Abstract
Purpose. This study aimed to evaluate climatic data, including mean temperature, relative humidity, and rainfall, and their association with malaria incidence throughout Thailand from 2012 to 2017. The correlation of climatic parameters including temperature, relative humidity, and rainfall in each province and the weekly malaria incidence was analyzed using Spearman's rank correlation. The results showed that the mean temperature correlated with malaria incidence (p value < 0.05) in 44 provinces in Thailand. These correlations were frequently found in the western and southern parts of Thailand. Relative humidity correlated with malaria incidence (p value < 0.05) in 35 provinces. These correlations were frequently found in the northern and northeastern parts of Thailand. Rainfall correlated with malaria incidence (p value < 0.05) in 38 provinces. These correlations were frequently found in the northern parts and some western parts of Thailand. The impacts of the mean temperature, relative humidity, and rainfall were observed frequently in specific provinces, including Chiang Mai, Chiang Rai, Trat, Kanchanaburi, Ubonratchathani, and Si Sa Ket. This is the first study to report areas where climatic data are associated with malaria incidence throughout Thailand from 2012 to 2017. These results can map out the climatic change process over time and across the country, which is the foundation for effective early warning systems for malaria, public health awareness campaigns, and the adoption of proper adaption measures that will help in malaria detection, diagnosis, and treatment.
Highlights
Climate changes are alternations in one or more climate variables, including temperature, relative humidity, rainfall, wind, and sunshine. ese changes may impact the survival and reproduction of vectors and the transmission of vectorborne diseases [1]
Climatic Data of ailand. e daily climatic data were derived from measurements of mean temperature, relative humidity, and rainfall from all weather stations across 77 provinces of ailand between 2012 and 2017. e climatic data were retrieved from the ai Meteorological Department. e climatic data included mean temperature (°C), relative humidity, and rainfall in all 77 provinces. e daily climatic data were transformed using Microsoft Office Excel (Microsoft Corporation, Redmond, VA, USA) to weekly climatic datasets to analyze with weekly malaria incidence data provided by the Bureau of Vector-Borne Diseases
An association between malaria incidence rates and climatic factors has been established. is study examined the impact of climatic variables, including mean temperature, relative humidity, and rainfall, on malaria incidence throughout 77 provinces in six regions of ailand
Summary
Climate changes are alternations in one or more climate variables, including temperature, relative humidity, rainfall, wind, and sunshine. ese changes may impact the survival and reproduction of vectors and the transmission of vectorborne diseases [1]. Climate changes are alternations in one or more climate variables, including temperature, relative humidity, rainfall, wind, and sunshine. Malaria, caused by Plasmodium spp., is one of the most climate-sensitive mosquito-borne diseases. Climate changes can directly affect malaria transmission by shifting the vector’s geographic range and increasing the reproductive and biting rates and by shortening Plasmodium spp. incubation period [2]. Because of the effect of the location and monsoons, ailand has a relatively high temperature and humidity all year-round, which is ideal for the reproduction of Anopheles mosquitoes. Exploring the relationships between climate change and malaria transmission in ailand is the first step in developing effective early warning systems for malaria because malaria has been endemic for more than 10 consecutive years in some areas of ailand. Exploring the relationships between climate change and malaria transmission in ailand is the first step in developing effective early warning systems for malaria because malaria has been endemic for more than 10 consecutive years in some areas of ailand. e objective of this study is to clarify the relationship between climate variables and malaria incidence dynamics throughout the 77 provinces of ailand between 2012 and 2017
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