Is climate a primary driver of Vietnam’s dengue, or a shared long-term trend? A five-method analysis over 36 years

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Abstract Background Vietnam’s reported dengue burden has risen roughly five-fold since 1990. Multi-decadal studies linking climate indices to dengue rarely separate genuine year-to-year coupling from a long-term trend the two share. Methods We assembled a provenance-preserving national annual dengue series (1990-2025; OpenDengue plus Ministry of Health figures) and correlated it with annual and March-May means of eight tropical sea surface temperature (SST) indices at lags of zero and one year under five trend-correction lenses: raw, linear detrending, first-differencing, socio-demographic-index residualisation and AR(1) prewhitening. Findings Cases rose 3·5 percent annually. Seven predictors were significant at zero lag, led by the annual Indian Ocean Basin-Wide index (IOBW; Spearman +0·534), but linear detrending removed all. First-differencing preserved six, led by spring IOBW (+0·468), the annual Atlantic Multidecadal Oscillation (AMO; +0·462) and annual IOBW (+0·423); three survived AR(1) prewhitening - annual AMO and annual and spring IOBW. Spring AMO and a lag-1 Tropical North Atlantic signal (−0·452) did not, and are hypothesis-generating. El Niño-Southern Oscillation indices failed throughout. Interpretation Most of the apparent association reflects a trend shared by warming oceans and expanding surveillance; we could not demonstrate that climate is the primary driver at this scale. Trend is not the whole story: IOBW and annual AMO persist under trend- and persistence-removing transformations. Because transmission responds to climate over weeks to months, annual averaging smooths the lags through which El Niño acts; these nulls reflect temporal scale, not climate insensitivity; usable predictors will require monthly, province-level models. Funding Center for Environmental Intelligence, VinUniversity (project VUNI.CEI.FS_0001). Research in context Evidence before this study We searched PubMed, Web of Science and Google Scholar for studies published up to May 2026 linking large-scale climate indices or sea surface temperature to dengue incidence, combining dengue, climate, sea surface temperature, ENSO, teleconnection and time-series terms with Vietnam, without language restriction. Many studies covering two or more decades reported strong correlations between basin-scale indices and national dengue counts. Most, however, relied on raw correlations or a single detrending choice, and rarely tested whether an apparent association reflected genuine year-to-year coupling or merely a shared long-term trend. Added value of this study Most long-term studies remove the shared upward trend in only one way, or not at all. To our knowledge this is the first study to compare five trend-correction methods on a multi-decadal national dengue record and to read their agreement or disagreement as a diagnostic of which climate signals are real. A signal that appears only before the trend is removed is probably following it; one that persists is more likely real. Applied to a record spanning more than three decades, this comparison separates the two: several widely reported raw correlations weakened once the shared trend was accounted for. Implications of all the available evidence Climate-informed analyses of multi-decadal data should report at least two trend-correction approaches alongside the raw correlation and treat their disagreement as evidence about where a signal sits, rather than operationalising raw long-span correlations. For Vietnam, the apparent national-scale association is dominated by a shared long-term trend but retains a smaller, robust inter-annual component led by the Indian Ocean and AMO signals; genuine coupling is more likely detectable at monthly resolution and provincial scale, where statistical power and physical mechanism are jointly available. Surveillance systems should retain explicit source provenance, so trend-corrected re-analysis remains possible as records grow.

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