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Associations between El Niño-Southern Oscillation (ENSO) and tuberculosis incidence in China: a nationwide study
Xiaopeng Qin1,2, Yizhang Xia3, Jiang Xue2
1Subcenter of the National Clinical Research Center for Infectious Diseases, HIV/AIDS Clinical Treatment Center of Guangxi (Nanning), The Fourth People's Hospital of Nanning, Nanning, Guangxi 530023, PR China.
Background:
Climate variability may influence tuberculosis (TB) burden, but associations between the El Niño-Southern Oscillation (ENSO) and TB incidence remain poorly characterized across China.
Objective:
To quantify associations of ENSO and meteorological factors with TB notification incidence and assess regional and age-specific heterogeneity.
Methods:
Monthly TB surveillance data from 31 provincial-level administrative divisions in mainland China during 2005-2020 were analyzed using quasi-Poisson regression with distributed lag nonlinear models. Meteorological variables were examined alongside ENSO, with adjustment for relevant environmental and socioeconomic covariates. Subgroup analyses were conducted by geographic region and age group.
Results:
ENSO-related associations emerged at approximately 9 months, peaked at 10 months, and persisted for about 3 months. At lag 9 months, strong El Niño and strong La Niña conditions were associated with higher TB notification incidence than neutral conditions, with relative risks (RRs) of 1.048 (95% CI, 1.007-1.091) and 1.058 (95% CI, 1.032-1.085), respectively. Temperature showed a U-shaped association with TB notification incidence. Relative humidity of 67-87% was associated with higher TB notification incidence, peaking at 81% (RR, 1.101; 95% CI, 1.063-1.140). Regional and age-stratified analyses indicated heterogeneous exposure-response patterns.
Conclusions:
ENSO and local meteorological factors were associated with TB notification incidence through nonlinear and delayed exposure-response patterns. Climate forecasts may provide supplementary information for climate-sensitive TB surveillance within the environmental dimension of One Health.
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