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Covid-19 risk data during lockdown-like policy in Indonesia
Syuhada K.a, Wibisono A.a, Hakim A.a, Addini F.a
a Statistics Research Division, Institut Teknologi Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2021 The AuthorsCovid-19 pandemic has spread fast almost all countries in the world including Indonesia. In order to slow such pandemic confirmed cases, Indonesian local and central governments apply a lockdown-like policy. We call this Large-Scale Social Restriction (Pembatasan Sosial Berskala Besar, known as PSBB) and PSBB-variant that is Expanded and Tightened Social Restriction or Pembatasan Sosial yang Diperluas dan Diperketat (PSDD). In this paper, we present number of cases and case fatality rate before, during and after such lockdown-like policy. This article contains Covid-19 risk data of several cities and provinces in Indonesia. We have used central and local government Covid-19 tracking sites to determine the daily risks for several cities and provinces in Indonesia. All data were extracted on August 22, 2020. We developed these data and calculated daily rate of confirmed and active cases, case fatality rate and rate of case fatality rate before, during and after lockdown-like policy. Furthermore, such risk modeling is used to forecast of what so-called Value-at-Risk (VaR).[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Covid-19 pandemic,Risk data,Risk measure,Stochastic forecast, Value-at-risk[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1016/j.dib.2021.106801[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]