Browsing by Author "Pourghaderi, Ahmad Reza"

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    An Agile Systems Modeling Framework for Bed Resource Planning During COVID-19 Pandemic in Singapore.
    (Frontiers in public health, 2022-01) Lam, Sean Shao Wei; Pourghaderi, Ahmad Reza; Abdullah, Hairil Rizal; Nguyen, Francis Ngoc Hoang Long; Siddiqui, Fahad Javaid; Ansah, John Pastor; Low, Jenny G; Matchar, David Bruce; Ong, Marcus Eng Hock

    Background

    The COVID-19 pandemic has had a major impact on health systems globally. The sufficiency of hospitals' bed resource is a cornerstone for access to care which can significantly impact the public health outcomes.

    Objective

    We describe the development of a dynamic simulation framework to support agile resource planning during the COVID-19 pandemic in Singapore.

    Materials and methods

    The study data were derived from the Singapore General Hospital and public domain sources over the period from 1 January 2020 till 31 May 2020 covering the period when the initial outbreak and surge of COVID-19 cases in Singapore happened. The simulation models and its variants take into consideration the dynamic evolution of the pandemic and the rapidly evolving policies and processes in Singapore.

    Results

    The models were calibrated against historical data for the Singapore COVID-19 situation. Several variants of the resource planning model were rapidly developed to adapt to the fast-changing COVID-19 situation in Singapore.

    Conclusion

    The agility in adaptable models and robust collaborative management structure enabled the quick deployment of human and capital resources to sustain the high level of health services delivery during the COVID-19 surge.
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    How long will the COVID-19 pandemic last: commentary from Singapore’s perspective
    (Journal of EMS Medicine) Siddiqui, Fahad Javaid; Pourghaderi, Ahmad Reza; Malhotra, Rahul; Ansah, John Pastor; Matchar, David Bruce; Wei, Sean Lam Shao; Low, Jenny G; Ong, Marcus Eng Hock
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    ItemOpen Access
    How long will the COVID-19 pandemic last: commentary from Singapore’s perspective
    (Journal of EMS Medicine) Siddiqui, Fahad Javaid; Pourghaderi, Ahmad Reza; Malhotra, Rahul; Ansah, John Pastor; Matchar, David Bruce; Wei, Sean Lam Shao; Low, Jenny G; Ong, Marcus Eng Hock
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    The effectiveness of public health interventions against COVID-19: Lessons from the Singapore experience.
    (PloS one, 2021-01) Ansah, John P; Matchar, David Bruce; Shao Wei, Sean Lam; Low, Jenny G; Pourghaderi, Ahmad Reza; Siddiqui, Fahad Javaid; Min, Tessa Lui Shi; Wei-Yan, Aloysius Chia; Ong, Marcus Eng Hock

    Background

    In dealing with community spread of COVID-19, two active interventions have been attempted or advocated-containment, and mitigation. Given the extensive impact of COVID-19 globally, there is international interest to learn from best practices that have been shown to work in controlling community spread to inform future outbreaks. This study explores the trajectory of COVID-19 infection in Singapore had the government intervention not focused on containment, but rather on mitigation. In addition, we estimate the actual COVID-19 infection cases in Singapore, given that confirmed cases are publicly available.

    Methods and findings

    We developed a COVID-19 infection model, which is a modified SIR model that differentiate between detected (diagnosed) and undetected (undiagnosed) individuals and segments total population into seven health states: susceptible (S), infected asymptomatic undiagnosed (A), infected asymptomatic diagnosed (I), infected symptomatic undiagnosed (U), infected symptomatic diagnosed (E), recovered (R), and dead (D). To account for the infection stages of the asymptomatic and symptomatic infected individuals, the asymptomatic infected individuals were further disaggregated into three infection stages: (a) latent (b) infectious and (c) non-infectious; while the symptomatic infected were disaggregated into two stages: (a) infectious and (b) non-infectious. The simulation result shows that by the end of the current epidemic cycle without considering the possibility of a second wave, under the containment intervention implemented in Singapore, the confirmed number of Singaporeans infected with COVID-19 (diagnosed asymptomatic and symptomatic cases) is projected to be 52,053 (with 95% confidence range of 49,370-54,735) representing 0.87% (0.83%-0.92%) of the total population; while the actual number of Singaporeans infected with COVID-19 (diagnosed and undiagnosed asymptomatic and symptomatic infected cases) is projected to be 86,041 (81,097-90,986), which is 1.65 times the confirmed cases and represents 1.45% (1.36%-1.53%) of the total population. A peak in infected cases is projected to have occurred on around day 125 (27/05/2020) for the confirmed infected cases and around day 115 (17/05/2020) for the actual infected cases. The number of deaths is estimated to be 37 (34-39) among those infected with COVID-19 by the end of the epidemic cycle; consequently, the perceived case fatality rate is projected to be 0.07%, while the actual case fatality rate is estimated to be 0.043%. Importantly, our simulation model results suggest that there about 65% more COVID-19 infection cases in Singapore that have not been captured in the official reported numbers which could be uncovered via a serological study. Compared to the containment intervention, a mitigation intervention would have resulted in early peak infection, and increase both the cumulative confirmed and actual infection cases and deaths.

    Conclusion

    Early public health measures in the context of targeted, aggressive containment including swift and effective contact tracing and quarantine, was likely responsible for suppressing the number of COVID-19 infections in Singapore.