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Re-emergence of scrub typhus in Zhejiang Province, southern China: A 45-year population-based surveillance study
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Re-emergence of scrub typhus in Zhejiang Province, southern China: A 45year population-based surveillance study Jiangping Rena,b,c,1, Jimin Suna,b,1, Zhengting Wanga, Feng Linga,b, Xuguang Shia, Rong Zhanga, Ying Liua, Zhiping Chena,∗∗,2, Enfu Chena,b,∗,2 a
Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Hangzhou, China c Field Epidemiology Training Program of Zhejiang Province, Hangzhou, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Scrub typhus Epidemiology Seasonality China
Background: Scrub typhus is the leading cause of treatable unidentified febrile illnesses in Southeast Asia. This study was conducted to document the epidemiological characteristics of scrub typhus and its change in Zhejiang, one of traditional epidemic provinces in China. Methods: Scrub typhus surveillance data in Zhejiang province during 1957–1989 and 2006–2012 were obtained. Descriptive analysis was conducted to characterize the epidemiology of scrub typhus. The spatial distributions over the periods were explored using spatial autocorrelation analysis and spatiotemporal cluster analysis. Results: A total of 4104 cases and 7 deaths were reported from 1957 to 1989 and 2006 to 2017. The incidence declined since 1959, remained low from 1967 to 1989, and then exponentially increased after 2006. The seasonality changed from a summer pattern between 1957 and 1989 to a bimodal peak pattern in July to August and October to November from 2006 to 2017. One primary and three secondary high-risk clusters were affirmed in both periods from 1980 to 1989 and 2006 to 2017. The primary cluster expanded southwestward and the time span of the secondary clusters extended in the later period compared to the clusters in the previous time frame. Conclusion: Zhejiang recently underwent a seasonality change, geographic extension, and incidence increase in scrub typhus. More attention should be paid to controlling scrub typhus.
1. Introduction Scrub typhus, also known as bush typhus, is a mite-borne rickettsial zoonosis caused by the organism Orientia tsutsugamushi. It is the leading cause of treatable unidentified febrile illnesses in Southeast Asia. Humans occasionally become infected after being bitten by an infected chigger (the larval stage of a mite). Both rodents and mites are the natural reservoir hosts. The clinical spectrum varies from mild fever to multi-organ dysfunction [1]. It was considered as a lethal disease in the pre-antibiotic era and is militarily important, causing enormous losses during World War II and the Vietnam War. Early diagnosis and the timely use of antibiotics are quite important. The median untreatable mortality is 6%, with a range of 0%–70% [2]. Traditionally, scrub typhus is epidemic in the region called the “Tsutsugamushi Triangle,” which covers more than 8 million km2, from
the Russian Far East in the north to Pakistan in the west, Australia in the south, and Japan in the east [3]. It is estimated that one billion people are at risk of infection and one million morbidity occur annually in this region [3]. Recent evidence from the Arabian Peninsula, Chile, and Kenya indicated a potentially wider global distribution in tropical and subtropical regions [4–7]. Published reports from countries in the traditional “Tsutsugamushi Triangle” indicated an increase in scrub typhus cases over the past 10 years [8–11]. The drivers of the diffusion and reemergence are believed to include but are not limited to globalization, climate change, urbanization, and expansion of humans into previously uninhabited areas [3,8,12,13]. As Zhejiang is a traditional epidemic province in China, studies of scrub typhus in the area are limited. Therefore, we conducted this retrospective analysis to depict the profile of scrub typhus in Zhejiang and to provide the basis for further study and disease control.
∗
Corresponding author. 3399 Binsheng Road, Binjiang District, Hangzhou, China. Corresponding author. 3399 Binsheng Road, Binjiang District, Hangzhou, China. E-mail addresses: [email protected], [email protected] (Z. Chen), [email protected] (E. Chen). 1 Jiangping Ren and Jimin Sun contributed equally to this article. 2 Zhiping Chen and Enfu Chen contributed equally to this article. ∗∗
https://doi.org/10.1016/j.tmaid.2019.05.013 Received 28 June 2018; Received in revised form 17 May 2019; Accepted 20 May 2019 1477-8939/ © 2019 Published by Elsevier Ltd.
Please cite this article as: Jiangping Ren, et al., Travel Medicine and Infectious Disease, https://doi.org/10.1016/j.tmaid.2019.05.013
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2. Methods
2.4. Spatial autocorrelation analysis
2.1. Ethics statement
Spatial autocorrelation analysis was used to evaluate the spatial patterns. Global spatial autocorrelation is a measure of the overall clustering of the data. Several different statistics can identify the degree of autocorrelation, and Moran's I is the most frequently used. It ranges from −1 to +1, with negative values indicating dispersed patterns, positive values indicating clustered patterns, and zero indicating random spatial patterns. For statistical hypothesis testing, Moran's I values can be transformed to Z scores and P values, with an absolute Z score value > 1.65 and P value < 0.1 indicating significantly spatial autocorrelation. Global spatial autocorrelation analysis can be used to identify the overall distribution, but it cannot describe the local spatial patterns. However, local indicators of spatial association (LISA) can address this issue with local Moran's I and its Z score and P value. A high positive Z score and P value < 0.05 indicated spatial clusters (high-high: region with a high incidence surrounded by high incidences or low-low: region with a low incidence surrounded by low incidences). A negative Z score and P value < 0.05 indicates spatial outliers (highlow: region with a high incidence surrounded by low incidences, or low-high: region with a low incidence surrounded by high incidences). ArcGIS software (version 10.0.0) was used to conduct the spatial autocorrelation analysis.
Scrub typhus was incorporated into the Chinese notifiable disease monitoring system in 1957, but excluded between 1990 and 2005 due to its low incidence. As an important part of ongoing public health surveillance, the collection and analysis of data on notifiable infectious diseases by public health workers in charge of risk assessment and policy proposals are exempt from institutional review board assessment. It is authorized by the Law of the People's Republic of China on the Prevention and Treatment of Infectious Diseases. All of the collected data were supplied anonymously and no individual identifying information was provided. 2.2. Data collection and management Provincial surveillance data regarding scrub typhus between 1957 and 1989 were collected from a compilation of epidemiological data in Zhejiang province that were in the archives of the Zhejiang Provincial Center for Disease Control and Prevention. Demographic information, such as gender, age, occupation, and address, was not included, and there was no information regarding the geographical distribution in the surveillance data from 1957 to 1979. All of the surveillance data between 2006 and 2017 were retrieved from the China Information System for Disease Control and Prevention, which was established in 2004. It included basic demographic and clinical information reported by physicians. The annual demographic data of the counties in Zhejiang from 2006 to 2017 were obtained from Zhejiang's provincial Bureau of Statistics (http://tjj.zj.gov.cn/), and the data from 1957 to 1989 were from the Comprehensive Statistical Data and Materials on 50 Years of New Zhejiang [14].
2.5. Spatiotemporal cluster analysis SaTScan software (version 9.1.1) was used to detect the space-time clusters of scrub typhus and verified whether or not the clustering was caused by random variations. Circular scan windows and discrete Poisson models were used to scan the high rate areas with monthly units. Likelihood ratio tests were evaluated to determine the significance of the identified clusters and P values were obtained through Monte Carlo simulations after 999 replications. The null hypothesis of a spatiotemporally random distribution was rejected when the P value was < 0.05.
2.3. Descriptive epidemiology
3. Results
The epidemiological characteristics of scrub typhus cases in Zhejiang province were analyzed with R software (version 3.3.2) and WPS Office software. The data were divided into three periods: period one (1957–1979), period two (1980–1989), and period three (2006–2017). As no related data were obtained, the demographic characteristic analysis was not conducted during periods one and two, and the spatial distribution analysis was not included in period one. The chi-squared test, t-test, Kruskal-Wallis test, and linear models were employed to explore the profile of scrub typhus in Zhejiang province. The null hypothesis was rejected when the P value was < 0.05.
3.1. Temporal distribution A total of 4104 cases were diagnosed from 1957 to 1989 and from 2006 to 2017. The annualized average incidence during the study period was 2.3 per million, with the highest annual incidence reported in 1959 (10.0 per million) and the lowest in 2006 (0.2 per million, Fig. 1). Seven deaths were reported and the overall mortality was 0.2%. The incidence fell starting in 1959, remained low from 1967 to 1989
Fig. 1. The annual distribution of scrub typhus cases from 1957 to 1989 and from 2006 to 2017 in Zhejiang province, China. 2
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Fig. 2. The monthly distribution of scrub typhus cases during three different periods in Zhejiang province, China.
Chun'an (19.4 per million), and Xinchang (16.1 per million) ranked as the top five (Fig. 3).
and from 2006 to 2013, and then increased dramatically. Overall, 2104 cases and 7 deaths were reported during period one (from 1957 to 1979), with an annualized average incidence of 2.9 per million and a mortality rate of 0.3%. The vast majority of cases (93.2%) occurred between June and October and marked peaks were noted in July and August (Fig. 2). Overall, 570 cases and no deaths were reported during period two (from 1980 to 1989). The incidence of scrub typhus remained relatively low during this period, and the annualized average incidence (1.4 per million) was half of that in period one. The highest annual incidence was reported in 1989 (2.6 per million) and the lowest in 1981 (0.6 per million). Similar to the seasonal patterns in period one, 81.6% of cases were reported from July to October, and an incidence peak was observed in July and August (Fig. 2). A total of 1430 scrub typhus cases were reported during period three (from 2006 to 2017), with an annualized average incidence of 2.2 per million, and no deaths were confirmed. The annual incidence ranged from 0.2 per million (in 2006) to 5.3 per million (in 2017) and exponentially increased as a whole (R2 = 0.9, P < 0.01, log(y) = 0.3x602.4, Fig. 1). The seasonal patterns during period three were different from those in periods one and two. Two peaks were noted. The main peak was from July to August with 37.1% cases, and the minor peak covered October and November with 28.7% of reported cases (Fig. 2).
3.3. Spatial autocorrelation analysis of scrub typhus The global spatial autocorrelation analysis at the county level indicated that the geographical distribution of scrub typhus in Zhejiang was clustered as a whole in periods two (I = 0.05, Z = 1.76, P = 0.079) and three (I = 0.218, Z = 3.425, P = 0.001). Two high-high clusters were identified through LISA at the county level in period two, and five in period three. Compared to the clusters in period two, the high-high clusters between 2006 and 2017 moved from the south to the central and southwest part of the province, and the covered area significantly increased (Fig. 4). 3.4. Spatiotemporal clusters of scrub typhus One primary (cluster one) and three secondary (clusters two to four) high-risk clusters were scanned though space-time statistical analysis in period two (Fig. 3). The primary cluster included 173 cases and one county in southern Zhejiang from June 1984 to November 1988 (RR = 133.8, LLR = 641.4, P < 0.01). Clusters two, three, and four were located in middle and mideast Zhejiang from July to November 1989 (46 cases, RR = 22.50, LLR = 97.42, P < 0.01), southeastern Zhejiang from June to August 1980 (18 cases, RR = 75.48, LLR = 59.78, P < 0.01), and northwestern Zhejiang from June to October 1987 (6 cases, RR = 24.20, LLR = 13.34, P = 0.04), respectively. Four high-risk clusters (one primary and three secondary) were identified during period three (Fig. 3). The primary cluster was centered at 27.6 N, 119.1 E with a radius of 129.3 km and contained 13 counties and 435 cases in the southwest of the province from June 2016 to December 2017 (RR = 10.29, LLR = 555.05, P < 0.01). The three secondary clusters were situated in the center (358 cases, RR = 8.84, LLR = 421.30, P < 0.01), west (68 cases, RR = 27.82, LLR = 159.05, P < 0.01), and south (11 cases RR = 10.33, LLR = 15.72, P < 0.01) of the province. In comparison, the primary cluster expanded southwestward and the time span of three secondary clusters was longer in period three.
3.2. Spatial distribution Seven of the 11 prefecture cities reported scrub typhus cases from 1980 to 1989. No cases were diagnosed in northern and northeast Zhejiang (Ningbo, Jiaxing, Huzhou, and Zhoushan). Lishui (14.8 per million), Jinhua (3.7 per million), and Taizhou (0.7 per million) were the three prefecture cities with the highest annualized average incidence. Approximately one-third of counties (32.4%) reported cases during this period. Lishui (93.0 per million), Dongyang (10.2 per million), Yongkang (9.5 per million), Qingtian (9.0 per million), and Tiantai (5.3 per million) reported the highest annualized average incidence rates at the county level (Fig. 3). All of the 11 prefecture cities reported scrub typhus during period three. The annualized average incidence in Lishui (12.0 per million), Jinhua (6.0 per million), and Wenzhou (3.3 per million) ranked as the top three, while Jiaxing (0.1 per million) reported the lowest incidence. More than three-quarters of the counties were affected during 2006 and 2017, and the annualized average incidence in Qingyuan (37.0 per million), Pan'an (33.8 per million), Longquan (30.2 per million),
3.5. Demographic characteristics Females were reported slightly more frequently (male-female sex 3
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Fig. 3. The spatiotemporal clusters overlaid with the average annual incidence of scrub typhus between 1980 and 1989 (panel A) and 2006–2017 (panel B) in Zhejiang province, China.
4. Discussion
ratio: 0.9:1) and their incidence was higher than among males (2.3 per million vs 2.0 per million, Table 1). The overall mean age was 53.7 years (range: 7 months to 92 years). The age distribution varied significantly across different years (χ2 = 29.9, P < 0.01, Fig. 5) and genders (51.5 vs 55.7, t = −4.73, P < 0.01). The incidence also varied with age. Those aged 60–70 were reported to have the highest incidence (7.9 per million), followed by the 70–80 (5.4 per million) and 50–60 age groups (4.2 per million). The lowest incidence was reported in those aged between 10 and 20 (0.3 per million). Although females were more susceptible to scrub typhus as a whole, the incidence among those younger than 40 was higher in males than in females, while the trend reversed for populations older than 40. Most of the cases were farmers (76.01%). The distribution of occupation varied by gender (χ2 = 73.74, P < 0.01), with farmers (74.0%), workers (7.1%), and students (2.8%) as the three most frequently reported occupations for males, and farmers (77.9%), unemployed or homemakers (8.2%), and workers (3.9%) for females.
As an emerging and re-emerging disease with unspecific clinical manifestations, scrub typhus has been neglected and often misdiagnosed. No scrub typhus vaccine is available at present. Deratization and mite control can stop the transmission fundamentally, but it is usually difficult. Prevention strategies include avoiding unnecessary exposure, aggressive efforts to eliminate chigger breeding areas by weeding, and recommendations for personal protective measures, including preventing chigger bites by applying insect repellent, wearing long-sleeved shirts and long pants, and risk communication and community mobilization. Antibiotics such as doxycycline, azithromycin, and chloramphenicol are the treatments of choice for scrub typhus. A meta-analysis conducted by Fang [15] indicated that, compared to azithromycin and chloramphenicol, doxycycline acted more quickly for scrub typhus treatment, but had more adverse drug events. Since 1957, when scrub typhus was included in the Chinese notifiable disease monitoring system, the number of annually reported cases was approximately 1000 before 1986 in China, and then rose to > 2000 between 1986 and 1989 [16]. The annual incidence in Zhejiang
Fig. 4. Local indicators of spatial association (LISA) cluster maps for the average annual scrub typhus incidence from 1980 to 1989 (panel A) and from 2006 to 2017 (panel B) in Zhejiang province, China. 4
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Table 1 The character of scrub typhus cases in Zhejiang province during 2006 and 2017. Index
Male
Female
Total
Statistic
Mean age
51.52 (50.21,52.83)
55.69 (54.56,56.82)
53.69 (52.82,54.56)
t = −4.727,P < 0.001
0.9087 0.3614 0.5531 1.1042 2.0653 3.7247 6.6596 5.0451 2.0990 2.0445 508 (73.94%) 49 (7.13%) 8 (1.16%) 19 (2.77%) 14 (2.04%) 15 (2.18%) 12 (1.75%) 9 (1.31%) 9 (1.31%) 8 (1.16%) 17 (2.47%) 19 (2.77%) 47 (6.80%) 310 (45.10%) 273 (39.70%) 57 (8.30%)
0.6412 0.2441 0.5091 0.4975 2.1077 4.7740 9.1604 5.6925 3.6481 2.3252 579 (77.93%) 29 (3.90%) 61 (8.21%) 6 (0.81%) 14 (1.88%) 3 (0.40%) 5 (0.67%) 3 (0.40%) 4 (0.54%) 3 (0.40%) 14 (1.88%) 22 (2.96%) 48 (6.50%) 366 (49.30%) 288 (38.80%) 41 (5.50%)
0.7836 0.3054 0.5317 0.8084 2.0861 4.2353 7.8869 5.3676 2.9730 2.2429 1087 (76.01%) 78 (5.45%) 69 (4.83%) 25 (1.75%) 28 (1.96%) 18 (1.26%) 17 (1.19%) 12 (0.84%) 13 (0.91%) 11 (0.77%) 31 (2.17%) 41 (2.87%) 95 (6.60%) 676 (47.30%) 561 (39.20%) 98 (6.90%)
__
Incidence (per million)
Occupation
Seasonality
0–10 10–20 20–30 30–40 40–50 50–60 60–70 70–80 ≥80 Total Farmer Worker Unemployed Or Housework Student Scattered Children Retiree Cadre Commercial Service Childcare Children Migrant Worker Else Unclear Spring (Mar to May) Summer (Jun to Aug) Autumn (Sep to Nov) Winter (Dec to Feb)
χ2 = 29.859 P = 0.002
χ2 = 5.478 P = 0.140
Fig. 5. The age distribution of scrub typhus cases between different years from 2006 to 2017 in Zhejiang province, China.
identified between late October and early November, and lower latitudes were associated with a later peak incidence in South Korea [18]. A study conducted by Zhang et al. [16] concluded that there were four different seasonal patterns for scrub typhus in China: summer, winter, autumn-winter, and annually. The seasonality in south of the Yangtze River had a summer pattern, while it had an autumn-winter pattern in north of the river. The results of this study verified the seasonality change in scrub typhus in Zhejiang province, which is located in south of the Yangtze River. There was only one seasonal peak in summer between 1959 and 1989, while the seasonality changed between 2006 and 2017. Dual peaks were noted, including a major peak from July to August and a senior peak from October to November. Other provinces in south of the Yangtze River also underwent seasonal changes. The majority of cases occurred between June and October in Fujian province from 2006 to 2013 and in Jiangxi province between 2006 and 2012 [19,20]. Bimodal peaks were noted in Guangdong province, including one between June and July and another between September
province peaked in 1959, declined, and remained relatively low between 1967 and 1989. No increase was noted in Zhejiang between 1986 and 1989. The reason for the increase at the national level during this period might be related to the regional expansion in China after 1985 [17]. Before 1986, scrub typhus was limited to south of the Yangtze River, from Zhejiang and Hunan in the north to Yunnan and Sichuan in the west, Hainan in the south, and Taiwan in the east. However, the regional distribution has expanded northward since then. Until 2014, all of the provinces in China except Qinghai reported scrub typhus cases [8]. Studies conducted in countries from the traditional “Tsutsugamushi Triangle” after 2000 indicated an increase in the incidence of scrub typhus, and China, in particular, experienced an exponential increase starting in 2006 [3,8]. Similar to the whole of China, the incidence in Zhejiang also exponentially increased between 2006 and 2017. The seasonal pattern of scrub typhus changed with the geography, environment, and climate. The majority of cases occurred in spring to early summer in Yamagata Prefecture, Japan [12]. Most cases were
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change, geographic extension, and incidence increase in recent years. Although the exponential increase in the incidence as a whole started after 2006, scrub typhus has always been neglected by the health care sector and local government in Zhejiang. Limited resources have been provided and no systemic measures have been conducted on disease control. The high-risk population, senior farmers, are relatively low income and poorly educated. Targeted strategies and measures, such as health education and environmental management, should be undertaken immediately. Further research should also be conducted to understand the reason for these changes.
and October [21]. Park et al. [22] believed that the seasonal pattern was influenced by the vector cycles. Leptotrombidium scutellare, one scrub typhus vector, only feeds on human tissue fluid in autumn. L. pallidum, another scrub typhus vector, feeds in both autumn and spring [22]. This suggests that the seasonality change in south of the Yangtze River may be related to changes in the vector distribution. Mirroring the Chinese mainland and worldwide trends, Zhejiang has undergone a geographic extension of scrub typhus since 2006. The high-risk areas moved from the south to the central and southwest of the province. It is believed that the temporal and spatial distributions of scrub typhus are largely dependent on the distribution, activity, and abundance of the vectors and reservoirs. Wei et al. [23] indicated that a 1% increase in rodent density was associated with a 2.4% increase in the odds of scrub typhus cases after a 5-month lag in Guangzhou, southeastern China. Studies conducted in Japan, South Korea, and south and north China indicated that climate was an important influence on the epidemic of scrub typhus [12,23–27]. Meteorological factors, such as the temperature, duration of sunshine, rainfall, relative humidity, atmospheric pressure, and snowfall, were related to the incidence of scrub typhus. No related study was conducted in Zhejiang. However, the trend in temperature was in line with that of scrub typhus incidence in Zhejiang. The temperature increased as a whole in Zhejiang between 1951 and 2013, and can be divided into three phases: rose slightly without high fluctuations between 1951 and 1966, was relatively low from 1967 to 1989, and rose significantly between 1990 and 2013 [28]. Chiggers might indicate the connection between climate change and the incidence of scrub typhus. Chiggers are mainly located in grassy fields, gardens, parks, forests, bush, and moist areas around lakes or rivers, and their distribution is influenced by the humidity, temperature, and sunshine [29]. Changes in production and lifestyle also had an effect on the epidemic of vector-borne diseases. Kuo et al. [13] believed that farm abandonment (including abandonment of rice paddies) and periodic plowing in Taiwan increased the risk of spotted fever and scrub typhus because the mean tick and chigger loads were significantly higher in fallow plots than in plowed plots. Ticks and chiggers exhibit very low survival rates in flooded rice paddies, and periodic plowing can unintentionally mitigate vector burdens. Another study conducted in Taiwan indicated that the scrub typhus incidence was significantly positively correlated with the proportion of land that contained mosaics of cropland and vegetation [30]. Due to the success of hybrid rice by Yuan Longping and agricultural modernization, riceseeded areas have decreased significantly with the higher percentage of periodic plowing, and farm abandonment has become common in Zhejiang, a traditional rice-producing province. In addition, urbanization, globalization, and more eco-friendly surroundings are also important drivers of the emergence and re-emergence of vector-borne diseases as humans have more opportunities to come into contact with vectors including chiggers [31,32]. Inconsistent with surveys conducted in Korea, Japan, India, and other provinces in China, senior farmers were a high-risk population in Zhejiang province [10,33–35]. Females were more susceptible as a whole, and males were more likely to be infected in populations aged under 40. A study conducted in Guangdong province, China, indicated similar demographic characteristics to scrub typhus [36]. Females were also reported as the more susceptible gender in Korea, Japan, and Jiangsu and Fujian provinces in China [10,19,35,37,38]. However, epidemiological studies indicated that males were more apt to contracting this disease in Taiwan [39,40]. Inconsistencies were also found in seroepidemiology. A study conducted in south India indicated that age > 60 years and female gender were risk factors for the seropositivity of scrub typhus [34]. However, another study in south India showed a higher seropositivity in males [41]. The different predisposition might be related to the exposure chance, immunity, and personal protective habits in different populations [33,42,43]. In conclusion, this study for the first time documented the profile of scrub typhus in Zhejiang province and elucidated the seasonality
Funding This study was supported by the medical research program of Zhejiang Province (Nos. 2017KY291, 2018KY338, and 2019ZD003). Competing interests The authors declare that there are no competing interests. Acknowledgments We thank all of the participants in this study. We also appreciate the efforts of medical and health care institutions in Zhejiang province for their disease surveillance. References [1] Rajapakse S, Weeratunga P, Sivayoganathan S, Fernando SD. Clinical manifestations of scrub typhus. Trans Roy Soc Trop Med Hyg 2017;111:43–54. [2] Taylor AJ, Paris DH, Newton PN. A systematic review of mortality from untreated scrub typhus (Orientia tsutsugamushi). PLoS Neglected Trop Dis 2015;9. e3971. [3] Bonell A, Lubell Y, Newton PN, Crump JA, Paris DH. Estimating the burden of scrub typhus: a systematic review. PLoS Neglected Trop Dis 2017;11:e5838. [4] Maina AN, Farris CM, Odhiambo A, Jiang J, Laktabai J, Armstrong J, et al. Q fever, scrub typhus, and rickettsial diseases in children, Kenya. Emerg Infect Dis 2016;22:883–6. 2011–2012. [5] Cosson JF, Galan M, Bard E, Razzauti M, Bernard M, Morand S, et al. Detection of Orientia sp. DNA in rodents from Asia, west Africa and Europe. Parasites Vectors 2015;8:172–5. [6] Balcells M. Endemic scrub typhus-like illness, Chile. Emerg Infect Dis 2011;17:1659–63. [7] Izzard L, Fuller A, Blacksell SD, Paris DH, Richards AL, Aukkanit N, et al. Isolation of a NovelOrientia species (O. Chuto sp. nov.) from a patient infected in Dubai. J Clin Microbiol 2010;48:4404–9. [8] Wu Y, Qian Q, Soares Magalhaes RJ, Han Z, Hu W, Haque U, et al. Spatiotemporal Dynamics of scrub typhus transmission in mainland China, 2006-2014. PLoS Neglected Trop Dis 2016;10:e4875. [9] Upadhyaya BP, Shakya G, Adhikari S, Rijal N, Acharya J, Maharjan L, et al. Scrub typhus: an emerging neglected tropical disease in Nepal. J Nepal Health Res Counc 2016;14:122–7. [10] Lee H, Cho PY, Moon S, Na B, Kang Y, Sohn Y, et al. Current situation of scrub typhus in South Korea from 2001–2013. Parasites Vectors 2015;8:238–41. [11] Wei Y, Huang Y, Luo L, Xiao X, Liu L, Yang Z. Rapid increase of scrub typhus: an epidemiology and spatial-temporal cluster Analysis in Guangzhou city, southern China, 2006–2012. PLoS One 2014;9:e101976. [12] Seto J, Suzuki Y, Nakao R, Otani K, Yahagi K, Mizuta K. Meteorological factors affecting scrub typhus occurrence: a retrospective study of Yamagata Prefecture, Japan. Epidemiol Infect 2017;145:462–70. 1984–2014. [13] Kuo CC, Huang JL, Shu PY, Lee PL, Kelt DA. Cascading effect of economic globalization on human risks of scrub typhus and tick-borne rickettsial diseases. Ecol Appl 2012;22:1803–16. [14] Statistical Bureau of Zhejiang Province. Comprehensive statistical data and materials on 50 years of new Zhejiang. Beijing: China Statistics Press; 2000. [15] Fang Y, Huang Z, Tu C, Zhang L, Ye D, Zhu B. Meta-analysis of drug treatment for scrub typhus in Asia. Intern Med 2012;51:2313–20. [16] Zhang M, Wang XJ, Zhao ZT. Current epidemic status and issues on prevention and control of scrub typhus in China. Chin J Epidemiol 2011;32(4):419–23. [In Chinese)]. [17] Wu GH. The research status and prospect of scrub typhus epidemiology in China. Chin J Infect Dis 2000;18(2):142–4. [In Chinese)]. [18] Kim S, Kim D, Jeung YS, Yun NR, Han MA, Kim C. Effect of latitude and seasonal variation on scrub typhus, South Korea, 2001–2013. Am J Trop Med Hyg 2016;94:22–5. [19] Hang TW, Liu J, Hong RT, He S, Cheng L, Cheng Y, Deng YQ. Epidemiological characteristics of tsutsugamushi disease in Fujian, China (2010-2013). Strait J Prev Med 2015(06):8–10. [In Chinese)].
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Contents lists available at ScienceDirect
Travel Medicine and Infectious Disease journal homepage: www.elsevier.com/locate/tmaid
Re-emergence of scrub typhus in Zhejiang Province, southern China: A 45year population-based surveillance study Jiangping Rena,b,c,1, Jimin Suna,b,1, Zhengting Wanga, Feng Linga,b, Xuguang Shia, Rong Zhanga, Ying Liua, Zhiping Chena,∗∗,2, Enfu Chena,b,∗,2 a
Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Hangzhou, China c Field Epidemiology Training Program of Zhejiang Province, Hangzhou, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Scrub typhus Epidemiology Seasonality China
Background: Scrub typhus is the leading cause of treatable unidentified febrile illnesses in Southeast Asia. This study was conducted to document the epidemiological characteristics of scrub typhus and its change in Zhejiang, one of traditional epidemic provinces in China. Methods: Scrub typhus surveillance data in Zhejiang province during 1957–1989 and 2006–2012 were obtained. Descriptive analysis was conducted to characterize the epidemiology of scrub typhus. The spatial distributions over the periods were explored using spatial autocorrelation analysis and spatiotemporal cluster analysis. Results: A total of 4104 cases and 7 deaths were reported from 1957 to 1989 and 2006 to 2017. The incidence declined since 1959, remained low from 1967 to 1989, and then exponentially increased after 2006. The seasonality changed from a summer pattern between 1957 and 1989 to a bimodal peak pattern in July to August and October to November from 2006 to 2017. One primary and three secondary high-risk clusters were affirmed in both periods from 1980 to 1989 and 2006 to 2017. The primary cluster expanded southwestward and the time span of the secondary clusters extended in the later period compared to the clusters in the previous time frame. Conclusion: Zhejiang recently underwent a seasonality change, geographic extension, and incidence increase in scrub typhus. More attention should be paid to controlling scrub typhus.
1. Introduction Scrub typhus, also known as bush typhus, is a mite-borne rickettsial zoonosis caused by the organism Orientia tsutsugamushi. It is the leading cause of treatable unidentified febrile illnesses in Southeast Asia. Humans occasionally become infected after being bitten by an infected chigger (the larval stage of a mite). Both rodents and mites are the natural reservoir hosts. The clinical spectrum varies from mild fever to multi-organ dysfunction [1]. It was considered as a lethal disease in the pre-antibiotic era and is militarily important, causing enormous losses during World War II and the Vietnam War. Early diagnosis and the timely use of antibiotics are quite important. The median untreatable mortality is 6%, with a range of 0%–70% [2]. Traditionally, scrub typhus is epidemic in the region called the “Tsutsugamushi Triangle,” which covers more than 8 million km2, from
the Russian Far East in the north to Pakistan in the west, Australia in the south, and Japan in the east [3]. It is estimated that one billion people are at risk of infection and one million morbidity occur annually in this region [3]. Recent evidence from the Arabian Peninsula, Chile, and Kenya indicated a potentially wider global distribution in tropical and subtropical regions [4–7]. Published reports from countries in the traditional “Tsutsugamushi Triangle” indicated an increase in scrub typhus cases over the past 10 years [8–11]. The drivers of the diffusion and reemergence are believed to include but are not limited to globalization, climate change, urbanization, and expansion of humans into previously uninhabited areas [3,8,12,13]. As Zhejiang is a traditional epidemic province in China, studies of scrub typhus in the area are limited. Therefore, we conducted this retrospective analysis to depict the profile of scrub typhus in Zhejiang and to provide the basis for further study and disease control.
∗
Corresponding author. 3399 Binsheng Road, Binjiang District, Hangzhou, China. Corresponding author. 3399 Binsheng Road, Binjiang District, Hangzhou, China. E-mail addresses: [email protected], [email protected] (Z. Chen), [email protected] (E. Chen). 1 Jiangping Ren and Jimin Sun contributed equally to this article. 2 Zhiping Chen and Enfu Chen contributed equally to this article. ∗∗
https://doi.org/10.1016/j.tmaid.2019.05.013 Received 28 June 2018; Received in revised form 17 May 2019; Accepted 20 May 2019 1477-8939/ © 2019 Published by Elsevier Ltd.
Please cite this article as: Jiangping Ren, et al., Travel Medicine and Infectious Disease, https://doi.org/10.1016/j.tmaid.2019.05.013
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2. Methods
2.4. Spatial autocorrelation analysis
2.1. Ethics statement
Spatial autocorrelation analysis was used to evaluate the spatial patterns. Global spatial autocorrelation is a measure of the overall clustering of the data. Several different statistics can identify the degree of autocorrelation, and Moran's I is the most frequently used. It ranges from −1 to +1, with negative values indicating dispersed patterns, positive values indicating clustered patterns, and zero indicating random spatial patterns. For statistical hypothesis testing, Moran's I values can be transformed to Z scores and P values, with an absolute Z score value > 1.65 and P value < 0.1 indicating significantly spatial autocorrelation. Global spatial autocorrelation analysis can be used to identify the overall distribution, but it cannot describe the local spatial patterns. However, local indicators of spatial association (LISA) can address this issue with local Moran's I and its Z score and P value. A high positive Z score and P value < 0.05 indicated spatial clusters (high-high: region with a high incidence surrounded by high incidences or low-low: region with a low incidence surrounded by low incidences). A negative Z score and P value < 0.05 indicates spatial outliers (highlow: region with a high incidence surrounded by low incidences, or low-high: region with a low incidence surrounded by high incidences). ArcGIS software (version 10.0.0) was used to conduct the spatial autocorrelation analysis.
Scrub typhus was incorporated into the Chinese notifiable disease monitoring system in 1957, but excluded between 1990 and 2005 due to its low incidence. As an important part of ongoing public health surveillance, the collection and analysis of data on notifiable infectious diseases by public health workers in charge of risk assessment and policy proposals are exempt from institutional review board assessment. It is authorized by the Law of the People's Republic of China on the Prevention and Treatment of Infectious Diseases. All of the collected data were supplied anonymously and no individual identifying information was provided. 2.2. Data collection and management Provincial surveillance data regarding scrub typhus between 1957 and 1989 were collected from a compilation of epidemiological data in Zhejiang province that were in the archives of the Zhejiang Provincial Center for Disease Control and Prevention. Demographic information, such as gender, age, occupation, and address, was not included, and there was no information regarding the geographical distribution in the surveillance data from 1957 to 1979. All of the surveillance data between 2006 and 2017 were retrieved from the China Information System for Disease Control and Prevention, which was established in 2004. It included basic demographic and clinical information reported by physicians. The annual demographic data of the counties in Zhejiang from 2006 to 2017 were obtained from Zhejiang's provincial Bureau of Statistics (http://tjj.zj.gov.cn/), and the data from 1957 to 1989 were from the Comprehensive Statistical Data and Materials on 50 Years of New Zhejiang [14].
2.5. Spatiotemporal cluster analysis SaTScan software (version 9.1.1) was used to detect the space-time clusters of scrub typhus and verified whether or not the clustering was caused by random variations. Circular scan windows and discrete Poisson models were used to scan the high rate areas with monthly units. Likelihood ratio tests were evaluated to determine the significance of the identified clusters and P values were obtained through Monte Carlo simulations after 999 replications. The null hypothesis of a spatiotemporally random distribution was rejected when the P value was < 0.05.
2.3. Descriptive epidemiology
3. Results
The epidemiological characteristics of scrub typhus cases in Zhejiang province were analyzed with R software (version 3.3.2) and WPS Office software. The data were divided into three periods: period one (1957–1979), period two (1980–1989), and period three (2006–2017). As no related data were obtained, the demographic characteristic analysis was not conducted during periods one and two, and the spatial distribution analysis was not included in period one. The chi-squared test, t-test, Kruskal-Wallis test, and linear models were employed to explore the profile of scrub typhus in Zhejiang province. The null hypothesis was rejected when the P value was < 0.05.
3.1. Temporal distribution A total of 4104 cases were diagnosed from 1957 to 1989 and from 2006 to 2017. The annualized average incidence during the study period was 2.3 per million, with the highest annual incidence reported in 1959 (10.0 per million) and the lowest in 2006 (0.2 per million, Fig. 1). Seven deaths were reported and the overall mortality was 0.2%. The incidence fell starting in 1959, remained low from 1967 to 1989
Fig. 1. The annual distribution of scrub typhus cases from 1957 to 1989 and from 2006 to 2017 in Zhejiang province, China. 2
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Fig. 2. The monthly distribution of scrub typhus cases during three different periods in Zhejiang province, China.
Chun'an (19.4 per million), and Xinchang (16.1 per million) ranked as the top five (Fig. 3).
and from 2006 to 2013, and then increased dramatically. Overall, 2104 cases and 7 deaths were reported during period one (from 1957 to 1979), with an annualized average incidence of 2.9 per million and a mortality rate of 0.3%. The vast majority of cases (93.2%) occurred between June and October and marked peaks were noted in July and August (Fig. 2). Overall, 570 cases and no deaths were reported during period two (from 1980 to 1989). The incidence of scrub typhus remained relatively low during this period, and the annualized average incidence (1.4 per million) was half of that in period one. The highest annual incidence was reported in 1989 (2.6 per million) and the lowest in 1981 (0.6 per million). Similar to the seasonal patterns in period one, 81.6% of cases were reported from July to October, and an incidence peak was observed in July and August (Fig. 2). A total of 1430 scrub typhus cases were reported during period three (from 2006 to 2017), with an annualized average incidence of 2.2 per million, and no deaths were confirmed. The annual incidence ranged from 0.2 per million (in 2006) to 5.3 per million (in 2017) and exponentially increased as a whole (R2 = 0.9, P < 0.01, log(y) = 0.3x602.4, Fig. 1). The seasonal patterns during period three were different from those in periods one and two. Two peaks were noted. The main peak was from July to August with 37.1% cases, and the minor peak covered October and November with 28.7% of reported cases (Fig. 2).
3.3. Spatial autocorrelation analysis of scrub typhus The global spatial autocorrelation analysis at the county level indicated that the geographical distribution of scrub typhus in Zhejiang was clustered as a whole in periods two (I = 0.05, Z = 1.76, P = 0.079) and three (I = 0.218, Z = 3.425, P = 0.001). Two high-high clusters were identified through LISA at the county level in period two, and five in period three. Compared to the clusters in period two, the high-high clusters between 2006 and 2017 moved from the south to the central and southwest part of the province, and the covered area significantly increased (Fig. 4). 3.4. Spatiotemporal clusters of scrub typhus One primary (cluster one) and three secondary (clusters two to four) high-risk clusters were scanned though space-time statistical analysis in period two (Fig. 3). The primary cluster included 173 cases and one county in southern Zhejiang from June 1984 to November 1988 (RR = 133.8, LLR = 641.4, P < 0.01). Clusters two, three, and four were located in middle and mideast Zhejiang from July to November 1989 (46 cases, RR = 22.50, LLR = 97.42, P < 0.01), southeastern Zhejiang from June to August 1980 (18 cases, RR = 75.48, LLR = 59.78, P < 0.01), and northwestern Zhejiang from June to October 1987 (6 cases, RR = 24.20, LLR = 13.34, P = 0.04), respectively. Four high-risk clusters (one primary and three secondary) were identified during period three (Fig. 3). The primary cluster was centered at 27.6 N, 119.1 E with a radius of 129.3 km and contained 13 counties and 435 cases in the southwest of the province from June 2016 to December 2017 (RR = 10.29, LLR = 555.05, P < 0.01). The three secondary clusters were situated in the center (358 cases, RR = 8.84, LLR = 421.30, P < 0.01), west (68 cases, RR = 27.82, LLR = 159.05, P < 0.01), and south (11 cases RR = 10.33, LLR = 15.72, P < 0.01) of the province. In comparison, the primary cluster expanded southwestward and the time span of three secondary clusters was longer in period three.
3.2. Spatial distribution Seven of the 11 prefecture cities reported scrub typhus cases from 1980 to 1989. No cases were diagnosed in northern and northeast Zhejiang (Ningbo, Jiaxing, Huzhou, and Zhoushan). Lishui (14.8 per million), Jinhua (3.7 per million), and Taizhou (0.7 per million) were the three prefecture cities with the highest annualized average incidence. Approximately one-third of counties (32.4%) reported cases during this period. Lishui (93.0 per million), Dongyang (10.2 per million), Yongkang (9.5 per million), Qingtian (9.0 per million), and Tiantai (5.3 per million) reported the highest annualized average incidence rates at the county level (Fig. 3). All of the 11 prefecture cities reported scrub typhus during period three. The annualized average incidence in Lishui (12.0 per million), Jinhua (6.0 per million), and Wenzhou (3.3 per million) ranked as the top three, while Jiaxing (0.1 per million) reported the lowest incidence. More than three-quarters of the counties were affected during 2006 and 2017, and the annualized average incidence in Qingyuan (37.0 per million), Pan'an (33.8 per million), Longquan (30.2 per million),
3.5. Demographic characteristics Females were reported slightly more frequently (male-female sex 3
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Fig. 3. The spatiotemporal clusters overlaid with the average annual incidence of scrub typhus between 1980 and 1989 (panel A) and 2006–2017 (panel B) in Zhejiang province, China.
4. Discussion
ratio: 0.9:1) and their incidence was higher than among males (2.3 per million vs 2.0 per million, Table 1). The overall mean age was 53.7 years (range: 7 months to 92 years). The age distribution varied significantly across different years (χ2 = 29.9, P < 0.01, Fig. 5) and genders (51.5 vs 55.7, t = −4.73, P < 0.01). The incidence also varied with age. Those aged 60–70 were reported to have the highest incidence (7.9 per million), followed by the 70–80 (5.4 per million) and 50–60 age groups (4.2 per million). The lowest incidence was reported in those aged between 10 and 20 (0.3 per million). Although females were more susceptible to scrub typhus as a whole, the incidence among those younger than 40 was higher in males than in females, while the trend reversed for populations older than 40. Most of the cases were farmers (76.01%). The distribution of occupation varied by gender (χ2 = 73.74, P < 0.01), with farmers (74.0%), workers (7.1%), and students (2.8%) as the three most frequently reported occupations for males, and farmers (77.9%), unemployed or homemakers (8.2%), and workers (3.9%) for females.
As an emerging and re-emerging disease with unspecific clinical manifestations, scrub typhus has been neglected and often misdiagnosed. No scrub typhus vaccine is available at present. Deratization and mite control can stop the transmission fundamentally, but it is usually difficult. Prevention strategies include avoiding unnecessary exposure, aggressive efforts to eliminate chigger breeding areas by weeding, and recommendations for personal protective measures, including preventing chigger bites by applying insect repellent, wearing long-sleeved shirts and long pants, and risk communication and community mobilization. Antibiotics such as doxycycline, azithromycin, and chloramphenicol are the treatments of choice for scrub typhus. A meta-analysis conducted by Fang [15] indicated that, compared to azithromycin and chloramphenicol, doxycycline acted more quickly for scrub typhus treatment, but had more adverse drug events. Since 1957, when scrub typhus was included in the Chinese notifiable disease monitoring system, the number of annually reported cases was approximately 1000 before 1986 in China, and then rose to > 2000 between 1986 and 1989 [16]. The annual incidence in Zhejiang
Fig. 4. Local indicators of spatial association (LISA) cluster maps for the average annual scrub typhus incidence from 1980 to 1989 (panel A) and from 2006 to 2017 (panel B) in Zhejiang province, China. 4
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Table 1 The character of scrub typhus cases in Zhejiang province during 2006 and 2017. Index
Male
Female
Total
Statistic
Mean age
51.52 (50.21,52.83)
55.69 (54.56,56.82)
53.69 (52.82,54.56)
t = −4.727,P < 0.001
0.9087 0.3614 0.5531 1.1042 2.0653 3.7247 6.6596 5.0451 2.0990 2.0445 508 (73.94%) 49 (7.13%) 8 (1.16%) 19 (2.77%) 14 (2.04%) 15 (2.18%) 12 (1.75%) 9 (1.31%) 9 (1.31%) 8 (1.16%) 17 (2.47%) 19 (2.77%) 47 (6.80%) 310 (45.10%) 273 (39.70%) 57 (8.30%)
0.6412 0.2441 0.5091 0.4975 2.1077 4.7740 9.1604 5.6925 3.6481 2.3252 579 (77.93%) 29 (3.90%) 61 (8.21%) 6 (0.81%) 14 (1.88%) 3 (0.40%) 5 (0.67%) 3 (0.40%) 4 (0.54%) 3 (0.40%) 14 (1.88%) 22 (2.96%) 48 (6.50%) 366 (49.30%) 288 (38.80%) 41 (5.50%)
0.7836 0.3054 0.5317 0.8084 2.0861 4.2353 7.8869 5.3676 2.9730 2.2429 1087 (76.01%) 78 (5.45%) 69 (4.83%) 25 (1.75%) 28 (1.96%) 18 (1.26%) 17 (1.19%) 12 (0.84%) 13 (0.91%) 11 (0.77%) 31 (2.17%) 41 (2.87%) 95 (6.60%) 676 (47.30%) 561 (39.20%) 98 (6.90%)
__
Incidence (per million)
Occupation
Seasonality
0–10 10–20 20–30 30–40 40–50 50–60 60–70 70–80 ≥80 Total Farmer Worker Unemployed Or Housework Student Scattered Children Retiree Cadre Commercial Service Childcare Children Migrant Worker Else Unclear Spring (Mar to May) Summer (Jun to Aug) Autumn (Sep to Nov) Winter (Dec to Feb)
χ2 = 29.859 P = 0.002
χ2 = 5.478 P = 0.140
Fig. 5. The age distribution of scrub typhus cases between different years from 2006 to 2017 in Zhejiang province, China.
identified between late October and early November, and lower latitudes were associated with a later peak incidence in South Korea [18]. A study conducted by Zhang et al. [16] concluded that there were four different seasonal patterns for scrub typhus in China: summer, winter, autumn-winter, and annually. The seasonality in south of the Yangtze River had a summer pattern, while it had an autumn-winter pattern in north of the river. The results of this study verified the seasonality change in scrub typhus in Zhejiang province, which is located in south of the Yangtze River. There was only one seasonal peak in summer between 1959 and 1989, while the seasonality changed between 2006 and 2017. Dual peaks were noted, including a major peak from July to August and a senior peak from October to November. Other provinces in south of the Yangtze River also underwent seasonal changes. The majority of cases occurred between June and October in Fujian province from 2006 to 2013 and in Jiangxi province between 2006 and 2012 [19,20]. Bimodal peaks were noted in Guangdong province, including one between June and July and another between September
province peaked in 1959, declined, and remained relatively low between 1967 and 1989. No increase was noted in Zhejiang between 1986 and 1989. The reason for the increase at the national level during this period might be related to the regional expansion in China after 1985 [17]. Before 1986, scrub typhus was limited to south of the Yangtze River, from Zhejiang and Hunan in the north to Yunnan and Sichuan in the west, Hainan in the south, and Taiwan in the east. However, the regional distribution has expanded northward since then. Until 2014, all of the provinces in China except Qinghai reported scrub typhus cases [8]. Studies conducted in countries from the traditional “Tsutsugamushi Triangle” after 2000 indicated an increase in the incidence of scrub typhus, and China, in particular, experienced an exponential increase starting in 2006 [3,8]. Similar to the whole of China, the incidence in Zhejiang also exponentially increased between 2006 and 2017. The seasonal pattern of scrub typhus changed with the geography, environment, and climate. The majority of cases occurred in spring to early summer in Yamagata Prefecture, Japan [12]. Most cases were
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change, geographic extension, and incidence increase in recent years. Although the exponential increase in the incidence as a whole started after 2006, scrub typhus has always been neglected by the health care sector and local government in Zhejiang. Limited resources have been provided and no systemic measures have been conducted on disease control. The high-risk population, senior farmers, are relatively low income and poorly educated. Targeted strategies and measures, such as health education and environmental management, should be undertaken immediately. Further research should also be conducted to understand the reason for these changes.
and October [21]. Park et al. [22] believed that the seasonal pattern was influenced by the vector cycles. Leptotrombidium scutellare, one scrub typhus vector, only feeds on human tissue fluid in autumn. L. pallidum, another scrub typhus vector, feeds in both autumn and spring [22]. This suggests that the seasonality change in south of the Yangtze River may be related to changes in the vector distribution. Mirroring the Chinese mainland and worldwide trends, Zhejiang has undergone a geographic extension of scrub typhus since 2006. The high-risk areas moved from the south to the central and southwest of the province. It is believed that the temporal and spatial distributions of scrub typhus are largely dependent on the distribution, activity, and abundance of the vectors and reservoirs. Wei et al. [23] indicated that a 1% increase in rodent density was associated with a 2.4% increase in the odds of scrub typhus cases after a 5-month lag in Guangzhou, southeastern China. Studies conducted in Japan, South Korea, and south and north China indicated that climate was an important influence on the epidemic of scrub typhus [12,23–27]. Meteorological factors, such as the temperature, duration of sunshine, rainfall, relative humidity, atmospheric pressure, and snowfall, were related to the incidence of scrub typhus. No related study was conducted in Zhejiang. However, the trend in temperature was in line with that of scrub typhus incidence in Zhejiang. The temperature increased as a whole in Zhejiang between 1951 and 2013, and can be divided into three phases: rose slightly without high fluctuations between 1951 and 1966, was relatively low from 1967 to 1989, and rose significantly between 1990 and 2013 [28]. Chiggers might indicate the connection between climate change and the incidence of scrub typhus. Chiggers are mainly located in grassy fields, gardens, parks, forests, bush, and moist areas around lakes or rivers, and their distribution is influenced by the humidity, temperature, and sunshine [29]. Changes in production and lifestyle also had an effect on the epidemic of vector-borne diseases. Kuo et al. [13] believed that farm abandonment (including abandonment of rice paddies) and periodic plowing in Taiwan increased the risk of spotted fever and scrub typhus because the mean tick and chigger loads were significantly higher in fallow plots than in plowed plots. Ticks and chiggers exhibit very low survival rates in flooded rice paddies, and periodic plowing can unintentionally mitigate vector burdens. Another study conducted in Taiwan indicated that the scrub typhus incidence was significantly positively correlated with the proportion of land that contained mosaics of cropland and vegetation [30]. Due to the success of hybrid rice by Yuan Longping and agricultural modernization, riceseeded areas have decreased significantly with the higher percentage of periodic plowing, and farm abandonment has become common in Zhejiang, a traditional rice-producing province. In addition, urbanization, globalization, and more eco-friendly surroundings are also important drivers of the emergence and re-emergence of vector-borne diseases as humans have more opportunities to come into contact with vectors including chiggers [31,32]. Inconsistent with surveys conducted in Korea, Japan, India, and other provinces in China, senior farmers were a high-risk population in Zhejiang province [10,33–35]. Females were more susceptible as a whole, and males were more likely to be infected in populations aged under 40. A study conducted in Guangdong province, China, indicated similar demographic characteristics to scrub typhus [36]. Females were also reported as the more susceptible gender in Korea, Japan, and Jiangsu and Fujian provinces in China [10,19,35,37,38]. However, epidemiological studies indicated that males were more apt to contracting this disease in Taiwan [39,40]. Inconsistencies were also found in seroepidemiology. A study conducted in south India indicated that age > 60 years and female gender were risk factors for the seropositivity of scrub typhus [34]. However, another study in south India showed a higher seropositivity in males [41]. The different predisposition might be related to the exposure chance, immunity, and personal protective habits in different populations [33,42,43]. In conclusion, this study for the first time documented the profile of scrub typhus in Zhejiang province and elucidated the seasonality
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