Rapid increase of scrub typhus incidence in Guangzhou, southern China, 2006―2014
Sun et al. BMC Infectious Diseases
Rapid increase of scrub typhus incidence in Guangzhou, southern China, 2006―2014
Ye Sun 1
Yue-Hong Wei 0
Yu Ma 0
Sake J. de Vlas
Hong-Wu Yao 1
Yong Huang 0
Mai-Juan Ma 1
Kun Liu 1
Xiao-Ning Li 0
Xin-Lou Li 1
Wen-Hui Zhang 1
Li-Qun Fang 1
Zhi-Cong Yang 0
Wu-Chun Cao 1
0 Guangzhou Center for Disease Control and Prevention , Guangdong Province, Guangzhou 510440 , People's Republic of China
1 The State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology , 20 Dong-Da Street, Fengtai District, Beijing 100071 , People's Republic of China
Background: In the last decade, scrub typhus (ST) has been emerging or re-emerging in some areas of Asia, including Guangzhou, one of the most affected endemic areas of ST in China. Methods: Based on the data on all cases reported in Guangzhou from 2006 to 2014, we characterized the epidemiological features, and identified environmental determinants for the spatial distribution of ST using a panel negative binomial model. Results: A total of 4821 scrub typhus cases were reported in Guangzhou during 2006―2014. The annual incidence increased noticeably and the increase was relatively high and rapid in rural townships and among elderly females. The majority of cases (86.8%) occurred during May―October, and farmers constituted the majority of the cases, accounting for 33.9% in urban and 61.6% in rural areas. The number of housekeeper patients had a rapid increment in both rural and urban areas during the study period. Atmospheric pressure and relative humidity with lags of 1 or 2 months, distributions of broadleaved forest and rural township were identified as determinants for the spatiotemporal distribution of scrub typhus. Conclusion: Our results indicate that surveillance and public education need to be focused on the elderly farmers in rural areas covered with broadleaf forest in southern China.
Scrub typhus, a bacterial zoonosis caused by Orientia
tsutsugamushi (O. tsutsugamushi), is characterized by
fever, eschar or ulcer, rash, lymphadenopathy,
hepatosplenomegaly. Severe complications or even death may occur.
O. tsutsugamushi is transmitted occasionally to humans
by the bites of infected chiggers (larval trombiculid mites)
[1, 2]. Rodents are important to maintenance of the
disease in that they are known as incidental hosts for
chiggers . It is endemic across extensive areas of the
AsiaPacific rim, and over one billion people are at risk to the
disease . Recently, a re-emerging picture has been
reported from some Asian countries after decades of silence
in these regions [4–7]. It was estimated that one million
new infections occur worldwide annually, however, which
would most likely rise due to the current reemergence in
Asia . In the lack of effective human vaccines and
convenient and quick diagnostic methods, scrub typhus poses
a significant threat to public health [3, 8].
Human cases of scrub typhus were reported in 1948 in
Guangzhou. Constantly troubled by the disease, Guangzhou
has listed it as one of the local reportable infectious diseases
since 1995 . Recently, a rapid increase of the disease was
observed with more than one thousand cases reported in
2012, a nearly four-fold increase as compared to 2006 .
Scrub typhus in Guangzhou is of the summer-type and is
more virulent than the autumn-type scrub typhus which is
endemic in Northern China . The increased incidence of
scrub typhus in Guangzhou offers an opportunity to
enhance our understanding of the epidemiology of this
reemerging disease, as well as its spatial and temporal
heterogeneity, which will help guide targeted interventions
against this disease.
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
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reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
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The study area of Guangzhou prefecture (22°26’ to 23°56’
north latitude, 112°57’ to 114°03’ east longitude), a
political subdivision of a province, is the capital of Guangdong
Province in southern China. Located at the Pearl River
Delta, Guangzhou harbors around 13 million residents in
its 12 counties with a total land area of nearly 7500 km2
features a subtropical monsoon climate with annual average
temperatures of 21–23 °C and annual average
precipitations around 1900 mm. The landscape is characterized by
mountains and hills in north or northeast, basin and
alluvial plain in south or southwest.
Data collection and management
All clinically diagnosed and laboratory-confirmed cases of
scrub typhus are reported to the China Information
System for Disease Control and Prevention (CISDCP) since
2006. The diagnosis of scrub typhus is based on the
national guide lines issued by the Chinese Center for Disease
Control and Prevention (http://www.chinacdc.cn/tzgg/
200901/t20090105_40316.htm). The clinical diagnosis of
patients were mainly based on some of the following
clinical manifestations and signs: (i) Epidemiological exposure
history within 3 weeks prior to the onset, (ii) fever, (iii)
lymphadenopathy, (iv) skin rash, and (v) specific eschar or
ulcer. A clinically diagnosed cases are defined by meeting
at least above “i, ii, and v” or “ii, iii, iv, and v” after
excluding other diseases with similar clinical manifestations. A
laboratory-confirmed case is defined as a clinically
diagnosed patient with at least one of the following laboratory
results: (vi) An agglutination titer ≥ 1:160 in the Weil-Felix
test using the OXK strain of Proteus mirabilis, (vii) a
fourfold or greater rise in serum IgG antibody titers between
acute and convalescent sera detected by using indirect
immunofluorescence antibody assay (IFA), (viii) detection of
O. tsutsugamushi by polymerase chain reaction (PCR) in
clinical specimens, or (ix) isolation of O. tsutsugamushi
from clinical specimens. A patient meeting above “i, ii, iii
or iv” or “ii, iii, iv” after excluding other diseases with
similar clinical manifestations, and at least one of above “vii,
viii, ix” is also diagnosed as a laboratory-confirmed case
according to the Technical Guides for Prevention and
Control of Scrub Typhus (available at:
To explore factors influencing the spatiotemporal
distribution of scrub typhus cases in Guangzhou, data on
meteorological, environmental and ecological factors were collected.
The following meteorological data were obtained from
China Meteorological Data Sharing Service System
(available at: http://data.cma.cn/) : average monthly atmospheric
pressure, average monthly temperature, average monthly
relative humidity, aggregate monthly precipitation, and
average monthly wind velocity. Land cover data were
derived from a raster version of the “GlobCover 2009 land
cover map” provided by the European Space Agency
(available at http://due.esrin.esa.int/page_globcover.php).
Elevation raster with a spatial resolution of 1 *1 km2 was
obtained from the Global Digital Elevation Data Products
(http://www.gscloud.cn). Population data at the township
level were obtained from the National Bureau of
Statistics of China, which is based on the Sixth National
Census in 2010. These variables were extracted for
each township of Guangzhou in ArcMap version 9.3.
Epidemiological features analysis
Each reported case was geo-referenced to a digital map
of Guangzhou. A thematic map was created to display
the case locations and the average annual incidence at
township level. Temporal dynamic of the disease for
each county were shown by a heat map of monthly
incidences from 2006 to 2014. Area feature was classified as
rural or urban at township level. For rural and urban
areas separately, monthly and annual incidences, and
proportions of occupations were plotted over time.
Decomposition of annual incidences and average annual
incidence by sex and age was also performed, where the
average annual incidence was further stratified by urban
versus rural areas. In addition, a map series of the
incidences at the township level was created for each year
from 2006 to 2014.
Analysis of potential factors associated with the spatial
distribution of scrub typhus
A multi-level negative binomial regression model was
used to relate the monthly scrub typhus incidences from
2006 to 2014 to potential risk factors at the township
level, using the population size as an offset (Additional
file 1: Table S1). Variables with p-values under 0.10 in
the univariate analysis were included in the multivariate
analysis. The incidence rate ratio (IRR) in response to
the change of each variable by a given amount
(Additional file 1: Table S1) was used to show the impact
of each variable. Two-sided p-values under 0.05 were
considered statistically significant. Considering that the
mean incubation period of scrub typhus in humans is
10–12 days  and that the life cycle of chigger is
several months , we first examined possible time lags of
the influence of each meteorological factor (0–3 months)
on monthly incidence of scrub typhus. The most
significant lag was then used in the negative binomial regression.
Correlations between co-variables were assessed, and highly
correlated variables (Spearman correlation coefficients > 0.7)
were not entered in the model simultaneously. The
multivariate model was selected by comparing the log likelihood
of the models and the changes of p-values of model
coefficients when a covariate was included or excluded . The
analysis was performed in STATA 9.1 software (StataCorp
LP, CollegeStation TX, USA) .
A total of 4821 clinically diagnosed and
laboratoryconfirmed cases were reported in Guangzhou during
2006―2014, among whom 14 patients died (CFR: 0.3%).
All 12 counties of Guangzhou and 98.8% of the
townships (159/161) were affected. Cases were mainly
distributed in areas with high densities of built-up lands and
croplands (Fig. 1a). The average annual incidences varied
greatly across the 159 townships, ranging from 2.2 to
395 per100, 000 person-years, and rural and suburban
townships had higher average annual incidences than
the urban ones (Fig. 1b). Eleven out of 12 counties
showed increasing incidences during the 9 years except
for Liwan County in the heat map (Fig. 2). Additional
file 2: Figure S1 showed the spatial expansion and
distributional dynamics of the disease at the township level.
The majority of cases (86.8%) occurred during
May―October, and the incidence peaked in either June/
July (most years from 2006―2014) or October
(2007―2008) with dual peaks in some years. The annual
incidence increased slowly during Period I (2006―2008)
and grew steadily during Period II (2009―2011), then
fluctuated and remained high in Period III
(2012―2014). Rural areas had 2–4 times higher
incidences and a more rapid increase of the incidence than
urban areas during the study period (Fig. 3). Farmers
constitute the majority of the cases over the study period,
accounting for 33.9% in urban and 61.6% in rural areas,
followed by housekeepers, persons taking housekeeping as
their career in their own house or employed by others,
who accounted for 19.6% in urban and 12.5% in rural
areas. The rapid growth of the number of housekeeper
patients was noticeable during the whole period, with an
increment of more than 10 times in rural areas and 6 times
in urban areas (Additional file 3: Figure S2). Period III was
a stage of high growth of the number of cases for
housekeepers and farmers, as well as retirees in urban areas.
The senior population older than 60 years had the
highest average annual incidence, especially the senior
females, which have also shown a quicker rise of average
annual incidences in both urban and rural areas during
the three periods, rather than other age groups. The age
difference in average annual incidence seemed greater in
recent period (Additional file 4: Figure S3). Interestingly,
in both rural and urban areas, average annual incidences
in males were higher than that in females among the
population younger than 50, but the direction of gender
difference reversed in the older population, i.e., elderly
females were more prone to infection with scrub typhus
than elderly males.
Univariate negative binomial regressions found that
monthly incidences of the disease at the township level
were significantly associated with all meteorological
variables with 0–2 months lags, various forests, grassland,
croplands and artificial surfaces, mean elevation, and
type of township (rural vs. urban). Four variables,
including average atmospheric pressure with 1-month lag,
average relative humidity with 2-month lags, percentage
coverage of broadleaved forest and type of township,
were shown to be independent predictors for the
spatiotemporal distribution of the disease in the multivariate
regression model. Each one hundred Pa increase of
average atmospheric pressure was associated with an 11%
(95% CI: 10–12%) decrease in the incidence of scrub
typhus in the next month, while a 10% rise in monthly
average relative humidity corresponded to an 4% (95%
CI: 3–5%) increase in the scrub typhus incidence in the
month after the next. For every 10% increase in the
percentage coverage of broadleaved forest, the incidence of
the disease went up by 5% (95% CI: 3–6%). On average,
a rural township had an 81% (95% CI: 43–129%) higher
risk than an urban township (Table 1).
Guangzhou, one of the most affected endemic areas of
scrub typhus in mainland China , had experienced a
rapid increase of scrub typhus incidence during 2006–
2014. Our results showed that the hot spots of the
disease mainly clustered in rural areas. However, the
increasing incidence in urban areas requires more
attention because of the much larger population [5, 16].
Some other Asian cities have seen similar increases, for
which the increasing outdoor recreation and leisure
activities in city parks had been discovered as one of risk
The dual peaks, one in June/July and the other in
October, were probably linked to the circulation of two
different species of mite vectors in the two seasons .
The divergent prototypes of O. tsutsugamushi identified
in Guangzhou could contribute to the dual-peak pattern
of this disease . In addition, seasonal changes in the
human exposure to mite vectors due to farming or
outdoor activities cannot be excluded as a risk factor of the
Farmers constituted the majority of the cases. Agricultural
activities would increase the exposure to pathogen-carrying
chigger mites [19–21]. Notably, about 20–40% of urban
cases were also classified as farmers annually, likely a result
of the accelerated urbanization in China in recent decades.
Residents in newly urbanized areas may still be engaged in a
certain level of agricultural activities. Housekeepers were the
second largest group of patients and in both rural and urban
townships, and the increment of case number was observant
(43 and 272 cases during Periods I and III in urban area,
Fig. 1 The spatial dynamic of scrub typhus in Guangzhou. a Spatial distribution of the locations of confirmed scrub typhus cases overlapped by
the land cover, 2006―2014. b Average annual incidence of scrub typhus in township, 2006―2014
and 23 and 257 cases during Periods I and III in rural area,
respectively). The majority of the housekeepers were elderly
females (>50 years females, 43.2%). The high exposure of
housekeepers to infected mites could be associated with
their more leisure time and outdoor activities such as
walking in parks , which should not be overlooked in the
planning of intervention programs. The growth of retiree
patients in urban areas recently was also noteworthy.
Our data showed that the elder population had higher
incidence than the younger during the study period.
Also the incidence of rural seniors was rising, especially
for females. In modern China, young adults from rural
areas often work as laborers in urban areas, leaving the
elderly in their hometown taking care of grandchildren
as well as farming. More interestingly, elderly females
(>50 years) had higher incidence than elderly males,
whereas an opposite pattern was observed among the
younger generations, regardless of urban or rural
townships (Additional file 4: Figure S3). Boys are usually
more active in outdoor activities and thus had higher
exposure to chigger mites than girls. In rural areas, it is
common that elderly males in their fifties or sixties work
as laborers in urban cities, but most elderly females stay
in their hometown and undertake most of the farming
work and housework. Also the keen-on-health Cantonese,
especially the elderly, love outdoor exercise, making them
more exposed to the disease. The high incidence of the
elderly and children could also be attributed to relative
low immune level and lack of personal protection.
We found that a higher incidence of scrub typhus
was related to the increase of relative humidity at a
2-month lag and the decrease of atmosphere pressure
at a 1-month lag. Chigger mites thrive in a moist
habitat [23, 24]. Larval population density of chiggers
is high in areas of high humidity , and chiggers
survive and thrive well at relative humidity above 50%
. While high atmospheric pressure is thought to
be adverse to mites’ survival . The time lags in the
effect of meteorological factors may be related to the
life cycle of chigger mites as about 2–3 months 
and the incubation period of the disease (mean of
10–12 days) . Because of the nature of that a
chigger normally feeds on its host only once in its life
cycle and the infection transmitted by a chigger must
Fig. 2 Heat map of monthly incidence of each township in Guangzhou, 2006―2014. Monthly incidences of all townships were shown in the heat map
Fig. 3 Temporal distribution of monthly scrub typhus incidence for rural and urban areas separately. The bar charts in black and red represent
the monthly incidence in rural and urban areas, and the black and red line represents the annual incidence of the scrub typhus in rural and
urban areas in Guangzhou, 2006―2014
Table 1 The association between monthly scrub typhus incidence and potential influencing factors by panel negative binomial
aAP, monthly average atmospheric pressure with 1-month lag; Temperature, monthly average temperature with 1-month lag; RH, monthly average relative humidity with
2-month lag; Precipitation, monthly aggregate precipitation with 2-month lag; WV, monthly average wind velocity with 1-month lag; ST, current monthly aggregate proportion
of sunlight time; Croplands, percentage coverage of post-flooding or irrigated croplands (or aquatic) and rainfed croplands; CV, percentage coverage of mosaic cropland and
vegetation (grassland/shrub/forest); BF, Percentage coverage of broadleaved forest; NF, percentage coverage of needle leaved forest; MF, percentage coverage of mixed
broadleaved and needle leaved forest; GF, percentage coverage of mosaic grassland and forest or shrub; Shrub, percentage coverage of broadleaved or needle leaved, and
evergreen or deciduous shrub; HV, percentage coverage of herbaceous vegetation (grassland, savannas or lichens/mosses); AS, percentage coverage of artificial surfaces and
associated areas; BL, percentage coverage of bared land; WB, percentage coverage of water bodies; Elevation, mean elevation; FT, feature of township (rural vs. urban)
have been derived from the female parent by
transovarian transmission [12, 25], the infection rate and
population density of larval trombiculid mites largely
depend on those of the last generation and the
habitat during the time between egg hatch and settling
down on a host for a larvae, which are influenced by
relative humidity and atmosphere pressure in previous
about 1–2 months. The contribution of broadleaved
forest to the risk of scrub typhus incidence was shown
according to our study, where intense substrate vegetative
canopies could increase the population density of chigger
mites . These factors are similar to those identified in
other endemic areas of the disease in Asia .
In this study, we characterized the epidemiological
features of this reemerging disease in Guangzhou, and
identified environmental determinants of the spatial
distribution of ST using a panel negative binomial
model at township level. However, all the cases used in
this analysis were clinically diagnosed and
laboratoryconfirmed cases based on the national guidelines, and
we cannot separate out laboratory-confirmed cases
from reported cases. The lack of information on the
specific laboratory diagnosis approaches for each
reported patient is a limitation of the study. Still, our
results provide possible targets for focused prevention
and control of ST (i.e., the elderly farmers in rural areas
covered with broadleaf forest). Additional experimental
studies and the identification of confirmed cases should
further explore the epidemic dynamics and influencing
factors of ST.
Our study highlighted the urgent need for prevention
programs to contain the spread of scrub typhus in
Guangzhou. A set of preventive strategies including
public education and personal protection equipment
shall be promoted in high-risk populations such as the
elderly, farmers and housekeepers. Surveillance and
early diagnosis should be reinforced in suburb and
rural areas, especially places covered by broadleaf
forests. We recommend future studies collect behavioral
factors so that risk assessment can be adjusted for
individual exposure levels.
Additional file 1: Table S1. Description of potentially influencing
factors used in the analysis. (DOCX 19 kb)
Additional file 2: Figure S1. Spatial distribution dynamics of the annual
incidence of scrub typhus in Guangzhou, 2006–2014. (DOCX 357 kb)
Additional file 3: Figure S2. The temporal dynamic of the proportion of
scrub typhus patients by occupation groups in Guangzhou, 2006–2014.
(DOCX 142 kb)
Additional file 4: Figure S3. Age- and gender-specific incidence of
scrub typhus in Guangzhou. The star indicates a significant difference of
the average incidence between males and females. (DOCX 161 kb)
95% CI: 95% confidence interval; CFR: Case fatality rate; CISDCP: China Information
System for Disease Control and Prevention; IFA: Indirect immunofluorescence
antibody assay; IRR: Incidence rate ratio; O. tsutsugamushi: Orientia tsutsugamushi;
PCR: Polymerase chain reaction; ST: Scrub typhus
The authors thank all medical staff contributing to the diagnosis, report and
epidemiological investigation of scrub typhus patients in Guangzhou.
This work was supported by the grants from the Natural Science Foundation
of China (No. 81621005), the Basic Work on Special Program for Science &
Technology Research (2013FY114600), the Special Program for Science &
Technology Research (AWS15J006), the Natural Fund of Guangdong Province
(2015A030313813), the Medical Research Grant of Guangdong Province
China (A2014586), Science and the Technology Plan Grant of Guangdong
Province (2013B021800028; 201607010130), and The Project for Key Medicine
Discipline Construction of Guangzhou Municipality (2013-2015-07). The
funders had no role in study design, data collection and analysis, decision to
publish, or reparation of the manuscript.
Availability of data and materials
The data of scrub typhus patients in Guangzhou are available from
Guangzhou Center for Disease Control and Prevention. For approved
reasons, there may be access restrictions applied to this data. Anyone
interested in it, please contact Yue-Hong Wei, Email: .
All other relevant data is in the paper and its Additional files 1, 2, 3 and 4.
W-CC, Z-CY, Y-HW and L-QF conceived and designed the experiments.
Y-HW, YM, YH, X-NL and Z-CY conducted the epidemiological investigation
and collected the data of scrub typhus patients. YS, Y-HW, YY, L-QF, SJdV,
W-CC, H-WY, W-HZ, M-JM, KL and X-LL analyzed the data and interpreted
the results. YS, YY, SJdV, L-QF and W-CC contributed substantially to the
writing of the manuscript. All authors contributed to the revision of the
manuscript and approved the final draft.
Ethics approval and consent to participate
The research protocol was approved by the human ethics committee of
Guangzhou Center for Disease Control and Prevention (GZCDC) and by the
institutional review board of State Key Laboratory of Pathogen and Biosecurity,
Beijing Institute of Microbiology and Epidemiology. All study-related data were
anonymized before analyses.
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