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Systematic evaluations of the cumulative effects and mortality displacement of ambient particulate matter (PM) pollution on deaths are lacking. We aimed to discern the cumulative effect profile of PM exposure, and investigate the presence of mortality displacement in a large-scale population. We conducted a time-series analysis with different exposure-lag models on 13 cities in Jiangsu, China, to estimate the effects of PM pollution on non-accidental, cardiovascular, and respiratory mortality (2015–2019). Over-dispersed Poisson generalized additive models were integrated with distributed lag models to estimate cumulative exposure effects, and assess mortality displacement. Pooled cumulative effect estimates with lags of 0–7 and 0–14 days were substantially larger than those with single-day and 2-day moving average lags. For each 10 μg/m3 increment in PM 2.5 concentration with a cumulative lag of 0–7 days, we estimated an increase of 0.50 % (95 % CI: 0.29, 0.72), 0.63 % (95 % CI: 0.38, 0.88), and 0.50 % (95 % CI: 0.01, 1.01) in pooled estimates of non-accidental, cardiovascular, and respiratory mortality, respectively. Both PM 10 and PM 2.5 were associated with significant increases in non-accidental and cardiovascular mortality with a cumulative lag of 0–14 days. We observed mortality displacement within 30 days for non-accidental, cardiovascular, and respiratory deaths. Our findings suggest that risk assessment based on single-day or 2-day moving average lag structures may underestimate the adverse effects of PM pollution. The cumulative effects of PM exposure on non-accidental and cardiovascular mortality can last up to 14 days. Evidence of mortality displacement for non-accidental, cardiovascular, and respiratory deaths was found. • Maximum effect estimates were found at around 1-week cumulative PM exposure. • Cumulative PM exposure over 14 days increases all-cause and cardiovascular deaths. • PM exposure may primarily advance death among the frail subpopulation in China. [ABSTRACT FROM AUTHOR]

Hepatitis E virus (HEV) is a frequently overlooked causative agent of acute hepatitis. Evaluating the long-term durability of hepatitis E vaccine efficacy holds crucial importance. This study was an extension to a randomised, double-blind, placebo-controlled, phase-3 clinical trial of the hepatitis E vaccine conducted in Dontai County, Jiangsu, China. Participants were recruited from 11 townships in Dongtai County. In the initial trial, a total of 112 604 healthy adults aged 16–65 years were enrolled, stratified according to age and sex, and randomly assigned in a 1:1 ratio to receive three doses of hepatitis E vaccine or placebo intramuscularly at month 0, month 1, and month 6. A sensitive hepatitis E surveillance system including 205 clinical sentinels, covering the entire study region, was established and maintained for 10 years after vaccination. The primary outcome was the per-protocol efficacy of hepatitis E virus vaccine to prevent confirmed hepatitis E occurring at least 30 days after administration of the third dose. Throughout the study, the participants, site investigators, and laboratory staff remained blinded to the treatment assignments. This study is registered with ClinicalTrials.gov (NCT01014845). During the 10-year study period from Aug 22, 2007, to Oct 31, 2017, 90 people with hepatitis E were identified; 13 in the vaccine group (0·2 per 10 000 person-years) and 77 in the placebo group (1·4 per 10 000 person-years), corresponding to a vaccine efficacy of 83·1% (95% CI 69·4–91·4) in the modified intention-to-treat analysis and 86·6% (73·0 to 94·1) in the per-protocol analysis. In the subsets of participants assessed for immunogenicity persistence, of those who were seronegative at baseline and received three doses of hepatitis E vaccine, 254 (87·3%) of 291 vaccinees in Qindong at the 8·5-year mark and 1270 (73·0%) of 1740 vaccinees in Anfeng at the 7·5-year mark maintained detectable concentrations of antibodies. Immunisation with this hepatitis E vaccine offers durable protection against hepatitis E for up to 10 years, with vaccine-induced antibodies against HEV persisting for at least 8·5 years. National Natural Science Foundation of China, Fujian Provincial Natural Science Foundation, Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, and the Fundamental Research Funds for the Central Universities. [ABSTRACT FROM AUTHOR]

[Display omitted] The Escherichia coli -produced human papillomavirus (HPV) 16/18 bivalent vaccine (Cecolin) has received prequalification by the World Health Organization based on its high efficacy and good safety profile. We aimed to evaluate the immunogenicity and safety of the second-generation nonavalent HPV 6/11/16/18/31/33/45/52/58 vaccine (Cecolin 9) through the randomized, blinded phase 2 clinical trial. Eligible healthy women aged 18–45 years were randomly (1:1) allocated to receive three doses of 1.0 mL (270 µg) of Cecolin 9 or placebo with a 0-1-6-month schedule. The primary endpoint was the seroconversion rate and geometric mean titer of neutralizing antibodies (nAbs) one month after the full vaccination course (month 7). The secondary endpoint was the safety profile including solicited adverse reactions occurring within 7 d, adverse events (AEs) occurring within 30 d after each dose, and serious adverse events (SAEs) occurring during the 7-month follow-up period. In total, 627 volunteers were enrolled and randomly assigned to Cecolin 9 (n = 313) or placebo (n = 314) group in Jiangsu Province, China. Almost all participants in the per-protocol set for immunogenicity (PPS-I) seroconverted for nAbs against all the nine HPV types at month 7, while two failed to seroconvert for HPV 11 and one did not seroconvert for HPV 52. The incidence rates of total AEs in the Cecolin 9 and placebo groups were 80.8% and 72.9%, respectively, with the majority of them being mild and recovering shortly. None of the SAEs were considered related to vaccination. In conclusion, the E. coli -produced 9-valent HPV (9vHPV) vaccine candidate was well tolerated and immunogenic, which warrants further efficacy studies in larger populations. [ABSTRACT FROM AUTHOR]

Background: The rapid emergence and global spread of COVID-19 have caused substantial global disruptions that have impacted malaria programs worldwide. Innovative strategies to enable countries aiming to eliminate malaria as well as those that are already certified as malaria-free, are needed to address malaria importation in the context of the COVID-19 pandemic. China was certified as malaria-free in 2021 and now aims to prevent the malaria re-establishment. Nonpharmaceutical interventions such as entry screening, quarantining, and health education for individuals returning from international travel during the COVID-19 pandemic present both opportunities and challenges to the management of imported malaria. This study aimed to describe and analyze the operational challenges associated with an integrated surveillance and case management program in which malaria re-establishment prevention measures were incorporated into the COVID-19 program in China.Methods: After the integration of malaria re-establishment prevention activities into the COVID-19 program for 10 months in Jiangsu Province, China, a focus-group discussion of public health workers working on preventing malaria re-establishment and controlling COVID-19 was held in June 2021, aiming to explore the operational challenges and lessons learned from the integrated approach.Results: From 01 August 2020 to 31 May 2021, 8,947 overseas travelers with Yangzhou as the final destination underwent 14-day managed quarantine and 14-day home isolation. Of these travelers, 5,562 were from malaria-endemic regions. A total of 26,026 education booklets and materials were distributed to expand malaria-related knowledge. Twenty-two patients with unknown fever were screened for malaria with rapid diagnostic tests, and one patient was confirmed to have imported malaria. The challenges associated with the implementation of the integrated malaria surveillance and case management program include neglect of malaria due to COVID-19, lack of a standard operating procedure for malaria screening, mobility of public health providers, and difficulties in respecting the timeline of the "1-3-7" surveillance strategy.Conclusions: China's experience highlights the feasibility of integrated case surveillance and management of existing infectious diseases and new emerging infections. It also demonstrates the importance of a sound public health infrastructure with adequate, trained field staff for screening, testing, contact tracing, and providing health education, all of which are crucial for the success of both malaria re-establishment prevention program and the effective control of COVID-19. [ABSTRACT FROM AUTHOR]

Background: The tiller number per unit area is one of the main agronomic components in determining yield. A real-time assessment of this trait could contribute to monitoring the growth of wheat populations or as a primary phenotyping indicator for the screening of cultivars for crop breeding. However, determining tiller number has been conventionally dependent on tedious and labor-intensive manual counting. In this study, an automatic tiller-counting algorithm was developed to estimate the tiller density under field conditions based on terrestrial laser scanning (TLS) data. The novel algorithm, which is named ALHC, involves two steps: (1) the use of an adaptive layering (AL) algorithm for cluster segmentation and (2) the use of a hierarchical clustering (HC) algorithm for tiller detection among the clusters. Three field trials during the 2016–2018 wheat seasons were conducted to validate the algorithm with twenty different wheat cultivars, three nitrogen levels, and two planting densities at two ecological sites (Rugao & Xuzhou) in Jiangsu Province, China. Result: The results demonstrated that the algorithm was promising across different cultivars, years, growth stages, planting densities, and ecological sites. The tests from Rugao and Xuzhou in 2016–2017 and Rugao in 2017–2018 showed that the algorithm estimated the tiller number of the wheat with regression coefficient (R2) values of 0.61, 0.56 and 0.65, respectively. In short, tiller counting with the ALHC generally underestimated the tiller number and performed better for the data with lower plant densities, compact plant types and the jointing stage, which were associated with overlap and noise between plants and inside the dense canopy. Conclusions: Differing from the previous methods, the ALHC proposed in this paper made full use of 3D crop information and developed an automatic tiller counting method that is suitable for the field environment. [ABSTRACT FROM AUTHOR]