Connection

Co-Authors

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This is a "connection" page, showing publications co-authored by Salihu Musa and Daihai He.
Salihu Musa
Connection Strength
3.477
Daihai He
  1. Transmission dynamics of SARS-CoV-2: A modeling analysis with high-and-moderate risk populations. Results Phys. 2021 Jul; 26:104290.
    View in: PubMed
    Score: 0.946
  2. Estimation of exponential growth rate and basic reproduction number of the coronavirus disease 2019 (COVID-19) in Africa. Infect Dis Poverty. 2020 Jul 16; 9(1):96.
    View in: PubMed
    Score: 0.893
  3. Using Proper Mean Generation Intervals in Modeling of COVID-19. Front Public Health. 2021; 9:691262.
    View in: PubMed
    Score: 0.239
  4. Reinfection or Reactivation of Severe Acute Respiratory Syndrome Coronavirus 2: A Systematic Review. Front Public Health. 2021; 9:663045.
    View in: PubMed
    Score: 0.238
  5. High Infection Fatality Rate Among Elderly and Risk Factors Associated With Infection Fatality Rate and Asymptomatic Infections of COVID-19 Cases in Hong Kong. Front Med (Lausanne). 2021; 8:678347.
    View in: PubMed
    Score: 0.237
  6. A conceptual model for the coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China with individual reaction and governmental action. Int J Infect Dis. 2020 Apr; 93:211-216.
    View in: PubMed
    Score: 0.218
  7. Phase-shifting of the transmissibility of macrolide-sensitive and resistant Mycoplasma pneumoniae epidemics in Hong Kong, from 2015 to 2018. Int J Infect Dis. 2019 Apr; 81:251-253.
    View in: PubMed
    Score: 0.203
  8. Shrinkage in serial intervals across transmission generations of COVID-19. J Theor Biol. 2021 11 21; 529:110861.
    View in: PubMed
    Score: 0.060
  9. Estimating the generation interval and inferring the latent period of COVID-19 from the contact tracing data. Epidemics. 2021 09; 36:100482.
    View in: PubMed
    Score: 0.060
  10. Attach importance of the bootstrap t test against Student's t test in clinical epidemiology: a demonstrative comparison using COVID-19 as an example. Epidemiol Infect. 2021 04 30; 149:e107.
    View in: PubMed
    Score: 0.059
  11. Inferencing superspreading potential using zero-truncated negative binomial model: exemplification with COVID-19. BMC Med Res Methodol. 2021 02 10; 21(1):30.
    View in: PubMed
    Score: 0.058
  12. Imitation dynamics in the mitigation of the novel coronavirus disease (COVID-19) outbreak in Wuhan, China from 2019 to 2020. Ann Transl Med. 2020 Apr; 8(7):448.
    View in: PubMed
    Score: 0.055
  13. The basic reproduction number of novel coronavirus (2019-nCoV) estimation based on exponential growth in the early outbreak in China from 2019 to 2020: A reply to Dhungana. Int J Infect Dis. 2020 05; 94:148-150.
    View in: PubMed
    Score: 0.054
  14. Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak. J Clin Med. 2020 Feb 01; 9(2).
    View in: PubMed
    Score: 0.054
  15. Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak. Int J Infect Dis. 2020 Mar; 92:214-217.
    View in: PubMed
    Score: 0.054
  16. Simple framework for real-time forecast in a data-limited situation: the Zika virus (ZIKV) outbreaks in Brazil from 2015 to 2016 as an example. Parasit Vectors. 2019 Jul 12; 12(1):344.
    View in: PubMed
    Score: 0.052
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.