Typhus group rickettsiosis, which is a neglected vector-borne infectious disease, including epidemic typhus and endemic typhus, is caused by Rickettsia prowazekii and Rickettsia typhi, respectively [1]. Epidemic typhus or louse-borne typhus, is usually transmitted through the human body louse [2]. Endemic typhus or murine or flea-borne typhus, is usually transmitted by fleas. The main transmission cycle is rat-fleas, and other transmission cycles, including fleas from opossums, dogs, and cats, are reported worldwide [3,4,5]. Rare epidemic typhus outbreaks have been reported during past several decades. However, murine typhus is widely distributed around the world. The incubation period for murine typhus is 8 to 12 days. Murine typhus could be a self-limiting clinical presentation with mild symptoms, such as fever, headache, exanthema, muscle pain, joint pain and vomiting [6]. However, sometimes murine typhus may cause severe complications if the diagnosis and treatment are not timely [7]. In recent years, many regions have reported murine typhus cases with severe complications, such as pneumonia, pancreatitis, and septic shock [8,9,10]. There are only a few regions still monitor murine typhus, such as Texas, Hawaii, California and Taiwan [7, 11]. Moreover, murine typhus poses a threat to the health of travelers, and travel destinations primarily locate in Southeast Asia, Africa and America [12].
TGR has been reported as a Class C notifiable communicable disease which should be reported within 24 h after being diagnosed in China. It was reported that the main type of TGR in China was endemic typhus, and the main vector was Xenopsylla cheopis [13,14,15]. TGR is widely distributed in mainland China with a total of 29,211 TGR cases located in 29 provinces and 795 counties from 2005 to 2017. Among the cases, there were 9129 cases in Xishuangbanna Dai autonomous prefecture of Yunnan province, accounting for 31.25% of all cases in China. The annual incidence here ranged from 105.87 in 2011 to 10.67 in 2017 per 100,000 individuals, greater more than the average incidence in China (0.16/100,000). According to the precious study, under suitable climate conditions, Xenopsylla cheopis had a survival period of 377 days, and an average life span of 172.4 days. The optimum growth temperature was 23 °C, and at this temperature, the breeding cycle was generally 20 to 44 days [16]. The possible routes of transmission are flea bites, contamination of excoriated skin, and inhalation of contaminated aerosols [5]. According to our previous study, we found that TGR was sensitive to the climate, and most cases occurred from May to October. Meteorological factors may affect TGR incidence both directly and indirectly by affecting vector ecology, vector–human interactions, and bacterial reproduction. Li et al. used Pearson correlation analysis to analyze the correlation between meteorological factors and TGR incidence from 2005 to 2013 in Baoshan city, Yunnan province. They concluded that temperature and precipitation were closely related to TGR incidence [17]. However, the study neglected the nonlinear relationship and lag effects between meteorological factors and TGR incidence.
Distributed lag non-linear models (DLNMs) represent a modeling framework to flexibly describe associations showing potentially nonlinear and delayed effects in time series data. This methodology rests on the definition of a crossbasis, a bi-dimensional functional space expressed by the combination of two sets of basis functions, which specify the relationships in the dimensions of predictor and lags, respectively [18]. DLNMs have been widely used to analyze air pollution on years of life lost, mortality, hospital admissions and so on [19,20,21]. Furthermore, in recent years, DLNMs have been applied to study association between meteorological factors and communicable diseases, for example, dengue, hand, foot and mouth disease, severe fever with thrombocytopenia syndrome (SFTS) [22,23,24]. In detail, Sun et al. found a reversed U-shaped nonlinear relationship between ambient temperature and SFTS [24]. However, no study has been conducted to study the association between meteorological factors and TGR incidence. Therefore, we used DLNM to explore the temporal lag association between meteorological factors and TGR incidence. Results can be used as an early warning for public health authorities, and have a better understanding of TGR ecology.