Since the discovery of Legionnaires’ disease (LD), limited progress has been made in understanding the epidemiology of sporadic cases of LD. Outbreaks have confirmed that air conditioning and potable water systems can be sources of community-acquired LD. However, studying the association between water quality and LD incidence has been challenging due to the heterogeneity of water systems across large geographic areas. Furthermore, although seasonal trends in incidence have been linked to increased rainfall and temperatures, the large geographic units have posed similar difficulties. To address this issue, a retrospective ecological study was conducted in Washington, DC, from 2001 to 2019. The study identified aseasonal pattern of LD incidence, with the majority of cases occurring between June and December, peaking in August, October, and November. Increased temperature was found to be associated with LD incidence. In surface water, higher concentrations of manganese, iron, and strontium were positively associated with LD, while aluminum and orthophosphate showed a negative association. Intreatment plant water, higher concentrations of total organic carbon, aluminum, barium, and chlorine were positively associated with LD, while strontium, zinc, and orthophosphate showed a negative association. The results for orthophosphates and turbidity were inconclusive, indicating the need for further research.

The article aims to estimate and forecast the transmissibility of shigellosis and explore the association of meteorological factors with shigellosis. The mathematical model named Susceptible–Exposed–Symptomatic/Asymptomatic–Recovered–Water/Food (SEIARW) was used to explore the feature of shigellosis transmission based on the data of Wuhan City, China, from 2005 to 2017. The study applied effective reproduction number (Reff) to estimate the transmissibility. Daily meteorological data from 2008 to 2017 were used to determine Spearman's correlation with reported new cases and Reff. The SEIARW model fit the data well (χ2 = 0.00046, p > 0.999). The simulation results showed that the reservoir-to-person transmission of the shigellosis route has been interrupted. The Reff would be reduced to a transmission threshold of 1.00 (95% confidence interval (CI) 0.82–1.19) in 2035. Reducing the infectious period to 11.25 days would also decrease the value of Reff to 0.99. There was a significant correlation between new cases of shigellosis and atmospheric pressure, temperature, wind speed and sun hours per day. The correlation coefficients, although statistically significant, were very low (<0.3). In Wuhan, China, the main transmission pattern of shigellosis is person-to-person. Meteorological factors, especially daily atmospheric pressure and temperature, may influence the epidemic of shigellosis.

Bacterial dysentery (BD) brings a major disease burden to developing countries. Exploring the influence of temperature and its interaction with other meteorological factors on BD is significant for the prevention and early warning of BD in the context of climate change. Daily BD cases and meteorological data from 2008 to 2018 were collected in all nine prefecture-level cities in Jilin Province. A one-stage province-level model and a two-stage city-specific multivariate meta-pooled level distributed lag non-linear model were established to explore the correlation between temperature and BD, then the weather-stratified generalised additive model was used to test the interaction. During the study period, a total of 26 971 cases of BD were developed. The one-stage and two-stage cumulative dose-response ‘J’ curves overlapped, and results showed a positive correlation between temperature and BD with a 1–6 days lag effect. Age group ⩾5 years was found to be more sensitive to the effects. Moreover, there was a significant interaction between temperature, humidity and precipitation (P = 0.004, 0.002, respectively) on BD under high temperature (>0 °C), reminding residents and policymakers to pay attention to the prevention of BD in situations with both high temperature and humidity, high temperature and precipitation during the temperate monsoon climate.

This study proposed a novel ensemble analysis strategy to improve hand, foot and mouth disease (HFMD) prediction by integrating environmental data. The approach began by establishing a vector autoregressive model (VAR). Then, a dynamic Bayesian networks (DBN) model was used for variable selection of environmental factors. Finally, a VAR model with constraints (CVAR) was established for predicting the incidence of HFMD in Chengdu city from 2011 to 2017. DBN showed that temperature was related to HFMD at lags 1 and 2. Humidity, wind speed, sunshine, PM10, SO2 and NO2 were related to HFMD at lag 2. Compared with the autoregressive integrated moving average model with external variables (ARIMAX), the CVAR model had a higher coefficient of determination (R2, average difference: + 2.11%; t = 6.2051, P = 0.0003 < 0.05), a lower root mean-squared error (−24.88%; t = −5.2898, P = 0.0007 < 0.05) and a lower mean absolute percentage error (−16.69%; t = −4.3647, P = 0.0024 < 0.05). The accuracy of predicting the time-series shape was 88.16% for the CVAR model and 86.41% for ARIMAX. The CVAR model performed better in terms of variable selection, model interpretation and prediction. Therefore, it could be used by health authorities to identify potential HFMD outbreaks and develop disease control measures.

Cellulitis is a common infection of the skin and soft tissue. Susceptibility to cellulitis is related to microorganism virulence, the host immunity status and environmental factors. This retrospective study from 2001 to 2013 investigated relationships between the monthly incidence rate of cellulitis and meteorological factors using data from the Taiwanese Health Insurance Dataset and the Taiwanese Central Weather Bureau. Meteorological data included temperature, hours of sunshine, relative humidity, total rainfall and total number of rainy days. In otal, 195 841 patients were diagnosed with cellulitis and the incidence rate was strongly correlated with temperature (γS = 0.84, P < 0.001), total sunshine hours (γS = 0.65, P < 0.001) and total rainfall (γS = 0.53, P < 0.001). The incidence rate of cellulitis increased by 3.47/100 000 cases for every 1° elevation in environmental temperature. Our results may assist clinicians in educating the public of the increased risk of cellulitis during warm seasons and possible predisposing environmental factors for infection.

The seasonality of individual influenza subtypes/lineages and the association of influenza epidemics with meteorological factors in the tropics/subtropics have not been well understood. The impact of the 2009 H1N1 pandemic on the prevalence of seasonal influenza virus remains to be explored. Using wavelet analysis, the periodicities of A/H3N2, seasonal A/H1N1, A/H1N1pdm09, Victoria and Yamagata were identified, respectively, in Panzhihua during 2006–2015. As a subtropical city in southwestern China, Panzhihua is the first industrial city in the upper reaches of the Yangtze River. The relationship between influenza epidemics and local climatic variables was examined based on regression models. The temporal distribution of influenza subtypes/lineages during the pre-pandemic (2006–2009), pandemic (2009) and post-pandemic (2010–2015) years was described and compared. A total of 6892 respiratory specimens were collected and 737 influenza viruses were isolated. A/H3N2 showed an annual cycle with a peak in summer–autumn, while A/H1N1pdm09, Victoria and Yamagata exhibited an annual cycle with a peak in winter–spring. Regression analyses demonstrated that relative humidity was positively associated with A/H3N2 activity while negatively associated with Victoria activity. Higher prevalence of A/H1N1pdm09 and Yamagata was driven by lower absolute humidity. The role of weather conditions in regulating influenza epidemics could be complicated since the diverse viral transmission modes and mechanism. Differences in seasonality and different associations with meteorological factors by influenza subtypes/lineages should be considered in epidemiological studies in the tropics/subtropics. The development of subtype- and lineage-specific prevention and control measures is of significant importance.

Since the late 1990s, hand, foot and mouth disease (HFMD) has become a common health problem that mostly affects children and infants in Southeast and East Asia. Global climate change is considered to be one of the major risk factors for HFMD. This study aimed to assess the correlation between meteorological factors and HFMD in the Asia-Pacific region. PubMed, Web of Science, Embase, China National Knowledge Infrastructure, Wanfang Data and Weipu Database were searched to identify relevant articles published before May 2018. Data were collected and analysed using R software. We searched 2397 articles and identified 51 eligible papers in this study. The present study included eight meteorological factors; mean temperature, mean highest temperature, mean lowest temperature, rainfall, relative humidity and hours of sunshine were positively correlated with HFMD, with correlation coefficients (CORs) of 0.52 (95% confidence interval (CI) 0.42–0.60), 0.43 (95% CI 0.23–0.59), 0.43 (95% CI 0.23–0.60), 0.27 (95% CI 0.19–0.35), 0.19 (95% CI 0.02–0.35) and 0.19 (95% CI 0.11–0.27), respectively. There were sufficient data to support a negative correlation between mean pressure and HFMD (COR = −0.51, 95% CI −0.63 to −0.36). There was no notable correlation with wind speed (COR = 0.10, 95% CI −0.03 to 0.23). Our findings suggest that meteorological factors affect the incidence of HFMD to a certain extent.

Hand, foot and mouth disease (HFMD) risk has become an increasing concern in the Beijing–Tianjin–Hebei region, which is the biggest urban agglomeration in north-eastern Asia. In the study, spatiotemporal epidemiological features of HFMD were analysed, and a Bayesian space–time hierarchy model was used to detect local spatial relative risk (RR) and to assess the effect of meteorological factors. From 2009 to 2013, there was an obvious seasonal pattern of HFMD risk. The highest risk period was in the summer, with an average monthly incidence of 4·17/103, whereas the index in wintertime was 0·16/103. Meteorological variables influenced temporal changes in HFMD. A 1 °C rise in air temperature was associated with an 11·5% increase in HFMD (corresponding RR 1·122). A 1% rise in relative humidity was related to a 9·51% increase in the number of HFMD cases (corresponding RR 1·100). A 1 hPa increment in air pressure was related to a 0·11% decrease in HFMD (corresponding RR 0·999). A 1 h increase in sunshine was associated with a 0·28% rise in HFMD cases (corresponding RR 1·003). A 1 m/s rise in wind speed was related to a 6·2% increase in HFMD (corresponding RR 1·064). High-risk areas were mainly large cities, such as Beijing, Tianjin, Shijiazhuang and their neighbouring areas. These findings can contribute to risk control and implementation of disease-prevention policies.

Dengue fever (DF) is the most prevalent and rapidly spreading mosquito-borne disease globally. Control of DF is limited by barriers to vector control and integrated management approaches. This study aimed to explore the potential risk factors for autochthonous DF transmission and to estimate the threshold effects of high-order interactions among risk factors. A time-series regression tree model was applied to estimate the hierarchical relationship between reported autochthonous DF cases and the potential risk factors including the timeliness of DF surveillance systems (median time interval between symptom onset date and diagnosis date, MTIOD), mosquito density, imported cases and meteorological factors in Zhongshan, China from 2001 to 2013. We found that MTIOD was the most influential factor in autochthonous DF transmission. Monthly autochthonous DF incidence rate increased by 36·02-fold [relative risk (RR) 36·02, 95% confidence interval (CI) 25·26–46·78, compared to the average DF incidence rate during the study period] when the 2-month lagged moving average of MTIOD was >4·15 days and the 3-month lagged moving average of the mean Breteau Index (BI) was ⩾16·57. If the 2-month lagged moving average MTIOD was between 1·11 and 4·15 days and the monthly maximum diurnal temperature range at a lag of 1 month was <9·6 °C, the monthly mean autochthonous DF incidence rate increased by 14·67-fold (RR 14·67, 95% CI 8·84–20·51, compared to the average DF incidence rate during the study period). This study demonstrates that the timeliness of DF surveillance systems, mosquito density and diurnal temperature range play critical roles in the autochthonous DF transmission in Zhongshan. Better assessment and prediction of the risk of DF transmission is beneficial for establishing scientific strategies for DF early warning surveillance and control.

Hand, foot, and mouth disease (HFMD) has caused public health concerns worldwide. We aimed to investigate the effect of meteorological factors on the HFMD epidemic in Qingdao, a port city in China. A total of 78641 cases were reported in Qingdao between January 2007 and December 2014. Of those, 71084 (90·39%) occurred in children aged 0–5 years, with an incidence of 1691·2/100000. The incidence increased from early spring, peaked between spring and summer, and decreased in late summer. Aetiological agents in all severe cases and selected mild cases were characterized by examining throat swabs. Except for enterovirus 71 (EV71) and coxsackievirus A16 (CA16), other EVs caused >50% of the HFMD cases between 2011 and 2014. EV71 was more frequent in the off-peak months than in the peak months and prone to causing more severe cases compared to CA16 (χ2 = 46·3, P < 0·001). CA10 caused more severe HFMD than did CA6 (χ2 = 20·49, P < 0·001) and all non-CA10 EVs (χ2 = 41·01, P < 0·001). Community-derived HFMD cases accounted for 65·11%. Spearman rank correlation analysis showed that HFMD incidence in children aged 0–5 years was positively correlated with atmospheric temperature (rs = 0·77, P < 0·001), relative humidity (rs = 0·507, P < 0·001), and precipitation (rs = 0·328, P < 0·001). Climate changes and CA10 surveillance in communities should be integrated into the current prophylactic programme.

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.

Varicella accounts for substantial morbidities and remains a public health issue worldwide, especially in children. Little is known about the effect of meteorological variables on varicella infection risk for children. This study described the epidemiology of paediatric varicella notifications in Hong Kong from 2004 to 2010, and explored the association between paediatric varicella notifications in children aged <18 years and various meteorological factors using a time-stratified case-crossover model, with adjustment of potential confounding factors. The analysis found that daily mean temperature, atmospheric pressure and Southern Oscillation Index (SOI) were positively associated with paediatric varicella notifications. We found that an interquartile range (IQR) increase in temperature (8·38°C) at lag 1 day, a 9·50 hPa increase in atmospheric pressure for the current day, and a 21·91 unit increase in SOI for the current day may lead to an increase in daily cases of 5·19% [95% confidence interval (CI) 1·90–8·58], 5·77% (95% CI 3·01–8·61), and 4·32% (95% CI 2·98–5·68), respectively. An IQR increase in daily relative humidity (by 11·96%) was associated with a decrease in daily paediatric varicella (−2·79%, 95% CI −3·84 to −1·73). These findings suggest that meteorological factors might be important predictors of paediatric varicella infection in Hong Kong.

The aim of this study was to determine whether certain weather variables influence the secondary post-tonsillectomy haemorrhage rate and to examine the influence of a change in these variables on secondary haemorrhage. This was a prospective study carried out in a tertiary referral institution. All patients undergoing bilateral tonsillectomy over a one-year period were included. Local weather data, including daily temperature (max/min), relative humidity and water vapour pressure, were acquired. All patients readmitted to our department with secondary post-tonsillectomy haemorrhage were recorded. Of 346 patients undergoing tonsillectomy, 32 developed secondary haemorrhage (9.2 per cent). A significant negative correlation was found between secondary haemorrhage rate and the average monthly temperature (max/min) and water vapour pressure (Pearson’s correlation = −0.8) (p ≤ 0.002). These results suggest that performing tonsillectomy in warmer weather when the water vapour pressure is higher may reduce the secondary haemorrhage rate.