Detection of Mpox Virus Using Microbial Cell-Free DNA: The Potential of Pathogen-Agnostic Sequencing for Rapid Identification of Emerging Pathogens.

BACKGROUND: The 2022 global outbreak of Monkeypox virus (MPXV) highlighted challenges with polymerase chain reaction detection as divergent strains emerged and atypical presentations limited the applicability of swab sampling. Recommended testing in the United States requires a swab of lesions, which arise late in infection and may be unrecognized. We present MPXV detections using plasma microbial cell-free DNA (mcfDNA) sequencing. METHODS: Fifteen plasma samples from 12 case-patients were characterized through mcfDNA sequencing. Assay performance was confirmed through in silico inclusivity and exclusivity assessments. MPXV isolates were genotyped using mcfDNA, and phylodynamic information was imputed using publicly available sequences. RESULTS: MPXV mcfDNA was detected in 12 case-patients. Mpox was not suspected in 5, with 1 having documented resolution of mpox >6 months previously. Six had moderate to severe mpox, supported by high MPXV mcfDNA concentrations; 4 died. In 7 case-patients, mcfDNA sequencing detected coinfections. Genotyping by mcfDNA sequencing identified 22 MPXV mutations at 10 genomic loci in 9 case-patients. Consistent with variation observed in the 2022 outbreak, 21 of 22 variants were G > A/C > T. Phylogenetic analyses imputed isolates to sublineages arising at different time points and from different geographic locations. CONCLUSIONS: We demonstrate the potential of plasma mcfDNA sequencing to detect, quantify, and, for acute infections with high sequencing coverage, subtype MPXV using a single noninvasive test. Sequencing plasma mcfDNA may augment existing mpox testing in vulnerable patient populations or in patients with atypical symptoms or unrecognized mpox. Strain type information may supplement disease surveillance and facilitate tracking emerging pathogens.

Using molecular methods to delineate norovirus outbreaks: a systematic review.

Noroviruses are among the major causative agents of human acute gastroenteritis, and the nature of norovirus outbreaks can differ considerably. The number of single-nucleotide polymorphisms (SNPs) between strains is used to assess their relationships. There is currently no universally accepted cutoff value for clustering strains that define an outbreak or linking the individuals involved. This study was conducted to estimate the threshold value of genomic variations among related strains within norovirus outbreaks. We carried out a literature search in the PubMed and Web of Science databases. SNP rates were defined as the number of SNPs/sequence length (bp) × 100%. The Mann-Whitney U-test was used in comparisons of the distribution of SNP rates for different sequence regions, genogroups (GI and GII), transmission routes, and sequencing methods. A total of 25 articles reporting on 108 norovirus outbreaks were included. In 99.1% of the outbreaks, the SNP rates were below 0.50%, and in 89.8%, the SNP rates were under 0.20%. Outbreak strains showed higher SNP rates when the P2 domain was used for sequence analysis (Z = -2.652, p = 0.008) and when an NGS method was used (Z = -3.686, p < 0.001). Outbreaks caused by different norovirus genotypes showed no significant difference in SNP rates. Compared with person-to-person outbreaks, SNP rates were lower in common-source outbreaks, but no significant difference was found when differences in sequencing methods were taken into consideraton. SNP rates under 0.20% and 0.50% could be considered as the rigorous and relaxed threshold, respectively, of strain similarity within a norovirus outbreak. More data are needed to evaluate differences within and between various norovirus outbreaks.

From SARS-CoV-2 to Global Preparedness: A Graphical Interface for Standardised High-Throughput Bioinformatics Analysis in Pandemic Scenarios and Surveillance of Drug Resistance.

The COVID-19 pandemic highlighted the need for a rapid, convenient, and scalable diagnostic method for detecting a novel pathogen amidst a global pandemic. While command-line interface tools offer automation for SARS-CoV-2 Oxford Nanopore Technology sequencing data analysis, they are inapplicable to users with limited programming skills. A solution is to establish such automated workflows within a graphical user interface software. We developed two workflows in the software Geneious Prime 2022.1.1, adapted for data obtained from the Midnight and Artic's nCoV-2019 sequencing protocols. Both workflows perform trimming, read mapping, consensus generation, and annotation on SARS-CoV-2 Nanopore sequencing data. Additionally, one workflow includes phylogenetic assignment using the bioinformatic tools pangolin and Nextclade as plugins. The basic workflow was validated in 2020, adhering to the requirements of the European Centre for Disease Prevention and Control for SARS-CoV-2 sequencing and analysis. The enhanced workflow, providing phylogenetic assignment, underwent validation at Uppsala University Hospital by analysing 96 clinical samples. It provided accurate diagnoses matching the original results of the basic workflow while also reducing manual clicks and analysis time. These bioinformatic workflows streamline SARS-CoV-2 Nanopore data analysis in Geneious Prime, saving time and manual work for operators lacking programming knowledge.

Temporal and Gene Reassortment Analysis of Influenza C Virus Outbreaks in Hong Kong, SAR, China.

From 2014 to week 07/2020 the Centre for Health Protection in Hong Kong conducted screening for influenza C virus (ICV). A retrospective analysis of ICV detections to week 26/2019 revealed persistent low-level circulation with outbreaks occurring biennially in the winters of 2015 to 2016 and 2017 to 2018 (R. S. Daniels et al., J Virol 94:e01051-20, 2020, https://doi.org/10.1128/JVI.01051-20). Here, we report on an outbreak occurring in 2019 to 2020, reinforcing the observation of biennial seasonality in Hong Kong. All three outbreaks occurred in similar time frames, were subsequently dwarfed by seasonal epidemics of influenza types A and B, and were caused by similar proportions of C/Kanagawa/1/76 (K)-lineage and C/São Paulo/378/82 S1- and S2-sublineage viruses. Ongoing genetic drift was observed in all genes, with some evidence of amino acid substitution in the hemagglutinin-esterase-fusion (HEF) glycoprotein possibly associated with antigenic drift. A total of 61 ICV genomes covering the three outbreaks were analyzed for reassortment, and 9 different reassortant constellations were identified, 1 K-lineage, 4 S1-sublineage, and 4 S2-sublineage, with 6 of these being identified first in the 2019-1920 outbreak (2 S2-lineage and 4 S1-lineage). The roles that virus interference/enhancement, ICV persistent infection, genome evolution, and reassortment might play in the observed seasonality of ICV in Hong Kong are discussed. IMPORTANCE Influenza C virus (ICV) infection of humans is common, with the great majority of people being infected during childhood, though reinfection can occur throughout life. While infection normally results in "cold-like" symptoms, severe disease cases have been reported in recent years. However, knowledge of ICV is limited due to poor systematic surveillance and an inability to propagate the virus in large amounts in the laboratory. Following recent systematic surveillance in Hong Kong SAR, China, and direct ICV gene sequencing from clinical specimens, a 2-year cycle of disease outbreaks (epidemics) has been identified, with gene mixing playing a significant role in ICV evolution. Studies like those reported here are key to developing an understanding of the impact of influenza C virus infection in humans, notably where comorbidities exist and severe respiratory disease can develop.

Introduction and acceptability of the Surveillance Outbreak Response Management and Analysis System (SORMAS) during the COVID-19 pandemic in Côte d'Ivoire.

BACKGROUND: The Surveillance Outbreak Response Management and Analysis System (SORMAS) has been implemented for various infectious diseases since 2015. 2020, at the beginning of the COVID-19 pandemic, SORMAS was adapted to SARS-CoV2. METHODS: We assessed the acceptability and usability of SORMAS and accompanied its implementation in two pilot regions of Côte d'Ivoire (Abidjan 2 and Gbêkê) from July/August 2021 to March 2022. We conducted 136 semi-structured interviews to cover knowledge on COVID-19, information on conventional surveillance systems for disease monitoring including COVID-19, acceptability of SORMAS, and impact of SORMAS on epidemic preparedness and surveillance. Scores before and 6-8 months after implementation were compared. RESULTS: SORMAS was implemented in two pilot regions in Côte d'Ivoire. The conventional software for the surveillance of the COVID-19 pandemic by the company MAGPI was maintained in parallel; the additional time needs to enter and manage the data in SORMAS were the main concern. SORMAS acceptance and satisfaction scores were high after the user training, which was prior to implementation, and after 6-8 months of use. The ability of SORMAS to improve COVID-19 preparedness and early detection of cases and contacts was widely acknowledged. To keep the understanding and skills of users up-to-date, regular refresher trainings were requested. The expectation to be able to make decisions based on data produced by SORMAS was high at baseline and the perceived experience after several months of use of the software was very positive. Unfortunately, the link with the laboratories could not be established in the pilot regions, but it is an existing feature of SORMAS that many users were asking for. Following the positive experience using SORMAS for COVID-19, the pilot regions expanded its use for monitoring and management of measles, yellow fever, meningitis, and cholera. CONCLUSION: SORMAS was very well accepted by users and decision makers in the two pilot regions of Côte d'Ivoire and its ability to improve epidemic preparedness and surveillance was acknowledged. If the hurdles of maintenance (tablets, server, and maintaining user skills) are handled sustainably, it can serve as a valid tool to identify, surveil and manage future outbreaks of various infectious diseases in Côte d'Ivoire.

Hepatitis C Virus Transmission Clusters in Public Health and Correctional Settings, Wisconsin, USA, 2016-20171.

Ending the hepatitis C virus (HCV) epidemic requires stopping transmission among networks of persons who inject drugs. Identifying transmission networks by using genomic epidemiology may inform community responses that can quickly interrupt transmission. We retrospectively identified HCV RNA-positive specimens corresponding to 459 persons in settings that use the state laboratory, including correctional facilities and syringe services programs, in Wisconsin, USA, during 2016-2017. We conducted next-generation sequencing of HCV and analyzed it for phylogenetic linkage by using the Centers for Disease Control and Prevention Global Hepatitis Outbreak Surveillance Technology platform. Analysis showed that 126 persons were linked across 42 clusters. Phylogenetic clustering was higher in rural communities and associated with female sex and younger age among rural residents. These data highlight that HCV transmission could be reduced by expanding molecular-based surveillance strategies to rural communities affected by the opioid crisis.

Molecular Characterization of Influenza C Viruses from Outbreaks in Hong Kong SAR, China.

In 2014, the Centre for Health Protection in Hong Kong introduced screening for influenza C virus (ICV) as part of its routine surveillance for infectious agents in specimens collected from patients presenting with symptoms of respiratory viral infection, including influenza-like illness (ILI). A retrospective analysis of ICV detections up to week 26 of 2019 revealed persistent low-level circulation, with two outbreaks having occurred in the winters of 2015 to 2016 and 2017 to 2018. These outbreaks occurred at the same time as, and were dwarfed by, seasonal epidemics of influenza types A and B. Gene sequencing studies on stored ICV-positive clinical specimens from the two outbreaks have shown that the hemagglutinin-esterase (HE) genes of the viruses fall into two of the six recognized genetic lineages (represented by C/Kanagawa/1/76 and C/São Paulo/378/82), with there being significant genetic drift compared to earlier circulating viruses within both lineages. The location of a number of encoded amino acid substitutions in hemagglutinin-esterase fusion (HEF) glycoproteins suggests that antigenic drift may also have occurred. Observations of ICV outbreaks in other countries, with some of the infections being associated with severe disease, indicates that ICV infection has the potential to have significant clinical and health care impacts in humans.IMPORTANCE Influenza C virus infection of humans is common, and reinfection can occur throughout life. While symptoms are generally mild, severe disease cases have been reported, but knowledge of the virus is limited, as little systematic surveillance for influenza C virus is conducted and the virus cannot be studied by classical virologic methods because it cannot be readily isolated in laboratories. A combination of systematic surveillance in Hong Kong SAR, China, and new gene sequencing methods has been used in this study to assess influenza C virus evolution and provides evidence for a 2-year cycle of disease outbreaks. The results of studies like that reported here are key to developing an understanding of the impact of influenza C virus infection in humans and how virus evolution might be associated with epidemics.

Introductions and early spread of SARS-CoV-2 in France, 24 January to 23 March 2020.

Following SARS-CoV-2 emergence in China, a specific surveillance was implemented in France. Phylogenetic analysis of sequences retrieved through this surveillance suggests that detected initial introductions, involving non-clade G viruses, did not seed local transmission. Nevertheless, identification of clade G variants subsequently circulating in the country, with the earliest from a patient who neither travelled to risk areas nor had contact with travellers, suggests that SARS-CoV-2 might have been present before the first recorded local cases.

An epidemiological and molecular study regarding the spread of vancomycin-resistant Enterococcus faecium in a teaching hospital in Bogotá, Colombia 2016.

BACKGROUND: Enterococcus faecium is ranked worldwide as one of the top ten pathogens identified in healthcare-associated infections (HAI) and is classified as one of the high priority pathogens for research and development of new antibiotics worldwide. Due to molecular biology techniques' higher costs, the approach for identifying and controlling infectious diseases in developing countries has been based on clinical and epidemiological perspectives. Nevertheless, after an abrupt vancomycin-resistant Enterococcus faecium dissemination in the Méderi teaching hospital, ending up in an outbreak, further measures needed to be taken into consideration. The present study describes the vancomycin-resistant Enterococcus faecium pattern within Colombian's largest installed-bed capacity hospital in 2016. METHODS: Thirty-three vancomycin-resistant Enterococcus faecium isolates were recovered during a 5-month period in 2016. Multilocus variable-number tandem-repeat analysis was used for molecular typing to determine clonality amongst strains. A modified time-place-sequence algorithm was used to trace VREfm spread patterns during the outbreak period and estimate transmission routes. RESULTS: Four clonal profiles were identified. Chronological clonal profile follow-up suggested a transitional spread from profile "A" to profile "B", returning to a higher prevalence of "A" by the end of the study. Antibiotic susceptibility indicated high-level vancomycin-resistance in most isolates frequently matching vanA gene identification. DISCUSSION: Transmission analysis suggested cross-contamination via healthcare workers. Despite epidemiological control of the outbreak, post-outbreak isolates were still being identified as having outbreak-related clonal profile (A), indicating reduction but not eradication of this clonality. This study supports the use of combined molecular and epidemiological strategies in an approach to controlling infectious diseases. It contributes towards a more accurate evaluation of the effectiveness of the epidemiological measures taken regarding outbreak control and estimates the main cause related to the spread of this microorganism.

Genetic relatedness of Vibrio cholerae isolates within and between households during outbreaks in Dhaka, Bangladesh.

BACKGROUND: Household contacts of cholera patients have a 100 times higher risk of developing a cholera infection than the general population. To compare the genetic relatedness of clinical and water source Vibrio cholerae isolates from cholera patients' households across three outbreaks, we analyzed these isolates using whole-genome-sequencing (WGS) and multilocus variable-number tandem-repeat analysis (MLVA). RESULTS: The WGS analyses revealed that 80% of households had source water isolates that were more closely related to clinical isolates from the same household than to any other isolates. While in another 20% of households an isolate from a person was more closely related to clinical isolates from another household than to source water isolates from their own household. The mean pairwise differences in single nucleotide-variant (SNV) counts for isolates from the same household were significantly lower than those for different households (2.4 vs. 7.7 p < 0.0001), and isolates from the same outbreak had significantly fewer mean pairwise differences compared to isolates from different outbreaks (mean: 6.2 vs. 8.0, p < 0.0001). Based on MLVA in outbreak 1, we observed that the majority of households had clinical isolates with MLVA genotypes related to other clinical isolates and unrelated to water source isolates from the same household. While in outbreak 3, there were different MLVA genotypes between households, however within the majority of households, the clinical and water source isolates had the same MLVA genotypes. The beginning of outbreak 2 resembled outbreak 1 and the latter part resembled outbreak 3. We validated our use of MLVA by comparing it to WGS. Isolates with the identical MLVA genotype had significantly fewer mean pairwise SNV differences than those isolates with different MLVA genotypes (mean: 4.8 vs. 7.7, p < 0.0001). Furthermore, consistent with WGS results, the number of pairwise differences in the five MLVA loci for isolates within the same household was significantly lower than isolates from different households (mean: 1.6 vs. 3.0, p < 0.0001). CONCLUSION: These results suggest that transmission patterns for cholera are a combination of person-to-person and water-to-person cholera transmission with the proportions of the two modes varying within and between outbreaks.

Diagnosis of Fatal Human Case of St. Louis Encephalitis Virus Infection by Metagenomic Sequencing, California, 2016.

We used unbiased metagenomic next-generation sequencing to diagnose a fatal case of meningoencephalitis caused by St. Louis encephalitis virus in a patient from California in September 2016. This case is associated with the recent 2015-2016 reemergence of this virus in the southwestern United States.

Infectious Disease Outbreak Response: Mind the Rights Gap.

The international organization responsible for international coordinated response to disease outbreaks-the World Health Organization (WHO)-was given permission to receive reports from sources other than the state in revisions to the International Health Regulations (IHR) in 2005. However, the organization struggles to protect its corresponding right to receive reports from non-state actors on outbreak events. This article examines the consequences of this implementation gap between what is stated in the IHR-the right of WHO to receive reports from non-state actors on outbreak events-and the reality that states remain able and willing to act to ensure that this right is not exercised. The article examines two recent cases: the first detection of Middle East Respiratory Syndrome (MERS) outbreak in Saudi Arabia, and the first months of the Ebola outbreak in Guinea. Both cases demonstrate how the WHO has struggled to balance states' concern with managing risk communication against WHO's right to receive reports from non-state actors. The article argues that to realize the full potential of a transparent disease outbreak reporting process, there is a need for a human rights framework that expressly articulates its right to receive reports and outlines appropriate behaviour for the WHO, states, and non-state actors.

Distinct Zika Virus Lineage in Salvador, Bahia, Brazil.

Sequencing of isolates from patients in Bahia, Brazil, where most Zika virus cases in Brazil have been reported, resulted in 11 whole and partial Zika virus genomes. Phylogenetic analyses revealed a well-supported Bahia-specific Zika virus lineage, which indicates sustained Zika virus circulation in Salvador, Bahia's capital city, since mid-2014.

Methicillin-resistant Staphylococcus aureus (MRSA) clusters in neonatal intensive care units (NICUs) and other neonatal units in New York State (NYS), 2001 to 2017.

BACKGROUND: New York State (NYS) mandates reporting of all hospital-associated communicable disease outbreaks. We describe trends in NYS surveillance for neonatal unit methicillin-resistant Staphylococcus aureus (MRSA) outbreaks, the evolution of national MRSA infection prevention and control (IPC) recommendations, and IPC measures taken by NYS neonatal units. METHODS: We evaluated trends of reported neonatal unit MRSA outbreaks by etiology from 2001 to 2017. We reviewed all reports and the use of IPC recommendations over time. RESULTS: From 2001 to 2017, 124 MRSA outbreaks were reported in 47 hospital neonatal units, with a total of 1,055 laboratory-confirmed infant cases, 18 infant deaths, and 52 laboratory-confirmed staff cases. The number of outbreaks increased with the level of care. During the study period, a higher proportion of hospitals reported implementing IPC measures, including reinforcing hand hygiene compliance (increased from 79.2% to 95.1%) and enhancing environmental cleaning and disinfection (increased from 4.2% to 78.0%) as well as performing active surveillance testing (AST) on exposed neonates (increased from 4.2% to 51.2%) and molecular testing on MRSA-positive isolates (increased from 5.3% to 18.9%). CONCLUSIONS: From 2001 to 2017, IPC measures in neonatal units increased in parallel with expanded national IPC recommendations. However, MRSA outbreaks in neonatal units continued to be frequent occurrences in NYS.

Key Characteristics and Perception of Different Outbreak Surveillance Systems in Côte d'Ivoire: Cross-Sectional Survey Among Users.

Background: Accurate and timely infectious disease surveillance is pivotal for effective public health responses. An important component of this is the disease surveillance tools used. Understanding views and experiences of users is crucial for informing policy decisions and ensuring the seamless functioning of surveillance systems. Objective: In this study, we aimed to assess the user perceptions of 3 disease surveillance tools used in Côte d'Ivoire, namely, MAGPI, District Health Information Software 2 (DHIS2), and Surveillance Outbreak Response Management and Analysis System (SORMAS), the latter was implemented in 2021 within a pilot scheme. Methods: We conducted interviews and a web-based survey distributed to users of the 3 surveillance tools. The survey assessed users' views of the surveillance tools' usefulness, ease of use, feelings toward the tool, conditions that may influence the use, and other characteristics. The descriptive analysis compared responses from SORMAS, MAGPI, and DHIS2 users, providing a comprehensive evaluation of their experiences. Results: Among the 159 respondents who actively use one of the systems, MAGPI was the most widely used surveillance tool among respondents (n=127, 79.9%), followed by DHIS2 (n=108, 67.9%), and SORMAS (n=25, 15.7%). In terms of users' perceptions, SORMAS, despite its limited implementation, emerged as a tool that allows for data analysis and had the most comprehensive set of functionalities. DHIS2 was appreciated for its frequency of report provision, although users reported occasional IT system failures. MAGPI was recognized for its ease of use but was reported to lack certain functionalities offered by the other surveillance systems. Conclusions: This study offers valuable insights into the perceptions of disease surveillance tools users in Côte d'Ivoire. While all systems were positively regarded, each exhibited strengths and weaknesses addressing different needs and functionalities. Policy makers and health officials can use these findings to enhance existing tools or consider a unified approach for infectious disease surveillance systems. Understanding users' perspectives allows them to optimize the choice of surveillance tools, ultimately strengthening public health responses in Côte d'Ivoire and potentially serving as a model for other countries facing similar decisions in their health care systems.

Can Citizen Science Contribute to Avian Influenza Surveillance?

Global change is an important driver of the increase in emerging infectious diseases in recent decades. In parallel, interest in nature has increased, and different citizen science platforms have been developed to record wildlife observations from the general public. Some of these platforms also allow registering the observations of dead or sick birds. Here, we test the utility of live, sick and dead observations of birds recorded on the platform Observation.org for the early detection of highly pathogenic avian influenza virus (HPAIV) outbreaks in the wild in Belgium and The Netherlands. There were no significant differences in the morbidity/mortality rate through Observation.org one to four weeks in advance. However, the results show that the HPAIV outbreaks officially reported by the World Organisation for Animal Health (WOAH) overlapped in time with sudden increases in the records of sick and dead birds in the wild. In addition, in two of the five main HPAIV outbreaks recorded between 2016 and 2021, wild Anseriformes mortality increased one to two months before outbreak declaration. Although we cannot exclude that this increase was related to other causes such as other infectious diseases, we propose that Observation.org is a useful nature platform to complement animal health surveillance in wild birds. We propose possible approaches to improve the utility of the platform for pathogen surveillance in wildlife and discuss the potential for HPAIV outbreak detection systems based on citizen science to complement current surveillance programs of health authorities.

Utility of prehospital call center ambulance dispatch data for COVID-19 cluster surveillance: A retrospective analysis.

INTRODUCTION: Cluster surveillance, identification, and containment are primary outbreak management techniques; however, adapting these for low- and middle-income countries is an ongoing challenge. We aimed to evaluate the utility of prehospital call center ambulance dispatch (CCAD) data for surveillance by examining the correlation between influenza-like illness (ILI)-related dispatch calls and COVID-19 cases. METHODS: We performed a retrospective analysis of state-level CCAD and COVID-19 data recorded between January 1 and April 30, 2020, in Telangana, India. The primary outcome was a time series correlation between ILI calls in CCAD and COVID-19 case counts. Secondarily, we looked for a year-to-year correlation of ILI calls in the same period over 2018, 2019, and 2020. RESULTS: On average, ILI calls comprised 12.9% (95% CI 11.7%-14.1%) of total daily calls in 2020, compared to 7.8% (95% CI 7.6%-8.0%) in 2018, and 7.7% (95% CI 7.5%-7.7%) in 2019. ILI call counts from 2018, 2019, and 2020 aligned closely until March 19, when 2020 ILI calls increased, representing 16% of all calls by March 23 and 27.5% by April 7. In contrast to the significant correlation observed between 2020 and previous years' January-February calls (2020 and 2019-Durbin-Watson test statistic [DW] = 0.749, p < 0.001; 2020 and 2018-DW = 1.232, p < 0.001), no correlation was observed for March-April calls (2020 and 2019-DW = 2.012, p = 0.476; 2020 and 2018-DW = 1.820, p = 0.208). In March-April 2020, the daily reported COVID-19 cases by time series significantly correlated with the ILI calls (DW = 0.977, p < 0.001). The ILI calls on a specific day significantly correlated with the COVID-19 cases reported 6 days prior and up to 14 days after (cross-correlation > 0.251, the 95% upper confidence limit). CONCLUSIONS: The statistically significant time series correlation between ILI calls and COVID-19 cases suggests prehospital CCAD can be part of early warning systems aiding outbreak cluster surveillance, identification, and containment.

Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates.

SARS-CoV-2 case data are primary sources for estimating epidemiological parameters and for modelling the dynamics of outbreaks. Understanding biases within case-based data sources used in epidemiological analyses is important as they can detract from the value of these rich datasets. This raises questions of how variations in surveillance can affect the estimation of epidemiological parameters such as the case growth rates. We use standardised line list data of COVID-19 from Argentina, Brazil, Mexico and Colombia to estimate delay distributions of symptom-onset-to-confirmation, -hospitalisation and -death as well as hospitalisation-to-death at high spatial resolutions and throughout time. Using these estimates, we model the biases introduced by the delay from symptom-onset-to-confirmation on national and state level case growth rates (rt) using an adaptation of the Richardson-Lucy deconvolution algorithm. We find significant heterogeneities in the estimation of delay distributions through time and space with delay difference of up to 19 days between epochs at the state level. Further, we find that by changing the spatial scale, estimates of case growth rate can vary by up to 0.13 d-1. Lastly, we find that states with a high variance and/or mean delay in symptom-onset-to-diagnosis also have the largest difference between the rt estimated from raw and deconvolved case counts at the state level. We highlight the importance of high-resolution case-based data in understanding biases in disease reporting and how these biases can be avoided by adjusting case numbers based on empirical delay distributions. Code and openly accessible data to reproduce analyses presented here are available.

Comparing surveillance approaches to support regaining free status after a foot-and-mouth disease outbreak.

Following an FMD eradication program, surveillance will be required to demonstrate that the program has been successful. The World Organization for Animal Health (OIE) provides guidelines including waiting periods and appropriate surveillance to support regaining FMD-free status. Serological surveillance is the recommended method for demonstrating freedom but is time consuming and expensive. New technologies such as real-time reverse transcription polymerase chain reaction (RT-qPCR) tests and sampling techniques such as bulk milk testing (BMT) of dairy cattle, oral swabs, and saliva collection with rope tethers in piggeries could enable surveillance to be done more efficiently. Epidemiological modelling was used to simulate FMD outbreaks, with and without emergency vaccination as part of the response, in Australia. Baseline post-outbreak surveillance approaches for unvaccinated and vaccinated animals based on the European FMD directive were compared with alternative approaches in which the sampling regime, sampling approaches and/or the diagnostic tests used were varied. The approaches were compared in terms of the resources required, time taken, cost, and effectiveness i.e., ability of the surveillance regime to correctly identify the infection status of herds. In the non-vaccination scenarios, the alternative approach took less time to complete and cost less, with the greatest benefits seen with larger outbreaks. In vaccinated populations, the alternative surveillance approaches significantly reduced the number of herds sampled, the total number of tests done and costs of the post-outbreak surveillance. There was no reduction in effectiveness using the alternative approaches, with one of the benefits being a reduction in the number of false positive herds. Alternative approaches to FMD surveillance based on non-invasive sampling methods and RT-qPCR tests have the potential to enable post outbreak surveillance substantiating FMD freedom to be done more quickly and less expensively than traditional approaches based on serological surveys.

Development and Validation of a Mucosal Antibody (IgA) Test to Identify Persistent Infection with Foot-and-Mouth Disease Virus.

It is well known that approximately 50% of cattle infected with foot-and-mouth disease (FMD) virus (FMDV) may become asymptomatic carrier (persistently infected) animals. Although transmission of FMDV from carrier cattle to naïve cattle has not been demonstrated experimentally, circumstantial evidence from field studies has linked FMDV-carrier cattle to cause subsequent outbreaks. Therefore, the asymptomatic carrier state complicates the control and eradication of FMD. Current serological diagnosis using tests for antibodies to the viral non-structural proteins (NSP-ELISA) are not sensitive enough to detect all carrier animals, if persistently infected after vaccination and do not distinguish between carriers and non-carriers. The specificity of the NSP ELISA may also be reduced after vaccination, in particular after multiple vaccination. FMDV-specific mucosal antibodies (IgA) are not produced in vaccinated cattle but are elevated transiently during the acute phase of infection and can be detected at a high level in cattle persistently infected with FMDV, irrespective of their vaccination status. Therefore, detection of IgA by ELISA may be considered a diagnostic alternative to RT-PCR for assessing FMDV persistent infection in ruminants in both vaccinated and unvaccinated infected populations. This study reports on the development and validation of a new mucosal IgA ELISA for the detection of carrier animals using nasal, saliva, and oro-pharyngeal fluid (OPF) samples. The diagnostic performance of the IgA ELISA using nasal samples from experimentally vaccinated and infected cattle demonstrated a high level of specificity (99%) and an improved level of sensitivity (76.5%). Furthermore, the detection of carrier animals reached 96.9% when parallel testing of samples was carried out using both the IgA-ELISA and NSP-ELISA.