The inflection point about COVID-19 may have passed.
Ontology highlight
ABSTRACT:
SUBMITTER: Gu C
PROVIDER: S-EPMC7130087 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
Publications
The inflection point about COVID-19 may have passed.
Gu Chaolin C Zhu Jie J Sun Yifei Y Zhou Kai K Gu Jiang J
Science bulletin 20200303 11
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Project description:BackgroundExponential-like infection growth leading to peaks (denoted by inflection points [IP] or turning points) is usually the hallmark of infectious disease outbreaks, including coronaviruses. To determine the IPs of the novel coronavirus (COVID-19), we applied the item response theory model to detect phase transitions for each country/region and characterize the IP feature on the temporal bar graph (TBG).MethodsThe IP (using the item difficulty parameter to locate) was verified by the differential equation in calculus and interpreted by the TBG with 2 virtual and real empirical data (i.e., from Collatz conjecture and COVID-19 pandemic in 2020). Comparisons of IPs, R2, and burst strength [BS = ln() denoted by the infection number at IP(Nip) and the item slope parameter(a) in item response theory were made for countries/regions and continents on the choropleth map and the forest plot.ResultsWe found that the evolution of COVID-19 on the TBG makes the data clear and easy to understand, the shorter IP (=53.9) was in China and the longest (=247.3) was in Europe, and the highest R2 (as the variance explained by the model) was in the US, with a mean R2 of 0.98. We successfully estimated the IPs for countries/regions on COVID-19 in 2020 and presented them on the TBG.ConclusionTemporal visualization is recommended for researchers in future relevant studies (e.g., the evolution of keywords in a specific discipline) and is not merely limited to the IP search in COVID-19 pandemics as we did in this study.
| S-EPMC8812627 | biostudies-literature
Project description:Oil prices have been in the downtrend since the recession of 2008. Since then, companies have struggled to survive as factors of production are being driven by external influences. International efforts to create a sustainable environment further intricates the supply and demand curve as countries develop policies and strategies to phase out fossil fuels. There has been a myriad of researches conducted by both public and private organisations that seem to agree and disagree on certain factors of a peak oil forecast. There is lack of research however, on finding common ground to determine the central tendencies if multiple predictions are accounted, which creates bias in decision making. The findings of this research provide a practical outlook for businesses and governments to better position their financial and policy decisions with regard to fossil fuels which could affect the lives of many. This research uses a novel prediction combination approach to determine an earliest-case peak oil occurrence through qualitative and quantitative methods for bias minimisation. The predictions are sourced from a balance of reputable private and public international agencies. The result interestingly finds commonality of reaching an earliest-case of peak oil in the year 2025 with feasible factors considered. The research discusses the inflection point forecast and financial risk mitigation recommendations for private entities and governments gathered from expert reports and articles in the field of oil supply and demand. Graphical abstract Unlabelled Image Highlights • Public and private economic experts peak oil predictions are qualitatively examined.• Predictions of peak oil occurrence are combined through a quantitative summation algorithm.• Commonality in predictions provides an earliest-case peak oil in 2025 with considerations.• Private and public experts agree on strategies to mitigate the effects of peak oil in businesses and economies.
| S-EPMC7331520 | biostudies-literature
Project description:Budding yeasts are highly suitable for aging studies, because the number of bud scars (stage) proportionally correlates with age. Its maximum stages are known to reach at 20-30 stages on an isolated agar medium. However, their stage dynamics in a liquid culture is virtually unknown. We investigate the population dynamics by counting scars in each cell. Here one cell division produces one new cell and one bud scar. This simple rule leads to a conservation law: "The total number of bud scars is equal to the total number of cells." We find a large discrepancy: extremely fewer cells with over 5 scars than expected. Almost all cells with 6 or more scars disappear within a short period of time in the late log phase (corresponds to the inflection point). This discrepancy is confirmed directly by the microscopic observations of broken cells. This finding implies apoptosis in older cells (6 scars or more).
| S-EPMC3083425 | biostudies-literature
Project description:BackgroundDuring the COVID-19 pandemic, one of the frequently asked questions is which countries (or continents) are severely hit. Aside from using the number of confirmed cases and the fatality to measure the impact caused by COVID-19, few adopted the inflection point (IP) to represent the control capability of COVID-19. How to determine the IP days related to the capability is still unclear. This study aims to (i) build a predictive model based on item response theory (IRT) to determine the IP for countries, and (ii) compare which countries (or continents) are hit most.MethodsWe downloaded COVID-19 outbreak data of the number of confirmed cases in all countries as of October 19, 2020. The IRT-based predictive model was built to determine the pandemic IP for each country. A model building scheme was demonstrated to fit the number of cumulative infected cases. Model parameters were estimated using the Solver add-in tool in Microsoft Excel. The absolute advantage coefficient (AAC) was computed to track the IP at the minimum of incremental points on a given ogive curve. The time-to-event analysis (a.k.a. survival analysis) was performed to compare the difference in IPs among continents using the area under the curve (AUC) and the respective 95% confidence intervals (CIs). An online comparative dashboard was created on Google Maps to present the epidemic prediction for each country.ResultsThe top 3 countries that were hit severely by COVID-19 were France, Malaysia, and Nepal, with IP days at 263, 262, and 262, respectively. The top 3 continents that were hit most based on IP days were Europe, South America, and North America, with their AUCs and 95% CIs at 0.73 (0.61-0.86), 0.58 (0.31-0.84), and 0.54 (0.44-0.64), respectively. An online time-event result was demonstrated and shown on Google Maps, comparing the IP probabilities across continents.ConclusionAn IRT modeling scheme fitting the epidemic data was used to predict the length of IP days. Europe, particularly France, was hit seriously by COVID-19 based on the IP days. The IRT model incorporated with AAC is recommended to determine the pandemic IP.
| S-EPMC7969250 | biostudies-literature
Project description:Predicting the outbreak risks and/or the inflection (turning or tipping) points of COVID-19 can be rather challenging. Here, it is addressed by modeling and simulation approaches guided by classic ecological theories and by treating the COVID-19 pandemic as a metapopulation dynamics problem. Three classic ecological theories are harnessed, including TPL (Taylor's power-law) and Ma's population aggregation critical density (PACD) for spatiotemporal aggregation/stability scaling, approximating virus metapopulation dynamics with Hubbell's neutral theory, and Ma's diversity-time relationship adapted for the infection-time relationship. Fisher-Information for detecting critical transitions and tipping points are also attempted. It is discovered that: (i) TPL aggregation/stability scaling parameter (b > 2), being significantly higher than the b-values of most macrobial and microbial species including SARS, may interpret the chaotic pandemic of COVID-19. (ii) The infection aggregation critical threshold (M 0) adapted from PACD varies with time (outbreak-stage), space (region) and public-health interventions. Exceeding M 0, local contagions may become aggregated and connected regionally, leading to epidemic/pandemic. (iii) The ratio of fundamental dispersal to contagion numbers can gauge the relative importance between local contagions vs. regional migrations in spreading infections. (iv) The inflection (turning) points, pair of maximal infection number and corresponding time, are successfully predicted in more than 80% of Chinese provinces and 68 countries worldwide, with a precision >80% generally.
| S-EPMC7536942 | biostudies-literature
Project description: Not available
| S-BSST563 | biostudies-other
Project description:Animal growth curves play an important role for animal breeders to optimize feeding and management strategies (De Lange et al., 2001 [1]; Brossard et al., 2009 [2]; Strathe et al., 2010 [3]). However, the genetic mechanism of the phenotypic difference between the inflection point and noninflection points of the growth curve remains unclear. Here, we report the differentially expressed gene pattern in pig longissimus dorsi among three typical time points of the growth curve, inflection point (IP), before inflection point (BIP) and after inflection point (AIP). The whole genome RNA-seq data was deposited at GenBank under the accession number PRJNA2284587. The RNA-seq libraries generated 117 million reads of 5.89 gigabases in length. Totals of 21,331, 20,996 and 20,139 expressed transcripts were identified in IP, UIP and AIP, respectively. Furthermore, we identified 757 differentially expressed genes (DEGs) between IP and UIP, and 271 DEGs between AIP and IP. Function enrichment analysis of DEGs found that the highly expressed genes in IP were mainly enriched in energy metabolism, global transcriptional activity and bone development intensity. This study contributes to reveal the genetic mechanism of growth curve inflection point.
| S-EPMC4664711 | biostudies-literature
Project description: Not available
| S-BSST416 | biostudies-other