Bayesian Geostatistical Modelling of COVID-19 Datasets
The COVID-19 dataset is obtained by extracting weather, longitude, latitude, ISO3666, cases and death of coronavirus patients across the globe. The data were extracted for a period of eight day choosing uniform time within the specified period. Then mapping of cases and deaths with reverence to continents were obtained. Bayesian Geostastical modelling was carried out on the dataset. The study found out that countries in the tropical region suffered less deaths/attacks compared to countries in the temperate region, this is due to high temperature in the tropical region.
[1] D. Pati, B.J Reich and D.B Dunson, ‘Bayesian geostatistical modelling with informative sampling locations’, Biometrika , 98, 1, pp. 35–48 doi: 10.1093/biomet/asq067C _2011 Biometrika Trust Printed in Great Britain B.
[2] H. Rue, S. Martino and N. Chopin, ‘Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations’. J.R. Stat Soc Ser B Stat Methodol 71:319-392, 2009
[3] I. M Held, M. Winton, K. Takahashi, T. Delworth, F. Zeng, and G.K. Vallis., ‘Probing the fast and slow components of global warming by returning abruptly to preindustrial forcing’, J.Clim., 23, 2418– 2427, doi:10.1175/2009JCLI3466.1 , 2010.
[4] G. C. S. Ronaldo, S. Nadine, E. B. Maria, M.C. Edgar, C. Frédérique, U. Jürg, and V. Penelope, ‘Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models’, Geospatial Health 8(1), pp. 97-110, 2013.
[5] P. Diggle, J. Tawn, R. A. Moyeed, ‘Model-based geostatistics’. Appl. Stat. 1998;47:299–350.
[6] P. Diggle, R. Menezes and T. Su, ‘Geostatistical inference under preferential sampling (with discussion)’. Appl. Statist. 59, 191–232, 2010.
[7] M. Paula, ‘Small Area Disease Risk Estimation and Visualization Using R’, The R Journal Vol. 10/1, 2018.
[8] J. Allaire, ‘Flexdashboard: R Markdown Format for Flexible Dashboards, https://CRAN.Rproject.org/package=flexdashboard. R package version 0.5. p504/2017.
[9] Chang W., Cheng J., Allaire J., Xie Y., and McPherson J. Shiny: Web Application Framework for R, 2017. URL https://CRAN.R- project.org/package=shiny. R package version 1.0.5. p504
[10] G. C. S. Ronaldo, S. Nadine, Maria E. B., M.C. Edgar, C. Frédérique, U. Jürg and V. Penelope ,‘Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models’, Geospatial Health 8(1), 2013, pp. 97-110
[11] K. Gunter, ‘Potential role of inanimate surfaces for the spread of coronaviruses and their inactivation with disinfectant agents', Infection Prevention in Practice, www.elsevier.com/locate, 2020.doi: 10.1016/j.infpip.2020.100044
[12] WHO.’ Infection prevention and control during health care when novel coronavirus (nCoV) infection is suspected’. Interim guidance. 25 January 2020.
[13] WHO(2020). ‘Novel Coronavirus (2019-nCoV)’. Situation Report 13. WHO;2020.
[14] J.F. Chan, Yuan S, K.H. Kok, K.K. To, H. Chu, nd J. Yang, ‘A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster’. Lancet 2020. https://doi.org/10.1016/s0140- 6736(20) 30154-9.
[15] G. Jianjun, T. Zhenxue and Y. Xu, ‘Breakthrough: Chloroquine phosphate has shown apparent efficacy in treatment of COVID19 associated pneumonia in clinical studies’, BioScience Trends Advance Publication,DOI:10.5582/bst.2029.01047,www.bioscienctrends.com/2020
[16] L. Kim, COVID-19 Had Us All Fooled, but Now We Might Have Finally Found Its Secret’ Medium Post https://www.truthorfiction.com/the-covid-19-chloroquine-controversy-explained/, 2020
[17] Data on Temperature, Humidity, Precipitation and Wind were obtained from www.timeanddate.com /2020
[18] Data on Cases and Deaths due to coronavirus were obtained from https://www.worldometers.info/coronavirus/ on 4/5/2020
[19] Data on ISO3666 were obtained from https://github.com/lukes/ISO-3166-Countries-with-Regional-Codes/blob/master/all/all.csv/2020.
[1] D. Pati, B.J Reich and D.B Dunson, ‘Bayesian geostatistical modelling with informative sampling locations’, Biometrika , 98, 1, pp. 35–48 doi: 10.1093/biomet/asq067C _2011 Biometrika Trust Printed in Great Britain B.
[2] H. Rue, S. Martino and N. Chopin, ‘Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations’. J.R. Stat Soc Ser B Stat Methodol 71:319-392, 2009
[3] I. M Held, M. Winton, K. Takahashi, T. Delworth, F. Zeng, and G.K. Vallis., ‘Probing the fast and slow components of global warming by returning abruptly to preindustrial forcing’, J.Clim., 23, 2418– 2427, doi:10.1175/2009JCLI3466.1 , 2010.
[4] G. C. S. Ronaldo, S. Nadine, E. B. Maria, M.C. Edgar, C. Frédérique, U. Jürg, and V. Penelope, ‘Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models’, Geospatial Health 8(1), pp. 97-110, 2013.
[5] P. Diggle, J. Tawn, R. A. Moyeed, ‘Model-based geostatistics’. Appl. Stat. 1998;47:299–350.
[6] P. Diggle, R. Menezes and T. Su, ‘Geostatistical inference under preferential sampling (with discussion)’. Appl. Statist. 59, 191–232, 2010.
[7] M. Paula, ‘Small Area Disease Risk Estimation and Visualization Using R’, The R Journal Vol. 10/1, 2018.
[8] J. Allaire, ‘Flexdashboard: R Markdown Format for Flexible Dashboards, https://CRAN.Rproject.org/package=flexdashboard. R package version 0.5. p504/2017.
[9] Chang W., Cheng J., Allaire J., Xie Y., and McPherson J. Shiny: Web Application Framework for R, 2017. URL https://CRAN.R- project.org/package=shiny. R package version 1.0.5. p504
[10] G. C. S. Ronaldo, S. Nadine, Maria E. B., M.C. Edgar, C. Frédérique, U. Jürg and V. Penelope ,‘Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models’, Geospatial Health 8(1), 2013, pp. 97-110
[11] K. Gunter, ‘Potential role of inanimate surfaces for the spread of coronaviruses and their inactivation with disinfectant agents', Infection Prevention in Practice, www.elsevier.com/locate, 2020.doi: 10.1016/j.infpip.2020.100044
[12] WHO.’ Infection prevention and control during health care when novel coronavirus (nCoV) infection is suspected’. Interim guidance. 25 January 2020.
[13] WHO(2020). ‘Novel Coronavirus (2019-nCoV)’. Situation Report 13. WHO;2020.
[14] J.F. Chan, Yuan S, K.H. Kok, K.K. To, H. Chu, nd J. Yang, ‘A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster’. Lancet 2020. https://doi.org/10.1016/s0140- 6736(20) 30154-9.
[15] G. Jianjun, T. Zhenxue and Y. Xu, ‘Breakthrough: Chloroquine phosphate has shown apparent efficacy in treatment of COVID19 associated pneumonia in clinical studies’, BioScience Trends Advance Publication,DOI:10.5582/bst.2029.01047,www.bioscienctrends.com/2020
[16] L. Kim, COVID-19 Had Us All Fooled, but Now We Might Have Finally Found Its Secret’ Medium Post https://www.truthorfiction.com/the-covid-19-chloroquine-controversy-explained/, 2020
[17] Data on Temperature, Humidity, Precipitation and Wind were obtained from www.timeanddate.com /2020
[18] Data on Cases and Deaths due to coronavirus were obtained from https://www.worldometers.info/coronavirus/ on 4/5/2020
[19] Data on ISO3666 were obtained from https://github.com/lukes/ISO-3166-Countries-with-Regional-Codes/blob/master/all/all.csv/2020.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:80329", author = "I. Oloyede", title = "Bayesian Geostatistical Modelling of COVID-19 Datasets", abstract = "The COVID-19 dataset is obtained by extracting weather, longitude, latitude, ISO3666, cases and death of coronavirus patients across the globe. The data were extracted for a period of eight day choosing uniform time within the specified period. Then mapping of cases and deaths with reverence to continents were obtained. Bayesian Geostastical modelling was carried out on the dataset. The study found out that countries in the tropical region suffered less deaths/attacks compared to countries in the temperate region, this is due to high temperature in the tropical region.
", keywords = "COVID-19, Bayesian, geostastical modelling, prior, posterior. ", volume = "15", number = "5", pages = "29-4", }
