Heidelberg Institute of Global Health, University Hospital and Medical Faculty, Heidelberg University, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany.
Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Im Neuenheimer Feld 324, 69120, Heidelberg, Germany.
Eur J Health Econ. 2023 Dec;24(9):1545-1559. doi: 10.1007/s10198-022-01561-8. Epub 2023 Jan 19.
The COVID-19 pandemic has entered its third year and continues to affect most countries worldwide. Active surveillance, i.e. testing individuals irrespective of symptoms, presents a promising strategy to accurately measure the prevalence of SARS-CoV-2. We aimed to identify the most cost-effective active surveillance strategy for COVID-19 among the four strategies tested in a randomised control trial between 18th November 2020 and 23rd December 2020 in Germany. The four strategies included: (A1) direct testing of individuals; (A2) direct testing of households; (B1) testing conditioned on upstream COVID-19 symptom pre-screening of individuals; and (B2) testing conditioned on upstream COVID-19 symptom pre-screening of households.
We adopted a health system perspective and followed an activity-based approach to costing. Resource consumption data were collected prospectively from a digital individual database, daily time records, key informant interviews and direct observations. Our cost-effectiveness analysis compared each strategy with the status quo and calculated the average cost-effective ratios (ACERs) for one primary outcome (sample tested) and three secondary outcomes (responder recruited, case detected and asymptomatic case detected).
Our results showed that A2, with cost per sample tested at 52,89 EURO, had the lowest ACER for the primary outcome, closely followed by A1 (63,33 EURO). This estimate was much higher for both B1 (243,84 EURO) and B2 (181,06 EURO).
A2 (direct testing at household level) proved to be the most cost-effective of the four evaluated strategies and should be considered as an option to strengthen the routine surveillance system in Germany and similar settings.
COVID-19 大流行已进入第三年，继续影响全球大多数国家。主动监测，即对无症状个体进行检测，是一种准确测量 SARS-CoV-2 流行率的有前途的策略。我们旨在确定在 2020 年 11 月 18 日至 12 月 23 日在德国进行的一项随机对照试验中测试的四种策略中，针对 COVID-19 的最具成本效益的主动监测策略。这四种策略包括：（A1）直接对个体进行检测；（A2）直接对家庭进行检测；（B1）对个体进行 COVID-19 症状预筛查的条件下进行检测；和（B2）对家庭进行 COVID-19 症状预筛查的条件下进行检测。
我们采用卫生系统视角，并遵循基于活动的成本核算方法。资源消耗数据从数字个体数据库、每日时间记录、关键知情人访谈和直接观察中前瞻性收集。我们的成本效益分析将每种策略与现状进行比较，并计算出一个主要结果（测试样本）和三个次要结果（招募应答者、检测病例和无症状病例检测）的平均成本效益比（ACER）。
我们的结果表明，A2 的每个样本测试成本为 52.89 欧元，具有最低的主要结果（测试样本）ACER，紧随其后的是 A1（63.33 欧元）。对于 B1（243.84 欧元）和 B2（181.06 欧元），这一估计值要高得多。
A2（家庭层面的直接检测）被证明是四种评估策略中最具成本效益的策略，应被视为加强德国和类似环境中的常规监测系统的一种选择。
