Background: World 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.
Methods: We 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.
Results: The 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.
Conclusions: We 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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http://dx.doi.org/10.1016/j.jiph.2021.05.019 | DOI Listing |
J Infect Dev Ctries
September 2024
General Directorate of Scientific Research Center, Salahaddin University-Erbil, Erbil, 44001, Kurdistan, Iraq.
Introduction: Coronavirus disease 2019 (COVID-19) first appeared in Iraq, including the Iraqi Kurdistan region governorates, in March 2020.
Methodology: 48,494 samples were collected from public hospitals in the Kurdish governates from February 2021 to May 2022. Viral RNA was extracted, and real time quantitative polymerase chain reaction (RT-PCR) was used to detect the COVID-19 variants.
Lancet Digit Health
November 2024
Department of Statistics, University of Oxford, Oxford, UK; College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK. Electronic address:
Background: Understanding underlying mechanisms of heterogeneity in test-seeking and reporting behaviour during an infectious disease outbreak can help to protect vulnerable populations and guide equity-driven interventions. The COVID-19 pandemic probably exerted different stresses on individuals in different sociodemographic groups and ensuring fair access to and usage of COVID-19 tests was a crucial element of England's testing programme. We aimed to investigate the relationship between sociodemographic factors and COVID-19 testing behaviours in England during the COVID-19 pandemic.
View Article and Find Full Text PDFAccess Microbiol
October 2024
Laboratory of Physiopathology and Molecular Genetics, Faculty of Sciences Ben M'Sik, Hassan II University of Casablanca (Morocco), Avenue Cdt Driss El Harti, PB 7955 Sidi Othman, Casablanca, Morocco.
During the 3 years following the emergence of the COVID-19 pandemic, the African continent, like other regions of the world, was substantially impacted by COVID-19. In Morocco, the COVID-19 pandemic has been marked by the emergence and spread of several SARS-CoV-2 variants, leading to a substantial increase in the incidence of infections and deaths. Nevertheless, the comprehensive understanding of the genetic diversity, evolution, and epidemiology of several viral lineages remained limited in Morocco.
View Article and Find Full Text PDFJpn J Infect Dis
November 2024
Department of Global Health Research, Graduate School of Medicine, Juntendo University, Japan.
Curr Res Microb Sci
May 2024
Cranfield University, College Road, Cranfield, Bedfordshire, MK43 0AL, UK.
Wastewater-based surveillance (WBS) offers an aggregate, and cost-effective approach for tracking infectious disease outbreak prevalence within communities, that provides data on community health complementary to individual clinical testing. This study reports on a 16-month WBS initiative on a university campus in England, UK, assessing the presence of SARS-CoV-2 in sewers from large buildings, downstream sewer locations, raw wastewater, partially treated and treated effluents. Key findings include the detection of the Alpha (B.
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