key: cord-330364-ye02hwhy authors: Semenza, Jan C.; Sewe, Maquines Odhiambo; Lindgren, Elisabet; Brusin, Sergio; Aaslav, Kaja Kaasik; Mollet, Thomas; Rocklöv, Joacim title: Systemic resilience to cross‐border infectious disease threat events in Europe date: 2019-05-17 journal: Transbound Emerg Dis DOI: 10.1111/tbed.13211 sha: doc_id: 330364 cord_uid: ye02hwhy Recurrent health emergencies threaten global health security. International Health Regulations (IHR) aim to prevent, detect and respond to such threats, through increase in national public health core capacities, but whether IHR core capacity implementation is necessary and sufficient has been contested. With a longitudinal study we relate changes in national IHR core capacities to changes in cross‐border infectious disease threat events (IDTE) between 2010 and 2016, collected through epidemic intelligence at the European Centre for Disease Prevention and Control (ECDC). By combining all IHR core capacities into one composite measure we found that a 10% increase in the mean of this composite IHR core capacity to be associated with a 19% decrease (p = 0.017) in the incidence of cross‐border IDTE in the EU. With respect to specific IHR core capacities, an individual increase in national legislation, policy & financing; coordination and communication with relevant sectors; surveillance; response; preparedness; risk communication; human resource capacity; or laboratory capacity was associated with a significant decrease in cross‐border IDTE incidence. In contrast, our analysis showed that IHR core capacities relating to point‐of‐entry, zoonotic events or food safety were not associated with IDTE in the EU. Due to high internal correlations between core capacities, we conducted a principal component analysis which confirmed a 20% decrease in risk of IDTE for every 10% increase in the core capacity score (95% CI: 0.73, 0.88). Globally (EU excluded), a 10% increase in the mean of all IHR core capacities combined was associated with a 14% decrease (p = 0.077) in cross‐border IDTE incidence. We provide quantitative evidence that improvements in IHR core capacities at country‐level are associated with fewer cross‐border IDTE in the EU, which may also hold true for other parts of the world. Global health security has been undermined by infectious disease threat events (IDTE) such as severe acute respiratory syndrome (SARS) during 2002 (SARS) during -2003 (Dzau, Fuster, Frazer, & Snair, 2017; Morens, Folkers, & Fauci, 2008; Paules & Fauci, 2017) . These IDTE have caused substantial human suffering, placed considerable pressure on government resources, and inflicted significant economic damage. In financial terms, the cost of potential pandemics can amount to US$60 billion per year (Sands, Mundaca-Shah, & Dzau, 2016; Sands, Turabi, Saynisch, & Dzau, 2016) . However, if mortality costs are also taken into account, the annual cost can be as high as US$490 billion (Fan, Summers, & Jamison, 2016) . To prevent, protect against, control and provide a public health response to the international spread of disease, the World Health Organization (WHO) led efforts to update the International Health Regulations (IHR), and the updated regulations were adopted in 2005 and came into force in 2007 (Gostin, DeBartolo, & Friedman, 2015; World Health Organisation, 2005) . The aim was to prepare 'States Parties' to be able to detect and respond to these threats more quickly and effectively. To prevent Public Health Emergencies of International Concern (PHEIC) that can be a threat to global health security, the IHR oblige all 'States Parties' to establish IHR core capacities (Table 1) to detect, assess, notify and report events, and to respond to public health risks and emergencies. However, the persistent occurrence of IDTE post IHR implementation has raised questions about the implementation, compliance, and enforcement of these measures (Commission on a Global Health Risk Framework for the Future, 2016; Gostin et al., 2015; Gostin, DeBartolo, & Katz, 2017; Hoffman, 2014; Suthar, Allen, Cifuentes, Dye, & Nagata, 2018; World Health Organisation, 2015) help to identify deficiencies in IHR core capacities and IHR non-compliance, additional factors might be responsible for the emergence of IDTE (Gostin et al., , 2017 . It is possible that IHR core capacities are necessary but not sufficient to prevent the spread, control or response to such threats. They might not comprehensively identify and mitigate all the underlying drivers and determinants of IDTE in an increasingly interconnected and interdependent world (Glaesser, Kester, Paulose, Alizadeh, & Valentin, 2017; Jones et al., 2008; Morens et al., 2008; Paules & Fauci, 2017; Semenza, Rocklov, Penttinen, & Lindgren, 2016; Weiss & McMichael, 2004 in Europe as a result of global resurgence, increasing mobility and low vaccine uptake, in part related to vaccine hesitancy (Leong, 2018; Massad, 2018) . In 2017, the chikungunya virus was introduced into France and Italy by viraemic passengers and spread by Aedes albopictus mosquitoes, in part due to favourable climatic conditions (Lillepold, Rocklov, Liu-Helmersson, Sewe, & Semenza, 2019; Rezza, 2018; Rocklöv et al., 2019; Semenza & Suk, 2018) . International donors invested US$0.88 billion in outbreak preparedness, response and management of cross-border externalities in 2013 (Schaferhoff et al., 2015) and national governments have allocated substantial resources to IHR core capacity implementation. The ECDC is an EU agency with a mission to monitor, identify (early warning and assessment) and respond to serious cross-border health Union, 2013) This is analogous to the World Health Organization (WHO) IHR, where countries are also committed to further build their capacities to detect, assess and notify, and report on public health emergencies of international concern. Thus, the cross-border IDTE we analyse here lend themselves to an analysis of IHR core capacities. European Centre for Disease Prevention and Control conducts epidemic intelligence, a process of systematic collection and collation of information on threats from health from a variety of sources. Cross-border IDTE are assessed and verified to ensure they correspond to real public health events (for examples of IDTE see Semenza, Rocklov, et al., 2016) ). The assessment is based on an analysis, using IHR and Early Warning and Response System (EWRS) criteria and expert opinion (Table S1 ). ECDC initiated data collection for epidemic intelligence in June 2005. We analysed cross-border IDTE that originated in one of the 28 EU Member States (EU28) from 2010 to 2016. This time period included the migrant wave of 2015 (Semenza, Carrillo-Santisteve, et al., 2016) . We included IDTE with a risk of introduction to or propagation between Member States within the EU/EEA and IDTE that may require timely and coordinated EU action to contain (Table S1 ). We also analysed cross-border IDTE for other parts of the world that were recorded by ECDC epidemic intelligence, despite the low numbers of IDTE identified in those countries. We excluded travelassociated Legionnaires' disease outbreaks not originating in the EU28 from the analysis due to changes in reporting during the study period. WHO has developed an analytical framework for monitoring the achievement of IHR core capacities (World Health Organisation, 2013) . It allows country data for each core capacity, PoE and potential hazards to be analysed in detail (Table 1) Organisation, 2011). The main purpose of the framework is to enable countries to measure their current status and assess progress over time. Although individual IHR core capacities do not necessarily carry the same weight in an assessment of capabilities, all attributes are given the same weight in the framework. The scores range from 0% to 100% and were available from 2010 to 2016 (World Health Organisation). The analysis also included potential hazard 1 (zoonotic events) and potential hazard 2 (food safety); however, potential hazard 3 (chemical events) and potential hazard 4 (radiation emergencies) were not included in this analysis as they do not relate directly to IDTE. We determined the incidence of cross-border IDTE per capita in different countries based on the annual number of IDTE in a country divided by the annual population of the country. We modelled the relative change in the incidence of cross-border IDTE that originated in one country of the EU28, with a panel study, using a longitudinal general estimation equation framework (GEE) (Hanley, Negassa, Edwardes, & Forrester, 2003) with a Poisson log-link using random effects by country of origin to adjust for unmeasured confounders. We used an exchangeable correlation structure of the observations within countries, not to make prior assumptions of the temporal covariance structure. Initially, we performed univariate analysis of the association of each of the IHR core capacities to cross-border A total of 135 cross-border IDTE in the EU28 met the study inclusion criteria between 2010 and 2016 (Tables 2; S1). Over the study period, the composite measure of the IHR core capacities, which averages 11 capacities ( Analysis of IDTE in other parts of the world (besides EU28) was constrained by few cross-border IDTE detected in these countries and reported to ECDC. Nevertheless, a 10% increase in the mean of all IHR core capacities combined was associated with a 14% decrease (p = 0.077) in the incidence of cross-border IDTE in countries other than the EU28. Due to sample size constraints, a regional analysis was not possible. The results for specific IHR core capacities for all non-EU countries combined is provided in the Supporting Information (Table S3) . With respect to the association of a 10% increase in individual core capacities with the incidence of cross-border IDTE in the EU28, core capacity 1 (national legislation, policy and financing) was associated with a 10% decrease (95% CI: 0.84, 0.98) in the incidence of cross-border IDTE ( Figure 2 ); core capacity 2 (coordination and Figure 2) . A bivariate analysis adjusted for GDP per capita yielded essentially the same point estimates (Table S4 ). The principal component analysis revealed that three components explained the majority of variability of the IHR core capacities (Table S5) . However, only the first PCA score was significantly related to IDTE with an estimated 20% decrease in risk for every 10% increase in the core capacity score (95% CI: 0.73, 0.88). The individual core capacity weights related to this component was in line with the univariate analysis by relating mainly to IHR core capacities and less so to hazards. The IRR estimate from the first PCA score was also very similar to the estimate from the average composite measure of the IHR core capacities (decrease 20% vs. 19%), and further indicated that the IRR from the univariate analysis of IHR core capacities cannot be combined, due to the strong inter-core capacity correlations. & Semenza, 2012; Wolicki et al., 2016) . To this end, surveillance needs to be flexible and sensitive and to encompass syndromic, laboratory-based, population-based and sentinel systems (Wolicki et al., 2016) . In our analysis, national surveillance was associated with fewer IDTE, presumably because they were intercepted prior to international spread. Response (core capacity 4) was highly significant in our analysis. Systemic resilience to IDTE entails management and coordination of operations to rapidly respond to epidemic events that could develop into public health emergencies of national or international concern. It also includes active case management, infection control and decontamination, the importance of which were demonstrated during the MERS-CoV and Ebola outbreaks in 2012 and 2014, respectively (Siedner, Gostin, Cranmer, & Kraemer, 2015; Zaki, Boheemen, Bestebroer, Osterhaus, & Fouchier, 2012) . In our analysis, preparedness (core capacity 5) was also pro- sharing of infectious agents must occur through national or collaborating centres (Gostin et al., 2017 to the contrary, vaccination coverage for example, has declined in certain countries (e.g. Italy). It is important to bear in mind that this longitudinal study has a much stronger plausibility of an inference of a causal association than a simple cross-sectional study. We relate a change in IHR core capacities to a change in IDTE over time. Thus, due to this temporal association, the causal inference is high, but nevertheless potentially subject to biases. Another potential bias is reporting bias due to the self-assessment of IHR core capacities (Gostin et al., 2017) which could have shifted our results to the null. Selective reporting could also have contributed to the high inter-core capacity correlations, which decreases the granularity of our results. To overcome this lack of objective metrics, WHO has introduced a Joint External Evaluation (JEE) as part of the IHR Monitoring and Evaluation Framework (Bell et al., 2017; World Health Organisation, 2019a ). This is a voluntary, multi-sectoral, peer-to-peer process with external experts to assess country capacity to prevent, detect and rapidly respond to public health risks. Such an assessment is likely to be more objective than a self-assessment of IHR core capacities. As of April 2019, 82 countries had conducted a JEE, but only five of these countries were EU Member States (Belgium, Finland, Latvia, Lithuania and Slovenia) (World Health Organisation, 2019b). Once all EU28 countries have completed a JEE, analysis of the association with IDTE will need to be revisited. We would like to thank Dr. Piotr Kramarz (ECDC) and two anonymous reviewers for critical feedback on our manuscript. The views and opinions expressed herein are the authors' own and do not necessarily state or reflect those of ECDC. ECDC is not responsible for the data and information collation and analysis and cannot be held liable for conclusions or opinions drawn. No conflict of interest. JCS conceived the study, developed the study design, led the data analysis and data interpretation, and wrote the manuscript. MOS conducted the analysis and contributed to the writing. EL contributed to the writing. SB, KKA and TM collected epidemic intelligence data. JR led the data analysis and contributed to the writing of the manuscript. All authors reviewed and approved the final manuscript. Jan C. 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