Sari Kovats

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Sari Kovats

• Centre on Global Change and Health (CGH)
• London School of Hygiene and Tropical Medicine,
  UK
• Wednesday 1st October 2003

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Discovery of El Niño

• 1860s First recorded use of term "El Niño" in
  Peru to describe periodic warming of coastal
  waters
• 1910-1930s Gilbert Walker documents the Southern
  Oscillation and its linkages with the Asian
  monsoon
• 1960s Jacob Jerkiness links El Niño in Pacific
  Ocean with Southern Oscillation in the
  atmosphere.
• 1981/82 First international efforts to reduce the
  impact of El Niño and improve forecasting
• 1985-87 First global climate models to simulate
  ENSO
• 1997 UN Interagency Task Force on El Niño
  established.
• 1997 Many models successfully forecast the onset
  of El Niño but fail to forecast its magnitude

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La Niña
El Niño
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El Niño events

• Year Year
• 18991900 Very strong 1951
• 190203 Strong 1953
• 190506 195758
• 191315 Strong (1963) immature event
• 191820 Strong 1965
• 192324 (1969) immature event
• 192526 197273 Strong
• 193031 197677
• 193233 (1979) immature event
• 193940 198283 Very strong
• 194041 Very strong 198788 Strong
• 194142 199194 3 Separate events?
• 194647 199798 Very strong
• 2002-03

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El Nino and Australia
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ENSO studies use a variety of parameters

• Climate station data
• temperature, precipitation, humidity
• limited spatial coverage
• El Niño or La Niña years
• Sea surface temperatures (SST) in the Pacific.
• SST anomalies are defined as deviations for a
  specified region from the averaged climate for
  19611990 (WMO).
• Southern Oscillation Index (SOI).
• simple index, defined as the normalized pressure
  difference between Tahiti, French Polynesia, and
  Darwin, Australia,
• Multivariate ENSO Index (MEI)

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• Literature review Kovats et al. Lancet, 2003.
  online.
• Criteria for inclusion.
• Published in peer reviewed journal
• Original research article using epidemiological
  data.
• Quantified any association with an ENSO parameter
  (e.g. El Niño year, SST, SOI or other index).
• The outcome was an infectious disease in humans.
• The time series included more than one El Niño
  event.

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Malaria - published times series studies (to 2002)
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Recommendations for conducting and reporting ENSO
and health studies

• Test and report results of association between
  weather parameters and ENSO parameter in the
  data.
• Report published assessments of ENSO
  teleconnections by climatologists in region of
  interest
• Describe the geographical area from which the
  health data are derived.
• Test and report results of association between
  weather parameters and disease outcome
• Use time series with more than one ENSO event
• Remove any trend and seasonal patterns in the
  time-series prior to assessing relationships
• Report associations both with and without
  adjustment for autocorrelation

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Hantavirus pulmonary syndrome emerging disease
in USA

• Rodent populations are reservoirs for
  hantaviruses.
• Hantavirus pulmonary syndrome (HPS) first
  detected in early 1990s in USA when.
• Above-average precipitation during winter/spring
  of 19921993 Engelthaler et al.. EID, 1999, 5
  8794.
• increased rodents populations
• and thereby increased contact between rodents and
  humans
• viral transmission.
• El Niño in 1997/98, rodent numbers (Peromyscus
  spp.) in this region increased 10 to 20-fold. A
  significant increase in reported cases of HPS was
  also reported.

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Total number affected by weather
disastersEm-dat database
El Niño years
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Disasters

• In an average El Niño year, around 35 per 1000
  persons are reported to be affected by a natural
  disaster. This is over four times greater than
  the rate in non-El Niño years
• El Niños global disaster footprint is largely
  determined by the consequences of drought .
• Every El Niño since at least 1982 has been
  associated with fires in Kalimantan, with
  consequent public health implications .
• During El Nino, intense rains and flooding
  caused hundreds of deaths in Peru, Colombia,
  Ecuador and Bolivia.
• Hurricanes in the Caribbean, the Gulf of Mexico,
  and off the coast of northern Australia are less
  common during El Niño, but more common during La
  Niña

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Weaknesses

• Need to identify correct climate driver
• Biological mechanisms not clear
• Alternative explanations, e.g. cyclical changes
  in immunity
• need to adjust for autocorrelation?
• Limited data series -
• need more than 1 event..
• Most appropriate geographical aggregation
• Disease data is of uncertain quality (and may not
  be disease-specific)

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What El Niño can tell us about the impacts of
global climate change on communicable diseases

• Climate variability can be important driver of
  year to year variation in disease.
• driven by precipitation
• Insight into effects not evident at local scales
• rainfall, predator balance
• Effects of increased frequency of ENSO events
  under climate change
• Adaptation to climate change
• epidemic prediction using seasonal forecasts

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What El Niño cannot tell us

• Cannot directly assess effects of progressive
  warming from direct extrapolation of ENSO-health
  relationships
• precipitation is main driver via changes in
  vector-abundance
• Rate of change greater in ENSO
• Magnitude of temperature change greater in ENSO

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summary

• At the global scale, the impact of natural
  disasters increases during El Niño.
• The effect of ENSO on the risk of malaria
  epidemics has been well established in parts of
  South Asia and South America.
• The evidence for an effect is weaker for other
  mosquito-borne and rodent-borne diseases, and for
  cholera in coastal regions.
• The strongest evidence for an association between
  ENSO and disease is provided by time series
  analysis over more than one event.