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Nova · Professor Researcher · re-ranking top 20…
Mingcan Huang

Mingcan Huang

· 2023 AQET Scholar

University of Washington · Electrical & Computer Engineering

Active 1993–2024

h-index78
Citations22.5k
Papers382160 last 5y
Funding
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Research topics

  • Computer Science
  • Medicine
  • Virology
  • Biology
  • Computer Security
  • Genetics
  • Evolutionary biology
  • Political Science
  • Geography
  • Internal medicine
  • Environmental health
  • Microbiology
  • Gynecology
  • Telecommunications
  • Medical emergency

Selected publications

  • The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

    Science · 2022 · 174 citations

    • Political Science
    • Evolutionary biology
    • Biology

    Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century.

  • Analytical Sensitivity of the Abbott BinaxNOW COVID-19 Ag Card

    Journal of Clinical Microbiology · 2021 · 87 citations

    • Computer Security
    • Computer Science
    • Medicine

    ) value of 29 to 30.

  • Urethral Microbiota in Men: Association of <i>Haemophilus influenzae</i> and <i>Mycoplasma penetrans</i> With Nongonococcal Urethritis

    Clinical Infectious Diseases · 2020 · 57 citations

    • Medicine
    • Internal medicine
    • Microbiology

    BACKGROUND: Nongonococcal urethritis (NGU) is a common syndrome with no known etiology in ≤50% of cases. We estimated associations between urethral bacteria and NGU in men who have sex with men (MSM) and men who have sex with women (MSW). METHODS: Urine was collected from NGU cases (129 MSM, 121 MSW) and controls (70 MSM, 114 MSW) attending a Seattle STD clinic. Cases had ≥5 polymorphonuclear leukocytes on Gram stain plus symptoms or discharge; controls had <5 PMNs, no symptoms, no discharge. NGU was considered idiopathic when Neisseria gonorrhoeae, Chlamydia trachomatis, Mycoplasma genitalium, Trichomonas vaginalis, adenovirus, and herpes simplex virus were absent. The urethral microbiota was characterized using 16S rRNA gene sequencing. Compositional lasso analysis was conducted to identify associations between bacterial taxa and NGU and to select bacteria for targeted qPCR. RESULTS: Among NGU cases, 45.2% were idiopathic. Based on compositional lasso analysis, we selected Haemophilus influenzae (HI) and Mycoplasma penetrans (MP) for targeted qPCR. Compared with 182 men without NGU, the 249 men with NGU were more likely to have HI (14% vs 2%) and MP (21% vs 1%) (both P ≤ .001). In stratified analyses, detection of HI was associated with NGU among MSM (12% vs 3%, P = .036) and MSW (17% vs 1%, P < .001), but MP was associated with NGU only among MSM (13% vs 1%, P = .004). Associations were stronger in men with idiopathic NGU. CONCLUSIONS: HI and MP are potential causes of male urethritis. MP was more often detected among MSM than MSW with urethritis.

  • Cryptic transmission of SARS-CoV-2 in Washington State

    medRxiv (Cold Spring Harbor Laboratory) · 2020 · 86 citations

    • Computer Science
    • Biology
    • Virology

    Following its emergence in Wuhan, China, in late November or early December 2019, the SARS-CoV-2 virus has rapidly spread throughout the world. On March 11, 2020, the World Health Organization declared Coronavirus Disease 2019 (COVID-19) a pandemic. Genome sequencing of SARS-CoV-2 strains allows for the reconstruction of transmission history connecting these infections. Here, we analyze 346 SARS-CoV-2 genomes from samples collected between 20 February and 15 March 2020 from infected patients in Washington State, USA. We found that the large majority of SARS-CoV-2 infections sampled during this time frame appeared to have derived from a single introduction event into the state in late January or early February 2020 and subsequent local spread, strongly suggesting cryptic spread of COVID-19 during the months of January and February 2020, before active community surveillance was implemented. We estimate a common ancestor of this outbreak clade as occurring between 18 January and 9 February 2020. From genomic data, we estimate an exponential doubling between 2.4 and 5.1 days. These results highlight the need for large-scale community surveillance for SARS-CoV-2 introductions and spread and the power of pathogen genomics to inform epidemiological understanding.

  • Cryptic transmission of SARS-CoV-2 in Washington state

    Science · 2020 · 323 citations

    • Computer Science
    • Virology
    • Biology

    After its emergence in Wuhan, China, in late November or early December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus rapidly spread globally. Genome sequencing of SARS-CoV-2 allows the reconstruction of its transmission history, although this is contingent on sampling. We analyzed 453 SARS-CoV-2 genomes collected between 20 February and 15 March 2020 from infected patients in Washington state in the United States. We find that most SARS-CoV-2 infections sampled during this time derive from a single introduction in late January or early February 2020, which subsequently spread locally before active community surveillance was implemented.

Frequent coauthors

  • Keith R. Jerome

    University of Washington

    482 shared
  • Lawrence Corey

    Fred Hutch Cancer Center

    299 shared
  • Anna Wald

    Fred Hutch Cancer Center

    241 shared
  • Alexander L. Greninger

    University of Washington

    240 shared
  • Michael Boeckh

    Fred Hutch Cancer Center

    193 shared
  • Pavitra Roychoudhury

    University of Washington

    191 shared
  • Christine Johnston

    Fred Hutch Cancer Center

    129 shared
  • Amalia Magaret

    University of Washington

    114 shared
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