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The trend analysis of COVID-19 cases before and after the Large-Scale Social Restriction (PSBB) in four provinces in Indonesia

Abstract

Purpose: As the intervention of COVID-19 pandemic, Indonesia implemented Large Scale Social Restriction (PSBB). The aim of present research was to evaluate daily new cases, active cases, and daily death of COVID-19 before and after the implementation of PSBB in 4 provinces: Jakarta, West Sumatra, Gorontalo, West Java.

Methods: Each parameter observed on four different time P0 (14 days before PSBB), P1 (0-13 days after PSBB), P2 (14-27 days after PSBB), and P3 (28-41 days after PSBB) from March 27, 2020 until May 22, 2020. Polynomial model was used to construct the trend of new cases and predicted active cases. The difference of the increase of new cases and the mean of death rate between periods was analysed using dependent T-test. The difference between predicted and measured active cases was analysed by independent T-test.

Results: COVID-19 daily new cases increased at P1 in Jakarta and West Sumatra and differed at P2 and P3, while declined since P1 in Gorontalo and West Java. There was significant higher of COVID-19 active cases compare to predicted active cases at P1 in all provinces, except West Java. The trend of declining daily death after PSBB implementation was observed in all provinces.

Conclusion: Different trends were observed in four provinces after the implementation of PSBB, which showed random trend of daily cases, mainly increase trend of active cases, and decrease trend of daily death. However, the length of PSBB implementation also differ, therefore prolonged observation was needed to evaluate the consideration of PSBB program continuation.

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How to Cite

Saputri, R. I., & Setiawan, W. E. (2021). The trend analysis of COVID-19 cases before and after the Large-Scale Social Restriction (PSBB) in four provinces in Indonesia. Bali Medical Journal, 10(2), 946–951. https://doi.org/10.15562/bmj.v10i2.2080

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Rosalina Intan Saputri
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BMJ Journal


Winardi Emmanuel Setiawan
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