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1
Moilanen, Ulla, and Sofia Paasikivi. "Esihistoriallisten tartuntatautien ja epidemioiden tutkimusmahdollisuudet Suomessa." Ennen ja nyt: Historian tietosanomat 23, no. 2 (June 1, 2023): 5–18. http://dx.doi.org/10.37449/ennenjanyt.125929.
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Epidemioiden historiallinen tutkimus painottaa usein kirjallisia lähteitä, mutta tartuntataudit ovat olleet ihmisten seuralaisina esihistoriallisista ajoista lähtien. Käsittelemme artikkelissa esihistoriallisten epidemioiden tutkimuskeinoja. Keskitymme muinaisten taudinaiheuttajien luonnontieteellisiin analyysimenetelmiin ja arkeologisessa aineistossa näkyviin epidemioiden epäsuoriin vaikutuksiin. Epidemioilla voi olla demografisia, poliittisia, sosiaalisia, uskonnollisia ja taloudellisia vaikutuksia, vaikka myös muut tekijät voivat laukaista kriisejä. Mahdollisista kriiseistä kertovat ilmiöt ovat usein monitulkintaisia, mutta minkä tahansa kriisiajanjakson tunnistaminen voi johtaa myös epidemian jäljille, sillä epidemiat liittyvät tyypillisesti muihin väestökriiseihin. Myös ilmastotekijät vaikuttavat tautien esiintymiseen. Esitämme, että arkeologisen aineiston monitieteisellä tutkimuksella voidaan tehdä päätelmiä kriisien kokonaisvaikutuksista ja että paras tapa esihistoriallisten epidemioiden tutkimukseen on kiinnittää huomiota sekä laajoihin että paikallisiin, pienimuotoisiin ilmiöihin ja arkeologisen aineiston piirteisiin monesta eri näkökulmasta. Historical research of epidemics often emphasises literary sources, but infectious diseases have accompanied humans since prehistoric times. This article discusses the ways prehistoric epidemics can be identified and studied. We focus on scientific analyses of ancient pathogens and the indirect impact of epidemics that may be visible in archaeological material. Epidemics can have demographic, political, social, religious and economic impacts, although other factors can also trigger similar crises. The phenomena are often complicated and challenging to identify and interpret. However, identifying any period of crisis in prehistory can also lead to the identification of an epidemic, since epidemics are typically linked to other population crises. Climate factors may also influence the emergence of diseases. The interdisciplinary study of archaeological data allows conclusions to be drawn about the overall impact of crises. Thus, the best way to study prehistoric epidemics is to focus on both large-scale and local, small-scale phenomena.
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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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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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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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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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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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Li, Xin, Xingyuan He, Lu Zhou, and Shushu Xie. "Impact of Epidemics on Enterprise Innovation: An Analysis of COVID-19 and SARS." Sustainability 14, no. 9 (April 26, 2022): 5223. http://dx.doi.org/10.3390/su14095223.
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This study analyzes the impact of SARS and COVID-19, the two most severe epidemics to occur in China since the 21st century, on corporate innovation, in order to find a path for sustained innovation growth under the epidemic. For COVID-19, the analysis used data from China’s A-share-listed companies from 2019 to 2020; a longer period (1999–2006) and a wider sample of Chinese industrial enterprises were used for the SARS epidemic. The empirical model was constructed using the difference-in-differences method. Both COVID-19 and SARS were found to have significantly reduced enterprise innovation. However, the effect of SARS disappeared after two years. For COVID-19, information asymmetry, financing constraints, and economic policy uncertainty moderated the epidemic’s effect on innovation. The results show that financing constraints and economic policy uncertainty reduce the epidemic’s negative impact. However, while most previous studies have found that an epidemic reduces the information asymmetry between investors and enterprises in the short term, thus raising enterprise innovation, we found that information asymmetry aggravated the epidemic’s negative impact. These findings can be applied to alleviate the current epidemic’s negative impact as well as improve enterprise innovation thereafter.
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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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Fitzpatrick, Mike. "Epidemics of epidemics." British Journal of General Practice 59, no. 566 (September 1, 2009): 705. http://dx.doi.org/10.3399/bjgp09x471747.
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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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Newson, R., D. Strachan, E. Archibald, J. Emberlin, P. Hardaker, and C. Collier. "Acute asthma epidemics, weather and pollen in England, 1987-1994." European Respiratory Journal 11, no. 3 (March 1, 1998): 694–701. http://dx.doi.org/10.1183/09031936.98.11030694.
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Recent epidemics of acute asthma have caused speculation that, if their causes were known, early warnings might be feasible. In particular, some epidemics seemed to be associated with thunderstorms. We wondered what risk factors predicting epidemics could be identified. Daily asthma admissions counts during 1987-1994, for two age groups (0-14 yrs and > or = 15 yrs), were measured using the Hospital Episodes System (HES). Epidemics were defined as combinations of date, age group and English Regional Health Authority (RHA) with exceptionally high asthma admission counts compared to the predictions of a log-linear autoregression model. They were compared with control days 1 week before and afterwards, regarding seven meteorological variables and 5 day average pollen counts for four species. Fifty six asthma epidemics were identified. The mean density of sferics (lightning flashes), temperature and rainfall on epidemic days were greater than those on control days. High sferics densities were overrepresented in epidemics. Simultaneously high sferics and grass pollen further increased the probability of an epidemic, but only to 15% (95% confidence interval 2-45%). Two thirds of epidemics were not preceded by thunderstorms. Thunderstorms and high grass pollen levels precede asthma epidemics more often than expected by chance. However, most epidemics are not associated with thunderstorms or unusual weather conditions, and most thunderstorms, even following high grass pollen levels, do not precede epidemics. An early warning system based on the indicators examined here would, therefore, detect few epidemics and generate an unacceptably high rate of false alarms.
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Mokkapatti, Rupa. "An experimental double-blind study to evaluate the use of Euphrasia in preventing conjunctivitis." British Homeopathic Journal 81, no. 01 (January 1992): 22–24. http://dx.doi.org/10.1016/s0007-0785(05)80288-1.
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AbstractA double-blind study using Euphrasia 30c or placebo was carried out during an epidemic of viral conjunctivitis. Nine hundred and ninety-four subjects were available at follow-up, when 48 subjects in the group given Euphrasia and 43 subjects in the placebo group had signs and symptoms of conjunctivitis, a difference which was not statistically significant. The protocol by which Euphrasia was tried may be used without change to scientifically confirm the efficacy of a genus epidemicus. The concept of genus epidemicus lends itself well to experimental double-blind studies in homœopathy during epidemics.
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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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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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Springbett, A. J., K. MacKenzie, J. A. Woolliams, and S. C. Bishop. "The Contribution of Genetic Diversity to the Spread of Infectious Diseases in Livestock Populations." Genetics 165, no. 3 (November 1, 2003): 1465–74. http://dx.doi.org/10.1093/genetics/165.3.1465.
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Abstract This article uses stochastic simulations with a compartmental epidemic model to quantify the impact of genetic diversity within animal populations on the transmission of infectious disease. Genetic diversity is defined by the number of distinct genotypes in the population conferring resistance to microparasitic (e.g., viral or bacterial) infections. Scenarios include homogeneous populations and populations composed of few (finite-locus model) or many (infinitesimal model) genotypes. Genetic heterogeneity has no impact upon the expected value of the basic reproductive ratio (the primary description of the transmission of infection) but affects the variability of this parameter. Consequently, increasing genetic heterogeneity is associated with an increased probability of minor epidemics and decreased probabilities of both major (catastrophic) epidemics and no epidemics. Additionally, heterogeneity per se is associated with a breakdown in the expected relationship between the basic reproductive ratio and epidemic severity, which has been developed for homogeneous populations, with increasing heterogeneity generally resulting in fewer infected animals than expected. Furthermore, increased heterogeneity is associated with decreased disease-dependent mortality in major epidemics and a complex trend toward decreased duration of these epidemics. In summary, more heterogeneous populations are not expected to suffer fewer epidemics on average, but are less likely to suffer catastrophic epidemics.
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Marani, Marco, Gabriel G. Katul, William K. Pan, and Anthony J. Parolari. "Intensity and frequency of extreme novel epidemics." Proceedings of the National Academy of Sciences 118, no. 35 (August 23, 2021): e2105482118. http://dx.doi.org/10.1073/pnas.2105482118.
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Observational knowledge of the epidemic intensity, defined as the number of deaths divided by global population and epidemic duration, and of the rate of emergence of infectious disease outbreaks is necessary to test theory and models and to inform public health risk assessment by quantifying the probability of extreme pandemics such as COVID-19. Despite its significance, assembling and analyzing a comprehensive global historical record spanning a variety of diseases remains an unexplored task. A global dataset of historical epidemics from 1600 to present is here compiled and examined using novel statistical methods to estimate the yearly probability of occurrence of extreme epidemics. Historical observations covering four orders of magnitude of epidemic intensity follow a common probability distribution with a slowly decaying power-law tail (generalized Pareto distribution, asymptotic exponent = −0.71). The yearly number of epidemics varies ninefold and shows systematic trends. Yearly occurrence probabilities of extreme epidemics, Py, vary widely: Py of an event with the intensity of the “Spanish influenza” (1918 to 1920) varies between 0.27 and 1.9% from 1600 to present, while its mean recurrence time today is 400 y (95% CI: 332 to 489 y). The slow decay of probability with epidemic intensity implies that extreme epidemics are relatively likely, a property previously undetected due to short observational records and stationary analysis methods. Using recent estimates of the rate of increase in disease emergence from zoonotic reservoirs associated with environmental change, we estimate that the yearly probability of occurrence of extreme epidemics can increase up to threefold in the coming decades.
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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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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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Shrum, Wesley, John Aggrey, Andre Campos, Janaina Pamplona da Costa, Jan Joseph, Pablo Kreimer, Rhiannon Kroeger, et al. "Who’s afraid of Ebola? Epidemic fires and locative fears in the Information Age." Social Studies of Science 50, no. 5 (June 29, 2020): 707–27. http://dx.doi.org/10.1177/0306312720927781.
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Epidemics have traditionally been viewed as the widespread occurrence of infectious disease within a community, or a sudden increase above what is typical. But modern epidemics are both more and less than the diffusion of viral entities. We argue that epidemics are ‘fire objects’, using a term coined by Law and Singleton: They generate locative fears through encounters that focus attention on entities that are unknown or imprecisely known, transforming spaces and humans into indeterminate dangers, alternating appearance and absence. The Ebola epidemic of 2014 had more complex impacts than the number of infections would suggest. We employ multi-sited qualitative interviews to argue that locative fear is the essence of modern global epidemics. In the discussion we contrast Ebola with both the Zika epidemic that followed and the ongoing coronavirus (COVID-19) pandemic.
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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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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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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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Miettinen, I. T., O. Zacheus, C.-H. von Bonsdorff, and T. Vartiainen. "Waterborne epidemics in Finland in 1998-1999." Water Science and Technology 43, no. 12 (June 1, 2001): 67–71. http://dx.doi.org/10.2166/wst.2001.0713.
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Fourteen waterborne epidemics occurred in Finland during 1998-1999. About 7,300 illness cases were registered in these outbreaks. All except one of the waterborne epidemics were associated with undisinfected groundwaters. An equal number of waterborne epidemics occurred in public and private water systems, but most cases of illness occurred in public water systems. The three largest epidemics comprised 6,700 illness cases. Insufficient purification treatment unable to remove Norwalk-like viruses caused the only waterborne epidemic in a surface water plant. The main reasons for groundwater outbreaks were floods and surface runoffs which contaminated water. Norwalk-like viruses caused eight and Campylobacter three of the outbreaks. In two cases the epidemic ceased by the exhaustion of susceptible persons in the exposed community but in most cases it was terminated by changing the water source, boiling the drinking water, and starting chlorination.
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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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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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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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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.
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Ball, Frank, and Philip O'Neill. "Strong Convergence of Stochastic Epidemics." Advances in Applied Probability 26, no. 03 (September 1994): 629–55. http://dx.doi.org/10.1017/s000186780002646x.
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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.
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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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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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Nguyen, Quang Thi Thieu, Dao Le Trang Anh, and Christopher Gan. "Epidemics and Chinese firms' stock returns: is COVID-19 different?" China Finance Review International 11, no. 3 (July 8, 2021): 302–21. http://dx.doi.org/10.1108/cfri-03-2021-0053.
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PurposeThis study investigates the Chinese stocks' returns during different epidemic periods to assess their effects on firms' market performance.Design/methodology/approachThe study employs an event study method on more than 3,000 firms listed on Shanghai and Shenzhen stock exchanges during periods of SARS, H5N1, H7N9 and COVID-19FindingsEpidemics' effect on firms' stock returns is persistent up to 10 days after the event dates. Although the impact varies with types and development of the disease, most firms experience a negative impact of the epidemics. Among the epidemics, COVID-19 has the greatest impact, especially when it grows into a pandemic. The epidemics' impact is uneven across industries. In addition, B-shares and stocks listed on Shanghai Stock Exchange are more negatively influenced by the epidemic than A-shares and those listed on Shenzhen Stock Exchange.Research limitations/implicationsThe results of the study contribute to the limited literature on the effects of disease outbreaks as an economic shock on firm market performance. Given the possibility of other epidemics in the future, the study provides guidance for investors in designing an appropriate investing strategy to cope with the epidemic shocks to the market.Originality/valueThe research is novel in the way it compares and assesses the economic impact of different epidemics on firms and considers their impact at different development stages.
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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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Ball, Frank. "A note on the total size distribution of carrier-borne epidemic models." Journal of Applied Probability 27, no. 4 (December 1990): 908–12. http://dx.doi.org/10.2307/3214833.
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The coupling method of Ball (1986) is extended to carrier-borne epidemics, thus providing a new proof of a result of Daniels (1972) concerning the total size distribution of Downton's stochastic carrier-borne epidemic. The generalization to multipopulation carrier-borne epidemics is immediate.
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Ball, Frank. "A note on the total size distribution of carrier-borne epidemic models." Journal of Applied Probability 27, no. 04 (December 1990): 908–12. http://dx.doi.org/10.1017/s0021900200028072.
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The coupling method of Ball (1986) is extended to carrier-borne epidemics, thus providing a new proof of a result of Daniels (1972) concerning the total size distribution of Downton's stochastic carrier-borne epidemic. The generalization to multipopulation carrier-borne epidemics is immediate.
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Fischer, T., T. Gerwald, S. Lajos, S. Woellert, Ch Kuttler, and J. Draeger. "Modeling the influence of the information domain on countermeasure effectiveness in case of COVID-19." Journal of Physics: Conference Series 2514, no. 1 (May 1, 2023): 012009. http://dx.doi.org/10.1088/1742-6596/2514/1/012009.
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Abstract A common way to model an epidemic — restricted to contagion aspects only — is a modification of the Kermack-McKendrick SIR Epidemic model (SIR model) with differential equations. (Mis-)Information about epidemics may influence the behavior of the people and thus the course of epidemics as well. We have thus coupled an extended SIR model of the COVID-19 pandemic with a compartment model of the (mis-)information-based attitude of the population towards epidemic countermeasures. The resulting combined model is checked concerning basic plausibility properties like positivity and boundedness. It is calibrated using COVID-19 data from RKI and attitude data provided by the COVID-19 Snapshot Monitoring (COSMO) study. The values of parameters without corresponding observation data have been determined using an L2 -fit under mild additional assumptions. The predictions of the calibrated model are essentially in accordance with observations. An uncertainty analysis of the model shows, that our results are in principle stable under measurement errors. We also assessed the scale, at which specific parameters can influence the evolution of epidemics. Another result of the paper is that in a multi-domain epidemic model, the notion of controlled reproduction number has to be redefined when being used as an indicator of the future evolution of epidemics.
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Liu, Zhenzhen, Xiaoke Xu, and Jianyun Zhou. "Quantitative effects of network connectivity on epidemics." International Journal of Modern Physics B 34, no. 28 (October 20, 2020): 2050262. http://dx.doi.org/10.1142/s0217979220502628.
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Epidemics are affected by the connectivity of nodes in networks in addition to the cooperation of infection transmission. We investigate quantitatively the effects of node connectivity on transmission dynamics by comparing epidemic diffusion in null models with gradual connection strength. Results show that: (1) the inhomogeneity of network connectivity accelerates the spreading of epidemics, this phenomenon is more significant in the early stage of propagation; (2) the enhancement of connectivity of homogenous nodes restrains epidemic spreading, and the spreading speed correlates negatively with connection strength; (3) the spreading speed of epidemics does not change linearly with the strength of rich-club property, which means that the connectivity among hub nodes does not appreciably affect disease diffusion.
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Grabow, B. S., D. A. Shah, and E. D. DeWolf. "Environmental Conditions Associated with Stripe Rust in Kansas Winter Wheat." Plant Disease 100, no. 11 (November 2016): 2306–12. http://dx.doi.org/10.1094/pdis-11-15-1321-re.
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Stripe rust has reemerged as a problematic disease in Kansas wheat. However, there are no stripe rust forecasting models specific to Kansas wheat production. Our objective was to identify environmental variables associated with stripe rust epidemics in Kansas winter wheat as an initial step in the longer-term goal of developing predictive models for stripe rust to be used within the state. Mean yield loss due to stripe rust on susceptible varieties was estimated from 1999 to 2012 for each of the nine Kansas crop reporting districts (CRD). A CRD was classified as having experienced a stripe rust epidemic when yield loss due to the disease equaled or exceeded 1%, and a nonepidemic otherwise. Epidemics were further classified as having been moderate or severe if yield loss was 1 to 14% or greater than 14%, respectively. The binary epidemic categorizations were linked to a matrix of 847 variables representing monthly meteorological and soil moisture conditions. Classification trees were used to select variables associated with stripe rust epidemic occurrence and severity (conditional on an epidemic having occurred). Selected variables were evaluated as predictors of stripe rust epidemics within a general estimation equations framework. The occurrence of epidemics within CRD was linked to soil moisture during the fall and winter months. In the spring, severe epidemics were linked to optimal (7 to 12°C) temperatures. Simple environmentally based stripe rust models at the CRD level may be combined with field-level disease observations and an understanding of varietal reaction to stripe rust as part of an operational disease forecasting system in Kansas.
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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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Edward, Frank. "Cholera: The Victorian Plague." Tanzania Zamani: A Journal of Historical Research and Writing 13, no. 2 (December 31, 2021): 181–85. http://dx.doi.org/10.56279/tza20211327.
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The Victorian Britain was swept by five cholera epidemics which led to evolution of sanitary culture that was punctuated by sanitary reforms and engineering. The epidemic made social, political and spatial relations to change. It also led to the emergence of a concept ‘sanitary city’ in the urban planning, a concept that circulated to other parts of the world. Victorian ideas were on the move. Many works on cholera epidemics and sanitary cities discuss mainly about the contributions of few actors, particularly Sir Edwin Chadwick, the main sanitation infrastructures and about a select of cholera epidemics that the swept across towns and cities during the Victorian era. On the contrary, the monograph by a historian Amanda J. Thomas sets out a novel departure by examining all five epidemics and explaining how knowledge and experience of each epidemic drew many actors as well as a series of interventions. It weaves together the social and epidemiological histories of cholera; biographical contributions of key Victorian figures particularly Sir Joseph Bazalgette, Dr. John Snow and William Farr; social history of urban poverty; and the critical accounts that portray reactions of people in the times of epidemics.
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Hughes, Cornelius G. "The Piper's Dance: A Paradigm of the Collective Response to Epidemic Disease." International Journal of Mass Emergencies & Disasters 11, no. 2 (August 1993): 227–45. http://dx.doi.org/10.1177/028072709301100205.
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A content analysis of the literature on epidemics, with particular reference to the American experience with AIDS, reveals the natural history of the response of endangered populations to epidemics. The paradigm contains four sequential phases: discernment, in which the threatened society becomes cognizant of the presence of a spreading lethal infection; a collective trauma with symptoms similar to other natural and man-made disasters and attended by denial, epidemic phobia, scapegoating and retribution guilt; avoidance behavior ruled by rational attempts to lessen the risk of contagion; and recovery, in which survivors enabled by biological immunity or medical technology witness the abatement of the epidemic. Though they have distinctive traits, epidemics illustrate the essential dynamics that mark natural and technological disasters.
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Fisher, Matthew C., Gina L. Koenig, Thomas J. White, and John W. Taylor. "Pathogenic Clones versus Environmentally Driven Population Increase: Analysis of an Epidemic of the Human Fungal PathogenCoccidioides immitis." Journal of Clinical Microbiology 38, no. 2 (2000): 807–13. http://dx.doi.org/10.1128/jcm.38.2.807-813.2000.
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For many pathogenic microbes that utilize mainly asexual modes of reproduction, it is unknown whether epidemics are due to either the emergence of pathogenic clones or environmentally determined increases in the population size of the organism. Descriptions of the genetic structures of epidemic populations, in conjunction with analyses of key environmental variables, are able to distinguish between these competing hypotheses. A major epidemic of coccidioidomycosis (etiologic agent, Coccidioides immitis) occurred between 1991 and 1994 in central California, representing an 11-fold increase above the mean number of cases reported from 1955 to 1990. Molecular analyses showed extensive genetic diversity, a lack of linkage disequilibria, and little phylogenetic structure, demonstrating that a newly pathogenic strain was not responsible for the observed epidemic. Epidemiological analyses showed that morbidity caused by C. immitis was best explained by the interaction between two variables, the lengths of droughts preceding epidemics and the amounts of rainfall. This shows that the principal factors governing this epidemic of C. immitis are environmental and not genetic. An important implication of this result is that the periodicity of cyclical environmental factors regulates the population size of C. immitis and is instrumental in determining the size of epidemics. This knowledge provides an important tool for predicting outbreaks of this pathogen, as well as a general framework that may be applied to determine the causes of epidemics of other fungal diseases.
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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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Benedicto, Andreu Segura. "Epidemics and Epidemiology." Epidemiology International Journal 6, no. 3 (2022): 1–2. http://dx.doi.org/10.23880/eij-16000247.
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The word Epidemiology was written for the first time in a report on the plague in Alghero in 1583. Although its etymology has it intricacy. For centuries it has been concerned with understanding and trying to control and prevent epidemics. During the cholera epidemic in London in 1848 the London Society of Epidemiology was formed. Main instrument of Public Health since then. The increase in chronic diseases-supposedly no communicable-gave way to the epidemiology of black boxes and the predominance of risk factors. And later to an enormous methodological progress increasingly complex and intricate but professionally very appealing. So few epidemiologists have experience in field control of epidemics. Thus, perhaps it is convenient to return, although partially, to the origins. Looking at the future.
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Clay, Patrick A., Meghan A. Duffy, and Volker H. W. Rudolf. "Within-host priority effects and epidemic timing determine outbreak severity in co-infected populations." Proceedings of the Royal Society B: Biological Sciences 287, no. 1922 (March 4, 2020): 20200046. http://dx.doi.org/10.1098/rspb.2020.0046.
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Co-infections of hosts by multiple pathogen species are ubiquitous, but predicting their impact on disease remains challenging. Interactions between co-infecting pathogens within hosts can alter pathogen transmission, with the impact on transmission typically dependent on the relative arrival order of pathogens within hosts (within-host priority effects). However, it is unclear how these within-host priority effects influence multi-pathogen epidemics, particularly when the arrival order of pathogens at the host-population scale varies. Here, we combined models and experiments with zooplankton and their naturally co-occurring fungal and bacterial pathogens to examine how within-host priority effects influence multi-pathogen epidemics. Epidemiological models parametrized with within-host priority effects measured at the single-host scale predicted that advancing the start date of bacterial epidemics relative to fungal epidemics would decrease the mean bacterial prevalence in a multi-pathogen setting, while models without within-host priority effects predicted the opposite effect. We tested these predictions with experimental multi-pathogen epidemics. Empirical dynamics matched predictions from the model including within-host priority effects, providing evidence that within-host priority effects influenced epidemic dynamics. Overall, within-host priority effects may be a key element of predicting multi-pathogen epidemic dynamics in the future, particularly as shifting disease phenology alters the order of infection within hosts.
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Castro Blanco, Elisabet, Maria Rosa Dalmau Llorca, Carina Aguilar Martín, Noèlia Carrasco-Querol, Alessandra Queiroga Gonçalves, Zojaina Hernández Rojas, Ermengol Coma, and José Fernández-Sáez. "A Predictive Model of the Start of Annual Influenza Epidemics." Microorganisms 12, no. 7 (June 21, 2024): 1257. http://dx.doi.org/10.3390/microorganisms12071257.
Full textAbstract:
Influenza is a respiratory disease that causes annual epidemics during cold seasons. These epidemics increase pressure on healthcare systems, sometimes provoking their collapse. For this reason, a tool is needed to predict when an influenza epidemic will occur so that the healthcare system has time to prepare for it. This study therefore aims to develop a statistical model capable of predicting the onset of influenza epidemics in Catalonia, Spain. Influenza seasons from 2011 to 2017 were used for model training, and those from 2017 to 2018 were used for validation. Logistic regression, Support Vector Machine, and Random Forest models were used to predict the onset of the influenza epidemic. The logistic regression model was able to predict the start of influenza epidemics at least one week in advance, based on clinical diagnosis rates of various respiratory diseases and meteorological variables. This model achieved the best punctual estimates for two of three performance metrics. The most important variables in the model were the principal components of bronchiolitis rates and mean temperature. The onset of influenza epidemics can be predicted from clinical diagnosis rates of various respiratory diseases and meteorological variables. Future research should determine whether predictive models play a key role in preventing influenza.
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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.
Full textAbstract:
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.
Full textAbstract:
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.
Full textAbstract:
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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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.
Full textAbstract:
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.