Journal articles on the topic 'COVID-19 Epidemic'
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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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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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Bagal, Dilip Kumar, and Pravajyoti Patra. "COVID-19: A Never Seen Pandemic." YMER Digital 21, no. 08 (August 8, 2022): 321–25. http://dx.doi.org/10.37896/ymer21.08/27.
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People have long been affected by epidemics and pandemics of communicable illnesses. The outbreaks have been around for thousands of years. Even in our modern day, epidemics have ravaged civilization till it leads people to despair. In the meanwhile, viruses have always offered huge difficulties that have ignited horrific epidemics and pandemics. A pandemic is the widespread spread of a new sickness. Viral respiratory diseases, such as those caused by a novel influenza virus or the coronavirus COVID-19, are the most likely to evolve into a pandemic. A pandemic is not the same as an epidemic. In an epidemic, many more cases of a health condition occur than would typically develop in a community or area, however the ailment does not move outside. The World Health Organization (WHO) is responsible for declaring when a worldwide epidemic is underway. The WHO achieves this by monitoring outbreaks of a disease and receiving advice from worldwide health experts. This paper depicts the impact of COVID-19 in globally in various fields and also visualize the current status of this pandemic. Keywords: COVID-19; Confirmed Case; Pandemic; WHO
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Williamson, Graham. "COVID-19 Epidemic Editorial." Open Nursing Journal 14, no. 1 (March 16, 2020): 37–38. http://dx.doi.org/10.2174/1874434602014010037.
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Velavan, Thirumalaisamy P., and Christian G. Meyer. "The COVID‐19 epidemic." Tropical Medicine & International Health 25, no. 3 (February 16, 2020): 278–80. http://dx.doi.org/10.1111/tmi.13383.
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Mustafina, Bakhytkul, Aiman Mussina, Anel Serikbayeva, and Erdos Baranbayev. "Epidemiological forecast of COVID-19 in Kazakhstan." JOURNAL OF HEALTH DEVELOPMENT 4, no. 39 (2020): 49–53. http://dx.doi.org/10.32921/2225-9929-2020-4-39-49-53.
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Currently, the epidemic situation in Kazakhstan is stable.The main reason for this is a correctly calculated epidemic forecast. This article provides a forecast of the epidemic situation in Kazakhstan using a mathematical model. The model is used to analyze the epidemic situation between Kazakhstan and other countries. In addition, the article discusses the ways and consequences of eliminating the epidemic. The developed model is used to describe how the upcoming epidemic situation is developing. In other words, the article analyzes and evaluates the epidemic caused by coronavirus infection in Kazakhstan using a mathematical model
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Tamm, M. V. "COVID-19 in Moscow: prognoses and scenarios." FARMAKOEKONOMIKA. Modern Pharmacoeconomic and Pharmacoepidemiology 13, no. 1 (April 24, 2020): 43–51. http://dx.doi.org/10.17749/2070-4909.2020.13.1.43-51.
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Aim: to present a mathematical model of the development of COVID-19 in Moscow along with the analysis of some scenarios of epidemic control and possible epidemic consequences.Materials and Methods. The modeling of the epidemics was based on the extended SEIR model proposed lately in the group of Prof. R. Neher and realized as a freely available software program. The authors based the choice of the parameters of modeling on published data on the epidemiological properties of the novel coronavirus SARS-CoV-2 and open access data on the registered cases of COVID-19 in Moscow for 8-27 March 2020.Results. Five potential scenarios of the development of COVID-19 epidemics are studied. The scenarios are differed by the levels of the control measures: Null Scenario corresponded to the lack of protective measures, Scenario A – mild measures of the epidemic control (closing of schools and universities, recommendations for senior citizens to stay inside), Scenario B – medium level of control (closing of all public places, recommendation for the citizens to stay inside), Scenarios C and D – complete lockdown (from the beginning of May 2020 within Scenario C and from the beginning of April 2020 within Scenario D). It was shown that within the Null Scenario, the lethality from the novel coronavirus in Moscow will exceed 100 thousand people, and the number of critically ill patients on the peak of the epidemics will exceed the capacities of the system of healthcare. Scenarios A and B did not provide for a radical decrease in the fatality rate, and the number of critically ill patients at the peak of epidemics will still exceed the capacities of the system of healthcare. Besides, within Scenario B, the epidemics will last for more than a year. Scenarios C and D will allow for the control of epidemics and a significant decrease in the rate of letha lity (by 30 and 400 times, respectively). At the same time, these two scenarios prevent the population from developing herd immunity, which would result in the population susceptibility to repeated epidemics outbreaks. Conclusion. The scenarios intended for the slow development of herd immunity in the conditions of epidemic control would not bring sufficient results: the lethality would remain unacceptably high, the capacities of the system of healthcare would be overloaded, and the time of limiting measures would be unacceptably long. Such measures as complete lockdown would stop the present epidemics. The earlier they are introduced, the more efficient will be the results. To prevent further repeated outbreaks of the epidemics, it is necessary to establish a system of available, quick, and efficient testing in combination with point isolation of the infected patients and their contacts.
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E, Rocchi, Peluso S, Sisti D, Rocchi M, and Carletti M. "Lessons From COVID-19 Epidemic?" Journal of Translational Science and Research 3, no. 1 (December 31, 2020): 1–3. http://dx.doi.org/10.24966/tsr-6899/100009.
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E, Rocchi, Peluso S, Sisti D, Rocchi M, and Carletti M. "Lessons From COVID-19 Epidemic?" Journal of Translational Science and Research 3, no. 1 (December 31, 2020): 1–3. http://dx.doi.org/10.24966/tsr-6899/100009.
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Gupta, Mayanka. "Epidemic Modelling of COVID-19." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (August 31, 2021): 1763–69. http://dx.doi.org/10.22214/ijraset.2021.37439.
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Abstract: COVID-19 has had a disastrous impact on millions of lives all over the world.199,466,211 confirmed cases of COVID19 and 4,244,541 deaths have been reported to WHO till 4th august. Analyzing the available data and predicting the pandemic trend is important since the situation can be controlled only when there is adequate preparation. Research using epidemiological models helps in analyzing different facets of COVID including infection, recovery and death rate. Predicting the daily increase of cases can help reduce the burden on health care workers and government by aiding them in planning the required resources in advance. Thus, in this project data driven epidemic modelling approach is used. COVID cases of 10 forthcoming days using three modelling techniques namely Polynomial Regression, Bayesian Ridge Regression and Support Vector Machine are predicted. The performance metric used to identify the best model are MSE and MAE. Polynomial Regression is found to have best performance followed by Bayesian ridge regression. Support Vector Machine has a poor performance. Keywords: Epidemic Modelling, COVID-19, Machine Learning, Polynomial Regression, Bayesian Ridge Regression, Support Vector Machine
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PAJK ŽONTAR, Tanja, and Rajko VIDRIH. "Nutrition and Covid-19 epidemic." Acta agriculturae Slovenica 117, no. 2 (July 14, 2021): 1. http://dx.doi.org/10.14720/aas.2021.117.2.1980.
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Proper nutrition is an essential part of an individual’s defence against numerous diseases including coronavirus disease SARS-CoV-2 (Covid-19). Nutritional status of individual is affected by several factors such as age, sex, health status, physical activity, life style and medications. Optimal nutrition and dietary nutrient intake impact the immune system, therefore the sustainable way to survive in current context is to strengthen the immune system. Inadequate intake of energy, protein, and specific micronutrients are associated with depressed immune function and increased susceptibility to infection. Predominantly vital for the encouraging of immune function are elements selenium, iron and zinc and vitamins A, D, C, E, B6, B9 (folate) and B12 as well as omega-3 polyunsaturated fatty acids. Thus, during this time it is important to take care of nutritional habits, following a healthy and balanced nutritional pattern containing a high amount of elements, antioxidants and vitamins. It is also recommended, that individuals should be mindful of physical activity, known to be associated with all-cause mortality. Regular physical activity also improves mental health and overall feelings of wellbeing. Thus, now in the time of epidemic, more than ever, wider access to healthy foods should be a top priority for governments around the world
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Bredan, Amin, and Omran Bakoush. "COVID-19 epidemic in Libya." Libyan Journal of Medicine 16, no. 1 (January 1, 2021): 1871798. http://dx.doi.org/10.1080/19932820.2021.1871798.
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Mahmodi, M. R., and A. V. Korenevskaya. "IMPACT OF COVID-19 ON E-COMMERCE OF RUSSIA." Scientific Journal ECONOMIC SYSTEMS 1, no. 181 (2021): 58–64. http://dx.doi.org/10.29030/2309-2076-2021-14-2-58-64.
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In December 2019, the World Health Organization (WHO) declared an epidemic due to the outbreak of the coronavirus in Wuhan, China. With the outbreak of the COVID-19 epidemic, it is still unclear how long the negative economic impact on the world will continue. In particular, the imposition of public or partial travel restrictions in many countries has led to widespread change in COVID-19, which has significantly altered consumer behavior and shaped the industry. While physical stores are plagued by epidemics due to customer actions and preferences, online retailers are increasing their sales volume and constantly gaining customers. Consumers have begun to prefer e-commerce, which is the fastest and most practical way to meet their needs in an epidemic environment. E-commerce is a way to minimize physical interaction, apart from receiving burdens. However, direct access to the product is very important not only for health, but also for practical savings, time and energy. The aim of this study was to investigate the impact of COVID-19, an infectious disease, on e-commerce and to assess changes in demand for different e-commerce products and product groups during the COVID-19 epidemic.
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Kim, DaeHyun. "Post-recovery Stigma in Early and Late COVID-19 Epidemic." Keimyung Medical Journal 41, no. 2 (December 15, 2022): 80–83. http://dx.doi.org/10.46308/kmj.2022.00171.
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People who recover from the novel coronavirus diseases 2019 (COVID-19) complain of psychological symptoms such as stress, anxiety, and depression by psycho-stress due to social stigma in the early stage of the epidemic. To assess the psychological stigma of early and late epidemic periods, stigma scale was compared between the first epidemic period (February-May 2020, n = 20) and the fifth epidemic period (February-May 2022, n = 21) post-recovery COVID-19 patients in outpatient clinic. The average total stigma score was significantly higher (79.6 ± 18.16) in post-recovery COVID-19 patients of the early (first) epidemic period compared to late (5th) epidemic period patients (37.5 ±10.99). Four subscales were significantly higher in early epidemic period compared to late epidemic period (enacted stigma 27.5 ± 7.25 vs. 13.0±4.18, disclosure concerns 19.5 ± 9.38 vs. 9.4 ± 2.99, negative self-image 16.2 ± 8.10 vs. 8.1±2.47, concern with public attitudes 16.6 ± 6.95 vs. 7.0 ± 2.01). In those who recovered from the early COVID-19 epidemic period, patients experienced significantly higher social stigma stress compared to the late epidemic period. In the early period of novel virus epidemics, the risk of personal stigmatization and stress should be prevented in public policy. Socio-psychological assessment and treatment should be considered for the patient in addition to physical symptoms.
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Sokolovsky, V. L., G. B. Furman, D. A. Polyanskaya, and E. G. Furman. "Spatio-temporal modeling of COVID-19 epidemic." Health Risk Analysis, no. 1 (March 2021): 23–37. http://dx.doi.org/10.21668/health.risk/2021.1.03.
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In autumn and winter 2020–2021 there was a growth in morbidity with COVID-19. Since there are no efficient medications and mass vaccination has only just begun, quarantine, limitations on travels and contacts between people as well as use of personal protection equipment (masks) still remain priority measures aimed at preventing the disease from spreading. In this work we have analyzed how the epidemic developed and what impacts quarantine measures exerted on the disease spread; to do that we applied various mathematical models. It was shown that simple models belonging to SIR-type (S means susceptible; I, infected; and R, recovered or removed from the infected group) allowed estimating certain model parameters such as morbidity and recovery coefficients that could be used in more complicated models. We examined spatio-temporal epidemiologic models based on finding solutions to non-stationary two-dimensional reaction-diffusion equations. Such models allow taking into account uneven distribution of population, changes in population mobility, and changes in frequency of contacts between susceptible and infected people due to quarantine. We applied obtained analytical and numerical solutions to analyze different stages in the epidemic as well as its wave-like development influenced by imposing and canceling quarantine limitations. To take into account ultimate rate at which the disease spreads and its incubation period (when an infected person is not a source of contagion), we suggest using equations similar to the Cattaneo-Vernotte one. The suggested model allows predicting where the front of morbidity spread is going to occur, that is, a moving frontier between areas where there are infected people and areas where they are absent. Use of such models provides an opportunity to introduce differential quarantine measures basing on more objective grounds. At the end of 2020 mass vaccination started in some countries. We estimated a necessary number of people that had to be vaccinated so that new waves of COVID-19 epidemic would be prevented; in our estimates, not less than 80% of the country population should be vaccinated. Correct prediction of epidemic development is becoming more and more vital at the moment due to new and more contagious COVID-19 virus strains occurring in England, South Africa, and some other countries. Our research results can be used for predicting spread of COVID-19 and other communicable diseases; they can make for taking the most efficient measures for successful control over epidemics.
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Wang, Haolun. "Big data in COVID-19 prevention and control: Modeling and analysis report." Applied and Computational Engineering 6, no. 1 (June 14, 2023): 35–44. http://dx.doi.org/10.54254/2755-2721/6/20230403.
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The COVID-19 epidemic has brought great external impact to China. China is facing complex internal and external environmental challenges. SIR epidemic model is a classical partition model, which is widely used to predict the progress of COVID-19. Although the SIR model may be useful in simulating multiple epidemics, it may not be sufficient to describe the spread of COVID-19. Therefore, some modifications were made and used to study the spread and control of COVID-19 epidemic on the SIR model of COVID-19 disease. Expand it by increasing the link between tracking and other interventions. By studying the SEIR model considering the interaction between human and infectious source. In this paper, we will use the classical SIR model to simulate and predict the spread of COVID-19. By distinguishing between confirmed and undiagnosed individuals, the development of COVID-19 is characterized by phased changes. Based on the preliminary data analysis of the epidemic on various industries, the actual impact of the epidemic on society was quantitatively analyzed.
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Chen, Yile, Liang Zheng, Junxin Song, Linsheng Huang, and Jianyi Zheng. "Revealing the Impact of Urban Form on COVID-19 Based on Machine Learning: Taking Macau as an Example." Sustainability 14, no. 21 (November 2, 2022): 14341. http://dx.doi.org/10.3390/su142114341.
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The COVID-19 pandemic has led to a re-examination of the urban space, and the field of planning and architecture is no exception. In this study, a conditional generative adversarial network (CGAN) is used to construct a method for deriving the distribution of urban texture through the distribution hotspots of the COVID-19 epidemic. At the same time, the relationship between urban form and the COVID-19 epidemic is established, so that the machine can automatically deduce and calculate the appearance of urban forms that are prone to epidemics and may have high risks, which has application value and potential in the field of planning and design. In this study, taking Macau as an example, this method was used to conduct model training, image generation, and comparison of the derivation results of different assumed epidemic distribution degrees. The implications of this study for urban planning are as follows: (1) there is a correlation between different urban forms and the distribution of epidemics, and CGAN can be used to predict urban forms with high epidemic risk; (2) large-scale buildings and high-density buildings can promote the distribution of the COVID-19 epidemic; (3) green public open spaces and squares have an inhibitory effect on the distribution of the COVID-19 epidemic; and (4) reducing the volume and density of buildings and increasing the area of green public open spaces and squares can help reduce the distribution of the 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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Feng, Qingxiang, Haipeng Wei, Jun Hu, Wenzhe Xu, Fan Li, Panpan Lv, and Peng Wu. "Analysis of the attention to COVID-19 epidemic based on visibility graph network." Modern Physics Letters B 35, no. 19 (June 1, 2021): 2150316. http://dx.doi.org/10.1142/s0217984921503164.
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Most of the existing researches on public health events focus on the number and duration of events in a year or month, which are carried out by regression equation. COVID-19 epidemic, which was discovered in Wuhan, Hubei Province, quickly spread to the whole country, and then appeared as a global public health event. During the epidemic period, Chinese netizens inquired about the dynamics of COVID-19 epidemic through Baidu search platform, and learned about relevant epidemic prevention information. These groups’ search behavior data not only reflect people’s attention to COVID-19 epidemic, but also contain the stage characteristics and evolution trend of COVID-19 epidemic. Therefore, the time, space and attribute laws of propagation of COVID-19 epidemic can be discovered by deeply mining more information in the time series data of search behavior. In this study, it is found that transforming time series data into visibility network through the principle of visibility algorithm can dig more hidden information in time series data, which may help us fully understand the attention to COVID-19 epidemic in Chinese provinces and cities, and evaluate the deficiencies of early warning and prevention of major epidemics. What’s more, it will improve the ability to cope with public health crisis and social decision-making level.
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Zhao, Bin. "Epidemic-related sites in covid-19 media reports." Clinical Research and Clinical Trials 2, no. 3 (November 15, 2020): 01–10. http://dx.doi.org/10.31579/2693-4779/005.
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Background: Since the outbreak of the COVID-19 virus in Wuhan, China, in early 2020, the Chinese government has formed a mode of information disclosure. More than 400 cities have announced specific location information for newly diagnosed cases of novel coronavirus pneumonia, including residential areas or places of stay. We have established a conditional random field model and a rule-dependent model based on Chinese geographical name elements. Taking Guangdong Province as an example, the identification of named entities and the automatic extraction of epidemic-related sites are carried out. This method will help locate the spread of the epidemic, prevent and control the spread of the epidemic, and gain more time for vaccine clinical trials. Methods: Based on the presentation form of the habitual place or place of stay of the diagnosed cases in the text of the web page, a conditional random field model is established, and a rule-dependent model is established according to the combination rule of the elements of the place words and the place name dictionary composed of provinces, cities and administrative regions. Findings: The results of the analysis based on the conditional random field model and the rule-dependent model show that the location of confirmed cases of new coronavirus pneumonia in Guangdong Province in mid-February is mainly concentrated in Guangzhou，Shenzhen，Zhuhai and Shantou Cities. In Guangzhou, Futian District has more epidemicsites and Huangpu and Conghua District have fewer epidemic sites. Government officials in Guangzhou City should pay attention to Futian District. Interpretation: Governments at all levels in Guangzhou Province have intervened to control the epidemic through various means in mid-February. According to the results of the model analysis, we believe that the administrative regions with more diagnosed locations should focus on and take measures such as blockades and control of personnel flow to control the disease in those administrative regions to avoid affecting other adjacent administrative regions.
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J, Sahu. "COVID-19 Epidemic: View from an Ophthalmologists Eye." Open Access Journal of Ophthalmology 6, no. 1 (January 4, 2021): 1–4. http://dx.doi.org/10.23880/oajo-16000224.
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COVID-19 pandemic is one of the worst medical emergencies the world has seen in quite some time. Still surrounded by a lot of controversies, it has managed to give all clinicians a run for their lives. In present circumstances, it remains of utmost importance that the right practice guidelines are made to reach clinicians in every possible way. Ophthalmologists remain an important link with coronavirus after preliminary reports of conjunctival and tear related spread in Chinese literature. There has been a lot of speculation and confusion for ophthalmologists in such circumstances. They do not want to disregard patients and at the same time are worried about the community spread from any probable case reporting to them. In such scenarios, it becomes critical to understand the current standard operating protocols for ophthalmologists.
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Greenland, John R., Marilyn D. Michelow, Linlin Wang, and Martin J. London. "COVID-19 Infection." Anesthesiology 132, no. 6 (June 1, 2020): 1346–61. http://dx.doi.org/10.1097/aln.0000000000003303.
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Abstract Healthcare systems worldwide are responding to Coronavirus Disease 2019 (COVID-19), an emerging infectious syndrome caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus. Patients with COVID-19 can progress from asymptomatic or mild illness to hypoxemic respiratory failure or multisystem organ failure, necessitating intubation and intensive care management. Healthcare providers, and particularly anesthesiologists, are at the frontline of this epidemic, and they need to be aware of the best available evidence to guide therapeutic management of patients with COVID-19 and to keep themselves safe while doing so. Here, the authors review COVID-19 pathogenesis, presentation, diagnosis, and potential therapeutics, with a focus on management of COVID-19–associated respiratory failure. The authors draw on literature from other viral epidemics, treatment of acute respiratory distress syndrome, and recent publications on COVID-19, as well as guidelines from major health organizations. This review provides a comprehensive summary of the evidence currently available to guide management of critically ill patients with COVID-19.
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Burda, Zdzislaw. "Modelling Excess Mortality in Covid-19-Like Epidemics." Entropy 22, no. 11 (October 30, 2020): 1236. http://dx.doi.org/10.3390/e22111236.
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We develop an agent-based model to assess the cumulative number of deaths during hypothetical Covid-19-like epidemics for various non-pharmaceutical intervention strategies. The model simulates three interrelated stochastic processes: epidemic spreading, availability of respiratory ventilators and changes in death statistics. We consider local and non-local modes of disease transmission. The first simulates transmission through social contacts in the vicinity of the place of residence while the second through social contacts in public places: schools, hospitals, airports, etc., where many people meet, who live in remote geographic locations. Epidemic spreading is modelled as a discrete-time stochastic process on random geometric networks. We use the Monte–Carlo method in the simulations. The following assumptions are made. The basic reproduction number is R0=2.5 and the infectious period lasts approximately ten days. Infections lead to severe acute respiratory syndrome in about one percent of cases, which are likely to lead to respiratory default and death, unless the patient receives an appropriate medical treatment. The healthcare system capacity is simulated by the availability of respiratory ventilators or intensive care beds. Some parameters of the model, like mortality rates or the number of respiratory ventilators per 100,000 inhabitants, are chosen to simulate the real values for the USA and Poland. In the simulations we compare ‘do-nothing’ strategy with mitigation strategies based on social distancing and reducing social mixing. We study epidemics in the pre-vacine era, where immunity is obtained only by infection. The model applies only to epidemics for which reinfections are rare and can be neglected. The results of the simulations show that strategies that slow the development of an epidemic too much in the early stages do not significantly reduce the overall number of deaths in the long term, but increase the duration of the epidemic. In particular, a hybrid strategy where lockdown is held for some time and is then completely released, is inefficient.
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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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Nowakowski, Piotr T. "Activities of Cultural Centres During the Covid-19 Epidemic in Poland." Roczniki Kulturoznawcze 11, no. 3 (December 16, 2020): 79–93. http://dx.doi.org/10.18290/rkult20113-7.
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Funkcjonowanie domów kultury w trakcie epidemii COVID-19 w Polsce
W związku z podjęciem kroków mających na celu zatrzymanie szerzenia się wirusa SARS-CoV-2 w Polsce od marca 2020 r. aktywność domów kultury uległa okresowemu zamrożeniu. Już na samym początku spowodowało to wyzwania o różnorakim charakterze, zwłaszcza finansowym. Brak możliwości organizowania imprez komercyjnych zmusił wiele placówek do poszukiwania alternatywnych źródeł dochodu. Przede wszystkim jednak epidemia postawiła pod znakiem zapytania możliwość realizacji działalności statutowej placówek kultury. W artykule omówiono nowe konteksty tej działalności, które sprowadzały się do odwołania lub zawieszenia imprez i zajęć, przeniesienia aktywności do sieci, podjęcia interaktywnej komunikacji z odbiorcą, reorganizacji pracy stacjonarnej, wreszcie aktywnego włączenia się w walkę z koronawirusem. Etap znoszenia ograniczeń wywołanych epidemią dał możliwość stopniowego przywracania działalności placówek kultury, a Ministerstwo Kultury i Dziedzictwa Narodowego opublikowało wytyczne dotyczące dalszego ich funkcjonowania. Doświadczenia pierwszego okresu epidemii mogą być nauką na przyszłość, z której mogą skorzystać czynniki odpowiedzialne za placówki kultury.
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Rogozhina, N. G. "COVID-19 in Indonesia." South East Asia: Actual problems of Development, no. 2 (47) (2020): 65–74. http://dx.doi.org/10.31696/2072-8271-2020-2-2-47-065-074.
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The article analyzes the political and socio-economic risks of the COVID-19 epidemic and the reasons for its rapid spread in Indonesia, which outstripped other Southeast Asian countries in terms of deaths from coronavirus infection. The author notes that the epidemiological crisis is not only a medical problem, but also affected the sphere of politics, causing an aggravation of the conflict of interests between the government and the provincial authorities by the nature of the measures taken to curb the spread of the epidemic. Its economic consequences will be a decrease in economic growth, an increase in the number of unemployed and deepening of the problem of inequality and poverty. Awareness of these economic risks determines the government strategy to combat COVID-19.
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Denisenko, Viktor V., and Anna V. Aleshukina. "Mathematical model of the spread of COVID-19 in the rostov region for 2020–2022." Medical academic journal 2, no. 2 (November 6, 2022): 171–76. http://dx.doi.org/10.17816/maj108663.
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BACKGROUND: In the context of the COVID-19 epidemic, there is a need for forecasting tools that enables us to predict the possible epidemic consequences and evaluate the effectiveness of epidemic control. Mathematical modeling can serve as such a tool.
AIM: The Aim is to present a mathematical model of the spread of COVID-19 in the Rostov Region for 20202022. To be more precise, the aim is to forecast how the number of people infected, recovered, hospitalized and died from the epidemic of the new coronovirus will change over this period of time.
MATERIALS AND METHODS: The modeling of the epidemics was based on the extended SEIR model proposed by R. Neyer et al. for forecasting the COVID-19 epidemic and implemented as a freely available web application.
RESULTS: The model under consideration made it possible to forecast the volume of hospitalization and the number of deaths in the course of COVID-19 epidemic in the Rostov region for 20202022.
CONCLUSIONS: The performed simulations demonstrated the capabilities the considered SEIR model for forecasting the COVID-19 epidemic. It was found that the number of hospitalized patients for the entire period covered by the model does not exceed the capabilities of the health care system of the Rostov Region.
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Mikulec, Anna, and Marek Zborowski. "Problem głodu na świecie w świetle pandemii COVID-19." Sztuka Leczenia 37, no. 2 (December 30, 2022): 65–70. http://dx.doi.org/10.4467/18982026szl.22.016.16675.
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Głód nadal stanowi poważny i dotkliwy, problem na świecie. Nawet podczas pandemii COVID-19 większy odsetek ludzi umiera z głodu niż z powodu koronawirusa. Czy zatem czeka nas nowa epidemia, tym razem głodu, na świecie? Celem pracy było przedstawienie obecnej sytuacji związanej z brakiem bezpieczeństwa żywnościowego na świecie w aspekcie trwającej jeszcze pandemii COVID-19. Należy spodziewać się, że w najbliższych latach będziemy zmuszeni mierzyć się z ogromnym kryzysem humanitarnym. W związku z powagą problemu przed całą ludzkością stoi dziś zadanie mające na celu zapobiegnięcie rozprzestrzenianiu się epidemii głodu na świecie. ABSTRACT The problem of hunger in the world in the context of the COVID-19 pandemic Hunger continues to be a serious and pressing problem in the world. Even during the COVID-19 pandemic, more people are dying of hunger than of the coronavirus. So, are we going to face a new epidemic, this time of hunger, in the world? The aim of the study was to present the current situation related to the lack of food security in the world in the context of the ongoing COVID-19 pandemic. It is to be expected that in the coming years we may face a huge humanitarian crisis and that all mankind is facing a sentence today aimed at preventing the spread of the hunger epidemic in the world.
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Wang, Yanjin, Pei Wang, Shudao Zhang, and Hao Pan. "Uncertainty Modeling of a Modified SEIR Epidemic Model for COVID-19." Biology 11, no. 8 (August 2, 2022): 1157. http://dx.doi.org/10.3390/biology11081157.
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Based on SEIR (susceptible–exposed–infectious–removed) epidemic model, we propose a modified epidemic mathematical model to describe the spread of the coronavirus disease 2019 (COVID-19) epidemic in Wuhan, China. Using public data, the uncertainty parameters of the proposed model for COVID-19 in Wuhan were calibrated. The uncertainty of the control basic reproduction number was studied with the posterior probability density function of the uncertainty model parameters. The mathematical model was used to inverse deduce the earliest start date of COVID-19 infection in Wuhan with consideration of the lack of information for the initial conditions of the model. The result of the uncertainty analysis of the model is in line with the observed data for COVID-19 in Wuhan, China. The numerical results show that the modified mathematical model could model the spread of COVID-19 epidemics.
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Nikulina, Olena, Valerii Severyn, Mariia Naduieva, and Anton Bubnov. "MODELING THE DEVELOPMENT OF EPIDEMIS BASED ON INFORMATION TECHNOLOGIES OF OPTIMIZATION." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 2 (6) (December 28, 2021): 47–52. http://dx.doi.org/10.20998/2079-0023.2021.02.08.
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Mathematical models of the epidemic have been developed and researched to predict the development of the COVID-19 coronavirus epidemic on thebasis of information technology for optimizing complex dynamic systems. Mathematical models of epidemics SIR, SIRS, SEIR, SIS, MSEIR in theform of nonlinear systems of differential equations are considered and the analysis of use of mathematical models for research of development ofepidemic of coronavirus epidemic COVID-19 is carried out. Based on the statistics of the COVID-19 coronavirus epidemic in the Kharkiv region, theinitial values of the parameters of the models of the last wave of the epidemic were calculated. Using these models, the program of the first-degreesystem method from the module of information technology integration methods for solving nonlinear systems of differential equations simulated thedevelopment of the last wave of the epidemic. Simulation shows that the number of healthy people will decrease and the number of infected peoplewill increase. In 12 months, the number of infected people will reach its maximum and then begin to decline. The information technology ofoptimization of dynamic systems is used to identify the parameters of the COVID-19 epidemic models on the basis of statistical data on diseases in theKharkiv region. Using the obtained models, the development of the last wave of the COVID-19 epidemic in Kharkiv region was predicted. Theprocesses of epidemic development according to the SIR-model with weakening immunity are given, with the values of the model parameters obtainedas a result of identification. Approximately 13 months after the outbreak of the epidemic, the number of infected people will reach its maximum andthen begin to decline. In 10 months, the entire population of Kharkiv region will be infected. These results will allow us to predict possible options forthe development of the epidemic of coronavirus COVID-19 in the Kharkiv region for the timely implementation of adequate anti-epidemic measures.
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Mitrokhin, Oleg V., Nina A. Ermakova, Ekaterina I. Akimova, and Ekaterina A. Sidorova. "COVID-19 — ways to improve the state preparedness for pandemia." HEALTH CARE OF THE RUSSIAN FEDERATION 66, no. 1 (March 4, 2022): 5–10. http://dx.doi.org/10.47470/0044-197x-2022-66-1-5-10.
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Introduction. Tasks are to execute a study of the preparedness of government and health systems for a pandemic to develop proposals for their modernization. The author proceeds from the hypothesis that epidemic and pandemic diseases will threaten society in the foreseeable future, and therefore it is necessary to develop preventive strategies for states to be prepared for new threats. The article summarizes the experience of government and public health in a pandemic of coronavirus infection. Purpose. To examine pandemic preparedness of public administration and health systems and develop proposals for their modernization. Material and methods. There was made an expert analysis of the problematic issues of public administration in the implementation of preventive and anti-epidemic measures using statistical materials and publications of domestic and foreign authors. The study applied information and legal databases, documents of the World Health Organization, health authorities of countries in conditions of coronavirus infection pandemic, analytical, informational, statistical methods of research. Results. Measures are proposed to modernize states’ preparedness for possible pandemics (epidemics) for the medium and long term. Conclusion. The author has proposed an algorithm for the activities of the government in preparedness to combat a pandemic (epidemic). It is necessary to introduce the principles of “double” (including epidemics) use of premises, buildings and structures and “double” (including epidemics) education of specialists in the field of veterinary medicine and biology, as well as paramedical personnel.
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Amofah, George. "COVID-19 epidemic response in Ghana." Ghana Medical Journal 54, no. 4s (December 31, 2020): 3–4. http://dx.doi.org/10.4314/gmj.v54i4s.2.
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The year 2020 has looked like a fairy tale as the COVID-19 pandemic swept across the world with devastating socio-economic and health consequences. The impact of the pandemic has depended, largely, on preparedness and response of countries, and their ability to adjust to the fast-evolving pandemic. The World Health Organization (WHO) declared the novel coronavirus outbreak a public health emergency of international concern (PHEIC) on 30th January 2020, and Ghana reported its first two confirmed cases on 12th March 2020.
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Rutland, Peter. "Learning from the COVID-19 Epidemic." Russia in Global Affairs 18, no. 2 (2020): 60–61. http://dx.doi.org/10.31278/1810-6374-2020-18-2-60-61.
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Hu, Chich-Ping. "The COVID-19 Epidemic Spreading Effects." Sustainability 14, no. 15 (August 8, 2022): 9750. http://dx.doi.org/10.3390/su14159750.
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Cities are hotbeds for the outbreak and spread of infectious diseases. In the process of urban development, frequent interpersonal interactions are conducive to the spread of viruses. After the outbreak of COVID-19 in Wuhan, China in 2019, it quickly spread to Europe, North America, and Asia. This paper collects data on the number of COVID-19-infected cases per 100,000 people in Taiwan from 1 January to 4 May 2022 and the researcher uses the spatial regression model to analyze the spatial effect of the COVID-19 epidemic. The results of the study find that the hot zones of COVID-19-infected cases per 100,000 people are distributed in Taipei City, New Taipei City, Keelung City, Yilan County, and Taoyuan City, and the cold zones are distributed in Changhua County, Yunlin County, Chiayi County, Chiayi City, Tainan City, and Kaohsiung City. There are three types of urban development indicators: density, urbanization, and transportation system and means of transport, all of which can significantly affect the spatial spread of COVID-19. There is a negative correlation between the area of the “urban planning” district, the “road area” per person, the current status of the urban planning district population “density”, and the number of infected cases of “COVID19”. There is a negative correlation between “urban planning”, “road area”, “urbanization”, and “density” of neighboring cities and “COVID19” in a certain city.
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Hidayat, Dayat, and Edwin Setiawan Nugraha. "Epidemic Model Analysis of Covid-19." E3S Web of Conferences 328 (2021): 06002. http://dx.doi.org/10.1051/e3sconf/202132806002.
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Covid-19 is a very extraordinary case not only in one country but all countries in the world. The number of deaths caused by Covid-19 is very large and the rate of spread of this disease is very high and fast. In this paper, we perform an analysis of a covid-19 epidemic model. This model is a development of the SEIR model in general which is equipped with a Quarantine (Q), Fatality (F) compartment, and there is a separation between detected and undetected infected people (I). Our analysis shows that there are two equilibria, namely, disease free equilibrium and endemic equilibrium. by using, Lyapunov function, we demonstrated that disease free is globally asymptotically stable if R0 < 1, and disease-free becomes unstable if R0 > 1. This result reveal that the intervention of infection rate and quarantine process are important to control and achieve global stability of disease-free equilibrium
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Shaghaghi, Navid, Andres Calle, George Kouretas, Jaidev Mirchandani, and Michael Castillo. "eVision: Epidemic Forecasting on COVID-19." Current Directions in Biomedical Engineering 7, no. 2 (October 1, 2021): 839–42. http://dx.doi.org/10.1515/cdbme-2021-2214.
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Abstract Vaccination is the primary strategy to prevent COVID-19 illness and hospitalization. However, supplies are scarce and due to the regional mutations of the virus, new vaccines or booster shots will need to be administered potentially regularly. Hence, the prediction of the rate of growth of COVID-19 cases is paramount to ensuring the ample supply of vaccines as well as for local, state, and federal government measures to ensure the availability of hospital beds, supplies, and staff. eVision is an epidemic forecaster aimed at combining Machine Learning (ML) - in the form of a Long Short-Term Memory (LSTM) Recursive Neural Network (RNN) - and search engine statistics, in order to make accurate predictions about the weekly number of cases for highly communicable diseases. By providing eVision with the relative popularity of carefully selected keywords searched via Google along with the number of positive cases reported from the US Centers for Disease Control and Prevention (CDC) and/or the World Health Organization (WHO) the model can make highly accurate predictions about the trend of the outbreak by learning the relationship between the two trends. Thus, in order to predict the trend of the outbreak in a specific region, eVision is provided with a weekly count of the number of COVID-19 cases in a region along with statistics surrounding common symptom search phrases such as “loss of smell” and “loss of taste” that have been searched on Google in that region since the start of the pandemic. eVision has, for instance, been able to achieve an accuracy of %89 for predicting the trend of the COVID-19 outbreak in the United States
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Bhutia, Santosini, Bichitrananda Patra, and Mitrabinda Ray. "COVID-19 epidemic: analysis and prediction." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 2 (June 1, 2022): 736. http://dx.doi.org/10.11591/ijai.v11.i2.pp736-745.
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“Novel Coronavirus”, commonly known as COVID-19 has spread nearly to the entire world. The number of impacted cases and deaths has increased significantly in each country, posing a challenge for the world’s health organizations. The goal of this paper was to better comprehend and analyze the growth of the disease in India, including confirmed, recovered, fatalities, and active cases of COVID-19. Data analysis affects an organization’s decision-making process with interactive visual representation. The proposed model was an ensemble model that was built using linear regression, polynomial regression, and support vector machine (SVM) regression models. The model predicted the number of confirmed cases from 30 th May 2021 to 15 th June 2021 based on the data available from 22 January 2020 to 29 May 2021 and improved accuracy was obtained when compared with the actual data. Forecasting the confirmed cases might assist health organizations in planning medical facilities. Following that, an appropriate machine leraning (ML) model must be found that can predict the number of new cases in the future.
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Wang, Hongling, Yafei Zhang, Lan Liu, Xiaodan Zhang, and Qiu Zhao. "ERCP during the COVID-19 epidemic." Endoscopy 52, no. 10 (September 23, 2020): 933–34. http://dx.doi.org/10.1055/a-1194-4745.
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Watson, Roger, and Mark Hayter. "The COVID‐19 epidemic of manuscripts." Journal of Advanced Nursing 76, no. 10 (June 12, 2020): 2454–55. http://dx.doi.org/10.1111/jan.14437.
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Nickalls, Kelly. "COVID-19 and the loneliness epidemic." Practice Nursing 31, no. 11 (November 2, 2020): 445. http://dx.doi.org/10.12968/pnur.2020.31.11.445.
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Rothkrantz, Leon. "Distant Learning during Covid-19 Epidemic." Communication & Cognition 55, no. 1-2 (June 2022): 3–20. http://dx.doi.org/10.57028/c55-003-z1020.
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During the academic year 2020-2021 Universities in the Netherlands were closed because of the COVID-19 pandemic. All real life lectures were replaced by distant learning. It was expected that during the academic year new innovative ways of digital teaching-learning have been developed. But it proved that most teachers used classical web-lectures to teach their classes. Even though students have access to learning material any time and any place, current tools for e-learning still have their limitations. The main shortcoming, compared to real life learning is the limited opportunity for human like interaction between student, teacher and material. Another problem is that web-lectures are self-paced programs, offered asynchronously. They allow students to take the course anytime, anywhere. This is an advantage for some students, but others miss the self-control to take and complete courses. They miss the social control of peer students and teachers. It proves that about 25% of students of Universities in the Netherlands suffer from burnout symptoms at the end of the academic year. These students suffered from feelings of loneliness, unhappiness, stress, nervousness, having a negative effect on their well-being sometimes resulting in a burn-out or depression. In this paper we report about a MOOC based on serious gaming technology, stimulating interaction and cooperation between participants.
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Gaidai, Oleg, and Yihan Xing. "COVID-19 Epidemic Forecast in Brazil." Bioinformatics and Biology Insights 17 (January 2023): 117793222311619. http://dx.doi.org/10.1177/11779322231161939.
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This study advocates a novel spatio-temporal method for accurate prediction of COVID-19 epidemic occurrence probability at any time in any Brazil state of interest, and raw clinical observational data have been used. This article describes a novel bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient time period, resulting in robust long-term forecast of the virus outbreak probability. COVID-19 daily numbers of recorded patients in all affected Brazil states were taken into account. This work aimed to benchmark novel state-of-the-art methods, making it possible to analyse dynamically observed patient numbers while taking into account relevant regional mapping. Advocated approach may help to monitor and predict possible future epidemic outbreaks within a large variety of multi-regional biological systems. Suggested methodology may be used in various modern public health applications, efficiently using their clinical survey data.
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Sokolovsky, V. L., G. B. Furman, D. A. Polyanskaya, and E. G. Furman. "Spatio-temporal modeling of COVID-19 epidemic." Health Risk Analysis, no. 1 (March 2021): 23–37. http://dx.doi.org/10.21668/health.risk/2021.1.03.eng.
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In autumn and winter 2020–2021 there was a growth in morbidity with COVID-19. Since there are no efficient medications and mass vaccination has only just begun, quarantine, limitations on travels and contacts between people as well as use of personal protection equipment (masks) still remain priority measures aimed at preventing the disease from spreading. In this work we have analyzed how the epidemic developed and what impacts quarantine measures exerted on the disease spread; to do that we applied various mathematical models. It was shown that simple models belonging to SIR-type (S means susceptible; I, infected; and R, recovered or removed from the infected group) allowed estimating certain model parameters such as morbidity and recovery coefficients that could be used in more complicated models. We examined spatio-temporal epidemiologic models based on finding solutions to non-stationary two-dimensional reaction-diffusion equations. Such models allow taking into account uneven distribution of population, changes in population mobility, and changes in frequency of contacts between susceptible and infected people due to quarantine. We applied obtained analytical and numerical solutions to analyze different stages in the epidemic as well as its wave-like development influenced by imposing and canceling quarantine limitations. To take into account ultimate rate at which the disease spreads and its incubation period (when an infected person is not a source of contagion), we suggest using equations similar to the Cattaneo-Vernotte one. The suggested model allows predicting where the front of morbidity spread is going to occur, that is, a moving frontier between areas where there are infected people and areas where they are absent. Use of such models provides an opportunity to introduce differential quarantine measures basing on more objective grounds. At the end of 2020 mass vaccination started in some countries. We estimated a necessary number of people that had to be vaccinated so that new waves of COVID-19 epidemic would be prevented; in our estimates, not less than 80% of the country population should be vaccinated. Correct prediction of epidemic development is becoming more and more vital at the moment due to new and more contagious COVID-19 virus strains occurring in England, South Africa, and some other countries. Our research results can be used for predicting spread of COVID-19 and other communicable diseases; they can make for taking the most efficient measures for successful control over epidemics.
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Zeng, Pinhong. "On the Transmission of COVID-19 and Its Prevention and Control Management." Discrete Dynamics in Nature and Society 2021 (July 27, 2021): 1–10. http://dx.doi.org/10.1155/2021/9629816.
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The spread of an epidemic is a typical public emergency and also one of the major problems that humans need to tackle in the 21st century. Therefore, the research on the spread, prevention, and control of epidemics is quite an essential task. This paper first briefly described and analyzed the development of COVID-19 and then introduced the basic epidemic models and idealized the population in the epidemic area by dividing them into four categories (Classes S, E, I, and R). After that, it set the relevant parameters of the basic SEIR model and the modified one and worked out the relevant differential equations and iterative equations. According to the feature of the epidemic situation and the changes in the number of contacts in different units of time, the epidemic data were substituted into the iterative equations for data fitting with an R Package. Then, analysis was performed on the epidemiological features such as the transmission time and epidemic peak and the epidemic trend was evaluated. Finally, sensitivity analysis was conducted on the parameters (government control and recovery rate), and the results showed that measures such as government restrictions on travel (reducing the contacts between virus carriers and susceptible persons) can effectively control the scale of the outbreak.
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Alrasheed, Hend, Alhanoof Althnian, Heba Kurdi, Heila Al-Mgren, and Sulaiman Alharbi. "COVID-19 Spread in Saudi Arabia: Modeling, Simulation and Analysis." International Journal of Environmental Research and Public Health 17, no. 21 (October 23, 2020): 7744. http://dx.doi.org/10.3390/ijerph17217744.
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The novel coronavirus Severe Acute Respiratory Syndrome (SARS)-Coronavirus-2 (CoV-2) has resulted in an ongoing pandemic and has affected over 200 countries around the world. Mathematical epidemic models can be used to predict the course of an epidemic and develop methods for controlling it. As social contact is a key factor in disease spreading, modeling epidemics on contact networks has been increasingly used. In this work, we propose a simulation model for the spread of Coronavirus Disease 2019 (COVID-19) in Saudi Arabia using a network-based epidemic model. We generated a contact network that captures realistic social behaviors and dynamics of individuals in Saudi Arabia. The proposed model was used to evaluate the effectiveness of the control measures employed by the Saudi government, to predict the future dynamics of the disease in Saudi Arabia according to different scenarios, and to investigate multiple vaccination strategies. Our results suggest that Saudi Arabia would have faced a nationwide peak of the outbreak on 21 April 2020 with a total of approximately 26 million infections had it not imposed strict control measures. The results also indicate that social distancing plays a crucial role in determining the future local dynamics of the epidemic. Our results also show that the closure of schools and mosques had the maximum impact on delaying the epidemic peak and slowing down the infection rate. If a vaccine does not become available and no social distancing is practiced from 10 June 2020, our predictions suggest that the epidemic will end in Saudi Arabia at the beginning of November with over 13 million infected individuals, and it may take only 15 days to end the epidemic after 70% of the population receive a vaccine.
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Popovskiy, Yuri B., and Nikolay I. Shchepetkov. "Insolation And Covid‑19: Protection From The Aggressor." Volume 28, Number 6, 2020, no. 03-2020 (December 2020): 4–8. http://dx.doi.org/10.33383/2020-029.
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The article reviews the importance of insolation as a factor of prevention and containment of infectious diseases and epidemics. The authors consider insolation not as a mean of curing the Сoronavirus Disease (WHO fairly calls such possibility “a myth”) but as a means to lower the risks of dissemination of the infection, to reduce viability of the virus in the environment, to support human protective immune mechanisms affecting susceptibility of the population as a whole, severity and recovery time, i.e. both sanitary and hygienic and prevention factors of the COVID‑19 epidemic containment. Apart from the germicidal and virucidal sanitising effects of solar rays, the article reviews anti-epidemic capabilities of insolation as a microclimate factor and a psychological and physiological regulator of human protective capabilities as well as the insolation standards as a mechanism of development density regulation. It is impossible to efficiently combat massive dissemination of highly contagious infections without concerted utilisation of all available means and measures: both medical and preventive and organisational. The unprecedented mobilisation of healthcare systems and large-scale restrictive quarantine measures are under special attention of the society. This article reviews the importance of insolation as a universal natural anti-epidemic factor which is undeservedly placed in the end of the list of effective infection combating measures.
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Elhadad, Sara, Zoltan Orban, and Attila Fülöp. "Pandemic COVID-19: challenge strategic decisions on building in Egypt." Acta Technica Jaurinensis 16, no. 2 (May 31, 2023): 83–89. http://dx.doi.org/10.14513/actatechjaur.00696.
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COVID-19 threatens the livelihood and lives of people all over the world. Presently, the disease presents a major health concern in Egypt and all over the world. Evaluating the built and physical environment is one of the solutions to reduce epidemic impact before developing its medications (as “prevention”). Epidemics have altered the usage of our built environment because of the infection fear. As a result, urbanism and architecture will never be the same after the COVID-19 epidemic. However, the current global epidemic poses significant challenges in the built environment at all levels, developing an antivirus-enabled paradigm to stop the spreading of virus or decrease the potential risks will take time. Many unanswered questions require further multidisciplinary studies. This investigation provides an overview for impact of the current COVID-19 Pandemic on the field of residential architecture and how it might change the architecture of built environment.
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Kubar, O. I. "Ethical comments on COVID-19." Russian Journal of Infection and Immunity 10, no. 2 (May 22, 2020): 287–94. http://dx.doi.org/10.15789/2220-7619-eco-1447.
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Over decades, the St. Petersburg Pasteur Institute has been conducting research on Ethical and legal aspects of infectious diseases. One of the areas in this study focuses on ethical issue in the planning and management during epidemics and pandemics. This concept becomes extremely relevant in the situation of the COVID-19 coronavirus pandemic, which has determined the urgent need for rapid updates on this issue and analyzing compliance of decisions and actions undertaken to ethical and legal regulations in Russia and abroad. The rational and practical side of following the global ideology of ethical commitment during worldwide threats due to spread of infectious diseases is aimed to facilitate in preventing violated integrity of anti-epidemic measures, formation of social unity and, finally, to ensure stability of human values, which will be discussed in this study.
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Maurya, Vikash, Sumit Anshul, Aakash ., and Umang Rastogi. "Dealing With Covid-19." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 2344–47. http://dx.doi.org/10.22214/ijraset.2022.42832.
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Abstract: Different Indian groups, private government and civil society organizations had developed different strategies to combat Covid-19 unique threat through measures such as escalation vaccines and sample testing per day. In this focused review, we discussed the challenges they face and the success stories used to manage COVID-19. With the first wave of the Covid-19 epidemic starting late last year, India had just over 1.5 million isolated beds in all of the 15,375 billion medical facilities of 1.38 billion people. That translates to skosh over 1 bed per 1,000 people. Only 18% of these were oxygen-supported beds, according to the 2020-21 annual report of the Department of Health and Family Welfare. Keywords: Covid, India, beds, government, epidemic .
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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.