Water Freedom System

Survive Global Water Shortages

Get Instant Access


develop predictive models of infectious diseases that in turn will allow us to develop a preemptive medicine: that is, to mitigate the impact of infectious disease, if not to prevent it by having an early warning system to initiate appropriate and responsive public health measures.


Jean-Paul Chretien, M.D., Ph.D.3 Department of Defense

Assaf Anyamba, Ph.D.4 NASA Goddard Space Flight Center

Jennifer Small, M.A.4 NASA Goddard Space Flight Center

Compton J. Tucker, Ph.D.4 NASA Goddard Space Flight Center

Seth C. Britch, Ph.D.5 U.S. Department of Agriculture

Kenneth J. Linthicum, Ph.D.5 U.S. Department of Agriculture

As Earth's climate changes, the frequency and intensity of heat waves, droughts, floods, and other extreme weather events are expected to increase over large regions (IPCC, 2007b). Trends already are apparent, with regions affected by drought and the frequency of heavy precipitation that leads to flooding increasing since the 1950s (IPCC, 2007a). Besides obvious, direct effects on human health, extreme events can facilitate infectious disease epidemics—for example, through effects on disease vector ecology, infrastructure, and human behavior.

Satellite observations and modeling allow prediction of some extreme weather events and consequent infectious disease activity. In this paper, we use

2The views expressed in this paper are the private views of the authors and are not to be construed as official or representing the true views of the Department of Defense.

3Coordinator, Overseas Laboratories, Global Emerging Infections Surveillance & Response System, 2900 Linden Lane, Silver Spring, MD 20910; Phone: 301-319-9418; Fax: 301-319-9213; E-mail: Jean-Paul.Chretien @ us. army. mil.

4Biospheric Sciences Branch, Greenbelt, MD.

5Agricultural Research Service, Center for Medical, Agricultural, and Veterinary Entomology, Gainesville, FL.


satellite and epidemiological data to examine connections between the El Niño/ Southern Oscillation (ENSO) phenomenon and two recent mosquito-borne epidemics in Africa: Rift Valley fever (RVF) and chikungunya fever, which followed heavy rains and drought, respectively. These case studies suggest considerations in developing early warning systems for extreme weather-associated epidemics.

El Niño/Southern Oscillation and Rift Valley Fever Prediction

The ENSO is an irregular, but natural, feature of the global climate system. It results from interactions between the oceans and the atmosphere across the Indo-Pacific region and affects the weather around the world. In the warm, or El Niño, phase of the cycle, sea surface temperatures are warmer than usual in the eastern-central equatorial Pacific Ocean. El Niño sometimes is followed by a cool, or La Niña, phase with colder-than-usual temperatures in the eastern-central equatorial Pacific. The warm and cool phases cycle over irregular intervals of several years but have characteristic effects on precipitation and temperature throughout much of the tropics.

In areas where it influences climate, El Niño is associated with increased risk of some infectious diseases (Kovats et al., 2003). For example, in East Africa, El Niño is associated with flooding and RVF activity (Linthicum et al., 1999)—epizootics among economically important livestock, with humans infected incidentally by the mosquito vectors or by handling or consuming infected animal products. Outbreaks begin near natural depressions ("dambos") that harbor Aedes mosquito eggs infected directly by the parent during development. The eggs hatch with dambo flooding, producing an initial wave of RVF vectors; other species that transmit the virus emerge over subsequent weeks (Linthicum et al., 1984) and propagate the outbreak. The largest recorded RVF outbreak, in 1997-1998, coincided with a strong El Niño. There were an estimated 89,000 human infections and hundreds of deaths in northeastern Kenya and southern Somalia (CDC, 1998).

Following the 1997-1998 outbreak, scientists at the U.S. National Aeronautics and Space Administration Goddard Space Flight Center (NASA-GSFC) and the Department of Defense Global Emerging Infections Surveillance and Response System (DOD-GEIS) initiated a partnership to forecast conditions favorable for RVF activity in Africa by monitoring ENSO and other climatic phenomena. The program uses satellite data from ongoing NASA and NOAA climate and environmental observation programs to provide predictions of areas at elevated RVF risk. The primary data sets are sea surface temperature (SST), rainfall, outgoing longwave radiation (OLR; which is correlated with cloud cover and rainfall), and Normalized Difference Vegetation Index (NDVI; a key measure for identifying risk areas). NDVI is correlated with rainfall but integrates effects of other climatic parameters, responds most to sustained rather than intermittent rains, and is available globally since 1981, while ground-based rain gauge coverage is limited in Africa.


Updated forecasts are available monthly, or more frequently if conditions warrant, on the DOD-GEIS public website.6 Forecasts and alerts also are communicated to public health agencies that can act on them to enhance surveillance or community preparedness in at-risk areas. Important partners in responding to forecasts and alerts include the World Health Organization (WHO), Food and Agriculture Organization of the United Nations (FAO), the U.S. Centers for Disease Control and Prevention's (CDC's) International Emerging Infections Program in Kenya, and two members of the DOD-GEIS network: the U.S. Army Medical Research Unit-Kenya (USAMRU-K) in Nairobi and the U.S. Naval Medical Research Unit-3 (NAMRU-3) in Cairo.

Rift Valley Fever Outbreaks in East Africa, 2006-2007

In September 2006, the NASA-GSFC/DOD-GEIS monitoring program identified indications of an impending El Niño episode, with SSTs anomalously elevated in the central-eastern Pacific Ocean (+2°C) and the western Indian Ocean (+1°C) (see Figure 2-3). These conditions enhanced precipitation over these areas and the Horn of Africa through November (see Figure 2-4). Rainfall increased through December, with vegetation response (see Figure 2-5A) and conditions favorable for RVF activity in large areas of northeastern Kenya and nearby areas in Somalia and Ethiopia, as well as in southern Kenya and northern Tanzania (see Figure 2-5B).

The NASA-GSFC/DOD-GEIS program released a series of epidemic warnings based on these observations. In September 2006, it issued a global, regional-scale forecast covering late 2006-early 2007 for possible El Niño-linked outbreaks, including RVF in East Africa, to the DOD-GEIS network (these forecasts were published online in the International Journal of Health Geographies, an open access journal, in December; Anyamba et al., 2006). As rainfall increased in the Horn of Africa, the FAO Emergency Prevention System for Transboundary Animal Diseases issued an RVF alert for the Horn in November, identifying areas flagged as conducive to RVF activity (FAO, 2006). NASA-GSFC/DOD-GEIS also communicated with the WHO, which transmitted alerts to the countries at risk for RVF activity and called for enhanced surveillance and community awareness.

USAMRU-K, in coordination with Kenya Medical Research Institute (KEMRI) and CDC's International Emerging Infections Program (IEIP), deployed a field team in early December to assess high-risk areas in the Garissa district of northeastern Kenya (which was experiencing severe flooding). USAMRU-K tested mosquitoes collected by the team in Garissa and from established collection sites in other areas (see Figure 2-6), identifying RVF virus-infected mosquitoes from Garissa. The field team also investigated local reports of possible


Was this article helpful?

0 0

Post a comment