Outbreaks of life-threatening infectious diseases such as Ebola in West Africa, Zika in South America, Avian influenza in China, and Nipah in India are occurring with increasing frequency. These emerging and re-emerging infections and their potential to spread across borders pose serious threats to public health and development. Responding to such threats necessitates identifying emerging health trends, conducting surveillance, diagnosing infections, and providing treatment for patients.
This roundtable convened scientists and industry experts to identify how preparedness and response to pandemics can be improved, including the capabilities that industry and the research community can offer to help governments tackle adverse biological events. The discussion was moderated by Gagandeep Kang, executive director of the Translational Health Science and Technology Institute.
Discussion Highlights
- Disease Reporting in India: Participants highlighted that the ability to sequence pathogens has transformed the ability to detect infections. High-throughput sequencing data can be used to understand preparedness and predict disease outbreaks, they explained. Participants added that this data can also be used to develop medical countermeasures—vaccines, diagnostic kits, and other treatment options. However, they emphasized, the development of preventive and treatment measures depends on effective and accurate disease reporting. Some participants raised serious concerns about infrastructure and human resource capabilities needed to accurately detect and report an outbreak. Noting that India only mandates a few institutions to report disease outbreaks, participants explained that reporting a higher number of infected cases is not a bad thing. Adequate information regarding the number and kinds of disease incidences in the country can be used to develop a comprehensive disease surveillance model. Therefore, more actors—both from the public and private sector—should be brought into this network, they underlined.
- Disease Surveillance in India: Participants pointed out that India has a skewed data collection model where multiple organizations across the local, state, and national levels collect data for the same disease. Since these organizations use differing case definitions, standards, and practices, and have little or no coordination (and often turf battles), this leads to different disease numbers being reported under different programs, participants explained. They highlighted that this results in the creation of a weak surveillance infrastructure, poor detection of outbreaks, an overburdened healthcare force as diagnostics is impaired, along with a convoluted, uncoordinated, and ineffective disease mapping mechanism. To overcome this, participants drew attention to the need to harmonize data collection tools and develop common reporting standards for all primary healthcare centers in India. In addition to developing domestic standards, participants also emphasized the importance of optimizing and working with international organizations to have common methods and protocols to facilitate cross-border data sharing. They added that to the extent that nations develop common data standardization, each would benefit from the resultant possibility of improving international cooperation in diagnostics and development of vaccines and/or treatments.
- Epidemiological Model of Diseases: Participants suggested engendering greater collaboration among scientists, academicians, industry, and data scientists to develop epidemiological models for diseases, which could help predict the location and timing of outbreaks. They argued that this model should also consider socio-economic circumstances, environmental conditions, and geographical terrains that are associated with disease occurrence. They highlighted that since this model can provide adequate background information on naturally occurring diseases, it will facilitate the recognition and prediction of unusual outbreaks. For diseases that manifest unusual symptoms, participants proposed that a horizontal network of primary healthcare should be created to detect and respond to such infections quickly. While participants recognized that training people to diagnose an infection and sequence the pathogen has proven quite feasible in India, they noted that retaining trained personnel in the absence of an outbreak is challenging. Therefore, they emphasized that the development of an epidemiological model of diseases can create career opportunities that might help retain talent.
- Centralized Repository for Diagnostics: Participants determined that diagnoses are impeded by the lack of data standardization and centralized collection. Therefore, they proposed that a centralized repository of standardized data to which all actors—including those in the nongovernmental sector—have incentives to provide data would significantly strengthen diagnostics. They underscored that this repository should contain genome sequences of pathogens and samples linked with the clinical histories of patients—without any personal identifiers—to identify, diagnose, and respond to diseases. As a result, they maintained that this repository can lend insight to disease epidemiology, pathogen evolution, infection trajectory, and help qualified laboratories perform and validate diagnoses. Participants added that this information should be available upon request for interested organizations, with some charges/fees, if necessary.
- Role of Scientists and Industry Experts: Participants underscored that a robust and effective technology ecosystem—from scientific innovation to commercialization—is needed to detect, understand, and respond to pandemics. They stated that while researchers can develop medical countermeasures for known pathogens, this can be scaled-up by industry experts to develop on-site diagnostic kits, vaccines, drugs, and other therapeutic options. India should also set aside funds to stockpile vaccines for rapid response to emergency outbreaks, participants added. However, some participants emphasized the need to focus on passive immunization—where antibodies are artificially introduced to a nonimmune individual—to protect against outbreaks as vaccination may take longer. Given the high mutation rates of viral pathogens, some participants also suggested developing broad spectrum antiviral drugs. Participants recognized that it is difficult to develop vaccines for flu prospectively. However, they emphasized the importance of creating a pipeline for vaccine development so that it can be generated rapidly in case there is an outbreak. Further, participants highlighted, for new epidemics by known or unknown pathogens, it is important to fast-track validation and accreditation mechanisms for point-of-care rapid diagnostic kits without compromising its safety.
This event summary was prepared by Shruti Sharma, a research analyst in the Technology and International Affairs Program at the Carnegie Endowment for International Peace.
List of Participants
- Gagandeep Kang, executive director, Translational Health Science and Technology Institute
- Frederik Kristensen, deputy chief executive officer, Coalition for Epidemic Preparedness Innovations
- Dipankar Nandi, professor, Department of Biochemistry, Indian Institute of Science
- Binay Panda, chief officer and head, Ganit Laboratory
- Chitra Pattabiraman, fellow, National Institute of Mental Health and Neurosciences
- George Perkovich, Ken Olivier and Angela Nomellini Chair and vice president for studies, Carnegie Endowment for International Peace
- S.R. Rao, former senior advisor, Department of Biotechnology, Ministry of Science & Technology
- Amrita Sekhar, consultant, Translational Health Science and Technology Institute
- Varsha Shridhar, director and cofounder, Molecular Solutions Care Health
- Rakesh Sood, distinguished fellow, Observer Research Foundation
- Varadharajan Sundaramurthy, group leader, National Centre for Biological Sciences
- Shashank Tripathi, assistant professor, Centre for Infectious Disease Research & intermediate fellow at Wellcome Trust India Alliance, Indian Institute of Science
