Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic

Abstract Background The COVID-19 pandemic has initiated several initiatives to better understand its behavior, and some projects are monitoring its evolution across countries, which naturally leads to comparisons made by those using the data. However, most “at a glance” comparisons may be misleading...

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Autores principales:	Abdinardo M. B. de Oliveira, Jane M. Binner, Anandadeep Mandal, Logan Kelly, Gabriel J. Power
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	COVID-19 Statistical models Epidemiological monitoring Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/bbefc32b188f44d79d5fb58465dfad57
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spelling	oai:doaj.org-article:bbefc32b188f44d79d5fb58465dfad572021-11-28T12:12:21ZUsing GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic10.1186/s12889-021-11891-61471-2458https://doaj.org/article/bbefc32b188f44d79d5fb58465dfad572021-11-01T00:00:00Zhttps://doi.org/10.1186/s12889-021-11891-6https://doaj.org/toc/1471-2458Abstract Background The COVID-19 pandemic has initiated several initiatives to better understand its behavior, and some projects are monitoring its evolution across countries, which naturally leads to comparisons made by those using the data. However, most “at a glance” comparisons may be misleading because the curve that should explain the evolution of COVID-19 is different across countries, as a result of the underlying geopolitical or socio-economic characteristics. Therefore, this paper contributes to the scientific endeavour by creating a new evaluation framework to help stakeholders adequately monitor and assess the evolution of COVID-19 in countries, considering the occurrence of spikes, "secondary waves" and structural breaks in the time series. Methods Generalized Additive Models were used to model cumulative and daily curves for confirmed cases and deaths. The Root Relative Squared Error and the Percentage Deviance Explained measured how well the models fit the data. A local min-max function was used to identify all local maxima in the fitted values. The pure Markov-Switching and the family of Markov-Switching GARCH models were used to identify structural breaks in the COVID-19 time series. Finally, a quadrants system to identify countries that are more/less efficient in the short/long term in controlling the spread of the virus and the number of deaths was developed. Such methods were applied in the time series of 189 countries, collected from the Centre for Systems Science and Engineering at Johns Hopkins University. Results Our methodology proves more effective in explaining the evolution of COVID-19 than growth functions worldwide, in addition to standardizing the entire estimation process in a single type of function. Besides, it highlights several inflection points and regime-switching moments, as a consequence of people’s diminished commitment to fighting the pandemic. Although Europe is the most developed continent in the world, it is home to most countries with an upward trend and considered inefficient, for confirmed cases and deaths. Conclusions The new outcomes presented in this research will allow key stakeholders to check whether or not public policies and interventions in the fight against COVID-19 are having an effect, easily identifying examples of best practices and promote such policies more widely around the world.Abdinardo M. B. de OliveiraJane M. BinnerAnandadeep MandalLogan KellyGabriel J. PowerBMCarticleCOVID-19Statistical modelsEpidemiological monitoringPublic aspects of medicineRA1-1270ENBMC Public Health, Vol 21, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 Statistical models Epidemiological monitoring Public aspects of medicine RA1-1270
spellingShingle	COVID-19 Statistical models Epidemiological monitoring Public aspects of medicine RA1-1270 Abdinardo M. B. de Oliveira Jane M. Binner Anandadeep Mandal Logan Kelly Gabriel J. Power Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic
description	Abstract Background The COVID-19 pandemic has initiated several initiatives to better understand its behavior, and some projects are monitoring its evolution across countries, which naturally leads to comparisons made by those using the data. However, most “at a glance” comparisons may be misleading because the curve that should explain the evolution of COVID-19 is different across countries, as a result of the underlying geopolitical or socio-economic characteristics. Therefore, this paper contributes to the scientific endeavour by creating a new evaluation framework to help stakeholders adequately monitor and assess the evolution of COVID-19 in countries, considering the occurrence of spikes, "secondary waves" and structural breaks in the time series. Methods Generalized Additive Models were used to model cumulative and daily curves for confirmed cases and deaths. The Root Relative Squared Error and the Percentage Deviance Explained measured how well the models fit the data. A local min-max function was used to identify all local maxima in the fitted values. The pure Markov-Switching and the family of Markov-Switching GARCH models were used to identify structural breaks in the COVID-19 time series. Finally, a quadrants system to identify countries that are more/less efficient in the short/long term in controlling the spread of the virus and the number of deaths was developed. Such methods were applied in the time series of 189 countries, collected from the Centre for Systems Science and Engineering at Johns Hopkins University. Results Our methodology proves more effective in explaining the evolution of COVID-19 than growth functions worldwide, in addition to standardizing the entire estimation process in a single type of function. Besides, it highlights several inflection points and regime-switching moments, as a consequence of people’s diminished commitment to fighting the pandemic. Although Europe is the most developed continent in the world, it is home to most countries with an upward trend and considered inefficient, for confirmed cases and deaths. Conclusions The new outcomes presented in this research will allow key stakeholders to check whether or not public policies and interventions in the fight against COVID-19 are having an effect, easily identifying examples of best practices and promote such policies more widely around the world.
format	article
author	Abdinardo M. B. de Oliveira Jane M. Binner Anandadeep Mandal Logan Kelly Gabriel J. Power
author_facet	Abdinardo M. B. de Oliveira Jane M. Binner Anandadeep Mandal Logan Kelly Gabriel J. Power
author_sort	Abdinardo M. B. de Oliveira
title	Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic
title_short	Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic
title_full	Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic
title_fullStr	Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic
title_full_unstemmed	Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic
title_sort	using gam functions and markov-switching models in an evaluation framework to assess countries’ performance in controlling the covid-19 pandemic
publisher	BMC
publishDate	2021
url	https://doaj.org/article/bbefc32b188f44d79d5fb58465dfad57
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Using GAM functions and Markov-Switching models in an evaluation framework to assess countries’ performance in controlling the COVID-19 pandemic

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