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  1. Baha Raja D, Abdul Taib NA, Teo AKJ, Jayaraj VJ, Ting CY
    Int Health, 2023 Jan 03;15(1):37-46.
    PMID: 35265998 DOI: 10.1093/inthealth/ihac005
    BACKGROUND: The computer simulation presented in this study aimed to investigate the effect of contact tracing on coronavirus disease 2019 (COVID-19) transmission and infection in the context of rising vaccination rates.

    METHODS: This study proposed a deterministic, compartmental model with contact tracing and vaccination components. We defined contact tracing effectiveness as the proportion of contacts of a positive case that was successfully traced and the vaccination rate as the proportion of daily doses administered per population in Malaysia. Sensitivity analyses on the untraced and infectious populations were conducted.

    RESULTS: At a vaccination rate of 1.4%, contact tracing with an effectiveness of 70% could delay the peak of untraced asymptomatic cases by 17 d and reduce it by 70% compared with 30% contact tracing effectiveness. A similar trend was observed for symptomatic cases when a similar experiment setting was used. We also performed sensitivity analyses by using different combinations of contact tracing effectiveness and vaccination rates. In all scenarios, the effect of contact tracing on COVID-19 incidence persisted for both asymptomatic and symptomatic cases.

    CONCLUSIONS: While vaccines are progressively rolled out, efficient contact tracing must be rapidly implemented concurrently to reach, find, test, isolate and support the affected populations to bring COVID-19 under control.

  2. Omar K, Baha Raja D, Abdul Taib NA, Rajaram N, Ahmed J, Arvinder-Singh HS, et al.
    Travel Med Infect Dis, 2022;47:102318.
    PMID: 35342008 DOI: 10.1016/j.tmaid.2022.102318
    BACKGROUND: Guided by the best practices adapted from national and international bodies including the World Health Organization (WHO), the Centers for Disease Control (CDC), and the UK Joint Biosecurity Centre (JBC), this paper aims to develop and provide an empirical risk stratification and assessment framework for advancing the safe resumption of global travel during the COVID-19 pandemic.

    METHOD: Variables included in our model are categorized into four pillars: (i) incidence of cases, (ii) reliability of case data, (iii) vaccination, and (iv) variant surveillance. These measures are combined based on weights that reflect their corresponding importance in risk assessment within the context of the pandemic to calculate the risk score for each country. As a validation step, the outcome of the risk stratification from our model is compared against four countries.

    RESULTS: Our model is found to have good agreement with these benchmarked risk designations for 27 out of the top 30 countries with the strongest travel ties to Malaysia (90%). Each factor within this model signifies its importance and can be adapted by governing bodies to address the changing needs of border control policies for the recommencement of international travel.

    CONCLUSION: In practice, the proposed model provides a turnkey solution for nations to manage transmission risk by enabling stakeholders to make informed, evidence-based decisions to minimize fluctuations of imported cases and serves as a structure to support the improvement, planning, and activation of public health control measures.

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