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Objectives Although the COVID-19 is known to cause by human-to-human transmission, it remains largely unclear whether ambient air pollutants and meteorological parameters could promote its transmission. Methods A retrospective study is conducted to study whether air quality index (AQI), four ambient air pollutants (PM2.5, PM10, NO2 and CO) and five meteorological variables (daily temperature, highest temperature, lowest temperature, temperature difference and sunshine duration) could increase COVID-19 incidence in Wuhan and XiaoGan between Jan 26th to Feb 29th in 2020. Results First, a significant correlation was found between COVID-19 incidence and AQI in both Wuhan (R2 = 0.13, p less then 0.05) and XiaoGan (R2 = 0.223, p less then 0.01). Specifically, among four pollutants, COVID-19 incidence was prominently correlated with PM2.5 and NO2 in both cities. In Wuhan, the tightest correlation was observed between NO2 and COVID-19 incidence (R2 = 0.329, p less then 0.01). In XiaoGan, in addition to the PM2.5 (R2 = 0.117, p less then 0.01) and NO2 (R2 = 0.015, p less then 0.05), a notable correlation was also observed between the PM10 and COVID-19 incidence (R2 = 0.105, p less then 0.05). Moreover, temperature is the only meteorological parameter that constantly correlated well with COVID-19 incidence in both Wuhan and XiaoGan, but in an inverse correlation (p less then 0.05). Conclusions AQI, PM2.5, NO2, and temperature are four variables that could promote the sustained transmission of COVID-19.Methods A priority-setting process (PSP) was launched to define priorities for patient-centered antimicrobial resistance (AMR) surveillance and research in low- and middle-income countries (LMICs). A list of uncertainties related to AMR surveillance in human health was generated using an online survey of stakeholders in LMICs, which asked for unanswered questions about diagnosis, treatment, or prevention of antibiotic resistance. Results A total of 445 respondents generated 1076 questions that were mapped to a final shortlist of 107 questions. The most common theme was the treatment of drug-resistant infections, followed by diagnosis, then prevention, and requests for local AMR data. The most asked question was a request for local AMR data, revealing the lack of basic information in many LMICs to guide actions to tackle AMR. The steering group recommended three research areas to be prioritized for funding in the next five years infection prevention and control in LMICs, improved electronic patient records, starting with laboratory information management systems, and sustainable behavior change among doctors and other health care professionals with a focus on diagnostic stewardship.Objectives The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. Methods We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January-15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. Results We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6-6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3-7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2-1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. Conclusions Early epidemic characteristics are important indicators for the size of the entire epidemic.Next-generation sequencing (NGS) is an emerging method with the potential of pan-pathogen screening. This study described a case of eosinophilic meningitis (EoM) with enzyme-linked immunosorbent assay (ELISA)-negative results for Angiostrongylus cantonensis (A. cantonensis), Trichinella spiralis and Paragonimus westermani and a positive identification of A. cantonensis by NGS in the cerebrospinal fluid.Objective To assess the relevance of urine test (UT), urine culture (UC) and stone culture (SC) for postoperative infections and to investigate the optimal perioperative antibiotic treatment strategy in association with percutaneous nephrolithotomy (PCNL) in patients with renal calculi. Materials and methods Between September 2016 and September 2018 1,060 patients treated with PCNL were included in the study. The results of UT, UC and SC were reviewed. The details of perioperatively administered antibiotics and postoperative infections were recorded. Results A positive UT was associated with an increased incidence of infection; this was also the case in patients with negative UC (p 0.05). The incidence of infection was decreased when pre-operative antibiotics were administered according to the sensitivity pattern based on UC (p less then 0.05). This outcome was particularly evident when the treatment duration exceeded 7 days (p less then 0.05). A positive SC was associated with increased incidence of infection, even if the patient had a negative UC and UT (p less then 0.05). The incidence of infection was significantly decreased when antibiotic treatment was administered based on the results of SC (p less then 0.05). Conclusion Pre-operative prophylaxis with a single-dose antibiotic was sufficient in patients with negative UC, whether UT was positive or negative. Pre-operative treatment with antibiotics according to the bacterial sensitivity pattern should be administered for ≥7 days in patients with positive UC. The postoperative antibiotic treatment strategy should be tailored according to the SC results.Patients with COVID-19 infection have an increased risk of cardiovascular complications and thrombotic events. click here Statins are known for their pleiotropic anti-inflammatory, antithrombotic and immunomodulatory effects. They may have a potential role as adjunctive therapy to mitigate the effects of endothelial dysfunction and dysregulated inflammation in patients with COVID-19 infection.