Impact of meteorological factors on the spatiotemporal patterns of dengue fever incidence

Abstract

Dengue fever is one of the most widespread vector-borne diseases and has caused more than 50 million infections annually over the world. For the purposes of disease prevention and climate change health impact assessment, it is crucial to understand the weather-disease associations for dengue fever. This study investigated the nonlinear delayed impact of meteorological conditions on the spatiotemporal variations of dengue fever in southern Taiwan during 1998-2011. We present a novel integration of a distributed lag nonlinear model and Markov random fields to assess the nonlinear lagged effects of weather variables on temporal dynamics of dengue fever and to account for the geographical heterogeneity. This study identified the most significant meteorological measures to dengue fever variations, i.e., weekly minimum temperature, and the weekly maximum 24-hour rainfall, by obtaining the relative risk (RR) with respect to disease counts and a continuous 20-week lagged time. Results show that RR increased as minimum temperature increased, especially for the lagged period 5-18 weeks, and also suggest that the time to high disease risks can be decreased. Once the occurrence of maximum 24-hour rainfall is >50 mm, an associated increased RR lasted for up to 15 weeks. A temporary one-month decrease in the RR of dengue fever is noted following the extreme rain. In addition, the elevated incidence risk is identified in highly populated areas. Our results highlight the high nonlinearity of temporal lagged effects and magnitudes of temperature and rainfall on dengue fever epidemics. The results can be a practical reference for the early warning of dengue fever.

Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan

“…Precipitation can create potential habitats for the aquatic stage of mosquito development and affect their distribution. The non-linear effects of precipitation have been shown in many studies [11, 35, 61]. In Singapore, high precipitation also had a positive effect on dengue transmission at a lag of 5–20 weeks and a negative impact at lag of 1–4 weeks [62].…”

“…The weekly and monthly data for multiple climate parameters were averaged from the daily data, including mean temperature, maximum temperature, minimum temperature, precipitation, and relative humidity. Because the three temperature measurements are highly correlated, only minimum temperature is included in the analysis, which was considered a more important index in the previous study [35]. …”

A Spatial Hierarchical Analysis of the Temporal Influences of the El Niño-Southern Oscillation and Weather on Dengue in Kalutara District, Sri Lanka

“…This limitation was partly overcome because of the presence of a more uniform spatial pattern for temperature [63]. We found spatial correlation of 85% between our observational stations.…”

“…Many studies have identified an overall increased risk of dengue for rainfall and temperature at lag weeks 9–16 [21,61]. A two months lag period for rainfall was documented in other statistical and mathematical modelling studies [22,62,63]. The vectorial capacity of Aedes mosquitoes is highly dependent on temperature.…”

Does ambient temperature interact with air pollution to alter blood pressure? A repeated-measure study in healthy adults

“…However, temperature has several different measures (e.g. average, minimum and maximum), which have been commonly used in the assessment of health effects related to climate change [26], and which measure is more closely associated with BP changes has been unclear. In the present analysis, we were able to take into account three different temperature variables and found that daily minimum temperature may be a better exposure measure to capture the temperature effects on BP.…”