Now I'm going to give some examples that pull together syndrome and event-based surveillance. ProMED is a system whereby all different events that are happening around the world can be reported into the system. It catalogs them and allows people to review them to assess whether there are trends or whether there are infections or events of international concern to that particular viewer. Health Map is another example where in partnership with proMED and other sources, it maps out each of these cases to allow people to evaluate whether there is a clustering of those cases and again the relevance of those cases to one's own jurisdiction. Another example is Bio Diaspora, and Bio Diaspora takes this idea of localization one step further by looking at travel patterns. Here we can see travel patterns over time from 2000 to 2012 from Hong Kong. We can see the most common cities where people from Hong Kong fly around the world. What we can see was around SARS. There was a rapid decline in the numbers of people coming in and out of Hong Kong because SARS was a public health emergency of international concern. But it also allowed people in cities around the world to assess the numbers of people who had flown in from Hong Kong at that time to assess the risks of SARS transmission. Notably in Toronto is a common place where people from Hong Kong fly and was a place that was really affected by the SARS outbreak that same year. The Bio Diaspora system can take this one step further. In preparation for the Vancouver Olympics, it was able to map out the numbers of people flying to Vancouver from different cities around the world and also what outbreaks were happening in those settings at that time. So as an example, we can see that in Orlando there was outbreaks of XDR or Extensively Drug Resistant Tuberculosis. It was about 3,200 passengers that were flying to Vancouver during that time. In Seoul Korea, there was Oseltamivir or Tamiflu resistant H1N1 and about 5,500 passengers flying to Vancouver during that time. Then in London there was over 10,000 passengers with ongoing outbreaks of Measles in London at the time. So it really facilitates an evaluation of what might be risks and what should public health professionals in Vancouver be looking for as they're doing their public health operation. Bio Diaspora has now been integrated into Blue Dot. One can see here the different types of data that are being integrated into the Blue Dot system to provide public health practitioners, security practitioners, travelers insights into outbreaks that may be happening. Many of these are consistent with the types of inputs that we've talked about including infectious disease outbreaks at hospitals and health care facilities, local mobility, livestock populations, mosquitoes and ticks, animal infectious diseases, population demographics, global flight ticket sales and real-time climate changes. Another example is epidemicIQ which also is looking to integrate many of these different data sources into functional tools that can be used to predict where outbreaks may happen. Finally, there's the electronic surveillance system that is implemented and supported in partnership between the Johns Hopkins Applied Physics Lab and the military. This is called the Electronic Surveillance System for Early Notification of Community-Based Epidemics or ESSENCE. In ESSENCE too in the national capital region, you can see the sources are very consistent with the types of sources we've talked about. Absenteeism, hospital emergency department visits, medications, visits to physicians, diagnostic laboratory tests. All of these are being integrated both in terms of volume as well as specific diagnoses along with pharmacy sales, try service health care for visits, hot line calls. All of these comes together to provide inputs to public health surveillance professionals and personnel, to provide inputs to whether there are emerging outbreaks happening. Here we are looking at a schematic that summarizes the different types of data inputs and the types of delays that one might expect associated with each of these. If we look at the first exposure, if there are biological sensors for example to a nuclear attack, it is the biological sensors that will first detect those. So as an example when you walk into conferences or concerts these days you might actually walk through a biological sensor looking for nuclear material. When you boarded a plane lately, you've gone through sensors that are looking for radioactive material. After that, there's an incubation period for when somebody starts having symptoms. That requires either surveillance of the citizens or people self-assessing that they're having symptoms related to exposure. After that, we rely on healthcare behaviors. Are people seeking health care? Are people missing school? After that we rely on how people are seeking information. As we've talked about web click streams. Are people buying groceries? Are people going out and buying over the counter or receiving prescription medications? Are people missing school or work and are there increased numbers of calls that are coming into triage phone line? After that, requires engagement with the health care system, either in the context of physician or allied health professionals. People phoning emergency medical services or 911, visiting emergency department or being hospitalized. After that, we're relying on the types of tests that might be associated with those visits, the laboratory tests as well as we've talked about radiological tests including X-rays. After that, we rely on the types of diagnoses that are made. Then finally, we are talking about confirmed diagnosis. So as you can see, confirmed diagnosis are the most sensitive and specific approach. But there's a lot of these types of data inputs that we can use that will really address some of the delays and facilitate earlier responses. The limitations that we've talked about are important. It really has to be the right presentation for the system to work. If there are hundreds of thousands of cases that are happening simultaneously you don't need a special detection system, it'll be in the news. But in the anthrax attacks of 2001, the best syndromic surveillance system likely would not have picked it up because it was so sporadic. So it really highlights the use of an event-based surveillance system to highlight when something as serious as an anthrax attack happens. There's a lot of false positives and I gave some examples of them. Each of those false positives are associated with significant money and time to respond to and sometimes people, and the public in general, can get desensitized to real events. It's important to effectively integrate these systems within existing public health systems. Importantly, it really only sets off alarms and you have to have a system in place in order to confirm and then effectively respond to any of these systems.
