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Covid-19 risk data during lockdown-like policy in Indonesia
Khreshna Syuhada1, Aqilah Wibisono1, Arief Hakim1
1Statistics Research Division, Institut Teknologi Bandung, 40132, Indonesia.
Data in Brief
|February 3, 2021
Summary
Indonesian governments implemented Large-Scale Social Restrictions (PSBB) and Expanded and Tightened Social Restrictions (PSDD) to curb COVID-19. Analysis of case data before, during, and after these policies reveals their impact on infection rates and fatality.
Area of Science:
- Epidemiology
- Public Health Policy
- Data Science
Background:
- The COVID-19 pandemic necessitated significant public health interventions globally, including Indonesia.
- Indonesia implemented Large-Scale Social Restriction (PSBB) and Expanded and Tightened Social Restriction (PSDD) policies to mitigate virus transmission.
Purpose of the Study:
- To analyze the impact of PSBB and PSDD policies on COVID-19 confirmed cases and case fatality rates in Indonesia.
- To model COVID-19 risk and forecast potential Value-at-Risk (VaR) based on policy implementation periods.
Main Methods:
- Collected daily COVID-19 risk data from central and local government tracking sites in Indonesia.
- Extracted data as of August 22, 2020.
- Calculated daily rates of confirmed cases, active cases, and case fatality rates before, during, and after policy implementation.
Main Results:
- The study presents data on COVID-19 confirmed cases and case fatality rates across various Indonesian cities and provinces.
- Calculations reveal changes in daily confirmed cases, active cases, and case fatality rates correlating with PSBB and PSDD policies.
- Risk modeling was performed to forecast Value-at-Risk (VaR) associated with the pandemic during these restrictions.
Conclusions:
- The implemented social restriction policies (PSBB and PSDD) in Indonesia demonstrated measurable effects on COVID-19 transmission dynamics and fatality rates.
- The findings provide critical data for evaluating the effectiveness of non-pharmaceutical interventions during pandemics.
- Risk modeling, including VaR forecasting, offers a framework for understanding and managing pandemic-related uncertainties.
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