Using the Newcomb-Benford law to study the association between a country's COVID-19 reporting accuracy and its development.
Ontology highlight
ABSTRACT:
SUBMITTER: Balashov VS
PROVIDER: S-EPMC8617306 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The contrast of fraud in international trade is a crucial task of modern economic regulations. We develop statistical tools for the detection of frauds in customs declarations that rely on the Newcomb-Benford law for significant digits. Our first contribution is to show the features, in the context of a European Union market, of the traders for which the law should hold in the absence of fraudulent data manipulation. Our results shed light on a relevant and debated question, since no general known theory can exactly predict validity of the law for genuine empirical data. We also provide approximations to the distribution of test statistics when the Newcomb-Benford law does not hold. These approximations open the door to the development of modified goodness-of-fit procedures with wide applicability and good inferential properties.
| S-EPMC6320519 | biostudies-literature
Project description:Processing massive transcriptomic datasets in a meaningful manner requires novel, possibly interdisciplinary, approaches. One principle that can address this challenge is the Benford law (BL), which posits that the occurrence probability of a leading digit in a large numerical dataset decreases as its value increases. Here, we analyzed large single-cell and bulk RNA-seq datasets to test whether cell types and tissue origins can be differentiated based on the adherence of specific genes to the BL. Then, we used the Benford adherence scores of these genes as inputs to machine-learning algorithms and tested their separation accuracy. We found that genes selected based on their first-digit distributions can distinguish between cell types and tissue origins. Moreover, despite the simplicity of this novel feature-selection method, its separation accuracy is higher than that of the mean-expression level approach and is similar to that of the differential expression approach. Thus, the BL can be used to obtain biological insights from massive amounts of numerical genomics data-a capability that could be utilized in various biomedical applications, e.g., to resolve samples of unknown primary origin, identify possible sample contaminations, and provide insights into the molecular basis of cancer subtypes.
| S-EPMC6770594 | biostudies-literature
Project description:Several cases of herpes zoster (HZ) following mRNA COVID-19 vaccination (BNT162b2 and mRNA-1273) have been reported, and the first epidemiological evidence suggests an increased risk. We used the worldwide pharmacovigilance database VigiBase to describe HZ cases following mRNA COVID-19 vaccination. We performed disproportionality analyses (case/non-case statistical approach) to assess the relative risk of HZ reporting in mRNA COVID-19 vaccine recipients compared to influenza vaccine recipients and according to patient age. To 30 June 2021, of 716 928 reports with mRNA COVID-19 vaccines, we found 7728 HZ cases. When compared to influenza vaccines, mRNA COVID-19 vaccines were associated with a significantly higher reporting of HZ (reporting odds ratio 1.9, 95% CI 1.8-2.1). Furthermore, we found a reduced risk of reporting HZ among under 40-year-old persons compared to older persons (reporting odds ratio 0.39, 95% CI 0.36-0.41). Mild and infrequent HZ reactions may occur shortly after mRNA COVID-19 vaccination, at higher frequency than reported with influenza vaccination, especially in patients over 40 years old. Further analyses are needed to confirm this risk.
| S-EPMC9111438 | biostudies-literature
Project description:ImportanceAlthough a growing number of studies have reported negative associations of the COVID-19 pandemic with academic performance among school-aged children, less is known about the pandemic's association with early childhood development.ObjectiveTo examine the association between the COVID-19 pandemic and early childhood development.Design, setting, and participantsIn this cohort study conducted in all accredited nursery centers in a Japanese municipality, baseline surveys of children aged 1 and 3 years (1000 and 922, respectively) were conducted between 2017 and 2019, and participants were followed up for 2 years.ExposureChildren's development was compared at age 3 or 5 years between cohorts that were exposed to the pandemic during the follow-up and a cohort that was not.Main outcome and measureChildren's developmental age was measured by nursery teachers using the Kinder Infant Development Scale (KIDS). Data were analyzed between December 8, 2022, and May 6, 2023.ResultsA total of 447 children (201 girls [45.0%] and 246 boys [55.0%]) aged 1 year at baseline were followed up to age 3 years, and 440 children (200 girls [45.5%] and 240 boys [54.5%]) aged 3 years at baseline were followed up to age 5 years. During the follow-up, the cohorts that were exposed to the pandemic were 4.39 months behind in development at age 5 compared with the cohort that was not (coefficient, -4.39; 95% credible interval, -7.66 to -1.27). Such a negative association was not observed in development at age 3 years (coefficient, 1.32; 95% credible interval, -0.44 to 3.01). Variations in development were greater during the pandemic than before the pandemic regardless of age. Additionally, the quality of care at nursery centers was positively associated with development at age 3 years during the pandemic (coefficient, 2.01; 95% credible interval, 0.58-3.44), while parental depression appeared to amplify the association between the pandemic and delayed development at age 5 (coefficient of interaction, -2.62; 95% credible interval, -4.80 to -0.49; P = .009).Conclusions and relevanceThe findings of this study showed an association between exposure to the pandemic and delayed childhood development at age 5 years. Variations in development widened during the pandemic regardless of age. It is important to identify children with developmental delays associated with the pandemic and provide them with support for learning, socialization, physical and mental health, and family support.
| S-EPMC10334298 | biostudies-literature
Project description:BackgroundBreast cancer is the most frequent cancer in women all over the world, and it is one of the leading causes of cancer-related deaths in women. A pathologist's partiality for the last digit of a patient's name can lead to errors in the measurement of malignancies. This means that, rather than recording the exact measurement of a tumor, a pathologist might round it off to his preferred terminal digit.MethodsIt is a retrospective cross-sectional study in which data on primary tumor resection for 1000 breast cancer patients was obtained from KRL Hospital's patient directory from November 2016 to December 2020. The tumors were measured in cm to one decimal point along their longest dimension. Ki-67 markers were used to categorize the tumors into nine categories. Terminal digit preference was evaluated using Benford's law.ResultsThe recording of the Ki-67 index revealed evidence of pentameric preference. The numbers three, five, and six appeared more frequently in the histogram of the Ki-67 index distribution measured in percentage. The frequency of nine dropped dramatically. However, the influence of tumor size terminal digits on Ki-67 staining scores (low proliferative vs high proliferative) assessed using the Mann-Whitney U Test demonstrated that tumor size terminal digits had no significant effect on Ki-67 staining scores (p = 0.114).ConclusionThe Ki-67 index shows evidence of pentameric preference for digits three, five, and six. The frequency of nine has dropped dramatically. The influence of tumor size on terminal digits on staining scores (low proliferative vs. high proliferative) was assessed using the Mann-Whitney U Test.
| S-EPMC9289319 | biostudies-literature
Project description:This paper presents two comprehensive studies examining how Schwartz's human values dimensions at the country level predict COVID-19 pandemic severity. Study 1 aggregated survey data across 89 countries from the European Social Survey and World Values Survey to assess societal-level conservation versus openness to change (CON-OTC) and self-enhancement versus self-transcendence (SE-ST) value-continuums. Study 2 developed an innovative archival measurement approach using 10 indicators to estimate these value dimensions for over 180 countries. Both studies employed multilevel modeling to test the relationships between country-level values and COVID-19 severity, measured through epidemiological indicators of transmission speed, case fatality rate, infection prevalence and mortality burden. Results revealed that the CON-OTC and SE-ST value-continuums showed consistent, significant negative associations with transmission speed and infection prevalence before adjusting for modernization, latitude, historical pathogen prevalence and government stringency across both studies. However, after accounting for these socioecological and policy covariates, the CON-OTC value-continuum positively predicted case fatality rate in both studies, implying conservation values could increase COVID-19 lethality. In contrast, across both studies, the SE-ST value-continuum negatively predicted case fatality rate after adjusting for the covariates, suggesting countries prioritizing self-enhancement values exhibited relatively lower pandemic severity and lethality when accounting for developmental, ecological, and policy factors. Accordingly, the studies advance theoretical understanding of how country's value priorities shape COVID-19 impact. Methodologically, these studies contribute through multilevel techniques that account for spatial dependencies, as well as an innovative ecological measurement. Overall, this research demonstrates the value of applying Schwartz's framework at a societal level to predict global health crises and pandemics.
| S-EPMC10474233 | biostudies-literature
Project description:Although most SARS-CoV-2-infected individuals experience mild COVID-19, some patients suffer from severe COVID-19, which is accompanied by acute respiratory distress syndrome and systemic inflammation. To identify factors driving severe progression of COVID-19, we performed single-cell RNA-seq using peripheral blood mononuclear cells (PBMCs) obtained from healthy donors, patients with mild or severe COVID-19, and patients with severe influenza. Patients with COVID-19 exhibited hyper-inflammatory signatures across all types of cells among PBMCs, particularly upregulation of the TNF/IL-1beta-driven inflammatory response as compared to severe influenza. In classical monocytes from patients with severe COVID-19, type I IFN response co-existed with the TNF/IL-1beta-driven inflammation, and this was not seen in patients with milder COVID-19 infection. Based on this, we propose that the type I IFN response exacerbates inflammation in patients with severe COVID-19 infection.
2020-07-06 | GSE149689 | GEO
Project description:Although some studies reported the comprehensive mRNA expression analysis of coronavirus disease 2019 (COVID-19) using blood samples to understand its pathogenesis, the characteristics of RNA expression in COVID-19 and sepsis have not been compared. We compared the transcriptome expression of whole blood samples from patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and patients with sepsis caused by other bacteria who entered the intensive care unit to clarify the COVID-19-specific RNA expression and understand its pathogenesis. Transcriptomes related to mitochondria were upregulated in COVID-19, whereas those related to neutrophils were upregulated in sepsis. However, the transcriptomes related to neutrophils were upregulated in both COVID-19 and sepsis compared to in healthy controls, whereas the mitochondrial transcriptomes were upregulated in COVID-19 and downregulated in sepsis compared to in healthy controls. Moreover, sepsis showed sub-optimal intrinsic apoptotic features compared with COVID-19. The transcriptome expression of COVID-19 has been examined in vitro but has not been widely validated using human specimens. This study improves the understanding of the pathogenesis of COVID-19 and can contribute to the development of treatments.
2022-11-29 | GSE199816 | GEO
Project description:The novel coronavirus (COVID-19) was first identified in China in December 2019. Within a short period of time, the infectious disease has spread far and wide. This study focuses on the distribution of COVID-19 confirmed cases in China-the original epicentre of the outbreak. We show that the upper tail of COVID-19 cases in Chinese cities is well described by a power law distribution, with exponent around one in the early phases of the outbreak (when the number of cases was growing rapidly) and less than one thereafter. This finding is significant because it implies that (i) COVID-19 cases in China is heavy tailed and disperse; (ii) a few cities account for a disproportionate share of COVID-19 cases; and (iii) the distribution generally has no finite mean or variance. We find that a proportionate random growth model predicated by Gibrat's law offers a plausible explanation for the emergence of a power law in the distribution of COVID-19 cases in Chinese cities in the early phases of the outbreak.
| S-EPMC9115516 | biostudies-literature
Project description:SARS-CoV-2 infection poses a worldwide public health problem affecting millions of people worldwide. There is a critical need for improvements in the noninvasive prognosis of COVID-19. We hypothesized that matrix-assisted laser desorption ionization mass spectrometry (MALDI-TOF MS) analysis combined with molecular-weight directed bottom-up proteomic analysis of plasma proteins may predict high and low risk cases of COVID-19. Patients and Methods: We used MALDI MS to analyze plasma small proteins and peptides isolated using C18 micro-columns from a cohort containing a total of 117 cases of high and low risk cases split into training (n = 88) and validation sets (n= 29). The plasma protein/peptide fingerprint obtained was used to train the algorithm before validation using a blinded test cohort. Several sample preparation, MS and data analysis parameters were optimized to achieve an overall accuracy of 85%, a sensitivity of 90%, and a specificity of 81% in the training set. In the blinded test set, this signature reached an overall accuracy of 93.1%, a sensitivity of 87.5%, and a specificity of 100%. From this signature, we identified two distinct regions corresponding to the single and doubly protonated proteins in the MALDI-TOF profile belonging to the same proteoforms. A combination of 1D SDS-PAGE and quantitative bottom-up proteomic analysis allowed the identification of intact and truncated forms of serum amyloid A-1 and A-2 proteins. We found a plasma proteomic profile that discriminates against patients with high and low risk COVID-19. Proteomic analysis of C18-fractionated plasma may have a role in the noninvasive prognosis of COVID-19. Further validation will be important to consolidate its clinical utility.
2021-06-22 | PXD021581 | Pride