Predicting an epidemic trajectory is difficult.
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ABSTRACT:
SUBMITTER: Wilke CO
PROVIDER: S-EPMC7682412 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Publications
Predicting an epidemic trajectory is difficult.
Wilke Claus O CO Bergstrom Carl T CT
Proceedings of the National Academy of Sciences of the United States of America 20201103 46
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Project description:A pipeline involving data acquisition, curation, carefully chosen graphs and mathematical models, allows analysis of COVID-19 outbreaks at 3,546 locations world-wide (all countries plus smaller administrative divisions with data available). Comparison of locations with over 50 deaths shows all outbreaks have a common feature: H(t) defined as loge(X(t)/X(t-1)) decreases linearly on a log scale, where X(t) is the total number of Cases or Deaths on day, t (we use ln for loge). The downward slopes vary by about a factor of three with time constants (1/slope) of between 1 and 3 weeks; this suggests it may be possible to predict when an outbreak will end. Is it possible to go beyond this and perform early prediction of the outcome in terms of the eventual plateau number of total confirmed cases or deaths? We test this hypothesis by showing that the trajectory of cases or deaths in any outbreak can be converted into a straight line. Specifically Y(t) ≡ -ln(ln(N / X(t)), is a straight line for the correct plateau value N, which is determined by a new method, Best-Line Fitting (BLF). BLF involves a straight-line facilitation extrapolation needed for prediction; it is blindingly fast and amenable to optimization. We find that in some locations that entire trajectory can be predicted early, whereas others take longer to follow this simple functional form. Fortunately, BLF distinguishes predictions that are likely to be correct in that they show a stable plateau of total cases or death (N value). We apply BLF to locations that seem close to a stable predicted N value and then forecast the outcome at some locations that are still growing wildly. Our accompanying web-site will be updated frequently and provide all graphs and data described here.
| S-EPMC7325180 | biostudies-literature
Project description:BackgroundAccurate prediction of the difficult airway (DA) could help to prevent catastrophic consequences in emergency resuscitation, intensive care, and general anesthesia. Until now, there is no nomogram prediction model for DA based on ultrasound assessment. In this study, we aimed to develop a predictive model for difficult tracheal intubation (DTI) and difficult laryngoscopy (DL) using nomogram based on ultrasound measurement. We hypothesized that nomogram could utilize multivariate data to predict DTI and DL.MethodsA prospective observational DA study was designed. This study included 2254 patients underwent tracheal intubation. Common and airway ultrasound indicators were used for the prediction, including thyromental distance (TMD), modified Mallampati test (MMT) score, upper lip bite test (ULBT) score temporomandibular joint (TMJ) mobility and tongue thickness (TT). Univariate and the Akaike information criterion (AIC) stepwise logistic regression were used to identify independent predictors of DTI and DL. Nomograms were constructed to predict DL and DTL based on the AIC stepwise analysis results. Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of the nomograms.ResultsAmong the 2254 patients enrolled in this study, 142 (6.30%) patients had DL and 51 (2.26%) patients had DTI. After AIC stepwise analysis, ULBT, MMT, sex, TMJ, age, BMI, TMD, IID, and TT were integrated for DL nomogram; ULBT, TMJ, age, IID, TT were integrated for DTI nomogram. The areas under the ROC curves were 0.933 [95% confidence interval (CI), 0.912-0.954] and 0.974 (95% CI, 0.954-0.995) for DL and DTI, respectively.ConclusionNomograms based on airway ultrasonography could be a reliable tool in predicting DA.Trial registrationChinese Clinical Trial Registry (No. ChiCTR-RCS-14004539 ), registered on 13th April 2014.
| S-EPMC8756724 | biostudies-literature
Project description:When we get sick, we want to be resilient and recover our original health. To measure resilience, we need to quantify a host's position along its disease trajectory. Here we present Looper, a computational method to analyze longitudinally gathered datasets and identify gene pairs that form looping trajectories when plotted in the space described by these phases. These loops enable us to track where patients lie on a typical trajectory back to health. We analyzed two publicly available, longitudinal human microarray datasets that describe self-resolving immune responses. Looper identified looping gene pairs expressed by human donor monocytes stimulated by immune elicitors, and in YF17D-vaccinated individuals. Using loops derived from training data, we found that we could predict the time of perturbation in withheld test samples with accuracies of 94% in the human monocyte data, and 65-83% within the same cohort and in two independent cohorts of YF17D vaccinated individuals. We suggest that Looper will be useful in building maps of resilient immune processes across organisms.
| S-EPMC6175499 | biostudies-literature
Project description:BackgroundBased on the upper airway anatomy and joint function parameters examined by ultrasound, a multiparameter ultrasound model for difficult airway assessment (ultrasound model) was established, and we evaluated its ability to predict difficult airways.MethodsA prospective case-cohort study of difficult airway prediction in adult patients undergoing elective surgery with endotracheal intubation under general anesthesia, and ultrasound phantom examination for difficult airway assessment before anesthesia, including hyomental distance, tongue thickness, mandibular condylar mobility, mouth opening, thyromental distance, and modified Mallampati tests, was performed. Receiver operating characteristic (ROC) curve analysis was used to evaluate the effectiveness of the ultrasound model and conventional airway assessment methods in predicting difficult airways.ResultsWe successfully enrolled 1000 patients, including 51 with difficult laryngoscopy (DL) and 26 with difficult tracheal intubation (DTI). The area under the ROC curve (AUC) for the ultrasound model to predict DL was 0.84 (95% confidence interval [CI]: 0.82-0.87), and the sensitivity and specificity were 0.75 (95% CI: 0.60-0.86) and 0.82 (95% CI: 0.79-0.84), respectively. The AUC for predicting DTI was 0.89 (95% CI: 0.87-0.91), and the sensitivity and specificity were 0.85 (95% CI: 0.65-0.96) and 0.81 (95% CI: 0.78-0.83), respectively. Compared with mouth opening, thyromental distance, and modified Mallampati tests, the ultrasound model predicted a greater AUC for DL (P < 0.05). Compared with mouth opening and modified Mallampati tests, the ultrasound model predicted a greater AUC for DTI (P < 0.05).ConclusionsThe ultrasound model has good predictive performance for difficult airways.Trial registrationThis study is registered on chictr.org.cn (ChiCTR-ROC-17013258); principal investigator: Jianling Xu; registration date: 06/11/2017).
| S-EPMC9533522 | biostudies-literature
Project description:ObjectivesTo investigate the characteristics and prognostic value of fecal lactoferrin trajectories in ulcerative colitis (UC).MethodsThis study used data from the UNIFI trial (ClinicalTrials.gov, NCT02407236) and included patients who received ustekinumab during induction for trajectory modeling (n = 637). Patients who received ustekinumab during maintenance therapy were used for 1-year outcome analyses (n = 403). The levels of fecal lactoferrin, fecal calprotectin, and serum C-reactive protein were measured at weeks 0, 2, 4, and 8. The trajectories of these biomarkers were developed using a latent class growth mixed model.ResultsThe trajectories of fecal lactoferrin, fecal calprotectin, and serum C-reactive protein were distinct, but all were associated with prior exposure to anti-tumor necrosis factor agents and vedolizumab. Furthermore, the fecal lactoferrin trajectory was the most valuable predictor of endoscopic, clinical, and histological remission. Compared to the high/moderate-rapid decrease trajectory group, the moderate-slow decrease, high-slow decrease, and high-stable groups had adjusted odds ratios (95% confidence interval) of 0.38 (0.18, 0.78; P = 0.010), 0.47 (0.23, 0.93; P = 0.032), and 0.33 (0.17, 0.63; P = 0.001), respectively, of 1-year endoscopic remission. Patients with high/moderate-rapid decrease trajectories also had the highest likelihood of achieving clinical and histological remission. Finally, we developed a patient-stratification scheme based on fecal lactoferrin trajectories and concentrations. Patients with good, moderate, and poor prognoses in the scheme had a distinct probability of achieving 1-year endoscopic remission (52.7%, 30.9%, and 12.8%, respectively).ConclusionsThe trajectory of fecal lactoferrin is a valuable prognostic factor for 1-year remission in UC.
| S-EPMC10680133 | biostudies-literature
Project description:IntroductionPredictive biomarkers of Parkinson's Disease progression are needed to expedite neuroprotective treatment development and facilitate prognoses for patients. This work uses measures derived from resting-state functional magnetic resonance imaging, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF), to predict an individual's current and future severity over up to 4 years and to elucidate the most prognostic brain regions.MethodsReHo and fALFF are measured for 82 Parkinson's Disease subjects and used to train machine learning predictors of baseline clinical and future severity at 1 year, 2 years, and 4 years follow-up as measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Predictive performance is measured with nested cross-validation, validated on an external dataset, and again validated through leave-one-site-out cross-validation. Important predictive features are identified.ResultsThe models explain up to 30.4% of the variance in current MDS-UPDRS scores, 55.8% of the variance in year 1 scores, and 47.1% of the variance in year 2 scores (p < 0.0001). For distinguishing high and low-severity individuals at each timepoint (MDS-UPDRS score above or below the median, respectively), the models achieve positive predictive values up to 79% and negative predictive values up to 80%. Higher ReHo and fALFF in several regions, including components of the default motor network, predicted lower severity across current and future timepoints.ConclusionThese results identify an accurate prognostic neuroimaging biomarker which may be used to better inform enrollment in trials of neuroprotective treatments and enable physicians to counsel their patients.
| S-EPMC8127393 | biostudies-literature
Project description:Understanding how epidemics spread in a system is a crucial step to prevent and control outbreaks, with broad implications on the system's functioning, health, and associated costs. This can be achieved by identifying the elements at higher risk of infection and implementing targeted surveillance and control measures. One important ingredient to consider is the pattern of disease-transmission contacts among the elements, however lack of data or delays in providing updated records may hinder its use, especially for time-varying patterns. Here we explore to what extent it is possible to use past temporal data of a system's pattern of contacts to predict the risk of infection of its elements during an emerging outbreak, in absence of updated data. We focus on two real-world temporal systems; a livestock displacements trade network among animal holdings, and a network of sexual encounters in high-end prostitution. We define the node's loyalty as a local measure of its tendency to maintain contacts with the same elements over time, and uncover important non-trivial correlations with the node's epidemic risk. We show that a risk assessment analysis incorporating this knowledge and based on past structural and temporal pattern properties provides accurate predictions for both systems. Its generalizability is tested by introducing a theoretical model for generating synthetic temporal networks. High accuracy of our predictions is recovered across different settings, while the amount of possible predictions is system-specific. The proposed method can provide crucial information for the setup of targeted intervention strategies.
| S-EPMC4357450 | biostudies-literature
Project description:The trajectory of COVID-19 epidemic waves in the general population of Belgium was analysed by defining quantitative criteria for epidemic waves from March 2020 to early 2023. Peaks and starting/ending times characterised nine waves numerated I to IX based on the daily reported incidence number (symbol INCID) and three "endemic" interval periods between the first four waves. The SIR compartmental model was applied to the first epidemic wave by fitting the daily prevalence pool (symbol I) calculated as the sum of the daily incidence rate and estimated number of subjects still infectious from the previous days. The basic reproductive number R0 was calculated based on the exponential growth rate during the early phase and on medical literature knowledge of the time of generation of SARS-CoV-2 infection. The first COVID-19 wave was well fitted by an open SIR model. According to this approach, dampened recurrent epidemic waves evolving through an endemic state would have been expected. This was not the case with the subsequent epidemic waves being characterised by new variants of concern (VOC). Evidence-based observations: 1) each epidemic wave affected less than a fifth of the general population; 2) the Vth epidemic wave (VOC Omicron) presented the greatest amplitude. The lack of recurrence of the same VOC during successive epidemic waves strongly suggests that a VOC has a limited persistence, disappearing from the population well before the expected proportion of the theoretical susceptible cohort being maximally infected. Fitting the theoretical SIR model, a limited persistence of VOCs in a population could explain that new VOCs replace old ones, even if the new VOC has a lower transmission rate than the preceding one. In conclusion, acquisition of potential defective mutations in VOC during an epidemic wave is a potential factor explaining the absence of resurgence of a same VOC during successive waves. Such an hypothesis is open to discussion and to rebuttal. A modified SIR model with epidemic waves of variable amplitude related not only to R0 and public health measures but also to acquisition of defective fitting in virus within a population should be tested.
| S-EPMC10903008 | biostudies-literature
Project description:BackgroundMultiple scores have been created in order to predict difficult cholecystectomy, nonetheless there is not a consensuated standard on which to use. The importance of a predictive score to be able to establish a difficult cholecystectomy would be a relevant instrument in order to better inform the patient, properly call for help when needed, choose the correct staff, and schedule and plan the surgical procedure accordingly.MethodsA diagnostic trial study was performed. All different predictive scores for difficult cholecystectomy were calculated for each patient. The correlation between the preoperative score and cholecystectomies considered as "difficult" were measured estimating the preoperative score's predictive value using a receiver operating characteristics curve in order to predict findings for difficult cholecystectomy.ResultsA total of 635 patients between 2014 and 2021 were selected. Selected patients had a mean age of 55.0 (interquartile range: 28.00) and were mostly female (64.25%). Surgical outcomes of patients with difficult cholecystectomy had statistically significant higher rates of subtotal cholecystectomies, drain usage, complications and reinterventions, prolonged surgical times, and longer hospital stay. When analyzing the predictive value on each of the different scores applied, score 4 had the highest performance for predicting difficult cholecystectomy with an area under the curve=0.783 (CI 95% 0.745-0.822).ConclusionsDifficult cholecystectomies are associated with worse surgical outcomes. The standardization and use of predictive scores for difficult cholecystectomy must be implemented in order to improve surgical outcomes as a result of more meticulous planning when scheduling the procedure.
| S-EPMC10389651 | biostudies-literature
Project description:To date, the feeding and oral-motor abilities of patients with CHARGE syndrome (CS) have not been longitudinally assessed. This study aims to investigate the level of these abilities at different ages and evaluate how they evolve during growth. We retrospectively analysed oral-motor features of 16 patients with molecularly confirmed CS (age range 4-21 years old; mean 11 years; SD 6 years; median 10 years). Nearly 100% of CS new-borns had weak sucking at birth, and half of them demonstrated poor coordination between breathing and swallowing. Over time, the percentages of children with tube feeding dependence (60% at birth) faced a slow but steady decrease (from 33% at 6 months, 25% at 12 months, to 13% at school age) in tandem with the decreasing risk of aspiration. The ability of eating foods requiring chewing was achieved at school age, after the acquisition of an adequate oral sensory processing. A mature chewing pattern with a variety of food textures was not achieved by more than half of patients, including those requiring artificial enteral nutrition. Most patients started prolonged oral-motor treatments with speech language therapists in early childhood.ConclusionsAlthough feeding and swallowing disorders are constant features in CS patients, a slow and gradual development of feeding abilities occurs in most cases. Rehabilitation plays a key role in overcoming structural and functional difficulties and attaining appropriate eating skills.What is known• Feeding problems and swallowing dysfunction have been noted in CHARGE syndrome. • The involvement of multiple factors, including structural problems in the mouth, throat, or esophagus, and neurological impairment, make feeding a complicated task in CHARGE individuals.What is new• Dysphagia gradually improves in most CHARGE children over time, though with a wide interindividual variability. • The percentages of children with tube feeding dependence decrease over time from 60% at birth to 33% at 6 months and 13% at school age.
| S-EPMC10167171 | biostudies-literature