Department of Philosophy, Boston University, 745 Commonwealth Avenue, Boston, MA 02215, United States of America.
Department of Psychology, University of Arizona, 1503 E University Blvd, Tucson, AZ 85721, United States of America.
Infect Genet Evol. 2021 Nov;95:105081. doi: 10.1016/j.meegid.2021.105081. Epub 2021 Sep 11.
Coronavirus disease 2019 (COVID-19) has harshly impacted Italy since its arrival in February 2020. In particular, provinces in Italy's Central and Northern macroregions have dealt with disproportionately greater case prevalence and mortality rates than those in the South. In this paper, we compare the morbidity and mortality dynamics of 16th and 17th century Plague outbreaks with those of the ongoing COVID-19 pandemic across Italian regions. We also include data on infectious respiratory diseases which are presently endemic to Italy in order to analyze the regional differences between epidemic and endemic disease. A Growth Curve Analysis allowed for the estimation of time-related intercepts and slopes across the 16th and 17th centuries. Those statistical parameters were later incorporated as criterion variables in multiple General Linear Models. These statistical examinations determined that the Northern macroregion had a higher intercept than the Southern macroregion. This indicated that provinces located in Northern Italy had historically experienced higher plague mortalities than Southern polities. The analyses also revealed that this geographical differential in morbidity and mortality persists to this day, as the Northern macroregion has experienced a substantially higher COVID-19 mortality than the Southern macroregion. These results are consistent with previously published analyses. The only other stable and significant predictor of epidemic disease mortality was foreign urban potential, a measure of the degree of interconnectedness between 16th and 17th century Italian cities. Foreign urban potential was negatively associated with plague slope and positively associated with plague intercept, COVID-19 mortality, GDP per capita, and immigration per capita. Its substantial contribution in predicting both past and present outcomes provides a temporal continuity not seen in any other measure tested here. Overall, this study provides compelling evidence that temporally stable geographical factors, impacting both historical and current foreign pathogen spread above and beyond other hypothesized predictors, underlie the disproportionate impact COVID-19 has had throughout Central and Northern Italian provinces.
自 2020 年 2 月新冠疫情在意大利爆发以来，意大利一直深受其害。特别是意大利中北部大区的省份所面临的病例流行率和死亡率，比南部省份更高。在本文中，我们将比较 16 世纪和 17 世纪黑死病爆发与当前意大利各地正在进行的 COVID-19 大流行的发病率和死亡率动态。我们还包括了目前意大利流行的传染性呼吸道疾病的数据，以便分析传染病和地方病之间的区域差异。增长曲线分析允许我们估算 16 世纪和 17 世纪的时间相关截距和斜率。这些统计参数后来被纳入多个一般线性模型中作为标准变量。这些统计检验确定，北方大区的截距高于南方大区。这表明，意大利北部地区的历史瘟疫死亡率高于南部地区。分析还表明，这种发病率和死亡率的地域差异一直持续到今天，因为北方大区的 COVID-19 死亡率明显高于南方大区。这些结果与之前发表的分析一致。唯一另一个稳定且显著的传染病死亡率预测因子是外国城市潜力，这是衡量 16 世纪和 17 世纪意大利城市之间相互联系程度的一个指标。外国城市潜力与瘟疫斜率呈负相关，与瘟疫截距、COVID-19 死亡率、人均国内生产总值和人均移民呈正相关。它在预测过去和现在的结果方面做出了重要贡献，这在任何其他测试的指标中都没有出现过。总的来说，这项研究提供了令人信服的证据，表明在时间上稳定的地理因素，影响了历史和当前外来病原体的传播，这比其他假设的预测因子更为重要，这是 COVID-19 在意大利中部和北部省份造成不成比例影响的原因。
