ofid/ofy210.1022.
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Abstract Background In contrast with other countries in Latin America, Peru had been notoriously spared by the global dissemination of carbapenem-resistant Klebsiella pneumoniae (CR-Kp), until recently. Even though, isolated cases of KPC-producing K. pneumoniae had been reported since 2013, it was not until 2016 that the first outbreak of NDM- producing K. pneumoniae was described in Peru. By 2017, rapid emergence of CR-Kp took place in Hospital Cayetano Heredia (HCH), a tertiary care hospital in Lima. Here, we provide a description of clinical, microbiological and molecular characteristics of CR-Kp isolates recovered at HCH. Methods Retrospective review of all CR-Kp clinical isolates recovered at HCH until December 2017. Antibiotic susceptibility data were obtained during routine care (Vitek or disc diffusion) and was assessed using CLSI breakpoints. DNA extraction was performed by heat shock, and PCR was performed to assess carriage of blaNDM gene. String test was performed to detect hypermucoviscosity. Results The first case of CR-Kp in HCH dated from July 2015. Since then, a total of 69 CR-Kp clinical isolates, from 60 patients have been recovered until December 2017. A significant increase in the number of cases was observed during 2017 (Figure 1). The average age of patients was 55. Urinary, and respiratory sources of infection or colonization were the most common ones (35% and 30%, respectively), followed by blood stream (17%) and intraabdominal (10%) infections. Isolate recovery and DNA extraction was achieved in 40 cases. Of these, 15 (38%) had a positive PCR for blaNDM carbapenemase gene (Figure 2). Antibiotic susceptibility testing revealed that amikacin was the most effective antimicrobial with the rest of antimicrobials having extremely high rates of resistance (Figure 3). String test was positive in two of these isolates, suggesting that hypervirulent CR-KP might be emerging in this region. Conclusion An epidemic of CR-Kp has established in our hospital, representing the first one reported in Peru. The different mechanisms of carbapenem resistance found suggest a polyclonal expansion. Amikacin remains the only active antimicrobial within the routinely tested antibiotics, highlighting the need to add other antimicrobials to the routine panel. Disclosures All authors: No reported disclosures.
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Kahlig, Pascal, Andreas Neumayr, and Daniel H. Paris. "Louse-borne relapsing fever—A systematic review and analysis of the literature: Part 2—Mortality, Jarisch–Herxheimer reaction, impact on pregnancy." PLOS Neglected Tropical Diseases 15, no. 3 (March 11, 2021): e0008656. http://dx.doi.org/10.1371/journal.pntd.0008656.
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Louse-borne relapsing fever (LBRF) is a classical epidemic disease, which in the past was associated with war, famine, poverty, forced migration, and crowding under poor hygienic conditions around the world. The disease’s causative pathogen, the spirochete bacterium Borrelia recurrentis, is confined to humans and transmitted by a single vector, the human body louse Pediculus humanus corporis. Since the disease was at its peak before the days of modern medicine, many of its aspects have never been formally studied and to date remain incompletely understood. In order to shed light on some of these aspects, we have systematically reviewed the accessible literature on LBRF since the recognition of its mode of transmission in 1907, and summarized the existing data on mortality, Jarisch–Herxheimer reaction (JHR), and impact on pregnancy. Publications were identified by using a predefined search strategy of electronic databases and a subsequent review of the reference lists of the obtained publications. All publications reporting patients with a confirmed diagnosis of LBRF published in English, French, German, and Spanish since 1907 were included. Data extraction followed a predefined protocol and included a grading system to judge the certainty of the diagnosis of reported cases. The high mortality rates often found in literature are confined to extreme scenarios. The case fatality rate (CFR) of untreated cases is on average significantly lower than frequently assumed. In recent years, a rise in the overall CFRs is documented, for which reasons remain unknown. Lacking standardized criteria, a clear diagnostic threshold defining antibiotic treatment-induced JHR does not exist. This explains the wide range of occurrence rates found in literature. Pre-antibiotic era data suggest the existence of a JHR-like reaction also in cases treated with arsenicals and even in untreated cases. LBRF-related adverse outcomes are observed in 3 out of 4 pregnancies.
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Barbuddhe, Sukhadeo B., Thomas Maier, Gerold Schwarz, Markus Kostrzewa, Herbert Hof, Eugen Domann, Trinad Chakraborty, and Torsten Hain. "Rapid Identification and Typing of Listeria Species by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry." Applied and Environmental Microbiology 74, no. 17 (July 7, 2008): 5402–7. http://dx.doi.org/10.1128/aem.02689-07.
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ABSTRACT Listeria monocytogenes is a food-borne pathogen that is the causative agent of human listeriosis, an opportunistic infection that primarily infects pregnant women and immunologically compromised individuals. Rapid, accurate discrimination between Listeria strains is essential for appropriate therapeutic management and timely intervention for infection control. A rapid method involving matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) that shows promise for identification of Listeria species and typing and even allows for differentiation at the level of clonal lineages among pathogenic strains of L. monocytogenes is presented. A total of 146 strains of different Listeria species and serotypes as well as clinical isolates were analyzed. The method was compared with the pulsed-field gel electrophoresis analysis of 48 Listeria strains comprising L. monocytogenes strains isolated from food-borne epidemics and sporadic cases, isolates representing different serotypes, and a number of Listeria strains whose genomes have been completely sequenced. Following a short inactivation/extraction procedure, cell material from a bacterial colony was deposited on a sample target, dried, overlaid with a matrix necessary for the MALDI process, and analyzed by MALDI-TOF MS. This technique examines the chemistry of major proteins, yielding profile spectra consisting of a series of peaks, a characteristic “fingerprint” mainly derived from ribosomal proteins. Specimens can be prepared in a few minutes from plate or liquid cultures, and a spectrum can be obtained within 1 minute. Mass spectra derived from Listeria isolates showed characteristic peaks, conserved at both the species and lineage levels. MALDI-TOF MS fingerprinting may have potential for Listeria identification and subtyping and may improve infection control measures.
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Riaz, Irbaz Bin, Huan He, Alexander J. Ryu, Rabbia Siddiqi, Syed Arsalan Ahmed Naqvi, Yuan Yao, Muhammad Husnain, et al. "A framework for living evidence synthesis in cancer: Living, interactive network meta-analysis for first-line treatment of metastatic renal cell carcinoma (mRCC)." Journal of Clinical Oncology 39, no. 6_suppl (February 20, 2021): 335. http://dx.doi.org/10.1200/jco.2021.39.6_suppl.335.
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335 Background: Systematic reviews are outdated quickly when the evidence is rapidly evolving as the process is laborious and there is little incentive for primary author team of an index SRMA to update the evidence. Consequently, there is an epidemic of redundant SRMAs performed by different teams—sometimes with conflicted results—for treatment of first line mRCC. Methods: We have created a living, interactive systematic review (LISR)and network meta-analysis(LINMA) for the treatment of first line mRCC using an Artificial intelligence (AI) assisted framework for evidence synthesis (Living, Interactive evidence synthesis framework) (LIvE) . The framework is implemented in five-layered architecture (application layer, shared module layer, core service layer, middleware layer, and storage layer) which work together to automate the identification of new studies and analysis and semi-automate the screening and data extraction. Dynamic features such as interactive tables, figures and evidence maps are enabled using Python and JavaScript programming languages. Results: We have maintained a living, interactive evidence profile for the first line treatment mRCC since September 2019 ( LIVING WEBSITE) . Living search strategy identifies new studies as they become available. As of October 13, 2020 LISR, includes data 14 clinical trials ( PRISMA ). Baseline characteristics are summarized in an interactive table ( TABLE) . Cabozantinib& Nivolumab (Cabo-Nivo) is the highest ranked drug for improving Overall Response (OR), Progression Free Survival (PFS) and Overall Survival (OS) whereas Ipilimumab in combination with Nivolumab (Ipi-Nivo) is highest ranked drug for achieving complete response (CR). Ipi-Nivo and Atezolizumab & Bevacizumab (Ate-Bev) ranked highest and Cabo-Nivo ranked lowest for treatment related Adverse events (TRAEs). Results of network meta-analysis are summarized as interactive tables and plots ( NMA ), summary of findings tables ( MULTIPLE COMAPRISONS ) and evidence maps ( MAP ). Conclusions: LISRs can potentially reduce redundancy, increase transparency, reproducibility, enable shared-decision making (at a guideline level, or in a patient-clinician dyad) and support living guidelines.
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Ekhtiari, Seper, Ibrahim Yusuf, Yosra AlMakadma, Austin MacDonald, Timothy Leroux, and Moin Khan. "Opioid Use in Athletes: A Systematic Review." Sports Health: A Multidisciplinary Approach 12, no. 6 (August 6, 2020): 534–39. http://dx.doi.org/10.1177/1941738120933542.
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Context: The opioid epidemic has been well-documented in the general population, but the literature pertaining to opioid use and misuse in the athletic population remains limited. Objectives: The objectives of this study were to seek answers to the following questions: (1) what are the rates of opioid use and misuse among athletes, (2) do these rates differ compared with the nonathletic population, and (3) are there specific subgroups of the athletic population (eg, based on sport, level of play) who may be at higher risk? Data Sources: The Embase, MEDLINE, and PubMed were used for the literature search. Study Selection: Records were screened in duplicate for studies reporting rates of opioid use among athletes. All study designs were included. Study Design: Systematic review. Level of Evidence: Level 4. Data Extraction: Data regarding rates of opioid use, medication types, prescription patterns, and predictors of future opioid use were collected. Study quality was assessed using the Methodological Index for Non-Randomized Studies (MINORS) criteria for clinical studies and 5 key domains previously identified for survey studies. Results: A total of 11 studies were eligible for inclusion (N = 226,256 athletes). Studies included survey studies and retrospective observational designs. Opioid use among professional athletes at any given time, as reported in 2 different studies, ranged from 4.4% to 4.7%, while opioid use over a National Football League career was 52%. High school athletes had lifetime opioid use rates of 28% to 46%. Risk factors associated with opioid use included Caucasian race, contact sports (hockey, football, wrestling), postretirement unemployment, and undiagnosed concussion. Use of opioids while playing predicted use of opioids in retirement. Conclusion: Overall, opioid use is prevalent among athletes, and use during a playing career predicts postretirement use. This issue exists even at the high school level, with similar rates to professional athletes. Further higher quality observational studies are needed to better define patterns of opioid use in athletes.
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Chiavaroli, Laura, Cyril W. C. Kendall, Catherine R. Braunstein, Sonia Blanco Mejia, Lawrence A. Leiter, David J. A. Jenkins, and John L. Sievenpiper. "Effect of pasta in the context of low-glycaemic index dietary patterns on body weight and markers of adiposity: a systematic review and meta-analysis of randomised controlled trials in adults." BMJ Open 8, no. 3 (March 2018): e019438. http://dx.doi.org/10.1136/bmjopen-2017-019438.
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ObjectiveCarbohydrate staples such as pasta have been implicated in the obesity epidemic. It is unclear whether pasta contributes to weight gain or like other low-glycaemic index (GI) foods contributes to weight loss. We synthesised the evidence of the effect of pasta on measures of adiposity.DesignSystematic review and meta-analysis using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.Data sourcesMEDLINE, Embase, CINAHL and the Cochrane Library were searched through 7 February 2017.Eligibility criteria for selecting studiesWe included randomised controlled trials ≥3 weeks assessing the effect of pasta alone or in the context of low-GI dietary patterns on measures of global (body weight, body mass index (BMI), body fat) and regional (waist circumference (WC), waist-to-hip ratio (WHR), sagittal abdominal diameter (SAD)) adiposity in adults.Data extraction and synthesisTwo independent reviewers extracted data and assessed risk of bias. Data were pooled using the generic inverse-variance method and expressed as mean differences (MDs) with 95% CIs. Heterogeneity was assessed (Cochran Q statistic) and quantified (I2statistic). GRADE assessed the certainty of the evidence.ResultsWe identified no trial comparisons of the effect of pasta alone and 32 trial comparisons (n=2448 participants) of the effect of pasta in the context of low-GI dietary patterns. Pasta in the context of low-GI dietary patterns significantly reduced body weight (MD=−0.63 kg; 95% CI −0.84 to –0.42 kg) and BMI (MD=−0.26 kg/m2; 95% CI −0.36 to –0.16 kg/m2) compared with higher-GI dietary patterns. There was no effect on other measures of adiposity. The certainty of the evidence was graded as moderate for body weight, BMI, WHR and SAD and low for WC and body fat.ConclusionsPasta in the context of low-GI dietary patterns does not adversely affect adiposity and even reduces body weight and BMI compared with higher-GI dietary patterns. Future trials should assess the effect of pasta in the context of other ‘healthy’ dietary patterns.Trial registration numberNCT02961088; Results.
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Adeoye, Abiodun Moshood, Oladimeji Adebayo, Busayo Abiola, Bamidele Iwalokun, Bamidele Tayo, Fadi Charchar, Akinlolu Ojo, and Richard Cooper. "The Association Between Selected Molecular Biomarkers and Ambulatory Blood Pressure Patterns in African Chronic Kidney Disease and Hypertensive Patients Compared With Normotensive Controls: Protocol for a Longitudinal Study." JMIR Research Protocols 9, no. 1 (January 17, 2020): e14820. http://dx.doi.org/10.2196/14820.
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Background Chronic kidney disease (CKD) is a burgeoning epidemic in sub-Saharan Africa. Abnormal blood pressure variations are prevalent in CKD and potentiate the risk of cardiovascular morbidity and mortality. Certain genetic variants (angiotensin II receptor type 1 1166 A>C and angiotensin-converting enzyme insertion and deletion polymorphisms) and biomarkers such as interleukin–6, tumor necrosis factor, soluble (s) E-selectin, homocysteine, and highly sensitive C-reactive protein have been shown to affect blood pressure variability among non-African CKD, hypertensive. and nonhypertensive CKD population. However, the contributions of the pattern, genetic, and environmental determinants of ambulatory blood pressure in African CKD have not been characterized. Understanding these interactions may help to develop interventions to prevent major cardiovascular events among people with CKD. Objective The overarching objective of this study is to identify, document, and develop approaches to address related phenomic, genetic, and environmental determinants of ambulatory blood pressure patterns in African CKD and non-CKD hypertensive patients compared with normotensive controls. Methods This is a longitudinal short-term follow-up study of 200 adult subjects with CKD and 200 each of age-matched hypertensives without CKD and apparently healthy controls. Demographic information, detailed clinical profile, electrocardiography, echocardiography, and 24-hr ambulatory blood pressure measurements will be obtained. Blood samples will be collected to determine albumin-creatinine ratio, fasting plasma glucose, lipid profile, electrolytes, urea and creatinine, C-reactive protein, serum homocysteine, fibroblast growth factor–23, and complete blood count, while 2 mL blood aliquot will be collected in EDTA (ethylenediaminetetraacetic acid) tubes and mixed using an electronic rolling system to prevent blood clots and subsequently used for DNA extraction and genetic analysis. Results A total of 239 participants have been recruited so far, and it is expected that the recruitment phase will be complete in June 2020. The follow-up phase will continue with data analysis and publications of results. Conclusions This study will help stratify Nigerian CKD patients phenotypically and genotypically in terms of their blood pressure variations with implications for targeted interventions and timing of medications to improve prognosis. International Registered Report Identifier (IRRID) DERR1-10.2196/14820
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Andrienko, Natalia, Gennady Andrienko, Siming Chen, Dirk Burghardt, Alexander Dunkel, and Ross Purves. "Geovisual analysis of VGI for understanding people's behaviour in relation to multifaceted context." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-10-2019.
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<p><strong>Abstract.</strong> Volunteered Geographic Information (VGI) in the form of actively and passively generated spatial content offers extensive potential for a wide range of applications. Realising this potential however requires methods which take account of the specific properties of such data, for example its heterogeneity, quality, subjectivity, spatial resolution and temporal relevance. The creation and production of such content through social media platforms is an expressive aspect of human behaviour, and as such influenced strongly by the co-occurrence of events and context external to the social media. In this project we are developing geovisual analysis methods which show how actors interact in location based social media (LBSM), and how their interactions influence, and are influenced by, their physical and social environment and relations.</p><p>In the first phase of the project, we developed and demonstrated a conceptual model enabling the extraction, analysis and visualisation of events and reactions to events in LBSM. A central element of this model and its implementation is the integration of spatial, temporal, thematic and social dimensions, or <i>facets</i>, combined with an explicit link between events and reactions. We have developed a conceptual model of collective reactions in LBSM [1] which includes a task matrix underpinning our methodological efforts. A key output of this conceptual model, and the resulting task matrix was the acknowledgement of the importance of exploring multiple dimensions in LBSM reactions to events, namely the spatial, temporal, thematic and social which relate to where, when, what and who questions which can be posed of such data.</p><p>The conceptual model formed a basis for our research on bridging the gap between visually-driven analysis and visual communication, or story telling [2]. Findings and results of the analysis often need to be communicated to an audience that lacks expertise in visualization and analysis methods. This requires analysis outcomes to be presented in simpler ways than that are typically used in analysis supporting systems. Not only analytical visualizations may be too complex for target audiences but also the information that needs to be presented. Analysis results may consist of multiple components, which may involve multiple heterogeneous facets. Hence, there exists a gap on the path from obtaining analysis findings to communicating them, within which two main challenges lie: information complexity and display complexity. We address this problem by proposing a general framework for story synthesis, in which the analyst creates and organises story contents from analysis results. Story synthesis includes selecting and assembling findings and arranging them in meaningful layouts that take into account the structure of information and inherent properties of its components (facets). Paper [2] proposes a facet-based generic framework for story synthesis which can be applied to different kinds of VGI and LBSM data.</p><p>To introduce our concepts, we use an example based on the IEEE VAST Challenge 2011 [3], requiring analysis of the circumstances of an epidemic outbreak in a fictive city Vastopolis. The data are geographically referenced microblog messages, some of which include keywords indicating disease symptoms, such as fever, chills, sweats, aches and pains, coughing, etc. The time span of the data is 3 weeks. An analyst needs to find out when and where the outbreak started and how it developed. The analyst uses a visual analytics system providing multiple types of interactive visual displays and supporting database queries and data transformations. Fig.1 shows how analysis artefacts are managed. In the course of the analysis, the analyst has obtained a set of findings (labelled F1-F5), which include the outbreak start time, the spatial clusters and the times of their existence, the differing sets of frequent keywords associated with the clusters, the location and time of the truck crash, and the ways of spreading and temporal development of two diseases. As the next natural step, these findings need to be communicated to any interested audience, but not as disjoint information pieces but as an integrated story. The pieces need to be arranged in appropriate ways revealing the relationships between the information pieces, such as temporal and spatial relationships. Figures 1C and 1D show examples of arrangements that might be created by the VAST Challenge analyst for conveying temporal and spatial relationships between the findings. Another kind of relationship the analyst may wish to reflect is the differences between the symptoms of two diseases that were discovered in the course of the analysis. For this purpose, the analyst may juxtapose the lists of the keywords corresponding to the central-eastern and south-western clusters. Analysts should be able to create and edit such arrangements in order to construct understandable and interesting stories.</p><p>A process of story synthesis includes the following activities: aggregate and summarize (as a means of simplification and achieving a desired level of detail), embed details (enable drilling down into aggregates), arrange (put information pieces in a meaningful layout), show facets (exhibit information structure), and annotate (include explanations and comments). Information facets play an important role in story synthesis. They need to be presented to story recipients to enable proper understanding of information. However, heterogeneous facets, such as space, time, population, semantics of message texts (represented by keywords or topics), etc. may be hard to present simultaneously while keeping the display simple and easy to understand and avoiding information overload. Such facets may be represented in complementary views providing different perspectives on the information. The task matrix introduced in paper [1] suggests taking into account only two facets at once. Inherent properties of information facets can be used for meaningful arrangement of story slices and for aggregation. Thus, temporal and spatial arrangements, as in Fig.1 (C, D), exploit the inherent properties of time (temporal ordering and distances) and space (spatial distances, neighbourhood, and relative directions). Paper [2] describes an example of analysing expressions of people’s reactions to political events and processes, such as the Brexit, in LBSM and organizing analysis findings in stories with the use of various facet-based layouts.</p><p>In the further work, we extend the research scope to studying reactions as a component of behaviour (along with human activities and emotions), incorporating external social and physical context to better allow events to be related and compared. This will not only include development of new analysis methods and workflows but also definition of new analysis tasks and, respectively, new types of analytical results. These extensions will require further work on finding, on the one hand, effective representations for analytical visualizations, on the other hand, expressive and easily understandable representations for communication of analysis findings. Besides, a general problem to be tackled is how to incorporate analyst’s input, such as background knowledge and context information that is not reflected in available data, in both analytical visualizations and stories presenting analysis results. It would be interesting to go beyond mere use of textual annotations towards representing such inputs in a visual form, which needs to be distinguishable from the representation of the data.</p>
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Liao, Zenghua, Zongqiang Yang, Peixin Huang, Ning Pang, and Xiang Zhao. "Multi-Model Fusion-Based Hierarchical Extraction for Chinese Epidemic Event." Data Science and Engineering, January 2, 2023. http://dx.doi.org/10.1007/s41019-022-00203-6.
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AbstractIn recent years, Coronavirus disease 2019 (COVID-19) has become a global epidemic, and some efforts have been devoted to tracking and controlling its spread. Extracting structured knowledge from involved epidemic case reports can inform the surveillance system, which is important for controlling the spread of outbreaks. Therefore, in this paper, we focus on the task of Chinese epidemic event extraction (EE), which is defined as the detection of epidemic-related events and corresponding arguments in the texts of epidemic case reports. To facilitate the research of this task, we first define the epidemic-related event types and argument roles. Then we manually annotate a Chinese COVID-19 epidemic dataset, named COVID-19 Case Report (CCR). We also propose a novel hierarchical EE architecture, named multi-model fusion-based hierarchical event extraction (MFHEE). In MFHEE, we introduce a multi-model fusion strategy to tackle the issue of recognition bias of previous EE models. The experimental results on CCR dataset show that our method can effectively extract epidemic events and outperforms other baselines on this dataset. The comparative experiments results on other generic datasets show that our method has good scalability and portability. The ablation studies also show that the proposed hierarchical structure and multi-model fusion strategy contribute to the precision of our model.
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Afyouni, Imad, Aamir Khan, and Zaher Al Aghbari. "Deep-Eware: spatio-temporal social event detection using a hybrid learning model." Journal of Big Data 9, no. 1 (June 28, 2022). http://dx.doi.org/10.1186/s40537-022-00636-w.
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AbstractEvent detection from social media aims at extracting specific or generic unusual happenings, such as, family reunions, earthquakes, and disease outbreaks, among others. This paper introduces a new perspective for the hybrid extraction and clustering of social events from big social data streams. We rely on a hybrid learning model, where supervised deep learning is used for feature extraction and topic classification, whereas unsupervised spatial clustering is employed to determine the event whereabouts. We present ‘Deep-Eware’, a scalable and efficient event-aware big data platform that integrates data stream and geospatial processing tools for the hybrid extraction and dissemination of spatio-temporal events. We introduce a pure incremental approach for event discovery, by developing unsupervised machine learning and NLP algorithms and by computing events’ lifetime and spatial spanning. The system integrates a semantic keyword generation tool using KeyBERT for dataset preparation. Event classification is performed using CNN and bidirectional LSTM, while hierarchical density-based spatial clustering was used for location-inference of events. We conduct experiments over Twitter datasets to measure the effectiveness and efficiency of our system. The results demonstrate that this hybrid approach for spatio-temporal event extraction has a major advantage for real-time spatio-temporal event detection and tracking from social media. This leads to the development of unparalleled smart city applications, such as event-enriched trip planning, epidemic disease evolution, and proactive emergency management services.
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Moreau, Nicolas, Melissa Roy, Andrew Wilson, and Laetitia Atlani Duault. "“Life is more important than football”: Comparative analysis of Tweets and Facebook comments regarding the cancellation of the 2015 African Cup of Nations in Morocco." International Review for the Sociology of Sport, January 20, 2020, 101269021989961. http://dx.doi.org/10.1177/1012690219899610.
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This study analyzes comments from two major social media, Facebook and Twitter, regarding the controversial cancellation of the 2015 African Cup of Nations (CAN) in Morocco and its transfer to Equatorial Guinea, a move precipitated by the contemporaneous outbreaks of Ebola in West Africa. Using frame analysis methodology (frames being the central ideas structuring a narrative account of an issue, event or controversy), it investigates how the sporting and health worlds are understood and conceptualized on Twitter and Facebook, in the context of a specific event. We also investigated the extent to which these frames are platform-specific. Data were collected by keyword extraction and submitted to a qualitative thematic and frame analysis, from which we identified six frames (Epidemic management, Sporting event, Political, Skepticism, Religion, and Economic). Analysis of these frames identified a number of classic issues from the sociology of not only football and epidemics but also of African political issues. The cancellation of the CAN thus provides an excellent window into the complex links between sport, heath and politics. Indeed, the online comments of social media users expressed a rich range of pre-existing frustrations, beliefs and political positions. Our results show that, in the context of the cancellation of the 2015 CAN, tweets mostly framed the event as an epidemic management issue, while Facebook comments typically framed it as an epidemic management, sporting and political event. Some themes treated in a factual way on Twitter became politicized on Facebook where, in addition, new political themes emerged. We conclude that studying social media conversations relating to a mega-sporting event could provide sociologically valuable insights about topics not typically directly associated with sport or health.
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Sun, Jingjing, Ziming Zeng, Tingting Li, and Shouqiang Sun. "Analyzing the spatiotemporal coupling relationship between public opinion and the epidemic during COVID-19." Library Hi Tech, June 22, 2023. http://dx.doi.org/10.1108/lht-10-2022-0462.
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PurposeThe outbreak of COVID-19 has become a major public health emergency worldwide. How to effectively guide public opinion and implement precise prevention and control is a hot topic in current research. Mining the spatiotemporal coupling between online public opinion and offline epidemics can provide decision support for the precise management and control of future emergencies.Design/methodology/approachThis study focuses on analyzing the spatiotemporal coupling relationship between public opinion and the epidemic. First, based on Weibo information and confirmed case information, a field framework is constructed using field theory. Second, SnowNLP is used for sentiment mining and LDA is utilized for topic extraction to analyze the topic evolution and the sentiment evolution of public opinion in each coupling stage. Finally, the spatial model is used to explore the coupling relationship between public opinion and the epidemic in space.FindingsThe findings show that there is a certain coupling between online public opinion sentiment and offline epidemics, with a significant coupling relationship in the time dimension, while there is no remarkable coupling relationship in space. In addition, the core topics of public concern are different at different coupling stages.Originality/valueThis study deeply explores the spatiotemporal coupling relationship between online public opinion and offline epidemics, adding a new research perspective to related research. The result can help the government and relevant departments understand the dynamic development of epidemic events and achieve precise control while mastering the dynamics of online public opinion.
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Bertasi, B., E. Galuppini, M. Tilola, L. Mangeri, F. Meletti, F. Righi, A. Scarazzato, E. Pavoni, and MN Losio. "Monitoring of SARS-CoV 2 on primary production and manually processed foods in Northern Italy." European Journal of Public Health 31, Supplement_3 (October 1, 2021). http://dx.doi.org/10.1093/eurpub/ckab165.235.
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Abstract Background SARS CoV2 pandemic has generated interest in research of virus spread sources, apart from human contagion. In particular different studies are performed to understand surfaces involvement; during the epidemic event, different types of studies on surfaces have been performed. However, there is little information regarding the presence of the virus in food; wastewater contamination and poor hygiene practices could be the sources of viral contamination in handled food products. The aim of this work was to analyze different types of food for Sars CoV 2 presence. Methods 390 samples of molluscs, 353 vegetables, 10 meat, 72 water, 169 berries, 16 seafood products and ready-to-eat dishes were analysed (2020-2021). Samples were selected from those provided for routine analysis during the pandemic period. The preparation was done based on ISO 15216-2 indications, followed by extraction with Nuclisense®Minimag® system; real-time PCR was applied to detect the Sars CoV2 virus Open Reading Frame 1ab, with two different master mixes. Results All samples tested were negative for ORF1ab detection. Many hypothesis can be made about negative Results: it could be possible that contamination levels in water, or on surfaces in contact with food, are too low to generate a detection signal; again, handling practices may be sufficient to avoid the transmission of the virus to food. Otherwise, the selected genetic target and the Real-time PCR performed, could have been not so efficient in detecting virus as expected. Conclusions In this preliminary work, food does not seem to be a substrate for Sars CoV2 contamination; other food categories or transformation/production processes could be investigated to confirm the obtained results. Also, different targets and amplification systems would have to be evaluated to verify the rule of foodstuffs as Sars CoV2 vehicles. Key messages Primary production and manual processed food don't seem to be at risk for SARS CoV2 contamination. Food has not been identified as a source of Sars CoV2 spreading.
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Tariq, Hisham, David Emes, Yebeen Boo, Alexander Light, Zia Sadique, Mishal Sameer Khan, Alan D. Knight, Osman Dar, and Logan Manikam. "Economic impact of Ebola virus disease outbreak on an extractive firm: a case study." UCL Open Environment 2, no. 1 (May 13, 2020). http://dx.doi.org/10.14324/111.444/ucloe.000007.
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The recent Ebola virus disease (EVD) epidemic was one of the most severe public health emergencies in modern times. The economic impact of epidemics has mostly been analysed at the macroeconomic level. Conversely, we aimed to estimate the economic costs of preventive measures of the epidemic to an extractive firm, ArcelorMittal (AM), using data in the epidemic region from March 2014 to December 2015. AM is the world’s largest steel producer and is particularly important in West Africa, where the extractive industry is economically crucial. Qualitative methods, in-depth interviews (IDIs) and focus group discussions (FGDs), were used to investigate the events and channels of impact of the epidemic on the firm, as perceived by employees and contractors. Quantitative data regarding these costs were also collected. Retrospective cost analysis estimated the actual cost of preventive methods adopted. Most respondents indicated the largest cost impact was suspension of the Phase II expansion, a series of projects designed to increase iron ore production in Liberia. The next largest cost was the preventive measures adopted to counter disease spread. Total costs incurred for adopting preventive measures were USD 10.58–11.11 million. The overall direct costs of preventive measures adopted within the fence, meaning within the physical boundary of the firm’s sites, shared 30–31% of the total costs incurred. The share of external donations supporting humanitarian response was 11–12% of the total costs, followed by 7–12% of relational costs. The firm’s response during the EVD epidemic focussed on its employees and operations, which was later expanded to the wider community and then in supporting the international humanitarian response.
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Remde, Alan, Stephen N. DeTurk, A. Almardini, Lauren Steiner, and Thomas Wojda. "Plant-predominant eating patterns – how effective are they for treating obesity and related cardiometabolic health outcomes? – a systematic review." Nutrition Reviews, September 8, 2021. http://dx.doi.org/10.1093/nutrit/nuab060.
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Abstract Context The obesity epidemic is a main driver of the chronic disease epidemic; however, present treatment approaches have suboptimal efficacy. Objectives To assess the efficacy of plant-predominant (vegan, vegetarian, plant-based whole foods [PBWFs]) diets in treating obesity and its main cardiometabolic sequelae: hyperlipidemia (HLD); indices of insulin resistance, glycemic control, and diabetes mellitus type 2 (DM2); and cardiovascular disease (CVD), including hypertension (HTN). Data Sources A systematic search of multiple databases was conducted for articles published between November 2019 and February 2020; databases searched included: PubMed, Medline (Ovid), Cochrane, CENTRAL, and CINAHL. Data Extraction and Analysis All interventional trials (randomized controlled trials [RCTs] and trials of non-randomized experimental design) that met the inclusion criteria (English language, duration of at least 4 weeks, primary end point congruent with above objectives, no major flaws in research design that would prevent interpretation) were included in the review. A total of 3135 articles were scanned and 84 were selected. The articles were collated and summarized in 2 evidence tables. Risk of bias for RCTs was assessed using the Cochrane Risk-of-Bias tool 2 as a guide. For non-randomized trials, higher risk of bias was assumed, and the JBI Critical Appraisal tool was used as a guide to determine inclusion. Results Plant-based diets, in general, demonstrated improved weight control and cardiometabolic outcomes related to lipids, cardiovascular end points, blood pressure, insulin sensitivity, A1C, and fasting glucose, and a lower risk of diabetes compared with usual diets and in some cases standard health-oriented diets such as the American Heart Association (AHA), American Diabetic Association (ADA), and Mediterranean diets. Preliminary studies suggest plant-predominant diets practiced as part of healthy lifestyle interventions may stabilize or even reverse DM 2 and CVD. The acceptability and sustainability of plant-predominant diets where measured were generally similar to other health-oriented diets. Conclusion Plant-predominant diets can play a major role in reversing the obesity and chronic disease epidemics. In the setting of sustained lifestyle intervention programs, they may arrest or even reverse DM2 and CVD. Further higher-level RCTs are needed to confirm and expand on these findings.
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Shi, Wen-zhong, Fanxin Zeng, Anshu Zhang, Chengzhuo Tong, Xiaoqi Shen, Zhewei Liu, and Zhicheng Shi. "Online public opinion during the first epidemic wave of COVID-19 in China based on Weibo data." Humanities and Social Sciences Communications 9, no. 1 (May 6, 2022). http://dx.doi.org/10.1057/s41599-022-01181-w.
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AbstractAs COVID-19 spread around the world, epidemic prevention and control policies have been adopted by many countries. This process has prompted online social platforms to become important channels to enable people to socialize and exchange information. The massive use of social media data mining techniques, to analyze the development online of public opinion during the epidemic, is of great significance in relation to the management of public opinion. This paper presents a study that aims to analyze the developmental course of online public opinion in terms of fine-grained emotions presented during the COVID-19 epidemic in China. It is based on more than 45 million Weibo posts during the period from December 1, 2019 to April 30, 2020. A text emotion extraction method based on a dictionary of emotional ontology has been developed. The results show, for example, that a high emotional effect is observed during holidays, such as New Year. As revealed by Internet users, the outbreak of the COVID-19 epidemic and its rapid spread, over a comparatively short period of time, triggered a sharp rise in the emotion “fear”. This phenomenon was noted especially in Wuhan and the immediate surrounding areas. Over the initial 2 months, although this “fear” gradually declined, it remained significantly higher than the more common level of uncertainty that existed during the epidemic’s initial developmental era. Simultaneously, in the main city clusters, the response to the COVID-19 epidemic in central cities, was stronger than that in neighboring cities, in terms of the above emotion. The topics of Weibo posts, the corresponding emotions, and the analysis conclusions can provide auxiliary reference materials for the monitoring of network public opinion under similar major public events.
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Lu, Zuqin. "Analysis model of college students' mental health based on online community topic mining and emotion analysis in novel coronavirus epidemic situation." Frontiers in Public Health 10 (September 13, 2022). http://dx.doi.org/10.3389/fpubh.2022.1000313.
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Under the epidemic situation of COVID-19, university students have different levels of anxiety, depression, and other psychological problems, and these differing levels present different challenges. Therefore, universities and relevant departments should carry out accurate psychological health education for university students. Through research, this paper found that students' psychological problems during the COVID-19 epidemic were mainly reflected in four aspects: depression, interpersonal relationship, sleep and eating disorders, and compulsive behavior. Through the discussion of family of origin, self-awareness and motivation attribution, and social pressure, this paper analyzed the causes of psychological problems. The information resources of the network are usually unstructured data, and the text information, as the most typical unstructured data, occupies a large proportion. Moreover, this text information often contains users' emotional response to major events. In this paper, a data preprocessing system is designed, and three data preprocessing rules are defined: expression data conversion rules, data deduplication rules and invalid data cleaning rules. The characteristics of online community text data are analyzed, and the text feature extraction method is selected according to its characteristics. The results of this study show that the proportion of university students with psychological problems is about 23%, which is slightly higher than the research results during the non-epidemic period. This paper suggests that college students should master methods of self-regulation, improve their levels of physical exercise, improve their physical fitness, and establish and improve their defense mechanisms to alleviate psychological conflicts and pressures.
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Mohammad, Abdolghani Abdollahi, and Mohammad Reza Firouzkouhi. "Qualitative Research in COVID 19 Pandemic." Journal of Shahid Sadoughi University of Medical Sciences, April 26, 2021. http://dx.doi.org/10.18502/ssu.v29i2.6083.
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Introduction: Quantitative research is not suitable for COVID pandemic research because it does not cover the social consequences of qualitative research. COVID 19 is a social event that is important because of the disruption of the natural order of society. To defeat the disease, social interaction is needed, so qualitative research is appropriate to find the challenges and experiences of society. Therefore, due to the inconsistency of people's health behaviors with epidemiological models, people's vulnerability in epidemics, unexpected consequences or surprising results, extracting participants' experiences from medical procedures and revealing flexibility in the face of social problems, the use of qualitative research in this pandemic that will be important.
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O’Reilly, A., M. Tibbs, A. Booth, E. Doyle, B. McKeague, and J. Moore. "A rapid review investigating the potential impact of a pandemic on the mental health of young people aged 12–25 years." Irish Journal of Psychological Medicine, September 11, 2020, 1–16. http://dx.doi.org/10.1017/ipm.2020.106.
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Abstract Objectives: In March 2020, the World Health Organization (WHO) officially declared the spread of coronavirus disease 2019 (COVID-19) as a pandemic. Adolescence and early adulthood are peak times for the onset of mental health difficulties. Exposure to a pandemic during this vulnerable developmental period places young people at significant risk of negative psychological experiences. The objective of this research was to summarise existing evidence on the potential impact of a pandemic on the mental health of 12–25 year olds. Methods: A rapid review of the published peer-reviewed literature, published between 1985 and 2020, using PsycINFO (Proquest) and Medline (Proquest) was conducted. Narrative synthesis was used across studies to identify key themes and concepts. Results: This review found 3,359 papers, which was reduced to 12 papers for data extraction. Results regarding the prevalence of psychological difficulties in youth were mixed, with some studies finding this group experience heightened distress during an infectious disease outbreak, and others finding no age differences or higher distress among adults. Gender, coping, self-reported physical health and adoption of precautionary measures appear to play a role in moderating the psychological impact of an infectious disease outbreak. Most studies were conducted after the peak of an epidemic/pandemic or in the recovery period. Conclusions: More longitudinal research with young people, particularly adolescents in the general population, before and during the early stages of an infectious disease outbreak is needed to obtain a clear understanding of how best to support young people during these events.
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Shenge, Juliet A., Robert K. Obi, and Kayode M. Salawu. "Assessment of Antiviral Activity of Curcuma longa on Two RNA Viruses." Nigerian Journal of Pure and Applied Sciences, May 2, 2021, 3915–28. http://dx.doi.org/10.48198/njpas/20.b21.
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Major pandemics and seasonal epidemics that have ravaged the world in the past and even at present, are mostly caused by RNA viruses. This has necessitated the need for continuous research to identify important natural products, with antiviral potentials, which can be harnessed for use in the prevention and treatment of viral infections. This study therefore, evaluated the antiviral property of Curcuma longa on two important RNA viruses of public health importance, namely polio and measles viruses. Extraction of active ingredients from turmeric rhizomes was done with the use of Analar grade methanol and concentrated using rotary evaporator. Polio and measles viruses were isolated from their respective vaccines using Reed-Muench method. Infective doses of the viruses and toxicity profile of extract were determined. Confluent Vero cells were inoculated with the viruses at different dilutions of the extract, incubated and observed for 7 days. Methanol extract of Curcuma longa inhibited polio virus at the maximum non-toxic concentration (MNTC) of 0.031μg μL-1 and inhibitory concentration (IC50) of 0.067 μg μL-1 with selectivity index of 2.16. Inhibition by the extract was observed prior to infection with the viruses. Phytochemical analysis of the extract showed presence of terpenes, saponins, alkaloids, flavonoids, tannins, cardiac glycosides and phenol as the bioactive phytochemicals. This study has shown that curcuma longa has potent inhibitory activity, hence can be harnessed in the development of an effective antiviral agent against polio and measles viruses.
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Ji, Cong, and Junbin Shao. "Shine: A novel strategy to extract specific, sensitive and well-conserved biomarkers from massive microbial genomic datasets." BMC Bioinformatics 24, no. 1 (April 4, 2023). http://dx.doi.org/10.1186/s12859-023-05195-2.
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Abstract Background Concentrations of the pathogenic microorganisms’ DNA in biological samples are typically low. Therefore, DNA diagnostics of common infections are costly, rarely accurate, and challenging. Limited by failing to cover updated epidemic testing samples, computational services are difficult to implement in clinical applications without complex customized settings. Furthermore, the combined biomarkers used to maintain high conservation may not be cost effective and could cause several experimental errors in many clinical settings. Given the limitations of recent developed technology, 16S rRNA is too conserved to distinguish closely related species, and mosaic plasmids are not effective as well because of their uneven distribution across prokaryotic taxa. Results Here, we provide a computational strategy, Shine, that allows extraction of specific, sensitive and well-conserved biomarkers from massive microbial genomic datasets. Distinguished with simple concatenations with blast-based filtering, our method involves a de novo genome alignment-based pipeline to explore the original and specific repetitive biomarkers in the defined population. It can cover all members to detect newly discovered multicopy conserved species-specific or even subspecies-specific target probes and primer sets. The method has been successfully applied to a number of clinical projects and has the overwhelming advantages of automated detection of all pathogenic microorganisms without the limitations of genome annotation and incompletely assembled motifs. Using on our pipeline, users may select different configuration parameters depending on the purpose of the project for routine clinical detection practices on the website https://bioinfo.liferiver.com.cn with easy registration. Conclusions The proposed strategy is suitable for identifying shared phylogenetic markers while featuring low rates of false positive or false negative. This technology is suitable for the automatic design of minimal and efficient PCR primers and other types of detection probes.
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Chan, Leo Ka Yu, Sui Sum Lin, Fiona Chan, and Danny Siu-Chun Ng. "Optimizing treatment for diabetic macular edema during cataract surgery." Frontiers in Endocrinology 14 (January 25, 2023). http://dx.doi.org/10.3389/fendo.2023.1106706.
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Diabetic macular edema (DME) causes visual impairment in diabetic retinopathy (DR). Diabetes mellitus is a global epidemic and diabetic individuals are at risk of developing DR. Approximately 1 in 10 diabetic patients suffers from DME, which is the commonest cause of vision-threatening DR at primary-care screening. Furthermore, diabetes predisposes to a higher frequency and a younger onset of cataract, which further threatens vision in DME patients. Although cataract extraction is an effective cure, vision may still deteriorate following cataract surgery due to DME progression or recurrence, of which the risks are significantly higher than for patients without concurrent or previous history of DME at the time of operation. The management of pre-existing DME with visually significant cataract is a clinical conundrum. Deferring cataract surgery until DME is adequately treated is not ideal because of prolonged visual impairment and maturation of cataract jeopardizing surgical safety and monitoring of DR. On the other hand, the progression or recurrence of DME following prompt cataract surgery is a profound disappointment for patients and ophthalmic surgeons who had high expectations for postoperative visual improvement. Prescription of perioperative anti-inflammatory eye drops is effective in lowering the risk of new-onset DME after cataract surgery. However, management of concurrent DME at the time of cataract surgery is much more challenging because DME is unlikely to resolve spontaneously even with the aid of anti-inflammatory non-steroidal or steroid eye drops. A number of clinical trials using intravitreal injection of corticosteroids and anti-vascular endothelial growth factor (anti-VEGF) as first-line therapy have demonstrated safety and efficacy to treat DME. These drugs have also been administered perioperatively for the prevention of DME worsening in patients undergoing cataract surgery. This article reviews the scientific evidence to guide ophthalmologists on the efficacy and safety of various therapies for managing patients with DME who are particularly vulnerable to cataract surgery-induced inflammation, which disintegrates the blood–retinal barrier and egression of fluid in macular edema.
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Vilain, Pascal, Salamta Bah-Assoumani, Ali-Mohamed Youssouf, and Laurent Filleul. "Outbreak of ED visits related to the use of synthetic cannabinoids, Mayotte Island." Online Journal of Public Health Informatics 10, no. 1 (May 22, 2018). http://dx.doi.org/10.5210/ojphi.v10i1.8950.
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ObjectiveTo confirm and to characterize the increase in emergency department (ED) visits related to the use of synthetic cannabinoids (SC)IntroductionOn October 2016, the Indian Ocean Regional Health Agency was alerted about an increase in ED visits related to adverse reactions associated with use of SC on Mayotte Island. In this context, an investigation based on a syndromic surveillance system was implemented by the regional unit of the French national public health agency.MethodsAn extraction of anonymized records routinely collected by the syndromic surveillance system (1) was carried out from January 1st, 2012 to October 30, 2016. ED visits related to the consumption of SC were identified from ICD-10 codes of the principal diagnostic according to two levels of confidence:- a probable case was defined as ED visit coded X69 (Intentional self-poisoning by and exposure to other and unspecified chemicals and noxious substances). This code has been implemented specifically by ED physicians since august 2015;- a suspect case was defined as ED visit coded: F11 (Mental and behavioral disorders due to use of opioids), F12 (Mental and behavioral disorders due to use of cannabinoids), F16 (Mental and behavioral disorders due to use of hallucinogens), F18 (Mental and behavioral disorders due to use of volatile solvents), F19 (Mental and behavioral disorders due to multiple drug use and use of other psychoactive substances).Based on these data, an epidemic curve and a descriptive analysis of ED visits were carried out.ResultsIn total, 146 ED visits related to adverse events associated with use of SC were registered from January 1st, 2012 to October 30, 2016. The epidemic curve shows two waves between 2015 and 2016 with a particularly high peak in August 2015 (Figure 1). In total, 49% (n=72/146) of these ED visits were probably related to adverse reactions associated to use SC and 51% (n=74/146) meet to the suspect case definition. On the surveillance period, men represented 84% of the patients (n=122) and median age (min – max) was 23 (8-62) years old. When the severity score variable was filled (n = 138), a vital emergency was reported for 4% (n = 5) of patients and 19% of patients were hospitalized.ConclusionsData from syndromic surveillance system allowed to confirm an increase in ED visits related to adverse reactions associated with use of SC in Mayotte Island. To our knowledge, it’s the first time that an outbreak related to use SC is described in the Ocean Indian areaThis phenomenon was particularly marked in 2015 with a peak of ED visits on August 2016.After this outbreak, the regional unit of the French national public health agency recommended the pursuit of the coding X69 in principal diagnosis with the following case definition: any patient with an adverse reaction attributed to synthetic cannabinoid use whether suspected by the medical team or declared by the patient himself or if the patient is in possession of the substance; and to raise awareness ED physicians to the notification of these poisonings to the Regional Addictive Surveillance Center.In conclusion, the young population, weakened by a precarious socio-economic situation, is a target for new synthetic drugs and a threat to public health. This emerging risk in Mayotte must be taken into account and must be actively monitored. In this context, collaborative work with the emergency services must continue in parallel with targeted prevention measures.References1. Vilain P, Maillard O, Raslan-Loubatie J, Abdou MA, Lernout T, Filleul L. Usefulness of Syndromic Surveillance for Early Outbreak Detection in Small Islands: The Case of Mayotte. Online Journal of Public Health Informatics. 2013;5(1):e149.
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Vieira, Paula Marinho, and Carla Cunha. "Long-term efficacy of psychotherapy in major depression: protocol of a network meta-analysis." Psychologist: Practice & Research Journal 2, no. 1 (November 30, 2019). http://dx.doi.org/10.33525/pprj.v2i1.35.
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Background: Depression is currently considered the epidemic of the century. In recent decades, research has established that psychotherapy is globally effective for the treatment of depression; however, it remains open which psychotherapeutic treatment is most effective and, particularly, if its efficacy is maintained over the long term. Given the difficulty in performing randomized and controlled clinical trials (RCTs) that simultaneously compare several psychotherapeutic models, meta-analyses aim to provide answers by synthesizing the evidence generated through direct comparisons of treatments.Goals: This protocol describes the meta-analysis study we will perform in order to assess the efficacy and acceptability of long-term results of psychotherapy (i.e., 18-month follow-up or higher) in the treatment of major depression in adults.Methods: Through the use of a recent methodological approach - the network meta-analysis - we will integrate the direct and indirect analysis of evidence from randomized and controlled clinical trials in this domain. We will systematically search seven databases for RCTs of psychotherapy, published since 1994, with evaluation of the efficacy in terms of long-term results for the treatment of depression. All studies with adult participants (18 to 65 years of age) diagnosed with major depression (according to DSM-IV, IV-TR, V or ICD-9, 10) will be eligible and all studies that compare psychotherapy (individual and face-to-face treatment) with a control condition (waiting-list, placebo) will be considered. Data extraction, quality assessment and risk of bias will be carried out independently by three researchers. The primary outcome measure will be the long-term efficacy of treatments (follow-ups of 18 months or above) measured by changes in the overall clinical response and symptoms of depression since post-treatment and follow-ups. The secondary measure will be the acceptability of treatment as measured by the proportion of participants who drop out of follow-up or start another treatment (not psychotherapy). A direct comparison (pairwise meta-analysis) of all studies comparing different psychotherapies will be performed. We will compare relative efficacy and acceptability by indirect comparison, through a bayesian network meta-analysis of random effects to compare different psychological interventions. Further analyses will be conducted if inconsistency and heterogeneity values are found. Discussion: The purpose of this review is to systematize and integrate evidence of long-term maintenance of the results of different psychotherapeutic treatments for major depression, administered individually and face-to-face in RCTs. For this reason, multiple direct and indirect comparisons of treatments (bayesian network) will be made, and the interrelationships between treatments will be estimated in terms of long-term efficacy and acceptability. Even though our scope will be focused on RCTs, we hope that the results obtained can contribute to summarize the present evidence available in terms of long-term results of psychotherapy (i.e., its effectiveness), optimizing the planning of future studies, providing public health guidelines and more informed clinical decisions on the treatment of depression.
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Wang, Mengying, Zhen Sun, Mo Jia, Yan Wang, Heng Wang, Xingxing Zhu, Lianzhong Chen, and Hong Ji. "Intelligent virtual case learning system based on real medical records and natural language processing." BMC Medical Informatics and Decision Making 22, no. 1 (March 4, 2022). http://dx.doi.org/10.1186/s12911-022-01797-7.
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Abstract Background Modernizing medical education by using artificial intelligence and other new technologies to improve the clinical thinking ability of medical students is an important research topic in recent years. Prominent medical universities are actively conducting research and exploration in this area. In particular, given the shortage of human resources, the need to maintain social distancing to prevent the spread of the epidemics, and the increase in the cost of medical education, it is critical to harness online learning to promote medical education. A virtual case learning system that uses natural language processing technology to process and present a hospital’s real medical records and evaluate student responses can effectively improve medical students’ clinical thinking abilities. Objective The purpose of this study is to develop a virtual case system, AIteach, based on actual complete hospital medical records and natural language processing technology, and achieve clinical thinking ability improvement through a contactless, self-service, trial-and-error system application. Methods Case extraction is performed on a hospital’s case data center and the best-matching cases are produced through natural language processing, word segmentation, synonym conversion, and sorting. A standard clinical questioning data module, virtual case data module, and student learning difficulty module are established to achieve simulation. Students can view the objective examination and inspection data of actual cases, including details of the consultation and physical examination, and automatically provide their learning response via a multi-dimensional evaluation system. In order to assess the changes in students’ clinical thinking after using AIteach, 15 medical graduate students were subjected to two simulation tests before and after learning through the virtual case system. The tests, which included the full-process case examination of cases having the same difficulty level, examined core clinical thinking test points such as consultation, physical examination, and disposal, and generated multi-dimensional evaluation indicators (rigor, logic, system, agility, and knowledge expansion). Thus, a complete and credible evaluation system is developed. Results The AIteach system used an internal and external double-cycle learning model. Students collect case information through online inquiries, physical examinations, and other means, analyze the information for feedback verification, and generate their detailed multi-dimensional clinical thinking after learning. The feedback report can be evaluated and its knowledge gaps analyzed. Such learning based on real cases is in line with traditional methods of disease diagnosis and treatment, and addresses the practical difficulties in reflecting actual disease progression while keeping pace with recent research. Test results regarding short-term learning showed that the average score (P < 0.01) increased from 69.87 to 85.6, the five indicators of clinical thinking evaluation improved, and there was obvious logical improvement, reaching 47%. Conclusion By combining real cases and natural language processing technology, AIteach can provide medical students (including undergraduates and postgraduates) with an online learning tool for clinical thinking training. Virtual case learning helps students to cultivate clinical thinking abilities even in the absence of clinical tutor, such as during pandemics or natural disasters.
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Pontais, Isabelle, Florian Franke, Barbara Philippot, François Valli, Gilles Viudes, and Céline Caserio-Schönemann. "Are the French SAMU data relevant for health surveillance?" Online Journal of Public Health Informatics 10, no. 1 (May 22, 2018). http://dx.doi.org/10.5210/ojphi.v10i1.8554.
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ObjectiveTo evaluate whether SAMU data could be relevant for health surveillance and proposed to be integrated into the French national syndromic surveillance SurSaUD® system.IntroductionThe syndromic surveillance SurSaUD® system developed by Santé publique France, the French National Public Health Agency collects daily data from 4 data sources: emergency departments (OSCOUR® ED network) [1], emergency general practioners (SOS Médecins network), crude mortality (civil status data) and electronic death certification including causes of death [2]. The system aims to timely identify, follow and assess the health impact of unusual or seasonal events on emergency medical activity and mortality. However some information could be missed by the system especially for non-severe (absence of ED consultation) or, in contrast, highly severe purposes (direct access to intensive care units).The French pre-hospital emergency medical service (SAMU) [3] represents a potential valuable data source to complete the SurSaUD® surveillance system, thanks to reactive pre-hospital data collection and a large geographical coverage on the whole territory. Data are still not completely standardized and computerized but a governmental project to develop a national common IT system involving all French SAMU is in progress and will be experimented in the following years.MethodsA pilot study was performed in the South of France PACA region, where data from the six local SAMU structures are centralized into an interconnected database. A minimal set of variables required for health monitoring (administrative and medical items) and modalities for data extraction and transmission to Santé publique France were defined.SAMU data were transmitted daily to Santé Publique France and the PACA regional team developed a Microsoft Access® application to import decrypted data, request database and analyze indicators.Retrospective part of the study was performed over a 2-year period (2013-2014) and the prospective part during 2015 was based on daily data collection. Completeness and quality of variables were analyzed. SAMU indicators including several level of specificity were built and compared to existing SurSaUD® indicators in different situations (for detection, seasonal follow-up and health impact assessment) using Spearman coefficient correlation.ResultsDuring the pilot study, data from five of the six SAMU structures of PACA region were structured enough to be analyzed. On the study period, almost 2,400,000 files were recorded and 89% contain medical information. Data completeness was high (87%) and stable during the whole period. The annual rate of SAMU solicitation was 16 for 100 inhabitants at the regional scale. 15% of the records were opened only for medical advice. In contrast, patients were evacuated directly in intensive care unit in 9.5% of cases without ED admission. Coding quality depended on the existence and the use of official thesauri and varied widely among SAMU structures. Despite coding variations, SAMU indicators for winter epidemics were significantly correlated with ED and SOS Médecins indicators. Respectively with ED flu, bronchiolitis and gastroenteritis indicators, the strongest correlations were found for SAMU lower respiratory infection (0.74), SAMU bronchiolitis (0.72) and SAMU gastroenteritis / diarrhea / vomiting (0.81).ConclusionsThis pilot study demonstrated the feasibility to collect daily SAMU activity data. The key strengths of SAMU data were a large geographic coverage, the subsidiarity with SurSaUD® system data sources, the follow-up of prehospital activity and for patients directly admitted into an intensive care unit. Some limitations were highlighted related to differences in coding practices especially for medical diagnosis. The generalization of this study will require the standardization of coding practices and homogenization of thesaurus. The implementation of the national SAMU information system should allow in a very next future to widely progressing on these topics.References[1] Fouillet A, Bousquet V, Pontais I, Gallay A and Caserio-Schönemann C. The French Emergency Department OSCOUR Network:Evaluation After a 10-year Existence. Online Journal of Public Health Informatics ISSN 1947-2579-7(1):e74, 2015[2] Caserio-Schönemann C, Bousquet V, Fouillet A, Henry V. Le système de surveillance syndromique SurSaUD (R). Bull Epidémiol Hebd 2014;3-4:38-44.[3] Baker, D.J.. The French prehospital emergency medicine system (SAMU): An introduction(2005) CPD Anaesthesia, 7 (1), pp. 20-25.
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Fix, Jonathan, Dennis Falls, Scott Proescholdbell, Amy Ising, Tony Fernandez, and Anna E. Waller. "Optimization of Linkage between North Carolina EMS and ED Data: EMS Naloxone Cases." Online Journal of Public Health Informatics 11, no. 1 (May 30, 2019). http://dx.doi.org/10.5210/ojphi.v11i1.9765.
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ObjectiveTo improve linkage between North Carolina’s Emergency Medical Services (EMS) and Emergency Department (ED) data using an iterative, deterministic approach.IntroductionThe opioid overdose crisis has rapidly expanded in North Carolina (NC), paralleling the epidemic across the United States. The number of opioid overdose deaths in NC has increased by nearly 40% each year since 2015.1 Critical to preventing overdose deaths is increasing access to the life-saving drug naloxone, which can reverse overdose symptoms and progression. Over 700 EMS agencies across NC respond to over 1,000,000 calls each year; naloxone administration was documented in over 15,000 calls in 2017.2Linking EMS encounters with naloxone administration to the corresponding ED visit assists in understanding the health outcomes of these patients. However, less than 66% of NC EMS records with naloxone administration in 2017 were successfully linked to an ED visit record. This study explored methods to improve EMS and ED data linkage, using a multistage process to maximize the number of correctly linked records while avoiding false linkages.MethodsEMS data were provided by the EMS Performance Improvement Center2 (EMSPIC); ED data were provided by NC DETECT.3 Optimization of current EMS/ED linkage methods began by extracting a non-random subset of EMS encounters with naloxone administration between January 1, 2017 and November 30, 2017 from 12 NC counties, representing eastern, central and western regions and the overall linkage performance of the larger dataset. Records were eligible for linkage if EMS recorded that the patient was “treated and transported” to the ED. All records in the subset were manually reviewed in NC DETECT to identify corresponding ED visit records. This produced a “gold standard” dataset of linked EMS/ED records.To evaluate linkage performance, we first identified all records eligible for linkage. Any EMS transport to either a hospital outside of NC or an NC ED not included in NC DETECT (e.g., military, VA and tribal hospitals) was excluded. Since existing linkage is performed daily and both EMS and ED records are updated over time to correct errors and missing data, existing linkage methods were re-run on updated data to evaluate the improvement provided solely by linking the most up-to-date data. Unlinked EMS records for which the encounter was an inter-facility transfer, transfer to helicopter transport, or the patient died during transfer were deemed ineligible for linkage, as these patients likely either bypassed or never made it to the ED.To initially improve linkage quality, we updated the mapping file of EMS/ED destinations. An exact destination match was required for linkage and the EMS destination variable is recorded as free-text; thus, all variations of a destination name and spelling were identified and mapped to a standardized name. The maximum time difference between EMS drop-off and ED intake was then allowed to exceed 60 minutes, in iterations of 90, 120, 240, and 360 minutes. With each iteration, we compared the linked IDs with the gold standard dataset to identify false links.Finally, a multistage linkage process was applied. First, deterministic linkage was run requiring exact matches for date of birth (DOB), sex/gender, and destination, and up to 360-minute difference between EMS/ED times. The unlinked records were then processed a second time, requiring exact matches for sex/gender and destination, DOB to be within +/- 10 days or +/- 1 year, and up to 60-minute difference between EMS/ED times.This multistage process was then run for all 2017 EMS encounters with naloxone administration to ensure that the new method was not over fit to the data subset. Potential bias in the linkage was assessed by comparing the distributions of age (mean and median) and gender (% male) among the linked and unlinked records in each dataset.Statistical analyses were completed using SAS 9.4 (Cary, NC). Linkage was executed using SQL Server.ResultsBetween 1/1/2017 and 11/30/2017, there were 14,793 EMS encounters with documented naloxone administration. Of these, 12,089 (81.7%) were recorded as “treated and transported”; 1,906 EMS encounters were included in the 12-county subset. The average age of patients was 45.1 years among all naloxone encounters and 45.2 years in the subset. 57.5% of all encounters were male; 58.1% were male in the subset.After removing EMS transports to non-NC or non-NC DETECT hospitals, the existing subset linkage was 61.8% (1,154/1,866). This included 38 (2.0%) false positives, apparently caused by ED records purged since this linkage was conducted. When the existing methods were run against the most current data, linkage improved to 72.2% (1,389/1,866), reflecting an absolute improvement of 10.4% by simply using updated data. Only 1 (0.05%) false positive was identified in this process.Following removal of unlinked inter-facility transfers, deaths during EMS transport, and transfers to helicopters, the records eligible for linkage dropped to 1,781. Linkage improved to 79.5% (1,417/1,781) when hospital names were standardized. Linkage using standardized hospital names and relaxing the EMS/ED time difference performed at the following levels: 82.3% at 90 minutes, 83.3% at 120 minutes, 87.9% at 240 minutes, and 89.4% at 360 minutes. Even when using the most relaxed time difference (+/- 360 minutes), only one false positive was identified, the same produced during initial linkage at +/- 60 minutes. The final multistage method produced linkage of 91.0% (1,620/1,781), with no additional false positives.Applying the initial methods to the statewide EMS dataset produced linkage of 64.8%. The multistage linkage process performed nearly identically on statewide data as observed for the subset, at 91.1%. For statewide data, the age of linked patients was younger (mean = 44.7 years [SD = 18.4], median = 41.0 years) than that of unlinked patients (mean = 48.0 years [SD = 19.3], median = 47.0 years). Additionally, linked patients were more likely to be male (58.1%) when compared to unlinked patients (54.2%).ConclusionsHigh quality linkage between EMS and ED records is essential for research and public health surveillance examining health outcomes. Using a multistage process, we improved the linkage of EMS encounters with documented naloxone administration to ED visits in North Carolina in 2017 from 64.8% to 91.1%, with less than 0.05% false positive rate. This improved linkage will facilitate future analyses of relationships between exposures during EMS encounters and outcomes experienced in hospitals. Future research should evaluate the generalizability of this linkage methodology to all EMS records, not just those with naloxone administration, as well as to pre-2017 data. Implementation of probabilistic linkage or machine learning as a final stage in a multistage process may further improve linkage outcomes, overcoming missing data or unpredictable errors in the data.References1. Kansagra SM, Cohen MK. The Opioid Epidemic in NC: Progress, Challenges, and Opportunities. N C Med J 2018; 79(3): 157-62.2. EMS Performance Improvement Center. About EMSPIC. https://www.emspic.org/about.3. NC DETECT. Background. http://ncdetect.org/background/