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1.
Emerg Infect Dis ; 28(1): 9-19, 2022 01.
Article in English | MEDLINE | ID: covidwho-1581410

ABSTRACT

State and local health departments established the California Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Respiratory Virus Sentinel Surveillance System to conduct enhanced surveillance for SARS-CoV-2 and other respiratory pathogens at sentinel outpatient testing sites in 10 counties throughout California, USA. We describe results obtained during May 10, 2020‒June 12, 2021, and compare persons with positive and negative SARS-CoV-2 PCR results by using Poisson regression. We detected SARS-CoV-2 in 1,696 (19.6%) of 8,662 specimens. Among 7,851 specimens tested by respiratory panel, rhinovirus/enterovirus was detected in 906 (11.5%) specimens and other respiratory pathogens in 136 (1.7%) specimens. We also detected 23 co-infections with SARS-CoV-2 and another pathogen. SARS-CoV-2 positivity was associated with male participants, an age of 35-49 years, Latino race/ethnicity, obesity, and work in transportation occupations. Sentinel surveillance can provide useful virologic and epidemiologic data to supplement other disease monitoring activities and might become increasingly useful as routine testing decreases.


Subject(s)
COVID-19 , Coinfection , Adult , Humans , Male , Middle Aged , Polymerase Chain Reaction , SARS-CoV-2 , Sentinel Surveillance
2.
Sci Rep ; 11(1): 24449, 2021 12 27.
Article in English | MEDLINE | ID: covidwho-1585776

ABSTRACT

Syndromic surveillance systems monitor disease indicators to detect emergence of diseases and track their progression. Here, we report on a rapidly deployed active syndromic surveillance system for tracking COVID-19 in Israel. The system was a novel combination of active and passive components: Ads were shown to people searching for COVID-19 symptoms on the Google search engine. Those who clicked on the ads were referred to a chat bot which helped them decide whether they needed urgent medical care. Through its conversion optimization mechanism, the ad system was guided to focus on those people who required such care. Over 6 months, the ads were shown approximately 214,000 times and clicked on 12,000 times, and 722 people were informed they needed urgent care. Click rates on ads and the fraction of people deemed to require urgent care were correlated with the hospitalization rate ([Formula: see text] and [Formula: see text], respectively) with a lead time of 9 days. Males and younger people were more likely to use the system, and younger people were more likely to be determined to require urgent care (slope: [Formula: see text], [Formula: see text]). Thus, the system can assist in predicting case numbers and hospital load at a significant lead time and, simultaneously, help people determine if they need medical care.


Subject(s)
COVID-19/epidemiology , Sentinel Surveillance , Ambulatory Care/statistics & numerical data , COVID-19/pathology , COVID-19/virology , Hospitalization/statistics & numerical data , Humans , Israel/epidemiology , Linear Models , SARS-CoV-2/isolation & purification , Search Engine
3.
S Afr Med J ; 111(11): 1078-1083, 2021 11 05.
Article in English | MEDLINE | ID: covidwho-1534499

ABSTRACT

BACKGROUND: Estimates of prevalence of anti-SARS-CoV-2 antibody positivity (seroprevalence) for tracking the COVID-19 epidemic are lacking for most African countries. OBJECTIVES: To determine the prevalence of antibodies against SARS-CoV-2 in a sentinel cohort of patient samples received for routine testing at tertiary laboratories in Johannesburg, South Africa. METHODS: This sentinel study was conducted using remnant serum samples received at three National Health Laboratory Service laboratories in the City of Johannesburg (CoJ) district. Collection was from 1 August to 31 October 2020. We extracted accompanying laboratory results for glycated haemoglobin (HbA1c), creatinine, HIV, viral load and CD4 T-cell count. An anti-SARS-CoV-2 targeting the nucleocapsid (N) protein of the coronavirus with higher affinity for IgM and IgG antibodies was used. We reported crude as well as population-weighted and test-adjusted seroprevalence. Multivariate logistic regression analysis was used to determine whether age, sex, HIV and diabetic status were associated with increased risk for seropositivity. RESULTS: A total of 6 477 samples were analysed, the majority (n=5 290) from the CoJ region. After excluding samples with no age or sex stated, the model population-weighted and test-adjusted seroprevalence for the CoJ (n=4 393) was 27.0% (95% confidence interval (CI) 25.4 - 28.6). Seroprevalence was highest in those aged 45 - 49 years (29.8%; 95% CI 25.5 - 35.0) and in those from the most densely populated areas of the CoJ. Risk for seropositivity was highest in those aged 18 - 49 years (adjusted odds ratio (aOR) 1.52; 95% CI 1.13 - 2.13; p=0.0005) and in samples from diabetics (aOR 1.36; 95% CI 1.13 - 1.63; p=0.001). CONCLUSIONS: Our study conducted between the first and second waves of the pandemic shows high levels of current infection among patients attending public health facilities in Gauteng Province.


Subject(s)
Antibodies, Viral/immunology , COVID-19/epidemiology , SARS-CoV-2/isolation & purification , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , COVID-19/immunology , Child , Child, Preschool , Cross-Sectional Studies , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Prevalence , SARS-CoV-2/immunology , Sentinel Surveillance , Seroepidemiologic Studies , South Africa/epidemiology , Young Adult
4.
JMIR Public Health Surveill ; 7(7): e27621, 2021 07 09.
Article in English | MEDLINE | ID: covidwho-1505428

ABSTRACT

BACKGROUND: The national severe acute respiratory illness (SARI) surveillance system in Yemen was established in 2010 to monitor SARI occurrence in humans and provide a foundation for detecting SARI outbreaks. OBJECTIVE: To ensure that the objectives of national surveillance are being met, this study aimed to examine the level of usefulness and the performance of the SARI surveillance system in Yemen. METHODS: The updated Centers for Disease Control and Prevention guidelines were used for the purposes of our evaluation. Related documents and reports were reviewed. Data were collected from 4 central-level managers and stakeholders and from 10 focal points at 4 sentinel sites by using a semistructured questionnaire. For each attribute, percent scores were calculated and ranked as follows: very poor (≤20%), poor (20%-40%), average (40%-60%), good (60%-80%), and excellent (>80%). RESULTS: As rated by the evaluators, the SARI surveillance system achieved its objectives. The system's flexibility (percent score: 86%) and acceptability (percent score: 82%) were rated as "excellent," and simplicity (percent score: 74%) and stability (percent score: 75%) were rated as "good." The percent score for timeliness was 23% in 2018, which indicated poor timeliness. The overall data quality percent score of the SARI system was 98.5%. Despite its many strengths, the SARI system has some weaknesses. For example, it depends on irregular external financial support. CONCLUSIONS: The SARI surveillance system was useful in estimating morbidity and mortality, monitoring the trends of the disease, and promoting research for informing prevention and control measures. The overall performance of the SARI surveillance system was good. We recommend expanding the system by promoting private health facilities' (eg, private hospitals and private health centers) engagement in SARI surveillance, establishing an electronic database at central and peripheral sites, and providing the National Central Public Health Laboratory with the reagents needed for disease confirmation.


Subject(s)
Sentinel Surveillance , Severe Acute Respiratory Syndrome/epidemiology , Centers for Disease Control and Prevention, U.S. , Disease Outbreaks , Humans , United States , Yemen/epidemiology
5.
BMC Public Health ; 21(1): 2019, 2021 11 05.
Article in English | MEDLINE | ID: covidwho-1503931

ABSTRACT

BACKGROUND: Since the end of January 2020, the coronavirus (COVID-19) pandemic has been responsible for a global health crisis. In England a number of non-pharmaceutical interventions have been introduced throughout the pandemic, including guidelines on healthcare attendance (for example, promoting remote consultations), increased handwashing and social distancing. These interventions are likely to have impacted the incidence of non-COVID-19 conditions as well as healthcare seeking behaviour. Syndromic Surveillance Systems offer the ability to monitor trends in healthcare usage over time. METHODS: This study describes the indirect impact of COVID-19 on healthcare utilisation using a range of syndromic indicators including eye conditions, mumps, fractures, herpes zoster and cardiac conditions. Data from the syndromic surveillance systems monitored by Public Health England were used to describe the number of contacts with NHS 111, general practitioner (GP) In Hours (GPIH) and Out-of-Hours (GPOOH), Ambulance and Emergency Department (ED) services over comparable periods before and during the pandemic. RESULTS: The peak pandemic period in 2020 (weeks 13-20), compared to the same period in 2019, displayed on average a 12% increase in NHS 111 calls, an 11% decrease in GPOOH consultations, and a 49% decrease in ED attendances. In the GP In Hours system, conjunctivitis consultations decreased by 64% and mumps consultations by 31%. There was a 49% reduction in attendance at EDs for fractures, and there was no longer any weekend increase in ED fracture attendances, with similar attendance patterns observed across each day of the week. There was a decrease in the number of ED attendances with diagnoses of myocardial ischaemia. CONCLUSION: The COVID-19 pandemic drastically impacted healthcare utilisation for non-COVID-19 conditions, due to a combination of a probable decrease in incidence of certain conditions and changes in healthcare seeking behaviour. Syndromic surveillance has a valuable role in describing and understanding these trends.


Subject(s)
COVID-19 , Pandemics , Emergency Service, Hospital , Humans , Patient Acceptance of Health Care , SARS-CoV-2 , Sentinel Surveillance
6.
BMC Med ; 19(1): 270, 2021 10 14.
Article in English | MEDLINE | ID: covidwho-1496171

ABSTRACT

BACKGROUND: In a prospective healthcare worker (HCW) cohort, we assessed the risk of SARS-CoV-2 infection according to baseline serostatus. METHODS: Baseline serologies were performed among HCW from 23 Swiss healthcare institutions between June and September 2020, before the second COVID-19 wave. Participants answered weekly electronic questionnaires covering information about nasopharyngeal swabs (PCR/rapid antigen tests) and symptoms compatible with coronavirus disease 2019 (COVID-19). Screening of symptomatic staff by nasopharyngeal swabs was routinely performed in participating facilities. We compared numbers of positive nasopharyngeal tests and occurrence of COVID-19 symptoms between HCW with and without anti-nucleocapsid antibodies. RESULTS: A total of 4812 HCW participated, wherein 144 (3%) were seropositive at baseline. We analyzed 107,807 questionnaires with a median follow-up of 7.9 months. Median number of answered questionnaires was similar (24 vs. 23 per person, P = 0.83) between those with and without positive baseline serology. Among 2712 HCW with ≥ 1 SARS-CoV-2 test during follow-up, 3/67 (4.5%) seropositive individuals reported a positive result (one of whom asymptomatic), compared to 547/2645 (20.7%) seronegative participants, 12 of whom asymptomatic (risk ratio [RR] 0.22; 95% confidence interval [CI] 0.07 to 0.66). Seropositive HCWs less frequently reported impaired olfaction/taste (6/144, 4.2% vs. 588/4674, 12.6%, RR 0.33, 95% CI 0.15-0.73), chills (19/144, 13.2% vs. 1040/4674, 22.3%, RR 0.59, 95% CI 0.39-0.90), and limb/muscle pain (28/144, 19.4% vs. 1335/4674, 28.6%, RR 0.68 95% CI 0.49-0.95). Impaired olfaction/taste and limb/muscle pain also discriminated best between positive and negative SARS-CoV-2 results. CONCLUSIONS: Having SARS-CoV-2 anti-nucleocapsid antibodies provides almost 80% protection against SARS-CoV-2 re-infection for a period of at least 8 months.


Subject(s)
COVID-19 , SARS-CoV-2 , Cohort Studies , Health Personnel , Humans , Prospective Studies , Sentinel Surveillance
7.
Public Health Rep ; 136(1_suppl): 72S-79S, 2021.
Article in English | MEDLINE | ID: covidwho-1495836

ABSTRACT

OBJECTIVE: Traditional public health surveillance of nonfatal opioid overdose relies on emergency department (ED) billing data, which can be delayed substantially. We compared the timeliness of 2 new data sources for rapid drug overdose surveillance-emergency medical services (EMS) and syndromic surveillance-with ED billing data. METHODS: We used data on nonfatal opioid overdoses in Kentucky captured in EMS, syndromic surveillance, and ED billing systems during 2018-2019. We evaluated the time-series relationships between EMS and ED billing data and syndromic surveillance and ED billing data by calculating cross-correlation functions, controlling for influences of autocorrelations. A case example demonstrates the usefulness of EMS and syndromic surveillance data to monitor rapid changes in opioid overdose encounters in Kentucky during the COVID-19 epidemic. RESULTS: EMS and syndromic surveillance data showed moderate-to-strong correlation with ED billing data on a lag of 0 (r = 0.694; 95% CI, 0.579-0.782; t = 9.73; df = 101; P < .001; and r = 0.656; 95% CI, 0.530-0.754; t = 8.73; df = 101; P < .001; respectively) at the week-aggregated level. After the COVID-19 emergency declaration, EMS and syndromic surveillance time series had steep increases in April and May 2020, followed by declines from June through September 2020. The ED billing data were available for analysis 3 months after the end of a calendar quarter but closely followed the trends identified by the EMS and syndromic surveillance data. CONCLUSION: Data from EMS and syndromic surveillance systems can be reliably used to monitor nonfatal opioid overdose trends in Kentucky in near-real time to inform timely public health response.


Subject(s)
Analgesics, Opioid/poisoning , Drug Overdose/epidemiology , Emergency Medical Services/statistics & numerical data , Opioid-Related Disorders/epidemiology , Population Surveillance/methods , Public Health Surveillance/methods , Sentinel Surveillance , Analgesics, Opioid/administration & dosage , COVID-19/epidemiology , Drug Overdose/prevention & control , Emergencies/epidemiology , Emergency Medical Services/trends , Humans , Kentucky/epidemiology , Pandemics , Public Health , SARS-CoV-2
8.
BMC Infect Dis ; 20(1): 148, 2020 Feb 18.
Article in English | MEDLINE | ID: covidwho-1453043

ABSTRACT

BACKGROUND: The influenza virus spreads rapidly around the world in seasonal epidemics, resulting in significant morbidity and mortality. Influenza-related incidence data are limited in many countries in Africa despite established sentinel surveillance. This study aimed to address the information gap by estimating the burden and seasonality of medically attended influenza like illness in Ethiopia. METHOD: Influenza sentinel surveillance data collected from 3 influenza like illness (ILI) and 5 Severe Acute Respiratory Illness (SARI) sites from 2012 to 2017 was used for analysis. Descriptive statistics were applied for simple analysis. The proportion of medically attended influenza positive cases and incidence rate of ILI was determined using total admitted patients and catchment area population. Seasonality was estimated based on weekly trend of ILI and predicted threshold was done by applying the "Moving Epidemic Method (MEM)". RESULT: A total of 5715 medically attended influenza suspected patients who fulfills ILI and SARI case definition (77% ILI and 23% SARI) was enrolled. Laboratory confirmed influenza virus (influenza positive case) among ILI and SARI suspected case was 25% (1130/4426) and 3% (36/1289). Of which, 65% were influenza type A. The predominantly circulating influenza subtype were seasonal influenza A(H3N2) (n = 455, 60%) and Influenza A(H1N1)pdm09 (n = 293, 38.81%). The estimated mean annual influenza positive case proportion and ILI incidence rate was 160.04 and 52.48 per 100,000 population. The Incidence rate of ILI was higher in the age group of 15-44 years of age ['Incidence rate (R) = 254.6 per 100,000 population', 95% CI; 173.65, 335.55] and 5-14 years of age [R = 49.5, CI 95%; 31.47, 130.43]. The seasonality of influenza has two peak seasons; in a period from October-December and from April-June. CONCLUSION: Significant morbidity of influenza like illness was observed with two peak seasons of the year and seasonal influenza A (H3N2) remains the predominantly circulating influenza subtype. Further study need to be considered to identify potential risks and improving the surveillance system to continue early detection and monitoring of circulating influenza virus in the country has paramount importance.


Subject(s)
Influenza, Human/epidemiology , Influenza, Human/virology , Adolescent , Adult , Child , Child, Preschool , Ethiopia/epidemiology , Female , Hospitalization/statistics & numerical data , Humans , Incidence , Infant , Influenza A Virus, H1N1 Subtype/isolation & purification , Influenza A Virus, H3N2 Subtype/isolation & purification , Laboratories , Male , Middle Aged , Respiratory Tract Diseases/epidemiology , Respiratory Tract Diseases/etiology , Seasons , Sentinel Surveillance , Young Adult
9.
Influenza Other Respir Viruses ; 14(5): 530-540, 2020 09.
Article in English | MEDLINE | ID: covidwho-1452864

ABSTRACT

BACKGROUND: Influenza is an acute infection affecting all age groups; however, elderly patients are at an increased risk. We aim to describe the clinical characteristics and the circulation of influenza virus types in elderly patients admitted for severe acute respiratory infection (SARI) to a tertiary care hospital in Bucharest, Romania, part of the I-MOVE+ hospital network. METHODS: We conducted an active surveillance study at the National Institute for Infectious Diseases "Prof. Dr Matei Balș," Bucharest, Romania, during three consecutive influenza seasons: 2015/16, 2016/17, and 2017/18. All patients aged 65 and older admitted to our hospital for SARI were tested for influenza by PCR. RESULTS: A total of 349 eligible patients were tested during the study period, and 149 (42.7%) were confirmed with influenza. Most patients, 321 (92.5%) presented at least one underlying condition at the time of hospital admission, the most frequent being cardiovascular disease, 270 (78.3%). The main influenza viral subtype circulating in 2015/16 was A(H1N1)pdm09, followed by A(H3N2) in 2016/17 and B influenza in 2017/18. Case fatality was highest in the 2015/16 season (3.7%), 0% in 2016/17, and 1.0% in 2017/18. Vaccination coverage in elderly patients with SARI from our study population was 22 (6.3%) over the three seasons. CONCLUSIONS: Our study has highlighted a high burden of comorbidities in elderly patients presenting with SARI during winter season in Romania. The influenza vaccine coverage rate needs to be substantially increased in the elderly population, through targeted interventions.


Subject(s)
Influenza, Human/epidemiology , Sentinel Surveillance , Age Factors , Aged , Aged, 80 and over , Female , Hospitalization/statistics & numerical data , Humans , Influenza A Virus, H1N1 Subtype/genetics , Influenza A Virus, H1N1 Subtype/immunology , Influenza A Virus, H3N2 Subtype/genetics , Influenza A Virus, H3N2 Subtype/immunology , Influenza B virus/genetics , Influenza B virus/immunology , Influenza Vaccines/immunology , Male , Romania/epidemiology , Seasons , Tertiary Healthcare
10.
Infect Control Hosp Epidemiol ; 41(5): 499-504, 2020 05.
Article in English | MEDLINE | ID: covidwho-1452452

ABSTRACT

OBJECTIVE: Older adults often have atypical presentation of illness and are particularly vulnerable to influenza and its sequelae, making the validity of influenza case definitions particularly relevant. We sought to assess the performance of influenza-like illness (ILI) and severe acute respiratory illness (SARI) criteria in hospitalized older adults. DESIGN: Prospective cohort study. SETTING: The Serious Outcomes Surveillance Network of the Canadian Immunization Research Network undertakes active surveillance for influenza among hospitalized adults. METHODS: Data were pooled from 3 influenza seasons: 2011/12, 2012/13, and 2013/14. The ILI and SARI criteria were defined clinically, and influenza was laboratory confirmed. Frailty was measured using a validated frailty index. RESULTS: Of 11,379 adult inpatients (7,254 aged ≥65 years), 4,942 (2,948 aged ≥65 years) had laboratory-confirmed influenza. Their median age was 72 years (interquartile range [IQR], 58-82) and 52.6% were women. The sensitivity of ILI criteria was 51.1% (95% confidence interval [CI], 49.6-52.6) for younger adults versus 44.6% (95% CI, 43.6-45.8) for older adults. SARI criteria were met by 64.1% (95% CI, 62.7-65.6) of younger adults versus 57.1% (95% CI, 55.9-58.2) of older adults with laboratory-confirmed influenza. Patients with influenza who were prefrail or frail were less likely to meet ILI and SARI case definitions. CONCLUSIONS: A substantial proportion of older adults, particularly those who are frail, are missed by standard ILI and SARI case definitions. Surveillance using these case definitions is biased toward identifying younger cases, and does not capture the true burden of influenza. Because of the substantial fraction of cases missed, surveillance definitions should not be used to guide diagnosis and clinical management of influenza.


Subject(s)
Influenza, Human/diagnosis , Influenza, Human/epidemiology , Aged , Aged, 80 and over , Bias , Canada/epidemiology , Female , Frail Elderly , Hospitalization , Humans , Immunization , Laboratories, Hospital , Male , Prospective Studies , Research , Sensitivity and Specificity , Sentinel Surveillance
11.
Int J Environ Res Public Health ; 18(18)2021 09 16.
Article in English | MEDLINE | ID: covidwho-1409512

ABSTRACT

Accurate predictions of COVID-19 epidemic dynamics may enable timely organizational interventions in high-risk regions. We exploited the interconnection of the Fresenius Medical Care (FMC) European dialysis clinic network to develop a sentinel surveillance system for outbreak prediction. We developed an artificial intelligence-based model considering the information related to all clinics belonging to the European Nephrocare Network. The prediction tool provides risk scores of the occurrence of a COVID-19 outbreak in each dialysis center within a 2-week forecasting horizon. The model input variables include information related to the epidemic status and trends in clinical practice patterns of the target clinic, regional epidemic metrics, and the distance-weighted risk estimates of adjacent dialysis units. On the validation dates, there were 30 (5.09%), 39 (6.52%), and 218 (36.03%) clinics with two or more patients with COVID-19 infection during the 2-week prediction window. The performance of the model was suitable in all testing windows: AUC = 0.77, 0.80, and 0.81, respectively. The occurrence of new cases in a clinic propagates distance-weighted risk estimates to proximal dialysis units. Our machine learning sentinel surveillance system may allow for a prompt risk assessment and timely response to COVID-19 surges throughout networked European clinics.


Subject(s)
COVID-19 , Artificial Intelligence , Disease Outbreaks , Humans , Renal Dialysis , SARS-CoV-2 , Sentinel Surveillance
13.
J Travel Med ; 27(8)2020 12 23.
Article in English | MEDLINE | ID: covidwho-1387947

ABSTRACT

RATIONALE FOR REVIEW: In response to increased concerns about emerging infectious diseases, GeoSentinel, the Global Surveillance Network of the International Society of Travel Medicine in partnership with the US Centers for Disease Control and Prevention (CDC), was established in 1995 in order to serve as a global provider-based emerging infections sentinel network, conduct surveillance for travel-related infections and communicate and assist global public health responses. This review summarizes the history, past achievements and future directions of the GeoSentinel Network. KEY FINDINGS: Funded by the US CDC in 1996, GeoSentinel has grown from a group of eight US-based travel and tropical medicine centers to a global network, which currently consists of 68 sites in 28 countries. GeoSentinel has provided important contributions that have enhanced the ability to use destination-specific differences to guide diagnosis and treatment of returning travelers, migrants and refugees. During the last two decades, GeoSentinel has identified a number of sentinel infectious disease events including previously unrecognized outbreaks and occurrence of diseases in locations thought not to harbor certain infectious agents. GeoSentinel has also provided useful insight into illnesses affecting different traveling populations such as migrants, business travelers and students, while characterizing in greater detail the epidemiology of infectious diseases such as typhoid fever, leishmaniasis and Zika virus disease. CONCLUSIONS: Surveillance of travel- and migration-related infectious diseases has been the main focus of GeoSentinel for the last 25 years. However, GeoSentinel is now evolving into a network that will conduct both research and surveillance. The large number of participating sites and excellent geographic coverage for identification of both common and illnesses in individuals who have traversed international borders uniquely position GeoSentinel to make important contributions of travel-related infectious diseases in the years to come.


Subject(s)
COVID-19 , International Cooperation , Sentinel Surveillance , Travel Medicine , COVID-19/epidemiology , COVID-19/prevention & control , Centers for Disease Control and Prevention, U.S. , Geographic Information Systems , Humans , SARS-CoV-2 , Travel Medicine/methods , Travel Medicine/trends , Travel-Related Illness , United States
14.
MMWR Morb Mortal Wkly Rep ; 69(28): 918-922, 2020 Jul 17.
Article in English | MEDLINE | ID: covidwho-1389847

ABSTRACT

To limit introduction of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), the United States restricted travel from China on February 2, 2020, and from Europe on March 13. To determine whether local transmission of SARS-CoV-2 could be detected, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) conducted deidentified sentinel surveillance at six NYC hospital emergency departments (EDs) during March 1-20. On March 8, while testing availability for SARS-CoV-2 was still limited, DOHMH announced sustained community transmission of SARS-CoV-2 (1). At this time, twenty-six NYC residents had confirmed COVID-19, and ED visits for influenza-like illness* increased, despite decreased influenza virus circulation.† The following week, on March 15, when only seven of the 56 (13%) patients with known exposure histories had exposure outside of NYC, the level of community SARS-CoV-2 transmission status was elevated from sustained community transmission to widespread community transmission (2). Through sentinel surveillance during March 1-20, DOHMH collected 544 specimens from patients with influenza-like symptoms (ILS)§ who had negative test results for influenza and, in some instances, other respiratory pathogens.¶ All 544 specimens were tested for SARS-CoV-2 at CDC; 36 (6.6%) tested positive. Using genetic sequencing, CDC determined that the sequences of most SARS-CoV-2-positive specimens resembled those circulating in Europe, suggesting probable introductions of SARS-CoV-2 from Europe, from other U.S. locations, and local introductions from within New York. These findings demonstrate that partnering with health care facilities and developing the systems needed for rapid implementation of sentinel surveillance, coupled with capacity for genetic sequencing before an outbreak, can help inform timely containment and mitigation strategies.


Subject(s)
Betacoronavirus/genetics , Betacoronavirus/isolation & purification , Community-Acquired Infections/diagnosis , Community-Acquired Infections/virology , Coronavirus Infections/diagnosis , Coronavirus Infections/virology , Pneumonia, Viral/diagnosis , Pneumonia, Viral/virology , Sentinel Surveillance , Adolescent , Adult , Aged , COVID-19 , Child , Child, Preschool , Community-Acquired Infections/epidemiology , Coronavirus Infections/epidemiology , Emergency Service, Hospital , Female , Humans , Infant , Male , Middle Aged , New York City/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , SARS-CoV-2 , Sequence Analysis , Travel-Related Illness , Young Adult
15.
JMIR Public Health Surveill ; 7(8): e29309, 2021 08 16.
Article in English | MEDLINE | ID: covidwho-1381348

ABSTRACT

The World Health Organization and others warn that substandard and falsified medicines harm health and waste money, especially in low- and middle-income countries. However, no country has measured the market-wide extent of the problem, and no standardized methods exist to estimate the prevalence of either substandard or falsified medicines. This is, in part, because the task seems overwhelming; medicine markets are huge and diverse, and testing medicines is expensive. Many countries do operate some form of postmarket surveillance of medicine, but their methods and goals differ. There is currently no clear guidance on which surveillance method is most appropriate to meet specific public health goals. In this viewpoint, we aimed to discuss the utility of both case finding and risk-based sentinel surveillance for substandard and falsified medicines, linking each to specific public health goals. We posit that choosing the system most appropriate to the goal, as well as implementing it with a clear understanding of the factors driving the production and sale of substandard and falsified medicines, will allow for surveillance resources to be concentrated most efficiently. We adapted principles used for disease outbreak responses to suggest a case-finding system that uses secondary data to flag poor-quality medicines, proposing risk-based indicators that differ for substandard and falsified medicines. This system potentially offers a cost-effective way of identifying "cases" for market withdrawal, enhanced oversight, or another immediate response. We further proposed a risk-based sentinel surveillance system that concentrates resources on measuring the prevalence of substandard and falsified medicines in the risk clusters where they are most likely to be found. The sentinel surveillance system provides base data for a transparent, spreadsheet-based model for estimating the national prevalence of substandard and falsified medicines. The methods we proposed are based on ongoing work in Indonesia, a large and diverse middle-income country currently aiming to achieve universal health coverage. Both the case finding and the sentinel surveillance system are designed to be adaptable to other resource-constrained settings.


Subject(s)
Counterfeit Drugs , Commerce , Humans , Public Health , Sentinel Surveillance
16.
Am J Public Health ; 111(8): 1542-1550, 2021 08.
Article in English | MEDLINE | ID: covidwho-1381327

ABSTRACT

Objectives. To evaluate the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) over 6 months in the Brazilian State of Rio Grande do Sul (population 11.3 million), based on 8 serological surveys. Methods. In each survey, 4151 participants in round 1 and 4460 participants in round 2 were randomly sampled from all state regions. We assessed presence of antibodies against SARS-CoV-2 using a validated lateral flow point-of-care test; we adjusted figures for the time-dependent decay of antibodies. Results. The SARS-CoV-2 antibody prevalence increased from 0.03% (95% confidence interval [CI] = 0.00%, 0.34%; 1 in every 3333 individuals) in mid-April to 1.89% (95% CI = 1.36%, 2.54%; 1 in every 53 individuals) in early September. Prevalence was similar across gender and skin color categories. Older adults were less likely to be infected than younger participants. The proportion of the population who reported leaving home daily increased from 21.4% (95% CI = 20.2%, 22.7%) to 33.2% (95% CI = 31.8%, 34.5%). Conclusions. SARS-CoV-2 infection increased slowly during the first 6 months in the state, differently from what was observed in other Brazilian regions. Future survey rounds will continue to document the spread of the pandemic.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/diagnosis , COVID-19/epidemiology , Adolescent , Adult , Aged , Aged, 80 and over , Brazil/epidemiology , Child , Child, Preschool , Female , Humans , Male , Middle Aged , Prevalence , Sentinel Surveillance , Seroepidemiologic Studies , Social Class , Young Adult
17.
JAMA Netw Open ; 4(8): e2119621, 2021 08 02.
Article in English | MEDLINE | ID: covidwho-1359743

ABSTRACT

Importance: In 2020 and early 2021, the National Football League (NFL) and National Collegiate Athletic Association (NCAA) opted to host football games in stadiums across the country. The in-person attendance of games varied with time and from county to county. There is currently no evidence on whether limited in-person attendance of games is associated with COVID-19 case numbers on a county-level. Objective: To assess whether NFL and NCAA football games with limited in-person attendance were associated with increased COVID-19 cases in the counties they were held compared with a matched set of counties. Design, Setting, and Participants: In this time-series cross-sectional study, every county hosting NFL or NCAA games with in-person attendance (treated group) in 2020 and 2021 was matched with a county that that did not host a game on the corresponding day but had an identical game history for up to 14 days prior (control group). A standard matching method was used to further refine this matched set so that the treated and matched control counties had similar population size, nonpharmaceutical interventions in place, and COVID-19 trends. The association of hosting games with in-person attendance with COVID-19 cases was assessed using a difference-in-difference estimator. Data were analyzed from August 29 to December 28, 2020. Exposures: Hosting NFL or NCAA games. Main Outcomes and Measures: The main outcome was estimation of new COVID-19 cases per 100 000 residents at the county level reported up to 14 days after a game among counties with NFL and NCAA games with in-person attendance. Results: A total of 528 games with in-person attendance (101 NFL games [19.1%]; 427 NCAA games [80.9%]) were included. The matching algorithm returned 361 matching sets of counties. The median (interquartile range [IQR]) number of attendance for NFL games was 9949 (6000 to 13 797) people. The median number of attendance for NCAA games was not available, and attendance was recorded as a binary variable. The median (IQR) daily new COVID-19 cases in treatment group counties hosting games was 26.14 (10.77-50.25) cases per 100 000 residents on game day. The median (IQR) daily new COVID-19 cases in control group counties where no games were played was 24.11 (9.64-48.55) cases per 100 000 residents on game day. The treatment effect size ranged from -5.17 to 4.72, with a mean (SD) of 1.21 (2.67) cases per 100 000 residents, within the 14-day period in all counties hosting the games, and the daily treatment effect trend remained relatively steady during this period. Conclusions and Relevance: This cross-sectional study did not find a consistent increase in the daily COVID-19 cases per 100 000 residents in counties where NFL and NCAA games were held with limited in-person attendance. These findings suggest that NFL and NCAA football games hosted with limited in-person attendance were not associated with substantial risk for increased local COVID-19 cases.


Subject(s)
COVID-19/epidemiology , Communicable Disease Control/statistics & numerical data , Population Health/statistics & numerical data , Sentinel Surveillance , Sports and Recreational Facilities/statistics & numerical data , COVID-19/prevention & control , COVID-19/transmission , Communicable Disease Control/methods , Cross-Sectional Studies , Football , Humans , Organizations, Nonprofit , SARS-CoV-2 , Societies , United States/epidemiology , Universities
18.
J Occup Environ Med ; 63(6): 528-531, 2021 06 01.
Article in English | MEDLINE | ID: covidwho-1288155

ABSTRACT

BACKGROUND: Health care workers (HCWs) experience increased occupational risk of contracting COVID-19, with temporal trends that might inform surveillance. METHODS: We analyzed data from a Veterans Affairs hospital-based COVID-19 worker telephone hotline collected over 40 weeks (2020). We calculated the proportion of COVID-19+ cases among persons-under-investigation (PUIs) for illness compared to rates from a nearby large university-based health care institution. RESULTS: We observed 740 PUIs, 65 (8.8%) COVID-19+. Time trends were similar at the study and comparison hospitals; only for the first of 10 four-week observation periods was the ratio for observed to expected COVID-19+ significant (P < 0.001). DISCUSSION: These data suggest that employee health COVID-19+ to PUI ratios could be utilized as a barometer of community trends. Pooling experience among heath care facilities may yield insights into occupational infectious disease outbreaks.


Subject(s)
COVID-19/epidemiology , Health Personnel/statistics & numerical data , Occupational Exposure/statistics & numerical data , COVID-19/diagnosis , Cohort Studies , Hospitals, University , Hospitals, Veterans , Humans , Incidence , Occupational Health/statistics & numerical data , SARS-CoV-2/isolation & purification , San Francisco/epidemiology , Sentinel Surveillance
19.
BMC Public Health ; 21(1): 1230, 2021 06 26.
Article in English | MEDLINE | ID: covidwho-1282253

ABSTRACT

BACKGROUND: The COVID-19 pandemic has continued to pose a major global public health risk. The importance of public health surveillance systems to monitor the spread and impact of COVID-19 has been well demonstrated. The purpose of this study was to describe the development and effectiveness of a real-time public health syndromic surveillance system (ACES Pandemic Tracker) as an early warning system and to provide situational awareness in response to the COVID-19 pandemic in Ontario, Canada. METHODS: We used hospital admissions data from the Acute Care Enhanced Surveillance (ACES) system to collect data on pre-defined groupings of symptoms (syndromes of interest; SOI) that may be related to COVID-19 from 131 hospitals across Ontario. To evaluate which SOI for suspected COVID-19 admissions were best correlated with laboratory confirmed admissions, laboratory confirmed COVID-19 hospital admissions data were collected from the Ontario Ministry of Health. Correlations and time-series lag analysis between suspected and confirmed COVID-19 hospital admissions were calculated. Data used for analyses covered the period between March 1, 2020 and September 21, 2020. RESULTS: Between March 1, 2020 and September 21, 2020, ACES Pandemic Tracker identified 22,075 suspected COVID-19 hospital admissions (150 per 100,000 population) in Ontario. After correlation analysis, we found laboratory-confirmed hospital admissions for COVID-19 were strongly and significantly correlated with suspected COVID-19 hospital admissions when SOI were included (Spearman's rho = 0.617) and suspected COVID-19 admissions when SOI were excluded (Spearman's rho = 0.867). Weak to moderate significant correlations were found among individual SOI. Laboratory confirmed COVID-19 hospital admissions lagged in reporting by 3 days compared with suspected COVID-19 admissions when SOI were excluded. CONCLUSIONS: Our results demonstrate the utility of a hospital admissions syndromic surveillance system to monitor and identify potential surges in severe COVID-19 infection within the community in a timely manner and provide situational awareness to inform preventive and preparatory health interventions.


Subject(s)
COVID-19 , Pandemics , Hospitals , Humans , Ontario/epidemiology , SARS-CoV-2 , Sentinel Surveillance
20.
Am J Infect Control ; 49(6): 685-689, 2021 06.
Article in English | MEDLINE | ID: covidwho-1279522

ABSTRACT

OBJECTIVES: Since December 2019, COVID-19 has caused a worldwide pandemic and Singapore has seen escalating cases with community spread. Aggressive contact tracing and identification of suspects has helped to identify local community clusters, surveillance being the key to early intervention. Healthcare workers (HCWs) have contracted COVID-19 infection both at the workplace and community. We aimed to create a prototype staff surveillance system for the detection of acute respiratory infection (ARI) clusters amongst our HCWs and describe its effectiveness. METHODS: A prototypical surveillance system was built on existing electronic health record infrastructure. RESULTS: Over a 10-week period, we investigated 10 ARI clusters amongst 7 departments. One of the ARI clusters was later determined to be related to COVID-19 infection. We demonstrate the feasibility of syndromic surveillance to detect ARI clusters during the COVID-19 outbreak. CONCLUSION: The use of syndromic surveillance to detect ARI clusters amongst HCWs in the COVID-19 pandemic may enable early case detection and prevent onward transmission. It could be an important tool in infection prevention within healthcare institutions.


Subject(s)
COVID-19 , Pandemics , Disease Outbreaks , Electronic Health Records , Health Personnel , Humans , SARS-CoV-2 , Sentinel Surveillance , Singapore/epidemiology
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