Background: The COVID-19 has caused a sizeable global outbreak and has been declared as a public health emergency of international concern. Sufficient evidence shows that temperature has an essential link with respiratory infectious diseases. The objectives of this study were to describe the exposure-response relationship between ambient temperature, including extreme temperatures, and mortality of COVID-19. Methods: The Poisson distributed lag non-linear model (DLNM) was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020, in Wuhan, China. Results: During the period mentioned above, the average daily number of COVID-19 deaths was approximately 45.2. Poisson distributed lag non-linear model showed that there was a non-linear relationship (U-shape) between the effect of ambient temperature and mortality. With confounding factors controlled, the daily cumulative relative death risk decreased by 12.3% (95% CI [3.4, 20.4%]) for every 1.0 °C increase in temperature. Moreover, the delayed effects of the low temperature are acute and short-term, with the most considerable risk occurring in 5–7 days of exposure. The delayed effects of the high temperature appeared quickly, then decrease rapidly, and increased sharply 15 days of exposure, mainly manifested as acute and long-term effects. Sensitivity analysis results demonstrated that the results were robust. Conclusions: The relationship between ambient temperature and COVID-19 mortality was non-linear. There was a negative correlation between the cumulative relative risk of death and temperature. Additionally, exposure to high and low temperatures had divergent impacts on mortality.

In advanced economies, economic factors have been found to be associated with many health outcomes, including health-related quality of life (HRQL), and people’s health is affected more by income inequality than by absolute income. However, few studies have examined the association of income inequality and absolute income with HRQL in transitional economies using individual data. This paper focuses on the effects of county or district income inequality and absolute income on the HRQL measured by EQ-5D and the differences between rural and urban regions in Shaanxi province, China. Data were collected from the 2008 National Health Service Survey conducted in Shaanxi, China. The EQ-5D index based on Japanese weights was employed as a health indicator. The income inequality was calculated on the basis of self-reported income. The special requirements for complex survey data analysis were considered in the bivariate analysis and linear regression models. The mean of the EQ-5D index was 94.6. The EQ-5D index of people with low income was lower than that in the high-income group (for people in the rural region: 93.2 v 96.1, P < 0.01; for people in the urban region: 95.5 v 96.8, P < 0.01). Compared with people with moderate inequality, the EQ-5D index of those with high inequality was relatively lower (for people living in the rural region: 91.1 v 95.8, P < 0.01; for people living in the urban region: 95.6 v 97.3, P < 0.01). Adjusted by age, gender, education, marital status, employment, medical insurance, and chronic disease, all the coefficients of the low-income group and high income inequality were significantly negative. After stratifying by income group, all the effects of high income inequality remained negative in both income groups. However, the coefficients of the models in the high income group were not statistically significant. Income inequality has damaging effects on HRQL in Shaanxi, China, especially for people with low income. In addition, people living in rural regions were more vulnerable to economic factors.

Immune checkpoint inhibitors (ICIs) are most commonly used for melanoma and non-small cell lung cancer (NSCLC) patients. FAT atypical cadherin 1 (FAT1), which frequently mutates in melanoma and NSCLC. In this study, we aim to investigate the association ofFAT1mutations with ICI response and outcome. We collected somatic mutation profiles and clinical information from ICI-treated 631 melanoma and 109 NSCLC samples, respectively. For validation, a pan-cancer cohort with 1661 patients in an immunotherapy setting was also used. Melanoma and NSCLC samples from the Cancer Genome Atlas were used to evaluate the potential immunologic mechanisms ofFAT1mutations. In melanoma, patients withFAT1mutations had a significantly improved survival outcome than those wild-type patients (HR: 0.67, 95% CI: 0.46–0.97,P = 0.033). An elevated ICI response rate also appeared inFAT1-mutated patients (43.2% vs. 29.2%,P = 0.032). Associations ofFAT1mutations with improved prognosis and ICI response were confirmed in NSCLC patients. In the pan-cancer cohort, the association betweenFAT1mutations and favorable ICI outcome was further validated (HR: 0.74, 95% CI: 0.58–0.96,P = 0.022). Genomic and immunologic analysis showed that a high mutational burden, increased infiltration of immune-response cells, decreased infiltration of immune-suppressive cells, interferon and cell cycle-related pathways were enriched in patients withFAT1mutations. Our study revealed thatFAT1mutations were associated with better immunogenicity and ICI efficacy, which may be considered as a biomarker for selecting patients to receive immunotherapy.

Background: Clonorchissinensis, one of the most important food-borne zoonotic trematodes, remains prevalent in China. Understanding its infection status in animals is crucial for controlling human clonorchiasis. Here we conducted a systematic review and meta-analysis to focus on the spatio-temporal disparities of C.sinensis infection in animals in China. Methods: Data on C.sinensis prevalence in snails, the second intermediate hosts, or animal reservoirs in China were extracted from electronic databases including PubMed, Embase, Web of Science, Chinese Wanfang database, CNKI, VIP, and China Biomedical Literature database. A random-effects meta-analysis model was utilized to estimate the pooled prevalence in each of the above animal hosts. Subgroup analysis and multivariable meta-regression were performed to explore potential sources of heterogeneity across studies and compare the temporal disparity of infection rates between high and low epidemic areas. Scatter plots were used to depict the biogeographical characteristics of regions reporting C.sinensis infection in animals. Results: The overall pooled prevalence of C.sinensis was 0.9% (95% CI: 0.6–1.2%) in snails, 14.2% (12.7–15.7%) in the second intermediate host, and 14.3% (11.4–17.6%) in animal reservoirs. Prevalence in low epidemic areas (with human prevalence < 1%) decreased from 0.6% (0.2–1.2%) before 1990 to 0.0% (0.0–3.6%) after 2010 in snails (P = 0.0499), from 20.3% (15.6–25.3%) to 8.8% (5.6–12.6%) in the second intermediate hosts (P = 0.0002), and from 18.3% (12.7–24.7%) to 4.7% (1.0–10.4%) in animal reservoirs. However, no similar decrease in prevalence was observed in high epidemic areas (with human prevalence ≥ 1.0%). C.sinensis infections were predominantly reported in areas with altitudes below 2346 m and annual cumulative precipitation above 345 mm and were mostly concentrated in eastern China. Conclusions: There are spatio-temporal disparities in the animal infections of C.sinensis in different areas of China. Animal infections are primarily concentrated in regions with low altitude and high precipitation. The results suggest that implementing One Health-based comprehensive measures targeting both humans and animals, especially in high epidemic areas, is essential for successful eradication of C.sinensis in China.