Covid-19 Dataset: Worldwide spread log including countries first case and first death.
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ABSTRACT:
SUBMITTER: Ali H
PROVIDER: S-EPMC7430301 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The outbreak of novel COVID-19 disease elicited a wide range of anti-contagion and economic policies like school closure, income support, contact tracing, and so forth, in the mitigation and suppression of the spread of the SARS-CoV-2 virus. However, a systematic evaluation of these policies has not been made. Here, 17 implemented policies from the Oxford COVID-19 Government Response Tracker dataset employed in 90 countries from December 31, 2019, to August 31, 2020, were analyzed. A Poisson regression model was applied to analyze the relationship between policies and daily confirmed cases using a generalized estimating equations approach. A lag is a fixed time displacement in time series data. With that, lagging (0, 3, 7, 10, and 14 days) was also considered during the analysis since the effects of policies implemented on a given day may affect the number of confirmed cases several days after implementation. The countries were divided into three groups depending on the number of waves of the pandemic observed in each country. Through subgroup analysis, we showed that with and without lagging, contact tracing and containment policies were significant for countries with two waves, while closing, economic, and health policies were significant for countries with three waves. Wave-specific analysis for each wave showed that significant health, economic, and containment policies varied across waves of the pandemic. Emergency investment in healthcare was consistently significant among the three groups of countries, while the Stringency index was significant among all waves of the pandemic. These findings may help in making informed decisions regarding whether, which, or when these policies should be intensified or lifted.
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Project description:BackgroundThe highly pathogenic H5N1 avian influenza virus, which is now widespread in Southeast Asia and which diffused recently in some areas of the Balkans region and Western Europe, has raised a public alert toward the potential occurrence of a new severe influenza pandemic. Here we study the worldwide spread of a pandemic and its possible containment at a global level taking into account all available information on air travel.Methods and findingsWe studied a metapopulation stochastic epidemic model on a global scale that considers airline travel flow data among urban areas. We provided a temporal and spatial evolution of the pandemic with a sensitivity analysis of different levels of infectiousness of the virus and initial outbreak conditions (both geographical and seasonal). For each spreading scenario we provided the timeline and the geographical impact of the pandemic in 3,100 urban areas, located in 220 different countries. We compared the baseline cases with different containment strategies, including travel restrictions and the therapeutic use of antiviral (AV) drugs. We investigated the effect of the use of AV drugs in the event that therapeutic protocols can be carried out with maximal coverage for the populations in all countries. In view of the wide diversity of AV stockpiles in different regions of the world, we also studied scenarios in which only a limited number of countries are prepared (i.e., have considerable AV supplies). In particular, we compared different plans in which, on the one hand, only prepared and wealthy countries benefit from large AV resources, with, on the other hand, cooperative containment scenarios in which countries with large AV stockpiles make a small portion of their supplies available worldwide.ConclusionsWe show that the inclusion of air transportation is crucial in the assessment of the occurrence probability of global outbreaks. The large-scale therapeutic usage of AV drugs in all hit countries would be able to mitigate a pandemic effect with a reproductive rate as high as 1.9 during the first year; with AV supply use sufficient to treat approximately 2% to 6% of the population, in conjunction with efficient case detection and timely drug distribution. For highly contagious viruses (i.e., a reproductive rate as high as 2.3), even the unrealistic use of supplies corresponding to the treatment of approximately 20% of the population leaves 30%-50% of the population infected. In the case of limited AV supplies and pandemics with a reproductive rate as high as 1.9, we demonstrate that the more cooperative the strategy, the more effective are the containment results in all regions of the world, including those countries that made part of their resources available for global use.
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Project description:Recently, a new respiratory infectious disease called COVID-19 has emerged and created a global emergency. It was initially linked to the animal-to-human transmission. However, it is now thought that COVID-19 is spreading through human-to-human transmission mainly via droplets. As there is no definite antiviral therapy for the treatment of cases with COVID-19 the best option for slowing down the pandemic and reducing mortality rates is protection against the virus of interest. To achieve this goal obtaining information about how first cases infected with COVID-19 is crucial. Hence, this study aims to review the studies published in peer-reviewed journals to report the first confirmed cases with COVID-19. Herein, we review the origin, symptoms, diagnostic tests, and progress of the disease and possible actions of authorities which would be effective in similar pandemics in the future. This study reviewed 13 cases (5 females and 8 males; 25-61 years old) from 10 countries. All cases have recovered from COVID-19. The results of this review suggested that timely reports of the confirmed cases, notifying World Health Organization and providing information to the general population about the methods of spreading the virus would have decreased the number of infected cases and mortality rates. In addition, the travel history of the first confirmed cases in various countries suggested that prompt actions in restricting travels and closing borders could be an efficient strategy in preventing the transmission of the disease outside of the affected sites. Efforts should be taken by health authorities for preparing the world for future epidemic/pandemic in terms of developing advanced screening strategies in the borders and diagnostic strategies for early identification of infected cases.
| S-EPMC7492837 | biostudies-literature
Project description:There is a worldwide effort of the research community to explore the medical, economic and sociologic impact of the COVID-19 pandemic. Many different disciplines try to find solutions and drive strategies to a great variety of different very crucial problems. The present study presents a novel analysis which results to clustering countries with respect to active cases, active cases per population and active cases per population and per area based on Johns Hopkins epidemiological data. The presented cluster results could be useful to a variety of different policy makers, such as physicians and managers of the health sector, economy/finance experts, politicians and even to sociologists. In addition, our work suggests a new specially designed clustering algorithm adapted to the request for comparison of the various COVID time-series of different countries.
| S-EPMC7258836 | biostudies-literature
Project description:Recent outbreaks of Zika virus (ZIKV) infections in Oceania's islands and the Americas were characterized by high numbers of cases and the spread of the virus to new areas. To better understand the origin of ZIKV, its epidemic history was reviewed. Although the available records and information are limited, two major genetic lineages of ZIKV were identified in previous studies. However, in this study, three lineages were identified based on a phylogenetic analysis of all virus sequences from GenBank, including those of the envelope protein (E) and non-structural protein 5 (NS5) coding regions. The spatial and temporal distributions of the three identified ZIKV lineages and the recombination events and mechanisms underlying their divergence and evolution were further elaborated. The potential migration pathway of ZIKV was also characterized. Our findings revealed the central roles of two African countries, Senegal and Cote d'Ivoire, in ZIKV evolution and genotypic divergence. Furthermore, our results suggested that the outbreaks in Asia and the Pacific islands originated from Africa. The results provide insights into the geographic origins of ZIKV outbreaks and the spread of the virus, and also contribute to a better understanding of ZIKV evolution, which is important for the prevention and control of ZIKV infections.
| S-EPMC8193378 | biostudies-literature
Project description:BackgroundDENV-1 is one of the four viral serotypes that causes Dengue, the most common mosquito-borne viral disease of humans. The prevalence of these viruses has grown in recent decades and is now present in more than 100 countries. Limited studies document the spread of DENV-1 over the world despite its importance for human health.Methodology/principal findingsWe used representative DENV-1 envelope gene sequences to unravel the dynamics of viral diffusion under a Bayesian phylogeographic approach. Data included strains from 45 distinct geographic locations isolated from 1944 to 2009. The estimated mean rate of nucleotide substitution was 6.56 × 10?? substitutions/site/year. The larger genotypes (I, IV and V) had a distinctive phylogenetic structure and since 1990 they experienced effective population size oscillations. Thailand and Indonesia represented the main sources of strains for neighboring countries. Besides, Asia broadcast lineages into the Americas and the Pacific region that diverged in isolation. Also, a transmission network analysis revealed the pivotal role of Indochina in the global diffusion of DENV-1 and of the Caribbean in the diffusion over the Americas.Conclusions/significanceThe study summarizes the spatiotemporal DENV-1 worldwide spread that may help disease control.
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Project description:COVID-19 has now taken a frightening form. As the days pass, it is becoming more and more widespread and now it has become an epidemic. The death rate, which was earlier in the hundreds, changed to thousands and then progressed to millions. If the same situation persists over time, the day is not far when the humanity of all the countries on the globe will be endangered and we yearn for breath. From January 2020 till now, many scientists, researchers and doctors have been trying to solve this complex problem so that proper arrangements can be made by the governments in the hospitals and the death rate can be reduced. The presented research article shows the estimated mortality rate by the ARIMA model and the regression model. This dataset has been collected precisely from DataHub-Novel Coronavirus 2019-Dataset from 22nd January to 29th June 2020. To show the current mortality rate of the entire subject, the correlation coefficients of attributes (MAE, MSE, RMSE and MAPE) were used, where the average absolute percentage error validated the model by 99.09%. The ARIMA model is used to generate auto_arima SARIMAX results, auto_arima residual plots, ARIMA model results, and corresponding prediction plots on the training dataset. These data indicate a continuous decline in death cases. By applying a regression model, the coefficients generated by the regression model are estimated, and the actual death cases and expected death cases are compared and analyzed. It is found that the predicted mortality rate has decreased after May 2, 2020. It will help the government and doctors prepare for the forthcoming plans. Based on short-period predictions, these methods can be used to forecast the mortality rate for a long period.
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Project description:Since its first discovery in December 2019 in Wuhan, China, COVID-19, caused by the novel coronavirus SARS-CoV-2, has spread rapidly worldwide. While African countries were relatively spared initially, the initial low incidence of COVID-19 cases was not sustained for long due to continuing travel links between China, Europe and Africa. In preparation, Zambia had applied a multisectoral national epidemic disease surveillance and response system resulting in the identification of the first case within 48 h of the individual entering the country by air travel from a trip to France. Contact tracing showed that SARS-CoV-2 infection was contained within the patient's household, with no further spread to attending health care workers or community members. Phylogenomic analysis of the patient's SARS-CoV-2 strain showed that it belonged to lineage B.1.1., sharing the last common ancestor with SARS-CoV-2 strains recovered from South Africa. At the African continental level, our analysis showed that B.1 and B.1.1 lineages appear to be predominant in Africa. Whole genome sequence analysis should be part of all surveillance and case detection activities in order to monitor the origin and evolution of SARS-CoV-2 lineages across Africa.
| S-EPMC7537667 | biostudies-literature
Project description:BackgroundThe emergence of a novel coronavirus (SARS-CoV-2) in Wuhan, China, at the end of 2019 has caused widespread transmission around the world. As new epicentres in Europe and America have arisen, of particular concern is the increased number of imported coronavirus disease 2019 (COVID-19) cases in Africa, where the impact of the pandemic could be more severe. We aim to estimate the number of COVID-19 cases imported from 12 major epicentres in Europe and America to each African country, as well as the probability of reaching 10,000 cases in total by the end of March, April, May, and June following viral introduction.MethodsWe used the reported number of cases imported from the 12 major epicentres in Europe and America to Singapore, as well as flight data, to estimate the number of imported cases in each African country. Under the assumption that Singapore has detected all the imported cases, the estimates for Africa were thus conservative. We then propagated the uncertainty in the imported case count estimates to simulate the onward spread of the virus, until 10,000 cases are reached or the end of June, whichever is earlier. Specifically, 1,000 simulations were run separately under four different combinations of parameter values to test the sensitivity of our results.ResultsWe estimated Morocco, Algeria, South Africa, Egypt, Tunisia, and Nigeria as having the largest number of COVID-19 cases imported from the 12 major epicentres. Based on our 1,000 simulation runs, Morocco and Algeria's estimated probability of reaching 10,000 cases by end of March was close to 100% under all scenarios. In particular, we identified countries with less than 1,000 cases in total reported by end of June whilst the estimated probability of reaching 10,000 cases by then was higher than 50% even under the most optimistic scenario.ConclusionsOur study highlights particular countries that are likely to reach (or have reached) 10,000 cases far earlier than the reported data suggest, calling for the prioritization of resources to mitigate the further spread of the epidemic.
| S-EPMC7424562 | biostudies-literature