Are Epidemic Early Warnings, Really “Early” Warnings?


Information technological innovations seem to have played quite an important role in detecting early warnings of the current “new flu”, “swine flu” or H1N1.  This topic is elaborated in today’s issue of New York Times. Apparently, WHO received the first warning already on April 10th through its web-crawler based monitoring system. This again proves the usefulness of mining unofficial data for monitoring.

One point missing in the debate however, is the fact that other emerging and re-emerging infectious diseases (EIDs) – such as avian influenza (H5N1), Ebola hemorrhagic fever, and West Nile viral encephalitis – emerge not only as the result of changes in host dynamics or in the pathogen. On the contrary, a range of underlying social- ecological changes such as land use change, deforestation and biodiversity loss seem to contribute to the rise of EIDs globally. Durell Kapan and colleagues article on the social-ecological dimensions of avian influenza is a nice synthesis of how land-use change contributes to increases in H5N1.

So, even if ICT innovations such as Google Flu or GPHIN provide the first signals of pending epidemic outbreaks, they are really not designed to capture changes in underlying social-ecological interactions that induce EIDs. For example, if you want to predict novel outbreaks of Hantavirus pulmonary syndrome (HPS) in Brazil, you might want to keep an eye on deforestation patterns and increases in sugarcane production. Or if you want to stay ahead of increasing risks of Ebola hemorrhagic fever outbreaks in Central West Africa, you might want to track coastal fish stock decrease in the region. These are known to increase “bush-meat” hunting and hence the risk of Ebola outbreaks.

The question is what to call such a system. If field epidemiologist Nathan Wolfe is doing early warning, maybe this approach should be called ecological “early-early warning”?

4 thoughts on “Are Epidemic Early Warnings, Really “Early” Warnings?”

  1. The critical question is whether the ecological data is sufficiently accurate to provide better forewarning than guessing – neither the bush-meat nor hantavirus examples above actually compare ecological signals with subsequent outbreak frequency, although the mechanisms are plausible. Other than not travelling there – what could you do about an imminent outbreak? Maybe the connections aren’t strong enough to trigger preventative action ‘on the ground’, but operate at a larger hierarchical level to modify policy about food availability and land use.

    Ecologically early is earlier than epidemiologically early!

  2. Environmental changes such as deforestation and biodiversity loss associated with outbreaks of some diseases are relatively “slow variables” compared with disease outbreaks themselves. It is unlikely that there are environmental indicators with sufficient sensitivity to act as effective early warning mechanisms for disease. However, disease outbreaks can be considered as an effective indicator of slow variable stress in vertebrates and their habitats. We can expect the frequency of disease outbreaks to increase as ecosystems are stressed by human use and poverty among people increases.

  3. I think the science of predicting early outbreaks of viral disease is a necessity and should continue to expand. We can, as this article points out, look to all sorts of early warning signs. If this is what a Field Epidemiologist does, I would consider it quite important work. At least as important as any other scientist predicting natural disaster. Preparation sometimes is all we can do. Once a disease like Ebola is loose it’s too late. The fatality rate can be 90%. If we know there is going to be a high risk area we can start to send medical supplies to that area or cleanup the area that could be infected with that type of mosquito, as is the usual carrier.

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