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  1. Lee KW, Chien TW, Yeh YT, Chou W, Wang HY
    Medicine (Baltimore), 2021 Mar 12;100(10):e24749.
    PMID: 33725830 DOI: 10.1097/MD.0000000000024749
    BACKGROUND: During the COVID-19 pandemic, one of the frequently asked questions is which countries (or continents) are severely hit. Aside from using the number of confirmed cases and the fatality to measure the impact caused by COVID-19, few adopted the inflection point (IP) to represent the control capability of COVID-19. How to determine the IP days related to the capability is still unclear. This study aims to (i) build a predictive model based on item response theory (IRT) to determine the IP for countries, and (ii) compare which countries (or continents) are hit most.

    METHODS: We downloaded COVID-19 outbreak data of the number of confirmed cases in all countries as of October 19, 2020. The IRT-based predictive model was built to determine the pandemic IP for each country. A model building scheme was demonstrated to fit the number of cumulative infected cases. Model parameters were estimated using the Solver add-in tool in Microsoft Excel. The absolute advantage coefficient (AAC) was computed to track the IP at the minimum of incremental points on a given ogive curve. The time-to-event analysis (a.k.a. survival analysis) was performed to compare the difference in IPs among continents using the area under the curve (AUC) and the respective 95% confidence intervals (CIs). An online comparative dashboard was created on Google Maps to present the epidemic prediction for each country.

    RESULTS: The top 3 countries that were hit severely by COVID-19 were France, Malaysia, and Nepal, with IP days at 263, 262, and 262, respectively. The top 3 continents that were hit most based on IP days were Europe, South America, and North America, with their AUCs and 95% CIs at 0.73 (0.61-0.86), 0.58 (0.31-0.84), and 0.54 (0.44-0.64), respectively. An online time-event result was demonstrated and shown on Google Maps, comparing the IP probabilities across continents.

    CONCLUSION: An IRT modeling scheme fitting the epidemic data was used to predict the length of IP days. Europe, particularly France, was hit seriously by COVID-19 based on the IP days. The IRT model incorporated with AAC is recommended to determine the pandemic IP.

    Matched MeSH terms: Communicable Disease Control/statistics & numerical data*
  2. Aung MN, Stein C, Chen WT, Garg V, Saraswati Sitepu M, Thu NTD, et al.
    J Infect Dev Ctries, 2021 Aug 31;15(8):1107-1116.
    PMID: 34516418 DOI: 10.3855/jidc.15254
    INTRODUCTION: National strategies to control COVID-19 pandemic consisted mostly of social distancing measures such as lockdowns, curfews, and stay-home guidelines, personal protection such as hand hygiene and mask wearing, as well as contact tracing, isolation and quarantine. Whilst policy interventions were broadly similar across the globe, there were some differences in individual and community responses. This study explored community responses to COVID-19 containment measures in different countries and synthesized a model. This exaplains the community response to pandemic containment measures in the local context, so as to be suitably prepared for future interventions and research.

    METHODOLOGY: A mutlinational study was conducted from April-June 2020 involving researchers from 12 countries (Japan, Austria, U.S., Taiwan, India, Sudan, Indonesia, Malaysia, Philippines, Myanmar, Vietnam and Thailand). Steps in this research consisted of carrying out open-ended questionnaires, qualitative analyses in NVivo, and a multinational meeting to reflect, exchange, and validate results. Lastly, a commuinty response model was synthesized from multinational experiences.

    RESULTS: Effective communication is key in promoting collective action for preventing virus transmission. Health literacy, habits and social norms in different populations are core components of public health interventions. To enable people to stay home while sustaining livelihoods, economic and social support are essential. Countries could benefit from previous pandemic experience in their community response. Whilst contact tracing and isolation are crucial intervention components, issues of privacy and human rights need to be considered.

    CONCLUSIONS: Understanding community responses to containment policies will help in ending current and future pandemics in the world.

    Matched MeSH terms: Communicable Disease Control/statistics & numerical data*
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