Global risks of infectious disease outbreaks and its relation to climate
Infectious disease outbreaks are recurring events which can lead to a large number of fatalities every year. Infectious disease outbreaks occur infrequently and the role of global warming and modes of climate variability for those outbreaks is not clear. Here we use an extreme value statistics appro...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2021-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ac188c |
| _version_ | 1797747538167595008 |
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| author | Christian L E Franzke Marcin Czupryna |
| author_facet | Christian L E Franzke Marcin Czupryna |
| author_sort | Christian L E Franzke |
| collection | DOAJ |
| description | Infectious disease outbreaks are recurring events which can lead to a large number of fatalities every year. Infectious disease outbreaks occur infrequently and the role of global warming and modes of climate variability for those outbreaks is not clear. Here we use an extreme value statistics approach to examine annual spatially aggregated infectious disease fatality data to compute their probability to occur using generalized Pareto distribution (GPD) models. The GPD provides a good model for modeling the fatality data and reveals that the number of fatalities follows a power-law. We find that the magnitude of Covid-19 is of an expected level given previous fatality data over the period 1900–2020. We also examined whether including co-variates in the GPD models provide better model fits. We find evidence that a pure linear trend is the best co-variate and, thus, has increased the propensity of large outbreaks to occur for most continents and world-wide. This suggests that mainly non-climate factors affect the likelihood of outbreaks. This linear trend function provides a crude representation of socio-economic trends such as improved public health. However, for South America the Atlantic multidecadal oscillation modulates the outbreak propensity as the best co-variate, showing that climate can play some role in infectious disease outbreaks in some regions. |
| first_indexed | 2024-03-12T15:53:00Z |
| format | Article |
| id | doaj.art-8d86f1f4a0c2416082822679d3729c21 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:53:00Z |
| publishDate | 2021-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-8d86f1f4a0c2416082822679d3729c212023-08-09T15:04:41ZengIOP PublishingEnvironmental Research Letters1748-93262021-01-0116808406310.1088/1748-9326/ac188cGlobal risks of infectious disease outbreaks and its relation to climateChristian L E Franzke0https://orcid.org/0000-0003-4111-1228Marcin Czupryna1Center for Climate Physics, Institute for Basic Science , Busan, Republic of Korea; Department of the Climate System, Pusan National University , Busan, Republic of KoreaInstitute of Finance, Cracow University of Economics , Cracow, PolandInfectious disease outbreaks are recurring events which can lead to a large number of fatalities every year. Infectious disease outbreaks occur infrequently and the role of global warming and modes of climate variability for those outbreaks is not clear. Here we use an extreme value statistics approach to examine annual spatially aggregated infectious disease fatality data to compute their probability to occur using generalized Pareto distribution (GPD) models. The GPD provides a good model for modeling the fatality data and reveals that the number of fatalities follows a power-law. We find that the magnitude of Covid-19 is of an expected level given previous fatality data over the period 1900–2020. We also examined whether including co-variates in the GPD models provide better model fits. We find evidence that a pure linear trend is the best co-variate and, thus, has increased the propensity of large outbreaks to occur for most continents and world-wide. This suggests that mainly non-climate factors affect the likelihood of outbreaks. This linear trend function provides a crude representation of socio-economic trends such as improved public health. However, for South America the Atlantic multidecadal oscillation modulates the outbreak propensity as the best co-variate, showing that climate can play some role in infectious disease outbreaks in some regions.https://doi.org/10.1088/1748-9326/ac188cglobal risksinfectious disease outbreaksclimate variabilityextreme value statistics |
| spellingShingle | Christian L E Franzke Marcin Czupryna Global risks of infectious disease outbreaks and its relation to climate Environmental Research Letters global risks infectious disease outbreaks climate variability extreme value statistics |
| title | Global risks of infectious disease outbreaks and its relation to climate |
| title_full | Global risks of infectious disease outbreaks and its relation to climate |
| title_fullStr | Global risks of infectious disease outbreaks and its relation to climate |
| title_full_unstemmed | Global risks of infectious disease outbreaks and its relation to climate |
| title_short | Global risks of infectious disease outbreaks and its relation to climate |
| title_sort | global risks of infectious disease outbreaks and its relation to climate |
| topic | global risks infectious disease outbreaks climate variability extreme value statistics |
| url | https://doi.org/10.1088/1748-9326/ac188c |
| work_keys_str_mv | AT christianlefranzke globalrisksofinfectiousdiseaseoutbreaksanditsrelationtoclimate AT marcinczupryna globalrisksofinfectiousdiseaseoutbreaksanditsrelationtoclimate |