The reachability of contagion in temporal contact networks: how disease latency can exploit the rhythm of human behavior

The symptoms of many infectious diseases influence their host to withdraw from social activity limiting their own potential to spread. Successful transmission therefore requires the onset of infectiousness to coincide with a time when its host is socially active. Since social activity and infectiousness are both temporal phenomena, we hypothesize that diseases are most pervasive when these two processes are synchronized. We consider disease dynamics that incorporate a behavioral response that effectively shortens the infectious period of the disease. We apply this model to data collected from face-to-face social interactions and look specifically at how the duration of the latent period effects the reachability of the disease. We then simulate the spread of the model disease on the network to test the robustness of our results. Diseases with latent periods that synchronize with the temporal social behavior of people, i.e. latent periods of 24 hours or 7 days, correspond to peaks in the number of individuals who are potentially at risk of becoming infected. The effect of this synchronization is present for a range of disease models with realistic parameters. The relationship between the latent period of an infectious disease and its pervasiveness is non-linear and depends strongly on the social context in which the disease is spreading.Comment: 9 Pages, 5 figure

Comparative evaluation of strain ratio on sonographic elastography and T2* values on 3 Tesla magnetic resonance imaging in differentiating malignant from benign axillary lymph nodes in breast cancer

Background: The study aimed to assess whether strain ratio and T2* values can improve the sensitivity and specificity of differentiating metastatic from benign axillary lymph nodes in breast cancer patients taking histopathology as reference standard.Methods: The study was done on 43 patients. A multi-echo transverse T2*W MR sequence was obtained with TE = 0.9- 1.5 ms, TR=37.2 ms and flip angle = 25°. Sonographic elastography was done using high frequency linear probe (L3-16 MHz). Manual selection of the region of interest was done on suspicious lymph nodes for calculation of T2* values and strain ratio. ROC curves were obtained for various T2* and strain ratio values in comparison to histopathological findings as gold standard.Results: Correlation with histopathology was better with T2* values than strain ratio. The sensitivity and specificity were calculated using cut off values obtained from ROC curve (31.225 ms for T2* value and 1.85 for SR) and were 70.37%, 68.75% for strain ratio and 96.29%, 93.75% for T2* value respectively. The positive predictive value and negative predictive value were also assessed, values being higher for T2* than strain ratio. Comparison of areas under ROC curve was statistically significant with p=0.018.Conclusions: T2* can be used as a potential biomarker for differentiating metastatic from benign axillary lymph nodes owing to its high sensitivity, specificity and relative ease of performance. Quantitative assessment of changes in T2* values may allow more objective analysis of signal changes with significant differences between benign and malignant lymph nodes, even in case of partial infiltration.

Significance of Correct Diagnosis of Odontogenic Extraoral Sinus: A Report Of Two Cases

Cutaneous draining sinus tracts of odontogenic origin often are a diagnostic challenge. A delay in correctly diagnosing these types of lesions can result in unnecessary antibiotic therapy and surgical treatment. This case report presents the clinical course of two cases with extra-oral sinus tract formation, from diagnosis and treatment to short-term follow-up and evaluation. These facial lesions were initially misdiagnosed as lesions of non-odontogenic origin. Later on an odontogenic cause was identified and endodontic intervention resulted in resolution of the problem, confirming the initial misdiagnosis

Comparative Assessment of Some Target Detection Algorithms for Hyperspectral Images

Target detection is of particular interest in hyperspectral image analysis as many unknown and subtle signals (spectral response) unresolved by multispectral sensors can be discovered in hyperspectral images. The detection of signals in the form of small objects and targets from hyperspectral sensors has a wide range of applications both civilian and military. It has been observed that a number of target detection algorithms are in vogue; each has its own advantages and disadvantages and assumptions. The selection of a particular algorithm may depend on the amount of information available as per the requirement of the algorithm, application area, the computational complexity etc. In the present study, three algorithms, namely, orthogonal subspace projection (OSP), constrained energy minimization (CEM) and a nonlinear version of OSP called kernel orthogonal subspace projection (KOSP), have been investigated for target detection from hyperspectral remote sensing data. The efficacy of algorithms has been examined over two different hyperspectral datasets which include a synthetic image and an AVIRIS image. The quality of target detection from these algorithms has been evaluated through visual interpretation as well as through receiver operating characteristic (ROC) curves. The performance of OSP algorithm has been found to be better than or comparable to CEM algorithm. However, KOSP out performs both the algorithms.Defence Science Journal, 2013, 63(1), pp.53-62, DOI:http://dx.doi.org/10.14429/dsj.63.376

Overview of liver disorders during pregnancy at a tertiary care centre: Uttarakhand scenario

Background: Liver disorders in pregnancy encompass a spectrum of diseases encountered during antenatal and postnatal period resulting in abnormal liver function tests and hepatobiliary dysfunction or both. This study is aimed at determining the causes of liver disorders during pregnancy and associated maternal and fetal outcomes over a period of 3 years at a tertiary care centre of Dehradun.Methods: All case records of patients with liver disorders during pregnancy from May 2013 to May 2016 were retrieved from medical record department of SGRRIMHS, Dehradun and analyzed for various causes of liver disorders and associated maternal and fetal outcomes.Results: During the three-year study period, 146 pregnant patients were found to have liver disorders. The study found that viral hepatitis was the most common cause of liver disorders followed by Intrahepatic cholestasis of pregnancy IHCP. There were 6 mortalities among the study group out of which hepatitis E was the culprit for maternal mortality in two patients. The serum bilirubin levels were directly proportional to the maternal deaths.Conclusions: Liver disorders during pregnancy are rare but an important cause of maternal and fetal morbidity and mortality. Early recognition, timely referral and aggressive management may lead to better maternal and fetal outcome

Analysis of maternal deaths over a period of three years at a tertiary care centre of Uttarakhand, India

Background: Globally, about 800 women die every day of preventable causes related to pregnancy and childbirth; 20 per cent of these women are from India. The study is aimed at evaluating maternal deaths over a period of three years at a tertiary care centre of Dehradun, India.Methods: This was a retrospective study conducted in the Department of Obstetrics and Gynecology at SGRRIMHS, Dehradun. The case record files of all maternal deaths from January 2015 to December 2017 was obtained from medical record section of the hospital. Maternal age, parity, educational status, antenatal registration, mode of delivery, admission death interval and causes of each maternal death was noted and analysed statistically.Results: There were 48 maternal deaths from January 2015 to December 2017.Maximum deaths were in the age group of 21-25 years. The maternal mortality ratio over a period of three years was 671 per one lac live births. Most of the maternal deaths were due to direct causes like hemorrhage , eclampsia followed by sepsis.Conclusions: Most of the maternal deaths are preventable. High risk cases should be identified at root level and early referral should be the moto. All women need access to antenatal care in pregnancy, skilled care during childbirth, and care and support in the weeks after childbirth. To avoid maternal deaths, unwanted and too-early pregnancies should be avoided. All women, including adolescents, should have access to contraception, safe abortion services to the full extent of the law, and quality post-abortion care. It is particularly important that all births are attended by skilled health professionals, as timely management and treatment can make the difference between life and death for both the mother and the baby

Detecting Signals of Seasonal Influenza Severity Through Age Dynamics

BACKGROUND: Measures of population-level influenza severity are important for public health planning, but estimates are often based on case-fatality and case-hospitalization risks, which require multiple data sources, are prone to surveillance biases, and are typically unavailable in the early stages of an outbreak. To address the limitations of traditional indicators, we propose a novel severity index based on influenza age dynamics estimated from routine physician diagnosis data that can be used retrospectively and for early warning. METHODS: We developed a quantitative \u27ground truth\u27 severity benchmark that synthesizes multiple traditional severity indicators from publicly available influenza surveillance data in the United States. Observing that the age distribution of cases may signal severity early in an epidemic, we constructed novel retrospective and early warning severity indexes based on the relative risk of influenza-like illness (ILI) among working-age adults to that among school-aged children using weekly outpatient medical claims. We compared our relative risk-based indexes to the composite benchmark and estimated seasonal severity for flu seasons from 2001-02 to 2008-09 at the national and state levels. RESULTS: The severity classifications made by the benchmark were not uniquely captured by any single contributing metric, including pneumonia and influenza mortality; the influenza epidemics of 2003-04 and 2007-08 were correctly identified as the most severe of the study period. The retrospective index was well correlated with the severity benchmark and correctly identified the two most severe seasons. The early warning index performance varied, but it projected 2007-08 as relatively severe 10 weeks prior to the epidemic peak. Influenza severity varied significantly among states within seasons, and four states were identified as possible early warning sentinels for national severity. CONCLUSIONS: Differences in age patterns of ILI may be used to characterize seasonal influenza severity in the United States in real-time and in a spatially resolved way. Future research on antigenic changes among circulating viruses, pre-existing immunity, and changing contact patterns may better elucidate the mechanisms underlying these indexes. Researchers and practitioners should consider the use of composite or ILI-based severity metrics in addition to traditional severity measures to inform epidemiological understanding and situational awareness in future seasonal outbreaks