supporting_information.pdf

The HIV pandemic continues to impose enormous morbidity, mortality and economic burdens across the globe. Simultaneously, innovations in antiretroviral therapy, diagnostic approaches and vaccine development are providing novel tools for treatment-as-prevention and prophylaxis. We developed a mathematical model to evaluate the added benefit of an HIV vaccine in the context of goals to increase rates of diagnosis, treatment, and viral suppression in 127 countries. Under status quo interventions, we predict a median of 49 million [1st and 3rd quartiles 44M, 58M] incident cases globally from 2015 to 2035. Achieving the UNAIDS 95–95–95 target was estimated to avert 25 million [20M, 33M] of these new infections, and an additional 6.3 million [4.8M, 8.7M] reduction was projected with the 2020 introduction of a 50%-efficacy vaccine gradually scaled up to 70% coverage. This added benefit of prevention through vaccination motivates imminent and ongoing clinical trials of viable candidates to realize the goal of HIV control

Effectiveness of UNAIDS targets and HIV vaccination across 127 countries

The HIV pandemic continues to impose enormous morbidity, mortality and economic burdens across the globe. Simultaneously, innovations in antiretroviral therapy, diagnostic approaches and vaccine development are providing novel tools for treatment-as-prevention and prophylaxis. We developed a mathematical model to evaluate the added benefit of an HIV vaccine in the context of goals to increase rates of diagnosis, treatment, and viral suppression in 127 countries. Under status quo interventions, we predict a median of 49 million [1st and 3rd quartiles 44M, 58M] incident cases globally from 2015 to 2035. Achieving the UNAIDS 95–95–95 target was estimated to avert 25 million [20M, 33M] of these new infections, and an additional 6.3 million [4.8M, 8.7M] reduction was projected with the 2020 introduction of a 50%-efficacy vaccine gradually scaled up to 70% coverage. This added benefit of prevention through vaccination motivates imminent and ongoing clinical trials of viable candidates to realize the goal of HIV control

Retrospective Analysis of the 2014-2015 Ebola Epidemic in Liberia.

The 2014-2015 Ebola epidemic has been the most protracted and devastating in the history of the disease. To prevent future outbreaks on this scale, it is imperative to understand the reasons that led to eventual disease control. Here, we evaluated the shifts of Ebola dynamics at national and local scales during the epidemic in Liberia. We used a transmission model calibrated to epidemiological data between June 9 and December 31, 2014, to estimate the extent of community and hospital transmission. We found that despite varied local epidemic patterns, community transmission was reduced by 40-80% in all the counties analyzed. Our model suggests that the tapering of the epidemic was achieved through reductions in community transmission, rather than accumulation of immune individuals through asymptomatic infection and unreported cases. Although the times at which this transmission reduction occurred in the majority of the Liberian counties started before any large expansion in hospital capacity and the distribution of home protection kits, it remains difficult to associate the presence of interventions with reductions in Ebola incidence

Interruption of tuberculosis detection and care during the Ebola virus disease epidemic (2014–2015) in Liberia: time-series analyses for 2013–2017

Objective Interrupted time-series analyses, using 5 years of routinely collected health information system data, were conducted to estimate the magnitude of impact of the 2014–2015 Ebola virus disease (EVD) epidemic and determine trends in tuberculosis (TB) care services in Liberia. Methods A segmented linear regression model was used to generate estimates and predictions for trends for three TB service indicators before, during, and after EVD, from January 2013 to December 2017. Results It was found that the number of presumptive TB cases declined significantly at the start of the EVD outbreak, with an estimated loss of 3222 cases (95% confidence interval (CI) −5691 to −752; P = 0.014). There was also an estimated loss of 709 cases per quarter post-EVD (95% CI −1346 to −71; P = 0.032). However, over the post-EVD period, quarterly increases were observed in the proportion of smear-positive to presumptive cases (1.45%, 95% CI 0.38% to 2.5%; P = 0.011) and the proportion of treatment success to TB cases evaluated (3.3%, 95% CI 0.82% to 5.79%; P = 0.013). Conclusions These findings suggest that the EVD outbreak (2014–2015) negatively affected TB care services. Rigorous quantitative analyses can be used to assess the magnitude of interruption and advocate for preparedness in settings with limited healthcare capacity

Lack of an Association between Passive Smoking and Incidence of Female Breast Cancer in Non-Smokers: Evidence from 10 Prospective Cohort Studies

<div><p>Background</p><p>Several case-control studies have suggested that passive smoking may increase the incidence of female breast cancer. However, the results of cohort studies have been inconsistent in establishing an association. The present study evaluated the association between passive smoking and incidence of female breast cancer through a meta-analysis of prospective cohort studies.</p><p>Methods</p><p>Relevant articles published before August 2012 were identified by searching the electronic databases PubMed, Embase, and Web of Science. Pooled relative risks (RRs) were determined with either a fixed or random effects model and were used to assess the strength of the association. Sensitivity and subgroup analyses according to ethnicity, menopausal status, and the period and place of exposure to passive smoking were also performed.</p><p>Results</p><p>Ten prospective cohort studies involving 782 534 female non-smokers were included in the meta-analysis and 14 831 breast cancer cases were detected. Compared with the women without exposure to passive smoking, the overall combined RR of breast cancer was 1.01 (95% confidence interval: 0.96 to 1.06, P = 0.73) among women with exposure to passive smoking. Similar results were achieved through the subgroup analyses. No evidence of publication bias was observed.</p><p>Conclusion</p><p>The results suggest that passive smoking may not be associated with increased incidence of breast cancer. However, the present conclusion should be considered carefully and confirmed with further studies.</p></div