Moniz Marta, Soares Patrícia, Nunes Carla
NOVA National School of Public Health, Public Health Research Center, Universidade NOVA de Lisboa, Lisbon, Portugal.
Comprehensive Health Research Center, Universidade NOVA de Lisboa, Lisbon, Portugal.
Port J Public Health. 2021 Apr 21;38(Suppl 1):40-46. doi: 10.1159/000515535.
At the end of January 2021, Portugal had over 700,000 confirmed COVID-19 cases. The burden of COVID-19 varies between and within countries due to differences in contextual and individual factors, transmission rates, and clinical and public health interventions.
To identify high-risk areas, between April and October, on a weekly basis and at the municipality level, and to assess the temporal evolution of COVID-19, considering municipalities classified by incidence levels.
This is an ecological study following a 3-step approach, i.e., (1) calculation of the relative risk (RR) of the number of new confirmed COVID-19 cases, weekly, per municipality, using a spatial scan analysis; (2) classification of the municipalities according to the European Centre for Disease Control incidence categorization on November 19; and (3) characterization of RR temporal evolution by incidence groups.
Between April and October, the mean RR was 0.53, with a SD of 1.44, varying between 0 and 46.4. Globally, the north and Lisbon and Tagus Valley (LVT) area were the regions with the highest number of municipalities with a RR above 3.2. In April and beginning of May, most of the municipalities with an RR above 3.2 were from the north, while between May and August most municipalities with an RR above 3.2 were from LVT area. Comparing the incidence in November and retrospectively analyzing the RR showed the huge variation, with municipalities with an RR of 0 at a certain time classified as extremely high in November.
Our results showed considerable variation in RR over time and space, with no consistent "better" or "worst" municipality. In addition to the several factors that influence COVID-19 transmission dynamics, there were some outbreaks over time and throughout the country and this may contribute to explaining the observed variation. Over time, on a weekly basis, it is important to identify critical areas allowing tailored and timely interventions in order to control outbreaks in early stages.
2021年1月底，葡萄牙有超过70万例新冠肺炎确诊病例。由于背景和个体因素、传播率以及临床和公共卫生干预措施的差异，新冠肺炎的负担在不同国家之间和国家内部有所不同。
在4月至10月期间，每周在市一级确定高风险地区，并根据发病率水平对各市进行分类，评估新冠肺炎的时间演变情况。
这是一项采用三步法的生态学研究，即：（1）使用空间扫描分析，每周计算每个市新确诊新冠肺炎病例数的相对风险（RR）；（2）根据11月19日欧洲疾病控制中心的发病率分类对各市进行分类；（3）按发病率组描述RR的时间演变特征。
4月至10月期间，平均RR为0.53，标准差为1.44，范围在0至46.4之间。总体而言，北部以及里斯本和塔霍河谷（LVT）地区是RR高于3.2的市数量最多的地区。4月和5月初，RR高于3.2的市大多来自北部，而5月至8月期间，RR高于3.2的市大多来自LVT地区。比较11月的发病率并回顾性分析RR显示出巨大差异，某些时候RR为0的市在11月被归类为极高风险。
我们的结果显示RR随时间和空间有很大变化，没有始终如一的“较好”或“较差”的市。除了影响新冠肺炎传播动态的几个因素外，随着时间推移在全国范围内出现了一些疫情暴发，这可能有助于解释观察到的变化。随着时间的推移，每周确定关键地区以便进行有针对性的及时干预，对于在早期控制疫情暴发很重要。
