Impact of Temperature and Rainfall on Typhoid/Paratyphoid Fever in Taizhou, China: Effect Estimation and Vulnerable Group Identification.

The impact of temperature and rainfall on the occurrence of typhoid/paratyphoid fever are not fully understood. This study aimed to characterize the effect of daily ambient temperature and total rainfall on the incidence of typhoid/paratyphoid in a sub-tropical climate city of China and to identify the vulnerable groups for disease prevention. Daily notified typhoid/paratyphoid fever cases and meteorological data for Taizhou from 2005 to 2013 were extracted from the National Notifiable Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. Distributed lag nonlinear model was used to quantify the association between daily mean temperature, total rainfall, and typhoid/paratyphoid fever. Subgroup analyses by gender, age, and occupation were conducted to identify the vulnerable groups. A total of 625 typhoid fever cases and 1,353 paratyphoid fever cases were reported during the study period. An increased risk of typhoid fever was detected with the increase of temperature (Each 2°C rise resulted in 6%, 95% [confidence interval] CI: 2-10% increase in typhoid cases), while the increased risk was associated with the higher temperature for paratyphoid (the highest cumulative risk of temperature was 33.40 [95% CI: 12.23-91.19] at 33°C). After the onset of mild precipitation, the relative risk of typhoid fever increased in a short-lasting and with a 13-26 days delay, and the risk was no significant after the continuous increase of precipitation (the highest cumulative risk of rainfall was 24.96 [95% CI: 4.54-87.21] at 100 mm). Whereas the risk of paratyphoid fever was immediate and long lasting, and increase rapidly with the increase of rainfall (each 100 mm increase was associated with 26% increase in paratyphoid fever cases). Significant temperature-typhoid/paratyphoid fever and rainfall-typhoid/paratyphoid fever associations were found in both genders and those aged 0-4 years old, 15-60 years old, farmers, and children. Characterized with a lagged, nonlinear, and cumulative effect, high temperature and rainfall could increase the risk of typhoid/paratyphoid fever in regions with a subtropical climate. Public health interventions such as early warning and community health education should be taken to prevent the increased risk of typhoid/paratyphoid fever, especially for the vulnerable groups.

Effect of temperature and its interactions with relative humidity and rainfall on malaria in a temperate city Suzhou, China.

Malaria is a climate-sensitive infectious disease. Many ecological studies have investigated the independent impacts of ambient temperature on malaria. However, the optimal temperature measures of malaria and its interaction with other meteorological factors on malaria transmission are less understood. This study aims to investigate the effect of ambient temperature and its interactions with relative humidity and rainfall on malaria in Suzhou, a temperate climate city in Anhui Province, China. Weekly malaria and meteorological data from 2005 to 2012 were obtained for Suzhou. A distributed lag nonlinear model was conducted to quantify the effect of different temperature measures on malaria. The best measure was defined as that with the minimum quasi-Akaike information criterion. GeoDetector and Poisson regression models were employed to quantify the interactions of temperature, relative humidity, and rainfall on malaria transmission. A total of 13,382 malaria cases were notified in Suzhou from 2005 to 2012. Each 5 °C rise in average temperature over 10 °C resulted in a 22% (95% CI: 17%, 28%) increase in malaria cases at lag of 4 weeks. In terms of cumulative effects from lag 1 to 8 weeks, each 5 °C increase over 10 °C caused a 175% growth in malaria cases (95% CI: 139%, 216%). Average temperature achieved the best performance in terms of model fitting, followed by minimum temperature, most frequent temperature, and maximum temperature. Temperature had an interactive effect on malaria with relative humidity and rainfall. High temperature together with high relative humidity and high rainfall could accelerate the transmission of malaria. Meteorological factors may affect malaria transmission interactively. The research findings could be helpful in the development of weather-based malaria early warning system, especially in the context of climate change for the prevention of possible malaria resurgence.

Public health professionals' perceptions of the capacity of China's CDCs to address emerging and re-emerging infectious diseases.

BACKGROUND: China's capacity to control and prevent emerging and re-emerging infectious diseases is critical to the nation's population health. This study aimed to explore the capacity of Centers for Disease Control and Prevention (CDCs) in China to deal with infectious diseases now and in the future. METHODS: A survey was conducted in 2015 among 973 public health professionals at CDCs in Beijing and four provinces, to assess their capacity to deal with emerging and re-emerging infectious diseases. RESULTS: Although most professionals were confident with the current capacity of CDCs to cope with outbreaks, nearly all indicated more funding was required to meet future challenges. Responses indicated that Yunnan Province faced more challenges than Anhui, Henan and Liaoning Provinces in being completely prepared and able to deal with outbreaks. Participants aged 20-39 years were more likely than those aged 40 and over to believe strategies such as interdisciplinary and international collaborations for disease surveillance and control, would assist capacity building. CONCLUSION: The capacity of China's CDCs to deal with infectious diseases was excellent. However, findings suggest it is imperative to increase the number of skilled CDC staff, financial support, and strengthen county level staff training and health education programs.

Effect of ambient temperatures on category C notifiable infectious diarrhea in China: An analysis of national surveillance data.

BACKGROUND: Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions. METHODS: Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature. RESULTS: A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier. CONCLUSIONS: The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.

Nonlinear and Threshold Effect of Meteorological Factors on Japanese Encephalitis Transmission in Southwestern China.

Although previous studies have reported that meteorological factors might affect the risk of Japanese encephalitis (JE), the relationship between meteorological factors and JE remains unclear. This study aimed to evaluate the relationship between meteorological factors and JE and identify the threshold temperature. Daily meteorological data and JE surveillance data in Dazhou, Sichuan, were collected for the study period from 2005 to 2012 (restricting to May-October because of the seasonal distribution of JE). A distributed lag nonlinear model was used to analyze the lagged and cumulative effect of daily average temperature and daily rainfall on JE transmission. A total of 622 JE cases were reported over the study period. We found JE was positively associated with daily average temperature and daily rainfall with a 25-day lag and 30-day lag, respectively. The threshold value of the daily average temperature is 20°C. Each 5°C increase over the threshold would lead to a 13% (95% CI: 1-17.3%) increase in JE. Using 0 mm as the reference, a daily rainfall of 100 mm would lead to a 132% (95% CI: 73-311%) increase in the risk of JE. Japanese encephalitis is climate-sensitive; meteorological factors should be taken into account for the future prevention and control measure making, especially in a warm and rainy weather condition.

Daily Temperature and Bacillary Dysentery: Estimated Effects, Attributable Risks, and Future Disease Burden in 316 Chinese Cities.

BACKGROUND: Bacillary dysentery (BD) remains a significant public health issue, especially in developing countries. Evidence assessing the risk of BD from temperature is limited, particularly from national studies including multiple locations with different climatic characteristics. OBJECTIVES: We estimated the effect of temperature on BD across China, assessed heterogeneity and attributable risks across cities and regions, and projected the future risk of BD under climate change. METHODS: Daily BD surveillance and meteorological data over 2014-2016 were collected from the Chinese Center for Disease Control and Prevention and the China Meteorology Administration, respectively. A two-stage statistical model was used to estimate city-specific temperature-BD relationships that were pooled to derive regional and national estimates. The risk of BD attributable to temperature was estimated, and the future burden of BD attributable to temperature was projected under different climate change scenarios. RESULTS: A positive linear relationship for the pooled effect was estimated at the national level. Subgroup analyses indicate that the estimated effect of temperature on BD was similar by age (≤5y or >5y) and gender. At baseline, estimated attributable risks for BD due to average daily mean temperatures above the 50th percentile were highest for the Inner Mongolia (16%), Northeast China (14%), and Northern China (13%). Most of the individual cities in the same regions and most of the cities in the Northwest, Southern, and Southwest regions, had high attributable risks (≥5%). The Northern, Northeast, Inner Mongolia, Northwest, and Southern China regions were identified as high risk for future BD, with estimated increases by the 2090s compared with baseline of 20% (95% confidence interval: 11%, 27%), 15% (6%, 20%), 15% (-1%, 22%), 12% (1%, 19%), and 11% (5%, 15%), respectively, under Representative Concentration Pathway 8.5. CONCLUSIONS: The positive association between temperature and BD in different climatic regions of China, and the projection for increased risk due to climate change, support efforts to mitigate future risks. https://doi.org/10.1289/EHP5779.

Characterising the Burden of Work-Related Injuries in South Australia: A 15-Year Data Analysis.

To characterise the burden of work-related injuries in South Australia, workers' compensation claim data were obtained from SafeWork South Australia between 2000 and 2014. Descriptive analyses were performed to investigate the burden of work-related injuries by age, gender, occupation, industry, and nature and mechanism of injury. Dunn's test was used to compare the injury costs and working days lost by industry and occupation. Ordinary linear regression was used to investigate the age-injury cost association. A total of 464,139 workers' compensation claims were reported during the 15-year period in South Australia, with an overall rate of 4.6 claims per 100 employees, resulting in a total of 20,861,001 working days lost and AU$14.9 billion dollars of compensation payment. Between 2000 to 2014, the annual claim rates, compensation payments, working days lost, and number of work-related death reduced by 59.3, 73.8, 87.1, and 78.6 percent, respectively, while the median compensation payment increased by 67.3% from AU$968 to AU$1620. A 1-year increase in age was associated with a 2.1% (Rate Ratio, RR = 1.021, 95% CI: 1.020-1.022) increase in compensation costs and a 1.3% (RR = 1.013, 95% CI: 1.012-1.020) increase in working days lost. Work-related injury rates are declining in most sectors, however some workers, especially young male technicians and labourers in the community services industry, remain at higher risk. Challenges for workers' health and safety include the aging labour force, vehicle incidents, and severe injuries among new and foreign-born workers.

Impact of meteorological factors on hemorrhagic fever with renal syndrome in 19 cities in China, 2005-2014.

This study aims to investigate the associations between meteorological factors and hemorrhagic fever with renal syndrome (HFRS) in 19 cities selected from HFRS high risk areas across different climate zones in three Provinces of China. De-identified daily reports of HFRS in Anhui, Heilongjiang, and Liaoning Provinces for 2005-2014 were obtained from the Chinese Center for Disease Control and Prevention. Daily weather data from each study location were obtained from the China meteorological Data Sharing Service System. Generalised estimating equation models (GEE) were used to quantify the city-specific HFRS-weather associations. Multivariate random-effects meta-regression models were used to pool the city-specific HFRS-weather effect estimates. HFRS showed an overall downward trend during the study period with a slight rebound after 2010. Meteorological factors were significantly associated with HFRS incidence. HFRS was relatively more sensitive to weather variability in subtropical regions (Anhui Province) than in temperate regions (Heilongjiang and Liaoning Provinces). The size of effect estimates and the duration of lagged effects varied by locations. Pooled results of the 19 cities showed that a 1 °C increase in maximum temperature (Tmax) resulted in a 1.6% (95% CI: 1.0%-2.2%) increase in HFRS; a 1 mm increase in weekly precipitation was associated with 0.2% (95%CI: 0.1%-0.3%) increase in HFRS; a 1% increase in average relative humidity was associated with a 0.9% (95%CI: 0.5%-1.2%) increase in HFRS. The lags with the largest effects for Tmax, precipitation, and relative humidity occurred in weeks 29, 22, and 16, respectively. Lagged effects of meteorological factors did not end after an epidemic season but waned gradually in the following 3-4 epidemic seasons. Weather variability plays a significant role in HFRS transmission in China. The long duration of lagged effects indicates the necessity of continuous interventions following the epidemics.

China's capacity of hospitals to deal with infectious diseases in the context of climate change.

OBJECTIVES: Infectious diseases are a major cause of morbidity and mortality in China. The capacity of hospitals to deal with the challenge from emerging and re-emerging infectious diseases due to climate change is of great importance to population health. This study aimed to explore the capacity of hospitals in China to deal with such challenges. METHODS: A cross-sectional questionnaire survey was utilized to gauge information regarding capacity of hospitals to deal with infectious diseases in the context of climate change among 611 clinical professionals whose roles pertained to infectious disease diagnosis, treatment and management in Anhui Province of China. Descriptive analysis and logistic regression analysis were performed on the data. RESULTS: More than 90% of participants believed climate change would have an adverse influence on population health and infectious disease control in China. Most indicated that their hospitals were well prepared for emerging infectious diseases at present, and they considered that logistical support in hospitals (e.g. administrative and maintenance services) should be strengthened for future capacity building. The majority of participants suggested that effective prevention and control measures, more interdisciplinary collaborations, more funding in rural areas for health care, and improved access to facilities enabling online reporting of infectious diseases, were extremely important strategies in building capacity to curb the population health impact of emerging and re-emerging infectious diseases due to climate change in China. CONCLUSIONS: Clinical professionals recognized that climate change will likely increase the transmission of infectious diseases. Although rural health care and hospitals' logistical support need to be improved, most professionals believed their hospitals to be capable of dealing with emerging diseases. They thought that interdisciplinary and cross-regional collaborations, together with necessary resource support (e.g. improved facilities for rural health care) would be important control strategies.

Perceptions of malaria control and prevention in an era of climate change: a cross-sectional survey among CDC staff in China.

BACKGROUND: Though there was the significant decrease in the incidence of malaria in central and southwest China during the 1980s and 1990s, there has been a re-emergence of malaria since 2000. METHODS: A cross-sectional survey was conducted amongst the staff of eleven Centers for Disease Control and Prevention (CDC) in China to gauge their perceptions regarding the impacts of climate change on malaria transmission and its control and prevention. Descriptive analysis was performed to study CDC staff's knowledge, attitudes, perceptions and suggestions for malaria control in the face of climate change. RESULTS: A majority (79.8%) of CDC staff were concerned about climate change and 79.7% believed the weather was becoming warmer. Most participants (90.3%) indicated climate change had a negative effect on population health, 92.6 and 86.8% considered that increasing temperatures and precipitation would influence the transmission of vector-borne diseases including malaria. About half (50.9%) of the surveyed staff indicated malaria had re-emerged in recent years, and some outbreaks were occurring in new geographic areas. The main reasons for such re-emergence were perceived to be: mosquitoes in high-density, numerous imported cases, climate change, poor environmental conditions, internal migrant populations, and lack of health awareness. CONCLUSIONS: This study found most CDC staff endorsed the statement that climate change had a negative impact on infectious disease transmission. Malaria had re-emerged in some areas of China, and most of the staff believed that this can be managed. However, high densities of mosquitoes and the continuous increase in imported cases of malaria in local areas, together with environmental changes are bringing about critical challenges to malaria control in China. This study contributes to an understanding of climate change related perceptions of malaria control and prevention amongst CDC staff. It may help to formulate in-house training guidelines, community health promotion programmes and policies to improve the capacity of malaria control and prevention in the face of climate change in China.

Association between dengue fever incidence and meteorological factors in Guangzhou, China, 2005-2014.

This study aims to (1) investigate the associations between climatic factors and dengue; and (2) identify the susceptible subgroups. De-identified daily dengue cases in Guangzhou for 2005-2014 were obtained from the Chinese Center for Disease Control and Prevention. Weather data were downloaded from the China Meteorological Data Sharing Service System. Distributed lag non-linear models (DLNM) were used to graphically demonstrate the three-dimensional temperature-dengue association. Generalised estimating equation models (GEE) with piecewise linear spline functions were used to quantify the temperature-dengue associations. Threshold values were estimated using a broken-stick model. Middle-aged and older people, people undertaking household duties, retirees, and those unemployed were at high risk of dengue. Reversed U-shaped non-linear associations were found between ambient temperature, relative humidity, extreme wind velocity, and dengue. The optimal maximum temperature (Tmax) range for dengue transmission in Guangzhou was 21.6-32.9°C, and 11.2-23.7°C for minimum temperature (Tmin). A 1°C increase of Tmax and Tmin within these ranges was associated with 11.9% and 9.9% increase in dengue at lag0, respectively. Although lag effects of temperature were observed for up to 141 days for Tmax and 150 days for Tmin, the maximum lag effects were observed at 32 days and 39 days respectively. Average relative humidity was negatively associated with dengue when it exceeded 78.9%. Maximum wind velocity (>10.7m/s) inhibited dengue transmission. Climatic factors had significant impacts on dengue in Guangzhou. Lag effects of temperature on dengue lasted the local whole epidemic season. To reduce the likely increasing dengue burden, more efforts are needed to strengthen the capacity building of public health systems.

Perceptions of capacity for infectious disease control and prevention to meet the challenges of dengue fever in the face of climate change: A survey among CDC staff in Guangdong Province, China.

BACKGROUND: Dengue fever is an important climate-sensitive mosquito-borne viral disease that poses a risk to half the world's population. The disease is a major public health issue in China where in 2014 a major outbreak occurred in Guangdong Province. This study aims to gauge health professionals' perceptions about the capacity of infectious disease control and prevention to meet the challenge of dengue fever in the face of climate change in Guangdong Province, China. METHODS: A cross-sectional questionnaire survey was administered among staff in the Centers for Disease Control and Prevention (CDCs) in Guangdong Province. Data analysis was undertaken using descriptive methods and logistic regression. RESULTS: In total, 260 questionnaires were completed. Most participants (80.7%) thought climate change would have a negative effect on population health, and 98.4% of participants reported dengue fever had emerged or re-emerged in China in recent years. Additionally, 74.9% of them indicated that the capability of the CDCs to detect infectious disease outbreak/epidemic at an early stage was excellent; 86.3% indicated laboratories could provide diagnostic support rapidly; and 83.1% believed levels of current staff would be adequate in the event of a major outbreak. Logistic regression analysis showed higher levels of CDCs were perceived to have better capacity for infectious disease control and prevention. Only 26.8% of participants thought they had a good understanding of climate change, and most (85.4%) thought they needed more information about the health impacts of climate change. Most surveyed staff suggested the following strategies to curb the public health impact of infectious diseases in relation to climate change: primary prevention measures, strengthening the monitoring of infectious diseases, the ability to actively forecast disease outbreaks by early warning systems, and more funding for public health education programs. CONCLUSION: Vigilant disease and vector surveillance, preventive practice and health promotion programs will likely be significant in addressing the threat of dengue fever in the future. Further efforts are needed to strengthen the awareness of climate change among health professionals, and to promote relevant actions to minimize the health burden of infectious diseases in a changing climate. Results will be critical for policy makers facing the current and future challenges associated with infectious disease prevention and control in China.

Infectious Diseases, Urbanization and Climate Change: Challenges in Future China.

China is one of the largest countries in the world with nearly 20% of the world's population. There have been significant improvements in economy, education and technology over the last three decades. Due to substantial investments from all levels of government, the public health system in China has been improved since the 2003 severe acute respiratory syndrome (SARS) outbreak. However, infectious diseases still remain a major population health issue and this may be exacerbated by rapid urbanization and unprecedented impacts of climate change. This commentary aims to explore China's current capacity to manage infectious diseases which impair population health. It discusses the existing disease surveillance system and underscores the critical importance of strengthening the system. It also explores how the growing migrant population, dramatic changes in the natural landscape following rapid urbanization, and changing climatic conditions can contribute to the emergence and re-emergence of infectious disease. Continuing research on infectious diseases, urbanization and climate change may inform the country's capacity to deal with emerging and re-emerging infectious diseases in the future.