Maxent modeling for predicting the global potential distribution of talaromycosis marneffei
10.13604/j.cnki.46-1064/r.2023.01.02
- Author:
BAO Xiu-li
;
WEI Wu-di
;
HE Jin-hao
;
WANG Gang
;
CHEN Li-xiang
;
LIU Yu-xuan
;
JIANG Jun-jun
;
YE Li
;
LIANG Hao
- Publication Type:Journal Article
- Keywords:
Talaromycosis marneffei;
rhizomys;
Maxent model;
distribution prediction
- From:
China Tropical Medicine
2023;23(1):10-
- CountryChina
- Language:Chinese
-
Abstract:
Abstract: Objective To predict the potential distribution of talaromycosis marneffei (TSM) and analyze its driving factors, so as to provide evidence for the surveillance and prevention of this disease. Methods The data of all laboratory-confirmed, non-duplicating TSM published in the English and Chinese literature from the first case in January 1964 to December 2018 was collected. A Maxent ecology model using environmental variables, Rhizomys distribution and HIV/AIDS epidemic was developed to forecast ecological niche of TSM worldwide, as well as identify the driving factors. Results A total of 705 articles (477 in Chinese and 228 in English) were obtained during the study period. After excluding imported cases, a total of 100 foci information were included in the model. The area under the receiver operating characteristic (ROC) curve (AUC) of the model was 0.997 for the training set and 0.991 for the test set. Maxent model revealed that Rhizomys distribution, mean temperature of warmest quarter, precipitation of wettest month, HIV/AIDS epidemic and mean temperature of driest quarter were the top 5 important variables affecting TSM distribution. In addition to identifying traditional TSM endemic areas (South of the Yangtze River in China, Southeast Asian, North and Northeast India), other potential endemic areas were also identified, including parts of the North of the Yangtze River, Central America, West Coast of Africa, East Coast of South America, the Korean Peninsula and Japan. Conclusion Our finding has discovered hidden high-risk areas and provided insights about driving factors of TSM distribution, which will help inform surveillance strategies and improve the effectiveness of public health interventions against TM infections.
- Full text:2.Maxent modeling for predicting the global potential distribution of talaromycosis marneffei.pdf
