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Changes in the spatial distribution of COVID-19 incidence in Italy using GIS-based maps.
Annals of Clinical Microbiology and Antimicrobials ( IF 5.7 ) Pub Date : 2020-07-18 , DOI: 10.1186/s12941-020-00373-z
Cecilia Acuti Martellucci 1, 2 , Ranjit Sah 3 , Ali A Rabaan 4 , Kuldeep Dhama 5 , Cristina Casalone 6 , Kovy Arteaga-Livias 7, 8 , Toyoaki Sawano 9, 10 , Akihiko Ozaki 11, 12 , Divya Bhandari 12 , Asaka Higuchi 12 , Yasuhiro Kotera 13 , Zareena Fathah 14 , Namrata Roy 15 , Mohammed Ateeq Ur Rahman 16 , Tetsuya Tanimoto 12 , Alfonso J Rodriguez-Morales 8, 17, 18
Affiliation  

Dear editor

Massive spreading of the pandemic Coronavirus Disease 2019 (COVID-19) in different continents [1, 2], have been observed [3]. Analyses mostly focused on the number of cases per country and administrative levels, multiple times without considering the relevance of the incidence rates. These help to see the concentration of disease among the population in terms of cases per 100,000 inhabitants. Even more, using geographical information systems (GIS)-based maps, stakeholders may rapidly analyze changes in the epidemiological situation [4,5,6,7]. Although the epidemic of COVID-19 caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) started in Italy on January 31, 2020, no reports on the use of GIS-based maps have been published to analyze the distinct differences in incidence rates across its regions and provinces during the last months. For these reasons, we have developed epidemiological maps of incidence rates using official populations, by regions (1st administrative level of the country) and provinces (2nd administrative level), for COVID-19 in Italy using GIS.

Surveillance cases data of the cumulative number at March 15, April 18, and June 8, 2020, officially reported by the Italian health authorities were used to estimate the cumulated incidence rates on those dates using reference population data on SARS-CoV-2 confirmed infections (cases/100,000 pop) and to develop the maps by regions and provinces, using the GIS software Kosmo® 3.1, as performed in previous related studies [6, 7]. Starting on March 8, 2020, the region of Lombardy, together with 14 additional northern and central provinces, in Piedmont, Emilia-Romagna, Veneto, and Marche, they were put under lockdown. On March 10, 2020, the government extended the lockdown measures to the whole country.

Up to March 15, 2020, after 44 days of epidemics, 24,053 cases of COVID-19 were reported in the country, for a cumulated rate of 39.6 cases/100,000 population, reaching 174,103 cases during April 18, 2020, for a rate of 286.78, and 232,855 cases during June 8, 2020, for a rate of 383.56. All the regions of the country have been affected, with rates ranging from 59.42 (Calabria) to 947.75 cases/100,000 population (Aosta Valley/Vallée d’Aoste) (June 8, 2020) (Fig. 1). Higher diversity is found in provinces, where incidence rates ranged from 28.23 (Sud Sardegna, Sardinia) to 1811.37 (Cremona, Lombardy) (June 8, 2020) (Table 1). At Lombardy are located five of the top ten provinces with higher incidence rates (Table 1, Fig. 1), with considerable increases and changes from March 15, 2020, to June 8, 2020, in approximately 3 months (Fig. 1, Table 1). Cremona (Lombardy), Piacenza (Emilia-Romagna), and Lodi (Lombardy) have become in the geographic core of the cumulated incidence rate of COVID-19 in the north of the country and Italy (Fig. 1).

Fig. 1
figure1

COVID-19 situation in Italy, on March 15, April 18, and June 8, 2020, by regions and provinces

Full size image
Table 1 Top ten provinces by incidence rate (cases/100,000 inhabitants), of COVID-19, Italy, on March 15, April 18, and June 8, 2020
Full size table

From the GIS-based maps, it is clear that spreading in the country is occurring from north regions and provinces such as Lombardy. On March 15, 2020, most of the southern regions were not affected (Fig. 1), but approximately a month later, all of them reported COVID-19 cases (Fig. 1), including the insular regions of Sicily and Sardinia. While the change between April 18 and June 8, has been 33%, there is still a concern in the country, mainly because, in this time, the number of deaths has reached over 34,000 deaths (14.6%).

Italy reached the top of countries with the highest number of reported COVID-19 cases, now is the ninth country in cumulated cases. It is the fourth in the European region, after Russia, the United Kingdom, and Spain. Italy represented one of the most significant sources of imported cases for other continents, as is the case of Latin America, that received their first cases from Milan, Lombardy [8,9,10].

Patient 1 of Italy (it was not possible to find patient 0) was discovered on February 20, 2020, when a 38-year-old man from the city of Codogno had shown up at the hospital. Since that date, two large clusters of outbreaks have spread first in Northern Italy, later all over the country (Fig. 1) [11]. Cases are multiplying, and the national healthcare system is collapsing [12,13,14]. Many regions are increasing intensive care beds, revolutionizing entire hospital wards. In Italy, the coordination of the swabs is managed regionally. Once the epidemic began, for example, the Veneto region started immediately with active surveillance, i.e., on asymptomatic, and this contained the spread of the virus compared to other Northern Regions.

The health system is indeed regionalized, and dispositions of the Ministry of Health are translated into multiple regional decrees and regulations, often at different timings [15]. Many regions, for example, adopted evolving criteria for testing and diagnosis, according to dispositions from the central Government, but also to test capacity, which was heavily reliant on the availability of reagents. Samples were collected either in healthcare facilities, in provisional collection points, or even in people’s houses, depending on the region and the phase of the pandemic. The epitome of these differences is the two most heavily affected regions, Lombardy and Veneto. Lombardy hospitalized, even cases with relatively modest symptoms, causing numerous nosocomial outbreaks (9% of infections were among health professionals until March). Veneto, instead, deployed widespread testing since the beginning, maintaining disease management as much as possible at the primary health care level [15].

The healthcare workers are facing COVID-19 pulling 12 h shifts in critical situations with minimal to non-existent personal protective equipment (PPE) [12,13,14]. Lacking PPE led both many healthcare workers to become COVID-19 positive (7145), and to the death of several doctors (51; about 9% of the total cases; March 27, 2020) [11].

As observed in the GIS-based maps, the COVID-19 spreading in the country has been significant and moving from north to south across the time, with provinces reaching more than 1000 cases per 100,000 inhabitants (Fig. 1) [12,13,14]. Differences in the incidence by regions would be related to different social and economic factors. Such as people who travel abroad, for whom there is a sharp difference between northern regions (about 26% of travelers) and central and southern regions (about 19%). Or net income at the household level, which is ranging from 35,000€ in the North-east to 26,000€ in the South [16]. Additionally, as has been recently suggested, climatic conditions could also influence the transmission of SARS-CoV-2 [17].

Testing capacity increased over time. While some degree of ascertainment bias is inevitable, the number of swabs performed nationally stabilized around 70,000 per day in mid-April when the peak in the number of active cases was registered (Fig. 1). From that point onwards, daily cases only decreased, consistently with the impact of the lockdown imposed in early March. Besides, and most importantly, while it is true that the epidemic might have gone undetected for some time before Case 1 was discovered in Codogno, the growth in ICU beds demand for subjects with respiratory failure that ensued in the following weeks is most likely explained by a substantial increase of cases.

Considering the limitations of diagnostics and the asymptomatic cases, these figures would be many times more. Further characterization studies should include multiple GIS-based maps with other variables at the regions and provinces levels such as deaths, hospitalizations, and ICU rates per population to understand better the critical situation of the country and its administrative levels.

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Author notes

  1. Cecilia Acuti Martellucci and Ranjit Sah contributed equally; the order was decided by seniority

Affiliations

  1. Section of Hygiene and Preventive Medicine, Department of Biomedical Sciences and Public Health, University of the Marche Region, Ancona, Italy

    Cecilia Acuti Martellucci

  2. Department of Global Health Policy, School of International Health, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan

    Cecilia Acuti Martellucci

  3. Department of Microbiology, Tribhuvan University Teaching Hospital, Institute of Medicine, Kathmandu, Nepal

    Ranjit Sah

  4. Molecular Diagnostic Laboratory, Johns Hopkins Aramco Healthcare, Dhahran, Saudi Arabia

    Ali A. Rabaan

  5. Division of Pathology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh, 243 122, India

    Kuldeep Dhama

  6. Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta (IZSPLV), Turin, Italy

    Cristina Casalone

  7. Faculty of Medicine, Universidad Nacional Hermilio Valdizán, Huánuco, Peru

    Kovy Arteaga-Livias

  8. Masters in Clinical Epidemiology and Biostatistics, Universidad Cientifica del Sur, Calle Cantuarias 398, Miraflores, 15074, Lima, Peru

    Kovy Arteaga-Livias & Alfonso J. Rodriguez-Morales

  9. Department of Surgery, Sendai City Medical Center, Sendai, Miyagi, Japan

    Toyoaki Sawano

  10. Department of Public Health, Fukushima Medical University School of Medicine, Fukushima, Japan

    Toyoaki Sawano

  11. Department of Breast Surgery, Jyoban Hospital of Tokiwa Foundation, Iwaki, Fukushima, Japan

    Akihiko Ozaki

  12. Medical Governance Research Institute, Minato-ku, Tokyo, Japan

    Akihiko Ozaki, Divya Bhandari, Asaka Higuchi & Tetsuya Tanimoto

  13. University of Derby, Derby, UK

    Yasuhiro Kotera

  14. Royal Holloway, University of London, London, UK

    Zareena Fathah

  15. SRM Medical College, Hospital and Research Center, Chennai, India

    Namrata Roy

  16. Karnatak University, Dharwad, Karnataka, India

    Mohammed Ateeq Ur Rahman

  17. Public Health and Infection Research Group, Faculty of Health Sciences, Universidad Tecnologica de Pereira, Pereira, Risaralda, Colombia

    Alfonso J. Rodriguez-Morales

  18. Grupo de Investigación Biomedicina, Faculty of Medicine, Fundación Universitaria Autónoma de las Américas, Pereira, Risaralda, Colombia

    Alfonso J. Rodriguez-Morales

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Contributions

AJRM, conceptualization; data curation; formal analysis; methodology; software; writing-original draft; writing-review and editing. CAM, data curation; formal analysis; methodology; writing-review and editing. RS, AAR, KD, CC, KAL, TS, AO, DB, AH, YK, ZF, NR, MAUR, TT, writing-review and editing. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Alfonso J. Rodriguez-Morales.

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Martellucci, C.A., Sah, R., Rabaan, A.A. et al. Changes in the spatial distribution of COVID-19 incidence in Italy using GIS-based maps. Ann Clin Microbiol Antimicrob 19, 30 (2020). https://doi.org/10.1186/s12941-020-00373-z

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Keywords

  • SARS-CoV-2
  • COVID-19
  • Geographical information systems
  • Pandemic
  • Italy

中文翻译：
使用基于GIS的地图，意大利COVID-19发病率的空间分布变化。

亲爱的编辑

已观察到大流行性冠状病毒病2019（COVID-19）在不同大陆的大规模传播[1、2]，[3]。分析主要集中在每个国家和行政级别的病例数上，而没有考虑发病率的相关性。这些有助于根据每十万居民的病例数来查看人群中疾病的集中程度。使用基于地理信息系统（GIS）的地图，利益相关者甚至可以快速分析流行病学状况的变化[4,5,6,7]。尽管由严重急性呼吸系统综合症冠状病毒2（SARS-CoV-2）引起的COVID-19流行于2020年1月31日在意大利开始，在过去的几个月中，尚未发布有关使用基于GIS的地图的报告来分析其地区和省份发病率的明显差异。由于这些原因，我们使用GIS通过意大利（GIS）的地区（国家第一行政级别）和省（第二行政级别）使用官方人口开发了发病率的流行病学地图。

意大利卫生部门正式报告的2020年3月15日，4月18日和2020年6月8日的累计病例数数据使用SARS-CoV-2确诊感染的参考人群数据估算了这些日期的累积发病率（例/ 100000 POP）和开发由地区和省份的地图，使用GIS软件科斯莫® 3.1，如在先前的相关研究[6,7]进行。从2020年3月8日开始，伦巴第地区以及皮埃蒙特，艾米利亚-罗马涅，威尼托和马尔凯的其他14个北部和中部省份都被锁定。2020年3月10日，政府将封锁措施扩大到全国。

截至2020年3月15日，在经历了44天的流行之后，该国共报告了24053例COVID-19病例，累计发生率为39.6例/ 100000人口，到2020年4月18日达到174103例，发生率为286.78例以及2020年6月8日期间的232,855例案件，比率为383.56。该国所有地区均受到影响，发病率范围从59.42（卡拉布里亚）到947.75例/ 100,000人口（奥斯塔山谷/瓦莱达奥斯特）（2020年6月8日）（图1）。在各省发现多样性更高，这些省的发病率范围从28.23（撒丁岛南萨德纳）到1811.37（伦巴第大区克雷莫纳）（2020年6月8日）（表1）。伦巴第大区是发病率最高的十个省中的五个（表1，图1），从2020年3月15日到2020年6月8日，在大约3个月内有显着的增加和变化（图1，表1）。 1）。

图。1
图1

2020年3月15日，4月18日和2020年6月8日意大利各地区和省的COVID-19情况

全尺寸图片
表1 2020年3月15日，4月18日和2020年6月8日意大利COVID-19的发病率最高的十个省（病例/ 100,000居民）
全尺寸表

从基于GIS的地图中可以明显看出，该国的蔓延发生在伦巴第这样的北部地区和省份。到2020年3月15日，大多数南部地区没有受到影响（图1），但是大约一个月后，他们都报告了COVID-19病例（图1），包括西西里岛和撒丁岛的岛屿地区。尽管4月18日至6月8日之间的变化为33％，但该国仍存在担忧，主要是因为在此期间，死亡人数已超过34,000人（14.6％）。

意大利是报告COVID-19病例数最高的国家，目前是累计病例的第九个国家。它是仅次于俄罗斯，英国和西班牙的欧洲地区的第四位。意大利是其他大洲最重要的进口案例来源国之一，拉丁美洲是从伦巴第米兰收到第一批案件的拉丁美洲国家[8,9,10]。

2020年2月20日，一名来自科多诺市的38岁男子出现在医院，当时发现了意大利的1号病人（不可能找到0号病人）。从那时起，两个大的疫情爆发首先在意大利北部蔓延，随后在整个意大利蔓延（图1）[11]。病例在增加，国家医疗体系正在崩溃[12,13,14]。许多地区正在增加重症监护病床，彻底改变了整个医院的病房。在意大利，棉签的协调是按地区进行的。例如，一旦流行开始，威尼托地区立即开始进行积极监测，即无症状，与其他北部地区相比，其中包含病毒的传播。

卫生系统的确是区域性的，卫生部的部署通常会在不同的时间转换为多个区域性法令和法规[15]。例如，根据中央政府的部署，许多地区采用了不断发展的测试和诊断标准，但测试能力也严重依赖于试剂的可用性。根据大流行的地区和阶段，在医疗机构，临时收集点甚至在人们的房屋中收集样本。这些差异的缩影是两个受影响最大的地区，伦巴第和威尼托。伦巴第人住院，甚至症状相对较轻的病例，也引起了许多医院内暴发（直到3月份，其中9％的感染是在卫生专业人员中）。威尼托，

在危急情况下，医护人员面临的COVID-19轮班要12小时，而个人防护装备（PPE）最少或不存在[12,13,14]。缺少个人防护装备导致许多医护人员都成为COVID-19阳性（7145），并导致多名医生死亡（51；占病例总数的9％； 2020年3月27日）[11]。

正如基于GIS的地图所观察到的那样，COVID-19在该国的传播非常重要，并且在整个时间范围内从北向南传播，各省每100,000居民中有1000例以上（图1）[12,13， 14]。各地区发病率的差异将与不同的社会和经济因素有关。例如，出国旅行的人，在北部地区（约占旅行者的26％）与中部和南部地区（约占19％）之间存在明显差异。或家庭一级的纯收入，从东北的35,000欧元到南部的26,000欧元不等[16]。另外，正如最近所建议的，气候条件也可能影响SARS-CoV-2的传播[17]。

测试能力随时间增加。尽管一定程度的确定性偏差是不可避免的，但当活动病例数达到峰值时，全国4月中旬每天进行拭子检测的数量稳定在7万左右（图1）。从那时起，每日病例仅减少了，这与三月初实行的封锁的影响保持一致。此外，最重要的是，尽管确实确实可能在科多尼奥发现病例1之前一段时间就没有发现这种流行病，但以下几周随后出现的呼吸衰竭患者的ICU病床需求的增长很可能是由以下原因解释的：案件数量大幅增加。

考虑到诊断和无症状病例的局限性，这些数字会增加很多倍。进一步的特征研究应包括多个基于GIS的地图，以及区域和省级的其他变量，例如死亡，住院和每人的ICU率，以更好地了解国家及其行政级别的严峻状况。

如果需要。

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作者须知

  1. 塞西莉亚·阿库蒂·马泰鲁奇和兰吉特·萨赫贡献均等；顺序是由资历决定的

隶属关系

  1. 意大利安科纳马尔凯地区大学生物医学与公共卫生系卫生与预防医学科

    塞西莉亚·阿库蒂·马泰鲁奇

  2. 东京大学文京区东京大学医学研究科国际卫生学院全球卫生政策系

    塞西莉亚·阿库蒂·马泰鲁奇

  3. 尼泊尔加德满都医学院附属Tribhuvan大学教学医院微生物学系

    兰吉特（Ranjit Sah）

  4. 分子诊断实验室，约翰·霍普金斯·阿美医疗保健公司，沙特阿拉伯达兰

    阿里·拉班（Ali A.Rabaan）

  5. ICAR-印度兽医研究所病理学科，印度北方邦巴里利伊扎特纳加尔，243122，印度

    库尔迪普·达玛（Kuldeep Dhama）

  6. 义大利利古里亚和瓦莱达奥斯塔（IZSPLV）的皮埃蒙特动物基金会动物园（IZSPLV），都灵，意大利

    克里斯蒂娜·卡萨隆（Cristina Casalone）

  7. 秘鲁瓦努科国立赫尔米利奥·瓦尔迪桑大学医学院

    科维·阿塔加·利维亚斯

  8. 南方生命科学大学，临床流行病学和生物统计学硕士，卡米亚里亚斯大街398号，米拉弗洛雷斯，15074，秘鲁利马

    Kovy Arteaga-Livias和Alfonso J.Rodriguez-Morales

  9. 日本宫城县仙台市仙台市医疗中心外科

    泽野丰明

  10. 福岛医科大学医学院公共卫生系，日本福岛

    泽野丰明

  11. 日本福岛县磐城常磐基金会常磐医院乳腺外科

    尾崎明彦

  12. 日本东京都港区医学治理研究所

    尾崎明彦（Akihiko Ozaki），Divya Bhandari，Hi口（Asaka Higuchi）和谷本哲也

  13. 德比大学，英国德比

    小田康宏

  14. 英国伦敦大学皇家霍洛威学院

    Zareena Fathah

  15. 印度钦奈SRM医学院，医院和研究中心

    南拉塔·罗伊（Narrata Roy）

  16. 卡纳塔克大学，印度卡纳塔克邦达瓦

    穆罕默德·阿泰克·乌尔·拉曼

  17. 哥伦比亚佩里拉市Pereira Tecnologica de Pereira大学卫生科学学院公共卫生和感染研究小组

    阿方索·罗德里格斯·莫拉雷斯

  18. 哥斯达黎加大学医学博士学位，哥伦比亚里萨拉尔达佩雷拉大学医学院

    阿方索·罗德里格斯·莫拉雷斯

s
  1. Cecilia Acuti Martellucci查看作者出版物

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  2. Ranjit Sah查看作者出版物

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  5. 克里斯蒂娜·卡萨隆（Cristina Casalone）查看作者出版物

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会费

AJRM，概念化；数据策划；形式分析；方法; 软件; 书面原始草案；写作审查和编辑。CAM，数据管理；形式分析；方法; 写作审查和编辑。RS，AAR，KD，CC，KAL，TS，AO，DB，AH，YK，ZF，NR，MAUR，TT，写审阅和编辑。所有作者阅读并认可的终稿。

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开放存取本文是根据知识共享署名4.0国际许可许可的，该许可允许以任何媒介或格式使用，共享，改编，分发和复制，只要您对原始作者和出处提供适当的信誉，链接到知识共享许可，并指出是否进行了更改。本文的图像或其他第三方材料包含在该文章的知识共享许可中，除非在该材料的信用栏中另有说明。如果该材料未包含在该文章的创用CC许可中，并且您的预期用途未得到法律法规的许可或超出了许可的用途，则您需要直接获得版权所有者的许可。要查看此许可证的副本，请访问http://creativecommons.org/licenses/by/4.0/。

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引用本文

Martellucci，CA，Sah，R.，Rabaan，AA等。使用基于GIS的地图，意大利COVID-19发病率的空间分布变化。安临床微生物学Antimicrob 19， 30（2020）。https://doi.org/10.1186/s12941-020-00373-z

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  • DOI ：https ：//doi.org/10.1186/s12941-020-00373-z

关键词

  • SARS-CoV-2
  • 新冠肺炎
  • 地理信息系统
  • 大流行
  • 意大利
更新日期：2020-07-18
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