Female reproductive factors and risk of all-cause and cause-specific mortality among women: The Japan Public Health Center-based Prospective Study (JPHC study).

PURPOSE: We investigated the association between reproductive history and mortality from all and major causes among Japanese women. METHODS: A large-scale population-based cohort study in Japan included 40,149 eligible women aged 40-69 years in 1990-1994. A total of 4788 deaths were reported during follow-up (average 20.9 years). A Cox proportional hazards regression model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CI) for all-cause and major causes of mortality, adjusting for potential confounders. RESULTS: Inverse associations with all-cause mortality were found in parous women (0.74 [0.67-0.82]), women with two or three births compared with a single birth (2 births: 0.88 [0.78-0.99]; 3 births: 0.83 [0.74-0.94]), parous women who breastfed (0.81 [0.75-0.87]), women who were older at menopause (0.88 [0.80-0.97]; p-trend: <0.01), and women who had a longer fertility span (0.85 [0.76-0.95]; p-trend: <0.01). A positive association was seen between all-cause mortality and later age at first birth (≥30 years) than early childbearing (≤22 years). CONCLUSIONS: Our study suggests that parous, two or three births, breastfeeding, late age at menopause, and longer reproductive span are associated with lower risk of all-cause of mortality.

Reduced Risk of Importing Ebola Virus Disease because of Travel Restrictions in 2014: A Retrospective Epidemiological Modeling Study.

BACKGROUND: An epidemic of Ebola virus disease (EVD) from 2013-16 posed a serious risk of global spread during its early growth phase. A post-epidemic evaluation of the effectiveness of travel restrictions has yet to be conducted. The present study aimed to estimate the effectiveness of travel restrictions in reducing the risk of importation from mid-August to September, 2014, using a simple hazard-based statistical model. METHODOLOGY/PRINCIPAL FINDINGS: The hazard rate was modeled as an inverse function of the effective distance, an excellent predictor of disease spread, which was calculated from the airline transportation network. By analyzing datasets of the date of EVD case importation from the 15th of July to the 15th of September 2014, and assuming that the network structure changed from the 8th of August 2014 because of travel restrictions, parameters that characterized the hazard rate were estimated. The absolute risk reduction and relative risk reductions due to travel restrictions were estimated to be less than 1% and about 20%, respectively, for all models tested. Effectiveness estimates among African countries were greater than those for other countries outside Africa. CONCLUSIONS: The travel restrictions were not effective enough to expect the prevention of global spread of Ebola virus disease. It is more efficient to control the spread of disease locally during an early phase of an epidemic than to attempt to control the epidemic at international borders. Capacity building for local containment and coordinated and expedited international cooperation are essential to reduce the risk of global transmission.

Predicting the international spread of Middle East respiratory syndrome (MERS).

BACKGROUND: The Middle East respiratory syndrome (MERS) associated coronavirus has been imported via travelers into multiple countries around the world. In order to support risk assessment practice, the present study aimed to devise a novel statistical model to quantify the country-level risk of experiencing an importation of MERS case. METHODS: We analyzed the arrival time of each reported MERS importation around the world, i.e., the date on which imported cases entered a specific country, which was modeled as a dependent variable in our analysis. We also used openly accessible data including the airline transportation network to parameterize a hazard-based risk prediction model. The hazard was assumed to follow an inverse function of the effective distance (i.e., the minimum effective length of a path from origin to destination), which was calculated from the airline transportation data, from Saudi Arabia to each country. Both country-specific religion and the incidence data of MERS in Saudi Arabia were used to improve our model prediction. RESULTS: Our estimates of the risk of MERS importation appeared to be right skewed, which facilitated the visual identification of countries at highest risk of MERS importations in the right tail of the distribution. The simplest model that relied solely on the effective distance yielded the best predictive performance (Area under the curve (AUC) = 0.943) with 100 % sensitivity and 79.6 % specificity. Out of the 30 countries estimated to be at highest risk of MERS case importation, 17 countries (56.7 %) have already reported at least one importation of MERS. Although model fit measured by Akaike Information Criterion (AIC) was improved by including country-specific religion (i.e. Muslim majority country), the predictive performance as measured by AUC was not improved after accounting for this covariate. CONCLUSIONS: Our relatively simple statistical model based on the effective distance derived from the airline transportation network data was found to help predicting the risk of importing MERS at the country level. The successful application of the effective distance model to predict MERS importations, particularly when computationally intensive large-scale transmission models may not be immediately applicable could have been benefited from the particularly low transmissibility of the MERS coronavirus.