Time series analysis of Japanese encephalitis and weather in Linyi City, China

Sero-molecular epidemiology of Japanese encephalitis virus in swine population of western Uttar Pradesh, India: Unraveling the geographical expansion of the virus

BACKGROUND & OBJECTIVES

Swine is a good sentinel for forecast of Japanese encephalitis virus (JEV) outbreaks in humans. The present study was envisaged with objectives to know the sero-conversion period of JEV and to assess the prevalence of JEV in swine population of western Uttar Pradesh state of India.

METHODS

A total of 252 swine serum samples were screened using IgM ELISA over the period of one year to determine the sero-conversion rate and compared seasonally to check the transmission peak of virus. Further, 321 swine blood and serum samples were collected from all seven divisions of western Uttar Pradesh to determine prevalence of JEV using real time RT-PCR and ELISA.

RESULTS

Seasonal sero-conversion rate was high during monsoon and post-monsoon (32%) followed by winter (22.91%) and summer (10.71%) seasons. The sero-conversion was observed in all months indicating viral activity throughout the year in the region. The low degree of correlation was found between meteorological variables (day temperature, rainfall) and sero-conversion rate. A total of 52 samples (16.19%) were found positive by real time RT-PCR while sero-positivity of 29.91% was observed using IgG and IgM ELISA(s). The overall prevalence of JEV was 39.25%.

INTERPRETATION & CONCLUSION

The presence of JEV was recorded throughout the year with peak occurrence during monsoon and post-monsoon season indicating that virus has spread its realm to western region of the state. The information generated in the present study will aid in initiating timely vector control measures and human vaccination program to mitigate risk of JEV infection in the region.

Design a protocol to investigate the effects of climate change in vivo

Climate change has a variety of effects on communities and the environment, most of which have been directly addressed, such as floods, droughts, and fires. To date, the impacts of climate change on health in in vivo conditions have not been assessed, and no protocol has been developed in this regard. Therefore, the purpose of the current study is to develop a protocol as well as design and build a pilot to deal with climate change in vivo to show the direct effects of climate change on health. For this purpose, twenty specialists, comprising ten experts active in field climate and 10 experts in field medicine and anatomy, have been consulted to design the proposed exposure protocol using the Delphi method. According to the prepared protocol, an exposure pilot was then designed and built, which provides the climatic conditions for animal exposure with a fully automatic HMI-PLC system. The results showed the average 12:12-h day/night temperature, humidity, and circadian cycle for three consecutive ten-year periods selected for exposure of 1-month-old male rats. The duration of the exposure period is four months, which is equivalent to a ten-year climatic period. This study is a framework and a starting point for examining the effects of climate change on in vivo conditions that have not yet been considered.

Climate Change and Vector-Borne Diseases in China: A Review of Evidence and Implications for Risk Management

Simple Summary

Vector-borne diseases are among the most rapidly spreading infectious diseases and are widespread all around the world. In China, many types of vector-borne diseases have been prevalent in different regions, which is a serious public health problem with significant association with meteorological factors and weather events. Under the background of current severe climate change, the outbreaks and transmission of vector-borne diseases have been proven to be impacted greatly due to rapidly changing weather conditions. This study summarizes research progress on the association between climate conditions and all types of vector-borne diseases in China. A total of seven insect-borne diseases, two rodent-borne diseases, and a snail-borne disease were included, among which dengue fever is the most concerning mosquito-borne disease. Temperature, rainfall, and humidity have the most significant effect on vector-borne disease transmission, while the association between weather conditions and vector-borne diseases shows vast differences in China. We also make suggestions about future research based on a review of current studies.

Abstract

Vector-borne diseases have posed a heavy threat to public health, especially in the context of climate change. Currently, there is no comprehensive review of the impact of meteorological factors on all types of vector-borne diseases in China. Through a systematic review of literature between 2000 and 2021, this study summarizes the relationship between climate factors and vector-borne diseases and potential mechanisms of climate change affecting vector-borne diseases. It further examines the regional differences of climate impact. A total of 131 studies in both Chinese and English on 10 vector-borne diseases were included. The number of publications on mosquito-borne diseases is the largest and is increasing, while the number of studies on rodent-borne diseases has been decreasing in the past two decades. Temperature, precipitation, and humidity are the main parameters contributing to the transmission of vector-borne diseases. Both the association and mechanism show vast differences between northern and southern China resulting from nature and social factors. We recommend that more future research should focus on the effect of meteorological factors on mosquito-borne diseases in the era of climate change. Such information will be crucial in facilitating a multi-sectorial response to climate-sensitive diseases in China.

Association between meteorological factors and the prevalence dynamics of Japanese encephalitis

Japanese encephalitis (JE) is an acute infectious disease caused by the Japanese encephalitis virus (JEV) and is transmitted by mosquitoes. Meteorological conditions are known to play a pivotal role in the spread of JEV. In this study, a zero-inflated generalised additive model and a long short-term memory model were used to assess the relationship between the meteorological factors and population density of Culex tritaeniorhynchus as well as the incidence of JE and to predict the prevalence dynamics of JE, respectively. The incidence of JE in the previous month, the mean air temperature and the average of relative humidity had positive effects on the outbreak risk and intensity. Meanwhile, the density of all mosquito species in livestock sheds (DMSL) only affected the outbreak risk. Moreover, the region-specific prediction model of JE was developed in Chongqing by used the Long Short-Term Memory Neural Network. Our study contributes to a better understanding of the JE dynamics and helps the local government establish precise prevention and control measures.

A review of the impact of outdoor and indoor environmental factors on human health in China

The Intergovernmental Panel on Climate Change (IPCC) reported that global climate change has led to the increased occurrence of extreme weather events. In the context of global climate change, more evidence indicates that abnormal meteorological conditions could increase the risk of epidemiological mortality and morbidity. In this study, using a systematic review, we evaluated a total of 175 studies (including 158 studies on outdoor environment and 17 studies on indoor environment) to summarize the impact of outdoor and indoor environment on human health in China using the database of PubMed, Web of Science, the Cochrane Library, and Embase. In particular, we focused on studies about cardiovascular and respiratory mortality and morbidity, the prevalence of digestive system diseases, infectious diseases, and preterm birth. Most of the studies we reviewed were conducted in three of the metropolises of China, including Beijing, Guangzhou, and Shanghai. For the outdoor environment, we summarized the effects of climate change-related phenomena on health, including ambient air temperature, diurnal temperature range (DTR), temperature extremes, and so on. Studies on the associations between temperature and human health accounted for 79.7% of the total studies reviewed. We also screened out 19 articles to explore the effect of air temperature on cardiovascular diseases in different cities in the final meta-analysis. Besides, modern lifestyle involves a large amount of time spent indoors; therefore, indoor environment also plays an important role in human health. Nevertheless, studies on the impact of indoor environment on human health are rarely reported in China. According to the limited reports, adverse indoor environment could impose a high health risk on children.

The Role of Temperature in Transmission of Zoonotic Arboviruses

We reviewed the literature on the role of temperature in transmission of zoonotic arboviruses. Vector competence is affected by both direct and indirect effects of temperature, and generally increases with increasing temperature, but results may vary by vector species, population, and viral strain. Temperature additionally has a significant influence on life history traits of vectors at both immature and adult life stages, and for important behaviors such as blood-feeding and mating. Similar to vector competence, temperature effects on life history traits can vary by species and population. Vector, host, and viral distributions are all affected by temperature, and are generally expected to change with increased temperatures predicted under climate change. Arboviruses are generally expected to shift poleward and to higher elevations under climate change, yet significant variability on fine geographic scales is likely. Temperature effects are generally unimodal, with increases in abundance up to an optimum, and then decreases at high temperatures. Improved vector distribution information could facilitate future distribution modeling. A wide variety of approaches have been used to model viral distributions, although most research has focused on the West Nile virus. Direct temperature effects are frequently observed, as are indirect effects, such as through droughts, where temperature interacts with rainfall. Thermal biology approaches hold much promise for syntheses across viruses, vectors, and hosts, yet future studies must consider the specificity of interactions and the dynamic nature of evolving biological systems.

Risk factors associated with sustained circulation of six zoonotic arboviruses: a systematic review for selection of surveillance sites in non-endemic areas

Arboviruses represent a significant burden to public health and local economies due to their ability to cause unpredictable and widespread epidemics. To maximize early detection of arbovirus emergence in non-endemic areas, surveillance efforts should target areas where circulation is most likely. However, identifying such hotspots of potential emergence is a major challenge. The ecological conditions leading to arbovirus outbreaks are shaped by complex interactions between the virus, its vertebrate hosts, arthropod vector, and abiotic environment that are often poorly understood. Here, we systematically review the ecological risk factors associated with the circulation of six arboviruses that are of considerable concern to northwestern Europe. These include three mosquito-borne viruses (Japanese encephalitis virus, West Nile virus, Rift Valley fever virus) and three tick-borne viruses (Crimean-Congo hemorrhagic fever virus, tick-borne encephalitis virus, and louping-ill virus). We consider both intrinsic (e.g. vector and reservoir host competence) and extrinsic (e.g. temperature, precipitation, host densities, land use) risk factors, identify current knowledge gaps, and discuss future directions. Our systematic review provides baseline information for the identification of regions and habitats that have suitable ecological conditions for endemic circulation, and therefore may be used to target early warning surveillance programs aimed at detecting multi-virus and/or arbovirus emergence.

Time series analysis of mumps and meteorological factors in Beijing, China

Background

Over the past decades there have been outbreaks of mumps in many countries, even in populations that were vaccinated. Some studies suggest that the incidence of mumps is related to meteorological changes, but the results of these studies vary in different regions. To date there is no reported study on correlations between mumps incidence and meteorological parameters in Beijing, China.

Methods

A time series analysis incorporating selected weather factors and the number of mumps cases from 1990 to 2012 in Beijing was performed. First, correlations between meteorological variables and the number of mumps cases were assessed. A seasonal autoregressive integrated moving average model with explanatory variables (SARIMAX) was then constructed to predict mumps cases.

Results

Mean temperature, rainfall, relative humidity, vapor pressure, and wind speed were significantly associated with mumps incidence. After constructing the SARIMAX model, mean temperature at lag 0 (β = 0.016, p < 0.05, 95% confidence interval 0.001 to 0.032) was positively associated with mumps incidence, while vapor pressure at lag 2 (β = ˗0.018, p < 0.05, 95% confidence interval ˗0.038 to ˗0.002) was negatively associated. SARIMAX (1, 1, 1) (0, 1, 1)₁₂ with temperature at lag 0 was the best predictive construct.

Conclusions

The incidence of mumps in Beijing from 1990 to 2012 was significantly correlated with meteorological variables. Combining meteorological variables, a predictive SARIMAX model that could be used to preemptively estimate the incidence of mumps in Beijing was established.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-4011-6) contains supplementary material, which is available to authorized users.

An exploratory model for the non-fatal drowning risks in children in Guangdong, China

Background

Drowning is a leading cause of accidental death in children under 14 years of age in Guangdong, China. We developed a statistical model to classify the risk of drowning among children based on the risk factors.

Methods

A multiple-stage cluster random sampling was employed to select the students in Grades 3 to 9 in two townships in Qingyuan, Guangdong. Questionnaire was a self-reported measure consisting of general information, knowledge, attitudes and activities. A univariate logistic regression model was used to preliminarily select the independent variables at a P value of 0.1 for multivariable model. Three-quarters of the participants were randomly selected as a training sample to establish the model, and the remaining were treated as a testing sample to validate the model.

Results

A total of 8390 children were included in this study, about 12.18% (1013) experienced drowning during the past one year. In the univariate logistic regression model, introvert personality, unclear distributions of water areas on the way to school, and bad relationships with their classmates and families were positively associated with drowning. However, females, older age and lower swimming skills were negatively associated with drowning. After employing the prediction model with these factors to estimate drowning risk of the students in the testing samples, the results of Hosmer-Lemeshow tests showed non-significant differences between the predictive results and actual risk (χ2 = 5.97, P = 0.65).

Conclusions

Male, younger children, higher swimming skills, bad relationship with their classmates and families, introvert personality and unclear distributions of water areas on the way to school were important risk factors of non-fatal drowning among children. The prediction model based on these variables has an acceptable predictive ability.

Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012)

Objectives

Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model.

Methods

A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970–2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE).

Results

Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004–0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009–0.037) displayed the highest prediction accuracy.

Conclusions

The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.

Time Series Analysis of Hemorrhagic Fever with Renal Syndrome: A Case Study in Jiaonan County, China

Exact prediction of Hemorrhagic fever with renal syndrome (HFRS) epidemics must improve to establish effective preventive measures in China. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied to establish a highly predictive model of HFRS. Meteorological factors were considered external variables through a cross correlation analysis. Then, these factors were included in the SARIMA model to determine if they could improve the predictive ability of HFRS epidemics in the region. The optimal univariate SARIMA model was identified as (0,0,2)(1,1,1)₁₂. The R² of the prediction of HFRS cases from January 2014 to December 2014 was 0.857, and the Root mean square error (RMSE) was 2.708. However, the inclusion of meteorological variables as external regressors did not significantly improve the SARIMA model. This result is likely because seasonal variations in meteorological variables were included in the seasonal characteristics of the HFRS itself.

Impact of meteorological changes on the incidence of scarlet fever in Hefei City, China

Studies on scarlet fever with meteorological factors included were few. We aimed to illustrate meteorological factors' effects on monthly incidence of scarlet fever. Cases of scarlet fever were collected from the report of legal infectious disease in Hefei City from 1985 to 2006; the meteorological data were obtained from the weather bureau of Hefei City. Monthly incidence and corresponding meteorological data in these 22 years were used to develop the model. The model of auto regressive integrated moving average with covariates was used in statistical analyses. There was a highest peak from March to June and a small peak from November to January. The incidence of scarlet fever ranges from 0 to 0.71502 (per 10⁵ population). SARIMAX (1,0,0)(1,0,0)₁₂ model was fitted with monthly incidence and meteorological data optimally. It was shown that relative humidity (β = -0.002, p = 0.020), mean temperature (β = 0.006, p = 0.004), and 1 month lag minimum temperature (β = -0.007, p < 0.001) had effect on the incidence of scarlet fever in Hefei. Besides, the incidence in a previous month (AR(β) = 0.469, p < 0.001) and in 12 months before (SAR(β) = 0.255, p < 0.001) was positively associated with the incidence. This study shows that scarlet fever incidence was negatively associated with monthly minimum temperature and relative humidity while was positively associated with mean temperature in Hefei City, China. Besides, the ARIMA model could be useful not only for prediction but also for the analysis of multiple correlations.

Short-term effects of floods on Japanese encephalitis in Nanchong, China, 2007-2012: A time-stratified case-crossover study

This time-stratified case-crossover study aimed to quantify the impact of floods on daily Japanese encephalitis (JE) cases from 2007 to 2012 in Nanchong city of Sichuan Province, China. Using conditional logistic regression analysis, we calculated the odds ratios (ORs) and 95% confidence intervals (CIs) at different lagged days, adjusting for daily average temperature (AT) and daily average relative humidity (ARH). A total of 370 JE cases were notified during the study period, with the median patient age being 4.2years. The seasonal pattern of JE cases clustered in July and August during the study period. Floods were significantly associated with an increased number of JE cases from lag 23 to lag 24, with the strongest lag effect at lag 23 (OR=2.00, 95% CI: 1.14-3.52). Similarly, AT and ARH were positively associated with daily JE cases from lag 0 to lag 8 and from lag 0 to lag 9, respectively. Floods, with AT and ARH, can be used to forecast JE outbreaks in the study area. Based on the results of this study, recommendations include undertaking control measures before the number of cases increases, especially for regions with similar geographic, climatic, and socio-economic conditions as those in the study area.

Nonlinear and threshold of the association between meteorological factors and bacillary dysentery in Beijing, China

Previous studies examining the weather-bacillary dysentery association were of a large time scale (monthly or weekly) and examined the linear relationship without checking the linearity assumption. We examined this association in Beijing at a daily scale based on the exposure-response curves using generalized additive models. Our analyses suggested that there were thresholds for effects of temperature and relative humidity, with an approximately linear effect for temperature >12·5 °C [excess risk (ER) for 1 °C increase: 1·06%, 95% confidence interval (CI) 0·63-1·49 on lag day 3] and for relative humidity >40% (ER for 1% increase: 0·18%, 95% CI 0·12-0·24 at lag day 4); and there were linear effects of rainfall (ER for 1-mm increase: 0·22%, 95% CI 0·12-0·32), negative effects for wind speed (ER: -2·91%, 95% CI -4·28 to -1·52 at lag day 3) and sunshine duration (ER: -0·25% 95% CI -0·43 to -0·07 at lag day 4). This study suggests that there are thresholds for the effects of temperature and relative humidity on bacillary dysentery, and these findings should be considered in its prevention and control programmes.

The potential impact of climate change and ultraviolet radiation on vaccine-preventable infectious diseases and immunization service delivery system

Climate change and solar ultraviolet radiation may affect vaccine-preventable infectious diseases (VPID), the human immune response process and the immunization service delivery system. We systematically reviewed the scientific literature and identified 37 relevant publications. Our study shows that climate variability and ultraviolet radiation may potentially affect VPID and the immunization delivery system through modulating vector reproduction and vaccination effectiveness, possibly influencing human immune response systems to the vaccination, and disturbing immunization service delivery. Further research is needed to determine these affects on climate-sensitive VPID and on human immune response to common vaccines. Such research will facilitate the development and delivery of optimal vaccination programs for target populations, to meet the goal of disease control and elimination.

Short-term effects of meteorological factors on children hand, foot and mouth disease in Guangzhou, China

Hand, foot and mouth disease (HFMD) is a contagious viral illness that commonly affects infants and children. The underlying risk factors have not yet been systematically examined. This study analyzed the short-term effects of meteorological factors on children HFMD in Guangzhou, China. Daily count of HFMD among children younger than 15 years and meteorological variables from 2009 to 2011 were collected to construct the time series. A generalized additive model was applied to estimate the effects of meteorological factors on HFMD occurrence, after adjusting for long-term trend, seasonal trend, day of week, and public holidays. A negative association between temperature and children HFMD occurrence was observed at lag days 1-3, with the relative risk (RR) for a 1 °C increase on lag day 2 being 0.983 (95% confidence intervals (CI) 0.977 to 0.989); positive effect was found for temperature at lag days 5-9, with the highest effect at lag day 6 (RR = 1.014, 95% CI 1.006 to 1.023). Higher humidity was associated with increased HFMD at lag days 3-10, with the highest effect at lag day 8 (RR = 1.009 for 1% increase in relative humidity, 95% CI 1.007 to 1.010). And we also observed significant positive effect for rainfall at lag days 4 and 8 (RR = 1.001, 95% CI 1.000 to 1.002) for 1-mm increase. Subgroup analyses showed that the positive effects of temperature were more pronounced among younger children. This study suggests that meteorological factors might be important predictors of children HFMD occurrence in Guangzhou.

Meteorological factors are associated with hemorrhagic fever with renal syndrome in Jiaonan County, China, 2006-2011

This study examined the effect of meteorological factors on the occurrence of hemorrhagic fever with renal syndrome (HFRS) using a generalized additive model with penalized smoothing splines in Jiaonan, China, from 2006 to 2011. The dose-response relationship was first examined, and then the association between daily meteorological variables and HFRS occurrence was investigated according to the dose-response curves. There were two linear segments in the temperature-HFRS relationship curve. When daily temperature was lower than 17 °C, a positive association was found [with excessive risk (ER) for 1 °C increase on the current day being 2.56 %, 95 % confidence interval (CI): 0.36 % to 4.80 %]. An inverse association was found when daily temperature was higher than 17 °C [ER for 1 °C increase on the current day was -12.82 % (95 % CI: -17.51 % to -7.85 %)]. Inverse associations were observed for relative humidity [ER for 1 % increase on lag day 4 was -1.21 % (95 % CI: -1.63 % to -0.79 %)] and rainfall [ER for 1 mm increase on lag day 1 was -2.20 % (95 % CI: -3.56 % to -0.82 %)]. Meteorological factors might be important predictor of HFRS epidemics in Jiaonan County.

A spatial and temporal analysis of Japanese encephalitis in mainland China, 1963-1975: a period without Japanese encephalitis vaccination

More than a million Japanese encephalitis (JE) cases occurred in mainland China from the 1960s to 1970s without vaccine interventions. The aim of this study is to analyze the spatial and temporal pattern of JE cases reported in mainland China from 1965 to 1973 in the absence of JE vaccination, and to discuss the impacts of climatic and geographical factors on JE during that period. Thus, the data of reported JE cases at provincial level and monthly precipitation and monthly mean temperature from 1963 to 1975 in mainland China were collected. Local Indicators of Spatial Association analysis was performed to identify spatial clusters at the province level. During that period, The epidemic peaked in 1966 and 1971 and the JE incidence reached up to 20.58/100000 and 20.92/100000, respectively. The endemic regions can be divided into three classes including high, medium, and low prevalence regions. Through spatial cluster analysis, JE epidemic hot spots were identified; most were located in the Yangtze River Plain which lies in the southeast of China. In addition, JE incidence was shown to vary among eight geomorphic units in China. Also, the JE incidence in the Loess Plateau and the North China Plain was showed to increase with the rise of temperature. Likewise, JE incidence in the Loess Plateau and the Yangtze River Plain was observed a same trend with the increase of rainfall. In conclusion, the JE cases clustered geographically during the epidemic period. Besides, the JE incidence was markedly higher on the plains than plateaus. These results may provide an insight into the epidemiological characteristics of JE in the absence of vaccine interventions and assist health authorities, both in China and potentially in Europe and Americas, in JE prevention and control strategies.

Japanese encephalitis risk and contextual risk factors in southwest China: a Bayesian hierarchical spatial and spatiotemporal analysis

It is valuable to study the spatiotemporal pattern of Japanese encephalitis (JE) and its association with the contextual risk factors in southwest China, which is the most endemic area in China. Using data from 2004 to 2009, we applied GISmapping and spatial autocorrelation analysis to analyze reported incidence data of JE in 438 counties in southwest China, finding that JE cases were not randomly distributed, and a Bayesian hierarchical spatiotemporal model identified the east part of southwest China as a high risk area. Meanwhile, the Bayesian hierarchical spatial model in 2006 demonstrated a statistically significant association between JE and the agricultural and climatic variables, including the proportion of rural population, the pig-to-human ratio, the monthly precipitation and the monthly mean minimum and maximum temperatures. Particular emphasis was placed on the time-lagged effect for climatic factors. The regression method and the Spearman correlation analysis both identified a two-month lag for the precipitation, while the regression method found a one-month lag for temperature. The results show that the high risk area in the east part of southwest China may be connected to the agricultural and climatic factors. The routine surveillance and the allocation of health resources should be given more attention in this area. Moreover, the meteorological variables might be considered as possible predictors of JE in southwest China.

Safety of Japanese encephalitis live attenuated vaccination in post-marketing surveillance in Guangdong, China, 2005-2012

We reviewed the adverse events following immunization of live attenuated Japanese encephalitis vaccine in Guangdong Province, China. During the period of 2005-2012, 23 million doses of live attenuated Japanese encephalitis vaccine were used and 1426 adverse events were reported (61.24 per million doses); of which, 570 (40%) were classified as allergic reactions (24.48 per million doses), 31 (2%) were neurologic events (1.33 per million doses), and 36 (2.5%) were diagnosed as serious adverse events (1.55 per million doses). This study suggests that the JEV-L has a reasonable safety profile, most adverse events are relatively mild, with relatively rare neurologic events being observed.

Regional impact of climate on Japanese encephalitis in areas located near the three gorges dam

Background

In this study, we aim to identify key climatic factors that are associated with the transmission of Japanese encephalitis virus in areas located near the Three Gorges Dam, between 1997 and 2008.

Methods

We identified three geographical regions of Chongqing, based on their distance from the Three Gorges Dam. Collectively, the three regions consisted of 12 districts from which study information was collected. Zero-Inflated Poisson Regression models were run to identify key climatic factors of the transmission of Japanese encephalitis virus for both the whole study area and for each individual region; linear regression models were conducted to examine the fluctuation of climatic variables over time during the construction of the Three Gorges Dam.

Results

Between 1997 and 2008, the incidence of Japanese encephalitis decreased throughout the entire city of Chongqing, with noticeable variations taking place in 2000, 2001 and 2006. The eastern region, which is closest to the Three Gorges Dam, suffered the highest incidence of Japanese encephalitis, while the western region experienced the lowest incidence. Linear regression models revealed that there were seasonal fluctuations of climatic variables during this period. Zero-Inflated Poisson Regression models indicated a significant positive association between temperature (with a lag of 1 and 3 months) and Japanese encephalitis incidence, and a significant negative association between rainfall (with a lag of 0 and 4 months) and Japanese encephalitis incidence.

Conclusion

The spatial and temporal trends of Japanese encephalitis incidence that occurred in the City of Chongqing were associated with temperature and rainfall. Seasonal fluctuations of climatic variables during this period were also observed. Additional studies that focus on long-term data collection are needed to validate the findings of this study and to further explore the effects of the Three Gorges Dam on Japanese encephalitis and other related diseases.

Identifying high-risk areas of bacillary dysentery and associated meteorological factors in Wuhan, China

Spatial distribution of bacillary dysentery incidence was mapped at the district level in Wuhan, China. And a generalized additive time series model was used to examine the effect of daily weather factors on bacillary dysentery in the high-risk areas, after controlling for potential confounding factors. Central districts were found to be the high-risk areas. The time series analysis found an acute effect of meteorological factors on bacillary dysentery occurrence. A positive association was found for mean temperature (excess risk (ER) for 1°C increase being 0.94% (95% confidence interval (CI): 0.46% to 1.43% on the lag day 2), while a negative effect was observed for relative humidity and rainfall, the ER for 1% increase in relative humidity was −0.21% (95% CI: −0.34% to −0.08%), and the ER for 1 mm increase in rainfall was −0.23% (95% CI: −0.37% to −0.09%). This study suggests that bacillary dysentery prevention and control strategy should consider local weather variations.

The effect of vaccination coverage and climate on Japanese encephalitis in Sarawak, Malaysia

BACKGROUND

Japanese encephalitis (JE) is the leading cause of viral encephalitis across Asia with approximately 70,000 cases a year and 10,000 to 15,000 deaths. Because JE incidence varies widely over time, partly due to inter-annual climate variability effects on mosquito vector abundance, it becomes more complex to assess the effects of a vaccination programme since more or less climatically favourable years could also contribute to a change in incidence post-vaccination. Therefore, the objective of this study was to quantify vaccination effect on confirmed Japanese encephalitis (JE) cases in Sarawak, Malaysia after controlling for climate variability to better understand temporal dynamics of JE virus transmission and control.

METHODOLOGY/PRINCIPAL FINDINGS

Monthly data on serologically confirmed JE cases were acquired from Sibu Hospital in Sarawak from 1997 to 2006. JE vaccine coverage (non-vaccine years vs. vaccine years) and meteorological predictor variables, including temperature, rainfall and the Southern Oscillation index (SOI) were tested for their association with JE cases using Poisson time series analysis and controlling for seasonality and long-term trend. Over the 10-years surveillance period, 133 confirmed JE cases were identified. There was an estimated 61% reduction in JE risk after the introduction of vaccination, when no account is taken of the effects of climate. This reduction is only approximately 45% when the effects of inter-annual variability in climate are controlled for in the model. The Poisson model indicated that rainfall (lag 1-month), minimum temperature (lag 6-months) and SOI (lag 6-months) were positively associated with JE cases.

CONCLUSIONS/SIGNIFICANCE

This study provides the first improved estimate of JE reduction through vaccination by taking account of climate inter-annual variability. Our analysis confirms that vaccination has substantially reduced JE risk in Sarawak but this benefit may be overestimated if climate effects are ignored.

Short-term effect of El Niño-Southern Oscillation on pediatric hand, foot and mouth disease in Shenzhen, China

Hand, foot and mouth disease (HFMD) was an emerging viral infectious disease in recent years in Shenzhen. The underlying risk factors have not yet been systematically examined. This study analyzed the short-term effect of El Niño-Southern Oscillation on pediatric HFMD in Shenzhen, China. Daily count of HFMD among children aged below 15 years old, Southern Oscillation Index (SOI), and weather variables were collected to construct the time series. A distributed lag non-linear model was applied to investigate the effect of daily SOI on pediatric HFMD occurrence during 2008-2010. We observed an acute effect of SOI variation on HFMD occurrence. The extremely high SOI (SOI = 45, with 0 as reference) was associated with increased HFMD, with the relative risk (RR) being 1.66 (95% Confidence Interval [CI]: 1.34-2.04). Further analyses of the association between HFMD and daily mean temperature and relative humidity supported the correlation between pediatric HFMD and SOI. Meteorological factors might be important predictors of pediatric HFMD occurrence in Shenzhen.

Identifying the high-risk areas and associated meteorological factors of dengue transmission in Guangdong Province, China from 2005 to 2011

We examined the spatial distribution pattern and meteorological drivers of dengue fever (DF) in Guangdong Province, China. Annual incidence of DF was calculated for each county between 2005 and 2011 and the geographical distribution pattern of DF was examined using Moran's I statistic and excess risk maps. A time-stratified case-crossover study was used to investigate the short-term relationship between DF and meteorological factors and the Southern Oscillation Index (SOI). High-epidemic DF areas were restricted to the Pearl River Delta region and the Han River Delta region, Moran's I of DF distribution was significant from 2005 to 2006 and from 2009 to 2011. Daily vapour pressure, mean and minimum temperatures were associated with increased DF risk. Maximum temperature and SOI were negatively associated with DF transmission. The risk of DF was non-randomly distributed in the counties in Guangdong Province. Meteorological factors could be important predictors of DF transmission.

Temperature changes between neighboring days and mortality in summer: a distributed lag non-linear time series analysis

BACKGROUND

Many studies have shown that high temperatures or heat waves were associated with mortality and morbidity. However, few studies have examined whether temperature changes between neighboring days have any significant impact on human health.

METHOD

A distributed lag non-linear model was employed to investigate the effect of temperature changes on mortality in summer during 2006-2010 in two subtropical Chinese cities. The temperature change was defined as the difference of the current day's and the previous day's mean temperature.

RESULTS

We found non-linear effects of temperature changes between neighboring days in summer on mortality in both cities. Temperature increase was associated with increased mortality from non-accidental diseases and cardiovascular diseases, while temperature decrease had a protective effect on non-accidental mortality and cardiovascular mortality in both cities. Significant association between temperature changes and respiratory mortality was only found in Guangzhou.

CONCLUSION

This study suggests that temperature changes between neighboring days might be an alternative temperature indicator for studying temperature-mortality relationship.

Climate change and mosquito-borne diseases in China: a review

China has experienced noticeable changes in climate over the past 100 years and the potential impact climate change has on transmission of mosquito-borne infectious diseases poses a risk to Chinese populations. The aims of this paper are to summarize what is known about the impact of climate change on the incidence and prevalence of malaria, dengue fever and Japanese encephalitis in China and to provide important information and direction for adaptation policy making. Fifty-five papers met the inclusion criteria for this study. Examination of these studies indicates that variability in temperature, precipitation, wind, and extreme weather events is linked to transmission of mosquito-borne diseases in some regions of China. However, study findings are inconsistent across geographical locations and this requires strengthening current evidence for timely development of adaptive options. After synthesis of available information we make several key adaptation recommendations including: improving current surveillance and monitoring systems; concentrating adaptation strategies and policies on vulnerable communities; strengthening adaptive capacity of public health systems; developing multidisciplinary approaches sustained by an new mechanism of inter-sectional coordination; and increasing awareness and mobilization of the general public.

Spatial analysis of dengue fever in Guangdong Province, China, 2001-2006

Guangdong Province is the area most seriously affected by dengue fever in China. In this study, we describe the spatial distribution of dengue fever in Guangdong Province from 2001 to 2006 with the objective of informing priority areas for public health planning and resource allocation. Annualized incidence at a county level was calculated and mapped to show crude incidence, excess hazard, and spatial smoothed incidence. Geographic information system-based spatial scan statistics was conducted to detect the spatial distribution pattern of dengue fever incidence at the county level. Spatial scan cluster analyses suggested that counties around Guangzhou City and Chaoshan Region were at increased risk for dengue fever (P < .01). Some spatial clusters of dengue fever were found in Guangdong Province, which allowed intervention measures to be targeted for maximum effect.

Japanese encephalitis: on the One Health agenda

Japanese encephalitis (JE) is one of the most well studied arthropod zoonotic diseases with human and animal research and their integration spanning 6-7 decades. JE research and policy in some Asian countries has epitomized the 'One Health' strategy of attainment of optimal health for people, animals, and the environment. However, despite significant mitigation of JE in some Asian countries primarily due to vaccination programs and infrastructural development, JE continues to be a major disease burden in the Asian region. Arthropod-borne zoonotic infections such as JE present some of the greatest challenges to animal and human health globally. Their emergence involves a complex interplay of vectors, hosts, environment, climate, and anthropogenic factors. Therefore, the integrated management of infectious agents that affect both humans and animals is perhaps the most highly coveted strategy that public health policy makers aspire to attain in the twenty-first century. This is in response to the seemingly growing challenges of controlling the burden of emerging infectious diseases such as shrinking financial budgets and resources, increasing demand for public health deliverables, demographic shifts and mobility, global trade economies, and climate and landscape changes. Thus, while JE research and policy is an excellent example of the One Health strategy in action, further work is required to address the obstinate burden of transmission.