Quantification of the sensitivity of early detection surveillance

Understanding drivers and barriers to stakeholder participation in syndromic surveillance for application in Australia

Early detection of disease is crucial for an effective and timely disease control and eradication response and requires sensitive and robust surveillance systems. The use of early warning systems based on the systematic monitoring of health data and the identification of syndromes, known as syndromic surveillance systems, has been used for early identification of human and animal health events. Despite the marked development in animal health syndromic surveillance (AHSyS) systems in the last two decades, challenges for the implementation of functional AHSyS systems continue to exist, with limited research investigating stakeholder perspectives on these systems. The current project aimed to identify key drivers and barriers of livestock industry private sector stakeholder participation in syndromic surveillance in New South Wales (NSW), Australia. To achieve this aim, a qualitative study was conducted using semi-structured interviews with seven international syndromic surveillance experts and 17 private sector stakeholders, including abattoirs, knackeries, animal health consultants/veterinarians, research institutions, livestock industries, pharmaceutical companies, private veterinary laboratories and a national animal health body. The expert consultation identified that despite the significant advancements on AHSyS in the last two decades, implementation of AHSyS systems continue to be limited, with key considerations being the lack of data standardisation, issues with data privacy, data integration and the limited consideration of stakeholder needs for supporting decision-making and benefits from participation. Strong iterative collaboration with all stakeholders with high levels of trust, appropriate resourcing, and balance between regulatory and industry needs are required for supporting system sustainability. Animal health surveillance was important for all stakeholders in the consultation, however understanding of syndromic surveillance systems was limited. A significant amount of health and production data is already being collected by stakeholders; however, the data type and data collection platforms are highly variable, confirming the complexity for standardisation and integration. The major stakeholder concerns were in relation to privacy, protection of information and the potential commercial and/or trade implications of data misuse or misrepresentation, the required additional resourcing for participating and the regulatory nature of such system. Despite these concerns, all stakeholders showed interest in being involved in further discussions on the development of an AHSyS system. A successful AHSyS system should consider representativeness and quality of the data, simplicity in data collection and processing, clear benefits and value of the outputs, and strong collaboration across all relevant stakeholders. Outcomes from this project will inform future activities for the development of AHSyS initiatives in Australia.

Vaccination and surveillance for high pathogenicity avian influenza in poultry-current situation and perspectives

The International Alliance for Biological Standardization (IABS), in collaboration with the World Organization for Animal Health (WOAH) convened a hybrid meeting on 22-23 October 2024 at the WOAH Headquarters (HQ) in Paris, France to discuss the global state of vaccination and surveillance for high pathogenicity avian influenza (HPAI) in poultry. The primary objective of the meeting was to advance vaccination acceptance to both control virus spread and reduce disease. Vaccination is increasingly recognized as a tool to complement biosecurity, movement controls and stamping-out of infected flocks. However, concerns persist regarding the risk of undetected, sustained transmission (silent infection) in vaccinated flocks as a result of inadequate surveillance. This has contributed to both vaccination hesitancy and trade barriers. The meeting aimed to assess the current state of the art regarding HPAI surveillance programs in vaccinated populations and their effectiveness. Representatives of multiple stakeholders were invited to share their experiences and perspectives on the use of vaccination and accompanying surveillance to control the growing H5N1 panzootic and its global impact. Several conclusions and recommendations emerged as essential to advancing the acceptance of vaccination strategies. These included (1) the utility of quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) as a sensitive, specific and economical tool to detect virus in vaccinated populations, (2) regular testing of dead birds within a flock as a highly effective method for early detection of outbreaks in vaccinated flocks and demonstrating freedom from infection and, (3) the importance of collecting information on circulating field strains in the selection of candidate vaccine antigens to ensure adequate efficacy. Testing sentinel birds was deemed less effective for surveillance and serological testing of vaccinated birds was considered more useful for assessing immunity levels than for determining the infection status of a flock. There was broad agreement on the need to standardize surveillance outcomes in terms of accepted confidence levels to promote safe and fair trade. However, it was acknowledged that context and pragmatic considerations will shape the development of situation specific plans, which must be statistically valid, scientifically sound, economically feasible and operationally sustainable for both governments and industry. Concomitantly, it was recommended that trade policies tied to vaccination and surveillance should be based solely on science and risks. To this end, enforcement of existing international rules and resolution of disputes are considered a shared responsibility. Peer reviewed publications were proposed as a central mechanism for developing the stronger guidelines needed to facilitate fair trade agreements and enable implementation of global vaccination programs. Rapid dissemination of information, consistent messaging and exchange of virus isolates were also seen as critical for coordinating an effective global response to controlling HPAI.

Quantification of early detection surveillance in PRRS-free regions

In May 2022, a national control program targeting porcine reproductive and respiratory syndrome virus was launched in Denmark, and the first regions are approaching a PRRS-free status. Hence, the question now arises as to how the surveillance should be performed to identify new incursions of the PRRS virus in PRRS-free regions as early as possible. The aim of the present study was to quantify the early detection sensitivity of the current and alternative PRRS surveillance systems in Denmark at a regional level. The current PRRS surveillance system is composed of a notifiable surveillance component and an active serological surveillance component, consisting of monthly sampling (breeding and multiplier farms) or yearly sampling (production farms). The results from the present study estimated that the current surveillance system would have a 21.5 % [16.0 %;32.4 %]min;max probability of detecting an incursion of PRRS into a PRRS-free region. If monthly serum samples were taken on all farms, the probability would be increased to 87.7 % [87.4 %;88.6 %]min;max. Adding a syndromic surveillance component to the existing surveillance system resulted in an early detection sensitivity of 23.9 % [17.6 %;34.6 %]min;max, while targeted risk-based sampling resulted in probabilities of 27.8 % [17.9 %;33.8 %]min;max and 62.6 % [17.9 %;79.5 %]min;max for quarterly or monthly sampling frequencies, respectively. Results from the present study indicate a relatively low chance of detecting newly infected farms within the first month in a PRRS-free region with the current surveillance system. The probability of early detection of PRRS can be increased either by increasing the sampling frequency on all farms or by using targeted risk-based sampling.

Non-detection of emerging and re-emerging pathogens in wastewater surveillance to confirm absence of transmission risk: A case study of polio in New York

Infectious disease surveillance systems, including wastewater surveillance, can alert communities to the threat of emerging pathogens. We need methods to infer understanding of transmission dynamics from non-detection. We estimate a sensitivity of detection of poliovirus in wastewater to inform the sensitivity of wastewater surveillance for poliovirus using both a clinical epidemiology and fecal shedding approach. We then apply freedom from disease to estimate the sensitivity of the wastewater surveillance network. Estimated sensitivity to detect a single poliovirus infection was low, <11% at most wastewater treatment plants and <3% in most counties. However, the maximum threshold for the number of infections when polio is not detected in wastewater was much lower. Prospective wastewater surveillance can confirm the absence of a polio threat and be escalated in the case of poliovirus detection. These methods can be applied to any emerging or re-emerging pathogen, and improve understanding from wastewater surveillance.

Development and validation of HBV surveillance models using big data and machine learning

BACKGROUND

The construction of a robust healthcare information system is fundamental to enhancing countries' capabilities in the surveillance and control of hepatitis B virus (HBV). Making use of China's rapidly expanding primary healthcare system, this innovative approach using big data and machine learning (ML) could help towards the World Health Organization's (WHO) HBV infection elimination goals of reaching 90% diagnosis and treatment rates by 2030. We aimed to develop and validate HBV detection models using routine clinical data to improve the detection of HBV and support the development of effective interventions to mitigate the impact of this disease in China.

METHODS

Relevant data records extracted from the Family Medicine Clinic of the University of Hong Kong-Shenzhen Hospital's Hospital Information System were structuralized using state-of-the-art Natural Language Processing techniques. Several ML models have been used to develop HBV risk assessment models. The performance of the ML model was then interpreted using the Shapley value (SHAP) and validated using cohort data randomly divided at a ratio of 2:1 using a five-fold cross-validation framework.

RESULTS

The patterns of physical complaints of patients with and without HBV infection were identified by processing 158,988 clinic attendance records. After removing cases without any clinical parameters from the derivation sample (n = 105,992), 27,392 cases were analysed using six modelling methods. A simplified model for HBV using patients' physical complaints and parameters was developed with good discrimination (AUC = 0.78) and calibration (goodness of fit test p-value >0.05).

CONCLUSIONS

Suspected case detection models of HBV, showing potential for clinical deployment, have been developed to improve HBV surveillance in primary care setting in China. (Word count: 264).

Evaluation of a voluntary passive surveillance component in cattle through notification of excess mortality

Passive surveillance can be most effective in the early detection of disease outbreaks given that farmers observe their animals daily. The European Animal Health Law states that unexplained excess mortality should be reported to the veterinary authorities. In the Netherlands, in addition to notifications to the competent authority, Royal GD is commissioned a passive surveillance component that consists of a veterinary helpdesk and postmortem examination for early detection of emerging diseases. The aim of this study was to evaluate this voluntary passive surveillance component through excess mortality in cattle. Weekly on-farm mortality was calculated using the cattle Identification and Registration records. Mortality was assessed on regional level for dairy, veal and other beef cattle using a Generalized Linear Model (GLM) (log-link, negative binomial). We used a cumulative sum of the model residuals to identify periods of excess mortality. The mortality was defined as excessive when above five times the standard error. The analysis was also conducted on herd level, but these models did not converge. We checked for an association between the two passive surveillance components elements and excess mortality. A GLM (log-link, negative binomial) with the number of contacts or submissions per region as the dependent variables and excess mortality per region and year as independent variables was carried out. Overall, the models showed significantly higher use of passive surveillance components in periods of excess mortality compared to non-excess periods. In dairy cattle the odds for contact or submission were between 1.72 (1.59-1.86) and 2.02 (1.82-2.25). For veal calves we found the odds of 2.19 (1.18-4.04) and 2.24 (1.78-2.83) relative to periods without excess mortality. Beef cattle operations, other than veal, showed only an increased odds for postmortem submissions in calves of 3.71 (2.74-5.01), submissions for cattle and contact in general was not increased for this farm type. In conclusion, the voluntary passive surveillance component in the Netherlands is used more often in periods of excess mortality in cattle. The chance of getting a timely response is highest for dairy farms. For veal calf operations the chance of receiving a timely response is more likely for postmortem submissions. A comparison with passive surveillance for excess mortality in other countries was not possible because no literature could be found. However, the method of this study can be used by other countries to evaluate their passive surveillance. This would make comparison of the performance of passive surveillance in different countries possible.

West Nile virus surveillance using sentinel birds: results of eleven years of testing in corvids in a region of northern Italy

The natural transmission cycle of West Nile virus (WNV) involves birds as primary hosts and mosquitoes as vectors, but this virus can spread to mammals, human beings included. Asymptomatic infected donors pose a risk to the safety of blood transfusions and organ transplants, as WNV can be transmitted through these medical procedures. Since 2009, the region of Emilia-Romagna in northern Italy has been implementing an integrated surveillance system in order to detect WNV circulation in the environment at an early stage. Here we report the results of the two components of the surveillance system, the active testing of corvids and humans, and demonstrate that bird surveillance alone improves a surveillance system based solely on human case detection. As WNV risk reduction measures are applied on a provincial basis, we assessed the ability of this surveillance system component to detect virus circulation prior to the notification of the first human case for each province. Overall, 99 epidemic seasons were evaluated as a result of 11 years (2013-2023) of surveillance in the nine provinces of the region. In this period, 22,314 corvids were tested for WNV and 642 (2.9%) were found to be infected. WNV was generally first detected in birds in July, with sample prevalence peaks occurring between August and September. During the same period, 469 autochthonous human cases were notified, about 60% of which were reported in August. WNV was detected 79 times out of the 99 seasons considered. The virus was notified in birds 73 times (92.4%) and 60 times (75.9%) in humans. WNV was first or only notified in birds in 57 seasons (72.1%), while it was first or only notified in humans in 22 seasons (27.8%). Active surveillance in corvids generally allows the detection of WNV before the onset of human cases. Failure of virus detection occurred mainly in seasons where the number of birds tested was low. Our results show that active testing of a minimum of 3.8 corvids per 100 km2 provides a satisfactory timeliness in the virus detection, but for early detection of WNV it is crucial to test birds between mid-June and mid-August.

Exploring Options for Syndromic Surveillance in Aquaculture: Outbreak Detection of Salmon Pancreas Disease Using Production Data from Norwegian Farms

Syndromic surveillance (SyS) is an important tool for early warning and monitoring of health in human and animal populations, but its use in aquaculture has been limited. Our study objective was to design a SyS system for Atlantic salmon aquaculture and to evaluate its performance in detecting pancreas disease (PD) outbreaks caused by salmonid alphaviruses on farms. We defined SyS outbreak alarms as cases where monthly farm mortality exceeded predefined cutoffs or deviated significantly from expected values based on predictive generalized linear models. These models were trained for each salmon production area in Norway, using data from 2014 to 2017. The outcome variable was fish mortality per farm-month, and input variables were production and environmental predictors, as well as an offset for the number of fish at risk. We also added autoregressive components to explain temporal dependency within fish cohorts. Subsequently, data from 2018 to 2021 was used to parameterize and validate the SyS system's performance against the current national PD surveillance program, which relies on routine farm-screening tests using molecular techniques and reports of clinical findings. The study covered 19,119 farm-months, involving 1,618 fish cohorts. The performance of our SyS system varied across production areas, with sensitivity ranging from 80.5% to 87.4% and a false alarm rate of 45.3%-53.2%. The absence of alarms was usually observed in farms that were truly negative for PD, i.e., a negative predictive value range of 81.2%-94.0%. The median time for alarms being raised was either in the same month as the current PD surveillance program or 1 month prior or after it. Our results indicate that the SyS system is a valuable tool for monitoring mortality on salmon farms, but alarms are unspecific if evaluated against an individual disease (PD). Increasing the frequency and granularity of mortality reporting might improve the SyS system's performance.

EFSA Panel on Animal Health and Animal Welfare (AHAW), European Union Reference Laboratory for Avian Influenza, Nielsen SS, Alvarez J, Bicout DJ, Calistri P, Canali E, Drewe JA, Garin‐Bastuji B, Gortázar C, Herskin MS, Michel V, Miranda Chueca MÁ, Padalino B, Roberts HC, Spoolder H, Stahl K, Velarde A, Viltrop A, Winckler C, Bortolami A, Guinat C, Harder T, Stegeman A, Terregino C, Lanfranchi B, Preite L, Aznar I, Broglia A, Baldinelli F, Gonzales Rojas JL. Vaccination of poultry against highly pathogenic avian influenza - Part 2. Surveillance and mitigation measures

Selecting appropriate diagnostic methods that take account of the type of vaccine used is important when implementing a vaccination programme against highly pathogenic avian influenza (HPAI). If vaccination is effective, a decreased viral load is expected in the samples used for diagnosis, making molecular methods with high sensitivity the best choice. Although serological methods can be reasonably sensitive, they may produce results that are difficult to interpret. In addition to routine molecular monitoring, it is recommended to conduct viral isolation, genetic sequencing and phenotypic characterisation of any HPAI virus detected in vaccinated flocks to detect escape mutants early. Following emergency vaccination, various surveillance options based on virological testing of dead birds ('bucket sampling') at defined intervals were assessed to be effective for early detection of HPAIV and prove disease freedom in vaccinated populations. For ducks, virological or serological testing of live birds was assessed as an effective strategy. This surveillance could be also applied in the peri-vaccination zone on vaccinated establishments, while maintaining passive surveillance in unvaccinated chicken layers and turkeys, and weekly bucket sampling in unvaccinated ducks. To demonstrate disease freedom with > 99% confidence and to detect HPAI virus sufficiently early following preventive vaccination, monthly virological testing of all dead birds up to 15 per flock, coupled with passive surveillance in both vaccinated and unvaccinated flocks, is recommended. Reducing the sampling intervals increases the sensitivity of early detection up to 100%. To enable the safe movement of vaccinated poultry during emergency vaccination, laboratory examinations in the 72 h prior to the movement can be considered as a risk mitigation measure, in addition to clinical inspection; sampling results from existing surveillance activities carried out in these 72 h could be used. In this Opinion, several schemes are recommended to enable the safe movement of vaccinated poultry following preventive vaccination.

High quality of SARS-CoV-2 molecular diagnostics in a diverse laboratory landscape through supported benchmark testing and External Quality Assessment

A two-step strategy combining assisted benchmark testing (entry controls) and External Quality Assessments (EQAs) with blinded simulated clinical specimens to enhance and maintain the quality of nucleic acid amplification testing was developed. This strategy was successfully applied to 71 diagnostic laboratories in The Netherlands when upscaling the national diagnostic capacity during the SARS-CoV-2 pandemic. The availability of benchmark testing in combination with advice for improvement substantially enhanced the quality of the laboratory testing procedures for SARS-CoV-2 detection. The three subsequent EQA rounds demonstrated high quality testing with regard to specificity (99.6% correctly identified) and sensitivity (93.3% correctly identified). Even with the implementation of novel assays, changing workflows using diverse equipment and a high degree of assay heterogeneity, the overall high quality was maintained using this two-step strategy. We show that in contrast to the limited value of Cq value for absolute proxies of viral load, these Cq values can, in combination with metadata on strategies and techniques, provide valuable information for laboratories to improve their procedures. In conclusion, our two-step strategy (preparation phase followed by a series of EQAs) is a rapid and flexible system capable of scaling, improving, and maintaining high quality diagnostics even in a rapidly evolving (e.g. pandemic) situation.

A new methodology to extrapolate disease freedom to an area using surveillance results from selected aquatic populations

According to Chapter 1.4 of the World Organisation for Animal Health (WOAH) Aquatic Animal Health Code, an entire country or zone can be classified as free of a disease only if there is compelling evidence that all susceptible populations within the country or zone are free. However, the methods for achieving freedom are not prescribed in the WOAH standards and guidelines. Within this context, this paper describes a novel methodology to determine if surveillance results can be extrapolated from a study population to a target population. A framework of six criteria was developed to standardize a method for extrapolating surveillance results to other susceptible populations that have not been sampled. Criteria 1 assesses the internal validity for the freedom claim on the source population. Criteria 2 assesses which other susceptible populations have a non-negligible probability of exposure. Criteria 3 assesses whether the risk of infection upon exposure of the source population is the same or greater than each of the other susceptible populations. Finally, Criteria 4, 5 and 6 assess if the other susceptible populations would transmit the infection to the source population or if they have the same exposure pathways as the source population. We illustrate the use of this novel methodology using two hypothetical case scenarios. The presented methodology has the advantage of being applicable either retrospectively or prospectively. When applied retrospectively, it can be used to assess if the surveillance results of the source population can be extrapolated to the target population. When applied prospectively it can be used to design a more efficient surveillance system by selecting source populations from which it is easier to extrapolate surveillance results to the rest of the target population. Conclusions drawn using this methodology depend on the validity of the assumptions made when working through the methodology. We therefore recommend cautious application of the criteria and thorough review of all assumptions.

Epidemiology-driven approaches to surveillance in HPAI-vaccinated poultry flocks aiming to demonstrate freedom from circulating HPAIV

Incursion pressure of high pathogenicity avian influenza viruses (HPAIV) by secondary spread among poultry holdings and/or from infected migratory wild bird populations increases worldwide. Vaccination as an additional layer of protection of poultry holdings using appropriately matched vaccines aims at reducing clinical sequelae of HPAIV infection, disrupting HPAIV transmission, curtailing economic losses and animal welfare problems and cutting exposure risks of zoonotic HPAIV at the avian-human interface. Products derived from HPAIV-vaccinated poultry should not impose any risk of virus spread or exposure. Vaccination can be carried out with zero-tolerance for infection in vaccinated herds and must then be flanked by appropriate surveillance which requires tailoring at several levels: (i) Controlling appropriate vaccination coverage and adequate population immunity in individual flocks and across vaccinated populations; (ii) assessing HPAI-infection trends in unvaccinated and vaccinated parts of the poultry population to provide early detection of new/re-emerged HPAIV outbreaks; and (iii) proving absence of HPAIV circulation in vaccinated flocks ideally by real time-monitoring. Surveillance strategies, i.e. selecting targets, tools and random sample sizes, must be accommodated to the specific epidemiologic and socio-economic background. Methodological approaches and practical examples from three countries or territories applying AI vaccination under different circumstances are reviewed here.

The Role of Wildlife and Pests in the Transmission of Pathogenic Agents to Domestic Pigs: A Systematic Review

Wild animals and pests are important reservoirs and vectors of pathogenic agents that can affect domestic pigs. Rapid globalization, anthropogenic factors, and increasing trends toward outdoor pig production facilitate the contact between domestic pigs and wildlife. However, knowledge on the transmission pathways between domestic pigs and the aforementioned target groups is limited. The present systematic review aims to collect and analyze information on the roles of different wild animal species and pests in the spread of pathogens to domesticated pigs. Overall, 1250 peer-reviewed manuscripts published in English between 2010 and 2022 were screened through the PRISMA framework using PubMed, Scopus, and Web of Science databases. A total of 84 studies reporting possible transmission routes of different pathogenic agents were included. A majority of the studies (80%) focused on the role of wild boars in the transmission of pathogenic agents to pig farms. Studies involving the role of rodents (7%), and deer (6%) were the next most frequent, whereas the role of insects (5%), wild carnivores (5%), wild birds (4%), cats (2%), and badgers (1%) were less available. Only 3.5% of studies presented evidence-based transmission routes from wildlife to domestic pigs. Approximately 65.5% of the included studies described possible risks/risk factors for pathogens' transmission based on quantitative data, whereas 31% of the articles only presented a hypothesis or qualitative analysis of possible transmission routes or risk factors and/or contact rates. Risk factors identified include outdoor farms or extensive systems and farms with a low level of biosecurity as well as wildlife behavior; environmental conditions; human activities and movements; fomites, feed (swill feeding), water, carcasses, and bedding materials. We recommend the strengthening of farm biosecurity frameworks with special attention to wildlife-associated parameters, especially in extensive rearing systems and high-risk zones as it was repeatedly found to be an important measure to prevent pathogen transmission to domestic pigs. In addition, there is a need to focus on effective risk-based wildlife surveillance mechanisms and to raise awareness among farmers about existing wildlife-associated risk factors for disease transmission.

In-silico characterization of the relationship between the Porcine reproductive and respiratory syndrome virus prevalence at the piglet and litter levels in a farrowing room

BACKGROUND

Family oral fluids (FOF) sampling has been described as a sampling technique where a rope is exposed to sows and respective suckling litters and thereafter wrung to obtain fluids. PCR-based testing of FOF reveals presence of PRRS virus RNA only at the litter level, as opposed to conventional individual-animal-based sampling methods that demonstrate PRRSV RNA at the piglet level. The relationship between the PRRSV prevalence at the individual piglet level and at the litter level in a farrowing room has not been previously characterized. Using Monte Carlo simulations and data from a previous study, the relationship between the proportion of PRRSV-positive (viremic) pigs in the farrowing room, the proportion of litters in the farrowing room with at least one viremic pig, and the likely proportion of litters to be positive by a FOF RT-rtPCR test in a farrowing room was characterized, taking into account the spatial distribution (homogeneity) of viremic pigs within farrowing rooms.

RESULTS

There was a linear relationship between piglet-level- and litter-level prevalence, where the latter was always larger than the former. When the piglet-level prevalence was 1%, 5%, 10%, 20%, and 50%, the true-litter level prevalence was 5.36%, 8.93%, 14.29%, 23.21%, and 53.57%, respectively. The corresponding apparent-litter prevalence by FOF was 2.06%, 6.48%, 11.25%, 21.60%, and 51.56%, respectively.

CONCLUSION

This study provides matching prevalence estimates to help guide sample size calculations. It also provides a framework to estimate the likely proportion of viremic pigs, given the PRRSV RT-rtPCR positivity rate of FOF samples submitted from a farrowing room.

European Food Safety Authority (EFSA), Berezowski J, De Balogh K, Dórea FC, Ruegg S, Broglia A, Zancanaro G, Gervelmeyer A. Coordinated surveillance system under the One Health approach for cross-border pathogens that threaten the Union - options for sustainable surveillance strategies for priority pathogens

This report provides guidance for Member states who plan to submit applications under the work programme 'CP-g-22-04.01 Direct grants to Member States' authorities'. The priority pathogens on which the coordinated surveillance under the grant initiative shall focus have been identified in a prioritisation exercise with Member States and ECDC. These are Crimean Congo haemorrhagic fever, echinococcosis, hepatitis E, highly pathogenic avian influenza (HPAI), influenza in swine, Lyme disease, Q-fever, Rift Valley fever, tick-borne encephalitis, West Nile fever and Disease X (Disease Y of animals). Surveillance activities (surveillance cards) have been proposed for these agents in this report. Member States should select one or more diseases from the list of priority diseases and then choose surveillance activities from the surveillance cards and modify them where needed, to reflect their national needs and situation. Member States can also design alternative surveillance activities for the priority infectious agents that may better fit the epidemiological situation in their country. Further, this report provides a section on surveillance perspectives that links infectious agents to different hosts, allowing Member States to consider the testing for multiple infectious agents in samples from a single host population, as well as sections providing guidance on surveillance in vectors and wildlife and for Disease X (Disease Y in animals). Member States are encouraged to develop cross-sectoral collaborations and the report provides guidance on cross-sectoral collaboration to help them. Finally, there is a roadmap providing an overall description of the steps in the process of developing a surveillance system in order to apply for the grant.

Epidemiology of Ebolaviruses from an Etiological Perspective

Since the inception of the ebolavirus in 1976, 32 outbreaks have resulted in nearly 15,350 deaths in more than ten countries of the African continent. In the last decade, the largest (2013-2016) and second largest (2018-2020) ebolavirus outbreaks have occurred in West Africa (mainly Guinea, Liberia, and Sierra Leone) and the Democratic Republic of the Congo, respectively. The 2013-2016 outbreak indicated an alarming geographical spread of the virus and was the first to qualify as an epidemic. Hence, it is imperative to halt ebolavirus progression and develop effective countermeasures. Despite several research efforts, ebolaviruses' natural hosts and secondary reservoirs still elude the scientific world. The primary source responsible for infecting the index case is also unknown for most outbreaks. In this review, we summarize the history of ebolavirus outbreaks with a focus on etiology, natural hosts, zoonotic reservoirs, and transmission mechanisms. We also discuss the reasons why the African continent is the most affected region and identify steps to contain this virus.

Investing in preparedness for rapid detection and control of epidemics: analysis of health system reforms and their effect on 2021 Ebola virus disease epidemic response in Guinea

The 2014-2016 West Africa Ebola Virus Disease (EVD) Epidemic devastated Guinea's health system and constituted a public health emergency of international concern. Following the crisis, Guinea invested in the establishment of basic health system reforms and crucial legal instruments for strengthening national health security in line with the WHO's recommendations for ensuring better preparedness for (and, therefore, a response to) health emergencies. The investments included the scaling up of Integrated Disease Surveillance and Response; Joint External Evaluation of International Health Regulation capacities; National Action Plan for Health Security; Simulation Exercises; One Health platforms; creation of decentralised structures such as regional and prefectural Emergency Operation Centres; Risk assessment and hazard identification; Expanding human resources capacity; Early Warning Alert System and community preparedness. These investments were tested in the subsequent 2021 EVD outbreak and other epidemics. In this case, there was a timely declaration and response to the 2021 EVD epidemic, a lower-case burden and mortality rate, a shorter duration of the epidemic and a significant reduction in the cost of the response. Similarly, there was timely detection, response and containment of other epidemics including Lassa fever and Marburg virus disease. Findings suggest the utility of the preparedness activities for the early detection and efficient containment of outbreaks, which, therefore, underlines the need for all countries at risk of infectious disease epidemics to invest in similar reforms. Doing so promises to be not only cost-effective but also lifesaving.

Changes in Estimating the Wild Boar Carcasses Sampling Effort: Applying the EFSA ASF Exit Strategy by Means of the WBC-Counter Tool

African swine fever (ASF) is a devastating disease, resulting in the high mortality of domestic and wild pigs, spreading quickly around the world. Ensuring the prevention and early detection of the disease is even more crucial given the absence of licensed vaccines. As suggested by the European Commission, those countries which intend to provide evidence of freedom need to speed up passive surveillance of their wild boar populations. If this kind of surveillance is well-regulated in domestic pig farms, the country-specific activities to be put in place for wild populations need to be set based on wild boar density, hunting bags, the environment, and financial resources. Following the indications of the official EFSA opinion 2021, a practical interpretation of the strategy was implemented based on the failure probabilities of wrongly declaring the freedom of an area even if the disease is still present but undetected. This work aimed at providing a valid, applicative example of an exit strategy based on two different approaches: the first uses the wild boar density to estimate the number of carcasses need to complete the exit strategy, while the second estimates it from the number of wild boar hunted and tested. A practical free access tool, named WBC-Counter, was developed to automatically calculate the number of needed carcasses. The practical example was developed using the ASF data from Sardinia (Italian island). Sardinia is ASF endemic from 43 years, but the last ASFV detection dates back to 2019. The island is under consideration for ASF eradication declaration. The subsequent results provide a practical example for other countries in approaching the EFSA exit strategy in the best choices for its on-field application.

Linking digital surveillance and in-depth virology to study clinical patterns of viral respiratory infections in vulnerable patient populations

To improve the identification and management of viral respiratory infections, we established a clinical and virologic surveillance program for pediatric patients fulfilling pre-defined case criteria of influenza-like illness and viral respiratory infections. The program resulted in a cohort comprising 6,073 patients (56% male, median age 1.6 years, range 0–18.8 years), where every patient was assessed with a validated disease severity score at the point-of-care using the ViVI ScoreApp. We used machine learning and agnostic feature selection to identify characteristic clinical patterns. We tested all patients for human adenoviruses, 571 (9%) were positive. Adenovirus infections were particularly common and mild in children ≥1 month of age but rare and potentially severe in neonates: with lower airway involvement, disseminated disease, and a 50% mortality rate (n = 2/4). In one fatal case, we discovered a novel virus: HAdV-80. Standardized surveillance leveraging digital technology helps to identify characteristic clinical patterns, risk factors, and emerging pathogens.

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We used mobile health technology to enable clinical pattern recognition

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The ViVI ScoreApp provided precision data for cross-cohort meta-analysis

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Neonates with adenovirus infection are at risk of severe or fatal disease outcomes

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In one neonate with disseminated disease, we found a new adenovirus: HAdV-D80

Assessment of the Current Surveillance System for Human Leptospirosis in Ecuador by Decision Analytic Modeling

Leptospirosis is a globally disseminated zoonotic disease with no national surveillance systems. On the other hand, surveillance is crucial for improving population health, and surveillance systems produce data that motivates action. Unfortunately, like many other countries, Ecuador put in place a monitoring system that has never been tested. The goal of this study was to use scenario tree modeling to assess the sensitivity of Ecuador's current national surveillance system to human leptospirosis as the basis for an economic assessment of the system. We created a decision-tree model to analyze the current system's sensitivity. The inputs were described as probabilities distributions, and the model assessed the program's sensitivity as an output. The model also considers the geographical and weather variations across Ecuador's three continental regions: Andean, Amazonia, and the Coast. Several data sources were used to create the model, including leptospirosis records from Ecuador's Ministry of Public Health, national and international literature, and expert elicitation, all of which were incorporated in a Bayesian framework. We were able to determine the most critical parameters influencing each scenario's output (CSU) sensitivity through sensitivity analysis. The Coast region had the best sensitivity scenario, with a median of 0.85% (IC 95% 0.41-0.99), followed by the Amazonia with a median of 0.54% (CI 95% 0.18-0.99) and the Andes with a median of 0.29% (CI 95% 0.02-0.89). As per the sensitivity study, the most influential criteria on the system's sensitivity were "Attendance or probability of going to a health center" and "probability of having symptoms," notably for the Coast and Amazonia Regions.

Evaluation of Early Warning, Alert and Response System for Ebola Virus Disease, Democratic Republic of the Congo, 2018-2020

The 10th and largest Ebola virus disease epidemic in the Democratic Republic of the Congo (DRC) was declared in North Kivu Province in August 2018 and ended in June 2020. We describe and evaluate an Early Warning, Alert and Response System (EWARS) implemented in the Beni health zone of DRC during August 5, 2018–June 30, 2020. During this period, 194,768 alerts were received, of which 30,728 (15.8%) were validated as suspected cases. From these, 801 confirmed and 3 probable cases were detected. EWARS showed an overall good performance: sensitivity and specificity >80%, nearly all (97%) of alerts investigated within 2 hours of notification, and good demographic representativeness. The average cost of the system was US $438/case detected and US $1.8/alert received. The system was stable, despite occasional disruptions caused by political insecurity. Our results demonstrate that EWARS was a cost-effective component of the Ebola surveillance strategy in this setting.

Use of Slaughterhouses as Sentinel Points for Genomic Surveillance of Foot-and-Mouth Disease Virus in Southern Vietnam

The genetic diversity of foot-and-mouth disease virus (FMDV) poses a challenge to the successful control of the disease, and it is important to identify the emergence of different strains in endemic settings. The objective of this study was to evaluate the sampling of clinically healthy livestock at slaughterhouses as a strategy for genomic FMDV surveillance. Serum samples (n = 11,875) and oropharyngeal fluid (OPF) samples (n = 5045) were collected from clinically healthy cattle and buffalo on farms in eight provinces in southern and northern Vietnam (2015-2019) to characterize viral diversity. Outbreak sequences were collected between 2009 and 2019. In two slaughterhouses in southern Vietnam, 1200 serum and OPF samples were collected from clinically healthy cattle and buffalo (2017 to 2019) as a pilot study on the use of slaughterhouses as sentinel points in surveillance. FMDV VP1 sequences were analyzed using discriminant principal component analysis and time-scaled phylodynamic trees. Six of seven serotype-O and -A clusters circulating in southern Vietnam between 2017-2019 were detected at least once in slaughterhouses, sometimes pre-dating outbreak sequences associated with the same cluster by 4-6 months. Routine sampling at slaughterhouses may provide a timely and efficient strategy for genomic surveillance to identify circulating and emerging FMDV strains.

Optimizing surveillance for early disease detection: Expert guidance for Ostreid herpesvirus surveillance design and system sensitivity calculation

To keep pace with rising opportunities for disease emergence and spread, surveillance in aquaculture must enable the early detection of both known and new pathogens. Conventional surveillance systems (designed to provide proof of disease freedom) may not support detection outside of periodic sampling windows, leaving substantial blind spots to pathogens that emerge in other times and places. To address this problem, we organized an expert panel to envision optimal systems for early disease detection, focusing on Ostreid herpesvirus 1 (OsHV-1), a pathogen of panzootic consequence to oyster industries. The panel followed an integrative group process to identify and weight surveillance system traits perceived as critical to the early detection of OsHV-1. Results offer a road map with fourteen factors to consider when building surveillance systems geared to early detection; factor weights can be used by planners and analysts to compare the relative value of different designs or enhancements. The results were also used to build a simple, but replicable, model estimating the system sensitivity (SSe) of observational surveillance and, in turn, the confidence in disease freedom that negative reporting can provide. Findings suggest that optimally designed observational systems can contribute substantially to both early detection and disease freedom confidence. In contrast, active surveillance as a singular system is likely insufficient for early detection. The strongest systems combined active with observational surveillance and engaged joint industry and government involvement: results suggest that effective partnerships can generate highly sensitive systems, whereas ineffective partnerships may seriously erode early detection capability. Given the costs of routine testing, and the value (via averted losses) of early detection, we conclude that observational surveillance is an important and potentially very effective tool for health management and disease prevention on oyster farms, but one that demands careful planning and participation. This evaluation centered on OsHV-1 detection in farmed oyster populations. However, many of the features likely generalize to other pathogens and settings, with the important caveat that the pathogens need to manifest via morbidity or mortality events in the species, life stages and environments under observation.

Population surveillance approach to detect and respond to new clusters of COVID-19

BACKGROUND

To maintain control of the coronavirus disease 2019 (COVID-19) epidemic as lockdowns are lifted, it will be crucial to enhance alternative public health measures. For surveillance, it will be necessary to detect a high proportion of any new cases quickly so that they can be isolated, and people who have been exposed to them traced and quarantined. Here we introduce a mathematical approach that can be used to determine how many samples need to be collected per unit area and unit time to detect new clusters of COVID-19 cases at a stage early enough to control an outbreak.

METHODS

We present a sample size determination method that uses a relative weighted approach. Given the contribution of COVID-19 test results from sub-populations to detect the disease at a threshold prevalence level to control the outbreak to 1) determine if the expected number of weekly samples provided from current healthcare-based surveillance for respiratory virus infections may provide a sample size that is already adequate to detect new clusters of COVID-19 and, if not, 2) to determine how many additional weekly samples were needed from volunteer sampling.

RESULTS

In a demonstration of our method at the weekly and Canadian provincial and territorial (P/T) levels, we found that only the more populous P/T have sufficient testing numbers from healthcare visits for respiratory illness to detect COVID-19 at our target prevalence level-assumed to be high enough to identify and control new clusters. Furthermore, detection of COVID-19 is most efficient (fewer samples required) when surveillance focuses on healthcare symptomatic testing demand. In the volunteer populations: the higher the contact rates; the higher the expected prevalence level; and the fewer the samples were needed to detect COVID-19 at a predetermined threshold level.

CONCLUSION

This study introduces a targeted surveillance strategy, combining both passive and active surveillance samples, to determine how many samples to collect per unit area and unit time to detect new clusters of COVID-19 cases. The goal of this strategy is to allow for early enough detection to control an outbreak.

Quantification of the sensitivity of early detection surveillance

Early detection surveillance is used for various purposes, including the early detection of non-communicable diseases (e.g. cancer screening), of unusual increases of disease frequency (e.g. influenza or pertussis outbreaks), and the first occurrence of a disease in a previously free population. This latter purpose is particularly important due to the high consequences and cost of delayed detection of a disease moving to a new population. Quantifying the sensitivity of early detection surveillance allows important aspects of the performance of different systems, approaches and authorities to be evaluated, compared and improved. While quantitative evaluation of the sensitivity of other branches of surveillance has been available for many years, development has lagged in the area of early detection, arguably one of the most important purposes of surveillance. This paper, using mostly animal health examples, develops a simple approach to quantifying the sensitivity of early detection surveillance, in terms of population coverage, temporal coverage and detection sensitivity. This approach is extended to quantify the benefits of risk-based approaches to early detection surveillance. Population-based clinical surveillance (based on either farmers and their veterinarians, or patients and their local health services) provides the best combination of sensitivity, practicality and cost-effectiveness. These systems can be significantly enhanced by removing disincentives to reporting, for instance by implementing effective strategies to improve farmer awareness and engagement with health services and addressing the challenges of well-intentioned disease notification policies that inadvertently impose barriers to reporting.

EFSA Panel on Animal Health and Welfare (EFSA AHAW Panel), Nielsen SS, Alvarez J, Bicout DJ, Calistri P, Depner K, Drewe JA, Garin‐Bastuji B, Gonzales Rojas JL, Gortázar Schmidt C, Herskin M, Michel V, Miranda Chueca MÁ, Pasquali P, Roberts HC, Sihvonen LH, Stahl K, Calvo AV, Viltrop A, Winckler C, Gubbins S, Antoniou S, Broglia A, Abrahantes JC, Dhollander S, Van der Stede Y. Rift Valley Fever - assessment of effectiveness of surveillance and control measures in the EU

Effectiveness of surveillance and control measures against Rift Valley Fever (RVF) in Mayotte (overseas France) and in continental EU were assessed using mathematical models. Surveillance for early detection of RVF virus circulation implies very low design prevalence values and thus sampling a high number of animals, so feasibility issues may rise. Passive surveillance based on notified abortions in ruminants is key for early warning and at present the only feasible surveillance option. The assessment of vaccination and culling against RVF in Mayotte suggests that vaccination is more effective when quickly implemented throughout the population, e.g. at a rate of 200 or 2,000 animals vaccinated per day. Test and cull is not an option for RVF control in Mayotte given the high number of animals that would need to be tested. If the risk of RVFV introduction into the continental EU increases, ruminant establishments close to possible points of disease incursion should be included in the surveillance. An enhanced surveillance on reproductive disorders should be applied during summer in risk areas. Serosurveillance targets of 0.3% animals should be at least considered. RVF control measures possibly applied in the continental EU have been assessed in the Netherlands, as an example. Culling animals on farms within a 20 km radius of detected farms appears as the most effective measure to control RVF spread, although too many animals should be culled. Alternative measures are vaccination in a 50 km radius around detection, ring vaccination between 20 and 50 km and culling of detected farms. The assessment of zoning showed that, following RVFV introduction and considering an R0 = 2, a mean vector dispersal of 10 km and 10 farms initially detected, RVFV would spread beyond a radius of up to 100 km or 50 km from the infected area with 10% or 55% probability, respectively.