Search

Background: Bangkok plays a central role in the commerce of Thailand. This study aimed to characterize the district-level spatial-temporal patterns of dengue in Thailand and explore if a dengue peak in Bangkok led the peaks of dengue in other Thai provinces. Methods: Monthly dengue data at district level in Thailand from January 2004 to December 2017 were obtained and used to assess the spatial and seasonal patterns of dengue in Thailand. As our seasonal decomposition and cross-correlation analyses showed that dengue in Bangkok peaked in November, which was a few months after the dengue peak in most other provinces, we used a time-series generalized linear model to explore if there was another province in which the dengue case number was most predictive of dengue case numbers in other Thai provinces. Results: The highest district-level annual dengue incidence rates (per 10,000) in the three time periods (i.e. 2004–2008, 2009–2013 and 2014–2017) were 58.08 (Samphanthawong), 85.93 (Mueang Krabi), and 66.60 (Mae Sariang), respectively. Dengue incidence rates in the western part of Northern Thailand, southern part of Central Thailand, southern part of Eastern Thailand, and Southern Thailand were higher than in other regions. Dengue in most districts of Thailand peaked in June, July or August, but dengue peaks in all districts of Bangkok occurred in November. The number of dengue cases in Nakhon Ratchasima was most predictive of the number of dengue cases in other provinces in Thailand by a one-month lag. Conclusions: Our results suggest that the dengue peak in Bangkok did not lead the peaks of dengue in other Thai provinces. Future research exploring how changes in socio-ecological factors (e.g. road network and climate factors) in Nakhon Ratchasima have affected the transmission of dengue in Thailand might shed some new light on the prevention and control of dengue. [ABSTRACT FROM AUTHOR]

Background: The mosquitoes Aedes aegypti and Ae. albopictus are the primary vectors of dengue virus, and their geographic distributions are predicted to expand further with economic development, and in response to climate change. We aimed to estimate the impact of future climate change on dengue transmission through the development of a Suitable Conditions Index (SCI), based on climatic variables known to support vectorial capacity. We calculated the SCI based on various climate change scenarios for six countries in the Asia-Pacific region (Australia, China, Indonesia, The Philippines, Thailand and Vietnam)., Methods: Monthly raster climate data (temperature and precipitation) were collected for the period January 2005 to December 2018 along with projected climate estimates for the years 2030, 2050 and 2070 using Representative Concentration Pathway (RCP) 4·5, 6·0 and 8·5 emissions scenarios. We defined suitable temperature ranges for dengue transmission of between 17·05-34·61 °C for Ae. aegypti and 15·84-31·51 °C for Ae. albopictus and then developed a historical and predicted SCI based on weather variability to measure the expected geographic limits of dengue vectorial capacity. Historical and projected SCI values were compared through difference maps for the six countries., Findings: Comparing different emission scenarios across all countries, we found that most South East Asian countries showed either a stable pattern of high suitability, or a potential decline in suitability for both vectors from 2030 to 2070, with a declining pattern particularly evident for Ae. albopictus. Temperate areas of both China and Australia showed a less stable pattern, with both moderate increases and decreases in suitability for each vector in different regions between 2030 and 2070., Interpretation: The SCI will be a useful index for forecasting potential dengue risk distributions in response to climate change, and independently of the effects of human activity. When considered alongside additional correlates of infection such as human population density and socioeconomic development indicators, the SCI could be used to develop an early warning system for dengue transmission., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objectives: The burden of dengue fever in Thailand is considerable, yet there are few large-scale studies exploring the drivers of transmission. This study aimed to investigate the spatiotemporal patterns and climatic drivers of severe dengue in Thailand., Methods: Geographic Information System (GIS) techniques and spatial cluster analysis were used to visualize the spatial distribution and detect high-risk clusters of severe dengue in 76 provinces of Thailand from January 1999 to December 2014. The seasonal patterns of severe dengue cases in different provinces were identified. A two-stage modelling approach combining a generalized linear model with a distributed lag non-linear model was used to quantify the effects of monthly mean temperature and relative humidity on the occurrence of severe dengue cases in 51 provinces of Thailand., Results: Significant severe dengue clustering was detected, especially during epidemic years, and the location of these clusters showed substantial inter-annual variation. Severe dengue cases in Northern and Northeastern Thailand peaked in June to August and this pattern was stable across the study period, whereas the seasonality of severe dengue cases in other regions (especially Central Thailand) was less predictable. The risk of the occurrence of severe dengue cases increased with an increase in mean temperature in Northeastern Thailand, Central Thailand, and Southern Thailand, with peaks occurring between 24 °C to 30 °C in Northeastern Thailand and 27 °C to 29 °C in Southern Thailand West Coast, respectively. Relative humidity significantly affected the occurrence of severe dengue cases in Northeastern and Central Thailand, with optimal ranges observed for each region., Conclusions: Our findings substantiate the potential for developing climate-based dengue early warning systems for Thailand, and have implications for informing pre-emptive vector control., (Copyright © 2018 Elsevier B.V. All rights reserved.)