ArticleJournal of infection and public health2021
New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors.
Article in Journal of infection and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 21 citations in OpenAlex.
- SARS-CoV-2 and Environmental Changes: The Perfect Storm.Current issues in molecular biology · 2024Review
- Enhancing COVID-19 forecasting precision through the integration of compartmental models, machine learning and variants.Scientific reports · 2024Article
- Predicting soil erosion potential under CMIP6 climate change scenarios in the Chini Lake Basin, Malaysia.Geoscience letters · 2023Article
- Mapping Chini Lake (Pahang, Malaysia) using Sentinel-2 images to determine the effect of acid mine drainage in the pre- to post-COVID-19 restriction period.Environmental monitoring and assessment · 2022Article
- Impact of Different Air Pollutants (PMInternational journal of environmental research and public health · 2022Article
- COVID-19 in Southeast Asia: current status and perspectives.Bioengineered · 2022Review
- Forecasting the Severity of COVID-19 Pandemic Amidst the Emerging SARS-CoV-2 Variants: Adoption of ARIMA Model.Computational and mathematical methods in medicine · 2022Article
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2 authors at 2 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundWorld Health Organization has reported fifty countries have now detected the new coronavirus (B.1.1.7 variant) since a couple of months ago. In Indonesia, the B.1.1.7 cases have been found in several provinces since January 2021, although they are still in a lower number than the old variant of COVID-19. Therefore, this study aims to create a forecast analysis regarding the occasions of COVID-19 and B.1.1.7 cases based on data from the 1st January to 18th March 2021, and also analyze the association between meteorological factors with B.1.1.7 incidences in three different provinces of Indonesia such as the West Java, South Sumatra and East Kalimantan.
methodsWe used the Autoregressive Moving Average Models (ARIMA) to forecast the number of cases in the upcoming 14 days and the Spearman correlation analysis to analyze the relationship between B.1.1.7 cases and meteorological variables such as temperature, humidity, rainfall, sunshine, and wind speed.
resultsThe results of the study showed the fitted ARIMA models forecasted there was an increase in the daily cases in three provinces. The total cases in three provinces would increase by 36% (West Java), 13.5% (South Sumatra), and 30% (East Kalimantan) as compared with actual cases until the end of 14 days later. The temperature, rainfall and sunshine factors were the main contributors for B.1.1.7 cases with each correlation coefficients; r = -0.230; p < 0.05, r = 0.211; p < 0.05 and r = -0.418; p < 0.01, respectively.
conclusionsWe recapitulated that this investigation was the first preliminary study to analyze a short-term forecast regarding COVID-19 and B.1.1.7 cases as well as to determine the associated meteorological factors that become primary contributors to the virus spread.
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