Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China

Author:

Cheng Qu1,Jing Qinlong2,Collender Philip A.3,Head Jennifer R.4,Li Qi1,Yu Hailan1,Li Zhichao5,Ju Yang6,Chen Tianmu7,Wang Peng1,Cleary Eimear8,Lai Shengjie8

Affiliation:

1. Huazhong University of Science and Technology

2. Guangzhou Center for Disease Control and Prevention

3. University of California

4. University of California, Berkeley

5. Chinese Academy of Sciences

6. Nanjing University

7. Xiamen University

8. University of Southampton

Abstract

Abstract Background Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions. Methods In this study, we use a distributed lag non-linear model to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China, stratified by prior water availability. Results Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24–55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 (95% credible interval (CI): 1.02–1.83) occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7-121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43–0.79), occurring at a lag of 45 days. Conclusions These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.

Publisher

Research Square Platform LLC

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