Infección por SARS-CoV-2 en niños: características clínicas y dinámica de la transmisión de SARS-CoV-2 en un centro de salud privado: Uruguay / SARS-CoV-2 infection in children: clinical characteristics and dynamics of SARS-CoV-2 transmission in a private health center: Uruguay

INTRODUCCIÓN: Hasta la fecha, la prevalencia y gravedad de la enfermedad COVID- 19 en niños es menor que en adultos. Existen controversias en relación a la dinámica de la transmisión y al rol que juegan en la diseminación de la enfermedad. OBJETIVO: Describir las características clínicas y la dinámica de transmisión de los pacientes bajo 15 años de edad notificados por sospecha y/o contacto para COVID-19 en el período 13 marzo - 20 noviembre 2020, en un prestador integral privado de salud (Médica Uruguaya Corporación de Asistencia Médica, MUCAM). METODOLOGÍA: Estudio descriptivo, retrospectivo, en el que se describen manifestaciones clínicas, noción epidemiológica, casos secundarios, gravedad y evolución. Se estimó el riesgo y la tasa de ataque secundaria intradomiciliaria. RESULTADOS: Cumplieron los criterios de inclusión 539 pacientes. El diagnóstico se confirmó en 29 (5,3%): 13 (7,0%) de los 351 niños sintomáticos y 16 (4,5%) de los 188 asintomáticos. Tuvieron noción de contacto el 100% de los casos confirmados y 85% de los no confirmados (p < 0.05). El OR para la infección a partir de un contacto intradomiciliario fue 26,5 (9,8- 71,7) y la tasa de ataque secundaria intradomiciliaria 23% ± 4,1. CONCLUSIONES: En esta serie, en los pacientes bajo 15 años de edad predominaron las formas leves y asintomáticas. Uno de cada cinco expuestos intradomiciliarios contrajo la enfermedad siendo esta noción de contacto decisiva para indicar estudios confirmatorios. La mayoría de los niños no continuó la cadena de transmisión.

BACKGROUND: To date, the prevalence and severity of the COVID-19 disease in children is lower than in adults. There are controversies regarding the dynamics of transmission and the role they play in the spread of the disease. AIM: To describe the clinical characteristics and transmission dynamics of patients under 15 years of age reported for suspicion and/or contact for COVID-19 in the period March 13 - November 20, 2020, in a private comprehensive health provider (Médica Uruguaya Medical Assistance Corporation, MUCAM). METHODS: Descriptive, retrospective study, in which clinical manifestations, epidemiological notion, secondary cases, severity and evolution are described. The risk and rate of secondary intradomiciliary attack were estimated. RESULTS: 539 patients met the inclusion criteria. The diagnosis was confirmed in 29 (5.3%): 13 (7.0%) of the 351 symptomatic children and 16 (4.5%) of the 188 asymptomatic. 100% of the confirmed cases and 85% of the unconfirmed cases had the notion of contact (p < 0.05). The OR for infection from an indoor contact was 26.5 (9.8-71.7) and the rate of secondary indoor attack 23% ± 4.1. CONCLUSIONS: In this series, mild and asymptomatic forms predominated in patients under 15 years of age. One in five exposed indoors contracted the disease, this notion of contact being decisive to indicate confirmatory studies. Most of the children did not continue the chain of transmission.

Modeling transmission dynamics of severe acute respiratory syndrome coronavirus 2 in São Paulo, Brazil

Abstract INTRODUCTION Severe acute respiratory syndrome coronavirus 2 has been transmitted to more than 200 countries, with 92.5 million cases and 1,981,678 deaths. METHODS This study applied a mathematical model to estimate the increase in the number of cases in São Paulo state, Brazil during four epidemic periods and the subsequent 300 days. We used different types of dynamic transmission models to measure the effects of social distancing interventions, based on local contact patterns. Specifically, we used a model that incorporated multiple transmission pathways and an environmental class that represented the pathogen concentration in the environmental reservoir and also considered the time that an individual may sustain a latent infection before becoming actively infectious. Thus, this model allowed us to show how the individual quarantine and active monitoring of contacts can influence the model parameters and change the rate of exposure of susceptible individuals to those who are infected. RESULTS The estimated basic reproductive number, R o , was 3.59 (95% confidence interval [CI]: 3.48 - 3.72). The mathematical model data prediction coincided with the real data mainly when the social distancing measures were respected. However, a lack of social distancing measures caused a significant increase in the number of infected individuals. Thus, if social distancing measures are not respected, we estimated a difference of at least 100,000 cases over the next 300 days. CONCLUSIONS: Although the predictive capacity of this model was limited by the accuracy of the available data, our results showed that social distancing is currently the best non-pharmacological measure.

Principles of dynamics model and its application in forecasting the epidemics and evaluation the efforts of prevention and control interventions / 中华预防医学杂志

During the epidemics of COVID-19 in domestic China and recently continuing rapid spread worldwide, a bunch of studies fitted the epidemics by transmission dynamics model to nowcast and forecast the trend of epidemics of COVID-19. However, due to little known of the new virus in early stage and much uncertainty in the comprehensive strategies of prevention and control for epidemics, majority of models, not surprisingly, predict in less accuracy, although the dynamics model has its great value in better understanding of transmission. This comment discusses the principle assumptions and limitations of the dynamics model in forecasting the epidemic trend, as well as its great potential role in evaluation the efforts of prevention and control strategies.

Neglected Plasmodium vivax malaria in northeastern States of India.

Background & objectives: the northeastern states of India are co-endemic for Plasmodium falciparum and P. vivax malaria. The transmission intensity is low-to-moderate resulting in intermediate to stable malaria. Malaria control prioritized P. falciparum being the predominant and life threatening infection (>70%). P. vivax malaria remained somewhat neglected. The present study provides a status report of P. vivax malaria in the northeastern States of India. Methods: Data on spatial distribution of P. vivax from seven northeastern states (Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland and Tripura) were analysed retrospectively from 2008–2013. In addition, cross-sectional malarial surveys were conducted during 1991-2012 in malaria endemic pockets across the states of Assam, Meghalaya, Mizoram and Tripura to ascertain the prevalence of P. vivax in different age groups. Results: Vivax malaria was encountered in all northeastern States but there existed a clear division of two malaria ecotypes supporting ≤30 and >30 per cent of total malaria cases. High proportions of P. vivax cases (60–80%) were seen in Arunachal Pradesh and Nagaland in the north with alpine environment, 42-67 per cent in Manipur, whereas in Assam it varied from 23-31 per cent with subtropical and tropical climate. Meghalaya, Tripura and Mizoram had the lowest proportion of P. vivax cases. Malaria cases were recorded in all age groups but a higher proportion of P. vivax consistently occurred among <5 yr age group compared to P. falciparum (P<0.05). P. vivax cases were recorded throughout the year with peak coinciding with rainy season although transmission intensity and duration varied. Interpretation & conclusions: In northeast India, P. vivax is a neglected infection. Estimating the relapsing pattern and transmission dynamics of P. vivax in various ecological settings is an important pre-requisite for planning malaria elimination in the northeastern states.

The potential impact of new diagnostic tests on tuberculosis epidemics.

Background & objectives: New diagnostic tests for tuberculosis, especially those based on nucleic acid amplification, offer the possibility of early and accurate diagnosis of active TB. In this study we use mathematical modelling to explore the potential epidemiological impact of these new tests, with particular reference to India. Methods: A behavioural model of patient-doctor interactions embedded in an epidemiological model of Mycobacterium tuberculosis transmission, linked to field data, was used to investigate the effects of early diagnosis in preventing future TB cases. Results: New diagnostic tests for active TB will have a bigger impact sooner where: disease incidence is high and most cases are due to recent infection; advances in test technology (test sensitivity, specificity, etc.) are combined with early diagnosis; new tests have not only better technical specifications than current tests, but also compensate for the misuse of existing tests; health system delays are long compared with patient delays, assuming the former are more amenable to change. Interpretation & conclusions: New diagnostic tests will certainly improve TB control, but the highest impact will be obtained by applying tests with higher sensitivity and specificity early in the infectious period. Refined behavioural and epidemiological models should be able to investigate the mechanisms by which early diagnosis could be achieved, in addition to the consequent epidemiological effects.

Application of complex networks model in preventing and controlling communicable disease / 中华流行病学杂志

To discuss the application of complex networks models in preventing and controlling communicable disease, analyze and control the spread of infectious diseases by using the models and the software of complex networks based on its basic properties. Compared with conventional epidemiological approach, the complex networks theory, as a new theory, not only can describe the dynamic process of infections diseases spreading but also forecast the situation of infectious disease. The influence of the network's topology on the infections diseases transmission can be deeply understood through the research on disease spreading by its theory, so to control the spread of diseases. Complex networks theory approach can be used in epidemiological research for having much advantage compared with those conventional epidemiological approaches.