**5. ENSO and Health-Sensitive Climate Impacts**

In most conceptualisations of climate and health links, the variables of rainfall and temperature dominate as climate drivers of hypothesised and actual health outcomes. Further, an often unstated assumption in many analyses of the relationship between ENSO and disease is that ENSO "signals" will be found in disease incidence time series. While this might be self-evident, the way in which this axiom is applied is often naïve. This is because ENSO forcing of adverse health outcomes is usually explored without prior investigation of the extent to which a disease-relevant climate variable, such as rainfall or temperature, is ENSO sensitive for a specific location, region, or time period.

There is no doubt that ENSO has a marked impact on climate fields, with this impact being geographically and seasonally dependent. Given this, graphics of ENSO climate-related impacts (Figures 7 and 8) should be useful indicators of where direct ENSO/climate-driven (rainfall/temperature) variations in disease might occur. In effect, such canonical patterns, as appear in El Niño and La Niña composites (Figures 7 and 8), should assist with identifying potential ENSO -health "hotspots". However, having said that, an essential in the approach to any ENSO-health study informed by canonical patterns of health-sensitive climate impacts is the recognition that ENSO composites of rainfall and temperature patterns are only averages (the climatology) and as such mask much El Niño/La Niña inter-event variability in climate impacts. For example, and beyond the broad **EL NIÑO CLIMATE IMPACTS**

central Pacific (CP–"Modoki") and eastern Pacific (EP) ENSO types, Johnson [48] identified nine different "flavours" of ENSO; a distinct climate outcome is associated with each one. Paek et al. [49] also highlight that no two ENSO events are the same, and provide a useful analysis of the differences of the strong 1997–1998 and 2015–2016 El Niño events. It is perhaps no surprise that some ENSO-health studies do not find consistent temporal or spatial ENSO-health associations, as the "strength" of climate forcing may vary from ENSO event to event, both temporally and geographically. Although there have been no systematic studies of the way in which different flavours of ENSO might manifest in variable regional or local ENSO-health associations, the contrasting rainfall fields for El Niño and El Niño-Modoki events hint at potential temporal and spatial inconsistencies of ENSO-health associations (Figure 9). For example, in El Niño-Modoki events not only is the degree of departure of rainfall from the long-term mean weak, but the spatial pattern of both positive and negative rainfall anomalies is fragmented and somewhat different, and for some regions opposite (e.g., equatorial South America, equatorial eastern Pacific) when compared to El Niño events (Figure 9). The implications for ENSO-health studies of such contrasting climate responses for different ENSO types is clear, especially if an ENSO index that does not discriminate between ENSO types is applied bluntly to the analysis of disease incidence time series.

**Figure 7.** Canonical climate impact patterns of El Niño for (**a**) December–February and (**b**) June–August. Sourced and redrawn from the Climate Predicition Centre http://www.cpc.ncep.noaa.gov/products/ analysis\_monitoring/ensostuff/ensofaq.shtml#GLOBALimpacts.

**Figure 8.** Canonical climate impact patterns of La Niña for (**a**) December–February and (**b**) June–August. Sourced and redrawn from the Climate Predicition Centre http://www.cpc.ncep.noaa.gov/products/ analysis\_monitoring/ensostuff/ensofaq.shtml#GLOBALimpacts.

**Figure 9.** *Cont*.

**Figure 9.** Rainfall anomalies for (**a**) El Niño and (**b**) El Niño Modoki events. Sourced and redrawn from Japan Agency for Marine, Earth Science and Technology. http://www.jamstec.go.jp/frcgc/research/ d1/iod/enmodoki\_home\_s.html.en.
