INTEGRATION OF BAYESIAN MODEL AND ADAPTIVE CLUSTERED SAMPLING INTO CONTACT TRACING TO CURB THE SPREAD OF COVID -19 CASES
Abstract
Covid-19 is a communicable virus that causes serious illness (Severe acutepiratory syndrome (SARS)) and middle east respiratory syndrome (MARS)). Ä°ts outbreak started in Wuhan, China on December 8, 2019. Fever, cough, tiredness are its signs and symptoms and appear between two to fourteen days after exposure. The severity of COVID-19 can include complications; pneumonia, heart problems, acute kidney injuries. Covid-19 careers should be identified in order to curb the spread of the virus within a population. In this regards, contact tracing is the current technique in use to identify and track the Covid-19 carriers. The aim is to curb the spread of the virus within the population. In order to achieve this goal effectively, appropriate technique is required in the identification of Covid-19 carriers and Modeling. It is known that Covid-19 carriers are hidden, clustered and very difficult to identify in the population. At this point, the Adaptive Cluster Sampling, which is a specialized sampling for identification of hidden and clustered event and Bayesian Model, comes to the practice. Therefore, in this study, Adaptive Cluster Sampling which is capable of tracking hidden and clustered events and Bayesian Model are integrated in contact tracing, and the application on how this technique is used is included
References
Acharya B, Bhattarai G, Gier A, Stein A. (2000). Systematic adaptive cluster sampling for the assessment of rare tree species in Nepal. Forest Ecology and Management 137(2000):65-73.
Ashley L. Greiner, et. al. (2015). Addressing contact tracing challenges – Critical to halting Ebola Virus Diseases transmission. International Journal of Infectious Diseases. Vol. 41, Page 53 – 55.
Bishnu P. K. (2020). Impact of the COVID-19 in Tourism Industry in Nepal and Policy Recommendation. Journal of Tourism & Adventure. 3:1, 76-91
Brown J. A. and Manly B.J.F. (1998). Restricted adaptive cluster sampling. Environmental and Ecological Statistics 5:49-63.
Centre for the Study of Economies of Africa (CSEA). (2020). The implication of Covid-19 on the Nigerian Economy. Retrieved April 13th, 2020, from http://cseaafrica.org/the-implication-of-covid19-on-the-nigerian-economy
Channappanavar R, Perlman S. (2017). Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology. Seminars in immunopathology. 39(5):529-39.
Gelman, A. and Rubin, D. (1996) Markov chain Monte Carlo methods in biostatistics.Statistical Methods in Medical Research, 5, 339–355
Goncalves, Kelly C. M., Moura, Fernando A. S. (2016). A Mixture Model for Rare and Clustered Populations Under Adaptive Cluster Sampling. Bayesian Analysis 11, Number 2, pp. 519–544.
Nairametrics (2020).https://nairametrics.com/2020/08/03/Covid-19-update-in-nigeria/
Olayiwola O. M. et al. (2020). Adaptive cluster sampling with model-based approach for estimating total number of hidden COVID-19 carriers in Nigeria. Statistical Journal of the IAOS. Vol. 36. S103–S109 S103.
NCDC (2020), https://covid19.ncdc.gov.ng. Accessed June 18th, 2020
Oruonye E.D. & Ahmed Y.M. (2020).An appraisal of the potential impacts of COVID-19 on Tourism in Nigeria. Journal of Economics and Technology Research. Vol. 1 no 1. Pages 32 – 4
Peterson K. Ozili (2020) COVID-19 pandemic and economic crisis: The Nigerian experiences Structural causes. Munich Personal RePEc Archive
PwC (2020): Nigeria’s Webinar COVID-19: Economic Implication and Policy Responses
R Core Team. 2017. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/
Rapley, V. and Welsh, A. (2008). Model-Based Inferences from Adaptive Cluster Sampling. Bayesian Analysis. 3(4): 717–736. MR2469797. doi: http://dx.doi.org/10.1214/08-BA327. 520, 521, 522, 523, 535, 536, 539, 540
Thompson, S. (1990). “Adaptive cluster sampling.†Journal of the American Statistical Association 85: 1050–1059.
Thompson S. K (2017): Adaptive and Network Sampling for Inference and Interventions in Changing Populations. Journal of Survey Statistics and Methodology. 5 (1): 1-21. 10.1093/jssam/smw035.
World Health Organization (2015).Implementation and management of contact tracing for Ebola Virus disease (September, 2015).
World Health Organization (2020).Contact tracing in the context of Covid-19, interim guidance.
Worldometer (2020). https://www.worldometers.info/coronavirus/#countries. Accessed on June 23, 2020 2, 2020.
World Health Organization (WHO). Novel Coronavirus – China 2020 [14 January 2020].
Available from: https://www.who.int/csr/don/12-january-2020-novel-coronavirus-china/en/.
Yin Y, Wunderink RG. (2018). MERS, SARS and other coronaviruses as causes of pneumonia. Respirology (Carlton, Vic). 23(2):130-7.
Copyright (c) 2021 FUDMA JOURNAL OF SCIENCES
This work is licensed under a Creative Commons Attribution 4.0 International License.
FUDMA Journal of Sciences
