Sensitivity of Household Transmission to Household Contact Structure and Size

Study the influence of household contact structure on the spread of an influenza-like illness. Examine whether changes to in-home care giving arrangements can significantly affect the household transmission counts.We simulate two different behaviors for the symptomatic person; either s/he remains at home in contact with everyone else in the household or s/he remains at home in contact with only the primary caregiver in the household. The two different cases are referred to as full mixing and single caregiver, respectively.The results show that the household's cumulative transmission count is lower in case of a single caregiver configuration than in the full mixing case. The household transmissions vary almost linearly with the household size in both single caregiver and full mixing cases. However the difference in household transmissions due to the difference in household structure grows with the household size especially in case of moderate flu.These results suggest that details about human behavior and household structure do matter in epidemiological models. The policy of home isolation of the sick has significant effect on the household transmission count depending upon the household size

Transmission of Novel Influenza A(H1N1) in Households with Post-Exposure Antiviral Prophylaxis

BACKGROUND: Despite impressive advances in our understanding of the biology of novel influenza A(H1N1) virus, little is as yet known about its transmission efficiency in close contact places such as households, schools, and workplaces. These are widely believed to be key in supporting propagating spread, and it is therefore of importance to assess the transmission levels of the virus in such settings. METHODOLOGY/PRINCIPAL FINDINGS: We estimate the transmissibility of novel influenza A(H1N1) in 47 households in the Netherlands using stochastic epidemic models. All households contained a laboratory confirmed index case, and antiviral drugs (oseltamivir) were given to both the index case and other households members within 24 hours after detection of the index case. Among the 109 household contacts there were 9 secondary infections in 7 households. The overall estimated secondary attack rate is low (0.075, 95%CI: 0.037-0.13). There is statistical evidence indicating that older persons are less susceptible to infection than younger persons (relative susceptibility of older persons: 0.11, 95%CI: 0.024-0.43. Notably, the secondary attack rate from an older to a younger person is 0.35 (95%CI: 0.14-0.61) when using an age classification of <or=12 versus >12 years, and 0.28 (95%CI: 0.12-0.50) when using an age classification of <or=18 versus >18 years. CONCLUSIONS/SIGNIFICANCE: Our results indicate that the overall household transmission levels of novel influenza A(H1N1) in antiviral-treated households were low in the early stage of the epidemic. The relatively high rate of adult-to-child transmission indicates that control measures focused on this transmission route will be most effective in minimizing the total number of infections

Quantum key distribution based on orthogonal states allows secure quantum bit commitment

For more than a decade, it was believed that unconditionally secure quantum bit commitment (QBC) is impossible. But basing on a previously proposed quantum key distribution scheme using orthogonal states, here we build a QBC protocol in which the density matrices of the quantum states encoding the commitment do not satisfy a crucial condition on which the no-go proofs of QBC are based. Thus the no-go proofs could be evaded. Our protocol is fault-tolerant and very feasible with currently available technology. It reopens the venue for other "post-cold-war" multi-party cryptographic protocols, e.g., quantum bit string commitment and quantum strong coin tossing with an arbitrarily small bias. This result also has a strong influence on the Clifton-Bub-Halvorson theorem which suggests that quantum theory could be characterized in terms of information-theoretic constraints.Comment: Published version plus an appendix showing how to defeat the counterfactual attack, more references [76,77,90,118-120] cited, and other minor change

Eosinophilic esophagitis associated to esophagus achalasia - case report

Univ Sao Paulo, Fac Med, Dept Pediat, Allergy & Immunol Unit, Sao Paulo, BrazilUniv Sao Paulo, Fac Med, Dept Pediat, Pediat Surg Unit, Sao Paulo, BrazilWeb of Scienc

Health-related quality of life and its correlates in Japanese patients with myotonic dystrophy type 1

Makiko Endo,1 Kaori Odaira,2 Ryohei Ono,3 Go Kurauchi,4 Atsushi Koseki,5 Momoko Goto,3 Yumi Sato,4 Seiko Kon,6 Norio Watanabe,7 Norio Sugawara,8 Hiroto Takada,6 En Kimura9 1Clinical Research Unit, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-8551, Japan; 2Regional Medical Liaison Office, National Hospital Organization, Aomori Hospital, Namioka, Aomori 038-1331, Japan; 3Section for Development and Disability Training, National Hospital Organization, Aomori Hospital, Namioka, Aomori 038-1331, Japan; 4Department of Rehabilitation, National Hospital Organization, Aomori Hospital, Namioka, Aomori 038-1331, Japan; 5Section for Development and Disability Training, National Hospital Organization, Hanamaki Hospital, Hanamaki, Iwate 025-0033, Japan; 6Department of Neurology, National Hospital Organization, Aomori Hospital, Namioka, Aomori 038-1331, Japan; 7School of Public Health, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan; 8Department of Clinical Epidemiology, Translational Medical Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-8551, Japan; 9Department of Clinical Research Support, Translational Medical Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-8551, Japan Purpose: Myotonic dystrophy type 1 (DM1) is a common form of muscular dystrophy that presents with a variety of symptoms that can affect patients&rsquo; quality of life (QoL). Despite the importance of clarifying patients&rsquo; subjective experience in both physical and psychosocial aspects for improved symptom management, there is lack of evidence concerning QoL of patients with DM1 in Japan.Patients and methods: A cross-sectional study was performed with 51 DM1 patients who completed questionnaires that measured health-related QoL (HRQoL), depression, and daytime sleepiness. Activities of daily living, body mass index (BMI), and genetic information were also collected, together with general demographic information. Correlation analyses using these variables were performed. Furthermore, regression analysis was utilized to assess the relationship that HRQoL, depression, and daytime sleepiness scores have with other variables.Results: Physical component summary (PCS) score was affected by the disease more than the mental component summary (MCS) score among study participants. Moderate correlation was observed between PCS and depression, PCS and Barthel index, and depression and daytime sleepiness. Regression analysis revealed that age, sex, cytosine&ndash;thymine&ndash;guanine repeats, and BMI did not predict the aforementioned dependent variables.Conclusion: DM1 symptoms influenced physical component scores more than mental component scores, although the state of physical wellness seemed to affect patients&rsquo; mood. Explaining the QoL of these patients only using biologic and genetic characteristics was not sufficient. We conclude that social and psychological aspects of these patients&rsquo; lives and the nature of adjustments made by patients due to DM1 to require further examination in order to improve the standard of care. Keywords: depression, excessive daytime sleepiness, chronic illness, psychosocial perspective&nbsp

Estimating time to onset of swine influenza symptoms after initial novel A(H1N1v) viral infection

Characterization of the incubation time from infection to onset is important for understanding the natural history of infectious diseases. Attempts to estimate the incubation time distribution for novel A(H1N1v) have been, up to now, based on limited data or peculiar samples. We characterized this distribution for a generic group of symptomatic cases using laboratory-confirmed swine influenza case-information. Estimates of the incubation distribution for the pandemic influenza were derived through parametric time-to-event analyses of data on onset of symptoms and exposure dates, accounting for interval censoring. We estimated a mean of about 1·6-1·7 days with a standard deviation of 2 days for the incubation time distribution in those who became symptomatic after infection with the A(H1N1v) virus strain. Separate analyses for the <15 years and ⩾15 years age groups showed a significant (P<0·02) difference with a longer mean incubation time in the older age group