Many studies have investigated heat wave related mortality, but less attention has been given to the health effects of cold spells in the context of global warming. The 2008 cold spell in China provided a unique opportunity to estimate the effects of the 2008 cold spell on mortality in subtropical regions, spatial heterogeneity of the effects, stratification effect and added effects caused by sustained cold days. Thirty-six study communities were selected from 15 provinces in subtropical China. Daily mortality and meteorological data were collected for each community from 2006 to 2010. A distributed lag linear non-linear model (DLNM) with a lag structure of up to 27 days was used to analyze the association between the 2008 cold spell and mortality. Multivariate meta-analyses were used to combine the cold effects across each community. The 2008 cold spell increased mortality by 43.8% (95% CI: 34.8% ~ 53.4%) compared to non-cold spell days with the highest effects in southern and central China. The effects were more pronounced for respiratory mortality (RESP) than for cardiovascular (CVD) or cerebrovascular mortality (CBD), for females more than for males, and for the elderly aged ≥75 years old more than for younger people. Overall, 148,279 excess deaths were attributable to the 2008 cold spell. The cold effect was mainly from extreme low temperatures rather than sustained cold days during this 2008 cold spell. The 2008 cold spell increased mortality in subtropical China, which was mainly attributable to the low temperature rather than the sustained duration of the cold spell. The cold effects were spatially heterogeneous and modified by individual-specific characteristics such as gender and age.

Dengue fever is a severe public heath challenge in south China. A dengue outbreak was reported in Chaozhou city, China in 2015. Intensified interventions were implemented by the government to control the epidemic. However, it is still unknown the degree to which intensified control measures reduced the size of the epidemics, and when should such measures be initiated to reduce the risk of large dengue outbreaks developing? We selected Xiangqiao district as study setting because the majority of the indigenous cases (90.6%) in Chaozhou city were from this district. The numbers of daily indigenous dengue cases in 2015 were collected through the national infectious diseases and vectors surveillance system, and daily Breteau Index (BI) data were reported by local public health department. We used a compartmental dynamic SEIR (Susceptible, Exposed, Infected and Removed) model to assess the effectiveness of control interventions, and evaluate the control effect of intervention timing on dengue epidemic. A total of 1250 indigenous dengue cases was reported from Xiangqiao district. The results of SEIR modeling using BI as an indicator of actual control interventions showed a total of 1255 dengue cases, which is close to the reported number (n = 1250). The size and duration of the outbreak were highly sensitive to the intensity and timing of interventions. The more rigorous and earlier the control interventions implemented, the more effective it yielded. Even if the interventions were initiated several weeks after the onset of the dengue outbreak, the interventions were shown to greatly impact the prevalence and duration of dengue outbreak. This study suggests that early implementation of rigorous dengue interventions can effectively reduce the epidemic size and shorten the epidemic duration.

An international spread of Zika virus (ZIKV) infection has attracted global attention in 2015. The infection also affected Guangdong province, which is located in southern China. Multiple factors, including frequent communication with South America and Southeast Asia, suitable climate (sub-tropical) for the habitat of Aedes species, may increase the risk of ZIKV disease transmission in this region. An analytic hierarchy process (AHP) method was used to develop a semi-quantitative ZIKV risk assessment model. After selecting indicators, we invited experts in related professions to identify the index weight and based on that a hierarchical structure was generated. Then a series of pairwise comparisons were used to determine the relative importance of the criteria. Finally, the optimal model was established to estimate the spatial and seasonal transmission risk of ZIKV. A total of 15 factors that potentially influenced the risk of ZIKV transmission were identified. The factor that received the largest weight was epidemic of ZIKV in Guangdong province (combined weight [CW] =0.37), followed by the mosquito density (CW = 0.18) and the epidemic of DENV in Guangdong province (CW = 0.14). The distribution of 123 districts/counties’ RIs of ZIKV in Guangdong through different seasons were presented, respectively. Higher risk was observed within Pearl River Delta including Guangzhou, Shenzhen and Jiangmen, and the risk is greater in summer and autumn compared to spring and winter.

Background: Several studies have investigated the associations between ambient temperature and years of life lost (YLLs), but few focused on the difference of life loss attributable to temperature among different socioeconomic development levels. Objectives: We investigated the disparity in temperature-YLL rate relationships and life loss per death attributable to nonoptimal temperature in regions with various development levels. Methods: Three hundred sixty-four Chinese counties or districts were classified into 92 high-development regions (HDRs) and 272 low-development regions (LDRs) according to socioeconomic factors of each location using K-means clustering approach. We used distributed lag non-linear models (DLNM) and multivariate meta-analysis to estimate the temperature-YLL rate relationships. We calculated attributable fraction (AF) of YLL and temperature-related average life loss per death to compare mortality burden of temperature between HDRs and LDRs. Stratified analyses were conducted by region, age, sex and cause of death. Results: We found that non-optimal temperatures increased YLL rates in both HDRs and LDRs, but all subgroups in LDRs were more vulnerable. The disparity of cold effects between HDRs and LDRs was significant, while the difference in heat effect was insignificant. The overall AF of non-optimal temperature in LDRs [AF = 12.2, 95% empirical confidence interval (eCI):11.0–13.5%] was higher than that in HDRs (AF = 8.9, 95% eCI: 8.3–9.5%). Subgroups analyses found that most groups in LDRs had greater AFs than that in HDRs. The average life loss per death due to non-optimal temperature in LDRs (1.91 years, 95% eCI: 1.72–2.10) was also higher than that in HDRs (1.32 years, 95% eCI: 1.23–1.41). Most of AFs and life loss per death were caused by moderate cold in both HDRs and LDRs. Conclusions: Mortality burden caused by temperature was more significant in LDRs than that in HDRs, which means that more attention should be paid to vulnerable populations in LDRs in planning adaptive strategies.

Air pollution is now a significant environmental issue in China. To better understand the health impacts of ambient air pollution, this study investigated the potential interaction between PM₁₀ and NO₂ on mortality in Guangzhou, China. Time series data of daily non-accidental mortality and concentrations of PM₁₀ and NO₂ from 2006 to 2010 were collected. Based on generalized additive model, we developed two models (bivariate model and stratified model) to explore the interaction both qualitatively and quantitatively. At lag of 0–2 days, greater interactive effects between PM₁₀ and NO₂ were presented in the graphs. Positive modified effects were also found between the two pollutants on total non-accidental death and cardiovascular death. When the NO₂ concentration was at a high level (>76.14 μg/m³), PM₁₀ showed the greatest excess relative risk percentage (ERR%) for total non-accidental mortality (0.46, 95% CI: 0.13–0.79) and cardiovascular disease mortality (0.61, 95% CI: 0.06–1.16) for each 10 μg/m³ increase. During the period of high PM₁₀ concentration (>89.82 μg/m³), NO₂ demonstrated its strongest effect for total non-accidental mortality (ERR%: 0.92, 95% CI: 0.42–1.42) and cardiovascular disease mortality (ERR%: 1.20, 95% CI: 0.38–2.03). Our results suggest a positive interaction between PM₁₀ and NO₂ on non-accidental mortality in Guangzhou.