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1.
Public Health Pract (Oxf) ; 4: 100339, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2105787

ABSTRACT

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.

2.
J Biomed Inform ; : 104236, 2022 Oct 22.
Article in English | MEDLINE | ID: covidwho-2083188

ABSTRACT

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.

3.
Microorganisms ; 10(9)2022 Sep 16.
Article in English | MEDLINE | ID: covidwho-2071643

ABSTRACT

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.

4.
Int J Environ Res Public Health ; 19(19)2022 Sep 28.
Article in English | MEDLINE | ID: covidwho-2065956

ABSTRACT

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.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , COVID-19/epidemiology , Disease Outbreaks , Emergency Service, Hospital , Humans , Italy/epidemiology , Pandemics , Sentinel Surveillance , Syndrome
5.
Science of The Total Environment ; : 158967, 2022.
Article in English | ScienceDirect | ID: covidwho-2042127

ABSTRACT

Public health surveillance systems for COVID-19 are multifaceted and include multiple indicators reflective of different aspects of the burden and spread of the disease in a community. With the emergence of wastewater disease surveillance as a powerful tool to track infection dynamics of SARS-CoV-2, there is a need to integrate and validate wastewater information with existing disease surveillance systems and demonstrate how it can be used as a routine surveillance tool. A first step toward integration is showing how it relates to other disease surveillance indicators and outcomes, such as case positivity rates, syndromic surveillance data, and hospital bed use rates. Here, we present an 86-week long surveillance study that covers three major COVID-19 surges. City-wide SARS-CoV-2 RNA viral loads in wastewater were measured across 39 wastewater treatment plants and compared to other disease metrics for the city of Houston, TX. We show that wastewater levels are strongly correlated with positivity rate, syndromic surveillance rates of COVID-19 visits, and COVID-19-related general bed use rates at hospitals. We show that the relative timing of wastewater relative to each indicator shifted across the pandemic, likely due to a multitude of factors including testing availability, health-seeking behavior, and changes in viral variants. Next, we show that individual WWTPs led city-wide changes in SARS-CoV-2 viral loads, indicating a distributed monitoring system could be used to enhance the early-warning capability of a wastewater monitoring system. Finally, we describe how the results were used in real-time to inform public health response and resource allocation.

6.
31st ACM Web Conference, WWW 2022 ; : 924-929, 2022.
Article in English | Scopus | ID: covidwho-2029537

ABSTRACT

Novel infectious disease outbreaks, including most recently that of the COVID-19 pandemic, could be detected by non-specific syndromic surveillance systems. Such systems, utilizing a variety of data sources ranging from Electronic Health Records to internet data such as aggregated search engine queries, create alerts when unusually high rates of symptom reports occur. This is especially important for the detection of novel diseases, where their manifested symptoms are unknown. Here we improve upon a set of previously-proposed non-specific syndromic surveillance methods by taking into account both how unusual a preponderance of symptoms is and their effect size. We demonstrate that our method is as accurate as previously-proposed methods for low dimensional data and show its effectiveness for high-dimensional aggregated data by applying it to aggregated time-series health-related search engine queries. We find that in 2019 the method would have raised alerts related to several disease outbreaks earlier than health authorities did. During the COVID-19 pandemic the system identified the beginning of pandemic waves quickly, through combinations of symptoms which varied from wave to wave. Thus, the proposed method could be used as a practical tool for decision makers to detect new disease outbreaks using time series derived from search engine data even in the absence of specific information on the diseases of interest and their symptoms. © 2022 ACM.

7.
PLoS Global Public Health ; 2(7), 2022.
Article in English | CAB Abstracts | ID: covidwho-2021498

ABSTRACT

Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making-as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them difficult to diagnose using only syndromic presentation. Yet, with delays in getting reference laboratory tests and limited availability and poor sensitivity of point-of-care tests, syndromic diagnosis is the most-relied upon method in clinical practice today. Here, we examine the variability in diagnostic identification of respiratory infections during the annual infection cycle in northern New Mexico, by comparing syndromic diagnostics with polymerase chain reaction (PCR) and sequencing-based methods, with the goal of assessing gaps in our current ability to identify respiratory pathogens. Of 97 individuals that presented with symptoms of respiratory infection, only 23 were positive for at least one RNA virus, as confirmed by sequencing. Whereas influenza virus (n = 7) was expected during this infection cycle, we also observed coronavirus (n = 7), respiratory syncytial virus (n = 8), parainfluenza virus (n = 4), and human metapneumovirus (n = 1) in individuals with respiratory infection symptoms. Four patients were coinfected with two viruses. In 21 individuals that tested positive using PCR, RNA sequencing completely matched in only 12 (57%) of these individuals. Few individuals (37.1%) were diagnosed to have an upper respiratory tract infection or viral syndrome by syndromic diagnostics, and the type of virus could only be distinguished in one patient. Thus, current syndromic diagnostic approaches fail to accurately identify respiratory pathogens associated with infection and are not suited to capture emerging threats in an accurate fashion. We conclude there is a critical and urgent need for layered agnostic diagnostics to track known and unknown pathogens at the point of care to control future outbreaks.

8.
Expert Rev Mol Diagn ; 22(1): 49-60, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-2008441

ABSTRACT

INTRODUCTION: Pneumonia is one of the main causes of mortality associated with infectious diseases worldwide. Several challenges have been identified in the management of patients with pneumonia, ranging from accurate and cost-effective microbiological investigations, prompt and adequate therapeutic management, and optimal treatment duration. AREAS COVERED: In this review, an updated summary on the current management of pneumonia patients is provided and the epidemiological issues of infectious respiratory diseases, which in the current pandemic situation are of particular concern, are addressed. The clinical and microbiological approaches to pneumonia diagnosis are reviewed, including discussion about the new molecular assays pointing out both their strengths and limitations. Finally, the current recommendations about antibiotic treatment are examined and discussed depending on the epidemiological contexts, including those with high prevalence of multidrug-resistant bacteria. EXPERT OPINION: We claim that rapid diagnostic tests, if well-positioned in the diagnostic workflow and reserved for the subset of patients who could most benefit from these technologies, may represent an interesting and feasible tool to optimize timing of targeted treatments especially in terms of early de-escalation or discontinuation of antibiotic therapy.


Subject(s)
Diagnostic Tests, Routine , Pneumonia , Anti-Bacterial Agents/therapeutic use , Drug Resistance, Multiple, Bacterial , Humans , Pneumonia/diagnosis , Pneumonia/drug therapy , Prevalence
9.
MethodsX ; 9: 101820, 2022.
Article in English | MEDLINE | ID: covidwho-1983661

ABSTRACT

This article describes a new method for estimating weekly incidence (new onset) of symptoms consistent with Influenza and COVID-19, using data from the Flutracking survey. The method mitigates some of the known self-selection and symptom-reporting biases present in existing approaches to this type of participatory longitudinal survey data. The key novel steps in the analysis are: 1) Identifying new onset of symptoms for three different Symptom Groupings: COVID-like illness (CLI1+, CLI2+), and Influenza-like illness (ILI), for responses reported in the Flutracking survey. 2) Adjusting for symptom reporting bias by restricting the analysis to a sub-set of responses from those participants who have consistently responded for a number of weeks prior to the analysis week. 3) Weighting responses by age to adjust for self-selection bias in order to account for the under- and over-representation of different age groups amongst the survey participants. This uses the survey package [22] in R [30]. 4) Constructing 95% point-wise confidence bands for incidence estimates using weighted logistic regression from the survey package [21] in R [28]. In addition to describing these steps, the article demonstrates an application of this method to Flutracking data for the 12 months from 27th April 2020 until 25th April 2021.

10.
JMIR Public Health Surveill ; 8(8): e32347, 2022 08 03.
Article in English | MEDLINE | ID: covidwho-1974480

ABSTRACT

BACKGROUND: The COVID-19 pandemic has resulted in an unprecedented impact on the day-to-day lives of people, with several features potentially adversely affecting mental health. There is growing evidence of the size of the impact of COVID-19 on mental health, but much of this is from ongoing population surveys using validated mental health scores. OBJECTIVE: This study investigated the impact of the pandemic and control measures on mental health conditions presenting to a spectrum of national health care services monitored using real-time syndromic surveillance in England. METHODS: We conducted a retrospective observational descriptive study of mental health presentations (those calling the national medical helpline, National Health Service [NHS] 111; consulting general practitioners [GPs] in and out-of-hours; calling ambulance services; and attending emergency departments) from January 1, 2019, to September 30, 2020. Estimates for the impact of lockdown measures were provided using an interrupted time series analysis. RESULTS: Mental health presentations showed a marked decrease during the early stages of the pandemic. Postlockdown, attendances for mental health conditions reached higher than prepandemic levels across most systems-a rise of 10% compared to that expected for NHS 111 and 21% for GP out-of-hours service-while the number of consultations to GP in-hours service was 13% lower compared to the same time previous year. Increases were observed in calls to NHS 111 for sleep problems. CONCLUSIONS: These analyses showed marked changes in the health care attendances and prescribing for common mental health conditions across a spectrum of health care provision, with some of these changes persisting. The reasons for such changes are likely to be complex and multifactorial. The impact of the pandemic on mental health may not be fully understood for some time, and therefore, these syndromic indicators should continue to be monitored.


Subject(s)
COVID-19 , COVID-19/epidemiology , Communicable Disease Control , Delivery of Health Care , England/epidemiology , Humans , Mental Health , Pandemics , Retrospective Studies , State Medicine
11.
J Clin Microbiol ; 60(10): e0244621, 2022 10 19.
Article in English | MEDLINE | ID: covidwho-1949964

ABSTRACT

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.


Subject(s)
COVID-19 , Communicable Diseases , Nucleic Acids , Humans , Pathology, Molecular , COVID-19/diagnosis , Nucleic Acid Amplification Techniques/methods , Communicable Diseases/diagnosis , Molecular Diagnostic Techniques/methods
12.
Medicine (Madr) ; 13(58): 3432-3437, 2022 Jun.
Article in Spanish | MEDLINE | ID: covidwho-1931032

ABSTRACT

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.

13.
Sex Transm Infect ; 2022 Jul 05.
Article in English | MEDLINE | ID: covidwho-1923306

ABSTRACT

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.

14.
Microbiol Spectr ; 10(4): e0124822, 2022 08 31.
Article in English | MEDLINE | ID: covidwho-1909613

ABSTRACT

This study compares three of the most inclusive and widely used panels for respiratory syndromic testing in the United States, namely, Luminex NxTAG Respiratory Pathogen Panel (RPP), BioFire FilmArray Respiratory Panel (RP), and GenMark eSensor Respiratory Viral Panel (RVP). We compared the three assays using nasopharyngeal swab samples (n = 350) collected from symptomatic patients (n = 329) in the pre-coronavirus disease 2019 (COVID-19) era. There was no significant difference in the overall accuracies of BioFire and Luminex assays (P = 0.6171); however, significant differences were found between BioFire and GenMark (P = 0.0003) and between GenMark and Luminex (P = 0.0009). The positive percent agreement of the BioFire RP assay was 94.1%, compared to 97.3% for GenMark RVP and 96.5% for Luminex RPP. Overall negative percent agreement values were high for all three assays, i.e., 99.9% for BioFire and Luminex and 99.5% for GenMark. The three assays were equivalent for adenovirus, human metapneumovirus, influenza A, and respiratory syncytial virus. Increased false-positive results were seen with BioFire for the endemic coronaviruses and with GenMark for influenza B and the parainfluenza viruses. IMPORTANCE Clinical laboratories have multiple choices when it is comes to syndromic respiratory testing. Here, the Luminex NxTAG RPP is compared to the BioFire FilmArray RP and GenMark eSensor RVP for overall and per-target accuracy. As new tests come to market, it is important to ascertain their performance characteristics, compared to other widely used in vitro diagnostic products.


Subject(s)
COVID-19 , Influenza, Human , Respiratory Tract Infections , Viruses , Humans , Molecular Diagnostic Techniques/methods , Respiratory Tract Infections/diagnosis , Viruses/genetics
15.
J Clin Virol ; 153: 105221, 2022 08.
Article in English | MEDLINE | ID: covidwho-1907271

ABSTRACT

OBJECTIVES: Viral respiratory infections are common in children, and usually associated with non-specific symptoms. Respiratory panel-based testing was implemented during the COVID-19 pandemic, for the rapid differentiation between SARS-CoV-2 and other viral infections, in children attending the emergency department (ED) of the teaching hospital of Lille, northern France, between February 2021 and January 2022. METHODS: Samples were collected using nasopharyngeal swabs. Syndromic respiratory testing was performed with two rapid multiplex molecular assays: the BioFire® Respiratory Panel 2.1 - plus (RP2.1 plus) or the QIAstat-Dx Respiratory SARS-CoV-2 Panel. SARS-CoV-2 variant was screened using mutation-specific PCR-based assays and genome sequencing. RESULTS: A total of 3517 children were included in the study. SARS-CoV-2 was detected in samples from 265 children (7.5%). SARS-CoV-2 infected patients were younger than those without SARS-CoV-2 infection (median age: 6 versus 12 months, p < 0.0001). The majority of infections (61.5%) were associated with the Omicron variant. The median weekly SARS-CoV-2 positivity rate ranged from 1.76% during the Alpha variant wave to 24.5% with the emergence of the Omicron variant. Most children (70.2%) were treated as outpatients, and seventeen patients were admitted to the intensive care unit. Other respiratory viruses were more frequently detected in SARS-CoV-2 negative children than in positive ones (82.1% versus 37.4%, p < 0.0001). Human rhinovirus/enterovirus and respiratory syncytial virus were the most prevalent in both groups. CONCLUSIONS: We observed a low prevalence of SARS-CoV-2 infection in children attending pediatric ED, despite the significant increase due to Delta and Omicron variants, and an important circulation of other respiratory viruses. Severe disease was overall rare in children.


Subject(s)
COVID-19 , Respiratory Tract Infections , Virus Diseases , COVID-19/diagnosis , COVID-19/epidemiology , Emergency Service, Hospital , France , Humans , Infant , Pandemics , Respiratory Tract Infections/diagnosis , Respiratory Tract Infections/virology , SARS-CoV-2 , Virus Diseases/diagnosis
16.
Am J Infect Control ; 50(9): 1064-1066, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1885586

ABSTRACT

To evaluate the co-circulation of respiratory viruses during the SARS-CoV-2 Alpha surge, we performed a molecular respiratory panel on 1,783 nasopharyngeal swabs collected between January 15 and April 15, 2021, from symptomatic outpatients that tested negative for SARS-CoV-2 in North Carolina. Of these, 373 (20.9%) were positive for at least 1 virus tested on the panel. Among positive tests, over 90% were positive for rhinovirus and/or enterovirus, either as a single infection or coinfection, illustrating persistent co-circulation of some respiratory viruses despite active infection control measures.


Subject(s)
COVID-19 , Coinfection , Respiratory Tract Infections , COVID-19/epidemiology , Coinfection/epidemiology , Humans , Pandemics , Respiratory Tract Infections/epidemiology , Rhinovirus , SARS-CoV-2
17.
Int J Infect Dis ; 122: 337-344, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1882081

ABSTRACT

OBJECTIVE: Northern Syria faces a large burden of influenza-like illness (ILI) and severe acute respiratory illness (SARI). This study aimed to investigate the trends of Early Warning and Response Network (EWARN) reported ILI and SARI in northern Syria between 2016 and 2021 and the potential impact of SARS-CoV-2. METHODS: We extracted weekly EWARN data on ILI/ SARI and aggregated cases and consultations into 4-week intervals to calculate case positivity. We conducted a seasonal-trend decomposition to assess case trends in the presence of seasonal fluctuations. RESULTS: It was observed that 4-week aggregates of ILI cases (n = 5,942,012), SARI cases (n = 114,939), ILI case positivity, and SARI case positivity exhibited seasonal fluctuations with peaks in the winter months. ILI and SARI cases in individuals aged ≥5 years surpassed those in individuals aged <5 years in late 2019. ILI cases clustered primarily in Aleppo and Idlib, whereas SARI cases clustered in Aleppo, Idlib, Deir Ezzor, and Hassakeh. SARI cases increased sharply in 2021, corresponding with a severe SARS-CoV-2 wave, compared with the steady increase in ILI cases over time. CONCLUSION: Respiratory infections cause widespread morbidity and mortality throughout northern Syria, particularly with the emergence of SARS-CoV-2. Strengthened surveillance and access to testing and treatment are critical to manage outbreaks among conflict-affected populations.


Subject(s)
COVID-19 , Influenza, Human , Respiratory Tract Infections , Virus Diseases , COVID-19/epidemiology , Humans , Influenza, Human/diagnosis , Influenza, Human/epidemiology , Respiratory Tract Infections/diagnosis , Respiratory Tract Infections/epidemiology , SARS-CoV-2 , Seasons , Sentinel Surveillance , Syria/epidemiology
18.
Int J Environ Res Public Health ; 19(8)2022 04 13.
Article in English | MEDLINE | ID: covidwho-1809866

ABSTRACT

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


Subject(s)
Mass Gatherings , Sentinel Surveillance , Disease Outbreaks , Emergency Service, Hospital , Population Surveillance , Public Health Surveillance/methods
19.
Euro Surveill ; 27(16)2022 04.
Article in English | MEDLINE | ID: covidwho-1809281

ABSTRACT

BackgroundThe COVID-19 pandemic presented new challenges for the existing respiratory surveillance systems, and adaptations were implemented. Systematic assessment of the syndromic and sentinel surveillance platforms during the pandemic is essential for understanding the value of each platform in the context of an emerging pathogen with rapid global spread.AimWe aimed to evaluate systematically the performance of various respiratory syndromic surveillance platforms and the sentinel surveillance system in Israel from 1 January to 31 December 2020.MethodsWe compared the 2020 syndromic surveillance trends to those of the previous 3 years, using Poisson regression adjusted for overdispersion. To assess the performance of the sentinel clinic system as compared with the national SARS-CoV-2 repository, a cubic spline with 7 knots and 95% confidence intervals were applied to the sentinel network's weekly percentage of positive SARS-CoV-2 cases.ResultsSyndromic surveillance trends changed substantially during 2020, with a statistically significant reduction in the rates of visits to physicians and emergency departments to below previous years' levels. Morbidity patterns of the syndromic surveillance platforms were inconsistent with the progress of the pandemic, while the sentinel surveillance platform was found to reflect the national circulation of SARS-CoV-2 in the population.ConclusionOur findings reveal the robustness of the sentinel clinics platform for the surveillance of the main respiratory viruses during the pandemic and possibly beyond. The robustness of the sentinel clinics platform during 2020 supports its use in locations with insufficient resources for widespread testing of respiratory viruses.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , Israel/epidemiology , Pandemics , Sentinel Surveillance
20.
Front Microbiol ; 13: 854209, 2022.
Article in English | MEDLINE | ID: covidwho-1785373

ABSTRACT

Point-of-care syndromic panels allow for simultaneous and rapid detection of respiratory pathogens from nasopharyngeal swabs. The clinical performance of the QIAstat-Dx Respiratory SARS-CoV-2 panel RP2.0 (QIAstat-Dx RP2.0) and the BioFire FilmArray Respiratory panel RP2.1 (BioFire RP2.1) was evaluated for the detection of SARS-CoV-2 and other common respiratory pathogens. A total of 137 patient samples were retrospectively selected based on emergency department admission, along with 33 SARS-CoV-2 positive samples tested using a WHO laboratory developed test. The limit of detection for SARS-CoV-2 was initially evaluated for both platforms. The QIAstat-Dx RP2.0 detected SARS-CoV-2 at 500 copies/mL and had a positive percent agreement (PPA) of 85%. The BioFire RP2.1 detected SARS-CoV-2 at 50 copies/mL and had a PPA of 97%. Both platforms showed a negative percent agreement of 100% for SARS-CoV-2. Evaluation of analytical specificity from a range of common respiratory targets showed a similar performance between each platform. The QIAstat-Dx RP2.0 had an overall PPA of 82% (67-100%) in clinical samples, with differences in sensitivity depending on the respiratory target. Both platforms can be used to detect acute cases of SARS-CoV-2. While the QIAstat-Dx RP2.0 is suitable for detecting respiratory viruses within a clinical range, it has less analytical and clinical sensitivity for SARS-CoV-2 compared to the BioFire RP2.1.

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