Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends.

Introduction: Large-scale diagnostic testing has been proven insufficient to promptly monitor the spread of the Coronavirus disease 2019. Electronic resources may provide better insight into the early detection of epidemics. We aimed to retrospectively explore whether the Google search volume has been useful in detecting Severe Acute Respiratory Syndrome Coronavirus outbreaks early compared to the swab-based surveillance system. Methods: The Google Trends website was used by applying the research to three Italian regions (Lombardy, Marche, and Sicily), covering 16 million Italian citizens. An autoregressive-moving-average model was fitted, and residual charts were plotted to detect outliers in weekly searches of five keywords. Signals that occurred during periods labelled as free from epidemics were used to measure Positive Predictive Values and False Negative Rates in anticipating the epidemic wave occurrence. Results: Signals from "fever," "cough," and "sore throat" showed better performance than those from "loss of smell" and "loss of taste." More than 80% of true epidemic waves were detected early by the occurrence of at least an outlier signal in Lombardy, although this implies a 20% false alarm signals. Performance was poorer for Sicily and Marche. Conclusion: Monitoring the volume of Google searches can be a valuable tool for early detection of respiratory infectious disease outbreaks, particularly in areas with high access to home internet. The inclusion of web-based syndromic keywords is promising as it could facilitate the containment of COVID-19 and perhaps other unknown infectious diseases in the future.

Establishing severe acute respiratory infection (SARI) surveillance in a sentinel hospital, Ireland, 2021 to 2022.

BackgroundIn 2020, due to the COVID-19 pandemic, the European Centre for Disease Prevention and Control (ECDC) accelerated development of European-level severe acute respiratory infection (SARI) surveillance.AimWe aimed to establish SARI surveillance in one Irish hospital as part of a European network E-SARI-NET.MethodsWe used routine emergency department records to identify cases in one adult acute hospital. The SARI case definition was adapted from the ECDC clinical criteria for a possible COVID-19 case. Clinical data were collected using an online questionnaire. Cases were tested for SARS-CoV-2, influenza and respiratory syncytial virus (RSV), including whole genome sequencing (WGS) on SARS-CoV-2 RNA-positive samples and viral characterisation/sequencing on influenza RNA-positive samples. Descriptive analysis was conducted for SARI cases hospitalised between July 2021 and April 2022.ResultsOverall, we identified 437 SARI cases, the incidence ranged from two to 28 cases per week (0.7-9.2/100,000 hospital catchment population). Of 431 cases tested for SARS-CoV-2 RNA, 226 (52%) were positive. Of 349 (80%) cases tested for influenza and RSV RNA, 15 (4.3%) were positive for influenza and eight (2.3%) for RSV. Using WGS, we identified Delta- and Omicron-dominant periods. The resource-intensive nature of manual clinical data collection, specimen management and laboratory supply shortages for influenza and RSV testing were challenging.ConclusionWe successfully established SARI surveillance as part of E-SARI-NET. Expansion to additional sentinel sites is planned following formal evaluation of the existing system. SARI surveillance requires multidisciplinary collaboration, automated data collection where possible, and dedicated personnel resources, including for specimen management.

Changes in emergency department utilisation in Germany before and during different phases of the COVID-19 pandemic, using data from a national surveillance system up to June 2021.

BACKGROUND: During the COVID-19 pandemic and associated public health and social measures, decreasing patient numbers have been described in various healthcare settings in Germany, including emergency care. This could be explained by changes in disease burden, e.g. due to contact restrictions, but could also be a result of changes in utilisation behaviour of the population. To better understand those dynamics, we analysed routine data from emergency departments to quantify changes in consultation numbers, age distribution, disease acuity and day and hour of the day during different phases of the COVID-19 pandemic. METHODS: We used interrupted time series analyses to estimate relative changes for consultation numbers of 20 emergency departments spread throughout Germany. For the pandemic period (16-03-2020 - 13-06-2021) four different phases of the COVID-19 pandemic were defined as interruption points, the pre-pandemic period (06-03-2017 - 09-03-2020) was used as the reference. RESULTS: The most pronounced decreases were visible in the first and second wave of the pandemic, with changes of - 30.0% (95%CI: - 32.2%; - 27.7%) and - 25.7% (95%CI: - 27.4%; - 23.9%) for overall consultations, respectively. The decrease was even stronger for the age group of 0-19 years, with - 39.4% in the first and - 35.0% in the second wave. Regarding acuity levels, consultations assessed as urgent, standard, and non-urgent showed the largest decrease, while the most severe cases showed the smallest decrease. CONCLUSIONS: The number of emergency department consultations decreased rapidly during the COVID-19 pandemic, without extensive variation in the distribution of patient characteristics. Smallest changes were observed for the most severe consultations and older age groups, which is especially reassuring regarding concerns of possible long-term complications due to patients avoiding urgent emergency care during the pandemic.

Rapid multiplex PCR for respiratory viruses reduces time to result and improves clinical care: Results of a systematic review and meta-analysis.

OBJECTIVES: The clinical impact of rapid sample-to-answer "syndromic" multiplex polymerase chain reaction (PCR) testing for respiratory viruses is not clearly established. We performed a systematic literature review and meta-analysis to evaluate this impact for patients with possible acute respiratory tract infection in the hospital setting. METHODS: We searched EMBASE, MEDLINE, and Cochrane databases from 2012 to present and conference proceedings from 2021 for studies comparing clinical impact outcomes between multiplex PCR testing and standard testing. RESULTS: Twenty-seven studies with 17,321 patient encounters were included in this review. Rapid multiplex PCR testing was associated with a reduction of - 24.22 h (95% CI -28.70 to -19.74 h) in the time to results. Hospital length of stay was decreased by -0.82 days (95% CI -1.52 to -0.11 days). Among influenza positive patients, antivirals were more likely to be given (RR 1.25, 95% CI 1.06-1.48) and appropriate infection control facility use was more common with rapid multiplex PCR testing (RR 1.55, 95% CI 1.16-2.07). CONCLUSIONS: Our systematic review and meta-analysis demonstrates a reduction in time to results and length of stay for patients overall along with improvements in appropriate antiviral and infection control management among influenza-positive patients. This evidence supports the routine use of rapid sample-to-answer multiplex PCR testing for respiratory viruses in the hospital setting.

COVID-19 related risk factors and their association with non-syndromic orofacial clefts in five Arab countries: a case-control study.

BACKGROUND: The environmental etiology of non-syndromic orofacial clefts (NSOFCs) is still under research. The aim of this case-control study is to assess COVID-19 associated factors that may be related to the risk of NSOFC in five Arab countries. These factors include COVID-19 infection, COVID-19 symptoms, family member or friends infected with COVID-19, stress, smoking, socioeconomic status and fear of COVID-19. METHODS: The study took place in governmental hospitals in five Arab countries from November 2020 to November 2021. Controls are matched in the month of delivery and site of recruitment. A clinical examination was carried out using LASHAL classification. Maternal exposure to medication, illnesses, supplementation, COVID-19 infection during their pregestation and 1st trimester periods were evaluated using a validated questionnaire. Maternal exposure to stress was assessed using the Life Events scale, fear of covid-19 scale, family member or friend affected with covid-19 infection, pregnancy planning and threatened abortion. RESULTS: The study recruited 1135 infants (386 NSOFC and 749 controls). Living in urban areas, maternal exposure to medications 3-months pregestation, maternal exposure to any of the prenatal life events and maternal fear of COVID-19 significantly increased the risk of having a child with NSOFC. On the other hand, mothers exposed to supplementation 3-months pregestation, mothers suspected of having COVID-19 infection, family members or friends testing positive with COVID-19 significantly decreased the risk of having a child with NSOFC. CONCLUSIONS: This study suggests that NSOFC may be associated with maternal exposure to lifetime stress and COVID-19 fear in particular, with no direct effect of the COVID-19 infection itself. This highlights the importance of providing psychological support for expecting mothers during stressful events that affect populations such as the COVID-19 pandemic, in addition to the usual antenatal care.

The Clinical Performance of the BioCode Respiratory Pathogen Panel for the Detection of Viruses and Bacteria from Nasopharyngeal Swabs.

Early detection of microbial pathogens causing respiratory tract infection plays a crucial role in clinical management. The BioCode Respiratory Pathogen Panel (BioCode RPP) utilizes reverse transcriptase PCR (RT-PCR) in combination with barcoded magnetic beads to amplify, detect, and identify respiratory pathogens. This panel qualitatively detects and identifies 14 viruses, including influenza virus A with H1 pdm09, H1, and H3 subtyping; influenza B; respiratory syncytial virus (RSV); human metapneumovirus; parainfluenza virus 1; parainfluenza virus 2; parainfluenza virus 3; parainfluenza virus 4; coronavirus (229E, NL63, OC43, and HKU1); adenovirus; and human rhinovirus/enterovirus, and 3 bacteria, including Chlamydia pneumoniae, Mycoplasma pneumoniae, and Bordetella pertussis. Reproducibility, which was assessed with contrived specimens containing 12 targets at 3 clinical sites, with 2 operators at each site for 5 days, was 99.4% for Flu A H3 and Flu B, 98.9% for RSV, and 100% for the remaining 9 targets assayed. A multicenter clinical trial evaluated the performance of the BioCode RPP with 2,647 nasopharyngeal swab specimens from 5 geographically distinct sites and revealed comparable performance between the BioCode RPP and FilmArray Respiratory Panel (FA-RP). Specifically, the positive percent agreements (PPAs) for various pathogens ranged between 80.8% and 100% compared with the FA-RP (1.7 and 2.0). Negative percent agreement ranged from 98.4% to 100% for BioCode RPP. The BioCode RPP also offers scalable automated testing capability of up to 96 specimens in a single run with total sample-to-result time under 5 h. The invalid rate of the BioCode RPP on initial testing was 1.0% (26/2,649). IMPORTANCE Early detection of microbial pathogens causing respiratory tract infection plays a crucial role in clinical management. The BioCode Respiratory Pathogen Panel (BioCode RPP) is a high-throughput test that utilizes RT-PCR in combination with barcoded magnetic beads to amplify, detect, and identify 17 respiratory pathogens, including 14 viruses and 3 bacteria. This study summarizes data generated from a multicenter clinical trial evaluating the performance of the BioCode RPP on 2,647 nasopharyngeal swab specimens from five geographically distinct sites.

Impact of the first COVID-19 lockdown on male urethritis syndrome services in South Africa.

OBJECTIVES: Globally, there have been significant changes in utilisation of STI testing and treatment services during the period of the COVID-19 pandemic. The impact of COVID-19 in countries that use syndromic STI management is not documented. This study used routine STI surveillance data to evaluate the impact of COVID-19 on utilisation of STI syndromic management services during the first wave of the COVID-19 epidemic in South Africa. METHODS: We conducted a time-trend analysis of male urethritis syndrome (MUS) cases reported through routine national STI surveillance in South Africa and COVID-19 data available through the national dashboard. We defined three time periods (prelockdown, lockdown and postlockdown) based on COVID-19 response levels. Trends in MUS reporting was compared between these time periods at national and provincial level and with the number of positive COVID-19 tests in a district. RESULTS: An overall reduction of 27% in the national number of MUS cases reported (monthly average from 27 117 to 20 107) occurred between the pre-COVID-19 and COVID-19 lockdown periods (p<0.001), with a range of 18%-39% between the nine provinces. Postlockdown, case numbers returned almost to the prelockdown level (26 304; -3.0%). No significant difference was found in number of MUS cases between the prelockdown and postlockdown periods. A weak correlation (R2=0,21) was identified between the change in number of MUS reported and COVID-19 positive tests in a district. CONCLUSIONS: A strong reduction in reported MUS cases for syndromic management was observed during the first wave of the COVID-19 epidemic and lockdown across all provinces in South Africa. This is likely the result of various healthcare system and service delivery factors associated with lockdown measures. The observed return of MUS cases reported to prelockdown measures is reassuring.

Views on increased federal access to state and local National Syndromic Surveillance Program data: a nominal group technique study with state and local epidemiologists.

BACKGROUND: US public health authorities use syndromic surveillance to monitor and detect public health threats, conditions, and trends in near real-time. Nearly all US jurisdictions that conduct syndromic surveillance send their data to the National Syndromic Surveillance Program (NSSP), operated by the US. Centers for Disease Control and Prevention. However, current data sharing agreements limit federal access to state and local NSSP data to only multi-state regional aggregations. This limitation was a significant challenge for the national response to COVID-19. This study seeks to understand state and local epidemiologists' views on increased federal access to state NSSP data and identify policy opportunities for public health data modernization. METHODS: In September 2021, we used a virtual, modified nominal group technique with twenty regionally diverse epidemiologists in leadership positions and three individuals representing national public health organizations. Participants individually generated ideas on benefits, concerns, and policy opportunities relating to increased federal access to state and local NSSP data. In small groups, participants clarified and grouped the ideas into broader themes with the assistance of the research team. An web-based survey was used to evaluate and rank the themes using five-point Likert importance questions, top-3 ranking questions, and open-ended response questions. RESULTS: Participants identified five benefit themes for increased federal access to jurisdictional NSSP data, with the most important being improved cross-jurisdiction collaboration (mean Likert = 4.53) and surveillance practice (4.07). Participants identified nine concern themes, with the most important concerns being federal actors using jurisdictional data without notice (4.60) and misinterpretation of data (4.53). Participants identified eleven policy opportunities, with the most important being involving state and local partners in analysis (4.93) and developing communication protocols (4.53). CONCLUSION: These findings identify barriers and opportunities to federal-state-local collaboration critical to current data modernization efforts. Syndromic surveillance considerations warrant data-sharing caution. However, identified policy opportunities share congruence with existing legal agreements, suggesting that syndromic partners are closer to agreement than they might realize. Moreover, several policy opportunities (i.e., including state and local partners in data analysis and developing communication protocols) received consensus support and provide a promising path forward.

Forty Years of Molecular Diagnostics for Infectious Diseases.

Nearly 40 years have elapsed since the invention of the PCR, with its extremely sensitive and specific ability to detect nucleic acids via in vitro enzyme-mediated amplification. In turn, more than 2 years have passed since the onset of the coronavirus disease 2019 (COVID-19) pandemic, during which time molecular diagnostics for infectious diseases have assumed a larger global role than ever before. In this context, we review broadly the progression of molecular techniques in clinical microbiology, to their current prominence. Notably, these methods now entail both the detection and quantification of microbial nucleic acids, along with their sequence-based characterization. Overall, we seek to provide a combined perspective on the techniques themselves, as well as how they have come to shape health care at the intersection of technologic innovation, pathophysiologic knowledge, clinical/laboratory logistics, and even financial/regulatory factors.

Syndromic Surveillance Using Structured Telehealth Data: Case Study of the First Wave of COVID-19 in Brazil.

BACKGROUND: Telehealth has been widely used for new case detection and telemonitoring during the COVID-19 pandemic. It safely provides access to health care services and expands assistance to remote, rural areas and underserved communities in situations of shortage of specialized health professionals. Qualified data are systematically collected by health care workers containing information on suspected cases and can be used as a proxy of disease spread for surveillance purposes. However, the use of this approach for syndromic surveillance has yet to be explored. Besides, the mathematical modeling of epidemics is a well-established field that has been successfully used for tracking the spread of SARS-CoV-2 infection, supporting the decision-making process on diverse aspects of public health response to the COVID-19 pandemic. The response of the current models depends on the quality of input data, particularly the transmission rate, initial conditions, and other parameters present in compartmental models. Telehealth systems may feed numerical models developed to model virus spread in a specific region. OBJECTIVE: Herein, we evaluated whether a high-quality data set obtained from a state-based telehealth service could be used to forecast the geographical spread of new cases of COVID-19 and to feed computational models of disease spread. METHODS: We analyzed structured data obtained from a statewide toll-free telehealth service during 4 months following the first notification of COVID-19 in the Bahia state, Brazil. Structured data were collected during teletriage by a health team of medical students supervised by physicians. Data were registered in a responsive web application for planning and surveillance purposes. The data set was designed to quickly identify users, city, residence neighborhood, date, sex, age, and COVID-19-like symptoms. We performed a temporal-spatial comparison of calls reporting COVID-19-like symptoms and notification of COVID-19 cases. The number of calls was used as a proxy of exposed individuals to feed a mathematical model called "susceptible, exposed, infected, recovered, deceased." RESULTS: For 181 (43%) out of 417 municipalities of Bahia, the first call to the telehealth service reporting COVID-19-like symptoms preceded the first notification of the disease. The calls preceded, on average, 30 days of the notification of COVID-19 in the municipalities of the state of Bahia, Brazil. Additionally, data obtained by the telehealth service were used to effectively reproduce the spread of COVID-19 in Salvador, the capital of the state, using the "susceptible, exposed, infected, recovered, deceased" model to simulate the spatiotemporal spread of the disease. CONCLUSIONS: Data from telehealth services confer high effectiveness in anticipating new waves of COVID-19 and may help understand the epidemic dynamics.

Agreement of respiratory viruses' detection between nasopharyngeal swab and bronchoalveolar lavage in adults admitted for pneumonia: a retrospective study.

OBJECTIVES: The COVID-19 pandemic has highlighted the high diagnostic accuracy of the nasopharyngeal swab (including in intensive care unit (ICU) patients). This study aimed to compare nasopharyngeal swab and bronchoalveolar lavage (BAL) results for non-SARS-CoV-2 viruses in patients with suspected pneumonia. METHODS: A retrospective analysis was performed in one French academic hospital on consecutive adults from 2012 to 2018 and tested nasopharyngeal swab and BAL within 24 hours by using multiplex PCR. The agreement in pathogen detection between nasopharyngeal swab and BAL was evaluated. RESULTS: Patients were primarily men (n = 178/276, 64.5%), with a median age of 60 years (IQR: 51-68 years). Of the 276 patients, 169 (61%) were admitted to the ICU for acute respiratory distress. We detected at least one respiratory virus in 34.4% of the nasopharyngeal swabs (n = 95/276) and 29.0% of BAL (n = 80/276). Two or more viruses were detected in 2.5% of the nasopharyngeal swabs (n = 7/276) and 2.2% of BAL (n = 6/276). Rhinovirus/enteroviruses were the most frequently detected viral group in 10.2% (n = 29/285) of the nasopharyngeal swabs and 9.5% (n = 27/285) of BAL, followed by influenza A, detected in 5.6% (n = 16/285) of the nasopharyngeal swabs and 4.9% (n = 14/285) of BAL. Overall agreement was 83.7% (n = 231/276 (95% CI [78.7%, 87.7%])) (i.e. same pathogen or pathogen combination was identified in the nasopharyngeal swab and BAL for 231 patients). Rhinovirus/enterovirus (n = 29/231) and respiratory syncytial virus (n = 13/231) had the lowest agreement of 62.1% (n = 18/29 (95% CI [42.4%-78.7%])) and 61.5% (n = 8/13 (95% CI [32.3%-84.9%])), respectively). CONCLUSIONS: There was a good agreement between nasopharyngeal swabs and BAL in detecting respiratory viruses among adult patients with suspected pneumonia. However, these data still encourage BAL in the case of a negative nasopharyngeal swab.

Representativeness, Vaccination Uptake, and COVID-19 Clinical Outcomes 2020-2021 in the UK Oxford-Royal College of General Practitioners Research and Surveillance Network: Cohort Profile Summary.

BACKGROUND: The Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) is one of Europe's oldest sentinel systems, working with the UK Health Security Agency (UKHSA) and its predecessor bodies for 55 years. Its surveillance report now runs twice weekly, supplemented by online observatories. In addition to conducting sentinel surveillance from a nationally representative group of practices, the RSC is now also providing data for syndromic surveillance. OBJECTIVE: The aim of this study was to describe the cohort profile at the start of the 2021-2022 surveillance season and recent changes to our surveillance practice. METHODS: The RSC's pseudonymized primary care data, linked to hospital and other data, are held in the Oxford-RCGP Clinical Informatics Digital Hub, a Trusted Research Environment. We describe the RSC's cohort profile as of September 2021, divided into a Primary Care Sentinel Cohort (PCSC)-collecting virological and serological specimens-and a larger group of syndromic surveillance general practices (SSGPs). We report changes to our sampling strategy that brings the RSC into alignment with European Centre for Disease Control guidance and then compare our cohort's sociodemographic characteristics with Office for National Statistics data. We further describe influenza and COVID-19 vaccine coverage for the 2020-2021 season (week 40 of 2020 to week 39 of 2021), with the latter differentiated by vaccine brand. Finally, we report COVID-19-related outcomes in terms of hospitalization, intensive care unit (ICU) admission, and death. RESULTS: As a response to COVID-19, the RSC grew from just over 500 PCSC practices in 2019 to 1879 practices in 2021 (PCSC, n=938; SSGP, n=1203). This represents 28.6% of English general practices and 30.59% (17,299,780/56,550,136) of the population. In the reporting period, the PCSC collected >8000 virology and >23,000 serology samples. The RSC population was broadly representative of the national population in terms of age, gender, ethnicity, National Health Service Region, socioeconomic status, obesity, and smoking habit. The RSC captured vaccine coverage data for influenza (n=5.4 million) and COVID-19, reporting dose one (n=11.9 million), two (n=11 million), and three (n=0.4 million) for the latter as well as brand-specific uptake data (AstraZeneca vaccine, n=11.6 million; Pfizer, n=10.8 million; and Moderna, n=0.7 million). The median (IQR) number of COVID-19 hospitalizations and ICU admissions was 1181 (559-1559) and 115 (50-174) per week, respectively. CONCLUSIONS: The RSC is broadly representative of the national population; its PCSC is geographically representative and its SSGPs are newly supporting UKHSA syndromic surveillance efforts. The network captures vaccine coverage and has expanded from reporting primary care attendances to providing data on onward hospital outcomes and deaths. The challenge remains to increase virological and serological sampling to monitor the effectiveness and waning of all vaccines available in a timely manner.

Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.

BackgroundDuring the COVID-19 pandemic, large-scale diagnostic testing and contact tracing have proven insufficient to promptly monitor the spread of infections.AimTo develop and retrospectively evaluate a system identifying aberrations in the use of selected healthcare services to timely detect COVID-19 outbreaks in small areas.MethodsData were retrieved from the healthcare utilisation (HCU) databases of the Lombardy Region, Italy. We identified eight services suggesting a respiratory infection (syndromic proxies). Count time series reporting the weekly occurrence of each proxy from 2015 to 2020 were generated considering small administrative areas (i.e. census units of Cremona and Mantua provinces). The ability to uncover aberrations during 2020 was tested for two algorithms: the improved Farrington algorithm and the generalised likelihood ratio-based procedure for negative binomial counts. To evaluate these algorithms' performance in detecting outbreaks earlier than the standard surveillance, confirmed outbreaks, defined according to the weekly number of confirmed COVID-19 cases, were used as reference. Performances were assessed separately for the first and second semester of the year. Proxies positively impacting performance were identified.ResultsWe estimated that 70% of outbreaks could be detected early using the proposed approach, with a corresponding false positive rate of ca 20%. Performance did not substantially differ either between algorithms or semesters. The best proxies included emergency calls for respiratory or infectious disease causes and emergency room visits.ConclusionImplementing HCU-based monitoring systems in small areas deserves further investigations as it could facilitate the containment of COVID-19 and other unknown infectious diseases in the future.

Clinical Performance Evaluation of the NeuMoDx Flu A-B/RSV/SARS-CoV-2 Vantage Assay.

SARS-CoV-2 infections may present with various symptoms that are similar to those of other respiratory diseases. For this reason, the need for simultaneous detection of at least RSV and influenza viruses together with SARS-CoV-2 was evident from the early stages of the pandemic. In the present study, we evaluated the clinical performance of the NeuMoDx™ Flu A-B/RSV/SARS-CoV-2 Vantage Assay against the conventional low-plex PCR utilized to detect influenza A-B, RSV, and SARS-CoV-2. There were 115 known positive clinical samples and 35 negative controls obtained from asymptomatic health-care workers included in the study; 25 samples were positive for influenza viruses, 46 for RSV, and 44 for SARS-CoV-2. The sensitivity, specificity, positive predictive value, and negative predictive value of the evaluated method for influenza and SARS-CoV-2 were 100%. The Spearman correlation coefficient was 0.586 (p < 0.05) for influenza and 0.893 (p < 0.05) for SARS-CoV-2. The sensitivity of the aforementioned assay for RSV was 93.47%; the specificity and the positive predictive value were 100%, and the negative predictive value was 92.10%, while the Spearman correlation coefficient was not applicable for the RSV. Overall, the assay under evaluation was shown to be a reliable alternative for the simultaneous detection of influenza viruses, RSV and SARS-CoV-2.

[Diagnostic protocol for febrile syndrome of respiratory origin in geographical areas of endemic risk of tropical infections]. / Protocolo diagnóstico del síndrome febril con focalidad respiratoria en áreas geográficas de riesgo endémico de infecciones tropicales.

The syndromic surveillance of a group of diseases that have similar signs and symptoms, a common pathophysiology, and diverse etiology is aimed at rapidly detecting the presence of outbreaks which could potentially harm public health. This includes not only known outbreaks of infectious origin but also those of unknown origin. In patients suspected of having SARS-CoV-2/COVID-19, it is recommended to consider other etiologies of tropical fever in the differential diagnosis when these patients live in or come from endemic areas, as is the case of dengue, malaria, leptospirosis, acute Chagas disease, and rickettsiosis, among other endemic diseases. The possibility of SARS-CoV-2/AH1 AH5N1 MERS-CoV coinfection with these pathogens should also be considered.

Participatory disease surveillance for a mass gathering - a prospective cohort study on COVID-19, Germany 2021.

BACKGROUND: Mass gatherings (MGs) such as music festivals and sports events have been associated with a high risk of SARS-CoV-2 transmission. On-site research can foster knowledge of risk factors for infections and improve risk assessments and precautionary measures at future MGs. We tested a web-based participatory disease surveillance tool to detect COVID-19 infections at and after an outdoor MG by collecting self-reported COVID-19 symptoms and tests. METHODS: We conducted a digital prospective observational cohort study among fully immunized attendees of a sports festival that took place from September 2 to 5, 2021 in Saxony-Anhalt, Germany. Participants used our study app to report demographic data, COVID-19 tests, symptoms, and their contact behavior. This self-reported data was used to define probable and confirmed COVID-19 cases for the full "study period" (08/12/2021 - 10/31/2021) and within the 14-day "surveillance period" during and after the MG, with the highest likelihood of an MG-related COVID-19 outbreak (09/04/2021 - 09/17/2021). RESULTS: A total of 2,808 of 9,242 (30.4%) event attendees participated in the study. Within the study period, 776 individual symptoms and 5,255 COVID-19 tests were reported. During the 14-day surveillance period around and after the MG, seven probable and seven PCR-confirmed COVID-19 cases were detected. The confirmed cases translated to an estimated seven-day incidence of 125 per 100,000 participants (95% CI [67.7/100,000, 223/100,000]), which was comparable to the average age-matched incidence in Germany during this time. Overall, weekly numbers of COVID-19 cases were fluctuating over the study period, with another increase at the end of the study period. CONCLUSION: COVID-19 cases attributable to the mass gathering were comparable to the Germany-wide age-matched incidence, implicating that our active participatory disease surveillance tool was able to detect MG-related infections. Further studies are needed to evaluate and apply our participatory disease surveillance tool in other mass gathering settings.

Protocol to implement a syndromic surveillance survey of COVID-19 in Malawi.

Introduction: Malawi experienced two waves of COVID-19 between April 2020 and February 2021. A High negative impact of COVID-19 was experienced in the second wave, with increased hospital admissions that overwhelmed the healthcare system. This paper describes a protocol to implement a telephone-based syndromic surveillance system to assist public health leaders in the guidance, implementation, and evaluation of programs and policies for COVID-19 prevention and control in Malawi. Study design: This is a serial cross-sectional telephonic-based national survey focusing on the general population and People living with HIV and AIDS. Methods: We will conduct a serial cross-sectional telephone survey to assess self-reported recent and current experience of influenza-like illness (ILI)/COVID-19-like-illness (CLI), household deaths, access to routine health services, and knowledge related to COVID-19. Structured questionnaires will be administered to two populations: 1) the general population and 2) people living with HIV (PLHIV) on antiretroviral therapy (ART) at EGPAF-supported health facilities. Electronic data collection forms using secure tablets will be used based on randomly selected mobile numbers from electronic medical records (EMR) for PLHIV. We will use random digit dialing (RDD) for the general population to generate phone numbers to dial respondents. The technique uses computer-generated random numbers, using the 10-digit basic structure of mobile phone numbers for the two existing mobile phone companies in Malawi. Interviews will be conducted only with respondents that will verbally consent. A near real-time online dashboard will be developed to help visualize the data and share results with key policymakers. Conclusion: The designed syndromic surveillance system is low-cost and feasible to implement under COVID-19 restrictions, with no physical contact with respondents and limited movement of the study teams and communities. The system will allow estimation proportions of those reporting ILI/CLI among the general population and PLHIV on ART and monitor trends over time to detect locations with possible COVID-19 transmission. Reported household deaths in Malawi, access to health services, and COVID-19 knowledge will be monitored to assess the burden and impact on communities in Malawi.

Efficient algorithms for real-time syndromic surveillance.

OBJECTIVE: Outbreaks of influenza-like diseases often cause spikes in the demand for hospital beds. Early detection of these outbreaks can enable improved management of hospital resources. The objective of this study was to test whether surveillance algorithms designed to be responsive to a wide range of anomalous decreases in the time between emergency department (ED) presentations with influenza-like illnesses provide efficient early detection of these outbreaks. METHODS: Our study used data on ED presentations to major public hospitals in Queensland, Australia across 2017-2020. We developed surveillance algorithms for each hospital that flag potential outbreaks when the average time between successive ED presentations with influenza-like illnesses becomes anomalously small. We designed one set of algorithms to be responsive to a wide range of anomalous decreases in the time between presentations. These algorithms concurrently monitor three exponentially weighted moving averages (EWMAs) of the time between presentations and flag an outbreak when at least one EWMA falls below its control limit. We designed another set of algorithms to be highly responsive to narrower ranges of anomalous decreases in the time between presentations. These algorithms monitor one EWMA of the time between presentations and flag an outbreak when the EWMA falls below its control limit. Our algorithms use dynamic control limits to reflect that the average time between presentations depends on the time of year, time of day, and day of the week. RESULTS: We compared the performance of the algorithms in detecting the start of two epidemic events at the hospital-level: the 2019 seasonal influenza outbreak and the early-2020 COVID-19 outbreak. The algorithm that concurrently monitors three EWMAs provided significantly earlier detection of these outbreaks than the algorithms that monitor one EWMA. CONCLUSION: Surveillance algorithms designed to be responsive to a wide range of anomalous decreases in the time between ED presentations are highly efficient at detecting outbreaks of influenza-like diseases at the hospital level.

Respiratory Tract Infections and Laboratory Diagnostic Methods: A Review with A Focus on Syndromic Panel-Based Assays.

Respiratory tract infections (RTIs) are the focus of developments in public health, given their widespread distribution and the high morbidity and mortality rates reported worldwide. The clinical spectrum ranges from asymptomatic or mild infection to severe or fatal disease. Rapidity is required in diagnostics to provide adequate and prompt management of patients. The current algorithm for the laboratory diagnosis of RTIs relies on multiple approaches including gold-standard conventional methods, among which the traditional culture is the most used, and innovative ones such as molecular methods, mostly used to detect viruses and atypical bacteria. The implementation of molecular methods with syndromic panels has the potential to be a powerful decision-making tool for patient management despite requiring appropriate use of the test in different patient populations. Their use radically reduces time-to-results and increases the detection of clinically relevant pathogens compared to conventional methods. Moreover, if implemented wisely and interpreted cautiously, syndromic panels can improve antimicrobial use and patient outcomes, and optimize laboratory workflow. In this review, a narrative overview of the main etiological, clinical, and epidemiological features of RTI is reported, focusing on the laboratory diagnosis and the potentialities of syndromic panels.

Early Detection of SARS-CoV-2 Epidemic Waves: Lessons from the Syndromic Surveillance in Lombardy, Italy.

We evaluated the performance of the exponentially weighted moving average (EWMA) model for comparing two families of predictors (i.e., structured and unstructured data from visits to the emergency department (ED)) for the early detection of SARS-CoV-2 epidemic waves. The study included data from 1,282,100 ED visits between 1 January 2011 and 9 December 2021 to a local health unit in Lombardy, Italy. A regression model with an autoregressive integrated moving average (ARIMA) error term was fitted. EWMA residual charts were then plotted to detect outliers in the frequency of the daily ED visits made due to the presence of a respiratory syndrome (based on coded diagnoses) or respiratory symptoms (based on free text data). Alarm signals were compared with the number of confirmed SARS-CoV-2 infections. Overall, 150,300 ED visits were encoded as relating to respiratory syndromes and 87,696 to respiratory symptoms. Four strong alarm signals were detected in March and November 2020 and 2021, coinciding with the onset of the pandemic waves. Alarm signals generated for the respiratory symptoms preceded the occurrence of the first and last pandemic waves. We concluded that the EWMA model is a promising tool for predicting pandemic wave onset.