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Roles of Remote Sensing for Influenza Risk Prediction and Early Warning Roles of Remote Sensing for Influenza Risk Prediction and Early Warning

Richard Kiang, Radina Soebiyanto, Farida Adimi NASA Goddard Space Flight Center Richard Kiang, Radina Soebiyanto, Farida Adimi NASA Goddard Space Flight Center

GEO Health & Environment Community of Practice Workshop Centre National d’Études Spatiales (CNES) Paris, France, 27-29 July 2010 GEO Health & Environment Community of Practice Workshop Centre National d’Études Spatiales (CNES) Paris, France, 27-29 July 2010

Epidemic-prone acute respiratory diseases have no borders, and can be spread rapidly around the world. Global, coordinated surveillance & control efforts are essential. Epidemic-prone acute respiratory diseases have no borders, and can be spread rapidly around the world. Global, coordinated surveillance & control efforts are essential. 2003 SARS

Spread to 37 countries in weeks

2004 H5N1 Avian Influenza

Spread to 62 countries since 2004. There are still frequent outbreaks in Indonesia, Egypt, and some Southeast Asian countries.

2009 H1N1 Pandemic

Spread to 48 countries in a month despite heightened public awareness and substantial preventive and control efforts

Cilia being invaded by flu virus Source: National Geographic Source: CDC

hemaglutinin neuraminidase

Antigenic drift

mutations in HA & NA

Antigenic shift

novel genes through reassortment

Animals to humans

jumping across species

Seasonal epidemic

new strains continue to appear

Pandemics

e.g., 1918 H1N1 Spanish Flu, 1957 H2N2 Asian Flu, 1968 H3N2 Hong Kong Flu

Pandemic potentials

H5N1 Avian Flu, 2009 H1N1 “Swine Flu” pandemic

Genetic & Antigenic Variation Among Influenza Viruses Genetic & Antigenic Variation Among Influenza Viruses

First appeared in Hong Kong in 1996- 1997, HPAI has spread to approximately 60 countries. More than 250 million poultry were lost. Worldwide the mortality rate is 53%. Co-infection of human and avian influenza in humans may produce deadly strains of viruses through genetic reassortment. On average one major pandemic

• ccurred in each century. 90 years have

passed since the 1918 pandemic (0.675M deaths in the US, and 21-50M deaths worldwide).

H5N1 AI — THE PROBLEM H5N1 AI — THE PROBLEM

richard.kiang@nasa.gov

DISTRIBUTION OF H5N1 HUMAN CASES DISTRIBUTION OF H5N1 HUMAN CASES

Source: WHO. Cases from 2003 to June 19, 2008.

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Highly Pathogenic AI Cases Since January 2010 Highly Pathogenic AI Cases Since January 2010

FAO EMPRES FAO EMPRES

HUMANS POULTRY TRADE wild birds domestic birds ducks & geese

poultry, products, feed, waste, personnel, equipment

BIRD TRADE MIGRATORY BIRDS POULTRY

Sectors 1&2 Sectors 3&4

H5N1 TRANSMISSION PATHWAYS H5N1 TRANSMISSION PATHWAYS

LPAI spill over HPAI spill back

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human flu virus pandemic strain reassortment

?

Asia

43% thru poultry 14% thru mig. birds

Analysis of Global Spread of H5N1 through Phylogenetic Evidence, Poultry & Bird Trades, And Bird Migration Data Analysis of Global Spread of H5N1 through Phylogenetic Evidence, Poultry & Bird Trades, And Bird Migration Data

Africa

25% thru poultry 38% thru mig. birds

Europe

87% thru mig. birds

US

Most likely thru poultry to surrounding countries first, then thru migratory birds to US mainland

Source: Kilpatrick et al., PNAS 2006.

richard.kiang@nasa.gov

Objective 4 Objective 3 Objective 2 Objective 1

OBJECTIVES OBJECTIVES

Perform empirical AI outbreak risk analyses based on outbreak history, environmental parameters, and socio-economic factors. Identify spatiotemporal risk for AI outbreaks based on wetland distributions, prevalence of bird species, flyways of migratory birds, surface characteristics, and socioeconomic factors. Model the spread of AI virus from large commercial poultry farms to small and backyard farms under typical environmental and socioeconomic conditions. Model weekly influenza-like illness cases based on observed and forecast meteorological parameters for regions in the US and other tropical countries.

richard.kiang@nasa.gov

What environmental and socio-economical factors may contribute to highly pathogenic AI outbreaks?

Poultry Outbreaks, Human Cases, Wet Markets, And Distribution Centers Poultry Outbreaks, Human Cases, Wet Markets, And Distribution Centers

January – February 2006

Based on Media & Publicly Available Information

January – February 2006

Based on Media & Publicly Available Information

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Histograms of Distance from Neighborhoods With/without Outbreaks to Other Locations Histograms of Distance from Neighborhoods With/without Outbreaks to Other Locations Log (N+1) Log (N+1)

meters

What areas around wetlands may have higher risks for AI outbreaks?

NAMRU-2 Bird Surveillance Sites on Java

NAMRU-2 Bird Surveillance Study NAMRU-2 Bird Surveillance Study

The role of migratory birds in the spread of H5N1 remains under considerable debates. In Indonesia, migratory pathways are only known for shorebirds (East Asian-Australasian flyway) and migratory ducks and geese (East Asian & Central Asian flyways). 4067 birds comprising of 98 species and 23 genera were collected in 2006-2007. Most common birds: striated heron, common sandpiper, and domestic chicken.

6% 3% 14%

(continued) (continued) RNA was extracted from swabs; RT-PCR was conducted for H5N1 genes; antibodies was detected using hemagglutination inhibition and

• ther tests.

Species with the highest seropostive rates in each category are Muschovy duck (captive), striated heron (non-migratory) and Pacific golden plover (migratory). 16% of the captive birds (duck, swan, pigeon, etc.) showed H5N1 antibody. Infected captive birds can be asymptomatic. In Indonesia, the role of migratory birds in H5N1 transmission is limited.

ASTER False-Color, Google Earth And Land Use Maps Around Indramayu ASTER False-Color, Google Earth And Land Use Maps Around Indramayu

Supervised Classification Supervised Classification

EU’s & UK’s Practice: 3 km protection zone 10 km surveillance zone larger restricted zone

Buffer zones can be established to limit the spread

• f H5N1 around wetlands and the nearby farmlands

Buffer zones can be established to limit the spread

• f H5N1 around wetlands and the nearby farmlands

How do AI viruses spread on and off farms, within and across poultry sectors, and into the environment?

Densely Populated Sector I Poultry Production Area

Google Earth image

Detection of H5N1 Infection on a Poultry Farm Detection of H5N1 Infection on a Poultry Farm

Highly pathogenic AI infection on a poultry farm cannot be detected immediately. Some infected poultry may not look very sick. In a poultry house with 20,000 chickens, an infection of <1% may not be detected in a walkthrough. Using a SEIR model, it can be shown that it may take 4-5 days to detect an outbreak. Before an infection is detected, viruses continue to spread on farm and off farm, through service personnel, equipment, materials, and the poultry that have been shipped out.

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On-Farm and Off-Farm Spread of H5N1 On-Farm and Off-Farm Spread of H5N1

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Within and Across-Sector Spread of H5N1 Within and Across-Sector Spread of H5N1

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How does seasonality vary geographically? How is influenza transmission influenced by the environment? How can this be used for forecasting and pandemic early warning?

• Latitudinal variability in

influenza transmission pattern

• Experimental findings
• n the effect of

meteorological factors in influenza transmission, virus survivorship and host susceptibility

Viboud et al. (2006). PLoS Med 3(4):e89

Empirical Evidences of Environmental Influences On Influenza Transmissions Empirical Evidences of Environmental Influences On Influenza Transmissions

Hong Kong Hong Kong

Land surface temperature Air temperature Rainfall Relative humidity Dew point Evaporation Pressure Solar irradiance Sunshine hours Windspeed

Time series for environmental parameters and weekly seasonal influenza cases

Hong Kong Hong Kong

Training Prediction

Maricopa County, Arizona Maricopa County, Arizona

Land surface temperature Air temperature Rainfall Relative humidity Dew point Pressure Solar irradiance Windspeed

Time series for environmental parameters and weekly seasonal influenza cases

Maricopa County, Arizona Maricopa County, Arizona

Training Prediction

Time series for environmental parameters and weekly seasonal influenza cases

New York City New York City

Training Prediction

Epidemic-prone acute respiratory diseases have no borders, and can be spread rapidly around the world. Internationally coordinated surveillance & control efforts are

• essential. Better understanding of the influenza

seasonality and the environmental effects on transmission will help the global surveillance and control efforts. Epidemic-prone acute respiratory diseases have no borders, and can be spread rapidly around the world. Internationally coordinated surveillance & control efforts are

• essential. Better understanding of the influenza

seasonality and the environmental effects on transmission will help the global surveillance and control efforts.

Thank You!

richard.kiang@nasa.gov