Research Entomologist
The El Niño/Southern Oscillation (ENSO) is a large-scale ocean-atmosphere phenomenon that involves a warming or cooling of sea surface temperature (SST) across the central and east-central equatorial Pacific Ocean. El Niño and La Niña, the warm and cold phases, respectively, of the ENSO cycle, impact human health across much of the world through increased risk of natural disasters, such as droughts, floods, and tropical cyclones. These in turn affect agricultural yields, cause air pollution due to landscape fires, and enable transmission of various infectious diseases
During the summer and fall of 2014 and winter of 2015, the US National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) issued an El Niño Watch. The most recent estimate of January 8, 2015 assessed an approximately 50-60% chance of El Niño developing during the next 2 months (Northern Hemisphere winter) and persisting into spring
Following a strong El Niño in 1997-1998, US Government organizations and international partners collaborated to initiate a climatological monitoring program as part of a global surveillance network for emerging infectious diseases
Detailed descriptions of the El Niño indicators and other climatological data used in our program are available elsewhere
SST in the NINO3.4 region (eastern equatorial Pacific Ocean; 5°N-5°S, 120°W-170°W), often used as an indicator of the phase and amplitude of ENSO events (El Niño is characterized by five consecutive 3-month running means of SST anomalies in the NINO3.4 region above +0.5°C). SST anomalies in the Western Indian Ocean (WIO); warmer NINO3.4 and WIO SSTs indicate a higher likelihood of El Niño. Global SSTs (1981-present). Outgoing Longwave Radiation (OLR; 1979-present), an indicator of cloudiness (Positive anomalies indicate warm, dry conditions; negative anomalies indicate cool, cloudy conditions and rainfall). Precipitation (Global Precipitation Climatology Project; 1979-present).
To identify regions at risk for El Niño-associated infectious disease activity, we used the literature review of Kovats et al.
SSTs in the NINO3.4 and WIO regions reached higher-than-normal temperatures in October 2014 (+0.49°C and +0.48°C, respectively, just below the +0.5°C threshold that must persist for an El Niño event to occur) after cooling during the summer.
The tongue-appearing pattern of the SST anomaly off the Peruvian coast, with SST anomalies ≈ +1.5°C along the equator, is typical of a developing El Niño event (Figure 1).
Above-normal SSTs persisted in the equatorial eastern Pacific Ocean along the equator (≈ +1.5°C) and in the equatorial Indian Ocean (≈ +0.5-1.0°C). The tongue-like structure of the SST anomaly off the Peruvian coast is typical of a developing El Nino event.
WIO warming (anomalies ≈ +0.5°C to +1.0°C) off the east African coast also is consistent with previous El Niño events. Anomalous positive SST in the eastern Pacific Ocean drives tropical and extra-tropical convective activity influencing global rainfall and temperature patterns.
The SST anomalies during August-October 2014 are comparable to those preceding the 2006-2007 El Niño, with more extreme elevations in the WIO and less extreme but positive and rising NINO3.4 elevations (Table 1).
2006
2014
WIO
NINO3.4
WIO
NINO3.4
August
+0.17
+0.40
-0.00
+0.20
September
+0.09
+0.62
+0.09
+0.45
October
+0.17
+0.78
+0.48
+0.49
Some impacts from the current SST anomaly patterns can be observed in the pattern of global convective activity illustrated by the OLR anomaly patterns. During August through October 2014, large positive departures (>+35 watts per meter squared [W/m2]) in OLR across Indonesia and coastal southeast Asia indicate drier than average conditions, while large negative departures (<-40 W/m2) across northern China, the western Indian Ocean, central Asia, north-central and northeast Africa, Mexico/Central America, the southwestern United States, and the northeastern and southwestern tropical Pacific suggest wetter than normal conditions (Figure 2).
Used to infer tropical precipitation, current OLR anomalies show very dry conditions (brown to red colors) across Indonesia and most of southeast Asia and enhanced precipitation across northern China, the western Indian Ocean, central Asia, north-central and northeast Africa, Mexico/Central America, the southwestern United States, and the northeastern and southwestern tropical Pacific.
Further details of current ENSO conditions are available on the Climate Prediction Center website
The dramatic shifts in large-scale convective centers around the global tropics during El Niño lead to extreme weather conditions, with above-normal rainfall and flooding in some regions and unusually high temperatures and drought conditions in others (Figure 3).
El Niño events are associated with extremes of elevated or depressed rainfall (blue/green or yellow/red, respectively).
Currently, several regions show extreme departures in rainfall, including southeast Asia, northeast Africa, Mexico/Central America, and the southwestern United States (Figure 4).
Departures in average rainfall coincide with Outgoing Longwave Radiation anomalies (Fig. 2).
Considering these typical El Niño effects on regional weather and the recent El Niño forecast, there is a high likelihood for drought conditions to prevail in southeast Asia, west-central and southern Africa, northeast Brazil, Ecuador, and Mexico during the next 5 to 8 months; as well as elevated rainfall and flooding in southwest Asia, eastern Africa, coastal Peru and Ecuador, much of the southern portion of South America, and the US southwest, including southern California.
The development of these conditions has important implications for global public health. For each of several diseases, including ones of high global health significance, multiple epidemiological studies have linked El Niño events with increased incidence in human populations (Table 2).
Disease
Region
Possible El Nino Effects on Disease Dynamics
Cholera
Warmer water temperatures promote bacteria proliferation; flooding causes contamination of water sources, and may increase susceptibility to infection via stress.
Dengue
Hantavirus infection
Elevated rainfall increases food availability for rodent reservoirs (vegetation), which expands rodent populations and may promote contact with humans.
Leishmaniasis
Warmer temperatures or dry conditions may favor sand fly vectors or contribute to waning human immunity (e.g., via malnutrition or temporarily suppressing disease transmission).
Malaria
Elevated rainfall promotes
Plague
Heavy rains increase food availability for populations of susceptible rodents; cooler temperatures may increase infectious flea abundance.
Rift Valley fever
Flooding of dry mosquito vector habitats promotes hatching of (transovarially-) infected eggs, and vector breeding and survival.
Respiratory illness
Drought may contribute to forest fires, which cause air pollution that may increase risk of respiratory infection.
Ross River virus disease
Warm conditions may increase mosquito vector longevity, and thereby vectorial capacity.
El Niño may impact dynamics of other diseases related to ones with demonstrated El Niño associations. For example, chikungunya virus shares vectors with dengue virus (
Based on these findings and considerations, we recommend enhanced surveillance and preparedness for specific geographic regions that may be at risk for El Niño-linked infectious disease activity during late 2014 through spring 2015 (Figure 5).
Based on current global climate anomaly conditions and forecasts, El Niño is likely to develop during late 2014 and persist into early 2015. The expected effects on regional weather patterns include persistent high temperatures and drought in some areas, and heavy rainfall and flooding in others. This may enhance populations of particular vectors and the transmission of various infectious diseases in human and animal populations.
Although local weather conditions mediate part of ENSO’s influence on infectious disease transmission (“teleconnections”), incorporating ENSO indicators into disease risk predictions offers advantages. ENSO forecasts typically can anticipate local weather effects several months before they manifest, providing lead-time for public health risk communication, enhancement of disease and vector surveillance programs, provisioning of clinical resources (for example, vaccines and diagnostics), and other preparedness measures. Also, a large-scale climate phenomenon such as ENSO may predict ecological processes better than weather-based models by integrating the effects of multiple weather variables that interact in complex ways
Our El Niño-based infectious disease risk assessment for coming months requires some caveats. The development of El Niño events cannot be predicted with complete certainty. However, we expect predictability to be higher for this near-term forecast (versus, for example, a 1-year-ahead forecast). Predictability even at longer lead-times has been favorable without a high false-alarm rate during 1857-2003
A limitation to ENSO-based infectious disease predictions is the complex relationship between ENSO the and dynamics of certain diseases. The relationship has been strong and consistent for some diseases, such as RVF in East Africa
Our observations do not attempt to predict disease outbreaks or even elevated transmission risk, but instead highlight the occurrence of current and future ENSO conditions that might influence environmental conditions that influence the dynamics of certain diseases (Table 2, Figure 5). The linkages we describe between climate and disease transmission are based on many years of observations of teleconnections between specific persistent weather/climate anomalies and specific vector-borne and water-borne disease outbreaks in specific regions.
We encourage public health organizations to take steps to mitigate El Niño impacts, such as increased incidence of infectious disease, in areas likely to be affected. While some measures are specific to certain diseases, preparations should include risk communication to the public and relevant sectors; vector and public health surveillance to detect increased disease activity; and planning for surge capacity to respond to increased disease activity. In particular, we emphasize the need for public health monitoring as El Niño develops to improve understanding of regional health effects and facilitate development of early warning systems.
The authors have declared that no competing interests exist.
We thank Drs. Rohit A. Chitale, Joel C. Gaydos, and Kevin L. Russell for supporting this effort. We also thank Dr. Robert Adler and Mathew Sapiano of the Cooperative Institute for Climate and Satellites (CICS), University of Maryland for providing the interim Global Precipitation Climatology Project (GPCP) rainfall data used in the manuscript. The views expressed are those of the authors and do not necessarily reflect those of any part of the US Government.