Herrero et al. BMC Public Health (2022) 22:1397 https://doi.org/10.1186/s12889-022-13695-8 RESEARCH Open Access SARS‑CoV‑2 Catalonia contact tracing program: evaluation of key performance indicators Mercè Herrero1*, Pilar Ciruela1,2, Meritxell Mallafré‑Larrosa1, Sergi Mendoza1, Glòria Patsi‑Bosch1, Èrica Martínez‑Solanas1, Jacobo Mendioroz1,3, Mireia Jané1,2,4 and Epidemiological Surveillance Network of Catalonia Abstract Background: Guidance on SARS-CoV-2 contact tracing indicators have been recently revised by international public health agencies. The aim of the study is to describe and analyse contact tracing indicators based on Catalonia’s (Spain) real data and proposing to update them according to recommendations. Methods: Retrospective cohort analysis including Catalonia’s contact tracing dataset from 20 May until 31 Decem‑ ber 2020. Descriptive statistics are performed including sociodemographic stratification by age, and differences are assessed over the study period. Results: We analysed 923,072 contacts from 301,522 SARS-CoV-2 cases with identified contacts (67.1% contact trac‑ ing coverage). The average number of contacts per case was 4.6 (median 3, range 1–243). A total of 403,377 contacts accepted follow-up through three phone calls over a 14-day quarantine period (84.5% of contacts requiring follow- up). The percentage of new cases declared as contacts 14 days prior to diagnosis evolved from 33.9% in May to 57.9% in November. All indicators significantly improved towards the target over time (p < 0.05 for all four indicators). Conclusions: Catalonia’s SARS-CoV-2 contact tracing indicators improved over time despite challenging context. The critical revision of the indicator’s framework aims to provide essential information in control policies, new indicators proposed will improve system delay’s follow-up. The study provides information on COVID-19 indicators framework experience from country’s real data, allowing to improve monitoring tools in 2021–2022. With the SARS-CoV-2 pan‑ demic being so harmful to health systems and globally, is important to analyse and share contact tracing data with the scientific community. Keywords: SARS-CoV-2, COVID-19, Contact tracing, Program evaluation, Key performance indicator Background To date, the coronavirus disease (COVID-19) pandemic represents the biggest and most pressing global pub- lic health challenge, with more than 100 million peo- ple infected and over 2.1 million people who lost their *Correspondence: merce.herrerog@gencat.cat lives as of December 2020 [1]. In the absence of a cura- 1 Sub‑Directorate General of Surveillance and Response to Public Health tive treatment and with limited percentage of world- Emergencies, Public Health Agency of Catalonia, Generalitat of Catalonia, wide population vaccinated mostly in high-income 08005 Barcelona, Spain Full list of author information is available at the end of the article countries, a diagnostic testing, contact tracing, and © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Herrero et al. BMC Public Health (2022) 22:1397 Page 2 of 13 Fig. 1 Temporal evolution of SARS-CoV-2 cases and accumulated incidence, main events and strategies. Catalonia, May–December 2020. *Red events more related with the contact tracing program supported isolation strategy (TTSI) is considered, as Catalonia, one of the 17 regions of Spain with a popula- key measures of epidemiological surveillance to miti- tion of 7.7 million [9], was hard hit over the first wave, gate such a highly infectious and rapid spread disease having the basic reproductive number (R0) soared up to recognizing both its long incubation period and rela- 4.6 during the first 2 weeks of March before lockdown tively short disease course [2, 3]. Contact tracing (CT) measures [10] while in Spain was 5.89 (95% Confidence is the process of identifying, assessing and managing Interval (CI): 5.46–7.09) for the same period [11]. The people who have been exposed to a disease through a first severe acute respiratory syndrome coronavirus 2 14-day follow-up from the last point of exposure with (SARS-CoV-2) confirmed case in Catalonia was on Feb- the aim to reduce the time from symptom onset to iso- ruary 25, 2020, in a young woman who had been travel- lation and subsequently prevent onward transmission ling Northern Italy [12], after a hard containment phase breaking the chains of transmission [4, 5]. being implemented by the Epidemiological Surveillance The first wave of COVID-19 pandemic spread rapidly Network of Catalonia (XVEC) between January and in Spain, one of the most affected countries in Europe, March 2020. From February 25 up to December 31, 2020, together with Italy [6]. The first imported case in Spain 301,522 cases were notified at the MediatorCovidCon- was detected in the Canary Islands on January 31, 2020 tacts (MCC) platform [13, 14]. A national seroprevalence [7]. After unsuccessful efforts to contain the infection and study conducted between April and May, 2020, reported a clear situation of community transmission, on March 14, an overall 5.0% (95% CI 4.7–5.4) presence of SARS- the Spanish government declared a state of alarm encom- CoV-2 antibodies among the Spanish population, being passing a number of restrictions in all its autonomous greater in Catalonia and specially in the province of Bar- communities [8], notably entailing a strict lockdown. celona with a 7.0% (95% CI 5,7 - 8,6) [15]. The strategy led to an inflection of the epidemic curve, as On March 14, 2020, the Catalan government put in 6 days later the cases began to decrease [7], and the lock- place a strong public health response to effectively down lasted up until May 11, 2020. A second wave took control the pandemic (Fig. 1 displays the strategy place early July and a third wave in October following highlighted over the study period). It included a TTSI summer time and reopening of the schools (Fig. 1). plan to maintain the gradual decrease of cases over the de-escalation phase [16], for which the XVEC was Herrero et al. BMC Public Health (2022) 22:1397 Page 3 of 13 appointed responsible. This network was created in Ascertainment of cases 2015 and links healthcare professionals and the epide- A confirmed case met the criteria of COVID-19 noti- miological surveillance services intervening in Catalo- fication in Catalonia if tested positive by polymerase nia at different territorial levels. Before the pandemic, chain reaction (PCR) tests, being the result stored in CT was already conducted by the XVEC for several the Taga19 platform. Case detailed information was disease monitoring programs, such as tuberculosis, collected as part of the “Case epidemiological inter- measles, meningococcal disease or diphtheria disease, view” included in the COVID-19 protocol [21], which among others [17]. COVID-19 put a tremendous pres- contain demographic and clinical data. The case’s elec- sure on the existing public health system and healthcare tronic card was transferred from Taga19 platform (from providers, which had to adapt to the evolving pandemic cases) to MCC platform (from contacts). increasing capacity at all levels. A call center started to run on 20 May, 2020, to trace and follow-up all SARS- CoV-2 cases’ close contacts (CC) as part of the support Contact tracing program for COVID‑19 provided by the XVEC and similarly to the system car- CT in our protocol, follows the Centers for Diseases ried out in other countries [18, 19]. Certain vulnerable Control and Prevention procedure: “Contact Tracing populations were specifically targeted, such as nursery refers to the process of notifying contacts of exposure, homes as well as those areas with high incidence [20]. addressing questions and concerns, referring for SARS- CT programs are essential to contribute in preventing CoV-2 testing, encouraging self-quarantine, monitoring onward transmission in the community [4]. A set of CT of symptoms, and assessing the need for additional sup- indicators were used in Catalonia since the beginning portive services during the quarantine period (14 days of the pandemic based on international public health from last exposure)” [25]. During case investigation we targets. As the pandemic evolved, revising the indica- ask for CC and exposure setting, since 48 h prior to the tors is an evaluation exercise of the programme. The date of symptom onset (and could be extended to up to study describes and analyses the indicators used in the 14 days before in case of local outbreak declaration) and catalan CT program and, to our knowledge, constitutes ended at the date of case isolation. For asymptomatic the first country experience providing a systematic confirmed cases, the period started 48 hours prior to framework based on real country data, and highlights the date of microbiological sample collection. how to guide a COVID-19 control strategy according to The definition of a CC was a person who did not wear CT performance. appropriate personal protection equipment, while hav- ing face-to-face contact with a confirmed case for more than 15 min (throughout 24 h) within less than a 2-m Methods distance during the investigation period. Study design and population All CC were notified through a telephonic call in We conducted a retrospective-ascertained study of which 14-day quarantine instructions were provided, CC from confirmed SARS-CoV-2 cases managed in starting from their last exposure to the index case and Catalonia between 20 May and 31 December, 2020. ending with at least 72 hours without symptoms. The Contacts were included from 48 hours prior to the process of “verification” consists in the capability to get first diagnosed case on 20 May, and followed up until in touch with a contact through phone at the first call. 14 days after the last exposure to the index case, being In this initial call, information on the CC prior expo- January 14, 2021 the last follow-up date, according to sure to a confirmed case, settings of exposure, personal our protocol [21]. risk factors, COVID-19-like symptoms, needs of sup- This study followed the STROBE reporting guide- port during quarantine and sick leave was activated, line and all methods in the study were carried out in if needed and were collected through the “Contacts accordance with the Helsinki guidelines and declara- epidemiological interview” included in the COVID- tion or any other relevant guidelines [22, 23]. Infor- 19 protocol [21]. CC were monitored on days 7 and 14 mation was collected by case interviewers and contact of quarantine and when any relevant symptoms were tracers at all surveillance system levels according to the detected (fever, cough, or other COVID-19-like symp- COVID-19 protocol from the Public Health Agency toms), a PCR test for COVID-19 was performed. Start- of Catalonia (PHAC). The protocol follows regular ing on August 7, the protocol was updated, and PCR updates according to the pandemic control strategies was performed on all CC regardless of symptoms. changes [16, 20, 21, 24]. Strict General Data Protection Regulation compliance was ensured in regard to the database storage system and the contact tracing workforce granted accesses. Herrero et al. BMC Public Health (2022) 22:1397 Page 4 of 13 Data sources and assessed Key Performance Indicators social setting peaks at age 20–39 years and 60–79 years (KPI) and variables (22.3 and 23.0%) (Fig. 4b). As part of the monitoring and evaluation of the CT pro- gram, weekly KPI were collected, analysed and reported KPI 3. Percentage of close contact traced and quarantined to inform and guide the region’s TTSI strategy. From all identified CC, contact tracers verified 99.8% Table 1 shows an overview, as well as its calculation, (841,131): 84.5% (712,226) were eligible to follow-up targets and rationale, of the four KPI that encompass 12 (KPI3.1a) and 15.3% (128,905) were excluded from the sub-indicators monitoring and evaluating the Catalan system due to four possible reasons (confirmed case, contact tracing program. The four designated study areas contact of another case, out of quarantine period or not assessed the percentage of new SARS-CoV-2 cases in a contact) (KPI3.1b). From the eligible CC to be fol- which CC are identified and reported to MCC (KPI1), the lowed-up, 47.9% (403,377) accepted and 36.7% (308,849) average number of CC per case and its associated expo- presented four type of incidences (data error, refusal, sure characteristics (KPI2), the percentage of identified unanswered, invalid ID) which prevented contact tracers CC traced and quarantined (KPI3) and their outcomes from following them up (Fig. 5 and Table S3). throughout follow-up in terms of symptom development With an average of 56.6%, the percentage of traced and progression to case (KPI4). CC accepting quarantine follow-up (KPI3) signifi- cantly improved from 45.6% in May to 66.6% in Octo- Results ber, and descending to 51.7% in December due to the From 20 May to 31 December, 2020, a total of 301,522 third wave registered in Catalonia (p < 0.05) (Fig. 6, new cases of SARS-CoV-2 infection (KPI 1.1) and its Table S2). The nature of events preventing contact associated 923,072 CC (KPI 2.1) were registered in the tracers from reaching out CC, significantly decreased MCC platform. A total of 202,451 cases had informed the unanswered calls and improvement in data qual- contacts. ity, in detriment of a greater refusal by CC (p < 0.05) (Table S3). The total follow-up calls performed at days KPI 1. Percentage of cases with identified contacts 0, 7 and 14 throughout the study period was 970,067 The average percentage of informed cases over the study (KPI3.3, Table S1). period was 67.1% (KPI1), with a significant increase from 38.4% in May to 72.7% in December (p < 0.05) (Fig. 2). KPI 4. Percentage of new cases that were known close Significant regional differences were observed (Table S2 contact and Fig. S1, p < 0.05). A total of 32.672 CC (8.1% of CC accepting follow-up over the initial call) reported symptoms consistent with KPI 2. Average number of close contact per case COVID-19 and, therefore, became suspected cases The average number of close contact per informed case (KPI4.1–2). Significant differences were observed over was 4.6 (KPI2) during the study period, with a median the study period (Table S1). of 3, an interquartile range 1–5 (KPI2.2) and a range of With an overall 53.3% in the percentage of new cases 1–243 (KPI2.3). The average per informed case expe- that had a known previous exposure to a confirmed rienced a sustained increase from 2.46 to 4.34 over case (KPI4, Table S2), this indicator related to the time despite the staggering workload secondary to an known transmission chains significantly increased from escalation of cases (p < 0.05) (Fig. 3, Table S2). Notably 33.9% in May to 57.9% in November decreasing again 79.5% of the informed cases reported between 1 and 5 to 36.5% in December due to the third wave (p < 0.05) CC per case, and 13.1% reported between 6 and 10 CC (Fig. 7, Table S2). (Table 2). A summary of all KPI shown from May to December, From August onwards, the setting of exposure in 2020 can be found in the Table S1. which the contact took place was systematically col- lected. The distribution of the CC registered from August Discussion to December (804,831 CC representing a 95.5% of all To our knowledge, this study is the first to present a sys- CC), displayed a clear predominance of household con- tematic KPI framework to assess contact tracing per- tacts (47.4%) versus other settings of exposure (Fig. 4a). formance with real country data, starting as soon as the Moreover, when we conducted an analysis with those CC contact tracing program was designed and progressively reporting information on age (subset of 465,856, 57.9% implemented. As the main agencies providing COVID- of CC from August to December), we showed this met- 19 guidance updated their contact tracing recommenda- ric was age-dependent (p < 0.05), with household being tions [4, 26], our study provides with an opportunity to especially common among CC aged 40–59 (67.4%), while critically assess our evaluation system. As the Centers for Table 1 Key Performance Indicators (KPI) framework evaluating the Catalan Contact Tracing (CT) program Indicator Sub-indicator Calculation Target Definition and rationale Herrero et al. BMC Public Health 1. Percentage of cases with identified 1.1. Number of confirmed cases KPI1 is obtained from the division of 1.2 80% Output indicator reflecting the system’s CC 1.2. Number of confirmed cases with by 1.1, which are both direct outputs capacity to conduct case investigation identified CC from MCC extractions. Results are strati‑ and contact elicitation. The higher it is, the fied geographically and temporally greater impact can the CT program have. 2. Average number of CC per case 2.1. Number of identified CC KPI2 is obtained from the division of 2.1 5 Output indicator translating both the 2.2. Median and interquartile range by 1.2. Both 2.1, 2.2 and 2.3 are direct quality and quantity of contact elicitation. (2022) 22:1397 outputs from MCC. Results are stratified Its disaggregation by setting of exposure 2.3. Minimum and maximum by age, geo-temporally and setting of informs other COVID-19 control measures, exposure as well as facilitates index cases prioriti‑ zation in case of high ratios of contacts per case, with the goal to prioritize high risk settings and timely detect potential clusters, trace CCs and avoid uncontrolled community transmission. 3. Percentage of CC traced and quar‑ 3.1. Number of traced CC (“verified CC”) KPI3 is obtained from the division of 3.2 70% Outcome indicator rendering the quality antined 3.1a. CC verified accepting follow-up by 3.1a. Both 3.1 (including a/b), 3.2 and of contact tracers’ duty. Two aspects are 3.3 are direct outputs from MCC. Results assessed: 3.1b. CC verified to be excluded from are stratified geo-temporally 1. contact notification, quarantine instruc‑ follow-up tions recommendation, social support 3.2. Number of verified CC accepting needs identification and COVID-19-like quarantine and follow-up symptoms investigation over tracing call at 3.3. Total amount of follow-up calls day 0 (through KPI 3.1–2); performed (day 0, 7 and 14) 2. contact adherence to quarantine during follow-up calls at day 7 and 14 (through KPI 3.3). 4. Percentage of new cases that were a 4.1. Number of followed-up CC develop‑ 4.1 is a direct output from MCC, 4.2 being 80% with sustained and Outcome indicator elucidating the control known CC ing COVID-19 symptoms at tracing call calculated from the division of 4.1 by 3.2. gradual increase over over transmission chains. The more 4.2. Percentage of contacts with symp‑ 4.3 is a direct output from T19 platform, time suspected cases identified early, as well as toms at tracing call 4.4 being calculated from the division of new cases reporting having been exposed 4.3 by the number of confirmed cases in to a known case, the greater the traceabil‑ 4.3. Number of new cases that were a T19 within the period of study. Results ity and prevention of transmission in the known CC are stratified geo-temporally community. KPI4 is an indirect measure of the secondary attack rate in our setting at the moment of the study Page 5 of 13 Herrero et al. BMC Public Health (2022) 22:1397 Page 6 of 13 Fig. 2 Number and percentage of confirmed COVID-19 cases with identified close contacts (KPI1). Catalonia, May–December 2020. The total COVID-19 cases reported is indicated under brackets in the lower side of the figure Disease Control and Prevention highlights, the use and severe COVID-19 outbreaks explaining its low KPI1 assessment of key indicators in contact tracing programs values (Table S2). Moreover, our targets were ration- for COVID-19 is important as it allows to detect areas of alized according to socio-demographic characteristics improvement and implement changes to strengthen the in Catalonia. For example, Laxminarayan et al. [27] program. described an average of 7.3 CC per case in two Indian Despite the increase in new SARS-CoV-2 cases states (KPI2), whilst in our context 4.6 was the aver- during our study period (especially May to October age over the study period, close to other European set- 2020, before the start of the third wave), all four KPI tings, like 2.4 CC per case in Italy [28]. included in our contact tracing program raised signifi- The usefulness of stratifying results by household, cantly over time closely approaching the set targets. social and non-household/non-social contacts’ set- Our targets were set in a manner that contact tracing ting of exposure is similar with other country strate- would play a key role to pandemic control, explain- gies like the United Kingdom [29, 30]. The household ing its ambitious objectives. For instance, related to setting predominance in our study is probably related KPI1 (percentage of cases with identified contacts), its to the nature of COVID-19 imposed restrictions upon goal was established at 80% instead of 75% as Harvard mobility and social distancing. The household setting, TTSI strategy proposes [2]. Localized clusters of cases more predominant among the CC aged 40–59, could and outbreaks can put pressure in the limited human be explained by habits from Spanish population and resources and therefore reduce the system’s capac- teleworking increasing since the pandemic. The social ity to timely finalize case investigation and identify setting was more common among the CC aged 20 to contacts, as we observed, for instance, in Lleida dur- 29 years, age group prone to outdoors activities and ing July and August 2020, a region that suffered from gatherings [31]. This finding exemplifies the need to Herrero et al. BMC Public Health (2022) 22:1397 Page 7 of 13 Fig. 3 Number of close contacts per informed COVID-19 case (KPI2). Catalonia, May–December 2020. The monthly average number of contacts per informed COVID-19 case is incorporated inside the box Table 2 Range of close contacts per informed COVID-19 case. and detection of high-risk contacts, towards which Catalonia, May–December 2020 epidemiologist can take additional control actions, Number of close contacts per Informed cases % of such as urgent massive population screening [33]. informed case informed In KPI3, we assessed the percentage of new contacts cases traced and quarantined by the contact tracers, identify- 1–5 160,867 79.5% ing the need for governmental support (regarding social 6–10 26,508 13.1% or housing support for quarantine compliance). After 11–15 4642 2.3% summer relaxation of restrictions, the increase in the > 15 10,434 5.2% number of cases during July till October (from 607 cases/ Total 202,451 100,0% day in July, to 2943 cases/day in October) put the system under pressure, but the system responded with increase in interviewers. KPI3 improved reaching the expected target of 70% (72.7%) in December (Table S1). tailor communication strategies to target audiences, as Regarding KPI4, the proportion of CC developing evidence suggests that response’s effectiveness partly symptoms of COVID-19 during May–July was 10.7% depends on how communities receive, perceive, and average compared with August–December 8.2%, as act on the information provided by governments and during May–July, only symptomatic cases were tested other agencies [32]. Furthermore, KPI2 proved to be and their CC interviewed. To assess SARS-CoV-2 sec- very practical in identifying potential superspreading ondary attack rate, we monitored the variable collected events and contributed to early cluster investigation over case investigation on whether new cases are arising Herrero et al. BMC Public Health (2022) 22:1397 Page 8 of 13 Fig. 4 a: Distribution of close contacts stratified by setting exposure (Catalonia, data from August 2020). b. Distribution of close contacts by setting of exposure and age group (data from August 2020, Catalonia) Herrero et al. BMC Public Health (2022) 22:1397 Page 9 of 13 to diagnosis”; “time from case diagnosis to interview and contact quarantine”; “CC per case disaggregate by risk category and settings” and “% of CC confirmed as new SARS-CoV-2 infection”. In a “low – moderate risk transmission” time, additional to main KPIs and the new previous indicators, four additional are proposed: percentage of cases with no CC to declare”; “percentage of tested CC for SARS-CoV-2”; “percentage of traced CC adherent to quarantine measures” and “percentage of vaccinated CC”, vaccination in Spain started on 27 December 2020. According to Kretzschmar et al. and other interna- tional public health agencies [35] CT will only be effec- tive if the time from case symptom onset to reception of test results is within 3 days, and the time from receiving test results to quarantine of contacts is less than 1 day. In addition, we suggest two scenarios in KPI evaluation depending on the weekly SARS-CoV-2 incidence. Measuring process indicators belonging to the “time from case symptom onset to diagnosis, and to case interview and contact quarantine” will allow identify- ing bottlenecks in the system and carrying out tailored measures in each geographical area depending on the area in which the delay is identified. Due to our two sep- arated COVID-19 databases, storing either case or CC information has impeded its calculation, but at the time of writing this manuscript, it has been a fusion of the two databases and these metrics have been incorporated Fig. 5 Flow chart elucidating the close contact verification process by tracers in Catalonia in our framework. Centralizing contact management through a unique platform allowing diligent KPI appraisal is fundamental among contacts previously identified by the program. [25]. A special CT monitoring and evaluation team was We observed a significant increase over time of this set in the PHAC, in charge of assessing KPI on a daily indicator (from 33.9% in May to 57.9% in November), basis and issuing weekly reports with overtime trends. A translating the program’s effectiveness in interrupt- traffic light code was established for the four presented ing SARS-CoV-2 transmission chains [4]. Universal CC indicators and, under pre-defined thresholds, the con- testing established in early August, probably contrib- cerned territories were closely followed-up in order to uted to improve this indicator, contributing to detect adjust the control strategy, either regionally or nationally. asymptomatic cases. Moreover, the scale-up of CT workforce with continu- The speed of testing, case investigation, and contact ous training and support, as well as its integration with elicitation and tracing is essential for success in inter- the primary care providers and the PHAC, has been a key rupting community transmission. Given that complete- cornerstone of the program. Towards the recommended ness data is extensively covered by KPI framework minimum of 30 tracers per 100 k population, during used in our program, in order to further improve the emergencies [36], our workforce has been gradually CT monitoring we propose expanding it with timeli- heightened at every level (primary care, hospital facilities ness related KPIs as its shown in Table 3 adapted from and epidemiological surveillance units). international authors guidance [26, 34]. The new frame- Several limitations related to information systems work proposes a set of new process indicators prior- hinder the systematic evaluation of CT and KPI in itized according to the incidence of cases. After this our context. First, the existence of de-centralized study, we reviewed the indicators used in 2020 and data systems for some occupational settings and during 2021 new indicator’s framework was proposed nursery homes, mean these subsets of exposures are to be added (Table 3). During a high incidence period partially connected to the MCC platform and there- (> 3000 cases/day): “time from case symptoms onset fore underrepresented in our study. Second, the lack Herrero et al. BMC Public Health (2022) 22:1397 Page 10 of 13 Fig. 6 Number and percentage of close contacts traced and quarantined (KPI3). Catalonia, May–December 2020. The total amount of close contacts deemed necessary to follow-up (KPI3.1a) is indicated under brackets in the lower side of the figure of integration of digital CT to complement manual on the system’s actionable incidences. The critical efforts, as Catalonia has only systematically imple- revision of the KPI framework aims to provide essen- mented a mobile application to follow-up confirmed tial information in COVID-19 control policies. Adding cases’ symptoms (App STOP COVID19 CAT). Finally, timeliness indicators to identify delays and bottle- in order to ensure “General Data Protection Regula- necks in the system will inform targeted interventions. tion” compliance, no information that could poten- This information has multiple public health implica- tially identify the index case was provided to the tions since it will contribute to interrupt the spread of contact over initial notification call. Such legal con- the SARS-CoV-2, to break chains of transmission in straint implied the date of last exposure, from which the community as well as to being prepared in front of the 14 days quarantine was calculated, could not be other future epidemics. This work provides additional disclosed [36], which haltered the estimation of quar- information on COVID-19 indicators framework expe- antine adherence. rience from country’s real data, and allowed us to improve our monitoring tools in 2021–2022. Conclusions As the COVID-19 pandemic unfolds, CT remains fun- Abbreviations damental to support a TTSI strategy complimentary COVID-19: Coronavirus disease; CT: Contact tracing; CC: Close contact; KPI: Key to vaccination rollout. The presented results highlight performance indicators; MCC: MediatorCovidContacts; PCR: Polymerase chain the success of attentive program monitoring and eval- reaction; PHAC: Public Health Agency of Catalonia; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2; TTSI: T, diagnostic testing, T, contact trac‑ uation: despite not reaching the pursued targets, the ing, and SI, supported isolation; XVEC: Epidemiological Surveillance Network consistent upward trend reflects the work performed of Catalonia. Herrero et al. BMC Public Health (2022) 22:1397 Page 11 of 13 Fig. 7 Number and percentage of new COVID-19 cases that were a known close contact (KPI4). Catalonia, May–December 2020. The total amount of new COVID-19 cases is indicated under brackets in the lower side of the figure Table 3 Contact tracing monitoring and evaluation through a proposal framework of Key Performance Indicators (KPIs) High risk transmission Low-moderate risk transmission Mitigation strategy Maintenance - suppression strategy Incidence > 3000 cases/day (> 40 cases/100,000 inhab./day) Incidence < 3000 cases/day (< 15/30 cases/100,000 inhab./day) Minimal set of CT KPIs (daily). Additional to the KPI1,2,3,4. All previous CT KPIs plus the following (daily) 1. Time from case symptoms onset to diagnosis 1. % of cases with no CC to declare 2. Time from case diagnosis to case interview and contact quarantine 2. % of tested CC for SARS-CoV-2 3. CC per case (median, IQR, minimum, maximum), disaggregate by risk category and 3. % of traced CC adherent to quarantine measures settings 4. % of vaccinated CC 4. % of CC confirmed as new SARS-CoV-2 infection Prioritize backward CT and test only high-risk CC (cluster scoring), prioritise CC Set up forward CT and initiate universal CC testing (addi‑ interview and follow up if < 7 days from last exposure to the case. tionally to all previous) Legend: percentage (%), informed case (IC), close contact (CC), inhabitants (inhab.), interquartil range (IQR), key performance indicator (KPI), contact tracing (CT) Disaggregate KPI results by the following variables: geographically (regional epidemiological surveillance unit), sociodemographic (gender and age), exposure setting, CC symptom onset, type of COVID-19-like symptom, tracing incidence, contact media, vaccination status, day of follow-up Supplementary Information Acknowledgments The authors would like to thank all those who contributed to the surveil‑ The online version contains supplementary material available at https://​doi.​ lance and control of the COVID-19 pandemic in Catalonia: Central and org/​10.​1186/​s12889-​022-​13695-8. regional Epidemiological Surveillance Services (XVEC/SUVEC), Microbi‑ ologists of the SNMC network, and all healthcare workers in the Catalan Additional file 1. healthcare network. Herrero et al. BMC Public Health (2022) 22:1397 Page 12 of 13 CONSORTIUM NAME*: XVEC, Epidemiological Surveillance Network of Nuria ; Follia Alsina, M. Nuria ; Catalonia. Ferras Prats, Joaquim ; Sofia Minguell ; Ferrus Serra, Gloria ; Pere Godoy ; Alseda Graells, Miquel ; Parron Bernabe, Ignacio ; Cirera Viladot, Catalonia. Anna ; Cristina Rius Gibert ; Patricia Consortia representative: Pilar Ciruela Navas, email: pilar.​cirue​la@​gencat.​cat García de Olalla Rizo ; Glòria Perez Albarracin ; Sala Farre, Maria-Rosa ; Clotet Romero, Martinez Mateo, Ana ­Isabel1; Laura . Pequeño Saco, S­ andra1; Leon Garcia, Agata R ­ aquel1; Authors’ contributions Domenech, ­Elisabet1; M.H.G., M.M-L and P.C. conceptualized and designed the study. E.M., S.M. Pericas Escalé, ­Carles1. performed statistical analysis and contributed in revisions. M.H.; MML; GPB; Barrabeig Fabregat, ­Irene4,2; reviewed the scientific literature, drafted and revised the manuscript. P.C, M.J. Rovira ­Faixa1, ­Ariadna4; and J.M. collaborated in the critical review and validation of the final manu‑ Carol Torrades, Mònica5; script. XVEC revised and approved the final manuscript. All authors have read Guadalupe Fernandez, ­Victor5; and agreed to the published version of the manuscript. Bes Montalat, ­Nuria6; Follia Alsina, M. N ­ uria6; Funding Ferras Prats, ­Joaquim7; This research received no external funding. Minguell Verges, Sofía8; Ferrús Serra, ­Gloria8; Availability of data and materials Godoy Garcia, P ­ ere9; All data relevant to the study are included in the article or uploaded as Alseda Graells, M ­ iquel9; supplementary information. The datasets analyzed during the study are not Parron Bernabe, ­Ignacio10; publicly available (as they are personals patient’s data) but are available from Cirera Viladot, ­Anna10; the corresponding author on reasonable request. Rius Gibert, ­Cristina11; García de Olalla Rizo, P ­ atricia11; Pérez Albarracín Glòria11; Declarations Sala Farre, Maria-Rosa12; Clotet Romero, ­Laura12; Ethics approval and consent to participate Herrero Garcia, Mercè1; All methods in the study were carried out in accordance with the Helsinki Pilar Ciruela Navas 1,2. guidelines and declaration or any other relevant guideline. Meritxell Mallafré-Larrosa 1. All data used in the analysis were collected during routine public health sur‑ Sergi Mendoza ­Funes1, veillance activities, as part of the legislated mandate of the Health Department Glòria Patsi-Bosch1, of Catalonia, the competent authority for the surveillance of communicable Èrica Martínez-Solanas1, diseases, which is officially authorized to receive, treat and temporarily store Jacobo Mendioroz Peña1,3; personal data on cases of infectious disease. Therefore, all study activities Mireia Jané C­ heca1,2. formed part of public surveillance, were thus exempt from institutional 4. Epidemiological Surveillance and Response to Public Health Emergencies Unit board review from the Public Health Agency of Catalonia, and did not require in Barcelona South, Agency of Public Health of Catalonia, Generalitat of Catalonia. informed consent. All data were fully anonymized. All experimental protocols 5. Epidemiological Surveillance and Response to Public Health Emergencies were approved by the Public Health Agency of Catalonia as patients data are Unit in Catalonia Central, Agency of Public Health of Catalonia, Generalitat of used in the study. Catalonia. 6. Epidemiological Surveillance and Response to Public Health Emergencies Consent for publication Unit in Girona. Public Health Agency of Catalonia. Generalitat of Catalonia. Not applicable. 7. Epidemiological Surveillance and Response to Public Health Emergen‑ cies Unit in Terres de l’Ebre. Public Health Agency of Catalonia. Generalitat of Competing interests Catalonia. The authors declare no conflict of interest. 8. Epidemiological Surveillance and Response to Public Health Emergencies Unit in Tarragona. Public Health Agency of Catalonia. Generalitat of Catalonia. Author details 1 9. Epidemiological Surveillance and Response to Public Health Emergencies Sub‑Directorate General of Surveillance and Response to Public Health Unit in Lleida. Public Health Agency of Catalonia. Generalitat of Catalonia. Emergencies, Public Health Agency of Catalonia, Generalitat of Catalonia, 10. Epidemiological Surveillance and Response to Public Health Emergencies 08005 Barcelona, Spain. 2 CIBER Epidemiologia y Salud Pública (CIBERESP), Unit in Barcelona North-Maresme. Public Health Agency of Catalonia. Generali‑ Instituto Salud Carlos III, 28029 Madrid, Spain. 3 Research Support Unit of Cen‑ tat of Catalonia. tral Catalonia, University Institute for Research in Primary Health Care Jordi 11. Epidemiological Surveillance and Response to Public Health Emergen‑ Gol i Gurina, 08272 Sant Fruitós de Bages, Spain. 4 Public Health, Barcelona cies Unit in Barcelona City. Public Health Agency of Barcelona. Generalitat of University, Barcelona, Spain. Catalonia. 12. Epidemiological Surveillance and Response to Public Health Emergencies Received: 22 June 2021 Accepted: 20 June 2022 Unit Vallès Occidental i Vallès Oriental, Public Health Agency of Catalonia, Spain. Sub-Directorate General of Surveillance and Response to Public Health Emergencies, Public Health Agency of Catalonia, Generalitat of Catalonia, 08005 Barcelona, Spain; Carmona Parcerisa, Gloria ; Martinez Mateo, Ana References Isabel ; Pequeño Saco, Sandra ; Leon Garcia, Agata Raquel ; Domenech Cutillas, Johns Hopkins Coronavirus Resource Center; 2020. Available from: Elisabet ; Pericas Escalé, Carles ; Barrabeig Fabregat, Irene ; Rovira 2. Harvard Global Health Institute. Pandemic resilience: getting it done. A Faixa, Ariadna ; Monica Carol ; Guadalupe Fernandez, Victor ; Bes Montalat, Herrero et al. BMC Public Health (2022) 22:1397 Page 13 of 13 3. Moore S, Hill EM, Tildesley MJ, Dyson L, Keeling MJ. Articles Vaccination and 21. Subdirectorate General for Surveillance and Public Health Emergency non-pharmaceutical interventions for COVID-19 : a mathematical modelling Response - Public Health Agency of Catalonia (PHAC). Acting Protocol study. Lancet Infect Dis. 2021;3099(21):1–11. https://​doi.​org/​10.​1016/​S1473-​ against SARS-CoV-2 Infection Cases. 7 August Update [in Catalan]. 2020. 3099(21)​00143-2. 22. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. 4. World Health Organization. Contact tracing in the context of COVID-19. The strengthening the reporting of observational studies in epidemiology Interim guidance. Pediatr i Med Rodz. 2020;16(1):33–9 Available from: http://​ (STROBE) statement: guidelines for reporting observational studies. Lancet. www.​pimr.​pl/​index.​php/​issues/​2020-​vol-​16-​no-1/​conta​ct-​traci​ng-​in-​the-​ 2007;370(9596):1453–7 Available from: http://​www.​scielo.​br/​scielo.​php?​ conte​xt-​of-​covid-​19-​inter​im-​guida​nce-​1721?​aid=​1465. script=​sci_​artte​xt&​pid=​S0034-​71672​01900​05012​11&​tlng=​en. 5. Bi Q, Wu Y, Mei S, Ye C, Zou X, Zhang Z, et al. Epidemiology and transmission 23. World Medical Association. Declaration of Helsinki. Ethical principles of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, for medical research involving human subjects. J Indian Med Assoc. China: a retrospective cohort study. Lancet Infect Dis. 2020;20(8):911–9 2009;107:403–5 Available from: https://​www.​wma.​net/​polic​ies-​post/​wma-​ Available from: https://​linki​nghub.​elsev​ier.​com/​retri​eve/​pii/​S1473​30992​ decla​ration-​of-​helsi​nki-​ethic​al-​princ​iples-​for-​medic​al-​resea​rch-​invol​ving-​ 03028​75. human-​subje​cts/ [cited 6 Jul 2021]. 6. Ortenzi F, Albanese E, Fadda M. A transdisciplinary analysis of covid-19 in 24. Subdirectorate General for Surveillance and Public Health Emergency Italy: the most affected country in europe. Int J Environ Res Public Health. Response - Public Health Agency of Catalonia (PHAC). Acting Protocol 2020;17(24):1–12. against SARS-CoV-2 Infection Cases. 18 October Update [in Catalan]. 2020. 7. Working group for the surveillance and control of COVID-19 in Spain. The Available from: https://​canal​salut.​gencat.​cat/​web/.​conte​nt/_A-​Z/C/​coron​ first wave of the COVID-19 pandemic in Spain: characterisation of cases avirus-​2019-​ncov/​mater​ial-. [cited 21 Dec 2020] and risk factors for severe outcomes, as at 27 April 2020. Eurosurveillance. 25. Centers for disease control and prevention (CDC). Operational considera‑ 2020;25(50):1–13. https://​doi.​org/​10.​2807/​1560-​7917.​ES.​2020.​25.​50.​20014​31. tions for adapting a contact tracing program to respond to the COVID-19 8. España. Ministerio de la Presidencia. Real Decreto 463/2020. In: Boletín pandemic: Centers Dis Control Prev; 2020. Available from: https://​www.​cdc.​ Oficial del Estado; 2020. p. 25390–400. gov/​coron​avirus/​2019-​ncov/​global-​covid-​19/​opera​tional-​consi​derat​ions-​ 9. Idescat. Xifres de població. Generalitat de Catalunya. 2020. Available from: conta​ct-​traci​ng.​html. https://​www.​idesc​at.​cat/​tema/​xifpo [cited 21 Dec 2020] 26. European Centre for Disease Prevention and Control. Monitoring and evalu‑ 10. Subdirectorate general for surveillance and public health emergency ation framework for COVID-19 response activities in the EU/EEA and the UK response - Public Health Agency of Catalonia (PHAC). Dades COVID data‑ – 17 June 2020. Stockholm: ECDC; 2020. base: Generalitat de Catalunya; 2020. Available from: https://​dades​covid.​cat/ 27. Laxminarayan R, Wahl B, Dudala SR, Gopal K, Mohan BC, Neelima S, et al. [cited 21 Dec 2020] Epidemiology and transmission dynamics of COVID-19 in two Indian states. 11. Hyafil A, Moriña D. Analysis of the impact of lockdown on the reproduction Science (80- ). 2020;370(6517):691–7 Available from: https://​scien​ce.​scien​ number of the SARS-Cov-2 in Spain. Gac Sanit. 2021;35(5):453–8. cemag.​org/​conte​nt/​early/​2020/​09/​29/​scien​ce.​abd76​72/​tab-​figur​es-​data. 12. Subdirectorate general for surveillance and public health emergency 28. Fateh-Moghadam P, Battisti L, Molinaro S, Fontanari S, Dallago G, Binkin response - Public Health Agency of Catalonia (PHAC). Technical summary N, et al. Contact tracing during phase I of the COVID-19 pandemic in the report of the COVID-19 cases in Catalonia. 19 March (no. 1) [in Catalan]. province of Trento, Italy: key findings and recommendations. medRxiv. 2020; 2020. Available from: http://​salut​publi​ca.​gencat.​cat/​web/.​conte​nt/​minis​ite/​ Available from: https://​www.​medrx​iv.​org/​conte​nt/​10.​1101/​2020.​07.​16.​ aspcat/​butll​etins/​vigil​ancia​aspcat/​2020/​45/​INFOR​ME-​TECNIC-​3-​COVID-​19_​ 20127​357v1.​artic​le-​info. 020420.​pdf 29. UK Government. NHS Test and Trace statistics (England): methodology: GOV. 13. Subdirectorate general for surveillance and public health emergency UK; 2020. Available from: https://​www.​gov.​uk/​gover​nment/​publi​catio​ns/​ response - Public Health Agency of Catalonia (PHAC). TAGA-COVID-19 nhs-​test-​and-​trace-​stati​stics-​engla​nd-​metho​dology/​nhs-​test-​and-​trace-​stati​ (T19) database: Generalitat de Catalunya; 2020. Available from: https://​salut.​ stics-​engla​nd-​metho​dology#​secti​on-1 [cited 19 Dec 2020]. gencat.​cat/​rsa/​AppJa​va/​faces/​pages/​Porta​lRSA.​jsp [cited 25 Jan 2021] 30. Haroon S, Chandan JS, Middleton J, Cheng KK. Covid-19: breaking the chain 14. Subdirectorate general for surveillance and public health emergency of household transmission. BMJ. 2020;370:1–2. response - Public Health Agency of Catalonia (PHAC). Technical summary 31. Latsuzbaia A, Herold M, Bertemes JP, Mossong J. Evolving social contact pat‑ report of the COVID-19 Cases in Catalonia. 24 August (no. 23) [in Catalan] terns during the COVID-19 crisis in Luxembourg. PLoS One. 2020;15:1–13. 2020. 32. Hyland-Wood B, Gardner J, Leask J, Ecker UKH. Toward effective govern‑ 15. Pollán M, Pérez-Gómez B, Pastor-Barriuso R, Oteo J, Hernán MA, Pérez-Olm‑ ment communication strategies in the era of COVID-19. Humanit Soc Sci eda M, et al. Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, Commun. 2021;8(1):30 Available from: http://​www.​nature.​com/​artic​les/​ population-based seroepidemiological study. Lancet. 2020;396(10250):535– s41599-​020-​00701w. 44 Available from: https://​linki​nghub.​elsev​ier.​com/​retri​eve/​pii/​S0140​67362​ 33. Subdirectorate general for surveillance and public health emergency 03148​35. response - Public Health Agency of Catalonia (PHAC). Outbreak Risk Assess‑ 16. Subdirectorate General for Surveillance and Public Health Emergency ment Form [in Catalan] 2020. Response - Public Health Agency of Catalonia (PHAC). Acting Protocol 34. Grantz KH, Lee EC, D’Agostino McGowan L, Lee KH, Metcalf JCE, Gurley ES, against SARS-CoV-2 Infection Cases. 2020. et al. Maximizing and evaluating the impact of test-trace-isolate programs: 17. Generalitat de Catalunya. Decret 203/2015, de 15 de setembre, pel qual es A modeling study. PLoS Med [Internet]. 2021;18(4):1–16. Available from: crea la Xarxa de Vigilància Epidemiològica i es regulen els sistemes de noti‑ http://​dx.​doi.​org/​10.​1371/​journ​al.​pmed.​10035​85. ficació de malalties de declaració obligatòria i brots epidèmics [in Catalan]: 35. Kretzschmar ME, Rozhnova G, Bootsma MCJ, van Boven M, van de Wijgert Diari Oficial de la Generalitat de Catalunya Generalitat de Catalunya; 2015. p. JHHM, Bonten MJM. Impact of delays on effectiveness of contact trac‑ 1–19. ing strategies for COVID-19: a modelling study. Lancet Public Health. 18. Bellmunt JM, Caylà JA, Millet JP. Contact tracing in patients infected with 2020;5(8):e452–9. https://​doi.​org/​10.​1016/​S2468-​2667(20)​30157-2. SARS-CoV-2. The fundamental role of primary health care and public health. 36. Chen C, Luo Q, Chong N, Westergaard S, Brantley E, Salsberg E, et al. Coro‑ Semergen. 2020;46:55–64. https://​doi.​org/​10.​1016/j.​semerg.​2020.​06.​001. navirus disease 2019 planning and response: a tale of 2 health workforce 19. De Brito Lima Prado NM, TRA R, SCL C, De Barros SG, Magno L, Dos estimator tools. Med Care. 2021;59(10):S420–7. Santos HLPC, et al. The international response of primary health care to COVID-19: document analysis in selected countries. Cad Saude Publica. 2020;36(12):e00183820. Publisher’s Note 20. Subdirectorate General for Surveillance and Public Health Emergency Springer Nature remains neutral with regard to jurisdictional claims in pub‑ Response - Public Health Agency of Catalonia (PHAC). Acting Protocol lished maps and institutional affiliations. against SARS-CoV-2 Infection Cases in the Re-Opening Phase. Follow-up Indicators. 29 June Update [in Catalan]. 2020. Available from: http://​canal​ salut.​gencat.​cat/​coron​avirus