billion cases of diarrheal disease occur worldwide. Diarrheal disease is the
second leading cause of death in 0-4-year-old children, killing around 760,000
children every year . Diarrheal disease
accounts for 10.03% of deaths among children aged 1-59 months in the Americas
and 31.3% of death among children in South East Asia .
Infectious diarrhea is referred to diarrheal disease which is most often caused
by infections with viral, bacterial, and parasitic pathogens. According to the
web-based real-time disease surveillance system-China Information System for
Disease Control and Prevention, infectious diarrhea is grouped into three
classes, including class A (cholera), class B (bacillary dysentery, typhoid and
paratyphoid) and class C (other infectious diarrhea). In China, a total of
836,591 class C infectious diarrhea cases were reported and the incidence rate
was 62.39/105 in 2011 . Among overall diarrheal disease cases, 0-4-year-old
children accounted for 52.13%, and the incidence rate was 447.06/105 . Despite
remark improvement of public health disease system after the 2003 SARS
outbreak, infectious diarrhea poses a great threat to public health,
particularly in 0-4-year-old children.
diarrhea is vulnerable to the influence of meteorological factors, and the
occurrence and prevalence of infectious diarrhea are closely related to
meteorological factors including temperature, precipitation, relative humidity,
and air pressure [4-7]. For example, temperature
can directly affect the replication and survival of pathogen and predict the
number of bacillary dysentery patients. Two time-series analyses reported that
1°C rise of maximum temperature
resulted in 11.40% (95%CI:10.19%-12.69%) and 16% (95%CI:13%-19%) increase in
the number of bacillary dysentery, respectively [8,9].
Precipitation may influence the quality of drinking water via contaminating the
supply of drinking water, and there is a positive association between heavy
precipitation and risk of infectious diarrhea [8,10].
Moreover, climate changes usually affect the behavior habits of human beings,
and increase human exposures to environmental pathogens [8,11,12].
position of Shanghai is unique, facing the Huangpu River and bordering the East
China Sea. Tide level of the Huangpu River is susceptible to many
meteorological and hydrological factors such as temperature, ocean tide,
upstream flood, local precipitation and runoff. As a city with a subtropical
humid monsoon climate, Shanghai is characterized by a mild climate, abundant
precipitation, adequate light, and four distinct seasons. It has a sufficient
supply of fresh water and reaches the highest temperatures in July and August.
Spring in Shanghai is from March to May (recently described as until June).
Summer in Shanghai is long, from June to September. There is a particular “Plum
Rain Season” (Meiyu Season) from mid-June to early July, and it lasts for
nearly one month commencing in early summer. During this period, the
precipitation often equals to 25% of the annual total. Autumn of the region
comes in October and November, and winter begins from December to the next
February. The coldest period starts from the end of January to early February.
In this study, we
described the epidemiological and etiological characteristics of infectious
diarrhea cases among permanent residents in Yangpu district of Shanghai, China,
from 2006 to 2015, and examined the associations between the meteorological
factors and the incidence of infectious diarrhea.
2. Materials and methods
Yangpu district is
one of the 16 districts of Shanghai, China. It is located at 31°27’ north latitude and 121°52’
east longitude, in northeastern part of downtown Shanghai, bordering the
Huangpu River on the east and south. Yangpu district has a total area of 60.61km2 and about a population of 1.1 million [13,14].
data of Yangpu district from 2006 to 2015 were downloaded from China
Meteorological Data Network. The meteorological variables included daily wind
velocity, daily sunshine time, daily air pressure, daily maximum temperature,
daily minimum temperature, daily vapor pressure, daily relative humidity, and
daily precipitation. Demographic data during the study period were obtained
from the Public Security Bureau of Yangpu Administration.
surveillance data used in this study were obtained from the National Notifiable
Disease Surveillance System (NDSS), which was approved by Municipal Center for
Disease Control and Prevention of Shanghai. Infectious diarrhea cases included
cholera, bacillary dysentery, typhoid, paratyphoid, and other infectious
diarrhea in NDSS. All infectious diarrhea cases were diagnosed by clinical
symptoms and identified by the serological tests and stool specimen tests.
Information of reported cases included age, gender, and residential address,
type of disease, date of onset, and pathogens. According to the National
Communicable Disease Control Act of the People’s Republic of China, physicians
in hospitals have the responsibility to report every case of infectious
diarrhea to the local center for disease control and prevention within 24
The epidemiological characteristics of infectious
diarrhea cases in Yangpu district from 2006 to 2015 were analyzed by
descriptive analysis. Categorical variables were tested by either χ2 test or Poisson approximation. Kruskal-Wallis
test was employed to compare the monthly distributions of infectious diarrhea
cases among age groups and Nemenyi method was introduced in multiple
comparisons. The generalized additive model (GAM) was employed to examine
whether these meteorological variables were correlated to the incidence of
infectious diarrhea. The GAM method is usually used to perform linear and
nonlinear regression analysis in time-series studies with a Poisson regression . GAM has been widely used in studies of
association between meteorological variables and incidence of infectious
diarrhea, because of its strength in nonparametric adjustment of confounding
effects of seasonality and long-term trends [16-18].
In this study, the error distribution and correlation function in GAM were the
Poisson distribution and Log correlation, respectively. Smoothing spline method
was used in the form of non-linear function, and generalized cross validation
was chosen to estimate non-linear function. The GAM regression model was
described as follows:
Y represented the monthly number of infectious diarrhea cases. βi and fi
represented linear and non-linear functions based on their regression
effects in the model, respectively.
term and β0 represented the intercept
of regression equation. The degree of freedom was specified based on the result
of cross validation, and the possible lag effects (up to seven days) of
meteorological factors were assessed in GAM. The effects of meteorological
factors on the incidence of infectious diarrhea were described by effective
value. The effective value above 0 meant that meteorological factor had a
positive effect on the incidence, whereas the effective value under 0 meant a
negative effect. The statistical analyses
were conducted using SAS 9.4 (SAS Institute, Inc., Cary, NC), and two-tailed P<0.05
was considered statistically significant.
characteristics of infectious diarrhea
3606 infectious diarrhea cases in Yangpu district from 2006 to 2015, 1843
(51.1%) were male and 1763 (48.9%) were female, with a male-to-female sex ratio
1.05. The annual crude incidence rate ranged from 20.10/105 to 57.94/105,
with an average annual crude incidence rate was 33.20/105
and an age-standardized incidence rate by world standard population (ASIRW) of
63.36/105 during 2006-2015 period.
The average annual crude incidence rate was 366.13/105
in 0-4-year-old patients, and this rate was significantly higher than that of
24.13/105 in 5-year-old or older
The incidence rates of infectious diarrhea were highest in 2009, and crude
incidence rates were 57.04/105 in
male, 58.86/105 in female, 57.94/105 in total, respectively (Table 1).Occurrence
of infectious diarrhea cases in 0-4 year-old patients usually peaked at period
from November to next January, while the peak time of 5-year-old or older
patients was from July to September (Figure 1).
age stratification analysis showed that infectious diarrhea cases had
statistically different monthly distributions for each age group between 2006
and 2015 (χ2=199.95,
(Figure 2). Moreover, a significant difference
in the monthly proportion of each age group was found between 0-4-year group
and 15-59 year group (χ2=31.37, P<0.001)
and between 0-4 year group and >60 years group (χ2=17.24,
of infectious diarrhea cases from 0-4-year-old patients and5-year-old or older
total of 2809 cases with pathogen information were reported from 3606
infectious diarrhea cases. Due to different types of pathogens causing
infectious diarrhea in patients at different age groups, we analyzed the
pathogen spectrums from 910 cases of 0-4-year-old patients and 1899 cases of
5-year-old or older patients, respectively. In 0-4-year-old patients, rotavirus
accounted for 90.11% (820/910) and was the dominant pathogen followed by Salmonella
(8.02%, 73/910), Shigella
(1.76%, 16/910) and Campylobacter jejuni (0.11%, 1/910). The top five
pathogens were Vibrio
(56.92%, 1081/1899), Salmonella (15.38%,
(15.17%, 288/1899), norovirus (5.11%, 97/1899), and rotavirus (4.11%, 78/1899)
in 5-year-old or older patients (Figure 3).
Among the 1081cases of Vibrio infected patients, Vibrio parahemolyticus was the
predominant bacterial pathogen with a high proportion of 98.43% (1064/1081).
between the incidence of infectious diarrhea and meteorological factors
The GAM result of 0-4-year-old
patients was similar to the result of 5-year-old or older patients, so GAM
result was shown in the form of total patients. Monthly average wind velocity,
sunshine time, air pressure, vapor pressure, and relative humidity were
automatically excluded during the subsequent selection process. Monthly average
maximum temperature, minimum temperature and precipitation were introduced into
the non-linear part of model. Degrees of freedom (df) for the non-linear
functions were set as 3. The lag effects were insignificant and excluded in the
final GAM. The final GAM was shown as follows:
=f(maximum temperature, df=3)+f(minimum temperature, df=3)+f(precipitation,
shown in (Figure 4), with the increase of monthly
average maximum temperature, minimum temperature and precipitation, the
effective value gradually decreased and then increased, which was similar to
binary curve. Monthly average maximum temperature below 6.38°C and above 24.59°C
had positive effects on the incidence of infectious diarrhea. Monthly average minimum
temperature below 5.12°C and above
24.03°C had positive effect on the
incidence of infectious diarrhea. Monthly average precipitation below 1.48 mm
and above 7.40 mm had positive effects on the incidence of infectious diarrhea.
study described the epidemiology of infectious diarrhea cases and analyzed the
association between the meteorological factors and incidence of infectious
diarrhea cases in Yangpu district from 2006 to 2015. This study revealed that
the average annual crude incidence rate was 33.20/105
and the ASIRW was 63.36/105 during
2006-2015 period, which were relatively low compared with other provinces in
China . The average annual crude incidence
rate was 366.13/105 in 0-4-year-old
patients, whereas this rate was 24.13/105
in 5-year-old or older patients. Based on this significant difference, we
divided overall patients into 0-4-year-old and 5-year-old or older patients for
further analyses, such as peak time, pathogen spectrums and the associations
between meteorological factors and the incidence of infectious diarrhea.
results were consistent with other studies in China showing that infectious
diarrhea cases in 0-4-year-old patients usually peaked at period from November
to next January, while the peak time of 5-year-old or older patients was from
July to September [19,20]. The monthly
distributions of infectious diarrhea cases were statistically different among
different age groups. For example, the cases of 15-59 years group mainly
occurred in June, July and August, but 0-4years group cases occurred in
November, December and January. We further investigated the reason why pathogen
spectrums might differ among different age groups. Proportion of rotavirus accounted for 90.11% of infectious diarrhea cases and
was the dominant pathogen in 0-4-year-old patients, whereas it was only 4.11%
in 5-year-old or older patients. Rotavirus is one of the major reasons of
diarrhea diseases in 0-4-year-old patients, and about 30%-60% of hospital
admissions for diarrhea diseases in young children were infected with rotavirus [21-23]. In order to control the prevalence of rotavirus, several kinds of hygienic measures, such as
supplement of clean water and good sanitation, are recommended. We suggest that
rotavirus vaccine is the most economical and effective means to prevent rotavirus related infectious diarrhea in 0-4-year-old children.
Rotavirus vaccine has been proved to be responsible for a 67% reduction in
laboratory-confirmed rotavirus infections for 0-4-year-old children in England . In addition, 56.92% of 5-year-old or older
patients were infected with Vibrio, but there were no patients infected with Vibrio in
the 0-4-year-old patients. Vibrio parahemolyticus was
the predominant bacterial pathogen among Vibrio infected patients. Vibrio parahemolyticus has a
halophilic characteristic and is often isolated from seawater and seafood.
Shanghai is a coastal city and the consumption of contaminated seafood is the
main cause of acute diarrhea in adults . To
strengthen the supervision of hygiene conditions in the sale, transportation
and consumption of seafood may help reduce the occurrence of infectious
diarrhea in adults.
incidence of infectious diarrhea and meteorological factors varied widely in
different regions in mainland China , the
analysis in a certain area can provide more accurate and detailed information.
With a population of about 1.1 million, Yangpu district can be a good candidate
for the impact of meteorological factors on the incidence of infectious
diarrhea. Because of its strengths in the time series analysis, the GAM has
been widely used in the studies of the association between climate changes and
incidence of infectious diseases [16-18].
observed that maximum temperature below 6.38°C
and above 24.59°Chad positive effects
on the incidence of infectious diarrhea. The minimum temperature below 5.12°C and above 24.03°Chad
positive effects on the incidence of infectious diarrhea. Our results suggested
that the effects of maximum temperature and minimum temperature were similar.
High and low temperatures were associated with an increasing number of
infectious diarrhea cases. The following are the possible reasons for this
phenomenon. Firstly, the possible etiological and meteorological explanations
might be that temperature influences the replication and activity of pathogens.
For example, the stability of rotavirus is higher under low temperature and it
allows rotavirus to survive longer in contaminated environment, providing more
opportunities of virus transmission and infection. The highest level of rotavirus
was occurred in the colder and drier months, and the rotavirus infectivity was
weaker at 37°C than 4°C or 20°C
. Moreover, food poisoning which was caused
by bacteria such as Vibrio parahaemolyticus and Salmonella,
was common in summer, because food was easy to be rotten in high temperature . A 1°C
increase in temperature was associated with a 10.6% increased risk of bacillary
dysentery . Secondly, in winter, people
usually stay indoors to keep warm and avoid low temperature, providing more
chances for person-to-person contacts and rotavirus spread via fecal-oral route
and contaminated surfaces in closed environment .
found that precipitation above 7.40 mm had a positive effect on the incidence
of infectious diarrhea. More precipitation was associated with an increased
risk of infectious diarrhea caused by Vibrio parahaemolyticus. Increased precipitation
exerts an effect on the survival and transmission of waterborne disease
pathogens and leads to a lack of clean water and food supply . Because of contamination of the water
distribution systems, more precipitation can trigger higher risk of diarrhea
outbreaks . Excess precipitation is
positively associated with risk of infectious diarrhea in Beijing , Fiji , Taiwan
 and Bangladesh .
There are three possible mechanisms in which increased precipitation might
influence the quality of water supply and hence the risk of infectious diarrhea
outbreaks. Firstly, increased risk of sewer overflows caused by more
precipitation might result in water supply contamination . Secondly, excess precipitation will increase the
runoff of manure and animal excreta on soil and surface, leading to higher
waterborne pathogen concentrations in surface water [34,35].
Thirdly, excess precipitation increases turbulences and sediment resuspension,
leading to wide distributions of accumulated pathogens [36,37].
Moreover, precipitation below 1.48 mm also had a positive effect on the
incidence of infectious diarrhea. Less precipitation in winter and spring was
associated with more infectious diarrhea cases caused by rotavirus. And the
infectivity of rotavirus was increased by 0.3% when the precipitation had a
decrease of 10 mm .
limitations should be acknowledged. Firstly, although there have been large
improvements in the reporting of NDSS, under-reporting is an inevitable issue
in the surveillance of infectious diarrhea .
Because of its prosperous economic, yangpu district has a large number of
mobile populations, such as tourists or individuals who are on a business trip
for a short period of time. Some individuals with mild symptoms might do not go
to the hospital or take medicine by themselves. To a certain extent, the NDSS
includes the surveillance information of these mobile populations, but it is
difficult to avoid the missing data. Under-reporting would weaken the
assessment of the association between meteorological factors and infectious
diarrhea incidence. Secondly, lack of complete microbiological etiology might
limit the evaluation of effect of meteorological variables on each class of
infectious diarrhea. Thirdly, the multicollinearity caused by significant
correlations among some meteorological variables, such as a positive
correlation between temperature and precipitation, might result in the
instability of model parameters.
conclusion, our study suggested that residents in Yangpu district of Shanghai
had a relatively low risk of infectious diarrhea. The average annual crude
incidence rate, the peak time and the pathogen spectrums of infectious diarrhea
cases were distinct between different age groups. In 0-4-year-old patients, rotavirus
was the dominant pathogen. And Vibrio parahemolyticus was the predominant
bacterial pathogen in 5-year-old or older patients. High temperature and excess
precipitation had positive effects on the incidence of infectious diarrhea
caused by Vibrio
parahemolyticusin 5-year-old or older
people. Low temperature and little precipitation had positive effects on the
incidence of infectious diarrhea caused by rotavirus in
0-4-year-old children. Our findings have suggested that meteorological factors
can impact the incidence of infectious diarrhea, and might be references for
the prophylaxis and control of infectious diarrhea in urban areas of developing