Factors affecting Covid-19 cases before epidemic peaks

Bibliographic Data

ID21482044
AuthorsAndika Andika (0000-0003-0795-4248, Bandung Institute of Technology), P Wulandari (Bandung Institute of Technology), Halmar Halide (0000-0003-0449-7512, corresponding author)
Year2021
Volume35
PagesS103-S106
Publication date2021-01-01
Open AccessYes
TypeARTICLE
VenueGaceta Sanitaria (JOURNAL)
Journal identifiersISSN: 0213-9111 • E-ISSN: 1578-1283
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.gaceta.2021.10.007
PMID34929788
OpenAlexW4205347314
LanguageEN
References cited16

OBJECTIVE: The COVID-19 pandemic has disrupted people's normal life as a result of strict policies applied to slow down the pandemic. To find out how extensive the virus spread is, most countries increase their daily testing rates. METHOD: This simple modelling work uses stringency index and daily testing (including the lagged version up to the previous 14 days) to predict daily COVID-19 cases in India and Indonesia. A Stepwise Multiple Regression (SWMR) subroutine is used in this modelling to select factors based on a 0.01 significant level affecting daily COVID-19 cases before the epidemic peaks. RESULT: The models have high predictability close to 94% (Indonesia) and 99% (India). Increasing number of daily COVID-19 cases in Indonesia is associated with the country's increased testing capacity. On the other hand, stringency indices play more important role in determining India's daily COVID-19 cases. CLOCLUSION: Our finding shows that one question remains to be answered as to why testing and strict policy differ in determining daily cases in both Asian countries

MEDLINE · Public health · COVID-19 Digital Contact Tracing · COVID-19 epidemiological studies · SARS-CoV-2 detection and testing · Epidemiology

Tools

Open DOIOpen Access