Publications

The use of infectious disease modeling to support public health decision making, referred to in this report as “outbreak science,” has increased in prominence in the past decade. It has been used in the responses to several major outbreaks, from severe acute respiratory syndrome (SARS) in 2003, to H1N1 influenza in 2009, to the 2 most recent Ebola outbreaks in West Africa (2014-2016) and the Democratic Republic of the Congo (2018-current).

Sustained spread of SARS-CoV-2 has happened in major US cities. Capacity needs in Chinese cities could inform the planning of local healthcare resources.

Clade X was a day-long pandemic tabletop exercise conducted by the Johns Hopkins Center for Health Security on May 15, 2018, in Washington, DC. In this report, we briefly describe the exercise development process and focus principally on the findings and recommendations that arose from this project.

Clade X was a day-long pandemic tabletop exercise conducted by the Johns Hopkins Center for Health Security on May 15, 2018, in Washington, DC. Many details of the exercise are available online, including videos, background documents, and fact sheets.In this report, we briefly describe the exercise development process and focus principally on the findings and recommendations that arose from this project.

On July 26, 2019, the workshop “Biosafety and Biosecurity in the Era of Synthetic Biology: Meeting the Challenges in China and the U.S.”, co-hosted by Johns Hopkins Center for Health Security and Tianjin University Centre for Biosafety Research & Strategy, was held in Washington, D.C. of the United States. The goal of this workshop was to bring technical and policy experts from China and the U.S., as well as experts from Europe, together to develop a mutual understanding of each country’s current governance structures and to begin a dialogue on what is required to promote global biosafety and biosecurity.

On July 26, 2019, researchers, policymakers, and other stakeholders gathered at the St. Regis Hotel in Washington, DC, for a day-long dialogue on safety and security in an era of synthetic biology. The meeting, co-sponsored by the Johns Hopkins Center for Health Security and Tianjin University Centre for Biosafety Research and Strategy, drew more than 100 attendees and featured speakers from China, Europe, and the United States.

The United States and China are at the forefront of research and investment in synthetic biology. As leading countries in this rapidly evolving field, they have a responsibility to work together to promote safety and security. The goal of this meeting was to bring representatives from China and the United States together to develop a mutual understanding of each country’s current governance structures and to begin a dialogue on what is required to promote global safety and security. This report recounts the meeting’s activities and shares several key themes derived from the presentations and conversations of the day.

Present capacity to develop, evaluate, manufacture, distribute and administer effective medical countermeasures (e.g., vaccines, diagnostics, therapeutics) is inadequate to meet the burden of both recurrent and emerging outbreaks of infectious diseases. When such interventions are unavailable, public health measures (e.g., contact tracing, outbreak investigations, social distancing) and supportive clinical care remain the only feasible tools to slow an emerging outbreak. Decision-making under such circumstances can be greatly improved by the use of appropriate data and advanced analytics such as infectious disease modeling or machine learning. Furthermore, these analyses can guide decision-making when medical countermeasures become available, allowing them to be used in more effective ways. Data analyses already underpin public health actions such as anticipating resource requirements, refining situational awareness and monitoring control efforts^2,3,4,5. New applications of data science and statistical analyses to disease outbreaks could provide support to decision-makers during public health crises.

Infectious disease modeling has played a prominent role in recent outbreaks, yet integrating these analyses into public health decision-making has been challenging. We recommend establishing ‘outbreak science’ as an inter-disciplinary field to improve applied epidemic modeling.

The 2014–16 West Africa Ebola epidemic was a watershed moment for global health. The outbreak galvanized global action around strengthening infectious disease prevention, detection and response capabilities. We examined the nascent landscape of international programmes, initiatives and institutions established in the aftermath of the 2014–16 Ebola outbreak with the aim of assessing their progress to date to illustrate the current state of the world’s global health security architecture. We also compare these efforts with shortcomings in epidemic management documented during the epidemic, and underscore remaining gaps in regional and global epidemic response capabilities that might benefit from additional programmatic and financial support. Notably, most of the post-Ebola initiatives considered in this analysis have yet to meet their financial goals. Operational progress has also been limited, revealing a need for continued investments to improve outbreak surveillance and detection capabilities specifically. Furthermore, our review highlighted the dominance of the USA and Europe in leading and financing efforts to coordinate long-term recovery efforts in West Africa, strengthen health systems across the continent, and enhance global preparedness for future epidemics, raising important questions about ownership of global health security efforts in non-Western regions of the world. Finally, the lack of transparency and available data on these initiatives’ activities and budgets also complicate efforts to project their impacts on the global health security landscape.

This report highlights 15 technologies or categories of technologies that, with further scientific attention and investment, as well as attention to accompanying legal, regulatory, ethical, policy, and operational issues, could help make the world better prepared and equipped to prevent future infectious disease outbreaks from becoming catastrophic events.

It is important to distinguish between predicting the emergence of infectious diseases and their trajectory (see E. C. Holmes et al. Nature 558, 180–182; 2018). It is currently impossible to predict emergence, but feasible and effective to predict the trajectory.

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.

Every few years, a new pathogen emerges from the shadows to threaten global public health. And every few years, the global public health community struggles to mount a timely and effective response. The incremental advances that have defined public health in the last half century have been repeatedly outpaced by fast-moving epidemics. From HIV to Ebola, most innovations in preventing and containing outbreaks have come from medical countermeasures like vaccines, diagnostics, and therapeutics rather than advancements in epidemiological practice.

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.

In February 2016, Wellcome Trust organized a pledge among leading scientific organizations and health agencies encouraging researchers to release data relevant to the Zika outbreak as rapidly and widely as possible [1]. This initiative echoed a September 2015 World Health Organization (WHO) consultation that assessed data sharing during the recent West Africa Ebola outbreak and called on researchers to make data publicly available during public health emergencies [2]. These statements were necessary because the traditional way of communicating research results—publication in peer-reviewed journals, often months or years after data collection—is too slow during an emergency.