Effects of the El Niño-southern oscillation on dengue epidemics in Thailand, 1996-2005

Abstract

Background: Despite intensive vector control efforts, dengue epidemics continue to occur throughout Southeast Asia in multi-annual cycles. Weather is considered an important factor in these cycles, but the extent to which the El Niño-Southern Oscillation (ENSO) is a driving force behind dengue epidemics remains unclear.

Methods: We examined the temporal relationship between El Niño and the occurrence of dengue epidemics, and constructed Poisson autoregressive models for incidences of dengue cases. Global ENSO records, dengue surveillance data, and local meteorological data in two geographically diverse regions in Thailand (the tropical southern coastal region and the northern inland mountainous region) were analyzed.

Results: The strength of El Niño was consistently a predictor for the occurrence of dengue epidemics throughout time lags from 1 to 11 months in the two selected regions of Thailand. Up to 22% (in 8 northern inland mountainous provinces) and 15% (in 5 southern tropical coastal provinces) of the variation in the monthly incidence of dengue cases were attributable to global ENSO cycles. Province-level predictive models were fitted using 1996-2004 data and validated with out-of-fit data from 2005. The multivariate ENSO index was an independent predictor in 10 of the 13 studied provinces.

Conclusion: El Niño is one of the important driving forces for dengue epidemics across the geographically diverse regions of Thailand; however, spatial heterogeneity in the effect exists. The effects of El Niño should be taken into account in future epidemic forecasting for public health preparedness.

Figure 1

Study regions. Study regions and the Gulf of Thailand (A and B). The five provinces (C) in the coastal region and the eight provinces (D) in the northern inland region are numbered. Townships in the coastal region are shown as green spots.

Figure 2

Local meteorological data, 1996-2005. Monthly average daily mean temperature (Temp) (red line, units: degrees Fahrenheit) and monthly average daily relative humidity (Rh) (blue line, units: percentage) in (1) Petchaburi; (2) Prachuap Khirikhan; (3) Chumpon; (4) Surat thani; (5) Nakhon Sithammarat; (6) Chaingmail; (7) Lamphun; (8) Lamphang; (9) Phrae; (10) Nan; (11) Phayao; (12) Chaingrai; and (13) Maehongson.

Figure 3

Dengue surveillance data, 1996-2005. Monthly incidence of reported dengue cases per 100,000 population in (1) Petchaburi; (2) Prachuap Khirikhan; (3) Chumpon; (4) Surat Thani; (5) Nakhon Sithammarat; (6) Chaingmail; (7) Lamphun; (8) Lamphang; (9) Phrae; (10) Nan; (11) Phayao; (12) Chaingrai; and (13) Maehongson. The red dashed line indicates the 10-year-mean in each province.

Figure 4

El Niño Southern Oscillation (ENSO) data, 1996-2005. The monthly multivariate ENSO index (MEI) (red line with rectangles) and the anomalies of the sea level pressure index (SLP) (blue line with bars). MEI > 1 (or SLP < -1) defines the occurrence of El Niño. A more positive value of MEI (or a more negative value of SLP) indicates a stronger El Niño.

Figure 5

Observed (1996-2005), fitted (1996-2004), and forecasted (2005) monthly incidence of reported dengue cases. Observed (blue line, 1996-2005), fitted (red line, 1996-2004), and forecasted (green line, 2005) monthly incidence of reported dengue cases. (1) Petchaburi; (2) Prachuap Khirikhan; (3) Chumpon; (4) Surat thani; (5) Nakhon Sithammarat; (6) Chaingmail; (7) Lamphun; (8) Lamphang; (9) Phrae; (10) Nan; (11) Phayao; (12) Chaingrai; (13) Maehongson.