Space-time cluster detection techniques for infectious diseases: A systematic review.

BACKGROUND: Public health organizations have increasingly harnessed geospatial technologies for disease surveillance, health services allocation, and targeting place-based health promotion initiatives. METHODS: We conducted a systematic review around the theme of space-time clustering detection techniques for infectious diseases using PubMed, Web of Science, and Scopus. Two reviewers independently determined inclusion and exclusion. RESULTS: Of 2,887 articles identified, 354 studies met inclusion criteria, the majority of which were application papers. Studies of airborne diseases were dominant, followed by vector-borne diseases. Most research used aggregated data instead of point data, and a significant proportion of articles used a repetition of a spatial clustering method, instead of using a "true" space-time detection approach, potentially leading to the detection of false positives. Noticeably, most articles did not make their data available, limiting replicability. CONCLUSION: This review underlines recent trends in the application of space-time clustering methods to the field of infectious disease, with a rapid increase during the COVID-19 pandemic.

Work: A Social Determinant of Health Worth Capturing.

Work is a recognized social determinant of health. This became most apparent during the COVID-19 pandemic. Workers, particularly those in certain industries and occupations, were at risk due to interaction with the public and close proximity to co-workers. The purpose of this study was to assess how states collected work and employment data on COVID-19 cases, characterizing the need for systematic collection of case-based specific work and employment data, including industry and occupation, of COVID-19 cases. A survey was distributed among state occupational health contacts and epidemiologists in all 50 states to assess current practices in state public health surveillance systems. Twenty-seven states collected some kind of work and employment information from COVID-19 cases. Most states (93%) collected industry and/or occupation information. More than half used text-only fields, a predefined reference or dropdown list, or both. Use of work and employment data included identifying high risk populations, prioritizing vaccination efforts, and assisting with reopening plans. Reported barriers to collecting industry and occupation data were lack of staffing, technology issues, and funding. Scientific understanding of work-related COVID-19 risk requires the systematic, case-based collection of specific work and employment data, including industry and occupation. While this alone does not necessarily indicate a clear workplace exposure, collection of these data elements can help to determine and further prevent workplace outbreaks, thereby ensuring the viability of the nation's critical infrastructure.

Early introduction and rise of the Omicron SARS-CoV-2 variant in highly vaccinated university populations.

BACKGROUND: The Omicron variant of SARS-CoV-2 is highly transmissible in vaccinated and unvaccinated populations. The dynamics governing its establishment and propensity towards fixation (reaching 100% frequency in the SARS-CoV-2 population) in communities remain unknown. In this work, we describe the dynamics of Omicron at three institutions of higher education (IHEs) in the greater Boston area. METHODS: We use diagnostic and variant-specifying molecular assays and epidemiological analytical approaches to describe the rapid dominance of Omicron following its introduction to three IHEs with asymptomatic surveillance programs. RESULTS: We show that the establishment of Omicron at IHEs precedes that of the state and region, and that the time to fixation is shorter at IHEs (9.5-12.5 days) than in the state (14.8 days) or region. We show that the trajectory of Omicron fixation among university employees resembles that of students, with a 2-3 day delay. Finally, we compare cycle threshold (Ct) values in Omicron vs. Delta variant cases on college campuses, and identify lower viral loads among college affiliates harboring Omicron infections. CONCLUSIONS: We document the rapid takeover of the Omicron variant at IHEs, reaching near-fixation within the span of 9.5-12.5 days despite lower viral loads, on average, than the previously dominant Delta variant. These findings highlight the transmissibility of Omicron, its propensity to rapidly dominate small populations, and the ability of robust asymptomatic surveillance programs to offer early insights into the dynamics of pathogen arrival and spread.

Wastewater Surveillance for Infectious Disease: A Systematic Review.

Wastewater surveillance of SARS-CoV-2 has been shown to be a valuable source of information regarding SARS-CoV-2 transmission and COVID-19 cases. Though the method has been used for several decades to track other infectious diseases, there has not been a comprehensive review outlining all of the pathogens that have been surveilled through wastewater. Herein we identify what infectious diseases have been previously studied via wastewater surveillance prior to the COVID-19 pandemic. Infectious diseases and pathogens were identified in 100 studies of wastewater surveillance across 38 countries, as well as themes of how wastewater surveillance and other measures of disease transmission were linked. Twenty-five separate pathogen families were identified in the included studies, with the majority of studies examining pathogens from the family Picornaviridae, including polio and non-polio enteroviruses. Most studies of wastewater surveillance did not link what was found in the wastewater to other measures of disease transmission. Among those studies that did, the value reported varied by study. Wastewater surveillance should be considered as a potential tool for many infectious diseases. Wastewater surveillance studies can be improved by incorporating other measures of disease transmission at the population-level including disease incidence and hospitalizations.

Automated Travel History Extraction From Clinical Notes for Informing the Detection of Emergent Infectious Disease Events: Algorithm Development and Validation.

BACKGROUND: Patient travel history can be crucial in evaluating evolving infectious disease events. Such information can be challenging to acquire in electronic health records, as it is often available only in unstructured text. OBJECTIVE: This study aims to assess the feasibility of annotating and automatically extracting travel history mentions from unstructured clinical documents in the Department of Veterans Affairs across disparate health care facilities and among millions of patients. Information about travel exposure augments existing surveillance applications for increased preparedness in responding quickly to public health threats. METHODS: Clinical documents related to arboviral disease were annotated following selection using a semiautomated bootstrapping process. Using annotated instances as training data, models were developed to extract from unstructured clinical text any mention of affirmed travel locations outside of the continental United States. Automated text processing models were evaluated, involving machine learning and neural language models for extraction accuracy. RESULTS: Among 4584 annotated instances, 2659 (58%) contained an affirmed mention of travel history, while 347 (7.6%) were negated. Interannotator agreement resulted in a document-level Cohen kappa of 0.776. Automated text processing accuracy (F1 85.6, 95% CI 82.5-87.9) and computational burden were acceptable such that the system can provide a rapid screen for public health events. CONCLUSIONS: Automated extraction of patient travel history from clinical documents is feasible for enhanced passive surveillance public health systems. Without such a system, it would usually be necessary to manually review charts to identify recent travel or lack of travel, use an electronic health record that enforces travel history documentation, or ignore this potential source of information altogether. The development of this tool was initially motivated by emergent arboviral diseases. More recently, this system was used in the early phases of response to COVID-19 in the United States, although its utility was limited to a relatively brief window due to the rapid domestic spread of the virus. Such systems may aid future efforts to prevent and contain the spread of infectious diseases.

Effect of SARS-CoV-2 digital droplet RT-PCR assay sensitivity on COVID-19 wastewater based epidemiology

We developed and implemented a framework for examining how molecular assay sensitivity for a viral RNA genome target affects its utility for wastewater-based epidemiology. We applied this framework to digital droplet RT-PCR measurements of SARS-CoV-2 and Pepper Mild Mottle Virus genes in wastewater. Measurements were made using 10 replicate wells which allowed for high assay sensitivity, and therefore enabled detection of SARS-CoV-2 RNA even when COVID-19 incidence rates were relatively low (~10−5). We then used a computational downsampling approach to determine how using fewer replicate wells to measure the wastewater concentration reduced assay sensitivity and how the resultant reduction affected the ability to detect SARS-CoV-2 RNA at various COVID-19 incidence rates. When percent of positive droplets was between 0.024% and 0.5% (as was the case for SARS-CoV-2 genes during the Delta surge), measurements obtained with 3 or more wells were similar to those obtained using 10. When percent of positive droplets was less than 0.024% (as was the case prior to the Delta surge), then 6 or more wells were needed to obtain similar results as those obtained using 10 wells. When COVID-19 incidence rate is low (~ 10−5), as it was before the Delta surge and SARS-CoV-2 gene concentrations are <104 cp/g, using 6 wells will yield a detectable concentration 90% of the time. Overall, results support an adaptive approach where assay sensitivity is increased by running 6 or more wells during periods of low SARS-CoV-2 gene concentrations, and 3 or more wells during periods of high SARS-CoV-2 gene concentrations.

Enhancing Respiratory Disease Surveillance to Detect COVID-19 in Shelters for Displaced Persons, Thailand-Myanmar Border, 2020-2021.

We developed surveillance guidance for COVID-19 in 9 temporary camps for displaced persons along the Thailand-Myanmar border. Arrangements were made for testing of persons presenting with acute respiratory infection, influenza-like illness, or who met the Thailand national COVID-19 Person Under Investigation case definition. In addition, testing was performed for persons who had traveled outside of the camps in outbreak-affected areas or who departed Thailand as resettling refugees. During the first 18 months of surveillance, May 2020-October 2021, a total of 6,190 specimens were tested, and 15 outbreaks (i.e., >1 confirmed COVID-19 cases) were detected in 7 camps. Of those, 5 outbreaks were limited to a single case. Outbreaks during the Delta variant surge were particularly challenging to control. Adapting and implementing COVID-19 surveillance measures in the camp setting were successful in detecting COVID-19 outbreaks and preventing widespread disease during the initial phase of the pandemic in Thailand.

Tracing the First Days of the SARS-CoV-2 Pandemic in Greece and the Role of the First Imported Group of Travelers.

The first SARS-CoV-2 case in Greece was confirmed on February 26, 2020, and since then, multiple strains have circulated the country, leading to regional and country-wide outbreaks. Our aim is to enlighten the events that took place during the first days of the SARS-CoV-2 pandemic in Greece, focusing on the role of the first imported group of travelers. We used whole-genome SARS-CoV-2 sequences obtained from the infected travelers of the group as well as Greece-derived and globally subsampled sequences and applied dedicated phylogenetics and phylodynamics tools as well as in-house-developed bioinformatics pipelines. Our analyses reveal the genetic variants circulating in Greece during the first days of the pandemic and the role of the group's imported strains in the course of the first pandemic wave in Greece. The strain that dominated in Greece throughout the first wave, bearing the D614G mutation, was primarily imported from a certain group of travelers, while molecular and clinical data suggest that the infection of the travelers occurred in Egypt. Founder effects early in the pandemic are important for the success of certain strains, as those arriving early, several times, and to diverse locations lead to the formation of large transmission clusters that can be estimated using molecular epidemiology approaches and can be a useful surveillance tool for the prioritization of nonpharmaceutical interventions and combating present and future outbreaks. IMPORTANCE The strain that dominated in Greece during the first pandemic wave was primarily imported from a group of returning travelers in February 2020, while molecular and clinical data suggest that the origin of the transmission was Egypt. The observed molecular transmission clusters reflect the transmission dynamics of this particular strain bearing the D614G mutation while highlighting the necessity of their use as a surveillance tool for the prioritization of nonpharmaceutical interventions and combating present and future outbreaks.

Overcoming variant mutation-related impacts on viral sequencing and detection methodologies.

Prompt and accurate pathogen identification, by diagnostics and sequencing, is an effective tool for tracking and potentially curbing pathogen spread. Targeted detection and amplification of viral genomes depends on annealing complementary oligonucleotides to genomic DNA or cDNA. However, genomic mutations that occur during viral evolution may perturb annealing, which can result in incomplete sequence coverage of the genome and/or false negative diagnostic test results. Herein, we demonstrate how to assess, test, and optimize sequencing and detection methodologies to attenuate the negative impact of mutations on genome targeting efficiency. This evaluation was conducted using in vitro-transcribed (IVT) RNA as well as RNA extracted from clinical SARS-CoV-2 variant samples, including the heavily mutated Omicron variant. Using SARS-CoV-2 as a current example, these results demonstrate how to maintain reliable targeted pathogen sequencing and how to evaluate detection methodologies as new variants emerge.

Serology as a Tool to Assess Infectious Disease Landscapes and Guide Public Health Policy.

Understanding the local burden and epidemiology of infectious diseases is crucial to guide public health policy and prioritize interventions. Typically, infectious disease surveillance relies on capturing clinical cases within a healthcare system, classifying cases by etiology and enumerating cases over a period of time. Disease burden is often then extrapolated to the general population. Serology (i.e., examining serum for the presence of pathogen-specific antibodies) has long been used to inform about individuals past exposure and immunity to specific pathogens. However, it has been underutilized as a tool to evaluate the infectious disease burden landscape at the population level and guide public health decisions. In this review, we outline how serology provides a powerful tool to complement case-based surveillance for determining disease burden and epidemiology of infectious diseases, highlighting its benefits and limitations. We describe the current serology-based technologies and illustrate their use with examples from both the pre- and post- COVID-19-pandemic context. In particular, we review the challenges to and opportunities in implementing serological surveillance in low- and middle-income countries (LMICs), which bear the brunt of the global infectious disease burden. Finally, we discuss the relevance of serology data for public health decision-making and describe scenarios in which this data could be used, either independently or in conjunction with case-based surveillance. We conclude that public health systems would greatly benefit from the inclusion of serology to supplement and strengthen existing case-based infectious disease surveillance strategies.

Fundamental limits on inferring epidemic resurgence in real time using effective reproduction numbers

We find that epidemic resurgence, defined as an upswing in the effective reproduction number (R) of the contagion from subcritical to supercritical values, is fundamentally difficult to detect in real time. Inherent latencies in pathogen transmission, coupled with smaller and intrinsically noisier case incidence across periods of subcritical spread, mean that resurgence cannot be reliably detected without significant delays of the order of the generation time of the disease, even when case reporting is perfect. In contrast, epidemic suppression (where R falls from supercritical to subcritical values) may be ascertained 5–10 times faster due to the naturally larger incidence at which control actions are generally applied. We prove that these innate limits on detecting resurgence only worsen when spatial or demographic heterogeneities are incorporated. Consequently, we argue that resurgence is more effectively handled proactively, potentially at the expense of false alarms. Timely responses to recrudescent infections or emerging variants of concern are more likely to be possible when policy is informed by a greater quality and diversity of surveillance data than by further optimisation of the statistical models used to process routine outbreak data.

Syndromic Surveillance Systems for Mass Gatherings: A Scoping Review.

Syndromic surveillance involves the near-real-time collection of data from a potential multitude of sources to detect outbreaks of disease or adverse health events earlier than traditional forms of public health surveillance. The purpose of the present study is to elucidate the role of syndromic surveillance during mass gathering scenarios. In the present review, the use of syndromic surveillance for mass gathering scenarios is described, including characteristics such as methodologies of data collection and analysis, degree of preparation and collaboration, and the degree to which prior surveillance infrastructure is utilized. Nineteen publications were included for data extraction. The most common data source for the included syndromic surveillance systems was emergency departments, with first aid stations and event-based clinics also present. Data were often collected using custom reporting forms. While syndromic surveillance can potentially serve as a method of informing public health policy regarding specific mass gatherings based on the profile of syndromes ascertained, the present review does not indicate that this form of surveillance is a reliable method of detecting potentially critical public health events during mass gathering scenarios.

Building a robust interface between public health authorities and medical institutions in a densely populated city: State-of-the-art integrated pandemic and emerging disease preparedness in the Greater Tokyo Area in Japan

Enhanced global travel networks have heightened the risk of emerging infectious diseases escalating into pandemics in a short time. The COVID-19 pandemic in 2020 reminded us of the importance of peacetime efforts to establish a basis for responding to a pandemic. Kawasaki City, one of the government-designated cities in the Greater Tokyo area in Japan, has made continuous efforts to reinforce preparedness and response capacity for emerging diseases. City authorities have sought to enhance communication and foster trust between the public health authority and medical institutions through a real-time information sharing system. The City has built trustworthy relationships with multiple stakeholders through various forms of joint exercises. Kawasaki City has also effectively developed a human resource development program, the “Field Epidemiology Training Program-Kawasaki (FETP-K), " that collaborates closely with the national FETP. This chapter introduces the details of a series of activities and lessons for reinforcing pandemic and emerging disease preparedness in urban areas in Japan. © 2021 Elsevier Inc. All rights reserved.

Effectiveness and use of reverse transcriptase polymerase chain reaction point of care testing in a large-scale COVID-19 surveillance system.

BACKGROUND: Rapid COVID-19 testing platforms can identify infected individuals at the point of care (POC), allowing immediate isolation of infected individuals and reducing the risk of transmission. While lab-based nucleic acid amplification testing (NAAT) is often considered the gold standard to detect SARS-CoV-2 in the community, results typically take 2-7 days to return, rendering POC testing a critical diagnostic tool for infection control. The National Football League (NFL) and NFL Players Association deployed a new POC testing strategy using a newly available reverse transcriptase polymerase chain reaction (RT-PCR) rapid test during the 2020 season, and evaluated diagnostic effectiveness compared to other available devices using real-world population surveillance data. METHODS: RT-PCR POC test results were compared to NAAT results from same-day samples by calculation of positive and negative concordance. Sensitivity analyses were performed for three subgroups: (1) individuals symptomatic at time of positive test; (2) individuals tested during the pilot phase of rollout; and (3) individuals tested daily. RESULTS: Among 4989 same-day POC/NAAT pairs, 4957 (99.4%) were concordant, with 93.1% positive concordance and 99.6% negative concordance. Based on adjudicated case status, the false negative rate was 0.2% and false positive rate was 2.9%. In 43 instances, the immediate turnaround of results by POC allowed isolation of infected individuals 1 day sooner than lab-based testing. Positive/negative concordance in sensitivity analyses were relatively stable. CONCLUSION: RT-PCR POC testing provided timely results that were highly concordant with lab-based NAAT in population surveillance. Expanded use of effective RT-PCR POC can enable rapid isolation of infected individuals and reduce COVID-19 infection in the community.

VPipe: an Automated Bioinformatics Platform for Assembly and Management of Viral Next-Generation Sequencing Data.

Next-generation sequencing (NGS) is a powerful tool for detecting and investigating viral pathogens; however, analysis and management of the enormous amounts of data generated from these technologies remains a challenge. Here, we present VPipe (the Viral NGS Analysis Pipeline and Data Management System), an automated bioinformatics pipeline optimized for whole-genome assembly of viral sequences and identification of diverse species. VPipe automates the data quality control, assembly, and contig identification steps typically performed when analyzing NGS data. Users access the pipeline through a secure web-based portal, which provides an easy-to-use interface with advanced search capabilities for reviewing results. In addition, VPipe provides a centralized system for storing and analyzing NGS data, eliminating common bottlenecks in bioinformatics analyses for public health laboratories with limited on-site computational infrastructure. The performance of VPipe was validated through the analysis of publicly available NGS data sets for viral pathogens, generating high-quality assemblies for 12 data sets. VPipe also generated assemblies with greater contiguity than similar pipelines for 41 human respiratory syncytial virus isolates and 23 SARS-CoV-2 specimens. IMPORTANCE Computational infrastructure and bioinformatics analysis are bottlenecks in the application of NGS to viral pathogens. As of September 2021, VPipe has been used by the U.S. Centers for Disease Control and Prevention (CDC) and 12 state public health laboratories to characterize >17,500 and 1,500 clinical specimens and isolates, respectively. VPipe automates genome assembly for a wide range of viruses, including high-consequence pathogens such as SARS-CoV-2. Such automated functionality expedites public health responses to viral outbreaks and pathogen surveillance.

Cooperative Research and Infectious Disease Surveillance: A 2021 Epilogue.

As the world looks forward to turning a corner in the face of the COVID-19 pandemic, it becomes increasingly evident that international research cooperation and dialogue is necessary to end this global catastrophe. Last year, we initiated a research topic: "Infectious Disease Surveillance: Cooperative Research in Response to Recent Outbreaks, Including COVID-19," which aimed at featuring manuscripts focused on the essential link between surveillance and cooperative research for emerging and endemic diseases, and highlighting scientific partnerships in countries under-represented in the scientific literature. Here we recognize the body of work published from our manuscript call that resulted in over 50 published papers. This current analysis describes articles and authors from a variety of funded and unfunded international sources. The work exemplifies successful research and publications which are frequently cooperative, and may serve as a basis to model further global scientific engagements.

Global health security threats and related risks in Latin America

The costs of responding and mitigating the COVID-19 pandemic is a critical example of the need for continual investment for global health security (GHS) preparedness in today’s inter-connected world as exemplified earlier with Ebola, Zika, and H1N1. Microbial diversity including endemic and emerging infectious diseases unique to Latin America are well known. When combined with geopolitical, socioeconomic, and environmental factors, especially climate change and human migration, which are expanding the range of disease vectors and pathogens, the risk for infectious disease outbreaks greatly increases. Enhancing GHS requires a greater awareness and cooperation within the region as well as more effective infectious disease surveillance systems. Frameworks such as the International Health Regulations and Global Health Security Agenda underpin policies to strengthen health systems. Greater international cooperation aimed to effectively enhance infectious disease surveillance are pivotal to increasing trust among partner countries and strengthen health security systems and best practices to respond and mitigate infectious disease outbreaks. Here we discuss infectious disease threats and risks associated with the current socioeconomic and political climate that influence GHS in order to demonstrate the need for further investment.

Bacterial Epidemiology and Antimicrobial Resistance Profiles in Children Reported by the ISPED Program in China, 2016 to 2020.

The Infectious Disease Surveillance of Pediatrics (ISPED) program was established in 2015 to monitor and analyze the trends of bacterial epidemiology and antimicrobial resistance (AMR) in children. Clinical bacterial isolates were collected from 11 tertiary care children's hospitals in China in 2016 to 2020. Antimicrobial susceptibility testing was carried out using the Kirby-Bauer method or automated systems, with interpretation according to the Clinical and Laboratory Standards Institute 2019 breakpoints. A total of 288,377 isolates were collected, and the top 10 predominant bacteria were Escherichia coli, Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Klebsiella pneumoniae, Moraxella catarrhalis, Streptococcus pyogenes, Staphylococcus epidermidis, Pseudomonas aeruginosa, and Acinetobacter baumannii. In 2020, the coronavirus disease 2019 (COVID-19) pandemic year, we observed a significant reduction in the proportion of respiratory tract samples (from 56.9% to 44.0%). A comparable reduction was also seen in the primary bacteria mainly isolated from respiratory tract samples, including S. pneumoniae, H. influenzae, and S. pyogenes. Multidrug-resistant organisms (MDROs) in children were commonly observed and presented higher rates of drug resistance than sensitive strains. The proportions of carbapenem-resistant K. pneumoniae (CRKP), carbapenem-resistant A. baumannii (CRAB), carbapenem-resistant P. aeruginosa (CRPA), and methicillin-resistant S. aureus (MRSA) strains were 19.7%, 46.4%%, 12.8%, and 35.0%, respectively. The proportions of CRKP, CRAB, and CRPA strains all showed decreasing trends between 2015 and 2020. Carbapenem-resistant Enterobacteriaceae (CRE) and CRPA gradually decreased with age, while CRAB showed the opposite trend with age. Both CRE and CRPA pose potential threats to neonates. MDROs show very high levels of AMR and have become an urgent threat to children, suggesting that effective monitoring of AMR and antimicrobial stewardship among children in China are required. IMPORTANCE AMR, especially that involving multidrug-resistant organisms (MDROs), is recognized as a global threat to human health; AMR renders infections increasingly difficult to treat, constituting an enormous economic burden and producing tremendous negative impacts on patient morbidity and mortality rates. There are many surveillance programs in the world to address AMR profiles and MDRO prevalence in humans. However, published studies evaluating the overall AMR rates or MDRO distributions in children are very limited or are of mixed quality. In this study, we showed the bacterial epidemiology and resistance profiles of primary pathogens in Chinese children from 2016 to 2020 for the first time, analyzed MDRO distributions with time and with age, and described MDROs' potential threats to children, especially low-immunity neonates. Our study will be very useful to guide antiinfection therapy in Chinese children, as well as worldwide pediatric patients.

The one health landscape in Sub-Saharan African countries.

OBJECTIVES: One Health is transiting from multidisciplinary to transdisciplinary concepts and its viewpoints should move from 'proxy for zoonoses', to include other topics (climate change, nutrition and food safety, policy and planning, welfare and well-being, antimicrobial resistance (AMR), vector-borne diseases, toxicosis and pesticides issues) and thematic fields (social sciences, geography and economics). This work was conducted to map the One Health landscape in Africa. METHODS: An assessment of existing One Health initiatives in Sub-Saharan African (SSA) countries was conducted among selected stakeholders using a multi-method approach. Strengths, weaknesses, opportunities and threats to One Health initiatives were identified, and their influence, interest and impacts were semi-quantitatively evaluated using literature reviews, questionnaire survey and statistical analysis. RESULTS: One Health Networks and identified initiatives were spatiotemporally spread across SSA and identified stakeholders were classified into four quadrants. It was observed that imbalance in stakeholders' representations led to hesitation in buying-in into One Health approach by stakeholders who are outside the main networks like stakeholders from the policy, budgeting, geography and sometimes, the environment sectors. CONCLUSION: Inclusion of theory of change, monitoring and evaluation frameworks, and tools for standardized evaluation of One Health policies are needed for a sustained future of One Health and future engagements should be outputs- and outcomes-driven and not activity-driven. National roadmaps for One Health implementation and institutionalization are necessary, and proofs of concepts in One Health should be validated and scaled-up. Dependence on external funding is unsustainable and must be addressed in the medium to long-term. Necessary policy and legal instruments to support One Health nationally and sub-nationally should be implemented taking cognizance of contemporary issues like urbanization, endemic poverty and other emerging issues. The utilization of current technologies and One Health approach in addressing the ongoing pandemic of COVID-19 and other emerging diseases are desirable. Finally, One Health implementation should be anticipatory and preemptive, and not reactive in containing disease outbreaks, especially those from the animal sources or the environment before the risk of spillover to human.

Operationalizing Cooperative Research for Infectious Disease Surveillance: Lessons Learned and Ways Forward.

The current COVID-19 pandemic demonstrates the need for urgent and on-demand solutions to provide diagnostics, treatment and preventative measures for infectious disease outbreaks. Once solutions are developed, meeting capacities depends on the ability to mitigate technical, logistical and production issues. While it is difficult to predict the next outbreak, augmenting investments in preparedness, such as infectious disease surveillance, is far more effective than mustering last-minute response funds. Bringing research outputs into practice sooner rather than later is part of an agile approach to pivot and deliver solutions. Cooperative multi- country research programs, especially those funded by global biosecurity programs, develop capacity that can be applied to infectious disease surveillance and research that enhances detection, identification, and response to emerging and re-emerging pathogens with epidemic or pandemic potential. Moreover, these programs enhance trust building among partners, which is essential because setting expectation and commitment are required for successful research and training. Measuring research outputs, evaluating outcomes and justifying continual investments are essential but not straightforward. Lessons learned include those related to reducing biological threats and maturing capabilities for national laboratory diagnostics strategy and related health systems. Challenges, such as growing networks, promoting scientific transparency, data and material sharing, sustaining funds and developing research strategies remain to be fully resolved. Here, experiences from several programs highlight successful partnerships that provide ways forward to address the next outbreak.