2013 Conference of the International Medical Geology Association (25–29 August 2013)

Paper No. 4
Presentation Time: 2:10 PM

PREDICTIVE AID FOR SEASONAL, AVIAN AND PANDEMIC INFLUENZA AND ACUTE RESPIRATORY INFECTIONS USING REMOTE SENSING DATA


KIANG, Richard, NASA Goddard Space Flight Center, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Mailing Code 610.2, Greenbelt, MD 20771 and SOEBIYANTO, Radina P., Goddard Earth Sciences Technology and Research, Universities Space Research Association, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Mailing Code 610.2, Greenbelt, MD 20771, richard.kiang@nasa.gov

Epidemic-prone acute respiratory diseases have no borders. Recent events such as SARS in 2003, avian influenza (HPAI H5N1) in 2005 and the “swine flu” (A(H1N1)pdm09) in 2009, have shown that such diseases can spread rapidly to many countries in spite of heightened awareness in the general public and strengthened public health surveillance and response. These experiences not only affirmed that global, coordinated surveillance and control efforts are essential, but they also called for predictive capabilities for disease outbreaks and spread to reduce human morbidity and mortality, and to lessen economic losses. The current outbreaks of MERS-CoV and avian A(H7N9) have brought new concerns for possible pandemics in the coming years.

We used Earth observation data (MODIS, TRMM and ASTER), climate model output (GLDAS), weather station data, as well as epidemiological and socioeconomic data, to model disease transmission and outbreaks. Various mathematical and statistical techniques were used, including ARIMA, neural network, Hilbert-Huang empirical decomposition, and Markov Chain Monte Carlo method. For influenza in temperate and subtropical climates (e.g. United States and Hong Kong), we have shown that temperature is the essential predictor while rainfall is an important one in the subtropics. For avian influenza in Indonesia, proximity to roads, rivers or wet market were found to be important risk factors.

The U.S. National Strategy for Pandemic Influenza developed by the White House Homeland Security Council consists of three pillars -- preparedness and communication, surveillance and detection, and response and containment. The capabilities we are developing contribute to all three. The White House Office of Science and Technology Policy National Biosurveillance Science and Technology Roadmap considers remote sensing the most suitable tool for identifying environmental and climatic precursors to infectious disease outbreaks. Hence our approach is consistent with the recommendations of the Roadmap.