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Journal articles on the topic 'Epidemic'
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1
Karpova, L. S., T. P. Stolyarova, and N. M. Popovtseva. "Parameters of the Influenza Epidemic in Russia in the 2019-2020 Season." Epidemiology and Vaccinal Prevention 19, no. 6 (January 14, 2021): 8–17. http://dx.doi.org/10.31631/2073-3046-2020-19-6-8-17.
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Relevance. The National influenza center uses additional criteria: baselines and thresholds for epidemic intensity for early recognition of the onset and assessment of epidemic intensity. Aim. To characterize the parameters of the flu epidemic in the Russian Federation in the 2019-2020 season and assess the intensity of the last 2 epidemics and the effectiveness of baselines and intensity thresholds. Materials and methods. The database of the research Institute of influenza on weekly morbidity, hospitalization, deaths from influenza and ARVI in the cities-reference bases of the National center for influenza was used. The analysis of the flu situation is based on comparing the current incidence of influenza and ARVI with weekly epic thresholds and baselines. A comparative assessment of the intensity of the last 2 influenza epidemics was carried out using intensity thresholds calculated by the moving epidemic method (MEM). Results. The main parameters of the 2019-20 influenza epidemic compared to the previous one are described. There was an increase in the incidence of clinically diagnosed «fluenza» in the pre-epidemic period and the early onset of both epidemics and reaching a peak in the 6th calendar week. This season, the epidemic started among school children, then among adults, and in the past-among the adult population, the incidence of children 0-2 years old was below the thresholds in both epidemics. This season, the average duration of the epidemic and the incidence in cities were higher among school children and adults, and over the entire period of the epidemic, the incidence was higher in all age groups across the country. This season, the epidemic started in the North Caucasus Federal district, its intensity was medium and low, in the past - it started simultaneously in the Siberian, Ural and North Caucasus districts, and its intensity was very high (in the North Caucasus) and high (in the Siberian Federal district) and the average level of 6 districts. The intensity and duration of epidemics were higher in districts with an early onset (in the North Caucasus and Siberian Federal districts). Both epidemics in the country were of moderate intensity, but there were fewer deaths from influenza in the last epidemic. Conclusion. Comparative characteristics of epidemics using baselines and intensity thresholds allowed us to identify the features of the epidemic process in the seasons 2018-19 and 2019-20: the earlier onset of both epidemics; a noticeable increase in the incidence of fluenza before the beginning of epidemics; a decrease in the intensity of epidemics and mortality from influenza; features of the epidemic process in Federal districts. The effectiveness of using additional criteria in the analysis of the influenza epidemic in Russia and this season has been confirmed. In both epidemics, the weekly epidemic thresholds for influenza and ARVI were more sensitive when determining the start of the epidemic, and the end of it, on the contrary, were baselines, and the baselines of morbidity and hospitalization with a diagnosis «influenza» determined the beginning and end of the epidemic even more precisely.
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Brierly, Joseph E. "Epidemic Cycle." Journal of Biotechnology & Bioinformatics Research 2, no. 1 (March 31, 2020): 1–4. http://dx.doi.org/10.47363/jbbr/2019(1)104.
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This article explains the natural progression of a typical viral epidemic. Epidemics historically go through a progressive cycle because once a person is victimized normally there is an immune and non-infectious period of one or more years. At this time both immunity and infectiousness has not been scientifically verified for the Covid-19 virus. However, likely the Covid-19 virus will progress the way of other past virus epidemics. At present there is much untested and possibly unreliable information regarding the Covid-19 epidemic. This article shows the most likely way the Covid-19 epidemic will progress over time.
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Shi, Zizhong, Junru Li, and Xiangdong Hu. "Risk Assessment and Response Strategy for Pig Epidemics in China." Veterinary Sciences 10, no. 8 (July 26, 2023): 485. http://dx.doi.org/10.3390/vetsci10080485.
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Strengthening the analysis and risk assessment of the pig epidemic will help to better prevent and mitigate epidemic risks and promote the high-quality development of the pig industry. Based on a systematic understanding of live pig epidemics, a risk assessment index system was constructed, and the spatial and temporal variation characteristics of pig epidemics in China were explored by the entropy method. In recent years, the overall trend in pig epidemics over time first increased and then decreased; in space, the acceleration of the spread of epidemics across the country weakened. China still faces challenges, including many types and a wide range of diseases, large total livestock breeding and weak epidemic prevention and control capacity, and a large risk of introduced foreign animal epidemics. The spatial and temporal variations in the pig epidemic risk were obvious; one high-risk area, two medium–high-risk areas and 10 medium-risk areas have been found in recent years, during which time, the epidemic risk was highest in Beijing, Hainan, Liaoning, Tibet and Zhejiang. However, there were significant differences in the regional distribution of the risk level of pig epidemics in different years. To further build a secure “defense system” for the high-quality development of the pig industry, it is recommended to improve the monitoring and early warning system of pig epidemic risk, perfect the pig epidemic prevention and control system, and strengthen the regional collaboration mechanism of epidemic prevention and control.
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Pometti Benítez, Kevin. "Clima, salud pública y sociedad: causas, gestión y efectos de la fiebre amarilla en la Barcelona de 1821." Cuadernos de Estudios del Siglo XVIII, no. 29 (December 17, 2019): 247–77. http://dx.doi.org/10.17811/cesxviii.29.2019.247-277.
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RESUMENLa epidemia de fiebre amarilla que tuvo lugar en Barcelona en 1821 estuvo condicionada por la confluencia de causas endógenas y exógenas, ambientales y humanas, que fueron favorables al arraigo de una epidemia importada que generó serias repercusiones sobre la sociedad de su época. Por este motivo, en este artículo analizamos las particularidades del contexto ambiental que precedieron al inicio de la epidemia y que imperaron marcando las pautas propicias tanto para su desarrollo como para su progresiva extinción atendiendo, además, a lascondiciones de insalubridad que imperaban en la urbe. Por otra parte, centramos nuestra atención en las medidas que se implementaron en materia de salud pública para la gestión epidémica tanto para detectar su efectividad como sus repercusiones a nivel social, institucional, económico. Otro punto de interés reside en contrastar las condicionesambientales con las defunciones registradas en los puntos de observación habilitados para la contención de las personas infectadas por la fiebre amarilla.PALABRAS CLAVEFiebre amarilla, Barcelona, enfermedades vectoriales, salud pública, epidemias, clima. TITLEClimate, public health and society: causes, management and effects of Yellow Fever epidemic in Barcelona in 1821ABSTRACTThe Yellow Fever epidemic that took place in Barcelona in 1821 was a consequence of the confluence of endogenous and exogenous factors, human and environmental causes, which were favourable for the development of an imported disease that had deleterious effects over the society at that time. Because of that, in this paper we analyse the particularities of the environmental context that preceded the start of the epidemic and during its prevalence. Attending also to the insalubrity causes that characterized the city. Moreover, we centre our attention into analysing the sanitation politics applied by the authorities and medical institutions to evaluate the effectivity of those measures and to detect the repercussions over the society, the institutions and the economy. Another point of interest resides in to contrast the environmental conditions with the dead reports recovered from the observation points fitted out by authorities to contain the people affected by the epidemic.KEY WORDSYellow Fever, Barcelona, Vector Diseases, Public Health, Epidemics, Climate.
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Li, Wenjie, Yanyi Nie, Wenyao Li, Xiaolong Chen, Sheng Su, and Wei Wang. "Two competing simplicial irreversible epidemics on simplicial complex." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 9 (September 2022): 093135. http://dx.doi.org/10.1063/5.0100315.
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Higher-order interactions have significant implications for the dynamics of competing epidemic spreads. In this paper, a competing spread model for two simplicial irreversible epidemics (i.e., susceptible–infected–removed epidemics) on higher-order networks is proposed. The simplicial complexes are based on synthetic (including homogeneous and heterogeneous) and real-world networks. The spread process of two epidemics is theoretically analyzed by extending the microscopic Markov chain approach. When the two epidemics have the same 2-simplex infection rate and the 1-simplex infection rate of epidemic [Formula: see text] ([Formula: see text]) is fixed at zero, an increase in the 1-simplex infection rate of epidemic [Formula: see text] ([Formula: see text]) causes a transition from continuous growth to sharp growth in the spread of epidemic [Formula: see text] with [Formula: see text]. When [Formula: see text], the growth of epidemic [Formula: see text] is always continuous. With the increase of [Formula: see text], the outbreak threshold of epidemic [Formula: see text] is delayed. When the difference in 1-simplex infection rates between the two epidemics reaches approximately three times, the stronger side obviously dominates. Otherwise, the coexistence of the two epidemics is always observed. When the 1-simplex infection rates are symmetrical, the increase in competition will accelerate the spread process and expand the spread area of both epidemics; when the 1-simplex infection rates are asymmetrical, the spread area of one epidemic increases with an increase in the 1-simplex infection rate from this epidemic while the other decreases. Finally, the influence of 2-simplex infection rates on the competing spread is discussed. An increase in 2-simplex infection rates leads to sharp growth in one of the epidemics.
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Garcia-Soto, M., R. E. Fullilove, M. T. Fullilove, and K. Haynes-Sanstad. "The Peculiar Epidemic, Part I: Social Response to AIDS in Alameda County." Environment and Planning A: Economy and Space 30, no. 4 (April 1998): 731–46. http://dx.doi.org/10.1068/a300731.
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The morbidity and mortality caused by epidemics threaten social functioning of complex societies. Societies mount a social response to epidemics in order to contain the potential damage from uncontrolled disease. Despite the threat posed by epidemics, social and contextual ‘vulnerabilities’ often impede efforts to contain epidemics. The AIDS epidemic provides an example of a ‘peculiar’ epidemic, in which threat to social welfare failed to provoke adequate social efforts at containment. In order to examine the miscarriage of epidemic response, we interviewed 31 AIDS providers in Alameda County, California, about the development of their AIDS-related services. According to the people interviewed, epidemic response in the County was marred by stigma associated with AIDS, lack of adequate funding, difficulties in building collaborative effort in a fragmented care system, and other political and social problems. In spite of these obstacles, social mobilization enabled directors of a wide variety of health care agencies to incorporate care and prevention into their services. The findings support the concept that ‘vulnerabilities’ can derail epidemic response, making widespread social mobilization an essential tool for epidemic control. The discussion centers on the implication of these findings for the theoretical understanding of social response to epidemics.
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Muhsin, Sayyed Mohamed, and Murshid Muhammad. "Epidemics between Qadr and Ḥadhar: Insights from al-Nawawī (Epidemik Di antara Qadar dan Hadhar: Sorotan dari Al- Nawawi)." Journal of Islam in Asia (E-ISSN 2289-8077) 18, no. 2 (October 24, 2021): 144–58. http://dx.doi.org/10.31436/jia.v18i2.1054.
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Being a great jurist and influential scholar with seminal works on hadith, theology, biography and jurisprudence, al-Nawawī’s (d. 1277) views on epidemics are of great significance in these days of the pandemic. This article explores his views and explanations vis-à-vis epidemic to find his perspectives on balance between qadr (predestination) and ḥadhar (precaution) by conducting a content analysis of his various texts. In this article, the authors mainly referred to his texts Sharaḥ Muslim, Riyaḍ al-Ṣāliḥīn, al-Majmūʿ Sharaḥ Muhadhdhab, Rawḍat al-Ṭālibīn and al- Adhkār al-Muntakhab. This study substantiates that in the view of al-Nawawī, Islam postulates a balanced position between taking precaution and faith in Allah’s decrees in dealing with the situations of an epidemic. Thus, it holistically complements the concepts of qadr and hadhar to guide people towards leading a faithful and safe life in the trying times of epidemic. Keywords: Qadr, Ḥadhar, Precaution, Predestination, Al-Nawawī, Hadith, Epidemic. Abstrak Sebagai seorang juri dan seorang sarjana yang terkenal dan berpengaruh dalam ilmu hadis, agama, biografi dan falsafah perundangan, pandagan Imam Nawawi [d1277] pada epidemik pada masa kini mempunyai kesan signifikan dalam waktu pandemik sekarang. Artikel ini meninjau pandangan dan penghuraian perspektif epidemik dan keseimbangan di antara qadar [takdir] dan hadhar [pencegahan] dengan mengkaji analisa kandungan pelbagai hasil penulisan. Dalam artikel ini penulis merujuk kepada penulisan Sharaḥ Muslim, Riyaḍ al-Ṣāaliḥīn, al-Majmūʿ Sharaḥ Muhadhdhab, Rawḍat al-Ṭālibīn dan al- Adhkār al-Muntakhab. Kajian ini juga membuktikan pendapat Imam Nawawi bahawa Islam mencakna keseimbangan kedudukan di antara mengambil langkah berjaga-jaga yakni pencegahan dan keyakinan kepada kekuasaan dan penentuan Allah swt dalam mengurus situasi epidemik dalam konsep Qada dan Hadhar. Kata Kunci: Qadar, Hadhar, Pencegahan, Takdir, al-Nawawi, Hadith, Epidemik.
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Yoshikura, Hiroshi. "Measles Epidemic Influenced by COVID-19 Epidemic." Epidemiology International Journal 6, no. 3 (2022): 1–3. http://dx.doi.org/10.23880/eij-16000244.
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In Western Pacific, the number of measles cases dropped precipitously in early 2020. As the coverage of measles vaccine remained almost unchanged, the precipitous drop of the measles cases could not be attributed to measles vaccine. It was probably brought about by physical distancing and other measures to prevent spread of SARS-CoV-2. SARS-CoV-2 cases increased wave by wave, while the number of the deaths divided by that of the patients declined. The decline of the casefatality rate could not be attributable to SARS-CoV-2 vaccine, because the trend emerged from the start of the epidemic, far ahead of introduction of SARS-CoV-2 vaccine.
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Braz, Rui Moreira, Renato Fontes Guimarães, Osmar Abílio de Carvalho Júnior, and Pedro Luiz Tauil. "Spatial dependence of malaria epidemics in municipalities of the Brazilian Amazon." Revista Brasileira de Epidemiologia 17, no. 3 (September 2014): 615–28. http://dx.doi.org/10.1590/1809-4503201400030004.
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Introduction: In 2010, there were 305 (37.8%) municipalities with malaria epidemics in the Brazilian Amazon. The epidemics spread can be explained by the spatial distribution pattern. Objective: To analyze the spatial dependence, autocorrelation, of the malaria epidemics in the municipalities of this region. Methods: An automated algorithm was used for the detection of epidemic municipalities in 2003, 2007 and 2010. Spatial dependence was analyzed by applying the global and local Moran index on the epidemic months proportion variable. The epidemic municipalities clusters were identified using the TerraView software. Results: The global Moran index values were 0.4 in 2003; 0.6 in 2007; and 0.5 in 2010 (p = 0.01), confirming the spatial dependence among the epidemic municipalities. Box Map and Moran Map identified inter-municipal, interstate and borders clusters with spatial autocorrelation (p < 0.05). There were 10 epidemic municipalities clusters in 2003; 9 in 2007 and 8 in 2010. Discussion: The epidemic municipalities clusters may be linked to the health facilities difficulties on acting together. The structural limitations of the health services can be overcome by territorial integration to support planning and control activities, strengthening the interventions. Conclusion: The routine analysis of the epidemic municipalities clusters with spatial and temporal persistence may provide a new indicator of planning and integrated control prioritization, contributing to malaria epidemics reducing in inter-municipal, interstate and borders areas.
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Volz, Erik, and Lauren Ancel Meyers. "Epidemic thresholds in dynamic contact networks." Journal of The Royal Society Interface 6, no. 32 (July 29, 2008): 233–41. http://dx.doi.org/10.1098/rsif.2008.0218.
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The reproductive ratio, R 0 , is a fundamental quantity in epidemiology, which determines the initial increase in an infectious disease in a susceptible host population. In most epidemic models, there is a specific value of R 0 , the epidemic threshold, above which epidemics are possible, but below which epidemics cannot occur. As the complexity of an epidemic model increases, so too does the difficulty of calculating epidemic thresholds. Here we derive the reproductive ratio and epidemic thresholds for susceptible–infected–recovered (SIR) epidemics in a simple class of dynamic random networks. As in most epidemiological models, R 0 depends on two basic epidemic parameters, the transmission and recovery rates. We find that R 0 also depends on social parameters, namely the degree distribution that describes heterogeneity in the numbers of concurrent contacts and the mixing parameter that gives the rate at which contacts are initiated and terminated. We show that social mixing fundamentally changes the epidemiological landscape and, consequently, that static network approximations of dynamic networks can be inadequate.
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PESEN, Birgül, and Musaye KONAK ÖZÇELİK. "THE IMPACT OF SOME OUTSTANDING DISEASES FROM PAST TO PRESENT ON SOCIETY." Zeitschrift für die Welt der Türken / Journal of World of Turks 13, no. 1 (April 15, 2021): 227–48. http://dx.doi.org/10.46291/zfwt/130112.
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Diseases can be seen in people in different periods throughout history. Some of these diseases have become epidemics. Epidemic diseases from the past to the present have left deep marks in the society. Measures against epidemics have also been attempted in the past. Since the source of the epidemic diseases seen in the history and the effects of the disease are unknown, fear prevailed in the society. With the changes in the process and the steps taken in the field of health, the appropriate vaccine against epidemic diseases was found and the quarantine system was put into operation. However, despite the steps taken, it was understood that the public did not have enough information, so efforts were made to raise the awareness of the public. Despite the studies, the lethal effect of epidemics has led to ruptures in relations within society. The epidemic also had an impact on the economy and famines appeared in the society. Epidemic diseases affect the socio-economic life of the society very badly, and negativities have been noticed in individuals due to the epidemic. It has been found that the epidemic mostly affects people with weak body resistance (elderly, children). The Ottoman State continued its determination and acted within the framework of its activities in the fight against epidemic diseases. This determination continues today, and the state continues its struggle against the epidemic with its policies. In this study, after giving historical information about some epidemic diseases such as plague, syphilis, cholera, smallpox, malaria, measles, new coronavirus (covit-19), the effect of these diseases on the society was tried to be explained. Keywords: Epidemic, Society, Ottoman State, Disease, Health.
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LEGRAND, J., R. F. GRAIS, P. Y. BOELLE, A. J. VALLERON, and A. FLAHAULT. "Understanding the dynamics of Ebola epidemics." Epidemiology and Infection 135, no. 4 (September 26, 2006): 610–21. http://dx.doi.org/10.1017/s0950268806007217.
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SUMMARYEbola is a highly lethal virus, which has caused at least 14 confirmed outbreaks in Africa between 1976 and 2006. Using data from two epidemics [in Democratic Republic of Congo (DRC) in 1995 and in Uganda in 2000], we built a mathematical model for the spread of Ebola haemorrhagic fever epidemics taking into account transmission in different epidemiological settings. We estimated the basic reproduction number (R0) to be 2·7 (95% CI 1·9–2·8) for the 1995 epidemic in DRC, and 2·7 (95% CI 2·5–4·1) for the 2000 epidemic in Uganda. For each epidemic, we quantified transmission in different settings (illness in the community, hospitalization, and traditional burial) and simulated various epidemic scenarios to explore the impact of control interventions on a potential epidemic. A key parameter was the rapid institution of control measures. For both epidemic profiles identified, increasing hospitalization rate reduced the predicted epidemic size.
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Kaminsky, Joshua, Lindsay T. Keegan, C. Jessica E. Metcalf, and Justin Lessler. "Perfect counterfactuals for epidemic simulations." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1776 (May 20, 2019): 20180279. http://dx.doi.org/10.1098/rstb.2018.0279.
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Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervention, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a ‘single-world’ approach to matching simulations of controlled epidemics to their exact uncontrolled counterfactual. Our method borrows concepts from percolation approaches, prunes out possible epidemic histories and creates potential epidemic graphs (i.e. a mathematical representation of all consistent epidemics) that can be ‘realized’ to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models (e.g. SIR models), and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids nonsensical inferences. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.
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Zheng, Zhe, Virginia E. Pitzer, Joshua L. Warren, and Daniel M. Weinberger. "Community factors associated with local epidemic timing of respiratory syncytial virus: A spatiotemporal modeling study." Science Advances 7, no. 26 (June 2021): eabd6421. http://dx.doi.org/10.1126/sciadv.abd6421.
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Respiratory syncytial virus (RSV) causes a large burden of morbidity in young children and the elderly. Spatial variability in the timing of RSV epidemics provides an opportunity to probe the factors driving its transmission, including factors that influence epidemic seeding and growth rates. Using hospitalization data from Connecticut, New Jersey, and New York, we estimated epidemic timing at the ZIP code level using harmonic regression and then used a Bayesian meta-regression model to evaluate correlates of epidemic timing. Earlier epidemics were associated with larger household size and greater population density. Nearby localities had similar epidemic timing. Our results suggest that RSV epidemics grow faster in areas with more local contact opportunities, and that epidemic spread follows a spatial diffusion process based on geographic proximity. Our findings can inform the timing of delivery of RSV extended half-life prophylaxis and maternal vaccines and guide future studies on the transmission dynamics of RSV.
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Karpova, L. S., T. P. Stolyarova, N. M. Popovtseva, K. A. Stolyarov, and D. M. Danilenko. "Differences Depending on the Etiology of Influenza Epidemics in 2014-2017." Epidemiology and Vaccine Prevention 17, no. 1 (February 20, 2018): 13–19. http://dx.doi.org/10.31631/2073-3046-2018-17-1-13-19.
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The goal is to identify features of epidemic process of influenza depending on the etiology of epidemics to clarification of the forecast for future epidemics. Analysis of epidemics of influenza in Russia conducted according to the Federal center for influenza on morbidity, hospitalization and deaths from influenza in 59 Russian cities. The epidemic of influenza A(H1N1)pdm09 2015–16 different from the mixed epidemics of influenza (A(H3N2) and B) 2014–15 and 2016–17 high development rate, high incidence of influenza and ARI at its peak, the incidence of hospitalization with a diagnosis of «influenza» (14%) and high mortality among the infected (6,0 on 100000). The epidemic of influenza A(H3N2) and B started earlier (December). They had a longer duration and the incidence in the cities and in the country, but less than the incidence at the peak of the epidemic and the incidence of hospitalization with a diagnosis of «influenza» (7.5 and 7.3%) and smaller (8.6 and 20 times) the mortality from the influenza. In these epidemics among the dead was higher than the percentage of children under 14 years and persons over 65 years of age than in the influenza epidemic 2015–16. And among the deaths increased the proportion of persons with chronic lung disease and immunodeficiency, but decreased the proportion of individuals with obesity and diseases of the liver and kidneys. For the period from 2009 to 2017 the tendency to increase the intensity of influenza A(H3N2) epidemics was 2.4 times greater than the decrease in the intensity of epidemic of influenza A(H1N1)pdm09.
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Keddy, Karen H., Sandrama Nadan, Chetna Govind, and A. Willem Sturm. "Evidence for a clonally different origin of the two cholera epidemics of 2001–2002 and 1980–1987 in South Africa." Journal of Medical Microbiology 56, no. 12 (December 1, 2007): 1644–50. http://dx.doi.org/10.1099/jmm.0.47230-0.
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Vibrio cholerae O1 serotype Ogawa and serotype Inaba isolates from the cholera epidemic that occurred in 2001 and 2002 in South Africa were compared with isolates of V. cholerae O1 serotype Inaba from the epidemic that occurred between 1980 and 1987. PFGE using NotI digestion was used to compare stored isolates received during the 1980s epidemic with those received during the epidemic in 2001/2002. A selected number of these isolates were then sequenced to compare the sequence of the wbeT gene in the V. cholerae O1 Ogawa strains of 2001/2002 with that in the V. cholerae O1 Inaba strains of the 1980s and 2001/2002. Isolates from the recent epidemic were shown to be related, irrespective of serotype, and had comparable banding patterns on PFGE, using NotI. They were distinctly different from those from the previous epidemic. Sequencing of the wbeT gene showed that the gene was highly conserved between the two epidemics. A single deletional mutation of an adenine residue was observed in the V. cholerae serotype Inaba isolates from the 2001/2002 epidemic, resulting in the serotype switch between the V. cholerae O1 strains from the recent epidemic. The distinct differences in PFGE patterns among isolates from the first and second epidemics exclude the possibility that the Inaba strain from the 1980s became dormant in the environment and mutated to serotype Ogawa, causing the 2001/2002 epidemic, despite the apparent consistency in the site of mutation in the Inaba serotypes between the two epidemics.
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Sanatkar, M. R., C. Scoglio, B. Natarajan, S. A. Isard, and K. A. Garrett. "History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust." Phytopathology® 105, no. 7 (July 2015): 947–55. http://dx.doi.org/10.1094/phyto-12-14-0353-fi.
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Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.
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KOSIŃSKI, R. A., and Ł. ADAMOWSKI. "INFLUENCE OF THE INITIAL SOURCE OF EPIDEMIC AND PREVENTIVE VACCINATION ON THE SPREADING PHENOMENA IN A TWO-DIMENSIONAL LATTICE." International Journal of Modern Physics C 15, no. 06 (July 2004): 755–65. http://dx.doi.org/10.1142/s0129183104006200.
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The probabilistic model of epidemic in a two-dimensional lattice with an additional random, long range connections characteristic for the small world networks is presented. Relations describing the spreading process of epidemics, like epidemic curve or range of epidemic in time, were found. The influence of the borders of the lattice and the localization of the initial source of epidemic on the epidemic curve is found analytically. The application of the preventive vaccination in the population is discussed.
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Yan, Shu, Shao Ting Tang, Sen Pei, and Zhi Ming Zheng. "Seasonal Epidemics Immunization on Correlated Networks." Applied Mechanics and Materials 631-632 (September 2014): 976–79. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.976.
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The immunization strategy to halt virus is an important topic in epidemic spreading research. In this paper, we extend our seasonal epidemics immunization model on correlated networks. We apply numerical results of our model on different kinds of networks. We first investigate the relationship between epidemic prevalence and epidemic season. We find that the immunization performs best on negative correlated network, and give an explanation. We also present the result of epidemic prevalence with different vaccinating proportion and epidemic spreading probability.
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Neal, Peter. "Coupling of Two SIR Epidemic Models with Variable Susceptibilities and Infectivities." Journal of Applied Probability 44, no. 1 (March 2007): 41–57. http://dx.doi.org/10.1239/jap/1175267162.
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The variable generalised stochastic epidemic model, which allows for variability in both the susceptibilities and infectivities of individuals, is analysed. A very different epidemic model which exhibits variable susceptibility and infectivity is the random-graph epidemic model. A suitable coupling of the two epidemic models is derived which enables us to show that, whilst the epidemics are very different in appearance, they have the same asymptotic final size distribution. The coupling provides a novel approach to studying random-graph epidemic models.
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Neal, Peter. "Coupling of Two SIR Epidemic Models with Variable Susceptibilities and Infectivities." Journal of Applied Probability 44, no. 01 (March 2007): 41–57. http://dx.doi.org/10.1017/s0021900200002709.
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The variable generalised stochastic epidemic model, which allows for variability in both the susceptibilities and infectivities of individuals, is analysed. A very different epidemic model which exhibits variable susceptibility and infectivity is the random-graph epidemic model. A suitable coupling of the two epidemic models is derived which enables us to show that, whilst the epidemics are very different in appearance, they have the same asymptotic final size distribution. The coupling provides a novel approach to studying random-graph epidemic models.
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Xie, Jiarong, Fanhui Meng, Yiwen Huang, Zhengping Fan, Xiao Ma, and Yanqing Hu. "Optimal devoted resource strategies to epidemic extinction by increasing recovery rate." International Journal of Modern Physics C 31, no. 01 (November 18, 2019): 2050010. http://dx.doi.org/10.1142/s0129183120500102.
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Epidemic extinction requires substantial resources over the period of outbreak. It is crucial to have an efficient strategy to assign resources due to the limited budget. In this paper, on the basis of epidemic spreading model proposed in [Chen et al., PRE, 2019], we investigate how to allocate resources in different periods of epidemics. Our results show that due to the resource moderately concentrated during the period of outbreak, the epidemics become extinct with much fewer resources. Specifically, we found that the optimal devoted resource strategy saves total devoted resource several times. This study is helpful to understand the impact of devoted resources on epidemic extinction and to design epidemic strategies under limited budget.
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Nakajima, S., F. Nishikawa, K. Nakamura, H. Nakao, and K. Nakajima. "Reinfection with influenza B virus in children: analysis of the reinfection influenza B viruses." Epidemiology and Infection 113, no. 1 (August 1994): 103–12. http://dx.doi.org/10.1017/s0950268800051517.
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SUMMARYInfluenza B virus reinfection in Japanese children was studied epidemi-ologically during 1979–91 and virologically during 1985–91. During this investigation, there were four epidemics caused by influenza B viruses, each of which accompanied antigenic drift. Between the epidemics in 1987/88 and 1989/90, the viruses changed drastically, both genetically and antigenically. The minimum rate of reinfection with influenza B virus during the whole period was 3–25% depending on the influenza seasons. The antigens of primary and reinfection strains of influenza B virus isolated from 18 children during 1985–90, which covered three epidemic periods, were studied by haemagglutination inhibition tests. The results showed that the viruses isolated in the 1984/85 and 1987/88 influenza seasons, which belonged to the same lineage, were antigenically close, and reinfection occurred with these viruses. The results of amino-acid analysis of the HA1 polypeptide of these viruses corresponded with those of antigenic analysis. There were no specific amino-acid changes shared by the primary infection and reinfection influenza B viruses; the patients were infected with the viruses epidemic at that time.
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Shachar, Carmel, Tess Wise, Gali Katznelson, and Andrea Louise Campbell. "Criminal Justice or Public Health: A Comparison of the Representation of the Crack Cocaine and Opioid Epidemics in the Media." Journal of Health Politics, Policy and Law 45, no. 2 (December 3, 2019): 211–39. http://dx.doi.org/10.1215/03616878-8004862.
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Abstract Context: The opioid epidemic is a major US public health crisis. Its scope prompted significant public outreach, but this response triggered a series of journalistic articles comparing the opioid epidemic to the crack cocaine epidemic. Some authors claimed that the political response to the crack cocaine epidemic was criminal justice rather than medical in nature, motivated by divergent racial demographics. Methods: We examine these assertions by analyzing the language used in relevant newspaper articles. Using a national sample, we compare word frequencies from articles about crack cocaine in 1988–89 and opioids in 2016–17 to evaluate media framings. We also examine articles about methamphetamines in 1992–93 and heroin throughout the three eras to distinguish between narratives used to describe the crack cocaine and opioid epidemics. Findings: We find support for critics' hypotheses about the differential framing of the two epidemics: articles on the opioid epidemic are likelier to use medical terminology than criminal justice terminology while the reverse is true for crack cocaine articles. Conclusions: Our analysis suggests that race and legality may influence policy responses to substance-use epidemics. Comparisons also suggest that the evolution of the media narrative on substance use cannot alone account for the divergence in framing between the two epidemics.
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WATERS, E. K., H. S. SIDHU, and G. N. MERCER. "SPATIAL HETEROGENEITY IN SIMPLE DETERMINISTIC SIR MODELS ASSESSED ECOLOGICALLY." ANZIAM Journal 54, no. 1-2 (October 2012): 23–36. http://dx.doi.org/10.1017/s1446181113000035.
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AbstractPatchy or divided populations can be important to infectious disease transmission. We first show that Lloyd’s mean crowding index, an index of patchiness from ecology, appears as a term in simple deterministic epidemic models of the SIR type. Using these models, we demonstrate that the rate of movement between patches is crucial for epidemic dynamics. In particular, there is a relationship between epidemic final size and epidemic duration in patchy habitats: controlling inter-patch movement will reduce epidemic duration, but also final size. This suggests that a strategy of quarantining infected areas during the initial phases of a virulent epidemic might reduce epidemic duration, but leave the population vulnerable to future epidemics by inhibiting the development of herd immunity.
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Kenah, Eben, and Joel C. Miller. "Epidemic Percolation Networks, Epidemic Outcomes, and Interventions." Interdisciplinary Perspectives on Infectious Diseases 2011 (2011): 1–13. http://dx.doi.org/10.1155/2011/543520.
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Epidemic percolation networks (EPNs) are directed random networks that can be used to analyze stochastic “Susceptible-Infectious-Removed” (SIR) and “Susceptible-Exposed-Infectious-Removed” (SEIR) epidemic models, unifying and generalizing previous uses of networks and branching processes to analyze mass-action and network-based S(E)IR models. This paper explains the fundamental concepts underlying the definition and use of EPNs, using them to build intuition about the final outcomes of epidemics. We then show how EPNs provide a novel and useful perspective on the design of vaccination strategies.
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Karpova, L. S., M. Yu Pelikh, K. M. Volik, N. M. Popovtseva, T. P. Stolyarova, and D. A. Lioznov. "Evaluating the Effectiveness of New Criteria for Early Detection of the Start and Intensity of Influenza Epidemics in Russian Federation." Epidemiology and Vaccinal Prevention 22, no. 6 (January 4, 2024): 4–18. http://dx.doi.org/10.31631/2073-3046-2023-22-6-4-18.
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Relevance. During the COVID-19 pandemic, an early determination of the start of the influenza epidemic by the incidence of influenza and SARS in total is impossible, due to the similarity of the clinical picture of SARS and lung cases of COVID-19.Aim. The goal is to calculate and test new criteria for early detection of the start of influenza epidemics and their intensity for each of the cities–reference bases (61) of the 2 WHO National Influenza Centers based on the incidence of clinically diagnosed influenza.Tasks. To evaluate the effectiveness of baseline influenza incidence and epidemic intensity thresholds for the general population and age groups of each city in the epidemic of 2022–2023. To give a retrospective assessment of the effectiveness of influenza baselines for cities, compared with the baselines of the corresponding Federal Districts, for the seasons from 2009 to 2022. To estimate the intensity of epidemics by influenza incidence over the previous epidemies of the pandemic cycle of influenza A/California/H1N1/ virus.Materials and methods. By the 2022–2023 season. baseline lines and thresholds of influenza incidence intensity were calculated using the method of moving epidemics according to clinical diagnostic data not only for federal districts, but also for each of the observed cities (61). The calculation of the baselines was carried out according to the data of the computer database of the Influenza Research Institute on the incidence of influenza by age groups in each city over the previous 5 years in the season from 2016–2017 to 2021–2022.Results. In the 2022-23 season application of new criteria for the start of epidemics (prev.- and post-epidemic baseline influenza incidence) and their intensity revealed: early onset of the influenza epidemic (07–13.11 2022); simultaneous onset in all children's age groups; geographical spread of the epidemic in federal districts; intensity of the epidemic in the general population and age groups. The thresholds for the intensity of influenza morbidity made it possible to clarify the intensity levels of influenza epidemics from 2009 to 2023 and to show that the pandemic cycle of the influenza A(H1N1) virus continues. A comparison of the effectiveness of urban baselines with federal ones in the epidemic of 2022–2023 showed that urban baseline flu incidence lines revealed the start of epidemics 1–3 weeks earlier: among the general population in 12 cities, persons over 15 years old – in 9, children 3–6 years old – in 6 and 7–14 years old – in 5. A retrospective assessment of the effectiveness of city and federal influenza baselines (from 2009 to 2022) showed their effectiveness both in the seasons from 2009 to 2016 (before the baseline calculation period) and after. The effectiveness of urban baselines for early detection of the start of epidemics depended on the etiology of the epidemic – more with influenza A(H3N2) than with influenza A(H1N1), the level of intensity of influenza diseases and the age group of the population (more in children with low intensity and in adults with an average level).Conclusion. The results obtained on the basis of population epidemiological data on the incidence of influenza, namely, new criteria for detecting the start of an epidemic in cities, can be used in health management bodies in cities and subjects of the Russian Federation for early detection of epidemics and management decisions, timely introduction of anti-epidemic measures, creating a stock of medicines. The expected effect of the method of early epidemiological diagnosis of epidemics is a decrease in morbidity, etc.
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Chowell, Gerardo, Sushma Dahal, Amna Tariq, Kimberlyn Roosa, James M. Hyman, and Ruiyan Luo. "An ensemble n-sub-epidemic modeling framework for short-term forecasting epidemic trajectories: Application to the COVID-19 pandemic in the USA." PLOS Computational Biology 18, no. 10 (October 6, 2022): e1010602. http://dx.doi.org/10.1371/journal.pcbi.1010602.
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We analyze an ensemble of n-sub-epidemic modeling for forecasting the trajectory of epidemics and pandemics. These ensemble modeling approaches, and models that integrate sub-epidemics to capture complex temporal dynamics, have demonstrated powerful forecasting capability. This modeling framework can characterize complex epidemic patterns, including plateaus, epidemic resurgences, and epidemic waves characterized by multiple peaks of different sizes. We systematically assess their calibration and short-term forecasting performance in short-term forecasts for the COVID-19 pandemic in the USA from late April 2020 to late February 2022. We compare their performance with two commonly used statistical ARIMA models. The best fit sub-epidemic model and three ensemble models constructed using the top-ranking sub-epidemic models consistently outperformed the ARIMA models in terms of the weighted interval score (WIS) and the coverage of the 95% prediction interval across the 10-, 20-, and 30-day short-term forecasts. In our 30-day forecasts, the average WIS ranged from 377.6 to 421.3 for the sub-epidemic models, whereas it ranged from 439.29 to 767.05 for the ARIMA models. Across 98 short-term forecasts, the ensemble model incorporating the top four ranking sub-epidemic models (Ensemble(4)) outperformed the (log) ARIMA model 66.3% of the time, and the ARIMA model, 69.4% of the time in 30-day ahead forecasts in terms of the WIS. Ensemble(4) consistently yielded the best performance in terms of the metrics that account for the uncertainty of the predictions. This framework can be readily applied to investigate the spread of epidemics and pandemics beyond COVID-19, as well as other dynamic growth processes found in nature and society that would benefit from short-term predictions.
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Homicskó, Árpád. "The issues of managing the epidemic situation in the health care system in Hungary." Zbornik radova Pravnog fakulteta, Novi Sad 56, no. 2 (2022): 515–27. http://dx.doi.org/10.5937/zrpfns56-33689.
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In my study, I intend to explore the impact of the current epidemic situation on the health care system in Hungary. To this end, the legal environment applicable to the epidemic situation and the measures related to the health care system in the context of the epidemic situation will be presented. I think that in the 21st century and beyond, it will be increasingly important to deal with emerging epidemics, to which all countries must be able to respond appropriately. Managing the epidemic situations effectively and appropriately is in the interest of society as a whole. Furthermore, public health considerations are essential, and every country has to enhance efforts to fight epidemics. In the 21st century, states still have to consider their task to provide the necessary financial resources to combat epidemics. Health care systems should be suitable to meet public health and epidemiological considerations and the demands of general patient care.
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Ojiambo, Peter S., David H. Gent, Lucky K. Mehra, David Christie, and Roger Magarey. "Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients." PeerJ 5 (June 20, 2017): e3465. http://dx.doi.org/10.7717/peerj.3465.
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Empirical and mechanistic modeling indicate that pathogens transmitted via aerially dispersed inoculum follow a power law, resulting in dispersive epidemic waves. The spread parameter (b) of the power law model, which is an indicator of the distance of the epidemic wave front from an initial focus per unit time, has been found to be approximately 2 for several animal and plant diseases over a wide range of spatial scales under conditions favorable for disease spread. Although disease spread and epidemic expansion can be influenced by several factors, the stability of the parameter b over multiple epidemic years has not been determined. Additionally, the size of the initial epidemic area is expected to be strongly related to the final epidemic extent for epidemics, but the stability of this relationship is also not well established. Here, empirical data of cucurbit downy mildew epidemics collected from 2008 to 2014 were analyzed using a spatio-temporal model of disease spread that incorporates logistic growth in time with a power law function for dispersal. Final epidemic extent ranged from 4.16 ×108 km2 in 2012 to 6.44 ×108 km2 in 2009. Current epidemic extent became significantly associated (P < 0.0332; 0.56 < R2 < 0.99) with final epidemic area beginning near the end of April, with the association increasing monotonically to 1.0 by the end of the epidemic season in July. The position of the epidemic wave-front became exponentially more distant with time, and epidemic velocity increased linearly with distance. Slopes from the temporal and spatial regression models varied with about a 2.5-fold range across epidemic years. Estimates of b varied substantially ranging from 1.51 to 4.16 across epidemic years. We observed a significant b ×time (or distance) interaction (P < 0.05) for epidemic years where data were well described by the power law model. These results suggest that the spread parameter b may not be stable over multiple epidemic years. However, b ≈ 2 may be considered the lower limit of the distance traveled by epidemic wave-fronts for aerially transmitted pathogens that follow a power law dispersal function.
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Zhang, Yun, and Jin-Xuan Yang. "Contagion dynamics in multilayer networks with community structure." International Journal of Modern Physics B 35, no. 17 (July 2, 2021): 2150179. http://dx.doi.org/10.1142/s0217979221501794.
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The study of contagion dynamics in multilayer networks has become a hot topic. Networks have the characteristics of community structure. In this work, we present a comprehensive epidemic spreading model in multilayer networks with community structure. We consider the effects of population mobility, natural mortality and natural birth rate on population dynamics and contagion dynamics. The population size is determined by natural mortality and natural birth rate. The global and local epidemic thresholds are obtained. We analyze the factors which affect epidemic thresholds. The population mobility has no effect on the global epidemic threshold, but it can affect epidemic thresholds of each community. To control outbreaks of epidemics in influential communities can well control the spreading of diseases in the whole system. It is conductive to controlling outbreak of epidemics by reducing the internal average degree and interconnected links in influential communities. Numerical simulations on synthetic networks further support and enrich our conclusions.
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Sackett, Kathryn E., and Christopher C. Mundt. "The Effects of Dispersal Gradient and Pathogen Life Cycle Components on Epidemic Velocity in Computer Simulations." Phytopathology® 95, no. 9 (September 2005): 992–1000. http://dx.doi.org/10.1094/phyto-95-0992.
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The velocity of expansion of focal epidemics was studied using an updated version of the simulation model EPIMUL, with model parameters relevant to wheat stripe rust. The modified power law, the exponential model, and Lambert's general model were fit to primary disease gradient data from an artificially initiated field epidemic of stripe rust and employed to describe dispersal in simulations. The exponential model, which fit the field data poorly (R 2 = 0.728 to 0.776), yielded an epidemic that expanded as a traveling wave (i.e., at a constant velocity), after an initial buildup period. Both the modified power law and the Lambert model fit the field data well (R2 = 0.962 to 0.988) and resulted in dispersive epidemic waves (velocities increased over time for the entire course of the epidemic). The field epidemic also expanded as a dispersive wave. Using parameters based on the field epidemic and modified power law dispersal as a baseline, life cycle components of the pathogen (lesion growth rate, latent period, infectious period, and multiplication rate) and dispersal gradient steepness were varied within biologically reasonable ranges for this disease to test their effect on dispersive wave epidemics. All components but the infectious period had a strong influence on epidemic velocity, but none changed the general pattern of velocity increasing over time.
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Blum, Paul Richard. "Epidemic and the Individual: Renaissance Understandings of the Plague in View of Modern Experiences." Roczniki Kulturoznawcze 11, no. 3 (December 16, 2020): 53–68. http://dx.doi.org/10.18290/rkult20113-5.
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Epidemia a jednostka: renesansowe rozumienie plag z perspektywy nowoczesnych doświadczeń
Epidemie są wyzwaniem dla indywidualizmu. Chociaż myślimy o chorobach w kategoriach osobistego cierpienia i wyborów, plagi od dawna dotykają wspólnot i społeczności. Epidemie zwracają perspektywę na zbiorowość, transcendencję i to, co zewnętrzne, a strach, terapia i opieka stają się bardziej uniwersalne niż indywidualne. Oto wnioski, które możemy wyciągnąć z teorii epidemii filozofów renesansu. Marsilio Ficino (1433–1499) udzielił „Rady przeciwko zarazie” (Consilio contro la pestilenzia), podkreślając harmonię ciała ze środowiskiem (powietrze i planety). Girolamo Fracastoro (1477–1553) stworzył pierwszy opis kiły (syfilisu) zarówno pod względem naukowym, jak i poetyckim (Syphilis sive de morbo gallico). Wymyślił nazwę dla tej dolegliwości. Postrzegał aktywność seksualną jako jedno z typowych zachowań międzyludzkich. Troska o zdrowie wymaga szacunku dla innych, a obwinianie innych (jak w przypadku „choroby francuskiej”) jest bezużyteczne. Jean Fernel (1497-1558) wezwał do ściśle medycznych badań epidemii, jednocześnie przyznając, że dane są niewystarczające, stąd tytuł jego książki De abditis rerum causis („Ukryte przyczyny”). W ten sposób wyjaśnił irracjonalne zachowanie populacji i niektórych uczonych. Zadaniem jest przeżycie w niepewności i powstrzymanie epidemii poprzez powstrzymanie nieznanego.
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Karpova, L. S., K. M. Volik, K. A. Stolyarov, N. M. Popovtseva, T. P. Stolyarova, A. A. Sominina, and E. I. Burtseva. "FEATURES OF EPIDEMIC PROCESS OF INFLUENZA A(H1N1)PDM09 AND A(H3N2) IN RUSSIA FROM 2009 TO 2017." Problems of Virology, Russian journal 63, no. 4 (August 20, 2018): 177–84. http://dx.doi.org/10.18821/0507-4088-2018-63-4-177-184.
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The goal of this work is to compare the key parameters of influenza epidemics of different etiology. Four epidemics of influenza with predominance of influenza A(H1N1)pdm09 and 4 epidemics of influenza A(H3N2) were analyzed using the database of the Federal State Research Institute of Influenza on morbidity, hospitalization, deaths from influenza in 59 cities in the period from 2009 to 2017. The intensity of epidemics involving the influenza A(H1N1)pdm09 decreased from high to medium, while the intensity of epidemics of influenza A(H3N2) increased from low to medium. In the epidemic of influenza A(H1N1)pdm09 in the total population, the incidence of influenza and ARI decreased by a factor of 1.6, while the mortality among patients decreased by a factor of 1.7 in all age groups, except for those over 65 years, for whom the incidence and mortality increased by factors of 1.4 of 2.3, respectively. In the epidemic of A(H3N2), a trend for increasing morbidity and mortality was more pronounced among individuals older than 65 years. Pandemic influenza remains the leading cause of deaths. Among the dead in the epidemic of influenza A(H1N1)pdm09, the proportion of young individuals decreased (including a fourfold decrease of lethality in pregnant women), while the proportion of persons over 65 years increased 7.8 times; in the epidemic of influenza A(H3N2) only 2.5-fold increase was observed. In the epidemic of influenza A(H1N1)pdm09, the proportion of lethality increased among people with cardiovascular diseases and diseases of the internal organs; in the epidemic of influenza A(H3N2), the proportion of lethality increased among people with immunodeficiency, diseases of the internal organs and respiratory system.
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Kleczkowski, A., and C. A. Gilligan. "Parameter estimation and prediction for the course of a single epidemic outbreak of a plant disease." Journal of The Royal Society Interface 4, no. 16 (July 17, 2007): 865–77. http://dx.doi.org/10.1098/rsif.2007.1036.
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Many epidemics of plant diseases are characterized by large variability among individual outbreaks. However, individual epidemics often follow a well-defined trajectory which is much more predictable in the short term than the ensemble (collection) of potential epidemics. In this paper, we introduce a modelling framework that allows us to deal with individual replicated outbreaks, based upon a Bayesian hierarchical analysis. Information about ‘similar’ replicate epidemics can be incorporated into a hierarchical model, allowing both ensemble and individual parameters to be estimated. The model is used to analyse the data from a replicated experiment involving spread of Rhizoctonia solani on radish in the presence or absence of a biocontrol agent, Trichoderma viride . The rate of primary (soil-to-plant) infection is found to be the most variable factor determining the final size of epidemics. Breakdown of biological control in some replicates results in high levels of primary infection and increased variability. The model can be used to predict new outbreaks of disease based upon knowledge from a ‘library’ of previous epidemics and partial information about the current outbreak. We show that forecasting improves significantly with knowledge about the history of a particular epidemic, whereas the precision of hindcasting to identify the past course of the epidemic is largely independent of detailed knowledge of the epidemic trajectory. The results have important consequences for parameter estimation, inference and prediction for emerging epidemic outbreaks.
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Karpova, L. S., Y. M. Pelikh, and K. A. Stolyarov. "The Influenza Situation in the World and the Epidemic in Russia in Season 2016 - 2017." Epidemiology and Vaccine Prevention 16, no. 4 (August 20, 2017): 9–21. http://dx.doi.org/10.31631/2073-3046-2017-16-4-9-21.
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Analysis of the situation for influenza in the world are drawn according to data published on the websites of the WHO, and the epidemic 2016 - 2017 in Russia - database «Research Influenza Institute» on the weekly morbidity, hospitalization, deaths from influenza in 61 observed the city. The influenza epidemic 2016 - 2017 started early, the duration of its in cities and in the country was longer and higher was the incidence of influenza and ARI in the cities and in the country than in the epidemic 2015 - 2016. But the epidemic of influenza A(H3N2) 2016 - 2017 there was less incidence morbidity at the peak, the frequency of hospitalization and, especially, mortality from influenza in the total population by 20 times, and in all age groups, especially among persons older than 65 years by 17.5 times, compared to the epidemic 2015 - 2016, caused by the pandemic virus influenza A(H1N1)pdm09. The peculiarities of the epidemic 2016 -17 according to the Federal districts, first of all, the absence of a second rise in the incidence of influenza in the South of Russia. The intensity of the epidemics of influenza A(H3N2) seasons 2016 - 17 and 2014 - 2015 - was average, and the epidemic A(H1N1) pdm09 2015 - 2016 - high. The case fatality rate in epidemics involving the influenza A(H3N2) remains significantly lower than in the epidemic caused by the pandemic virus influenza A(H1N1)pdm09.
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Ball, Frank, and Owen D. Lyne. "Stochastic multi-type SIR epidemics among a population partitioned into households." Advances in Applied Probability 33, no. 1 (March 2001): 99–123. http://dx.doi.org/10.1017/s000186780001065x.
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We consider a stochastic model for the spread of an SIR (susceptible → infective → removed) epidemic among a closed, finite population that contains several types of individuals and is partitioned into households. The infection rate between two individuals depends on the types of the transmitting and receiving individuals and also on whether the infection is local (i.e., within a household) or global (i.e., between households). The exact distribution of the final outcome of the epidemic is outlined. A branching process approximation for the early stages of the epidemic is described and made fully rigorous, by considering a sequence of epidemics in which the number of households tends to infinity and using a coupling argument. This leads to a threshold theorem for the epidemic model. A central limit theorem for the final outcome of epidemics which take off is derived, by exploiting an embedding representation.
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Zixiao, Liu, Pan Dandan, and Ju Fei. "Research on the psychological root and transmission mechanism of rumours in major epidemics based on the perspective of psychoanalysis." Psychoanalysis and Psychotherapy in China 4, no. 2 (December 17, 2021): 170–81. http://dx.doi.org/10.33212/ppc.v4n2.2021.170.
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Since the Covid-19 epidemic, many rumours have been generated under the main theme of a whole people fighting the epidemic together. From the standpoint of depth psychology, a psychoanalytic perspective has its own advantages and unique research value on the psychological roots of rumours in major epidemics and their mechanisms of transmission, which this article discusses, along with the anxiety and fear created by the life instinct, the elements of attack and projection under the death instinct, and conjectures how the role of Lacan’s postulation that the unconscious is constituted like language all play a role as main causes of a current epidemic of rumours. The transmission mechanisms of epidemic rumours are the following: the spreading of panic caused by the interruption of emotional connection, aggressive spreading of rumours caused by hostility in processes of identification, and problems in mechanisms of projective identification, and the combined effect of audiovisual media. Furthermore, the authors make specific suggestions on how to deal with rumours in major epidemics, so as to improve understanding and response to these in cases of major epidemics.
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Lestayo O'Farrill, Zurina, José Luís Hernández Cáceres, and Esperanza O'Farrill Mons. "Nonlinear Analysis of Guillain Barré Time Series to Elucidate Its Epidemiology." ISRN Epidemiology 2013 (December 24, 2013): 1–5. http://dx.doi.org/10.5402/2013/635971.
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The etiology of Guillain Barré Syndrome (GBS) is not fully clarified, and there is a lack of agreement concerning its putative epidemic character. The low incidence rate of this disease is a disadvantage for employing the traditional statistical methods used in the analysis of epidemics. The objective of this paper is to clarify the GBS epidemic behavior applying a nonlinear time series identification approach. The authors obtained one time series of GBS and nine series of classical infectious epidemics (5 national and 4 international). These data were processed with advanced techniques of statistical time series analysis. This paper shows that GBS behaves similar to the other time series of classical epidemic studied. It corresponds to a nonlinear dynamics, with a point attractor. The spectral analysis pointed to an annual periodicity, and preference for the warmest month of the year was found. These results might suggest that Guillain Barré Syndrome has an epidemic behavior. The adequacy of nonlinear methods for analyzing the dynamics of epidemics, particularly those with low incidence rate, such as GBS was revealed.
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Te Beest, D. E., N. D. Paveley, M. W. Shaw, and F. van den Bosch. "Disease–Weather Relationships for Powdery Mildew and Yellow Rust on Winter Wheat." Phytopathology® 98, no. 5 (May 2008): 609–17. http://dx.doi.org/10.1094/phyto-98-5-0609.
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Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance.
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Earn, David J. D., Junling Ma, Hendrik Poinar, Jonathan Dushoff, and Benjamin M. Bolker. "Acceleration of plague outbreaks in the second pandemic." Proceedings of the National Academy of Sciences 117, no. 44 (October 19, 2020): 27703–11. http://dx.doi.org/10.1073/pnas.2004904117.
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Historical records reveal the temporal patterns of a sequence of plague epidemics in London, United Kingdom, from the 14th to 17th centuries. Analysis of these records shows that later epidemics spread significantly faster (“accelerated”). Between the Black Death of 1348 and the later epidemics that culminated with the Great Plague of 1665, we estimate that the epidemic growth rate increased fourfold. Currently available data do not provide enough information to infer the mode of plague transmission in any given epidemic; nevertheless, order-of-magnitude estimates of epidemic parameters suggest that the observed slow growth rates in the 14th century are inconsistent with direct (pneumonic) transmission. We discuss the potential roles of demographic and ecological factors, such as climate change or human or rat population density, in driving the observed acceleration.
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Nakamura, Gilberto M., Ana Carolina P. Monteiro, George C. Cardoso, and Alexandre S. Martinez. "Finite Symmetries in Agent-Based Epidemic Models." Mathematical and Computational Applications 24, no. 2 (April 23, 2019): 44. http://dx.doi.org/10.3390/mca24020044.
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Predictive analysis of epidemics often depends on the initial conditions of the outbreak, the structure of the afflicted population, and population size. However, disease outbreaks are subjected to fluctuations that may shape the spreading process. Agent-based epidemic models mitigate the issue by using a transition matrix which replicates stochastic effects observed in real epidemics. They have met considerable numerical success to simulate small scale epidemics. The problem grows exponentially with population size, reducing the usability of agent-based models for large scale epidemics. Here, we present an algorithm that explores permutation symmetries to enhance the computational performance of agent-based epidemic models. Our findings bound the stochastic process to a single eigenvalue sector, scaling down the dimension of the transition matrix to o ( N 2 ) .
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Karpova, L. S., N. M. Popovtseva, T. P. Stolyarova, and D. M. Danilenko. "Influence of the ways of spreading influenza epidemics across the territory Russia on the peculiarities of the epidemic process in various Federal districts." Journal Infectology 13, no. 4 (December 27, 2021): 90–99. http://dx.doi.org/10.22625/2072-6732-2021-13-4-90-99.
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Aims. Show the ways of spreading influenza epidemics across the territory of Russia over a long period (1968–2019) and their influence on the incidence of influenza and ARVI in total and separately influenza A (H1N1), A (H3N2) and B in the Federal Districts in the period from 2009 to 2019.Materials and methods. The analysis of influenza epidemics was carried out according to the computer database of the National center for influenza.Results. A retrospective analysis of influenza epidemics shows the absence of inter-epidemic seasons after 1986, the increase in epidemics of mixed etiology and different routes of entry and spread of influenza viruses in Russia. During the circulation of the influenza A (H1N1)pdm09 virus, influenza epidemics were mainly of mixed etiology. The main causative agents of epidemics entered the territory of Russia more often from the west and in both ways, and from the west and from the east. In the next season, the main pathogen changed, and the path of the virus circulating in the previous season also changed. Influenza viruses of different types A and B usually diverged in time. Influenza viruses of the same type A, but of different subtypes, usually spread in different directions, with one of them having a limited distribution in the districts. The tendency of greater intensity of the epidemic process in the districts involved in the epidemic first is shown.Conclusions. 2009 to 2019 the incidence was higher in the Northwestern and Ural districts of the European part of Russia. One of the reasons for the high morbidity in these districts is the predominance of the western route of influenza viruses entering the territory of Russia and the high intensity of the epidemic process in the districts that were the first to be involved in the epidemic.
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Zhao, Xixi, Meijia Li, Naem Haihambo, Xinni Wang, Bin Wang, Meirong Sun, Mingrou Guo, and Chuanliang Han. "Periodic Characteristics of Hepatitis Virus Infections From 2013 to 2020 and Their Association With Meteorological Factors in Guangdong, China: Surveillance Study." JMIR Public Health and Surveillance 9 (June 15, 2023): e45199. http://dx.doi.org/10.2196/45199.
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Background In the past few decades, liver disease has gradually become one of the major causes of death and illness worldwide. Hepatitis is one of the most common liver diseases in China. There have been intermittent and epidemic outbreaks of hepatitis worldwide, with a tendency toward cyclical recurrences. This periodicity poses challenges to epidemic prevention and control. Objective In this study, we aimed to investigate the relationship between the periodic characteristics of the hepatitis epidemic and local meteorological elements in Guangdong, China, which is a representative province with the largest population and gross domestic product in China. Methods Time series data sets from January 2013 to December 2020 for 4 notifiable infectious diseases caused by hepatitis viruses (ie, hepatitis A, B, C, and E viruses) and monthly data of meteorological elements (ie, temperature, precipitation, and humidity) were used in this study. Power spectrum analysis was conducted on time series data, and correlation and regression analyses were performed to assess the relationship between the epidemics and meteorological elements. Results The 4 hepatitis epidemics showed clear periodic phenomena in the 8-year data set in connection with meteorological elements. Based on the correlation analysis, temperature demonstrated the strongest correlation with hepatitis A, B, and C epidemics, while humidity was most significantly associated with the hepatitis E epidemic. Regression analysis revealed a positive and significant coefficient between temperature and hepatitis A, B, and C epidemics in Guangdong, while humidity had a strong and significant association with the hepatitis E epidemic, and its relationship with temperature was relatively weak. Conclusions These findings provide a better understanding of the mechanisms underlying different hepatitis epidemics and their connection to meteorological factors. This understanding can help guide local governments in predicting and preparing for future epidemics based on weather patterns and potentially aid in the development of effective prevention measures and policies.
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Ahmad, Wasim, Sayed Tauleha, Mohammad Zulkifle, and Ghulamuddin Sofi. "Role of Unani Medicine in Prevention and Treatment of Waba (Epidemics) including COVID-19: A Review." European Journal of Cell Science 2, no. 1 (August 15, 2020): 01–09. http://dx.doi.org/10.34154/2020-ejcs-0201-01-09/euraass.
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Mankind has faced many hardships like natural disaster, drought and epidemics. Study focuses on epidemics caused by microbes.Unani medicine has a long experience in treating epidemic diseases because its history is as old as the history of human being itself. More or less entire of the civilisations throughout the history became the basis for evolution of Unani medicine. Hippocrates (460-380BC) regarded it asbothart and science, discussed the epidemics and wrote a book on Epidemics. Body is assumed healthy when the humours are balanced. So, Unani scholars have rightly said Fa’il (Active agent) is not able to produce any change (Actions & Reactions) in the body without the prior presence of Munfa’il(Pertinent) having the capacity to accept it like in Waba(epidemic). The aim is to explore the fundamental concept of Waba from the Unani literature and understand COVID-19 in reference to existing literature of Unani medicine. The literature of Unani medicine was surveyed for concept of Waba(Epidemic) & related concepts. Internet was used to access indexed papers using search engines like Medline, PubMed, Science Direct, etc. Logical preventive strategies like quarantine, and useof fumigants, prophylactic drugs are mentioned in Unani literature that have been used in epidemics with flue like symptoms. This knowledge and experience may be used for achieving methods for prophylaxis, cure or add on therapeutic measures for COVID-19 epidemic.
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Rath, Padmalaya, and Shib Narayan Jana. "A Brief Account of Homoeopathic Approach to Fight COVID-19 Disaster." Homœopathic Links 33, no. 03 (September 2020): 147–52. http://dx.doi.org/10.1055/s-0040-1715889.
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AbstractDisasters are unfortunate but integral part of civilisation. While the incidence of disaster cannot be prevented altogether, the effects can be modified to the extent that there will be minimum or no loss of life, minimum loss to property and quick restoration to normalcy. Virtually in many instances effects can be reduced to nil or negligible if sufficient diligence is practiced. Epidemic diseases are regarded as disasters too. Homoeopathy is a medical system of therapeutics which claims to have effective intervention in epidemics. Any system of medicine that offers to intervene in any epidemic should be embraced. Epidemics have occurred in the past not only in India but in other countries as well, such as Cholera, Asian flu, Spanish flu, severe acute respiratory syndrome and Avian influenza. When an epidemic spreads in wider geographical area and affects large number of people, it is termed as pandemic. Coronavirus disease 2019 (COVID-19) is a pandemic that began in December 2019.Homoeopathic system of medicine claims to have effective treatment in epidemics. But hardly any effort seems to have been made to correlate the limited documented studies on epidemics that may consolidate the positive results of homoeopathy in such a way that can help policy makers to give a serious thought to the fact that homoeopathy can be trusted to combat epidemic diseases. This article involves data collection using existing published articles on case series/individual cases in peer-reviewed journals assessing the applicability of homoeopathy in epidemics/pandemics and in COVID-19. With such a background finding suitable solutions is a necessary step toward prevention and treatment of epidemic diseases.
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Parnell, S., T. R. Gottwald, N. J. Cunniffe, V. Alonso Chavez, and F. van den Bosch. "Early detection surveillance for an emerging plant pathogen: a rule of thumb to predict prevalence at first discovery." Proceedings of the Royal Society B: Biological Sciences 282, no. 1814 (September 7, 2015): 20151478. http://dx.doi.org/10.1098/rspb.2015.1478.
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Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E ( q *). We show that E ( q *) = r / (N /Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally.
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El Koufi, Amine, Abdelkrim Bennar, and Noura Yousfi. "A Stochastic Switched Epidemic Model with Two Epidemic Diseases." Complexity 2021 (March 23, 2021): 1–13. http://dx.doi.org/10.1155/2021/5560538.
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In this paper, we study a stochastic epidemic model with double epidemics which includes white noise and telegraph noise modeled by Markovian switching. Sufficient conditions for the extinction and persistence of the diseases are established. In the end, some numerical simulations are presented to demonstrate our analytical results.
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Yao, Yulin. "The Role of New Media Technologies in Epidemics -- Taking the 2014 Ebola outbreak as an example." Highlights in Science, Engineering and Technology 109 (July 24, 2024): 249–55. http://dx.doi.org/10.54097/whrnhe60.
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The Ebola outbreak in 2014 had a significant impact on the global public health system. However, New Media also played a crucial role. Before the outbreak of the epidemic, the role of New Media in the pandemic had already begun to receive attention from some scholars. The most unique aspect of the 2014 Ebola epidemic was the large-scale integration of new media and epidemic control. This paper analyzes the use of New Media during the epidemic to explore its impact on public opinion, information dissemination, and public health communication. The findings provide insights into the potential of New Media in future epidemic response and management.In this paper, the performance of New Media in the Ebola epidemic is analyzed, and it is concluded that New Media can facilitate cooperation among various parties, alleviate the pressure of the epidemic, promote the development of epidemic research, simplify epidemic control planning, and strengthen disease control. This paper also suggests the transmission of misinformation and the problems of epidemic anxiety and "Vaccine Hesitancy" brought about by new media technologies and their solutions, in order to prepare for future epidemics that may occur.
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Ball, Frank, and Philip O'Neill. "Strong Convergence of Stochastic Epidemics." Advances in Applied Probability 26, no. 3 (September 1994): 629–55. http://dx.doi.org/10.2307/1427812.
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This paper is concerned with a model for the spread of an epidemic in a closed, homogeneously mixing population in which new infections occur at rate f(x, y) and removals occur at rate g(x, y), where x and y are the numbers of susceptible and infective individuals, respectively, and f and g are arbitrary but specified positive real-valued functions. Sequences of such epidemics, indexed by the initial number of susceptibles n, are considered and conditions are derived under which the epidemic processes converge almost surely to a birth and death process as n tends to infinity. Thus a threshold theorem for such an epidemic model is obtained. The results are extended to models which incorporate immigration and emigration of susceptibles. The theory is illustrated by several examples of models taken from the epidemic literature. Generalizations to multipopulation epidemics are discussed briefly.