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Family resources and externalizing problem behaviors among "lads" in township junior high schools: the role of positive youth development and peers' positive moral character.

Authors: Gao S, Xie M
Journal: Frontiers in psychology
mental health psychology open access

Abstract

Scrub typhus is an acute endemic infectious disease caused by and transmitted via the bites of trombiculid mite larvae. It is highly prevalent throughout the Asia-Pacific region, particularly in Southeast Asia. Its endemic coverage spans eastward to Japan, westward to Afghanistan, southeastward to northern Australia, and northeastward to the coastal Russian Far East, forming the well-recognized “scrub typhus” (; ; ). In China, following the reinstatement of the national direct reporting system for notifiable infectious diseases in 2006, the incidence of scrub typhus has been steadily rising, accompanied by a progressive expansion of its epidemic geographical coverage (; ). As of now, except for Shanghai and the Ningxia Hui Autonomous Region, a total of 30 provinces, autonomous regions, and municipalities nationwide have reported indigenous cases, with Yunnan, Guangdong, and Fujian being high-incidence areas (; ; ). Following infection with , the incubation period typically lasts 5 to 14 days. Typical clinical manifestations consist of fever, rash, pathognomonic eschars or ulcers, headache, myalgia, cough, lymphadenopathy and hepatosplenomegaly (; ; ). Severe cases are prone to multisystem complications, including toxic hepatitis, acute kidney injury, pneumonia, acute respiratory distress syndrome (ARDS), myocarditis, meningitis, encephalitis, septic shock and multiple organ failure (; ; ). In the absence of timely and effective treatment, the case fatality rate can reach 14.3% to 70% (; ). Guangdong Province represents a historically high-burden region of scrub typhus, with a marked upward trend in notified incidence over recent years (; ). A proportion of patients may progress to severe scrub typhus as a result of delayed diagnosis and clinical intervention, which underscores the clinical value of early recognition of severe cases. Alongside the rapid advancement of artificial intelligence, machine learning algorithms have been extensively utilized in disease prediction and auxiliary diagnosis, benefiting from their superior performance in multi-dimensional data analysis, pattern identification and predictive visualization (; ; ).