"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets.

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

Genomic and Epidemiologic Surveillance of SARS-CoV-2 in the Pandemic Period: Sequencing Network of the Lazio Region, Italy.

Since the beginning of the COVID-19 pandemic, large-scale genomic sequencing has immediately pointed out that SARS-CoV-2 has rapidly mutated during the course of the pandemic, resulting in the emergence of variants with a public health impact. In this context, strictly monitoring the circulating strains via NGS has proven to be crucial for the early identification of new emerging variants and the study of the genomic evolution and transmission of SARS-CoV-2. Following national and international guidelines, the Lazio region has created a sequencing laboratory network (WGSnet-Lazio) that works in synergy with the reference center for epidemiological surveillance (SERESMI) to monitor the circulation of SARS-CoV-2. Sequencing was carried out with the aims of characterizing outbreak transmission dynamics, performing the genomic analysis of viruses infecting specific categories of patients (i.e., immune-depressed, travelers, and people with severe symptoms) and randomly monitoring variant circulation. Here we report data emerging from sequencing activities carried out by WGSnet-Lazio (from February 2020 to October 2022) linked with epidemiological data to correlate the circulation of variants with the clinical and demographic characteristics of patients. The model of the sequencing network developed in the Lazio region proved to be a useful tool for SARS-CoV-2 surveillance and to support public health measures for epidemic containment.

Population immunity predicts evolutionary trajectories of SARS-CoV-2.

The large-scale evolution of the SARS-CoV-2 virus has been marked by rapid turnover of genetic clades. New variants show intrinsic changes, notably increased transmissibility, and antigenic changes that reduce cross-immunity induced by previous infections or vaccinations. How this functional variation shapes global evolution has remained unclear. Here, we establish a predictive fitness model for SARS-CoV-2 that integrates antigenic and intrinsic selection. The model is informed by tracking of time-resolved sequence data, epidemiological records, and cross-neutralization data of viral variants. Our inference shows that immune pressure, including contributions of vaccinations and previous infections, has become the dominant force driving the recent evolution of SARS-CoV-2. The fitness model can serve continued surveillance in two ways. First, it successfully predicts the short-term evolution of circulating strains and flags emerging variants likely to displace the previously predominant variant. Second, it predicts likely antigenic profiles of successful escape variants prior to their emergence.

Impact of family networks on uptake of health interventions: evidence from a community-randomized control trial aimed at increasing HIV testing in South Africa.

INTRODUCTION: While it is widely acknowledged that family relationships can influence health outcomes, their impact on the uptake of individual health interventions is unclear. In this study, we quantified how the efficacy of a randomized health intervention is shaped by its pattern of distribution in the family network. METHODS: The "Home-Based Intervention to Test and Start" (HITS) was a 2×2 factorial community-randomized controlled trial in Umkhanyakude, KwaZulu-Natal, South Africa, embedded in the Africa Health Research Institute's population-based demographic and HIV surveillance platform (ClinicalTrials.gov # NCT03757104). The study investigated the impact of two interventions: a financial micro-incentive and a male-targeted HIV-specific decision support programme. The surveillance area was divided into 45 community clusters. Individuals aged ≥15 years in 16 randomly selected communities were offered a micro-incentive (R50 [$3] food voucher) for rapid HIV testing (intervention arm). Those living in the remaining 29 communities were offered testing only (control arm). Study data were collected between February and November 2018. Using routinely collected data on parents, conjugal partners, and co-residents, a socio-centric family network was constructed among HITS-eligible individuals. Nodes in this network represent individuals and ties represent family relationships. We estimated the effect of offering the incentive to people with and without family members who also received the offer on the uptake of HIV testing. We fitted a linear probability model with robust standard errors, accounting for clustering at the community level. RESULTS: Overall, 15,675 people participated in the HITS trial. Among those with no family members who received the offer, the incentive's efficacy was a 6.5 percentage point increase (95% CI: 5.3-7.7). The efficacy was higher among those with at least one family member who received the offer (21.1 percentage point increase (95% CI: 19.9-22.3). The difference in efficacy was statistically significant (21.1-6.5 = 14.6%; 95% CI: 9.3-19.9). CONCLUSIONS: Micro-incentives appear to have synergistic effects when distributed within family networks. These effects support family network-based approaches for the design of health interventions.

Molecular epidemiology of rotavirus among children in Western Canada: Dynamic changes in genotype prevalence in four consecutive seasons.

Rotavirus molecular surveillance remains important in the postvaccine era to monitor the changes in transmission patterns, identify vaccine-induced antigenic changes and discover potentially pathogenic vaccine-related strains. The Canadian province of Alberta introduced rotavirus vaccination into its provincial vaccination schedule in June 2015. To evaluate the impact of this program on stool rotavirus positivity rate, strain diversity, and seasonal trends, we analyzed a prospective cohort of children with acute gastroenteritis recruited between December 2014 and August 2018. We identified dynamic changes in rotavirus positivity and genotype trends during pre- and post-rotavirus vaccine introduction periods. Genotypes G9P[8], G1P[8], G2P[4], and G12P[8] predominated consecutively each season with overall lower rotavirus incidence rates in 2016 and 2017. The demographic and clinical features of rotavirus gastroenteritis were comparable among wild-type rotaviruses; however, children with G12P[8] infections were older (p < 0.001). Continued efforts to monitor changes in the molecular epidemiology of rotavirus using whole genome sequence characterization are needed to further understand the impact of the selection pressure of vaccination on rotavirus evolution.

Predictors of laboratory-confirmed mpox in people with mpox-like illness.

OBJECTIVES: We aimed to identify predictors of confirmed monkeypox (mpox) among people with mpox-like illness and to develop a multivariable model for confirmed mpox. METHODS: We performed an observational study using national epidemiologic surveillance data in Mexico from May to November 2022. People with mpox-like illness were reported to the Mexican Ministry of Health and real-time polymerase chain reaction was performed in clinical samples to confirm mpox. Sociodemographic and clinical data were collected with a case report form. We performed univariable logistic regressions to estimate the predictive capability of individual characteristics, reported with ORs and 95% CIs. Variables of interest were included in multivariable logistic regression models and Akaike information criterion was used to retain variables for the final model. Discrimination and calibration of the model were estimated in bootstrap resamples. RESULTS: A total of 5078 people were reported with mpox-like illness. Of 5078 people, 3291 (64.8%) had confirmed mpox. The strongest clinical predictors of confirmed mpox in univariable models were proctitis (OR 6.54, 5.93-7.21), inguinal adenopathy (OR 5.91, 5.36-6.52), and anogenital lesions (OR 5.45, 4.94-6.02). The final model included being a man who has sex with men (8.75, 7.37-10.38), HIV diagnosis (3.04, 2.51-3.69), inguinal adenopathy (2.24, 1.81-2.77), anogenital lesions (2.32, 1.97-2.74), and pustules (1.55, 1.32-1.81). Discrimination capability was excellent (c-statistic 0.88, 95% CI 0.87-0.89) and it was well calibrated (calibration slope 1, 95% CI 0.95-1.05). DISCUSSION: A third of people with mpox-like illness do not have mpox. Factors such as being a man who has sex with men, HIV diagnosis, inguinal adenopathy, pustules, and anogenital lesions are associated with confirmed mpox.

Attribution Analysis of Household Foodborne Disease Outbreaks in China, 2010-2020.

Foodborne diseases have become a serious public health problem worldwide, and foodborne disease outbreaks have placed a heavy disease burden on China. Foodborne disease outbreaks occur most frequently among families in China. The objectives of this study were to analyze the cause of household foodborne disease outbreaks in China from 2010 to 2020 and to identify where preventive measures could be targeted. All data were obtained from the China Foodborne Disease Surveillance System Report. A total of 17,985 outbreaks, which resulted in 73,252 illnesses, 38,829 hospitalizations, and 1269 deaths, were reported in this period. Most household outbreaks of foodborne diseases occurred in May-October, and the highest number occurred in July (3620 outbreaks, 20%). The province with the highest number of outbreaks was Yunnan Province (4829 outbreaks), followed by Hunan Province (2264 outbreaks). The attribution analysis revealed that fungi (mainly poisonous mushrooms) were the most implicated food category, with 8873 (49.3%) cases. The second was poisonous plants and their products, with 1552 (8.6%) cases. Fungi were the primary etiologic agent, with 31,125 illnesses, accounting for 42.5% of the incidents. Inedibility and misuse (9423 outbreaks), unknown origin (2505 outbreaks), and improper processing (2365 outbreaks) were the main contributing factors causing outbreaks of foodborne diseases. The results show that southwest China was a high-risk area for household foodborne diseases. Therefore, public health institutions should strengthen supervision and food safety education of residents to reduce the outbreaks of household foodborne diseases.

Respiratory syncytial virus surge in 2022 caused by lineages already present before the COVID-19 pandemic.

In 2022, Austria experienced a severe respiratory syncytial virus (RSV) epidemic with an earlier-than-usual start (Weeks 35/2021-45/2022) and increased numbers of pediatric patients in emergency departments. This surge came 2 years after a season with no cases detected as a result of coronavirus disease 2019 nonpharmaceutical interventions. We analyzed epidemiologic patterns and the phylodynamics of RSV based on approximately 30 800 respiratory specimens collected year-round over 10 years from ambulatory and hospitalized patients from 248 locations in Austria. Genomic surveillance and phylogenetic analysis of 186 RSV-A and 187 RSV-B partial glycoprotein sequences collected from 2018 to 2022 revealed that the 2022/2023 surge was driven by RSV-B in contrast to the surge in the 2021/2022 season that was driven by RSV-A. Whole-genome sequencing and phylodynamic analysis indicated that the RSV-B strain GB5.0.6a was the predominant genotype in the 2022/2023 season and emerged in late 2019. The results provide insight into RSV evolution and epidemiology that will be applicable to future monitoring efforts with the advent of novel vaccines and therapeutics.

Tailoring capture-recapture methods to estimate registry-based case counts based on error-prone diagnostic signals.

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database.

Reshaping surveillance for infectious diseases: less chasing of pathogens and more monitoring of drivers.

Animal health surveillance, despite its name, tends to focus on looking for disease. Often this involves searching for cases of infection with known pathogens (â€Ëœpathogen chasing'). Such an approach is both resource intensive and limited by the requirement for prior knowledge of disease likelihood. In this paper, the authors propose the gradual reshaping of surveillance towards the systems level, focusing on the processes (â€Ëœdrivers') that promote disease or health, rather than on the presence or absence of specific pathogens. Examples of relevant drivers include land-use change, increasing global interconnectedness, and finance and capital flows. Importantly, the authors suggest that surveillance should focus on detecting changes in patterns or quantities associated with such drivers. This would generate systems-level, risk-based surveillance information to identify areas where additional attention may be needed, and, over time, inform the implementation of prevention efforts. The collection, integration and analysis of data on drivers is likely to require investment in improving data infrastructures. A period of overlap would allow the two systems (traditional surveillance and driver monitoring) to be compared and calibrated. This would also lead to a better understanding of the drivers and their linkages, and thereby generate new knowledge that can improve surveillance and inform mitigation efforts. Since surveillance of drivers may give signals when changes are occurring, which could act as alerts and enable targeted mitigation, this might even enable disease to be prevented before it happens by directly intervening in the drivers themselves. Such surveillance focused on the drivers could be expected to bring additional benefits, since the same drivers promote multiple diseases. Further, focusing on drivers rather than pathogens should enable control of currently unknown diseases, making this approach particularly timely, given the increasing risk of emergence of new diseases.

La surveillance de la santé animale a tendance, malgré son nom, à se focaliser sur la recherche des maladies. Elle implique souvent de chercher les cas d'infection par des agents pathogènes connus (" chasse aux agents pathogènes "). Ce type d'approche exige non seulement beaucoup de ressources, mais elle est aussi limitée par la nécessité d'avoir une connaissance préalable de la probabilité de survenue de la maladie en question. Dans cet article, les auteurs proposent une refonte progressive de la surveillance pour la déplacer au niveau systémique, en se concentrant sur les processus (" facteurs ") influençant la maladie ou la santé plutôt que sur la présence ou non d'agents pathogènes spécifiques. Parmi les facteurs pertinents, on peut citer les changements dans l'utilisation des sols, l'interconnexion accrue au niveau mondial et les flux financiers et de capitaux. Les auteurs soulignent cet élément important : la surveillance devrait se focaliser sur la détection de changements au niveau des schémas ou des quantités associés à ces facteurs. Cela permettrait d'obtenir des informations de surveillance au niveau systémique et basées sur les risques, afin d'identifier les domaines auxquels il pourrait être nécessaire de porter une attention particulière - ce qui informerait, à terme, la mise en oeuvre des efforts de prévention. Il est probable qu'une amélioration des infrastructures de données soit nécessaire pour assurer la collecte, l'intégration et l'analyse des données sur les facteurs. Une période de chevauchement permettrait de comparer et de calibrer les deux systèmes (surveillance traditionnelle et surveillance des facteurs). Les facteurs et les liens entre eux seraient également mieux compris, ce qui générerait de nouvelles connaissances pouvant améliorer la surveillance et informer les efforts d'atténuation. Grâce à la surveillance des facteurs, des signaux pourraient être identifiés lorsque des changements se produisent, ce qui constituerait une alerte pour que des efforts d'atténuation ciblés soient mis en place afin d'intervenir directement sur les facteurs eux-mêmes et donc prévenir une maladie avant même qu'elle ne survienne. On peut s'attendre à ce que ce type de surveillance centrée sur les facteurs apporte des bénéfices supplémentaires, puisque les mêmes facteurs peuvent favoriser de multiples maladies. De surcroît, cette orientation axée sur les facteurs plutôt que sur les agents pathogènes devrait permettre de contrôler des maladies aujourd'hui inconnues, ce qui rend cette approche d'autant plus opportune, compte tenu du risque croissant d'émergence de nouvelles maladies.

La vigilancia zoosanitaria, pese a lo que su nombre indica, tiende a centrarse en la búsqueda de enfermedades, lo que a menudo pasa por tratar de localizar casos de infección por un patógeno conocido ("persecución de patógenos"). Semejante método no solo exige cuantiosos recursos, sino que además presenta la limitación de que obliga a conocer de antemano la probabilidad de aparición de una enfermedad. Los autores proponen una remodelación gradual de la vigilancia tendente a dotarla de carácter sistémico y a centrarla no tanto en la presencia o ausencia de determinados patógenos, sino en los procesos ("inductores" o "factores de inducción", drivers) que favorecen la enfermedad o la salud. Son ejemplo de tales procesos la evolución de los usos del suelo, el creciente nivel de interconexión mundial o los flujos financieros y de capitales. Un aspecto importante que apuntan los autores es que la vigilancia debería tener por objetivo la detección de cambios en las características o cantidades de esos factores de inducción. Ello generaría información de vigilancia basada en el riesgo de carácter sistémico, que serviría para determinar aquellas zonas a las que convendría prestar más atención y, con el tiempo, fundamentar la realización de actividades de prevención. Es probable que la obtención, integración y análisis de datos sobre los factores de inducción exijan inversiones para mejorar las infraestructuras de datos. Si hubiera una fase de solapamiento, sería posible comparar y valorar los resultados de ambos sistemas (vigilancia tradicional y seguimiento de los factores de inducción). Ello serviría para entender mejor los inductores y su vinculación recíproca, lo que generaría nuevos conocimientos con los que perfeccionar la vigilancia y en los que cimentar las actividades de mitigación. Dado que la vigilancia de los inductores puede generar una señal cuando se estén produciendo cambios, señal que a su vez activaría una alerta y propiciaría medidas selectivas de mitigación, podría ser que ello sirviera incluso para prevenir una enfermedad antes de que surgiera, actuando directamente sobre los propios factores de inducción. Cabría pensar que semejante tipo de vigilancia, centrarse en los inductores, puede tener otros efectos beneficiosos, en la medida en que un mismo inductor alimenta la aparición de varias enfermedades. Además, el hecho de centrarse en los factores de inducción, y no tanto en los patógenos, debería servir para controlar enfermedades actualmente desconocidas, por lo que este planteamiento, ante el creciente riesgo de aparición de nuevas enfermedades, resulta especialmente oportuno.

Environmental sampling for disease surveillance: Recent advances and recommendations for best practice.

The study of infectious diseases includes both the progression of the disease in its host and how it transmits between hosts. Understanding disease transmission is important for recommending effective interventions, protecting healthcare workers, and informing an effective public health response. Sampling the environment for infectious diseases is critical to public health since it can provide an understanding of the mechanisms of transmission, characterization of contamination in hospitals and other public areas, and the spread of a disease within a community. Measurements of biological aerosols, particularly those that may cause disease, have been an ongoing topic of research for decades, and so a wide variety of technological solutions exist. This wide field of possibilities can create confusion, particularly when different approaches yield different answers. Therefore, guidelines for best practice in this area are important to allow more effective use of this data in public health decisions. This review examines air, surface and water/wastewater sampling methods, with a focus on aerosol sampling, and a goal of recommending approaches to designing and implementing sampling systems that may incorporate multiple strategies. This is accomplished by developing a framework for designing and evaluating a sampling strategy, reviewing current practices and emerging technologies for sampling and analysis, and recommending guidelines for best practice in the area of aerosol sampling for infectious disease.

[Monkeypox: the other pandemic, the other challenge]. / Viruela símica: la otra pandemia, el otro reto.

Since the emergence of monkeypox in Europe, this disease has gradually spread throughout the rest of the world. In Mexico, epidemiological notices have been issued with the main guidelines to follow in terms of epidemiological surveillance and official figures have been published regularly on a microsite weeks after the first cases. These sources of information were reviewed and analyzed, based on which observations are issued, in addition to other relevant publications on the subject, with the interest of reinforcing the surveillance of this disease in the country.

Desde el surgimiento de la viruela símica en Europa la enfermedad se ha extendido paulatinamente por el resto del mundo. En México se han emitido avisos epidemiológicos con las principales pautas a seguir en materia de vigilancia epidemiológica y publicado las cifras oficiales de forma regular en un micrositio semanas después de los primeros casos. Se revisaron y analizaron dichas fuentes de información, con base en las cuales se emiten observaciones, además de otras publicaciones relevantes del tema, con el interés de reforzar la vigilancia de esta enfermedad en el país.

Surgical site infection surveillance in German hospitals: a national survey to determine the status quo of digitalization.

BACKGROUND: Surveillance of surgical site infections (SSI) relies on access to data from various sources. Insights into the practices of German hospitals conducting SSI surveillance and their information technology (IT) infrastructures are scarce. The aim of this study was to evaluate current SSI surveillance practices in German hospitals with a focus on employed IT infrastructures. METHODS: German surgical departments actively participating in the national SSI surveillance module "OP-KISS" were invited in August 2020 to participate in a questionnaire-based online survey. Depending on whether departments entered all data manually or used an existing feature to import denominator data into the national surveillance database, departments were separated into different groups. Selected survey questions differed between groups. RESULTS: Of 1,346 invited departments, 821 participated in the survey (response rate: 61%). Local IT deficits (n = 236), incompatibility of import specifications and hospital information system (n = 153) and lack of technical expertise (n = 145) were cited as the most frequent reasons for not using the denominator data import feature. Conversely, reduction of workload (n = 160) was named as the main motivation to import data. Questions on data availability and accessibility in the electronic hospital information system (HIS) and options to export data from the HIS for the purpose of surveillance, yielded diverse results. Departments utilizing the import feature tended to be from larger hospitals with a higher level of care. CONCLUSIONS: The degree to which digital solutions were employed for SSI surveillance differed considerably between surgical departments in Germany. Improving availability and accessibility of information in HIS and meeting interoperability standards will be prerequisites for increasing the amount of data exported directly from HIS to national databases and laying the foundation for automated SSI surveillance on a broad scale.

Heterogeneity in COVID-19 infection among older persons in South Africa: Evidence from national surveillance data.

Background: The 2021 World Health Organization study on the impact of COVID-19 on older people (≥60 years) in the African region highlighted the difficulties they faced as the virus spread across borders and dominated the way of life. These difficulties included disruptions to both essential health care services and social support, as well as disconnections from family and friends. Among those who contracted COVID-19, the risks of severe illness, complications, and mortality were highest among near-old and older persons. Objective: Recognizing that older persons are a diverse group including younger- and older-aged individuals, a study was conducted to track the epidemic among near-old (50-59 years) and older persons (≥60 years) in South Africa covering the 2 years since the epidemic emerged. Methods: Using a quantitative secondary research approach, data for near-old and older persons were extracted for comparative purposes. COVID-19 surveillance outcomes (confirmed cases, hospitalizations, and deaths) and vaccination data were compiled up to March 5th, 2022. COVID-19 surveillance outcomes were plotted by epidemiological week and epidemic waves to visualize the overall growth and trajectory of the epidemic. Means for each age-group and by COVID-19 waves, together with age-specific rates, were calculated. Results: Average numbers of new COVID-19 confirmed cases and hospitalizations were highest among people aged 50-59- and 60-69-years. However, average age-specific infection rates showed that people aged 50-59 years and ≥80 years were most vulnerable to contracting COVID-19. Age-specific hospitalization and death rates increased, with people aged ≥ 70 years most affected. The number of people vaccinated was slightly higher among people aged 50-59 years before Wave Three and during Wave Four, but higher among people aged ≥ 60 years during Wave Three. The findings suggest that uptake of vaccinations stagnated prior to and during Wave Four for both age groups. Discussion: Health promotion messages and COVID-19 epidemiological surveillance and monitoring are still needed, particularly for older persons living in congregate residential and care facilities. Prompt health-seeking should be encouraged, including testing and diagnosis as well as taking up vaccines and boosters, particularly for high-risk older persons.

Identifying animal viruses in humans.

Experimental virology can inform strategic monitoring for new viruses in humans.

Managing sources of error during pandemics.

The COVID-19 pandemic has highlighted important considerations for modeling future pandemics.