The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model

Abstract Background Natural disasters and infectious diseases result in widespread disruption to human health and livelihood. At the scale of a global pandemic, the co-occurrence of natural disasters is inevitable. However, the impact of natural disasters on the spread of COVID-19 has not been exten...

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Autores principales:	Maximillian Van Wyk de Vries, Lekaashree Rambabu
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	COVID-19 Epidemiology Agent-based model Natural disaster Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/c544e49175d74fe6a18ca96a00c0a7b4
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spelling	oai:doaj.org-article:c544e49175d74fe6a18ca96a00c0a7b42021-12-05T12:17:48ZThe impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model10.1186/s12976-021-00151-01742-4682https://doaj.org/article/c544e49175d74fe6a18ca96a00c0a7b42021-12-01T00:00:00Zhttps://doi.org/10.1186/s12976-021-00151-0https://doaj.org/toc/1742-4682Abstract Background Natural disasters and infectious diseases result in widespread disruption to human health and livelihood. At the scale of a global pandemic, the co-occurrence of natural disasters is inevitable. However, the impact of natural disasters on the spread of COVID-19 has not been extensively evaluated through epidemiological modelling. Methods We create an agent-based epidemiology model based on COVID-19 clinical, epidemiological, and geographic data. We first model 35 scenarios with varying natural disaster timing and duration for a COVID-19 outbreak in a theoretical region. We then evaluate the potential effect of an eruption of Vesuvius volcano on the spread of COVID-19 in Campania, Italy. Results In a majority of cases, the occurrence of a natural disaster increases the number of disease related fatalities. For a natural disaster fifty days after infection onset, the median increase in fatalities is 2, 59, and 180% for a 2, 14, and 31-day long natural disaster respectively, when compared to the no natural disaster scenario. For the Campania case, the median increase in fatalities is 1.1 and 2.4 additional fatalities per 100,000 for eruptions on day 1 and 100 respectively, and 60.0 additional fatalities per 100,000 for an eruption close to the peak in infections (day 50). Conclusion Our results show that the occurrence of a natural disaster in most cases leads to an increase in infection related fatalities, with wide variance in possible outcomes depending on the timing of the natural disaster relative to the peak in infections and the duration of the natural disaster.Maximillian Van Wyk de VriesLekaashree RambabuBMCarticleCOVID-19EpidemiologyAgent-based modelNatural disasterComputer applications to medicine. Medical informaticsR858-859.7Biology (General)QH301-705.5ENTheoretical Biology and Medical Modelling, Vol 18, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 Epidemiology Agent-based model Natural disaster Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5
spellingShingle	COVID-19 Epidemiology Agent-based model Natural disaster Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5 Maximillian Van Wyk de Vries Lekaashree Rambabu The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model
description	Abstract Background Natural disasters and infectious diseases result in widespread disruption to human health and livelihood. At the scale of a global pandemic, the co-occurrence of natural disasters is inevitable. However, the impact of natural disasters on the spread of COVID-19 has not been extensively evaluated through epidemiological modelling. Methods We create an agent-based epidemiology model based on COVID-19 clinical, epidemiological, and geographic data. We first model 35 scenarios with varying natural disaster timing and duration for a COVID-19 outbreak in a theoretical region. We then evaluate the potential effect of an eruption of Vesuvius volcano on the spread of COVID-19 in Campania, Italy. Results In a majority of cases, the occurrence of a natural disaster increases the number of disease related fatalities. For a natural disaster fifty days after infection onset, the median increase in fatalities is 2, 59, and 180% for a 2, 14, and 31-day long natural disaster respectively, when compared to the no natural disaster scenario. For the Campania case, the median increase in fatalities is 1.1 and 2.4 additional fatalities per 100,000 for eruptions on day 1 and 100 respectively, and 60.0 additional fatalities per 100,000 for an eruption close to the peak in infections (day 50). Conclusion Our results show that the occurrence of a natural disaster in most cases leads to an increase in infection related fatalities, with wide variance in possible outcomes depending on the timing of the natural disaster relative to the peak in infections and the duration of the natural disaster.
format	article
author	Maximillian Van Wyk de Vries Lekaashree Rambabu
author_facet	Maximillian Van Wyk de Vries Lekaashree Rambabu
author_sort	Maximillian Van Wyk de Vries
title	The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model
title_short	The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model
title_full	The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model
title_fullStr	The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model
title_full_unstemmed	The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model
title_sort	impact of natural disasters on the spread of covid-19: a geospatial, agent-based epidemiology model
publisher	BMC
publishDate	2021
url	https://doaj.org/article/c544e49175d74fe6a18ca96a00c0a7b4
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The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model

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