Reflections on IMED 2018, Vienna, Austria, November 2018
The International Meeting on Emerging Diseases and Surveillance (IMED) was attended by more than 700 frontline healthcare professionals, lab technicians, data scientists and policymakers from 90 countries, all with a wealth of knowledge and experience in infectious diseases, surveillance and outbreak management.
The meeting covered topics related to various emerging and re-emerging diseases such as MERS, Ebola, Nipah, Zika, Measles and Polio. The sessions also reflected the multisectoral approach needed to tackle emerging infectious diseases outbreaks.
We must take a one-health approach, engage in public-private partnerships, have strong surveillance systems, and strengthen the frontline workforce to prepare for and respond to epidemics and pandemics.
Disease surveillance in the digital era
Director of Worldpop Andrew Tatum delivered the first plenary session. He argued there is a strong need for reliable and accurate data on human population distribution and composition to help monitor and tackle outbreaks. The vast majority of population growth taking place in urban areas and low-income countries. But how can we measure population demographics, when there is a lack of national census or information recorded in some countries?
Haripriya Mukundarajan from Stanford University, showcased ABUZZ - a crowdsourced approach to surveillance, using mobile phones as mosquito sensors to capture the sound of their wings. Often viewed as the “Shazam” for mosquitoes, ABUZZ gets local citizens around the world, to capture the sound of mosquitoes through their mobile phones.
Modern mobile phones contain high-performance microphones which can capture the species-specific audio frequencies in sounds produced by the beating wings of mosquitoes. Through machine learning and neural networks, the audio recordings can be filtered based on their frequencies, providing species-specific identification. This innovative technological solution, allows anyone to participate in mosquito surveillance and data acquisition, potentially identifying infectious mosquitoes.
Both these talks highlighted how mobile technology and machine learning was revolutionising the way in which surveillance data is captured to predict disease outbreaks.
Frontline workforce development
Alongside healthcare workers from Ukraine, Georgia, India, Singapore, Sierra Leone, and Japan, I took part in a roundtable. Despite the diversity in backgrounds, one point remained unanimous; frontline healthcare workers need better guidance and tools to strengthen their ability to detect and manage infections.
This point was stressed by Hilary Bower, an Epidemiologist from UK Public Health Rapid Support Team and Assistant Professor of Infectious Disease Epidemiology at the London School of Hygiene and Tropical Medicine. She agreed that we are in an era where we have a vast amount of scientific knowledge, tools and innovations to help predict the next outbreak, however, we still need to focus on building the capacity of the frontline.
“The initial rate-limited factor in preventing the spread of infectious diseases is not the international outbreak response. It is the response at the “frontline”- in communities and countries at risk” Hilary Bower
She noted that it is at this level that we need to start the outbreak response, with the people who will be seeing the first case of an infectious disease. We need to ensure that they can recognise the problem and start the response right when they see it.
Strengthening the frontline requires training of healthcare professionals at the community and national level, a stockpile of supplies such as Personal Protective Equipment, scaling up of preparedness planning through national action plans, and participation from community members to help with case identification.
Where do we go from here?
The conference provided the opportunity to present a poster on behalf of BMJ on its flagship global health programme, the Clinical Decision Support (CDS) Training Initiative. The initiative supports frontline healthcare workers on infectious diseases and their differential diagnoses, by providing them access to BMJ Best Practice (an online clinical decision support tool) and BMJ Learning (an online interactive multimedia learning platform). The resources strengthen their ability to correctly detect, diagnose and manage infectious diseases and prevent wider spread of disease.
Competing Interests: I have read and understood the BMJ Group Conflicts of Interests Policy and Declare I do not have any conflicts of interests.
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