scholarly journals A data-driven epidemic model with social structure for understanding the COVID-19 infection on a heavily affected Italian province

Author(s):  
Mattia Zanella ◽  
Chiara Bardelli ◽  
Giacomo Dimarco ◽  
Silvia Deandrea ◽  
Pietro Perotti ◽  
...  

In this work, using a detailed dataset furnished by National Health Authorities concerning the Province of Pavia (Lombardy, Italy), we propose to determine the essential features of the ongoing COVID-19 pandemic in terms of contact dynamics. Our contribution is devoted to provide a possible planning of the needs of medical infrastructures in the Pavia Province and to suggest different scenarios about the vaccination campaign which possibly help in reducing the fatalities and/or reducing the number of infected in the population. The proposed research combines a new mathematical description of the spread of an infectious diseases which takes into account both age and average daily social contacts with a detailed analysis of the dataset of all traced infected individuals in the Province of Pavia. These information are used to develop a data-driven model in which calibration and feeding of the model are extensively used. The epidemiological evolution is obtained by relying on an approach based on statistical mechanics. This leads to study the evolution over time of a system of probability distributions characterizing the age and social contacts of the population. One of the main outcomes shows that, as expected, the spread of the disease is closely related to the mean number of contacts of individuals. The model permits to forecast thanks to an uncertainty quantification approach and in the short time horizon, the average number and the confidence bands of expected hospitalized classified by age and to test different options for an effective vaccination campaign with age-decreasing priority.

1997 ◽  
Vol 161 ◽  
pp. 197-201 ◽  
Author(s):  
Duncan Steel

AbstractWhilst lithopanspermia depends upon massive impacts occurring at a speed above some limit, the intact delivery of organic chemicals or other volatiles to a planet requires the impact speed to be below some other limit such that a significant fraction of that material escapes destruction. Thus the two opposite ends of the impact speed distributions are the regions of interest in the bioastronomical context, whereas much modelling work on impacts delivers, or makes use of, only the mean speed. Here the probability distributions of impact speeds upon Mars are calculated for (i) the orbital distribution of known asteroids; and (ii) the expected distribution of near-parabolic cometary orbits. It is found that cometary impacts are far more likely to eject rocks from Mars (over 99 percent of the cometary impacts are at speeds above 20 km/sec, but at most 5 percent of the asteroidal impacts); paradoxically, the objects impacting at speeds low enough to make organic/volatile survival possible (the asteroids) are those which are depleted in such species.


2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Marcos Amaku ◽  
Dimas Tadeu Covas ◽  
Francisco Antonio Bezerra Coutinho ◽  
Raymundo Soares Azevedo ◽  
Eduardo Massad

Abstract Background At the moment we have more than 177 million cases and 3.8 million deaths (as of June 2021) around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far. Methods We propose a new mathematical model to estimate the impact of vaccination delay against the 2019 coronavirus disease (COVID-19) on the number of cases and deaths due to the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations. Results The model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths will occur by the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, for each month of delay the number of deaths increases monotonically in a logarithmic fashion, for both the State of Sao Paulo and Brazil as a whole. Conclusions Our model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.


Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 457
Author(s):  
Isabel María Introzzi ◽  
María Marta Richard’s ◽  
Yesica Aydmune ◽  
Eliana Vanesa Zamora ◽  
Florencia Stelzer ◽  
...  

Recent studies suggest that the developmental curves in adolescence, related to the development of executive functions, could be fitted to a non-linear trajectory of development with progressions and retrogressions. Therefore, the present study proposes to analyze the pattern of development in Perceptual Inhibition (PI), considering all stages of adolescence (early, middle, and late) in intervals of one year. To this aim, we worked with a sample of 275 participants between 10 and 25 years, who performed a joint visual and search task (to measure PI). We have fitted ex-Gaussian functions to the probability distributions of the mean response time across the sample and performed a covariance analysis (ANCOVA). The results showed that the 10- to 13-year-old groups performed similarly in the task and differ from the 14- to 19-year-old participants. We found significant differences between the older group and all the rest of the groups. We discuss the important changes that can be observed in relation to the nonlinear trajectory of development that would show the PI during adolescence.


Author(s):  
Yong Sul Won ◽  
Jong-Hoon Kim ◽  
Chi Young Ahn ◽  
Hyojung Lee

While the coronavirus disease 2019 (COVID-19) outbreak has been ongoing in Korea since January 2020, there were limited transmissions during the early stages of the outbreak. In the present study, we aimed to provide a statistical characterization of COVID-19 transmissions that led to this small outbreak. We collated the individual data of the first 28 confirmed cases reported from 20 January to 10 February 2020. We estimated key epidemiological parameters such as reporting delay (i.e., time from symptom onset to confirmation), incubation period, and serial interval by fitting probability distributions to the data based on the maximum likelihood estimation. We also estimated the basic reproduction number (R0) using the renewal equation, which allows for the transmissibility to differ between imported and locally transmitted cases. There were 16 imported and 12 locally transmitted cases, and secondary transmissions per case were higher for the imported cases than the locally transmitted cases (nine vs. three cases). The mean reporting delays were estimated to be 6.76 days (95% CI: 4.53, 9.28) and 2.57 days (95% CI: 1.57, 4.23) for imported and locally transmitted cases, respectively. The mean incubation period was estimated to be 5.53 days (95% CI: 3.98, 8.09) and was shorter than the mean serial interval of 6.45 days (95% CI: 4.32, 9.65). The R0 was estimated to be 0.40 (95% CI: 0.16, 0.99), accounting for the local and imported cases. The fewer secondary cases and shorter reporting delays for the locally transmitted cases suggest that contact tracing of imported cases was effective at reducing further transmissions, which helped to keep R0 below one and the overall transmissions small.


2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
J. Wancata ◽  
M. Freidl ◽  
F. Friedrich ◽  
T. Matschnig ◽  
A. Unger ◽  
...  

Aims:The purpose of this study was to investigate disability among patients suffering from schizophrenia and to identify predictors of disability.Methods:101 patients from different types of psychiatric services in Vienna and diagnosed with schizophrenia according to ICD-10 were included. They were investigates by means of 36-Item self-administered version of the WHO Disability Assessment Schedule II (WHO-DAS-II) and the PANSS-scale. Patients’ mothers and fathers were asked to fill in the Family Problem Questionnaire.Results:The mean total score of the WHO-DAS-II was 74.1 (SD 21.9). When using weighted sub-scores the highest disability scores were found for social contacts, participation in society and household (means 2.58, 2.57 and 2.51 respectively). Using logistic regression, overall disability was positively associated with patient's age, overall severity of symptoms (PANSS) and number of previous hospital admissions. Overall disability was not associated with duration of illness and or patient's gender. The subjective burden experienced by patients’ fathers and mothers were increased by reduced social contacts and impaired participation in society, while we could not find an association with other domains of patient's disability (understanding, mobility, self-care, household).Conclusions:This study shows that schizophrenia results in disability in several domains. Family caregivers’ burden was predominantly increased by social consequences of schizophrenia.


Author(s):  
Daniel Roten ◽  
Kim B. Olsen

ABSTRACT We use deep learning to predict surface-to-borehole Fourier amplification functions (AFs) from discretized shear-wave velocity profiles. Specifically, we train a fully connected neural network and a convolutional neural network using mean AFs observed at ∼600 KiK-net vertical array sites. Compared with predictions based on theoretical SH 1D amplifications, the neural network (NN) results in up to 50% reduction of the mean squared log error between predictions and observations at sites not used for training. In the future, NNs may lead to a purely data-driven prediction of site response that is independent of proxies or simplifying assumptions.


2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Feng Chu ◽  
Lu Wang ◽  
Xin Liu ◽  
Chengbin Chu ◽  
Yang Sui

Ambulance location problem is a key issue in Emergency Medical Service (EMS) system, which is to determine where to locate ambulances such that the emergency calls can be responded efficiently. Most related researches focus on deterministic problems or assume that the probability distribution of demand can be estimated. In practice, however, it is difficult to obtain perfect information on probability distribution. This paper investigates the ambulance location problem with partial demand information; i.e., only the mean and covariance matrix of the demands are known. The problem consists of determining base locations and the employment of ambulances, to minimize the total cost. A new distribution-free chance constrained model is proposed. Then two approximated mixed integer programming (MIP) formulations are developed to solve it. Finally, numerical experiments on benchmarks (Nickel et al., 2016) and 120 randomly generated instances are conducted, and computational results show that our proposed two formulations can ensure a high service level in a short time. Specifically, the second formulation takes less cost while guaranteeing an appropriate service level.


2021 ◽  
Author(s):  
Ashley Gillman ◽  
Stephen Rose ◽  
Jye Smith ◽  
Jason A Dowling ◽  
Nicholas Dowson

Abstract Background / AimsPatient motion during positron emission tomography (PET) imaging can corrupt the image by causing blurring and quantitation error due to misalignment with the attenuation correction image. Data-driven techniques for tracking motion in PET imaging allow for retrospective motion correction, where motion may not have been prospectively anticipated.MethodsA two minute PET acquisition of a Hoffman phantom was acquired on a Bi- ograph mCT Flow, during which the phantom was rocked, simulating periodic motion with varying frequency. Motion was tracked using the sensitivity method, the axial centre-of-mass (COM) method, a novel 3D-COM method, and the principal component analysis (PCA) method. A separate two minute acquisition was acquired with no motion as a gold standard. The tracking signal was discretised into 10 gates using k-means clustering. Motion was modelled and corrected using the reconstruct-transform-add (RTA) technique, leveraging Multimodal Image Registration using Block-matching and Robust Regression (Mirorr) for rigid registration of non- attenuation-corrected 4D PET and Software for Tomographic Image Reconstruction (STIR) for PET reconstructions. Evaluation was performed by segmenting white matter (WM) and grey matter (GM) in the attenuation correction computed tomography (CT). The mean uptake in the region of GM was compared with that in the WM region. Additionally, the difference between the intensity distributions of WM and GM regions was measured with the t-statistic from a Welch's t-test.ResultsDifference in the mean distribution of WM to GM ranked the techniques in order of efficacy: no correction, sensitivity, axial-COM, 3D-COM, PCA, no motion. PCA correction had a great WM/GM separation measured by the t-value than the no motion scan. This was attributed to interpolation blurring during motion correction reducing class variance.ConclusionOf the techniques examined, PCA was found to be most effective for tracking rigid motion. The sensitivity and axial-COM techniques are mostly sensitive to axial motion, and so were ineffective in this phantom experiment. 3D-COM demonstrates improved transaxial motion sensitivity, but not to the level of effectiveness of PCA.


2021 ◽  
Vol 9 ◽  
Author(s):  
Hamad Ali ◽  
Barrak Alahmad ◽  
Abdullah A. Al-Shammari ◽  
Abdulmohsen Alterki ◽  
Maha Hammad ◽  
...  

Background: The emergence of new COVID-19 variants of concern coupled with a global inequity in vaccine access and distribution has prompted many public health authorities to circumvent the vaccine shortages by altering vaccination protocols and prioritizing persons at high risk. Individuals with previous COVID-19 infection may not have been prioritized due to existing humoral immunity.Objective: We aimed to study the association between previous COVID-19 infection and antibody levels after COVID-19 vaccination.Methods: A serological analysis to measure SARS-CoV-2 immunoglobulin (Ig)G, IgA, and neutralizing antibodies was performed on individuals who received one or two doses of either BNT162b2 or ChAdOx1 vaccines in Kuwait. A Student t-test was performed and followed by generalized linear regression models adjusted for individual characteristics and comorbidities were fitted to compare the average levels of IgG and neutralizing antibodies between vaccinated individuals with and without previous COVID-19 infection.Results: A total of 1,025 individuals were recruited. The mean levels of IgG, IgA, and neutralizing antibodies were higher in vaccinated subjects with previous COVID-19 infections than in those without previous infection. Regression analysis showed a steeper slope of decline for IgG and neutralizing antibodies in vaccinated individuals without previous COVID-19 infection compared to those with previous COVID-19 infection.Conclusion: Previous COVID-19 infection appeared to elicit robust and sustained levels of SARS-CoV-2 antibodies in vaccinated individuals. Given the inconsistent supply of COVID-19 vaccines in many countries due to inequities in global distribution, our results suggest that even greater efforts should be made to vaccinate more people, especially individuals without previous COVID-19 infection.


2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Alen Brkic ◽  
Andreas P. Diamantopoulos ◽  
Espen Andre Haavardsholm ◽  
Bjørg Tilde Svanes Fevang ◽  
Lene Kristin Brekke ◽  
...  

Abstract Background In Norway, an annual tender system for the prescription of biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) has been used since 2007. This study aimed to explore annual b/tsDMARDs costs and disease outcomes in Norwegian rheumatoid arthritis (RA) patients between 2010 and 2019 under the influence of the tender system. Methods RA patients monitored in ordinary clinical practice were recruited from 10 Norwegian centers. Data files from each center for each year were collected to explore demographics, disease outcomes, and the prescribed treatment. The cost of b/tsDMARDs was calculated based on the drug price given in the annual tender process. Results The number of registered RA patients increased from 4909 in 2010 to 9335 in 2019. The percentage of patients receiving a b/tsDMARD was 39% in 2010 and 45% in 2019. The proportion of b/tsDMARDs treated patients achieving DAS28 remission increased from 42 to 67%. The estimated mean annual cost to treat a patient on b/tsDMARDs fell by 47%, from 13.1 thousand euros (EUR) in 2010 to 6.9 thousand EUR in 2019. The mean annual cost to treat b/tsDMARDs naïve patients was reduced by 75% (13.0 thousand EUR in 2010 and 3.2 thousand EUR in 2019). Conclusions In the period 2010–2019, b/tsDMARD treatment costs for Norwegian RA patients were significantly reduced, whereas DAS28 remission rates increased. Our data may indicate that the health authorities’ intention to reduce treatment costs by implementing a tender system has been successful.


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