Aggregated hosptial admissions for 122 wastewater treatmant plant catchment areas in Scotland

Data used in "The impact of signal variability on epidemic growth rate estimation from wastewater surveillance data" https://www.medrxiv.org/content/10.1101/2023.03.07.23286904v1Daily number of people admitted to hosptal with COVID-19 as primary cause from to 01/05/2021 to 02/09/2022. Data were aggregated first to datazones (using the postcode of the patient's place of residence as the geographical identifier), and then to wastewater tratement plant (WWTP) catchment areas. Since there is some overlap between datazones and WWTP catchemnts, it is not always possible to know which WWTP catchment a patient belongs to - in such cases their admission is divided between the two catchments proportionally to the amount of overlap. This is why numbers are fractional.For anonymisation purposes, numbers that are non-zero and less than 5 are not presented. Instead the data gives "<5"

本数据集所用数据来自论文《信号变异性对基于污水监测数据估算疫情增长率的影响》（The impact of signal variability on epidemic growth rate estimation from wastewater surveillance data），链接为https://www.medrxiv.org/content/10.1101/2023.03.07.23286904v1。数据涵盖2021年5月1日至2022年9月2日期间，以新型冠状病毒肺炎（COVID-19）为首要诊断病因的每日住院入院人数。数据首先以患者居住地邮政编码作为地理标识聚合至数据分区（datazones），随后进一步聚合至污水处理厂（wastewater treatment plant, WWTP）集水区。由于数据分区与污水处理厂集水区之间存在部分重叠，无法始终确定患者所属的污水处理厂集水区——在此类场景下，将患者入院人数按照重叠区域的占比分配至对应集水区，这也是数据数值为小数的原因。出于匿名化需求，所有非零且小于5的数值均未直接展示，取而代之的是以"<5"标注。