Microorganisms are present in our daily life. While most of the time they cause minimal to no harm, they also have the potential of becoming pathogenic; triggering diseases that eventually lead to outbreaks. Critical questions in the epidemiological field are when, where, and why new microorganisms are going to cause outbreaks – ones that could potentially become a worldwide epidemic.

When responding to outbreaks, an expedient and coordinated response is of the essence in ensuring the minimal impact on communities. However, barriers still exist in creating high-quality responses to outbreaks of new diseases. These include a lag in time to trigger the awareness of local, state and federal health organizations due to: i) a mix of lack of funding, awareness, and political disbelief; ii) the communication of funding needs to create the appropriate response with the appropriate agencies; and finally, iii) the time required to develop vaccines is much more than the time needed for the disease to develop from a local outbreak to a global epidemic.

In an ideal world, a system, which samples potential pathogens over time and location regardless of the intensity of disease or presence of pathogenicity, would exist. This system would allow researchers to investigate viruses present in nature that at present inflict no harm on humans. Unfortunately, the current system retroactively identifies pathogens over time and location after it has infected multiple people and caused pathogenicity. This is possibly due to a lack of previous effective surveillance, resulting in researchers reactively investigate viruses and a rush for vaccine or drug development. The outcome is a hidden threat to population health that may not have been given the necessary attention to solving the issue.

Big data

However, many resources may be leveraged to solve this problem. New technology that would allow for improved, real-time communication and data collection is commonplace in our society. Additionally, the costs associated with genomic sequencing are decreasing, and pathogens are now starting to be sequenced near real-time as disease outbreaks unveil. We have seen recent examples of this during the 2013-2014 Ebola Outbreak in West Africa (Quick et al., 2016), on the 2015-2017 Zika Epidemic in the Americas (, as well as the military response from USAMRIID (Grubaugh et al., 2017) in Florida. These projects performed on-site real-time genomic sequencing which allowed for immediate response by the research community through the use of publicly available virus genome and sequence data resources.

The need for a new integrative platform for disease surveillance

Currently, there is a need for a platform that integrates data from multidisciplinary approaches into an easy interactive interface. One solution would be to integrate molecular data with the epidemiological and investigative process, packaged into a platform that provides the information and analytical tools in a manner that is easy to work. While decision makers will need more comprehensive data to change public policy, this platform would allow for preliminary assessments that could trigger attention and resources to emerging epidemiologic issues.

The quest for universal vaccines

In 2018, we are far from having universal vaccines to fight emerging pathogens. Zika, for example, is one of approximately 70 known mosquito-transmitted Flaviviruses, which also include human pathogens like Dengue virus and Japanese encephalitis virus. There is only one member of this group for which a broadly accessible vaccine is available, Yellow Fever virus. A pan-Flavivirus vaccine that can fight many if not all mosquito-borne flaviviruses is, however, urgently needed. Computational biology plays a crucial role here. We have a vast stockpile of genome data in publicly available databases, as well as algorithms and tools to perform comparative genomics screens (i.e., learn common patterns in genome architecture to study evolutionarily conserved domains), which will facilitate the development of novel vaccines.

Our current limitations

In most developed countries, we can create new technology and the organizational structure, but we face the conventional/non-progressive users that may not adhere to technology at state, county, and city level. We also face the issue of how to market a platform so not only the analysts adhere, but community users become part of it and actively participate.

In developing economies, we may have a lack of infrastructure as well as access to information for users. The investment on infrastructure in the next years on undeveloped risk areas will be essential to enable the surveillance on outbreaks.

Takeaway message

We advocate for focusing research agendas on currently neglected pathogens, such as Chikungunya and Mayaro viruses, which can cause severe outbreaks. Big data is being generated and disseminated rapidly, but it is not the sole solution. Scientists are struggling with not only how to handle the data, but to how to communicate its meaning in “laymen’s terms” to decision makers. Appropriate communication of the outcomes of data analysis is essential to help public health officials make the necessary changes in policy and enforcement at all levels to respond to outbreaks appropriately.

Multidisciplinary efforts, which include but are not limited to pathologists, epidemiologists, and bioinformaticians, are the key for a successful surveillance system and the advancement of vaccine research. For this to be accomplished, a common language must be established and used across these fields to facilitate effective and expedient communication and collaboration.

The need for implementation of infrastructure and novel surveillance analytics are essential for the domestic protection against infectious diseases, as well as military personnel and peacekeepers who are exposed to risk zones overseas. Having technology that enables the development of disease heat maps is essential for the safety of all.


Grubaugh, Nathan D., et al. “Genomic epidemiology reveals multiple introductions of Zika virus into the United States.” Nature 546.7658 (2017): 401.

Quick, Joshua, et al. “Real-time, portable genome sequencing for Ebola surveillance.” Nature 530.7589 (2016): 228.

This article was written by Adriano de Bernardi Schneider and Dr. Michael T. Wolfinger

Adriano de Bernardi Schneider, MS is a Brazilian molecular and computational biology researcher. His current focus of research is on the development of new tools and strategies to study viral transmission networks. He was part of a response effort to the 2015 Zika Outbreak, the Zika Response Working Group and is currently a Ph.D. Candidate in Bioinformatics and Computational Biology at the University of North Carolina at Charlotte.

Dr. Michael T. Wolfinger is an Austrian chemist specializing in theoretical biochemistry. His research field is computational RNA biology, where he focuses on the development of novel strategies and algorithms to study the regulation and evolution of bacteria, archaea, and viruses. He is affiliated with the University of Vienna and the Medical University of Vienna and has authored more than 25 contributions in international peer-reviewed scientific journals.