The Impact of COVID-19 on Mortality in Italy: Retrospective Analysis of Epidemiological Trends.

Publisher: JMIR Publications Country of Publication: Canada NLM ID: 101669345 Publication Model: Electronic Cited Medium: Internet ISSN: 2369-2960 (Electronic) Linking ISSN: 23692960 NLM ISO Abbreviation: JMIR Public Health Surveill Subsets: MEDLINE

Original Publication: Toronto : JMIR Publications, [2015]-

COVID-19*; Female ; Humans ; Italy/epidemiology ; Male ; Pandemics ; Retrospective Studies ; SARS-CoV-2

Background: Despite the available evidence on its severity, COVID-19 has often been compared with seasonal flu by some conspirators and even scientists. Various public discussions arose about the noncausal correlation between COVID-19 and the observed deaths during the pandemic period in Italy.
Objective: This paper aimed to search for endogenous reasons for the mortality increase recorded in Italy during 2020 to test this controversial hypothesis. Furthermore, we provide a framework for epidemiological analyses of time series.
Methods: We analyzed deaths by age, sex, region, and cause of death in Italy from 2011 to 2019. Ordinary least squares (OLS) linear regression analyses and autoregressive integrated moving average (ARIMA) were used to predict the best value for 2020. A Grubbs 1-sided test was used to assess the significance of the difference between predicted and observed 2020 deaths/mortality. Finally, a 1-sample t test was used to compare the population of regional excess deaths to a null mean. The relationship between mortality and predictive variables was assessed using OLS multiple regression models. Since there is no uniform opinion on multicomparison adjustment and false negatives imply great epidemiological risk, the less-conservative Siegel approach and more-conservative Holm-Bonferroni approach were employed. By doing so, we provided the reader with the means to carry out an independent analysis.
Results: Both ARIMA and OLS linear regression models predicted the number of deaths in Italy during 2020 to be between 640,000 and 660,000 (range of 95% CIs: 620,000-695,000) against the observed value of above 750,000. We found strong evidence supporting that the death increase in all regions (average excess=12.2%) was not due to chance (t 21 =7.2; adjusted P<.001). Male and female national mortality excesses were 18.4% (P<.001; adjusted P=.006) and 14.1% (P=.005; adjusted P=.12), respectively. However, we found limited significance when comparing male and female mortality residuals' using the Mann-Whitney U test (P=.27; adjusted P=.99). Finally, mortality was strongly and positively correlated with latitude (R=0.82; adjusted P<.001). In this regard, the significance of the mortality increases during 2020 varied greatly from region to region. Lombardy recorded the highest mortality increase (38% for men, adjusted P<.001; 31% for women, P<.001; adjusted P=.006).
Conclusions: Our findings support the absence of historical endogenous reasons capable of justifying the mortality increase observed in Italy during 2020. Together with the current knowledge on SARS-CoV-2, these results provide decisive evidence on the devastating impact of COVID-19. We suggest that this research be leveraged by government, health, and information authorities to furnish proof against conspiracy hypotheses that minimize COVID-19-related risks. Finally, given the marked concordance between ARIMA and OLS regression, we suggest that these models be exploited for public health surveillance. Specifically, meaningful information can be deduced by comparing predicted and observed epidemiological trends.
(©Alessandro Rovetta, Akshaya Srikanth Bhagavathula. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 07.04.2022.)

Respirology. 2021 Jun;26(6):552-565. (PMID: 33955623)
Front Cell Infect Microbiol. 2021 Oct 22;11:753721. (PMID: 34746028)
PeerJ. 2017 Jul 7;5:e3544. (PMID: 28698825)
Nature. 2020 May;581(7807):221-224. (PMID: 32225175)
Cell J. 2019 Jan;20(4):604-607. (PMID: 30124010)
Int J Infect Dis. 2020 Dec;101:138-148. (PMID: 33007452)
Results Phys. 2021 Aug;27:104509. (PMID: 34307005)
BMJ. 1999 Feb 27;318(7183):600-1. (PMID: 10037651)
AIMS Public Health. 2021 Aug 26;8(4):598-613. (PMID: 34786422)
Nature. 2021 Jul;595(7869):640-644. (PMID: 34321669)
Diabetes Metab Syndr. 2021 May-Jun;15(3):869-875. (PMID: 33892403)
BMJ Glob Health. 2020 Jun;5(6):. (PMID: 32532758)
BMC Public Health. 2021 Aug 16;21(1):1554. (PMID: 34399729)
Int J Environ Res Public Health. 2021 Jan 26;18(3):. (PMID: 33530563)
Sci Rep. 2021 Apr 27;11(1):9042. (PMID: 33907202)
Eur Respir Rev. 2021 Feb 9;30(159):. (PMID: 33568525)
Proc Natl Acad Sci U S A. 2020 Nov 3;117(44):27285-27291. (PMID: 33060298)
BMC Public Health. 2021 Sep 1;21(1):1607. (PMID: 34470630)
J Mol Cell Biol. 2022 Jan 29;13(12):918-920. (PMID: 34450642)
Eur J Epidemiol. 2016 Apr;31(4):337-50. (PMID: 27209009)
Euro Surveill. 2020 Dec;25(49):. (PMID: 33303064)
Sci Rep. 2021 Jan 21;11(1):1972. (PMID: 33479325)
Am J Epidemiol. 2017 Sep 15;186(6):639-645. (PMID: 28938712)
BMJ Open. 2021 Oct 7;11(10):e051506. (PMID: 34620662)
Public Health. 2021 May;194:135-142. (PMID: 33892351)
Nature. 2021 Dec;600(7890):701-706. (PMID: 34673755)
Vaccines (Basel). 2021 Sep 04;9(9):. (PMID: 34579226)
World J Pediatr. 2021 Oct;17(5):495-499. (PMID: 34478045)
JMIRx Med. 2021 Oct 18;2(4):e32233. (PMID: 34842858)
Am J Sports Med. 2020 Jan;48(1):NP13. (PMID: 31877094)
Yonsei Med J. 2021 Nov;62(11):961-968. (PMID: 34672129)
BMC Pulm Med. 2021 Mar 20;21(1):96. (PMID: 33743654)
Front Mol Biosci. 2021 Sep 17;8:728409. (PMID: 34604307)
Diabetes Metab Syndr. 2020 Sep - Oct;14(5):1467-1474. (PMID: 32771920)
Sovrem Tekhnologii Med. 2020;12(2):6-11. (PMID: 34513048)
Expert Rev Vaccines. 2021 Oct;20(10):1201-1209. (PMID: 34488546)
Clin Neuropsychol. 2007 Jul;21(4):553-68. (PMID: 17613978)
Sci Rep. 2021 Apr 22;11(1):8710. (PMID: 33888744)
Front Immunol. 2021 May 07;12:659339. (PMID: 34025658)
Nat Commun. 2021 Oct 13;12(1):5968. (PMID: 34645794)
Appl Health Econ Health Policy. 2020 Aug;18(4):509-517. (PMID: 32495067)
mBio. 2021 Feb 9;12(1):. (PMID: 33563817)
Front Physiol. 2020 Dec 09;11:588553. (PMID: 33362576)
JMIR Infodemiology. 2021 Aug 06;1(1):e29929. (PMID: 34447925)
N Engl J Med. 2021 Aug 12;385(7):585-594. (PMID: 34289274)
Int J Tuberc Lung Dis. 2007 Sep;11(9):938-43. (PMID: 17705968)
SN Compr Clin Med. 2020;2(7):874-876. (PMID: 32838138)
Eur J Integr Med. 2021 Apr;43:101313. (PMID: 33619437)
Sci Rep. 2021 Mar 5;11(1):5304. (PMID: 33674627)
Int J Prev Med. 2013 Feb;4(2):128-32. (PMID: 23543865)
BMC Public Health. 2021 Sep 3;21(1):1612. (PMID: 34479535)
BMC Public Health. 2021 May 12;21(1):902. (PMID: 33980180)
Environ Res. 2020 Jul;186:109639. (PMID: 32668559)
Econ Disaster Clim Chang. 2022;6(1):129-140. (PMID: 34703977)
J Phys Chem B. 2020 Aug 27;124(34):7336-7347. (PMID: 32790406)
Sci Rep. 2021 Aug 9;11(1):16144. (PMID: 34373540)
Cureus. 2020 Nov 9;12(11):e11397. (PMID: 33312795)
Eur J Epidemiol. 2019 Sep;34(9):801-808. (PMID: 31522327)

Keywords: COVID-19; Italy; deniers; epidemiology; excess deaths; infodemic; infodemiology; longitudinal analysis; mortality; pandemic; public health; time series

Date Created: 20220303 Date Completed: 20220411 Latest Revision: 20220716

20240105

PMC8993143

10.2196/36022

35238784