The role of benzathine penicillin G in predicting and preventing all-cause acute respiratory disease in military recruits: 1991-2017.

The adenovirus vaccine and benzathine penicillin G (BPG) have been used by the US military to prevent acute respiratory diseases (ARD) in trainees, though these interventions have had documented manufacturing problems. We fit Poisson regression and random forest models (RF) to 26 years of weekly ARD incidence data to explore the impact of the adenovirus vaccine and BPG prophylaxis on respiratory disease burden. Adenovirus vaccine availability was among the most important predictors of ARD in the RF, while BPG was the ninth most important. BPG was a significant protective factor against ARD (incidence rate ratio (IRR) = 0.68; 95% confidence interval (CI) 0.67-0.70), but less so than either the old or new adenovirus vaccine (IRR = 0.39, 95% CI 0.38-0.39 and IRR = 0.11, 95% CI 0.11-0.11), respectively. These results suggest that BPG is moderately predictive of, and significantly protective against ARD, though to a lesser extent than either the old or new adenovirus vaccine.

Risks of Death and Severe Disease in Patients With Middle East Respiratory Syndrome Coronavirus, 2012-2015.

Middle East respiratory syndrome coronavirus (MERS-CoV) is an emerging pathogen, first recognized in 2012, with a high case fatality risk, no vaccine, and no treatment beyond supportive care. We estimated the relative risks of death and severe disease among MERS-CoV patients in the Middle East between 2012 and 2015 for several risk factors, using Poisson regression with robust variance and a bootstrap-based expectation maximization algorithm to handle extensive missing data. Increased age and underlying comorbidity were risk factors for both death and severe disease, while cases arising in Saudi Arabia were more likely to be severe. Cases occurring later in the emergence of MERS-CoV and among health-care workers were less serious. This study represents an attempt to estimate risk factors for an emerging infectious disease using open data and to address some of the uncertainty surrounding MERS-CoV epidemiology.

Make Data Sharing Routine to Prepare for Public Health Emergencies.

Jean-Paul Chretien and colleagues argue that recent Ebola and Zika virus outbreaks highlight the importance of data sharing in scientific research.

What factors might have led to the emergence of Ebola in West Africa?

An Ebola outbreak of unprecedented scope emerged in West Africa in December 2013 and presently continues unabated in the countries of Guinea, Sierra Leone, and Liberia. Ebola is not new to Africa, and outbreaks have been confirmed as far back as 1976. The current West African Ebola outbreak is the largest ever recorded and differs dramatically from prior outbreaks in its duration, number of people affected, and geographic extent. The emergence of this deadly disease in West Africa invites many questions, foremost among these: why now, and why in West Africa? Here, we review the sociological, ecological, and environmental drivers that might have influenced the emergence of Ebola in this region of Africa and its spread throughout the region. Containment of the West African Ebola outbreak is the most pressing, immediate need. A comprehensive assessment of the drivers of Ebola emergence and sustained human-to-human transmission is also needed in order to prepare other countries for importation or emergence of this disease. Such assessment includes identification of country-level protocols and interagency policies for outbreak detection and rapid response, increased understanding of cultural and traditional risk factors within and between nations, delivery of culturally embedded public health education, and regional coordination and collaboration, particularly with governments and health ministries throughout Africa. Public health education is also urgently needed in countries outside of Africa in order to ensure that risk is properly understood and public concerns do not escalate unnecessarily. To prevent future outbreaks, coordinated, multiscale, early warning systems should be developed that make full use of these integrated assessments, partner with local communities in high-risk areas, and provide clearly defined response recommendations specific to the needs of each community.

Modeling the impact of interventions on an epidemic of ebola in sierra leone and liberia.

BACKGROUND: An Ebola outbreak of unparalleled size is currently affecting several countries in West Africa, and international efforts to control the outbreak are underway. However, the efficacy of these interventions, and their likely impact on an Ebola epidemic of this size, is unknown. Forecasting and simulation of these interventions may inform public health efforts. METHODS: We use existing data from Liberia and Sierra Leone to parameterize a mathematical model of Ebola and use this model to forecast the progression of the epidemic, as well as the efficacy of several interventions, including increased contact tracing, improved infection control practices, the use of a hypothetical pharmaceutical intervention to improve survival in hospitalized patients. FINDINGS: Model forecasts until Dec. 31, 2014 show an increasingly severe epidemic with no sign of having reached a peak. Modeling results suggest that increased contact tracing, improved infection control, or a combination of the two can have a substantial impact on the number of Ebola cases, but these interventions are not sufficient to halt the progress of the epidemic. The hypothetical pharmaceutical intervention, while impacting mortality, had a smaller effect on the forecasted trajectory of the epidemic. INTERPRETATION: Near-term, practical interventions to address the ongoing Ebola epidemic may have a beneficial impact on public health, but they will not result in the immediate halting, or even obvious slowing of the epidemic. A long-term commitment of resources and support will be necessary to address the outbreak.

Modeling the impact of interventions on an epidemic of ebola in sierra leone and liberia.

BACKGROUND: An Ebola outbreak of unparalleled size is currently affecting several countries in West Africa, and international efforts to control the outbreak are underway. However, the efficacy of these interventions, and their likely impact on an Ebola epidemic of this size, is unknown. Forecasting and simulation of these interventions may inform public health efforts. METHODS: We use existing data from Liberia and Sierra Leone to parameterize a mathematical model of Ebola and use this model to forecast the progression of the epidemic, as well as the efficacy of several interventions, including increased contact tracing, improved infection control practices, the use of a hypothetical pharmaceutical intervention to improve survival in hospitalized patients. FINDINGS: Model forecasts until Dec. 31, 2014 show an increasingly severe epidemic with no sign of having reached a peak. Modeling results suggest that increased contact tracing, improved infection control, or a combination of the two can have a substantial impact on the number of Ebola cases, but these interventions are not sufficient to halt the progress of the epidemic. The hypothetical pharmaceutical intervention, while impacting mortality, had a smaller effect on the forecasted trajectory of the epidemic. INTERPRETATION: Near-term, practical interventions to address the ongoing Ebola epidemic may have a beneficial impact on public health, but they will not result in the immediate halting, or even obvious slowing of the epidemic. A long-term commitment of resources and support will be necessary to address the outbreak.