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1.
MMWR Morb Mortal Wkly Rep ; 70(14): 523-527, 2021 Apr 09.
Artículo en Inglés | MEDLINE | ID: mdl-33830982

RESUMEN

Approximately 375,000 deaths during 2020 were attributed to COVID-19 on death certificates reported to CDC (1). Concerns have been raised that some deaths are being improperly attributed to COVID-19 (2). Analysis of International Classification of Diseases, Tenth Revision (ICD-10) diagnoses on official death certificates might provide an expedient and efficient method to demonstrate whether reported COVID-19 deaths are being overestimated. CDC assessed documentation of diagnoses co-occurring with an ICD-10 code for COVID-19 (U07.1) on U.S. death certificates from 2020 that had been reported to CDC as of February 22, 2021. Among 378,048 death certificates listing U07.1, a total of 357,133 (94.5%) had at least one other ICD-10 code; 20,915 (5.5%) had only U07.1. Overall, 97.3% of 357,133 death certificates with at least one other diagnosis (91.9% of all 378,048 death certificates) were noted to have a co-occurring diagnosis that was a plausible chain-of-event condition (e.g., pneumonia or respiratory failure), a significant contributing condition (e.g., hypertension or diabetes), or both. Overall, 70%-80% of death certificates had both a chain-of-event condition and a significant contributing condition or a chain-of-event condition only; this was noted for adults aged 18-84 years, both males and females, persons of all races and ethnicities, those who died in inpatient and outpatient or emergency department settings, and those whose manner of death was listed as natural. These findings support the accuracy of COVID-19 mortality surveillance in the United States using official death certificates. High-quality documentation of co-occurring diagnoses on the death certificate is essential for a comprehensive and authoritative public record. Continued messaging and training (3) for professionals who complete death certificates remains important as the pandemic progresses. Accurate mortality surveillance is critical for understanding the impact of variants of SARS-CoV-2, the virus that causes COVID-19, and of COVID-19 vaccination and for guiding public health action.


Asunto(s)
/mortalidad , Certificado de Defunción , Clasificación Internacional de Enfermedades , Vigilancia en Salud Pública/métodos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Masculino , Persona de Mediana Edad , Reproducibilidad de los Resultados , Estados Unidos/epidemiología , Adulto Joven
2.
JMIR Public Health Surveill ; 7(3): e26719, 2021 03 24.
Artículo en Inglés | MEDLINE | ID: mdl-33759790

RESUMEN

BACKGROUND: Patient travel history can be crucial in evaluating evolving infectious disease events. Such information can be challenging to acquire in electronic health records, as it is often available only in unstructured text. OBJECTIVE: This study aims to assess the feasibility of annotating and automatically extracting travel history mentions from unstructured clinical documents in the Department of Veterans Affairs across disparate health care facilities and among millions of patients. Information about travel exposure augments existing surveillance applications for increased preparedness in responding quickly to public health threats. METHODS: Clinical documents related to arboviral disease were annotated following selection using a semiautomated bootstrapping process. Using annotated instances as training data, models were developed to extract from unstructured clinical text any mention of affirmed travel locations outside of the continental United States. Automated text processing models were evaluated, involving machine learning and neural language models for extraction accuracy. RESULTS: Among 4584 annotated instances, 2659 (58%) contained an affirmed mention of travel history, while 347 (7.6%) were negated. Interannotator agreement resulted in a document-level Cohen kappa of 0.776. Automated text processing accuracy (F1 85.6, 95% CI 82.5-87.9) and computational burden were acceptable such that the system can provide a rapid screen for public health events. CONCLUSIONS: Automated extraction of patient travel history from clinical documents is feasible for enhanced passive surveillance public health systems. Without such a system, it would usually be necessary to manually review charts to identify recent travel or lack of travel, use an electronic health record that enforces travel history documentation, or ignore this potential source of information altogether. The development of this tool was initially motivated by emergent arboviral diseases. More recently, this system was used in the early phases of response to COVID-19 in the United States, although its utility was limited to a relatively brief window due to the rapid domestic spread of the virus. Such systems may aid future efforts to prevent and contain the spread of infectious diseases.


Asunto(s)
Enfermedades Transmisibles Emergentes/diagnóstico , Registros Electrónicos de Salud , Almacenamiento y Recuperación de la Información/métodos , Vigilancia en Salud Pública/métodos , Viaje/estadística & datos numéricos , Algoritmos , Enfermedades Transmisibles Emergentes/epidemiología , Estudios de Factibilidad , Femenino , Humanos , Aprendizaje Automático , Masculino , Persona de Mediana Edad , Procesamiento de Lenguaje Natural , Reproducibilidad de los Resultados , Estados Unidos/epidemiología
3.
J Public Health Manag Pract ; 27(3): 310-317, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33729189

RESUMEN

INTRODUCTION: COVID-19 represents an unprecedented challenge to policy makers as well as those entrusted with capturing, monitoring, and analyzing COVID-19 data. Effective public policy is data-informed policy. This requires a liaison between public health scientists and public officials. OBJECTIVE: This article details the experience, challenges, and lessons learned advising public officials in a large metropolitan area from March to October 2020. METHODS: To effectively do this, an R Markdown report was created to iteratively monitor the number of COVID-19 tests performed, positive tests obtained, COVID-19 hospitalization census, intensive care unit census, the number of patients with COVID-19 on ventilators, and the number of deaths due to COVID-19. RESULTS: These reports were presented and discussed at meetings with policy makers to further comprehension. DISCUSSION: To facilitate the fullest understanding by both the general public and policy makers alike, we advocate for greater centralization of public health surveillance data, objective operational definitions of metrics, and greater interagency communication to best guide and inform policy makers. Through consistent data reporting methods, parsimonious and consistent analytic methods, a clear line of communication with policy makers, transparency, and the ability to navigate unforeseen externalities such as "data dumps" and reporting delays, scientists can use information to best support policy makers in times of crises.


Asunto(s)
Personal Administrativo/psicología , Política de Salud , Difusión de la Información/métodos , Pandemias/prevención & control , Vigilancia en Salud Pública/métodos , Salud Pública/métodos , Adulto , Comunicación , Femenino , Florida/epidemiología , Humanos , Colaboración Intersectorial , Masculino , Persona de Mediana Edad
4.
Infect Dis Poverty ; 10(1): 21, 2021 Mar 01.
Artículo en Inglés | MEDLINE | ID: mdl-33648606

RESUMEN

BACKGROUND: Considering the widespread of coronavirus disease 2019 (COVID-19) pandemic in the world, it is important to understand the spatiotemporal development of the pandemic. In this study, we aimed to visualize time-associated alterations of COVID-19 in the context of continents and countries. METHODS: Using COVID-19 case and death data from February to December 2020 offered by Johns Hopkins University, we generated time-associated balloon charts with multiple epidemiological indicators including crude case fatality rate (CFR), morbidity, mortality and the total number of cases, to compare the progression of the pandemic within a specific period across regions and countries, integrating seven related dimensions together. The area chart is used to supplement the display of the balloon chart in daily new COVID-19 case changes in UN geographic regions over time. Javascript and Vega-Lite were chosen for programming and mapping COVID-19 data in browsers for visualization. RESULTS: From February 1st to December 20th 2020, the COVID-19 pandemic spread across UN subregions in the chronological order. It was first reported in East Asia, and then became noticeable in Europe (South, West and North), North America, East Europe and West Asia, Central and South America, Southern Africa, Caribbean, South Asia, North Africa, Southeast Asia and Oceania, causing several waves of epidemics in different regions. Since October, the balloons of Europe, North America and West Asia have been rising rapidly, reaching a dramatically high morbidity level ranging from 200 to 500/10 000 by December, suggesting an emerging winter wave of COVID-19 which was much bigger than the previous ones. By late December 2020, some European and American countries displayed a leading mortality as high as or over 100/100 000, represented by Belgium, Czechia, Spain, France, Italy, UK, Hungary, Bulgaria, Peru, USA, Argentina, Brazil, Chile and Mexico. The mortality of Iran was the highest in Asia (over 60/100 000), and that of South Africa topped in Africa (40/100 000). In the last 15 days, the CFRs of most countries were at low levels of less than 5%, while Mexico had exceptional high CFR close to 10%. CONCLUSIONS: We creatively used visualization integrating 7-dimensional epidemiologic and spatiotemporal indicators to assess the progression of COVID-19 pandemic in terms of transmissibility and severity. Such methodology allows public health workers and policy makers to understand the epidemics comparatively and flexibly.


Asunto(s)
/epidemiología , Vigilancia en Salud Pública/métodos , Gráficos por Computador , Salud Global/estadística & datos numéricos , Humanos , Pandemias/estadística & datos numéricos , Análisis Espacio-Temporal
7.
J Infect Public Health ; 14(3): 293-305, 2021 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-33610938

RESUMEN

BACKGROUND: Ebola virus (EBOV); a public health emergency of international concern,is known to pose threat of global outbreaks. EBOV has spread in African continent and due to unchecked international travel, importation of cases has been reported in different countries. In this alarming scenario, developing countries need to evaluate and upgrade their preparedness plan to contain the spread of EBOV. The present review lays down the updated preparedness plan for developing countries to contain future EBOV outbreaks. METHODS: The literature on EBOV outbreaks and preparedness strategies reported were searched on Pubmed and Google Scholar using the MeSH terms such as "Ebola virus disease, Epidemic, Outbreak, Imported case, Preparedness, Public health interventions" combined with Boolean operator (OR) for the period of 2011-2020. Additionally, World Health organization (WHO) and Centers for Disease Control & Prevention (CDC) websites were searched for the guidelines, reports, containment strategies, containment plan of countries, actions taken by countries and international partners, etc. RESULTS: The present review analyzed the EBOV outbreaks between 2011-2020 and containment strategies used by the affected countries. Based on the lessons learned from EBOV outbreaks and personal experience in infectious disease management, we have recommended a preparedness and response plan for EBOV containment in developing countries. CONCLUSION: Developing countries are particularly vulnerable to major outbreaks of EBOV due to increased international travel and unchecked transmission. The recommended preparedness plan will help developing counties to contain EBOV outbreaks in future.


Asunto(s)
Brotes de Enfermedades/prevención & control , Ebolavirus , Epidemias/prevención & control , Fiebre Hemorrágica Ebola/prevención & control , Vigilancia en Salud Pública/métodos , Defensa Civil , Trazado de Contacto , Países en Desarrollo , Fiebre Hemorrágica Ebola/epidemiología , Humanos , Pruebas en el Punto de Atención
8.
Public Health ; 192: 30-32, 2021 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-33611168

RESUMEN

OBJECTIVES: SARS-CoV-2 is a highly contagious virus that causes coronavirus disease 2019 (COVID-19) and can affect people of any age with potential for serious symptoms. Since the start of the COVID-19 pandemic, global infection rates have been on the rise with world leaders looking to slow and stop viral transmission. This study is looking at suburban cohabitation/familial infection to compare to similar studies from other countries. STUDY DESIGN: A retrospective review of medical records was collected using the Connecticut Electronic Disease Surveillance System. METHODS: A total of 406 cases who tested positive for SARS-COV-2 from February to June 2020 were reviewed from three towns located in Connecticut, USA. Cohabitation infection rates were identified using the home addresses of those with confirmed SARS-CoV-2 test results, with the first documented case being the index case, and additional home members being the secondary cases. RESULTS: Secondary transmission of SARS-CoV-2 developed in 126 of 406 household contacts (31%). Linear regression indicated positive relationship between cohabitation and age. CONCLUSIONS: The cohabitation infection attack rate of SARS-CoV-2 is significantly higher than previously reported. Age of household contacts and spousal relationship to the index case are risk factors for transmission of SARS-CoV-2 within a household.


Asunto(s)
/transmisión , Composición Familiar , Vigilancia en Salud Pública/métodos , /aislamiento & purificación , Adulto , Infecciones Comunitarias Adquiridas/transmisión , Trazado de Contacto/estadística & datos numéricos , Femenino , Humanos , Incidencia , Masculino , Persona de Mediana Edad , Pandemias , Estudios Retrospectivos , Factores de Riesgo , Estados Unidos/epidemiología
9.
BMC Public Health ; 21(1): 409, 2021 02 26.
Artículo en Inglés | MEDLINE | ID: mdl-33637080

RESUMEN

BACKGROUND: Simulation exercises can functionally validate World Health Organization (WHO) International Health Regulations (IHR 2005) core capacities. In 2018, the Vietnam Ministry of Health (MOH) conducted a full-scale exercise (FSX) in response to cases of severe viral pneumonia with subsequent laboratory confirmation for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) to evaluate the country's early warning and response capabilities for high-risk events. METHODS: An exercise planning team designed a complex fictitious scenario beginning with one case of severe viral pneumonia presenting at the hospital level and developed all the materials required for the exercise. Actors, controllers and evaluators were trained. In August 2018, a 3-day exercise was conducted in Quang Ninh province and Hanoi city, with participation of public health partners at the community, district, province, regional and national levels. Immediate debriefings and an after-action review were conducted after all exercise activities. Participants assessed overall exercise design, conduction and usefulness. RESULTS: FSX findings demonstrated that the event-based surveillance component of the MOH surveillance system worked optimally at different administrative levels. Detection and reporting of signals at the community and health facility levels were appropriate. Triage, verification and risk assessment were successfully implemented to identify a high-risk event and trigger timely response. The FSX identified infection control, coordination with internal and external response partners and process documentation as response challenges. Participants positively evaluated the exercise training and design. CONCLUSIONS: This exercise documents the value of exercising surveillance capabilities as part of a real-time operational scenario before facing a true emergency. The timing of this exercise and choice of disease scenario was particularly fortuitous given the subsequent appearance of COVID-19. As a result of this exercise and subsequent improvements made by the MOH, the country may have been better able to deal with the emergence of SARS-CoV-2 and contain it.


Asunto(s)
Brotes de Enfermedades/prevención & control , Vigilancia en Salud Pública/métodos , /epidemiología , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Humanos , Coronavirus del Síndrome Respiratorio de Oriente Medio/aislamiento & purificación , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Vietnam/epidemiología , Organización Mundial de la Salud
11.
Prev Vet Med ; 188: 105281, 2021 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-33530012

RESUMEN

Pigs (Sus scrofa) may be important surveillance targets for risk assessment and risk-based control planning against emerging zoonoses. Pigs have high contact rates with humans and other animals, transmit similar pathogens as humans including CoVs, and serve as reservoirs and intermediate hosts for notable human pandemics. Wild and domestic pigs both interface with humans and each other but have unique ecologies that demand different surveillance strategies. Three fundamental questions shape any surveillance program: where, when, and how can surveillance be conducted to optimize the surveillance objective? Using theory of mechanisms of zoonotic spillover and data on risk factors, we propose a framework for determining where surveillance might begin initially to maximize a detection in each host species at their interface. We illustrate the utility of the framework using data from the United States. We then discuss variables to consider in refining when and how to conduct surveillance. Recent advances in accounting for opportunistic sampling designs and in translating serology samples into infection times provide promising directions for extracting spatio-temporal estimates of disease risk from typical surveillance data. Such robust estimates of population-level disease risk allow surveillance plans to be updated in space and time based on new information (adaptive surveillance) thus optimizing allocation of surveillance resources to maximize the quality of risk assessment insight.


Asunto(s)
Enfermedades Transmisibles Emergentes/epidemiología , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/veterinaria , Vigilancia en Salud Pública/métodos , Enfermedades de los Porcinos/epidemiología , Enfermedades de los Porcinos/virología , Zoonosis/epidemiología , Animales , Animales Salvajes/virología , Coronavirus/aislamiento & purificación , Reservorios de Enfermedades/virología , Humanos , Sus scrofa/virología , Porcinos/virología , Zoonosis/transmisión
12.
JMIR Public Health Surveill ; 7(1): e25538, 2021 01 15.
Artículo en Inglés | MEDLINE | ID: mdl-33406053

RESUMEN

BACKGROUND: Nowcasting approaches enhance the utility of reportable disease data for trend monitoring by correcting for delays, but implementation details affect accuracy. OBJECTIVE: To support real-time COVID-19 situational awareness, the New York City Department of Health and Mental Hygiene used nowcasting to account for testing and reporting delays. We conducted an evaluation to determine which implementation details would yield the most accurate estimated case counts. METHODS: A time-correlated Bayesian approach called Nowcasting by Bayesian Smoothing (NobBS) was applied in real time to line lists of reportable disease surveillance data, accounting for the delay from diagnosis to reporting and the shape of the epidemic curve. We retrospectively evaluated nowcasting performance for confirmed case counts among residents diagnosed during the period from March to May 2020, a period when the median reporting delay was 2 days. RESULTS: Nowcasts with a 2-week moving window and a negative binomial distribution had lower mean absolute error, lower relative root mean square error, and higher 95% prediction interval coverage than nowcasts conducted with a 3-week moving window or with a Poisson distribution. Nowcasts conducted toward the end of the week outperformed nowcasts performed earlier in the week, given fewer patients diagnosed on weekends and lack of day-of-week adjustments. When estimating case counts for weekdays only, metrics were similar across days when the nowcasts were conducted, with Mondays having the lowest mean absolute error of 183 cases in the context of an average daily weekday case count of 2914. CONCLUSIONS: Nowcasting using NobBS can effectively support COVID-19 trend monitoring. Accounting for overdispersion, shortening the moving window, and suppressing diagnoses on weekends-when fewer patients submitted specimens for testing-improved the accuracy of estimated case counts. Nowcasting ensured that recent decreases in observed case counts were not overinterpreted as true declines and supported officials in anticipating the magnitude and timing of hospitalizations and deaths and allocating resources geographically.


Asunto(s)
/epidemiología , Vigilancia en Salud Pública/métodos , Teorema de Bayes , Humanos , Ciudad de Nueva York/epidemiología , Estudios Retrospectivos
13.
JMIR Public Health Surveill ; 7(2): e25651, 2021 02 25.
Artículo en Inglés | MEDLINE | ID: mdl-33513563

RESUMEN

BACKGROUND: During COVID-19, studies have reported the appearance of internet searches for disease symptoms before their validation by the World Health Organization. This suggested that monitoring of these searches with tools including Google Trends may help monitor the pandemic itself. In Europe and North America, dermatologists reported an unexpected outbreak of cutaneous acral lesions (eg, chilblain-like lesions) in April 2020. However, external factors such as public communications may also hinder the use of Google Trends as an infodemiology tool. OBJECTIVE: The study aimed to assess the impact of media announcements and lockdown enforcement on internet searches related to cutaneous acral lesions during the COVID-19 outbreak in 2020. METHODS: Two searches on Google Trends, including daily relative search volumes for (1) "toe" or "chilblains" and (2) "coronavirus," were performed from January 1 to May 16, 2020, with the United States, the United Kingdom, France, Italy, Spain, and Germany as the countries of choice. The ratio of interest over time in "chilblains" and "coronavirus" was plotted. To assess the impact of lockdown enforcement and media coverage on these internet searches, we performed an interrupted time-series analysis for each country. RESULTS: The ratio of interest over time in "chilblains" to "coronavirus" showed a constant upward trend. In France, Italy, and the United Kingdom, lockdown enforcement was associated with a significant slope change for "chilblain" searches with a variation coefficient of 1.06 (SE 0.42) (P=0.01), 1.04 (SE 0.28) (P<.01), and 1.21 (SE 0.44) (P=0.01), respectively. After media announcements, these ratios significantly increased in France, Spain, Italy, and the United States with variation coefficients of 18.95 (SE 5.77) (P=.001), 31.31 (SE 6.31) (P<.001), 14.57 (SE 6.33) (P=.02), and 11.24 (SE 4.93) (P=.02), respectively, followed by a significant downward trend in France (-1.82 [SE 0.45]), Spain (-1.10 [SE 0.38]), and Italy (-0.93 [SE 0.33]) (P<.001, P=0.004, and P<.001, respectively). The adjusted R2 values were 0.311, 0.351, 0.325, and 0.305 for France, Spain, Italy, and the United States, respectively, suggesting an average correlation between time and the search volume; however, this correlation was weak for Germany and the United Kingdom. CONCLUSIONS: To date, the association between chilblain-like lesions and COVID-19 remains controversial; however, our results indicate that Google queries of "chilblain" were highly influenced by media coverage and government policies, indicating that caution should be exercised when using Google Trends as a monitoring tool for emerging diseases.


Asunto(s)
/complicaciones , Internet , Medios de Comunicación de Masas/estadística & datos numéricos , Vigilancia en Salud Pública/métodos , Política Pública , Motor de Búsqueda/tendencias , Enfermedades de la Piel/virología , /epidemiología , Europa (Continente)/epidemiología , Humanos , Estados Unidos/epidemiología
14.
JMIR Public Health Surveill ; 7(2): e20335, 2021 02 15.
Artículo en Inglés | MEDLINE | ID: mdl-33481755

RESUMEN

BACKGROUND: In Japan, as a countermeasure against the COVID-19 outbreak, both the national and local governments issued voluntary restrictions against going out from residences at the end of March 2020 in preference to the lockdowns instituted in European and North American countries. The effect of such measures can be studied with mobility data, such as data which is generated by counting the number of requests made to Apple Maps for directions in select countries/regions, sub-regions, and cities. OBJECTIVE: We investigate the associations of mobility data provided by Apple Inc and an estimate an an effective reproduction number R(t). METHODS: We regressed R(t) on a polynomial function of daily Apple data, estimated using the whole period, and analyzed subperiods delimited by March 10, 2020. RESULTS: In the estimation results, R(t) was 1.72 when voluntary restrictions against going out ceased and mobility reverted to a normal level. However, the critical level of reducing R(t) to <1 was obtained at 89.3% of normal mobility. CONCLUSIONS: We demonstrated that Apple mobility data are useful for short-term prediction of R(t). The results indicate that the number of trips should decrease by 10% until herd immunity is achieved and that higher voluntary restrictions against going out might not be necessary for avoiding a re-emergence of the outbreak.


Asunto(s)
Número Básico de Reproducción , Teléfono Celular , Brotes de Enfermedades , Vigilancia en Salud Pública/métodos , Interpretación Estadística de Datos , Humanos , Japón/epidemiología , Reproducibilidad de los Resultados
15.
J Med Internet Res ; 23(2): e25799, 2021 02 03.
Artículo en Inglés | MEDLINE | ID: mdl-33475513

RESUMEN

BACKGROUND: SARS-CoV-2, the virus that caused the global COVID-19 pandemic, has severely impacted Central Asia; in spring 2020, high numbers of cases and deaths were reported in this region. The second wave of the COVID-19 pandemic is currently breaching the borders of Central Asia. Public health surveillance is necessary to inform policy and guide leaders; however, existing surveillance explains past transmissions while obscuring shifts in the pandemic, increases in infection rates, and the persistence of the transmission of COVID-19. OBJECTIVE: The goal of this study is to provide enhanced surveillance metrics for SARS-CoV-2 transmission that account for weekly shifts in the pandemic, including speed, acceleration, jerk, and persistence, to better understand the risk of explosive growth in each country and which countries are managing the pandemic successfully. METHODS: Using a longitudinal trend analysis study design, we extracted 60 days of COVID-19-related data from public health registries. We used an empirical difference equation to measure the daily number of cases in the Central Asia region as a function of the prior number of cases, level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: COVID-19 transmission rates were tracked for the weeks of September 30 to October 6 and October 7-13, 2020, in Central Asia. The region averaged 11,730 new cases per day for the first week and 14,514 for the second week. Infection rates increased across the region from 4.74 per 100,000 persons to 5.66. Russia and Turkey had the highest 7-day moving averages in the region, with 9836 and 1469, respectively, for the week of October 6 and 12,501 and 1603, respectively, for the week of October 13. Russia has the fourth highest speed in the region and continues to have positive acceleration, driving the negative trend for the entire region as the largest country by population. Armenia is experiencing explosive growth of COVID-19; its infection rate of 13.73 for the week of October 6 quickly jumped to 25.19, the highest in the region, the following week. The region overall is experiencing increases in its 7-day moving average of new cases, infection, rate, and speed, with continued positive acceleration and no sign of a reversal in sight. CONCLUSIONS: The rapidly evolving COVID-19 pandemic requires novel dynamic surveillance metrics in addition to static metrics to effectively analyze the pandemic trajectory and control spread. Policy makers need to know the magnitude of transmission rates, how quickly they are accelerating, and how previous cases are impacting current caseload due to a lag effect. These metrics applied to Central Asia suggest that the region is trending negatively, primarily due to minimal restrictions in Russia.


Asunto(s)
/epidemiología , /transmisión , Personal Administrativo , Armenia/epidemiología , Asia Central/epidemiología , Azerbaiyán/epidemiología , Benchmarking , Chipre/epidemiología , Dinamarca/epidemiología , Georgia (República)/epidemiología , Gibraltar/epidemiología , Humanos , Kosovo/epidemiología , Estudios Longitudinales , Pandemias/prevención & control , Salud Pública , Vigilancia en Salud Pública/métodos , Sistema de Registros , República de Macedonia del Norte/epidemiología , Federación de Rusia/epidemiología , Turquia/epidemiología
16.
BMC Infect Dis ; 21(1): 52, 2021 Jan 11.
Artículo en Inglés | MEDLINE | ID: mdl-33430793

RESUMEN

BACKGROUND: Workplace absenteeism increases significantly during influenza epidemics. Sick leave records may facilitate more timely detection of influenza outbreaks, as trends in increased sick leave may precede alerts issued by sentinel surveillance systems by days or weeks. Sick leave data have not been comprehensively evaluated in comparison to traditional surveillance methods. The aim of this paper is to study the performance and the feasibility of using a detection system based on sick leave data to detect influenza outbreaks. METHODS: Sick leave records were extracted from private French health insurance data, covering on average 209,932 companies per year across a wide range of sizes and sectors. We used linear regression to estimate the weekly number of new sick leave spells between 2016 and 2017 in 12 French regions, adjusting for trend, seasonality and worker leaves on historical data from 2010 to 2015. Outbreaks were detected using a 95%-prediction interval. This method was compared to results from the French Sentinelles network, a gold-standard primary care surveillance system currently in place. RESULTS: Using sick leave data, we detected 92% of reported influenza outbreaks between 2016 and 2017, on average 5.88 weeks prior to outbreak peaks. Compared to the existing Sentinelles model, our method had high sensitivity (89%) and positive predictive value (86%), and detected outbreaks on average 2.5 weeks earlier. CONCLUSION: Sick leave surveillance could be a sensitive, specific and timely tool for detection of influenza outbreaks.


Asunto(s)
Absentismo , Epidemias , Gripe Humana/epidemiología , Vigilancia en Salud Pública/métodos , Vigilancia de Guardia , Ausencia por Enfermedad , Francia/epidemiología , Humanos , Incidencia , Gripe Humana/virología , Seguro de Salud , Persona de Mediana Edad , Modelos Estadísticos , Estudios Retrospectivos , Sensibilidad y Especificidad , Lugar de Trabajo
17.
Lancet Public Health ; 6(1): e30-e38, 2021 01.
Artículo en Inglés | MEDLINE | ID: mdl-33308423

RESUMEN

BACKGROUND: Decisions about the continued need for control measures to contain the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on accurate and up-to-date information about the number of people testing positive for SARS-CoV-2 and risk factors for testing positive. Existing surveillance systems are generally not based on population samples and are not longitudinal in design. METHODS: Samples were collected from individuals aged 2 years and older living in private households in England that were randomly selected from address lists and previous Office for National Statistics surveys in repeated cross-sectional household surveys with additional serial sampling and longitudinal follow-up. Participants completed a questionnaire and did nose and throat self-swabs. The percentage of individuals testing positive for SARS-CoV-2 RNA was estimated over time by use of dynamic multilevel regression and poststratification, to account for potential residual non-representativeness. Potential changes in risk factors for testing positive over time were also assessed. The study is registered with the ISRCTN Registry, ISRCTN21086382. FINDINGS: Between April 26 and Nov 1, 2020, results were available from 1 191 170 samples from 280 327 individuals; 5231 samples were positive overall, from 3923 individuals. The percentage of people testing positive for SARS-CoV-2 changed substantially over time, with an initial decrease between April 26 and June 28, 2020, from 0·40% (95% credible interval 0·29-0·54) to 0·06% (0·04-0·07), followed by low levels during July and August, 2020, before substantial increases at the end of August, 2020, with percentages testing positive above 1% from the end of October, 2020. Having a patient-facing role and working outside your home were important risk factors for testing positive for SARS-CoV-2 at the end of the first wave (April 26 to June 28, 2020), but not in the second wave (from the end of August to Nov 1, 2020). Age (young adults, particularly those aged 17-24 years) was an important initial driver of increased positivity rates in the second wave. For example, the estimated percentage of individuals testing positive was more than six times higher in those aged 17-24 years than in those aged 70 years or older at the end of September, 2020. A substantial proportion of infections were in individuals not reporting symptoms around their positive test (45-68%, dependent on calendar time. INTERPRETATION: Important risk factors for testing positive for SARS-CoV-2 varied substantially between the part of the first wave that was captured by the study (April to June, 2020) and the first part of the second wave of increased positivity rates (end of August to Nov 1, 2020), and a substantial proportion of infections were in individuals not reporting symptoms, indicating that continued monitoring for SARS-CoV-2 in the community will be important for managing the COVID-19 pandemic moving forwards. FUNDING: Department of Health and Social Care.


Asunto(s)
/epidemiología , Vigilancia en Salud Pública/métodos , Características de la Residencia , Adolescente , Adulto , Anciano , Niño , Preescolar , Inglaterra/epidemiología , Femenino , Encuestas Epidemiológicas , Humanos , Masculino , Persona de Mediana Edad , Prevalencia , Adulto Joven
19.
Curr Opin Gastroenterol ; 37(1): 4-8, 2021 01.
Artículo en Inglés | MEDLINE | ID: mdl-33074996

RESUMEN

PURPOSE OF REVIEW: We discuss the potential role of the faecal chain in COVID-19 and highlight recent studies using waste water-based epidemiology (WBE) to track severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). RECENT FINDINGS: WBE has been suggested as an adjunct to improve disease surveillance and aid early detection of circulating disease. SARS-CoV-2, the aetiological agent of COVID-19, is an enveloped virus, and as such, typically not associated with the waste water environment, given high susceptibility to degradation in aqueous conditions. A review of the current literature supports the ability to detect of SARS-CoV-2 in waste water and suggests methods to predict community prevalence based on viral quantification. SUMMARY: The summary of current practices shows that while the isolation of SARS-CoV-2 is possible from waste water, issues remain regarding the efficacy of virial concentration and subsequent quantification and alignment with epidemiological data.


Asunto(s)
/epidemiología , Vigilancia en Salud Pública/métodos , Aguas del Alcantarillado/virología , /diagnóstico , Heces/virología , Salud Global , Humanos
20.
Am J Public Health ; 111(2): 269-276, 2021 02.
Artículo en Inglés | MEDLINE | ID: mdl-33351660

RESUMEN

Automated analysis of electronic health record (EHR) data is a complementary tool for public health surveillance. Analyzing and presenting these data, however, demands new methods of data communication optimized to the detail, flexibility, and timeliness of EHR data.RiskScape is an open-source, interactive, Web-based, user-friendly data aggregation and visualization platform for public health surveillance using EHR data. RiskScape displays near-real-time surveillance data and enables clinical practices and health departments to review, analyze, map, and trend aggregate data on chronic conditions and infectious diseases. Data presentations include heat maps of prevalence by zip code, time series with statistics for trends, and care cascades for conditions such as HIV and HCV. The platform's flexibility enables it to be modified to incorporate new conditions quickly-such as COVID-19.The Massachusetts Department of Public Health (MDPH) uses RiskScape to monitor conditions of interest using data that are updated monthly from clinical practice groups that cover approximately 20% of the state population. RiskScape serves an essential role in demonstrating need and burden for MDPH's applications for funding, particularly through the identification of inequitably burdened populations.


Asunto(s)
/epidemiología , Registros Electrónicos de Salud/estadística & datos numéricos , Informática en Salud Pública/instrumentación , Vigilancia en Salud Pública/métodos , Humanos , Massachusetts
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