943 10 20655 http://socictopen.socict.org/files/original/d8fb6b39dd1920dc7c5c19295bf61ba5.pdf 059973b455333ac432339bee124d9c19 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Agricultura sostenible Description An account of the resource Dominio científico: Agricultura sostenible Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource For a significant geography: readings on urban agriculture and the importance of fieldwork for research and teaching geography / Por uma Geografia significativa: leituras sobre a agricultura urbana e a importância do trabalho de campo para a pesquisa e o ensino de Geografia Creator An entity primarily responsible for making the resource Leandro Matias dos Santos, Michelle Emanuelle Silva, Cirlene Jeane Santos e Santos Description An account of the resource This article is based on the fieldwork carried out by researchers from NUAGRARIOtogether with the students of the 5th period of the subject Agrarian Geography, of the GeographyCourses (licenciatura and baccalaureate), Federal University of Alagoas on Urban Agriculture, in themunicipality of Maceió -AL. In order to verify if the selected areas virtually contained the practice ofurban agriculture. In this way, the main objective of the article is to demonstrate the importance of thework of campo no process of social formation through the understanding, observation and recognition ofreality, highlighting the geographic contents that can be approached through this methodology. Date A point or period of time associated with an event in the lifecycle of the resource 2018 Subject The topic of the resource Fieldwork. Teaching Geography, urban agriculture Identifier An unambiguous reference to the resource within a given context 10.17648/diversitas-journal-v3i1.596 Source A related resource from which the described resource is derived Diversitas Journal Publisher An entity responsible for making the resource available Universidade Estadual de Alagoas Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Social Sciences, Education, Science Relation A related resource <a href="https://doi.org/10.17648/diversitas-journal-v3i1.596" target="_blank" rel="noreferrer noopener">https://doi.org/10.17648/diversitas-journal-v3i1.596</a> http://socictopen.socict.org/files/original/d9e437fc18bbe4c7439e9b4b100bd776.pdf 557ba6241e7956448451e0939b2439e2 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Agricultura sostenible Description An account of the resource Dominio científico: Agricultura sostenible Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Foraminíferos Bentónicos y su relación con la materia orgánica particulada en el sedimento Foraminíferos Bentónicos y su relación con la materia orgánica particulada en el sedimento Creator An entity primarily responsible for making the resource Parada Ruffinatti Carmen, Losada Muñoz Diego Description An account of the resource The relation between some benthic foraminiferal species and the biocenosis with the organic particules rich substrate in a coastal lagoon surrounded by magrove forest, is stablisheci.Se establece la relación entre algunas especies de foraminíferos bentónicos y de la biocenosis en general, con el substrato rico en materia orgánica particulada de origen vegetal, en una laguna costera rodeada de manglares. Date A point or period of time associated with an event in the lifecycle of the resource 1986 Subject The topic of the resource Ammonia beccarii, Ecología de manglares, Foraminíferos bentônicos, biocenosis Source A related resource from which the described resource is derived Caldasia Publisher An entity responsible for making the resource available Universidad Nacional de Colombia Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science, Botany, Zoology Relation A related resource <a href="http://www.revistas.unal.edu.co/index.php/cal/article/view/34958" target="_blank" rel="noreferrer noopener">http://www.revistas.unal.edu.co/index.php/cal/article/view/34958</a> http://socictopen.socict.org/files/original/3338e9f5d9149b80a3cfbc731e1e0418.pdf 98e403b5efe39502f992d3b527bfda63 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Forecast Possible Risk for COVID-19 Epidemic Dissemination Under Current Control Strategies in Japan Creator An entity primarily responsible for making the resource Jun Yang, Binxiang Dai, Zhongxiang Chen Description An account of the resource COVID-19 has globally spread to over 4 million people and the epidemic situation in Japan is very serious. The purpose of this research was to assess the risk of COVID-19 epidemic dissemination in Japan by estimating the current state of epidemic dissemination and providing some epidemic prevention and control recommendations. Firstly, the period from 6 January to 31 March 2020 was divided into four stages and the relevant parameters were estimated according to the imported cases in Japan. The basic reproduction number of the current stage is 1.954 (95% confidence interval (CI) 1.851–2.025), which means COVID-19 will spread quickly, and the self-healing rate of Japanese is about 0.495 (95% CI 0.437–0.506), with small variations in the four stages. Secondly, the results were applied to the actual reported cases from 1 to 5 April 2020, verifying the reliability of the estimated data using the accumulated reported cases located within the 95% confidence interval and the relative error of forecast data of five days being less than 2 . 5 % . Thirdly, considering the medical resources in Japan, the times the epidemic beds and ventilators become fully occupied are predicted as 5 and 15 May 2020, respectively. Keeping with the current situation, the final death toll in Japan may reach into the millions. Finally, based on experience with COVID-19 prevention and control in China, robust measures such as nationwide shutdown, store closures, citizens isolating themselves at home, and increasing PCR testing would quickly and effectively prevent COVID-19 spread. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Basic reproduction number, COVID-19, SEIHR epidemic model Identifier An unambiguous reference to the resource within a given context DOI: 10.3390/ijerph17113872 Source A related resource from which the described resource is derived International Journal of Environmental Research and Public Health Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine http://socictopen.socict.org/files/original/c4d9e9b99008ff317cd4e8e05153d0d9.pdf 98e403b5efe39502f992d3b527bfda63 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Forecast Possible Risk for COVID-19 Epidemic Dissemination Under Current Control Strategies in Japan Creator An entity primarily responsible for making the resource Zhongxiang Chen, Jun Yang, Binxiang Dai Description An account of the resource COVID-19 has globally spread to over 4 million people and the epidemic situation in Japan is very serious. The purpose of this research was to assess the risk of COVID-19 epidemic dissemination in Japan by estimating the current state of epidemic dissemination and providing some epidemic prevention and control recommendations. Firstly, the period from 6 January to 31 March 2020 was divided into four stages and the relevant parameters were estimated according to the imported cases in Japan. The basic reproduction number of the current stage is 1.954 (95% confidence interval (CI) 1.851–2.025), which means COVID-19 will spread quickly, and the self-healing rate of Japanese is about 0.495 (95% CI 0.437–0.506), with small variations in the four stages. Secondly, the results were applied to the actual reported cases from 1 to 5 April 2020, verifying the reliability of the estimated data using the accumulated reported cases located within the 95% confidence interval and the relative error of forecast data of five days being less than 2 . 5 % . Thirdly, considering the medical resources in Japan, the times the epidemic beds and ventilators become fully occupied are predicted as 5 and 15 May 2020, respectively. Keeping with the current situation, the final death toll in Japan may reach into the millions. Finally, based on experience with COVID-19 prevention and control in China, robust measures such as nationwide shutdown, store closures, citizens isolating themselves at home, and increasing PCR testing would quickly and effectively prevent COVID-19 spread. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource covid-19, basic reproduction number, SEIHR epidemic model Identifier An unambiguous reference to the resource within a given context 10.3390/ijerph17113872 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine http://socictopen.socict.org/files/original/fe2f3e686e0d492514a13ae3fd566e72.pdf 3824a2dea921d27278e0edabd7f0daec Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Forecasting and Evaluating Multiple Interventions for COVID-19 Worldwide Creator An entity primarily responsible for making the resource Li Jin, Eric Boerwinkle, Momiao Xiong, Zixin Hu, Qiyang Ge, Shudi Li Description An account of the resource As the Covid-19 pandemic surges around the world, questions arise about the number of global cases at the pandemic's peak, the length of the pandemic before receding, and the timing of intervention strategies to significantly stop the spread of Covid-19. We have developed artificial intelligence (AI)-inspired methods for modeling the transmission dynamics of the epidemics and evaluating interventions to curb the spread and impact of COVID-19. The developed methods were applied to the surveillance data of cumulative and new COVID-19 cases and deaths reported by WHO as of March 16th, 2020. Both the timing and the degree of intervention were evaluated. The average error of five-step ahead forecasting was 2.5%. The total peak number of cumulative cases, new cases, and the maximum number of cumulative cases in the world with complete intervention implemented 4 weeks later than the beginning date (March 16th, 2020) reached 75,249,909, 10,086,085, and 255,392,154, respectively. However, the total peak number of cumulative cases, new cases, and the maximum number of cumulative cases in the world with complete intervention after 1 week were reduced to 951,799, 108,853 and 1,530,276, respectively. Duration time of the COVID-19 spread was reduced from 356 days to 232 days between later and earlier interventions. We observed that delaying intervention for 1 month caused the maximum number of cumulative cases reduce by −166.89 times that of earlier complete intervention, and the number of deaths increased from 53,560 to 8,938,725. Earlier and complete intervention is necessary to stem the tide of COVID-19 infection. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource forecasting, artificial intelligence, time series, autoencoder, Transmission dynamics, COVID-19 Identifier An unambiguous reference to the resource within a given context DOI: 10.3389/frai.2020.00041 Source A related resource from which the described resource is derived Frontiers in Artificial Intelligence Publisher An entity responsible for making the resource available Frontiers Media S.A. Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Electronic computers. Computer science http://socictopen.socict.org/files/original/0526b37f8074e8a3bd97215267a24dae.pdf 92d784ad17303aeacfa010c9a0512b8b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Forecasting COVID-19 Creator An entity primarily responsible for making the resource Matjaž Perc, Nina Gorišek Miksić, Mitja Slavinec, Andraž Stožer Description An account of the resource The World Health Organization declared the coronavirus disease 2019 a pandemic on March 11th, pointing to the over 118,000 cases in over 110 countries and territories around the world at that time. At the time of writing this manuscript, the number of confirmed cases has been surging rapidly past the half-million mark, emphasizing the sustained risk of further global spread. Governments around the world are imposing various containment measures while the healthcare system is bracing itself for tsunamis of infected individuals that will seek treatment. It is therefore important to know what to expect in terms of the growth of the number of cases, and to understand what is needed to arrest the very worrying trends. To that effect, we here show forecasts obtained with a simple iteration method that needs only the daily values of confirmed cases as input. The method takes into account expected recoveries and deaths, and it determines maximally allowed daily growth rates that lead away from exponential increase toward stable and declining numbers. Forecasts show that daily growth rates should be kept at least below 5% if we wish to see plateaus any time soon—unfortunately far from reality in most countries to date. We provide an executable as well as the source code for a straightforward application of the method on data from other countries. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource COVID-19, Pandemic, disease dynamics, exponential growth, virality Identifier An unambiguous reference to the resource within a given context DOI: 10.3389/fphy.2020.00127 Source A related resource from which the described resource is derived Frontiers in Physics Publisher An entity responsible for making the resource available Frontiers Media S.A. Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Physics Language A language of the resource EN http://socictopen.socict.org/files/original/3c9dd295e113e2d5e848e46ac3034f7d.pdf 9cb7bef2dbcf2a88c0e0455cb4e07d09 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Forecasting COVID-19 in Morocco Creator An entity primarily responsible for making the resource Mohammed Layelmam, Y. Ahmed Laaziz, Said Benchelha, Yahya Diyer, Sarra Rarhibou Description An account of the resource The COVID-19 has become a public health emergency of international concern. As of April 26, 2020, this pandemic has caused in Morocco more than 4065 confirmed infections and more than 161 reported deaths. To mitigate this epidemic threat and act quickly, it is very important to monitor and analyze changing trends and predict what might happen in the future. The main objective of this paper is to develop a successful prediction. We used in this study at the end of each week the TBATS model to forecast confirmed cases. This model is calculated on the basis of the daily historical data. From the results obtained we can conclude that the predictions obtained are close to reality and for the peak of this epidemic is not yet identified. The obtained results shows that this epidemics will continue to grow. For our forecast from 04/27/2020 to 05/03/2020 we estimate that the number of affected cases will achieve 4367 cases. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource forecasting, coronavirus, Morocco, COVID-19, TBATS Identifier An unambiguous reference to the resource within a given context DOI: 10.5799/jcei/8264 Source A related resource from which the described resource is derived Journal of Clinical and Experimental Investigations Publisher An entity responsible for making the resource available Association of Health Investigations Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine http://socictopen.socict.org/files/original/7155e2c261e6f8cc44e88d0353af704e.pdf 610c378eba60050573ea4c6c8f0990bd Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model Creator An entity primarily responsible for making the resource Jacopo Lenzi, Riccardo Valentini, Biao Tang, Maria Pia Fantini, Alessandro Lanza, Davide Gori, Antonio Navarra, Chiara Reno, Eleonora Barelli Description An account of the resource The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world’s centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource coronavirus, Pandemic, public health intervention, SARS-CoV-2, COVID-19, lockdown Identifier An unambiguous reference to the resource within a given context DOI: 10.3390/jcm9051492 Source A related resource from which the described resource is derived Journal of Clinical Medicine Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine http://socictopen.socict.org/files/original/b3aa896fbbb991d0dd332bbd4c5379f2.pdf 221ab4fabad0d6961227bcb17eed9875 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran) Creator An entity primarily responsible for making the resource T.T. Tran, L.T. Pham, Q.X. Ngo Description An account of the resource Currently, the pandemic caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the most serious issues worldwide. SARS-CoV-2 was first observed in Wuhan, China, on December 31, 2019; this disease has been rapidly spreading worldwide. Iran was the first Middle East country to report a coronavirus death, it has been severely affected. Therefore, it is crucial to forecast the pandemic spread in Iran. This study aims to develop a prediction model for the daily total confirmed cases, total confirmed new cases, total deaths, total new deaths, growth rate in confirmed cases, and growth rate in deaths. The model utilizes SARS-CoV-2 daily data, which are mainly collected from the official website of the European Centre for Disease Prevention and Control from February 20 to May 04, 2020 and other appropriated references. Autoregressive integrated moving average (ARIMA) is employed to forecast the trend of the pandemic spread. The ARIMA model predicts that Iran can easily exhibit an increase in the daily total confirmed cases and the total deaths, while the daily total confirmed new cases, total new deaths, and growth rate in confirmed cases/deaths becomes stable in the near future. This study predicts that Iran can control the SARS-CoV-2 disease in the near future. The ARIMA model can rapidly aid in forecasting patients and rendering a better preparedness plan in Iran. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Prediction, Iran, epidemic, Autoregressive Integrated Moving Average (ARIMA), covid-19 coronavirus Identifier An unambiguous reference to the resource within a given context DOI: 10.22034/GJESM.2019.06.SI.01 Source A related resource from which the described resource is derived Global Journal of Environmental Science and Management Publisher An entity responsible for making the resource available Global Journal of Environmental Science and Management Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Environmental sciences http://socictopen.socict.org/files/original/74c7df4c0ff645da5c16fec602495ffb.pdf 3eb1a86de5c1106502c89b4e63825a2c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique Creator An entity primarily responsible for making the resource B Datta, S. K. Tamang, P.D. Singh Description An account of the resource Artificial neural network is considered one of the most efficient methods in processing huge data sets that can be analyzed computationally to reveal patterns, trends, prediction, forecasting etc. It has a great prospective in engineering as well as in medical applications. The present work employs artificial neural network-based curve fitting techniques in prediction and forecasting of the Covid-19 number of rising cases and death cases in India, USA, France, and UK, considering the progressive trends of China and South Korea. In this paper, three cases are considered to analyze the outbreak of Covid-19 pandemic viz., (i) forecasting as per the present trend of rising cases of different countries (ii) forecasting of one week following up with the improvement trends as per China and South Korea, and (iii) forecasting if followed up the progressive trends as per China and South Korea before a week. The results have shown that ANN can efficiently forecast the future cases of COVID 19 outbreak of any country. The study shows that the confirmed cases of India, USA, France and UK could be about 50,000 to 1,60,000, 12,00,000 to 17,00,000, 1,40,000 to 1,50,000 and 2,40,000 to 2,50,000 respectively and may take about 2 to 10 months based on progressive trends of China and South Korea.  Similarly, the death toll for these countries just before controlling could be about 1600 to 4000 for India, 1,35,000 to 1,00,000 for USA, 40,000 to 55,000 for France, 35,000 to 47,000 for UK during the same period of study. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Artificial Neural Network (ANN), coronavirus covid-19, ann-curve fitting, forecast modelling Identifier An unambiguous reference to the resource within a given context DOI: 10.22034/GJESM.2019.06.SI.06 Source A related resource from which the described resource is derived Global Journal of Environmental Science and Management Publisher An entity responsible for making the resource available Global Journal of Environmental Science and Management Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Environmental sciences