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1.
BMC Fam Pract ; 22(1): 66, 2021 04 08.
Artículo en Inglés | MEDLINE | ID: mdl-33832436

RESUMEN

BACKGROUND: To estimate the prevalence of symptoms and signs related to a COVID-19 case series confirmed by polymerase chain reaction (PCR) for SARS-CoV-2. Risk factors and the associated use of health services will also be analysed. METHODS: Observational, descriptive, retrospective case series study. The study was performed at two Primary Care Health Centres located in Madrid, Spain. The subjects studied were all PCR SARS-CoV-2 confirmed cases older than 18 years, diagnosed from the beginning of the community transmission (March 13) until April 15, 2020. We collected sociodemographic, clinical, health service utilization and clinical course variables during the following months. All data was gathered by their own attending physician, and electronic medical records were reviewed individually. STATISTICAL ANALYSIS: A descriptive analysis was carried out and a Poisson regression model was adjusted to study associated factors to Health Services use. RESULTS: Out of the 499 patients studied from two health centres, 55.1% were women and mean age was 58.2 (17.3). 25.1% were healthcare professionals. The most frequent symptoms recorded related to COVID-19 were cough (77.9%; CI 95% 46.5-93.4), fever (77.7%; CI95% 46.5-93.4) and dyspnoea (54.1%, CI95% 46.6-61.4). 60.7% were admitted to hospital. 64.5% first established contact with their primary care provider before going to the hospital, with a mean number of 11.4 Healthcare Providers Encounters with primary care during all the follow-up period. The number of visit-encounters with primary care was associated with being male [IRR 1.072 (1.013, 1.134)], disease severity {from mild respiratory infection [IRR 1.404 (1.095, 1.801)], up to bilateral pneumonia [IRR 1.852 (1.437,2.386)]}, and the need of a work leave [IRR 1.326 (1.244, 1.413]. CONCLUSION: Symptoms and risk factors in our case series are similar to those in other studies. There was a high number of patients with atypical unilateral or bilateral pneumonia. Care for COVID has required a high use of healthcare resources such as clinical encounters and work leaves.


Asunto(s)
Aceptación de la Atención de Salud/estadística & datos numéricos , Neumonía Viral , Atención Primaria de Salud , Evaluación de Síntomas , /diagnóstico , /fisiopatología , Demografía , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Neumonía Viral/diagnóstico , Neumonía Viral/epidemiología , Neumonía Viral/etiología , Atención Primaria de Salud/métodos , Atención Primaria de Salud/estadística & datos numéricos , Factores de Riesgo , Índice de Severidad de la Enfermedad , Factores Socioeconómicos , España/epidemiología , Evaluación de Síntomas/métodos , Evaluación de Síntomas/estadística & datos numéricos
2.
J Glob Health ; 11: 10002, 2021 Apr 03.
Artículo en Inglés | MEDLINE | ID: mdl-33828849

RESUMEN

Background: This rapid evidence review identifies and integrates evidence from epidemiology, microbiology and fluid dynamics on the transmission of SARS-CoV-2 in indoor environments. Methods: Searches were conducted in May 2020 in PubMed, medRxiv, arXiv, Scopus, WHO COVID-19 database, Compendex & Inspec. We included studies reporting data on any indoor setting except schools, any indoor activities and any potential means of transmission. Articles were screened by a single reviewer, with rejections assessed by a second reviewer. We used Joanna Briggs Institute and Critical Appraisal Skills Programme tools for evaluating epidemiological studies and developed bespoke tools for the evaluation of study types not covered by these instruments. Data extraction and quality assessment were conducted by a single reviewer. We conducted a meta-analysis of secondary attack rates in household transmission. Otherwise, data were synthesised narratively. Results: We identified 1573 unique articles. After screening and quality assessment, fifty-eight articles were retained for analysis. Experimental evidence from fluid mechanics and microbiological studies demonstrates that aerosolised transmission is theoretically possible; however, we found no conclusive epidemiological evidence of this occurring. The evidence suggests that ventilation systems have the potential to decrease virus transmission near the source through dilution but to increase transmission further away from the source through dispersal. We found no evidence for faecal-oral transmission. Laboratory studies suggest that the virus survives for longer on smooth surfaces and at lower temperatures. Environmental sampling studies have recovered small amounts of viral RNA from a wide range of frequently touched objects and surfaces; however, epidemiological studies are inconclusive on the extent of fomite transmission. We found many examples of transmission in settings characterised by close and prolonged indoor contact. We estimate a pooled secondary attack rate within households of 11% (95% confidence interval (CI) = 9, 13). There were insufficient data to evaluate the transmission risks associated with specific activities. Workplace challenges related to poverty warrant further investigation as potential risk factors for workplace transmission. Fluid mechanics evidence on the physical properties of droplets generated by coughing, speaking and breathing reinforce the importance of maintaining 2 m social distance to reduce droplet transmission. Conclusions: This review provides a snap-shot of evidence on the transmission of SARS-CoV-2 in indoor environments from the early months of the pandemic. The overall quality of the evidence was low. As the quality and quantity of available evidence grows, it will be possible to reach firmer conclusions on the risk factors for and mechanisms of indoor transmission.


Asunto(s)
Contaminación del Aire Interior/análisis , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Ambiente Controlado , Monitoreo del Ambiente/estadística & datos numéricos , Contaminación del Aire Interior/prevención & control , Transmisión de Enfermedad Infecciosa/prevención & control , Microbiología Ambiental , Humanos
3.
Phys Rev Lett ; 126(11): 118301, 2021 Mar 19.
Artículo en Inglés | MEDLINE | ID: mdl-33798363

RESUMEN

Although COVID-19 has caused severe suffering globally, the efficacy of nonpharmaceutical interventions has been greater than typical models have predicted. Meanwhile, evidence is mounting that the pandemic is characterized by superspreading. Capturing this phenomenon theoretically requires modeling at the scale of individuals. Using a mathematical model, we show that superspreading drastically enhances mitigations which reduce the overall personal contact number and that social clustering increases this effect.


Asunto(s)
/epidemiología , Modelos Estadísticos , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Control de Infecciones/métodos , Control de Infecciones/estadística & datos numéricos , Pandemias , Red Social
4.
Nat Commun ; 12(1): 2429, 2021 04 23.
Artículo en Inglés | MEDLINE | ID: mdl-33893279

RESUMEN

We study the spatio-temporal spread of SARS-CoV-2 in Santiago de Chile using anonymized mobile phone data from 1.4 million users, 22% of the whole population in the area, characterizing the effects of non-pharmaceutical interventions (NPIs) on the epidemic dynamics. We integrate these data into a mechanistic epidemic model calibrated on surveillance data. As of August 1, 2020, we estimate a detection rate of 102 cases per 1000 infections (90% CI: [95-112 per 1000]). We show that the introduction of a full lockdown on May 15, 2020, while causing a modest additional decrease in mobility and contacts with respect to previous NPIs, was decisive in bringing the epidemic under control, highlighting the importance of a timely governmental response to COVID-19 outbreaks. We find that the impact of NPIs on individuals' mobility correlates with the Human Development Index of comunas in the city. Indeed, more developed and wealthier areas became more isolated after government interventions and experienced a significantly lower burden of the pandemic. The heterogeneity of COVID-19 impact raises important issues in the implementation of NPIs and highlights the challenges that communities affected by systemic health and social inequalities face adapting their behaviors during an epidemic.


Asunto(s)
/prevención & control , Control de Enfermedades Transmisibles/métodos , Factores Socioeconómicos , Algoritmos , /virología , Chile/epidemiología , Control de Enfermedades Transmisibles/estadística & datos numéricos , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Incidencia , Modelos Teóricos , Pandemias , Factores de Tiempo
5.
PLoS One ; 16(4): e0250110, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33852642

RESUMEN

BACKGROUND: Prediction of the dynamics of new SARS-CoV-2 infections during the current COVID-19 pandemic is critical for public health planning of efficient health care allocation and monitoring the effects of policy interventions. We describe a new approach that forecasts the number of incident cases in the near future given past occurrences using only a small number of assumptions. METHODS: Our approach to forecasting future COVID-19 cases involves 1) modeling the observed incidence cases using a Poisson distribution for the daily incidence number, and a gamma distribution for the series interval; 2) estimating the effective reproduction number assuming its value stays constant during a short time interval; and 3) drawing future incidence cases from their posterior distributions, assuming that the current transmission rate will stay the same, or change by a certain degree. RESULTS: We apply our method to predicting the number of new COVID-19 cases in a single state in the U.S. and for a subset of counties within the state to demonstrate the utility of this method at varying scales of prediction. Our method produces reasonably accurate results when the effective reproduction number is distributed similarly in the future as in the past. Large deviations from the predicted results can imply that a change in policy or some other factors have occurred that have dramatically altered the disease transmission over time. CONCLUSION: We presented a modelling approach that we believe can be easily adopted by others, and immediately useful for local or state planning.


Asunto(s)
/epidemiología , Número Básico de Reproducción , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Predicción , Humanos , Incidencia , Modelos Estadísticos , Pandemias , Salud Pública , Estados Unidos/epidemiología
6.
JAMA Netw Open ; 4(4): e217097, 2021 04 01.
Artículo en Inglés | MEDLINE | ID: mdl-33890990

RESUMEN

Importance: A significant proportion of COVID-19 transmission occurs silently during the presymptomatic and asymptomatic stages of infection. Children, although important drivers of silent transmission, are not included in the current COVID-19 vaccination campaigns. Objective: To estimate the benefits of identifying silent infections among children as a proxy for their vaccination. Design, Setting, and Participants: This study used an age-structured disease transmission model, parameterized with census data and estimates from published literature, to simulate the estimated synergistic effect of interventions in reducing attack rates during the course of 1 year among a synthetic population representative of the US demographic composition. The population included 6 age groups of 0 to 4, 5 to 10, 11 to 18, 19 to 49, 50 to 64, and 65 years or older based on US census data. Data were analyzed from December 12, 2020, to February 26, 2021. Exposures: In addition to the isolation of symptomatic cases within 24 hours of symptom onset, vaccination of adults was implemented to reach a 40% to 60% coverage during 1 year with an efficacy of 95% against symptomatic and severe COVID-19. Main Outcomes and Measures: The combinations of proportion and speed for detecting silent infections among children that would suppress future attack rates to less than 5%. Results: In the base-case scenarios with an effective reproduction number Re = 1.2, a targeted approach that identifies 11% of silent infections among children within 2 days and 14% within 3 days after infection would bring attack rates to less than 5% with 40% vaccination coverage of adults. If silent infections among children remained undetected, achieving the same attack rates would require an unrealistically high vaccination coverage (≥81%) of this age group, in addition to 40% vaccination coverage of adults. The estimated effect of identifying silent infections was robust in sensitivity analyses with respect to vaccine efficacy against infection and reduced susceptibility of children to infection. Conclusions and Relevance: In this simulation modeling study of a synthetic US population, in the absence of vaccine availability for children, a targeted approach to rapidly identify silent COVID-19 infections in this age group was estimated to significantly mitigate disease burden. These findings suggest that without measures to interrupt transmission chains from silent infections, vaccination of adults is unlikely to contain the outbreaks in the near term.


Asunto(s)
Infecciones Asintomáticas/epidemiología , Número Básico de Reproducción/estadística & datos numéricos , Transmisión de Enfermedad Infecciosa , Cobertura de Vacunación/estadística & datos numéricos , Vacunación , Adulto , Anciano , /prevención & control , /provisión & distribución , Niño , Simulación por Computador , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Femenino , Humanos , Recién Nacido , Masculino , Estados Unidos/epidemiología , Vacunación/métodos , Vacunación/normas
7.
JAMA Netw Open ; 4(3): e211283, 2021 03 01.
Artículo en Inglés | MEDLINE | ID: mdl-33688967

RESUMEN

Importance: Risks for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care personnel (HCP) are unclear. Objective: To evaluate the risk factors associated with SARS-CoV-2 seropositivity among HCP with the a priori hypothesis that community exposure but not health care exposure was associated with seropositivity. Design, Setting, and Participants: This cross-sectional study was conducted among volunteer HCP at 4 large health care systems in 3 US states. Sites shared deidentified data sets, including previously collected serology results, questionnaire results on community and workplace exposures at the time of serology, and 3-digit residential zip code prefix of HCP. Site-specific responses were mapped to a common metadata set. Residential weekly coronavirus disease 2019 (COVID-19) cumulative incidence was calculated from state-based COVID-19 case and census data. Exposures: Model variables included demographic (age, race, sex, ethnicity), community (known COVID-19 contact, COVID-19 cumulative incidence by 3-digit zip code prefix), and health care (workplace, job role, COVID-19 patient contact) factors. Main Outcome and Measures: The main outcome was SARS-CoV-2 seropositivity. Risk factors for seropositivity were estimated using a mixed-effects logistic regression model with a random intercept to account for clustering by site. Results: Among 24 749 HCP, most were younger than 50 years (17 233 [69.6%]), were women (19 361 [78.2%]), were White individuals (15 157 [61.2%]), and reported workplace contact with patients with COVID-19 (12 413 [50.2%]). Many HCP worked in the inpatient setting (8893 [35.9%]) and were nurses (7830 [31.6%]). Cumulative incidence of COVID-19 per 10 000 in the community up to 1 week prior to serology testing ranged from 8.2 to 275.6; 20 072 HCP (81.1%) reported no COVID-19 contact in the community. Seropositivity was 4.4% (95% CI, 4.1%-4.6%; 1080 HCP) overall. In multivariable analysis, community COVID-19 contact and community COVID-19 cumulative incidence were associated with seropositivity (community contact: adjusted odds ratio [aOR], 3.5; 95% CI, 2.9-4.1; community cumulative incidence: aOR, 1.8; 95% CI, 1.3-2.6). No assessed workplace factors were associated with seropositivity, including nurse job role (aOR, 1.1; 95% CI, 0.9-1.3), working in the emergency department (aOR, 1.0; 95% CI, 0.8-1.3), or workplace contact with patients with COVID-19 (aOR, 1.1; 95% CI, 0.9-1.3). Conclusions and Relevance: In this cross-sectional study of US HCP in 3 states, community exposures were associated with seropositivity to SARS-CoV-2, but workplace factors, including workplace role, environment, or contact with patients with known COVID-19, were not. These findings provide reassurance that current infection prevention practices in diverse health care settings are effective in preventing transmission of SARS-CoV-2 from patients to HCP.


Asunto(s)
/epidemiología , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Personal de Salud/estadística & datos numéricos , Exposición Profesional/estadística & datos numéricos , Adulto , Estudios Transversales , Femenino , Georgia/epidemiología , Humanos , Illinois/epidemiología , Masculino , Maryland/epidemiología , Persona de Mediana Edad , Características de la Residencia , Factores de Riesgo , Estudios Seroepidemiológicos , Estados Unidos/epidemiología
8.
Eur J Clin Invest ; 51(5): e13554, 2021 May.
Artículo en Inglés | MEDLINE | ID: mdl-33768536

RESUMEN

BACKGROUND: Estimates of community spread and infection fatality rate (IFR) of COVID-19 have varied across studies. Efforts to synthesize the evidence reach seemingly discrepant conclusions. METHODS: Systematic evaluations of seroprevalence studies that had no restrictions based on country and which estimated either total number of people infected and/or aggregate IFRs were identified. Information was extracted and compared on eligibility criteria, searches, amount of evidence included, corrections/adjustments of seroprevalence and death counts, quantitative syntheses and handling of heterogeneity, main estimates and global representativeness. RESULTS: Six systematic evaluations were eligible. Each combined data from 10 to 338 studies (9-50 countries), because of different eligibility criteria. Two evaluations had some overt flaws in data, violations of stated eligibility criteria and biased eligibility criteria (eg excluding studies with few deaths) that consistently inflated IFR estimates. Perusal of quantitative synthesis methods also exhibited several challenges and biases. Global representativeness was low with 78%-100% of the evidence coming from Europe or the Americas; the two most problematic evaluations considered only one study from other continents. Allowing for these caveats, four evaluations largely agreed in their main final estimates for global spread of the pandemic and the other two evaluations would also agree after correcting overt flaws and biases. CONCLUSIONS: All systematic evaluations of seroprevalence data converge that SARS-CoV-2 infection is widely spread globally. Acknowledging residual uncertainties, the available evidence suggests average global IFR of ~0.15% and ~1.5-2.0 billion infections by February 2021 with substantial differences in IFR and in infection spread across continents, countries and locations.


Asunto(s)
/epidemiología , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , /mortalidad , Humanos , Internacionalidad , Mortalidad , Estudios Seroepidemiológicos , Revisiones Sistemáticas como Asunto
9.
BMC Infect Dis ; 21(1): 242, 2021 Mar 05.
Artículo en Inglés | MEDLINE | ID: mdl-33673819

RESUMEN

BACKGROUND: Previous studies have indicated that the risk of infectious disease spread is greatest in locations where a population has massive and convenient access to the epicenter of an outbreak. However, the spatiotemporal variations and risk determinants of COVID-19 in typical labor export regions of China remain unclear. Understanding the geographical distribution of the disease and the socio-economic factors affecting its transmission is critical for disease prevention and control. METHODS: A total of 2152 COVID-19 cases were reported from January 21 to February 24, 2020 across the 34 cities in Henan and Anhui. A Bayesian spatiotemporal hierarchy model was used to detect the spatiotemporal variations of the risk posed by COVID-19, and the GeoDetector q statistic was used to evaluate the determinant power of the potential influence factors. RESULTS: The risk posed by COVID-19 showed geographical spatiotemporal heterogeneity. Temporally, there was an outbreak period and control period. Spatially, there were high-risk regions and low-risk regions. The high-risk regions were mainly in the southwest areas adjacent to Hubei and cities that served as economic and traffic hubs, while the low-risk regions were mainly in western Henan and eastern Anhui, far away from the epicenter. The accessibility, local economic conditions, and medical infrastructure of Wuhan in Hubei province all played an important role in the spatiotemporal heterogeneity of COVID-19 transmission. The results indicated that the q statistics of the per capita GDP and the proportion of primary industry GDP were 0.47 and 0.47, respectively. The q statistic of the population flow from Wuhan was 0.33. In particular, the results showed that the q statistics for the interaction effects between population density and urbanization, population flow from Wuhan, per capita GDP, and the number of doctors were all greater than 0.8. CONCLUSIONS: COVID-19 showed significant spatiotemporal heterogeneity in the labor export regions of China. The high-risk regions were mainly located in areas adjacent to the epicenter as well as in big cities that served as traffic hubs. Population access to the epicenter, as well as local economic and medical conditions, played an important role in the interactive effects of the disease transmission.


Asunto(s)
Control de Enfermedades Transmisibles/organización & administración , Transmisión de Enfermedad Infecciosa , Medición de Riesgo , /epidemiología , /transmisión , China/epidemiología , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Medición de Riesgo/métodos , Medición de Riesgo/estadística & datos numéricos , Factores de Riesgo , Determinantes Sociales de la Salud , Factores Socioeconómicos , Análisis Espacio-Temporal , Migrantes , Urbanización
11.
PLoS One ; 16(3): e0245519, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33657128

RESUMEN

Since the onset of the COVID-19 pandemic many researchers and health advisory institutions have focused on virus spread prediction through epidemiological models. Such models rely on virus- and disease characteristics of which most are uncertain or even unknown for SARS-CoV-2. This study addresses the validity of various assumptions using an epidemiological simulation model. The contributions of this work are twofold. First, we show that multiple scenarios all lead to realistic numbers of deaths and ICU admissions, two observable and verifiable metrics. Second, we test the sensitivity of estimates for the number of infected and immune individuals, and show that these vary strongly between scenarios. Note that the amount of variation measured in this study is merely a lower bound: epidemiological modeling contains uncertainty on more parameters than the four in this study, and including those as well would lead to an even larger set of possible scenarios. As the level of infection and immunity among the population are particularly important for policy makers, further research on virus and disease progression characteristics is essential. Until that time, epidemiological modeling studies cannot give conclusive results and should come with a careful analysis of several scenarios on virus- and disease characteristics.


Asunto(s)
/epidemiología , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Predicción/métodos , /transmisión , Humanos , Modelos Estadísticos , Pandemias , /patogenicidad
12.
PLoS One ; 16(3): e0247995, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33657164

RESUMEN

BACKGROUND: Primary care is the major point of access in most health systems in developed countries and therefore for the detection of coronavirus disease 2019 (COVID-19) cases. The quality of its IT systems, together with access to the results of mass screening with Polymerase chain reaction (PCR) tests, makes it possible to analyse the impact of various concurrent factors on the likelihood of contracting the disease. METHODS AND FINDINGS: Through data mining techniques with the sociodemographic and clinical variables recorded in patient's medical histories, a decision tree-based logistic regression model has been proposed which analyses the significance of demographic and clinical variables in the probability of having a positive PCR in a sample of 7,314 individuals treated in the Primary Care service of the public health system of Catalonia. The statistical approach to decision tree modelling allows 66.2% of diagnoses of infection by COVID-19 to be classified with a sensitivity of 64.3% and a specificity of 62.5%, with prior contact with a positive case being the primary predictor variable. CONCLUSIONS: The use of a classification tree model may be useful in screening for COVID-19 infection. Contact detection is the most reliable variable for detecting Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases. The model would support that, beyond a symptomatic diagnosis, the best way to detect cases would be to engage in contact tracing.


Asunto(s)
/diagnóstico , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Adulto , Anciano , Estudios de Cohortes , Trazado de Contacto , Minería de Datos/métodos , Árboles de Decisión , Femenino , Humanos , Masculino , Tamizaje Masivo/métodos , Persona de Mediana Edad , Probabilidad , Estudios Retrospectivos , Sensibilidad y Especificidad
13.
Sci Rep ; 11(1): 3601, 2021 02 11.
Artículo en Inglés | MEDLINE | ID: mdl-33574387

RESUMEN

In times of outbreaks, an essential requirement for better monitoring is the evaluation of the number of undiagnosed infected individuals. An accurate estimate of this fraction is crucial for the assessment of the situation and the establishment of protective measures. In most current studies using epidemics models, the total number of infected is either approximated by the number of diagnosed individuals or is dependent on the model parameters and assumptions, which are often debated. We here study the relationship between the fraction of diagnosed infected out of all infected, and the fraction of infected with known contaminator out of all diagnosed infected. We show that those two are approximately the same in exponential models and across most models currently used in the study of epidemics, independently of the model parameters. As an application, we compute an estimate of the effective number of infected by the SARS-CoV-2 virus in various countries.


Asunto(s)
/epidemiología , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Enfermedades no Diagnosticadas/epidemiología , /diagnóstico , Transmisión de Enfermedad Infecciosa/clasificación , Humanos , Modelos Estadísticos
15.
Medicine (Baltimore) ; 100(5): e23925, 2021 Feb 05.
Artículo en Inglés | MEDLINE | ID: mdl-33592845

RESUMEN

ABSTRACT: The World Health Organization (WHO) classified the spread of COVID-19 (Coronavirus Disease 2019) as a global pandemic in March. Scholars predict that the pandemic will continue into the coming winter and will become a seasonal epidemic in the following year. Therefore, the identification of effective control measures becomes extremely important. Although many reports have been published since the COVID-19 outbreak, no studies have identified the relative effectiveness of a combination of control measures implemented in Wuhan and other areas in China. To this end, a retrospective analysis by the collection and modeling of an unprecedented number of epidemiology records in China of the early stage of the outbreaks can be valuable.In this study, we developed a new dynamic model to describe the spread of COVID-19 and to quantify the effectiveness of control measures. The transmission rate, daily close contacts, and the average time from onset to isolation were identified as crucial factors in viral spreading. Moreover, the capacity of a local health-care system is identified as a threshold to control an outbreak in its early stage. We took these factors as controlling parameters in our model. The parameters are estimated based on epidemiological reports from national and local Center for Disease Control (CDCs).A retrospective simulation showed the effectiveness of combinations of 4 major control measures implemented in Wuhan: hospital isolation, social distancing, self-protection by wearing masks, and extensive medical testing. Further analysis indicated critical intervention conditions and times required to control an outbreak in the early stage. Our simulations showed that South Korea has kept the spread of COVID-19 at a low level through extensive medical testing. Furthermore, a predictive simulation for Italy indicated that Italy would contain the outbreak in late May under strict social distancing.In our general analysis, no single measure could contain a COVID-19 outbreak once a health-care system is overloaded. Extensive medical testing could keep viral spreading at a low level. Wearing masks functions as favorably as social distancing but with much lower socioeconomic costs.


Asunto(s)
Control de Enfermedades Transmisibles , Hospitalización/estadística & datos numéricos , Evaluación de Resultado en la Atención de Salud/métodos , /aislamiento & purificación , /economía , /prevención & control , China/epidemiología , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/organización & administración , Control de Enfermedades Transmisibles/normas , Trazado de Contacto/estadística & datos numéricos , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Modelos Teóricos , Mortalidad , Análisis de Sistemas , Tiempo de Tratamiento/estadística & datos numéricos
16.
Epidemiol Infect ; 149: e72, 2021 02 16.
Artículo en Inglés | MEDLINE | ID: mdl-33592163

RESUMEN

Due to the high incidence of COVID-19 case numbers internationally, the World Health Organization (WHO) declared a Public Health Emergency of global relevance, advising countries to follow protocols to combat pandemic advance through actions that can reduce spread and consequently avoid a collapse in the local health system. This study aimed to evaluate the dynamics of the evolution of new community cases, and mortality records of COVID-19 in the State of Pará, which has a subtropical climate with temperatures between 20 and 35 °C, after the implementation of social distancing by quarantine and adoption of lockdown. The follow-up was carried out by the daily data from the technical bulletins provided by the State of Pará Public Health Secretary (SESPA). On 18 March 2020, Pará notified the first case of COVID-19. After 7 weeks, the number of confirmed cases reached 4756 with 375 deaths. The results show it took 49 days for 81% of the 144 states municipalities, distributed over an area of approximately 1 248 000 km2 to register COVID-19 cases. Temperature variations between 24.5 and 33.1 °C did not promote the decline in the new infections curve. The association between social isolation, quarantine and lockdown as an action to contain the infection was effective in reducing the region's new cases registration of COVID-19 in the short-term. However, short periods of lockdown may have promoted the virus spread among peripheral municipalities of the capital, as well as to inland regions.


Asunto(s)
/epidemiología , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Adolescente , Adulto , Distribución por Edad , Anciano , Anciano de 80 o más Años , Brasil/epidemiología , /prevención & control , Niño , Preescolar , Comorbilidad , Diabetes Mellitus/epidemiología , Transmisión de Enfermedad Infecciosa/prevención & control , Femenino , Cardiopatías/epidemiología , Humanos , Lactante , Recién Nacido , Masculino , Persona de Mediana Edad , Cuarentena , Lluvia , Temperatura , Tiempo (Meteorología) , Adulto Joven
17.
PLoS One ; 16(2): e0247182, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33596247

RESUMEN

Since its discovery in the Hubei province of China, the global spread of the novel coronavirus SARS-CoV-2 has resulted in millions of COVID-19 cases and hundreds of thousands of deaths. The spread throughout Asia, Europe, and the Americas has presented one of the greatest infectious disease threats in recent history and has tested the capacity of global health infrastructures. Since no effective vaccine is available, isolation techniques to prevent infection such as home quarantine and social distancing while in public have remained the cornerstone of public health interventions. While government and health officials were charged with implementing stay-at-home strategies, many of which had little guidance as to the consequences of how quickly to begin them. Moreover, as the local epidemic curves have been flattened, the same officials must wrestle with when to ease or cease such restrictions as to not impose economic turmoil. To evaluate the effects of quarantine strategies during the initial epidemic, an agent based modeling framework was created to take into account local spread based on geographic and population data with a corresponding interactive desktop and web-based application. Using the state of Massachusetts in the United States of America, we have illustrated the consequences of implementing quarantines at different time points after the initial seeding of the state with COVID-19 cases. Furthermore, we suggest that this application can be adapted to other states, small countries, or regions within a country to provide decision makers with critical information necessary to best protect human health.


Asunto(s)
/epidemiología , Modelos Estadísticos , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Massachusetts/epidemiología , Pandemias , Salud Pública/métodos , Cuarentena/economía , Cuarentena/psicología , Procesos Estocásticos
20.
J Hosp Infect ; 110: 194-200, 2021 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-33549768

RESUMEN

BACKGROUND: Reducing COVID-19 transmission relies on controlling droplet and aerosol spread. Fluorescein staining reveals microscopic droplets. AIM: To compare the droplet spread in non-laminar and laminar air flow operating theatres. METHODS: A 'cough-generator' was fixed to a theatre trolley at 45°. Fluorescein-stained 'secretions' were projected on to a series of calibrated targets. These were photographed under UV light and 'source detection' software measured droplet splatter size and distance. FINDINGS: The smallest droplet detected was ∼120 µm and the largest ∼24,000 µm. An average of 25,862 spots was detected in the non-laminar theatre, compared with 11,430 in the laminar theatre (56% reduction). The laminar air flow mainly affected the smaller droplets (<1000 µm). The surface area covered with droplets was: 6% at 50 cm, 1% at 2 m, and 0.5% at 3 m in the non-laminar air flow; and 3%, 0.5%, and 0.2% in the laminar air flow, respectively. CONCLUSION: Accurate mapping of droplet spread in clinical environments is possible using fluorescein staining and image analysis. The laminar air flow affected the smaller droplets but had limited effect on larger droplets in our 'aerosol-generating procedure' cough model. Our results indicate that the laminar air flow theatre requires similar post-surgery cleaning to the non-laminar, and staff should consider full personal protective equipment for medium- and high-risk patients.


Asunto(s)
Aerosoles , Microbiología del Aire , /transmisión , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Ambiente Controlado , Quirófanos/estadística & datos numéricos , Humanos
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