A large temperature fluctuation may trigger an epidemic erythromelalgia outbreak in China

Abstract

Although erythromelalgia (EM) has been documented in the literature for almost 150 years, it is still poorly understood. To overcome this limitation, we examined the spatial distribution of epidemic EM, and explored the association between temperature fluctuation and epidemic EM outbreaks in China. We searched all peer-reviewed literature on primary epidemic EM outbreaks in China. A two-stage model was used to characterize the relationship between temperature fluctuation and epidemic EM outbreaks. We observed that epidemic EM outbreaks were reported from 13 provinces during 1960–2014 and they mainly occurred between February and March in southern China. The majority of EM cases were middle school students, with a higher incidence rate in female and resident students. The major clinical characteristics of EM cases included burning, sharp, tingling and/or stinging pain in toes, soles and/or dorsum of feet, fever, erythema and swelling. A large “V”-shaped fluctuation of daily average temperature (TM) observed during the epidemic EM outbreaks was significantly associated with the number of daily EM cases (β = 1.22, 95%CI: 0.66 ~ 1.79), which indicated that this “V”-shaped fluctuation of TM probably triggered the epidemic EM outbreaks.

Early detection of an epidemic erythromelalgia outbreak using Baidu search data

“…Due to little attention to EM by the public, no mass media reported EM during this outbreak, which adds weight to the utility of Internet search data and how it reflects individual’s health concerns and issues 29 . However, epidemic EM have mainly occurred in students living in schools, which makes our results useful for extrapolating to a similar population rather than general population 14 .…”

“…Most epidemic EM outbreaks in China have been reported between February and March, coinciding with a V-shaped temperature change: namely a sharp temperature decline followed by a rapid temperature rise within a few days. Previous studies have hypothesized that these large temperature fluctuations that occur in South China are associated with epidemic EM outbreaks 6 7 8 11 12 13 14 . Furthermore, Liu et al 14 recently found that one degree Celsius increment of daily temperature might trigger an average rise of 1.22 EM cases in epidemic EM outbreak.…”

“…Previous studies have hypothesized that these large temperature fluctuations that occur in South China are associated with epidemic EM outbreaks 6 7 8 11 12 13 14 . Furthermore, Liu et al 14 recently found that one degree Celsius increment of daily temperature might trigger an average rise of 1.22 EM cases in epidemic EM outbreak. During February 2014, the temperature in Foshan City of Guangdong Province experienced a very large temperature fluctuation, accompanied by an epidemic EM outbreak in two high schools.…”

Predicting Infectious Disease Using Deep Learning and Big Data

“…There are also examples of infectious disease prediction based on environmental factors such as weather [34][35][36][37]. Previous studies have confirmed that weather data comprises a factor that has a great influence on the occurrence of infectious diseases [38][39][40]. Liang et al showed that rainfall and humidity are risk factors for a hemorrhagic fever with a renal syndrome [41].…”

Primary erythromelalgia – case report

“…Tham and Giles rapported that erythromelalgia is associated with a neuropathy of small fibers and primary vasculopathies, characterized by an intermittent increase of blood flow, hypoxia, and possibly shunts, with increase in local cellular metabolism [5]. Due to the hypothesis of shunts, substances that alter the distribution of skin blood flow can improve the cutaneous oxygenation and induce symptoms relief [6]. Aspirin, which inhibits platelet aggregation can quickly relief the secondary symptoms of coagulopathy.…”