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Institution

Chinese Center for Disease Control and Prevention

GovernmentBeijing, China
About: Chinese Center for Disease Control and Prevention is a government organization based out in Beijing, China. It is known for research contribution in the topics: Population & Acquired immunodeficiency syndrome (AIDS). The organization has 16037 authors who have published 15098 publications receiving 423452 citations. The organization is also known as: China CDC & CCDC.


Papers
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Journal ArticleDOI
TL;DR: A substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030s and 2050s is predicted, considering land use changes and urbanization simultaneously.
Abstract: Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

102 citations

Journal ArticleDOI
01 Mar 2021-Talanta
TL;DR: RT-dPCR is highly accurate method and suitable for detection of pharyngeal swab samples from COVID-19 suspected patients and patients under isolation and observation who may not be exhibiting clinical symptoms.

102 citations

Journal ArticleDOI
TL;DR: Interactions between high temperature and PM10 and O3 in the effects on non-accidental and cardiovascular mortality were observed: low temperature modified the effects of air pollutants but not in a consistent fashion: the effect of PM10 oncardiovascular mortality was diminished but the association between O3 and non- Accidental mortality was strengthened.

102 citations

Journal ArticleDOI
TL;DR: Swine feedlot wastewater could become a source of chloramphenicol-resistance genes, which could then lead to the spread of antibiotic resistance and eventually pose a risk to public health.
Abstract: Chloramphenicol-resistance genes could be propagated to the surrounding environment via agricultural application of swine waste. This study investigated the potential risks of chloramphenicol-resistance genes from swine feedlots and their surrounding environment. We applied a culture-independent method to investigate levels of chloramphenicol-resistance genes in the wastewater from swine feedlots and the correspondingly impacted agricultural fields in Beijing. The cmlA, floR, fexA, cfr, and fexB genes were present in all samples, with the highest absolute concentrations of 1.50 × 106 copies/g in soil and 6.69 × 106 copies/mL in wastewater. The concentration of chloramphenicol residue was determined by ultra performance liquid chromatography-electrospray tandem mass spectrometry (UPLC-MS/MS), with the highest concentrations of 0.83 ng/g in soil and 11.5 ng/mL in wastewater. Significant correlations were found between chloramphenicol-resistance genes and chloramphenicol residues (r = 0.79, p = 0.0008) as we...

102 citations

Journal ArticleDOI
TL;DR: It is hypothesized that an ancestor of phylogroup A SEOV variants was first exported from China to Europe and then spread through the New World following the migration of Norway rats, and may have arisen only within the last several centuries.
Abstract: Despite the worldwide distribution, most of the known Seoul viruses (SEOV) are closely related to each other. In this study, the M and the S segment sequences of SEOV were recovered from 130 lung tissue samples (mostly of Norway rats) and from six patient serum samples by reverse transcription-PCR. Genetic analysis revealed that all sequences belong to SEOV and represent 136 novel strains. Phylogenetic analysis of all available M and S segment sequences of SEOV, including 136 novel Chinese strains, revealed four distinct groups. All non-Chinese SEOV strains and most of the Chinese variants fell into the phylogroup A, while the Chinese strains originating from mountainous areas clustered into three other distinct groups (B, C, and D). We estimated that phylogroup A viruses may have arisen only within the last several centuries. All non-Chinese variants appeared to be directly originated from China. Thus, phylogroup A viruses distributed worldwide may share a recent ancestor, whereas SEOV seems to be as diversified genetically as other hantaviruses. In addition, all available mitochondrial DNA (mtDNA) sequences of Norway rats, including our 44 newly recovered mtDNA sequences, were divided into two phylogenetic groups. The first group, which is associated with the group A SEOV variants, included most of rats from China and also all non-Chinese rats, while the second group consisted of a few rats originating only from mountain areas in China. We hypothesize that an ancestor of phylogroup A SEOV variants was first exported from China to Europe and then spread through the New World following the migration of Norway rats.

102 citations


Authors

Showing all 16076 results

NameH-indexPapersCitations
Richard Peto183683231434
Barry M. Popkin15775190453
Jian Yang1421818111166
Edward C. Holmes13882485748
Jian Li133286387131
Shaobin Wang12687252463
Elaine Holmes11956058975
Jian Liu117209073156
Sherif R. Zaki10741740081
Jun Yang107209055257
Nan Lin10568754545
Li Chen105173255996
Ming Li103166962672
George F. Gao10279382219
Tao Li102248360947
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20235
202283
20211,490
20201,678
20191,244
20181,041