Dinámica de la pandemia de SARS-COVID-19 en la provincia de Buenos Aires a partir del número reproductivo efectivo (Rt) / Dynamics of SARS-COVID-19 pandemic in the province of Buenos Aires based on the effective reproductive number (Rt)

INTRODUCCIÓN: Desde el comienzo de la pandemia de COVID-19 hasta el 31 de marzo de 2022, en la provincia de Buenos Aires se llegó a los 3 542 289 casos, de los cuales fallecieron 59 746. Una de las mediciones incorporadas a la vigilancia fue la estimación del número reproductivo efectivo (Rt), que proporciona información acerca de la velocidad con que una enfermedad puede propagarse. El objetivo de este estudio fue estimar la variación de Rt, del tiempo de duplicación y la tasa de contagio como expresión de la dinámica de la pandemia de COVID-19 desde marzo de 2020 hasta marzo de 2022 en la provincia de Buenos Aires. MÉTODOS: El Rt se estimó en ventanas semanales deslizantes, con una media de intervalo en serie paramétrica de 4,8 días y una desviación estándar de 2,3. El tiempo de duplicación aplicó la función logaritmo (ln), ya que se asumió que el crecimiento del número de casos seguía una distribución exponencial. La tasa de contagio (Tc) se calculó a partir de una regresión lineal de los ln de los casos acumulados en plazos de 7 días. RESULTADOS: Se estudiaron 3 495 338 casos confirmados. Se observaron tres momentos donde Rt>1. DISCUSIÓN: A medida que avanzó la pandemia, Rt pudo estimarse en tiempo real y mostró cómo fue evolucionando a lo largo de los dos años de pandemia en consonancia con las ondas u olas, que aparecieron en tres oportunidades durante la ventana histórica analizada.

Effectiveness of precise prevention and control strategies of dynamic zero COVID-19 in Ningbo, Zhejiang province / 中华流行病学杂志

Objective: To evaluate effectiveness of the precise prevention and control strategies of dynamic zero COVID-19 in Ningbo, Zhejiang province. Methods: Based on the incidence data of COVID-19 and case epidemiological survey report in Ningbo in December 2021, the incidence curve of COVID-19 was generated and a dynamics model was developed to estimate the case number of under different intervention measures. The basic reproduction number (R0) and real-time reproduction number (Rt) were calculated to evaluate intervention effect. Results: A total of 74 cases of COVID-19 had been confirmed in Ningbo as of 17 December, 2021. The R0 was estimated to be 4.3. With the strengthening of prevention and control measures, the Rt showed a gradual downward trend, dropping to below 1.0 on December 11 and 0.4 on December 14. The model fitting results showed that the actual case number was close to the estimated case number (76 cases) when the effectiveness of intervention was 90%. The number of cases decreased by 98.4% compared with that if no intervention was taken. Conclusion: The precise prevention and control strategies of dynamic zero COVID-19 have obvious effect, which can facilitate the rapid control of COVID-19 epidemic in Ningbo.

Social isolation relaxation and the effective reproduction number (Rt) of COVID-19 in twelve Brazilian cities / O relaxamento do isolamento social e o número efetivo de reprodução (Rt) do COVID-19 em doze municípios brasileiros

Abstract We analyzed the social isolation relaxation strategies adopted by the twelve biggest Brazilian cities in 2020, in relation to the number of cases, number of deaths and the effective reproduction number (Rt), which are internationally considered the fundamental epidemiological criteria for allowing wider population mobility in public spaces. The Brazilian central government has not set unique guidelines neither for closure nor for opening, and states and cities have taken the lead in strategy definition. Until July 31 2020, in Belém do Pará, Fortaleza, Manaus, Recife and Rio de Janeiro, where the epidemic peak had already been surpassed, and in Salvador and São Paulo, in which the peak seemed to be already reached, the Rt curve followed a decreasing path after the openings. Porto Alegre, a city in which the epidemic curve was flattened, had an increase in Rt after the start of relaxation. In Belo Horizonte, Brasília, Curitiba and Goiânia, where the curve was also flattened, the Rt remained stable after the opening. The decision on how to operationalize the relaxation of social isolation and the speed with which it happened was heterogeneous among the cities studied. Also, broad population testing strategies were not done in any of the cities.

Resumo Este trabalho analisou as estratégias de relaxamento do isolamento social adotadas pelas doze maiores cidades brasileiras em 2020, em relação ao número de casos, número de óbitos e ao número efetivo de reprodução (Rt), considerados internacionalmente os critérios epidemiológicos fundamentais para permitir uma maior mobilidade da população nos espaços públicos. O governo federal não estabeleceu diretrizes únicas nem para o fechamento nem para a abertura, e os estados e municípios assumiram o protagonismo na definição da estratégia. Até 31 de julho, em Belém do Pará, Fortaleza, Manaus, Recife e Rio de Janeiro, onde o pico epidêmico já havia sido ultrapassado, e em Salvador e São Paulo, em que o pico parecia já ter sido atingido, o Rt seguiu uma curva decrescente após as aberturas. Em Porto Alegre, aonde a curva epidêmica foi achatada, houve aumento do Rt após o início do relaxamento. Em Belo Horizonte, Brasília, Curitiba e Goiânia, nos quais a curva também foi achatada, o Rt manteve-se estável após a abertura. A decisão de como operacionalizar o relaxamento do isolamento social e a velocidade com que isso aconteceu foi heterogênea entre as cidades estudadas. Além disso, amplas estratégias de testagem populacional não foram realizadas em nenhuma das cidades.

La propagación de la COVID-19 en España y Brasil según tiempo y clima / Tempo, clima e propagação da COVID-19 na Espanha e no Brasil / The spread of COVID-19 in Spain and Brazil according to weather and climate

Objetivo: Este artículo de investigación busca conocer la influencia de la propagación del virus COVID-19 a través de la temperatura y de la humedad en España y Brasil. Métodos: Para el cálculo de la variación mensual del índice de propagación del virus COVID-19 por provincias en España se han utilizado, en primer lugar, las series climáticas de la AEMET de España e INMETRO de Brasil. Se han extraído las medias correspondientes y después se han sometido los datos a un proceso de homogenización, para posteriormente poder calcular el incremento mensual de temperatura y de humedad por provincias y estados. Este proceso metodológico establece una relación directamente proporcional entre el aumento de la temperatura y de la humedad con el índice de propagación del virus COVID-19. Resultados: En España, las condiciones climáticas favorecerán la disminución o aumento del índice reproductivo del virus. En Brasil las condiciones climáticas no favorecerán la disminución del índice reproductivo del virus y, climatológicamente, no existe un periodo óptimo para una desescalada y vuelta a la normalidad. Las variaciones de las condiciones climáticas en Brasil no son significativas, por lo que el clima de Brasil no influye en la disminución de propagación del virus. Conclusión: El clima influye en la propagación del virus. Descriptores: COVID-19; Transmisión de Enfermedad Infecciosa; Clima; Temperatura; Humedad.

Objetivo: Este artigo de pesquisa busca conhecer a influência da propagação do vírus COVID-19 através da temperatura e umidade na Espanha e no Brasil. Métodos: Para calcular a variação mensal do índice de propagação do vírus COVID-19 por províncias da Espanha, primeiramente, utilzaram-se as séries climáticas da AEMET da Espanha e do INMETRO do Brasil. Extraíram-se as médias correspondentes, para posterior submissão dos dados a um processo de homogeneização, com o intuito de calcular o aumento mensal de temperatura e umidade por províncias e estados. Esse processo metodológico estabeleceu uma relação diretamente proporcional entre o aumento da temperatura e da umidade com a taxa de disseminação do vírus COVID-19. Resultados: Na Espanha, as condições climáticas favoreceram a diminuição ou aumento do índice reprodutivo do vírus. No Brasil, entretanto, as condições climáticas não favorecem a diminuição do índice reprodutivo do virus, comprovando que climatologicamente não existe um período ideal para uma desaceleração e retorno à normalidade. As variações nas condições climáticas no Brasil não são significativas, portanto o clima não influencia na diminuição da propagação do vírus neste país. Conclusão: O clima influencia a disseminação do vírus. Descritores: COVID-19; Transmissão de Doença Infecciosa; Clima; Temperatura; Umidade.

Objective: This research article seeks to know the influence of the spread of the COVID-19 virus through temperature and humidity in Spain and Brazil. Methods: In order to calculate the monthly variation in the COVID-19 virus spread index by provinces in Spain, at first, the climatic series of the AEMET of Spain and INMETRO of Brazil were used. The corresponding means have been extracted and then the data have been subjected to a homogenization process, to later be able to calculate the monthly increase in temperature and humidity by provinces and states. This methodological process establishes a directly proportional the climatic conditions favored the decrease or increase of the reproductive index of the virus. In Brazil, however, the climatic conditions do not favor the decrease in the reproductive index of the virus, proving that climatologically there is no optimal period for de-escalation and return to normality. The variations in climatic conditions in Brazil are not significant, so the climate does not influence the decrease in the spread of the virus. Conclusion: Climate influences the spread of the virus. Descriptors: COVID-19; Disease Transmission, Infectious; Climate; Temperature; Humidity. relationship between the increase in temperature and humidity with the spread rate of the COVID-19 virus. Results: In Spain the climatic conditions favored the decrease or increase of the reproductive index of the virus. In Brazil, however, the climatic conditions do not favor the decrease in the reproductive index of the virus, proving that climatologically there is no optimal period for de-escalation and return to normality. The variations in climatic conditions in Brazil are not significant, so the climate does not influence the decrease in the spread of the virus. Conclusion: Climate influences the spread of the virus.

Impact of nonpharmaceutical strategies on trends of COVID-19 in São Paulo State

ABSTRACT Interrupted time series analyses were conducted to measure the impact of social distancing policies (instituted on March 22, 2020) and of subsequent mandatory masking in the community (instituted on May 4, 2020) on the incidence and effective reproductive number of COVID-19 in São Paulo State, Brazil. Overall, the impact of social distancing both on incidence and Rt was greater than the incremental effect of mandatory masking. Those findings may reflect either a small impact of face masking or the loosening of social distancing after mandatory use of masks.

Predictive model for Covid-19 incidence in a medium-sized municipality in Brazil (Ponta Grossa, Paraná) / Modelo predictivo de la ocurrencia de Covid-19 en un municipio de tamaño medio en Brasil (Ponta Grossa-Paraná) / Modelo preditivo da ocorrência de Covid-19 em município de médio porte no Brasil (Ponta Grossa-Paraná)

ABSTRACT Objective: to produce a predictive model for the incidence of COVID-19 cases, severity and deaths in Ponta Grossa, state of Paraná. Methods: this is an ecological study with data from confirmed cases of COVID-19 reported between March 21, 2020 and May 3, 2020 in Ponta Grossa and proportion of severity, hospitalization and lethality in the literature. A susceptible-infected-recovered (SIR) epidemic model was developed, and reproduction rate (R0), duration of epidemic, peak period, number of cases, hospitalized patients and deaths were estimated. Deaths were calculated by age group and in three scenarios: at day 24, at day 34, and at day 44 of the epidemic. Results: in the three scenarios assessed in this study, the variation in the number of cases was explained by an exponential curve (r2=0.74, 0.79 and 0.89, respectively, p<0.0001 in all scenarios). The SIR model estimated that, in the best scenario, the peak period will be around 120 days after the first case (between July 11, 2020 and July 25, 2020), estimated R0 will be 1.07 and will infect 0.23% of the population. In the worst scenario, peak period will involve 4,375 (95% CI; 4156-4594) cases and 825 (95% CI; 700-950) cases in the best scenario. Most cases and hospital admissions will involve patients aged 20 to 39 years, the number of deaths will be higher among the elderly and more pronounced among patients aged ≥80 years. Conclusion: this is the first study that provides COVID-19 projections for a municipality that is not a large capital. It shows a peak period at a later moment; therefore, the municipality will have more time to prepare and adopt protective measures to reduce the number of simultaneous cases.

RESUMEN Objetivo: obtener un modelo predictivo para la ocurrencia de casos, severidad y muertes por COVID-19 en Ponta Grossa-Paraná. Métodos: estudio ecológico con datos de casos confirmados de COVID-19 notificados del 21/03/2020 al 3/3/2020 en Ponta Grossa y proporción de severidad, hospitalización y letalidad en la literatura. Se construyó un modelo epidemiológico (SIR) infectado-recuperado susceptible y tasa de reproducción estimada (R0), duración de la epidemia, fecha pico, número de casos, hospitalizaciones y muertes. Este último por grupo de edad y en tres escenarios: a los 24 días, a los 34 días y a los 44 días de epidemia. Resultados: en los tres escenarios evaluados, la variación en el número de casos se explicó por una curva exponencial (r2 = 0.74, 0.79 y 0.89, respectivamente y p <0.0001 en total). El modelo SIR estimó que, en el mejor escenario, el pico ocurrirá alrededor de 120 días después del primer caso (entre el 7/11/2020 y el 25/7/2020), el R0 estimado será de 1.07 y alcanzará 0.23 % de habitantes infectados. En el peor de los casos, el pico estimado será de 4375 (IC del 95%: 4156-4594) y 825 (IC del 95%: 700-950) en el mejor de los casos. El mayor número estimado de casos y hospitalizaciones estará en el rango entre 20 y 39 años, el número de muertes será mayor entre los ancianos y más pronunciado entre ≥ 80 años. Conclusión: este es el primer estudio con proyecciones para COVID-19 en un municipio fuera de las grandes capitales y demostró que el pico llegará tarde, por lo tanto, el municipio tendrá más tiempo de preparación y que las medidas de protección pueden reducir el número simultáneo de casos.

RESUMO Objetivo: obter um modelo preditivo da ocorrência de casos, gravidade e óbitos por COVID-19 em Ponta Grossa-Paraná. Métodos: estudo ecológico com dados de casos confirmados de COVID-19 notificados de 21/03/2020 a 03/05/2020 em Ponta Grossa e proporção de gravidade, hospitalização e letalidade da literatura. Um modelo epidemiológico suscetível-infectado-recuperado (SIR) foi construído e estimadas taxa de reprodução (R0), duração da epidemia, data do pico, número de casos, hospitalizações e óbitos. Estas últimas por faixa etária e em três cenários: aos 24 dias, aos 34 dias e aos 44 dias de epidemia. Resultados: nos três cenários avaliados, a variação no número de casos foi explicada por uma curva exponencial (r2=0,74, 0,79 e 0,89, respectivamente e p<0,0001 em todos). O modelo SIR estimou que, no melhor cenário, o pico ocorrerá em torno de 120 dias após o primeiro caso (entre 11/07/2020 e 25/07/2020), o R0 estimado será 1,07 e chegará a 0,23% dos habitantes infectados. No pior cenário, o pico estimado será de 4375 (IC 95% 4156-4594) casos e 825 (IC 95% 700-950) no melhor cenário. O maior número estimado de casos e hospitalizações será na faixa entre 20 e 39 anos, o número de óbitos será maior entre idosos e mais acentuado entre ≥ 80 anos. Conclusão: este é o primeiro estudo com projeções para a COVID-19 em um município fora das grandes capitais e mostrou que o pico será tardio, portanto, o município terá mais tempo de preparo e que medidas protetivas podem reduzir o número simultâneo de casos.

Evaluación de la reserva ovárica: pasado, presente y futuro / Ovarian Reserve: Past, Present and Future / Avaliação da reserva ovariana: passado, presente e futuro

Resumen: La necesidad de investigar la reserva ovárica para apoyar la consejería acerca del éxito o fracaso de los tratamientos de reproducción asistida, principalmente en pacientes con riesgo de falla reproductiva, ha generado la descripción y el uso de pruebas histológicas, basales, dinámicas y ultrasonográficas. La presente revisión tiene como objetivo describir y analizar las diferentes pruebas de evaluación de la reserva ovárica, sus limitaciones y ventajas, y ampliar la información referente a las que, por sus características y resultados, son más utilizadas en la actualidad. Para cumplirlo se realizó búsqueda en bases de datos, incluyendo investigaciones originales, revisiones sistemáticas, metaanálisis, reportes de casos y consensos de expertos, en inglés y español, desde 1980. En cuanto a los resultados, puede decirse que pruebas como la biopsia ovárica, medición de Inhibina B, test de estímulo con FSH o con GnRH, y con citrato de clomifeno, han caído en desuso; la medición de la FSH, si bien todavía utilizada, claramente tiene menor capacidad predictiva que el Conteo de Folículos Antrales (CFA) y la Hormona Antimülleriana (HAM). Se concluye que el CFA y la medición de ham son las pruebas más recomendadas, con mejor capacidad predictiva y que, no obstante algunas limitaciones, permiten un acercamiento a la estimación de la respuesta al estímulo ovulatorio. Se plantean opciones para el futuro que permitirán, a mediano plazo, resolver los interrogantes sobre la "verdadera" reserva ovárica.

Abstract: The need to investigate the ovarian reserve to support counseling about the success or failure of assisted reproduction systems has generated the description and use of histological, basal, dynamic, and ultrasound text. The purpose of this review is to describe and analyze the different tests for evaluating ovarian reserve, their limitations and advantages, and to expand the information regarding those that, due to their characteristics and results, are most widely used today. To achieve this, databases searches were carried out, including for original research, systematic reviews, meta-nalyses, case reports and expert consensus, in English and Spanish, since 1980. Regarding the results, it can be said that tests such as ovarian biopsy, measurement of Inhibin B, FSH or GnRH stimulation test, and with clomiphene citrate, have fallen into disuse. FSH measurement, although still used, clearly has a lower predictive capacity than the Antral Follicle Count (AFC) and the Antimullerian Hormone (AMH). It is concluded that the AFC and the AMH measurement are the most recommended tests, with better predictive capacity and that, despite some limitations, they allow closer estimation of the response to ovulatory stimulus. Options for the future that will allow solving the questions in the medium term about the "true" ovarian reserve are proposed.

Resumo: A necessidade de pesquisar sobre a reserva ovariana para apoiar o aconselhamento acerca do sucesso ou do fracasso dos tratamentos de reprodução assistida, principalmente em pacientes com risco de falha reprodutiva, vem gerando a descrição e o uso de exames histológicos, basais, dinâmicos e ultrassonográficos. Esta revisão tem o objetivo de descrever e analisar os diferentes exames de avaliação da reserva ovariana, suas limitações e vantagens, e ampliar a informação referente aos que, por suas características e resultados, são mais utilizados na atualidade. Para isso, foi realizada busca em base de dados, que incluiu pesquisas originais, revisões sistemáticas, meta-aná-lise, relatos de caso e consenso de especialistas, em inglês e em espanhol, desde 1980. Quanto aos resultados, pode-se dizer que os exames como biópsia ovariana, a medição de Inibina B, exame de estímulo com FSH ou com GnRH, e com citrato de clomifeno estão em desuso; a medição da FSH, embora ainda utilizada, claramente tem menor capacidade preditiva que a contagem de folículos antrais (CFA) e o hormônio antimulleriano (HAM). Conclui-se que o CFA e a medição do HAM são os exames mais recomendados, com melhor capacidade preditiva e que, apesar de algumas limitações, permitem uma aproximação da estimativa da resposta ao estímulo da ovulação. São apresentadas opções para o futuro que possibilitarão, em médio prazo, resolver as questões sobre a "verdadeira" reserva ovariana.

Modelo SIR de la pandemia de COVID-19 en Colombia / SIR model of the COVID-19 pandemic in Colombia

RESUMEN Objetivo Desarrollar un modelo SIR pronóstico de la pandemia de COVID-19 en el territorio colombiano. Métodos Se utilizó un modelo SIR con enfoque determinístico para pronosticar el desarrollo de la pandemia de COVID-19 en Colombia. Los estados considerados fueron susceptibles (S), infecciosos (i) y recuperados o fallecidos (R). Los datos poblacionales se obtuvieron del Departamento Administrativo Nacional de estadística (Proyecciones de Población 2018-2020, difundida en enero de 2020) y los datos sobre casos diarios confirmados de COVID-19 del Instituto Nacional de Salud. Se plantearon diferentes modelos variando el número básico de reproducción (R0). Resultados A partir de los casos reportados por el Ministerio de Salud se crearon cuatro ambientes o escenarios simulados en un modelo SIR epidemiológico, se extendieron las series de tiempo hasta el 30 de mayo, fecha probable del 99% de infección poblacional. Un R0 de 2 es la aproximación más cercana al comportamiento de la pandemia durante los primeros 15 días desde el reporte del caso 0, el peor escenario se daría en la primera semana de abril con un R0 igual a 3. Conclusiones Se hacen necesarias nuevas medidas de mitigación y supresión en las fases de contención y transmisión sostenida, como aumento de la capacidad diagnostica por pruebas y desinfección de zonas pobladas y hogares de aislamiento.(AU)

ABSTRACT Objective To develop a prognostic SIR model of the COVID-19 pandemic in Colombia. Materials and Methods A SIR model with a deterministic approach was used to forecast the development of the COVID-19 pandemic in Colombia. The states considered were susceptible (S), infectious (i) and recovered or deceased (R). Population data were obtained from the National Administrative Department of Statistics (DANE) - Population Projections 2018-2020, released in January 2020-, and data on daily confirmed cases of COVID-19 from the National Institute of Health. Different models were proposed varying the basic reproduction number (R0). Results Based on the cases reported by the Ministry of Health, 4 simulated environments were created in an epidemiological SIR model. The time series was extended until May 30, the probable date when 99% of the population will be infected. R0=2 is the basic reproduction number and the closest approximation to the behavior of the pandemic during the first 15 days since the first case report; the worst scenario would occur in the first week of April with R0=3. Conclusions Further mitigation and suppression measures are necessary in the containment and sustained transmission phases, such as increased diagnostic capacity through testing and disinfection of populated areas and homes in isolation.(AU)

Predicciones de un modelo SEIR para casos de COVID-19 en Cali, Colombia / Predictions of a SEIR model for COVID-19 cases in Cali-Colombia

RESUMEN Objetivo Predecir el número de casos de COVID-19 en la ciudad de Cali-Colombia mediante el desarrollo de un modelo SEIR. Métodos Se utilizó un modelo determinista compartimental SEIR considerando los estados: susceptibles (S), expuestos (E), infectados (I) y recuperados (R). Los parámetros del modelo fueron seleccionados de acuerdo a la revisión de literatura. En el caso de la tasa de letalidad, se usaron los datos de la Secretaría de Salud Municipal de Cali. Se plantearon varios escenarios teniendo en cuenta variaciones en el número básico de reproducción (R0) y en la tasa de letalidad; además, se comparó la predicción hasta el 9 de abril con los datos observados. Resultados A través del modelo SEIR se encontró que, con el número básico de reproducción más alto (2,6) y utilizando la letalidad calculada para la ciudad de 2,0%, el número máximo de casos se alcanzaría el primero de junio con 195 666 (prevalencia); sin embargo, al comparar los casos observados con los esperados, al inicio la ocurrencia observada estaba por encima de la proyectada; pero luego cambia la tendencia con una disminución marcada de la pendiente. Conclusiones Los modelos epidemiológicos SEIR son métodos muy utilizados para la proyección de casos en enfermedades infecciosas; sin embargo, se debe tener en cuenta que son modelos deterministas que pueden utilizar parámetros supuestos y podrían generar resultados imprecisos.(AU)

ABSTRACT Objective To predict the number of cases of COVID-19 in the city of Cali-Colombia through the development of a SEIR model. Methods A SEIR compartmental deterministic model was used considering the states: susceptible (S), exposed (E), infected (I) and recovered (R). The model parameters were selected according to the literature review, in the case of the case fatality rate data from the Municipal Secretary of Health were used. Several scenarios were considered taking into account variations in the basic number of reproduction (R0), and the prediction until april 9 was compared with the observed data. Results Through the SEIR model it was found that with the highest basic number of reproduction [2,6] and using the case fatality rate for the city of 2,0%, the maximum number of cases would be reached on June 1 with 195 666 (prevalence). However, when comparing the observed with the expected cases, at the beginning the observed occurrence was above the projected, but then the trend changes decreasing the slope. Conclusions SEIR epidemiological models are widely used methods for projecting cases in infectious diseases, however it must be taken into account that they are deterministic models that can use assumed parameters and could generate imprecise results.(AU)

Estimación del intervalo serial y número reproductivo básico para los casos importados de COVID-19 / Estimation of serial interval and basic reproductive number for imported cases of COVID-19

RESUMEN Objetivo Estimar el intervalo serial y el número básico de reproducción de COVID-19 entre casos importados durante la fase de contención en Pereira, Colombia, 2020. Método Se realizó un estudio cuantitativo para determinar algunos aspectos de la dinámica de transmisión de la COVID-19. Se utilizaron las entrevistas epidemiológicas de campo en los que se incluyeron 12 casos confirmados por laboratorio con PCR-RT para SARS-CoV-2 importados y sus correspondientes casos secundarios confirmados, entre los que estaban contactos familiares y sociales. Resultados Los intervalos seriales en la COVID-19 se ajustan a una distribución Gamma, con una media del intervalo serial de 3,8 días (± 2,7) y un R0 de 1,7 (IC 95% 1,06-2,7) inferior a lo encontrado en otras poblaciones con inicio del brote. Conclusiones Un intervalo serial inferior al periodo de incubación como el que se estimó en este estudio sugiere un periodo de transmisión presintomático que, según otras investigaciones, alcanza un pico promedio a los 3,8 días, hecho que sugiere que durante la investigación epidemiológica de campo la búsqueda de contactos estrechos se realice desde al menos 2 días antes del inicio de síntomas del caso inicial.(AU)

ABSTRACT Objective To estimate the serial interval and the basic reproduction number of COVID-19 between imported cases during the containment phase in Pereira-Colombia, 2020. Method A quantitative study was carried out to determine the transmission dynamics for COVID-19. Field epidemiological data were used, which included 12 laboratory-confirmed cases with RT-PCR for imported SARS-CoV-2 and their corresponding confirmed secondary cases, including family and social contacts. Results The serial intervals in COVID-19 fit a Gamma distribution, with a mean of the serial interval of 3.8 days (2.7) and an R0 of 1.7 (95% CI 1.06-2.7) lower than that found in other populations with onset of the outbreak. Conclusions A serial interval lower than the incubation period such as that estimated in this study, suggests a presymptomatic transmission period that according to other investigations reaches an average peak at 3.8 days, suggesting that during the field epidemiological investigation the search for contacts Narrowing is performed from at least 2 days before the onset of symptoms of the initial case.(AU)

Modelo SIR de la pandemia de COVID-19 en Colombia / SIR model of the COVID-19 pandemic in Colombia / Modelo SIR da pandemia de COVID-19 na Colômbia

RESUMEN Objetivo Desarrollar un modelo SIR pronóstico de la pandemia de COVID-19 en el territorio colombiano. Métodos Se utilizó un modelo SIR con enfoque determinístico para pronosticar el desarrollo de la pandemia de COVID-19 en Colombia. Los estados considerados fueron susceptibles (S), infecciosos (i) y recuperados o fallecidos (R). Los datos poblacionales se obtuvieron del Departamento Administrativo Nacional de estadística (Proyecciones de Población 2018-2020, difundida en enero de 2020) y los datos sobre casos diarios confirmados de COVID-19 del Instituto Nacional de Salud. Se plantearon diferentes modelos variando el número básico de reproducción (R0). Resultados A partir de los casos reportados por el Ministerio de Salud se crearon cuatro ambientes o escenarios simulados en un modelo SIR epidemiológico, se extendieron las series de tiempo hasta el 30 de mayo, fecha probable del 99% de infección poblacional. Un R0 de 2 es la aproximación más cercana al comportamiento de la pandemia durante los primeros 15 días desde el reporte del caso 0, el peor escenario se daría en la primera semana de abril con un R0 igual a 3. Conclusiones Se hacen necesarias nuevas medidas de mitigación y supresión en las fases de contención y transmisión sostenida, como aumento de la capacidad diagnostica por pruebas y desinfección de zonas pobladas y hogares de aislamiento.

ABSTRACT Objective To develop a prognostic SIR model of the COVID-19 pandemic in Colombia. Materials and Methods A SIR model with a deterministic approach was used to forecast the development of the COVID-19 pandemic in Colombia. The states considered were susceptible (S), infectious (i) and recovered or deceased (R). Population data were obtained from the National Administrative Department of Statistics (DANE) - Population Projections 2018-2020, released in January 2020-, and data on daily confirmed cases of COVID-19 from the National Institute of Health. Different models were proposed varying the basic reproduction number (R0). Results Based on the cases reported by the Ministry of Health, 4 simulated environments were created in an epidemiological SIR model. The time series was extended until May 30, the probable date when 99% of the population will be infected. R0=2 is the basic reproduction number and the closest approximation to the behavior of the pandemic during the first 15 days since the first case report; the worst scenario would occur in the first week of April with R0=3. Conclusions Further mitigation and suppression measures are necessary in the containment and sustained transmission phases, such as increased diagnostic capacity through testing and disinfection of populated areas and homes in isolation.

RESUMO OBJETIVO Desenvolver um modelo SIR prognóstico da pandemia de COVID-19 no território colombiano. MÉTODOS Um modelo SIR com abordagem determinística foi usado para prever o desenvolvimento da pandemia de COVID-19 na Colômbia. Os estados considerados foram suscetíveis (S), infecciosos (i) e recuperados ou falecidos (R). Os dados populacionais foram obtidos do Departamento Administrativo Nacional de Estatística (Projeções de População 2018-2020, divulgado em janeiro de 2020) e dados sobre casos confirmados diariamente de COVID-19 do Instituto Nacional de Saúde. Diferentes modelos foram propostos variando o número básico de reprodução (R 0 ). RESULTADOS Dos casos relatados pelo Ministério da Saúde, quatro ambientes ou cenários simulados foram criados em um modelo epidemiológico de RIS, as séries temporais foram estendidas até 30 de maio, data provável de 99% de infecção populacional. Um R 0 de 2 é a aproximação mais próxima do comportamento da pandemia durante os primeiros 15 dias a partir do relato do caso 0, o pior cenário ocorreria na primeira semana de abril com um R 0 igual a 3. CONCLUSÕES Novas medidas de mitigação e supressão são necessárias nas fases de contenção e transmissão sustentada, como aumento da capacidade de diagnóstico por testes e desinfecção de áreas povoadas e residências isoladas.

Sars-CoV-2: A clinical update - II

SUMMARY INTRODUCTION A covid-19 pandemic decreed by WHO has raised greater awareness of it. EPIDEMIOLOGY The infection, reached the mark of 2,000,000 patients in 33 countries and caused the risk of the presence of comorbidities and advanced age. TRANSMISSIBILITY The transmissibility calculated so far is similar to the H1N1 epidemic, but with lower mortality rates. PHYSIOPATHOLOGY The SARS-CoV-2 virus, of the Coronaviridae family, has the capacity for cellular invasion through the angiotensin-converting enzyme 2 does not have a lower respiratory epithelium and in the cells of the small intestine mucosa. CLINICAL MANIFESTATIONS a presentation can be divided into mild (fever, fatigue, cough, myalgia, and sputum) and severe (cyanosis, dyspnoea, tachypnea, chest pain, hypoxemia and need for clinical measurement) and has an estimated estimate of 2%. DIAGNOSIS allows the detection of viral load in CRP-TR of patients with high clinical suspicion. TREATMENT based on supportive measures and infection control. In severe cases, the use of medications such as hydroxychloroquine and azithromycin or medication can be promising. Take care to avoid the use of corticosteroids. There are no restrictions on the use of resources and IECAs / BRAs.

RESUMO INTRODUÇÃO A pandemia de Covid-19 decretada pela OMS suscita maior conhecimento acerca da doença. EPIDEMIOLOGIA A infecção atingiu a marca de 2 milhões de pacientes em 33 países e levantou como fatores de risco a presença de comorbidades e a idade avançada. TRANSMISSIBILIDADE A transmissibilidade calculada até o momento é similar à da epidemia de H1N1, contudo, com taxa de mortalidade inferior. FISIOPATOLOGIA O vírus Sars-CoV-2, da família Coronaviridae, tem capacidade de invasão celular através da enzima conversora de angiotensina 2 presente no epitélio respiratório inferior e nas células da mucosa do intestino delgado. MANIFESTAÇÕES CLÍNICAS A apresentação pode ser dividida em leve (febre, fadiga, tosse, mialgia e escarro) e grave (cianose, dispneia, taquipneia, dor torácica, hipoxemia e necessidade de ventilação mecânica) e tem mortalidade estimada de pouco mais de 2%. DIAGNÓSTICO Dá-se pela detecção da carga viral no PCR-TR de pacientes com alta suspeição clínica. TRATAMENTO Baseado em medidas de suporte e de controle de infecção. Em casos graves, uso de medicamentos como hidroxicloroquina e azitromicina ou remdesevir pode ser promissor. Deve-se evitar o uso de corticosteroides. Não há evidências suficientes para abster-se do uso de ibuprofeno e IECAs/BRAs.

Translating transmissibility measures into recommendations for coronavirus prevention

ABSTRACT The rapid increase in clinical cases of the new coronavirus disease, COVID-19, suggests high transmissibility. However, the estimates of the basic reproductive number reported in the literature vary widely. Considering this, we drew the function of contact-rate reduction required to control the transmission from both detectable and undetectable sources. Based on this, we offer a set of recommendations for symptomatic and asymptomatic populations during the current pandemic. Understanding the dynamics of transmission is essential to support government decisions and improve the community's adherence to preventive measures.

Data Fitting and Scenario Analysis of Vaccination in the 2014 Ebola Outbreak in Liberia

OBJECTIVES: This study aimed to extend an epidemiological model (SEIHFR) to analyze epidemic trends, and evaluate intervention efficacy. METHODS: SEIHFR was modified to examine disease transmission dynamics after vaccination for the Ebola outbreak. Using existing data from Liberia, sensitivity analysis of various epidemic scenarios was used to inform the model structure, estimate the basic reproduction number ℜ₀ and investigate how the vaccination could effectively change the course of the epidemic. RESULTS: If a randomized mass vaccination strategy was adopted, vaccines would be administered prophylactically or as early as possible (depending on the availability of vaccines). An effective vaccination rate threshold for Liberia was estimated as 48.74% among susceptible individuals. If a ring vaccination strategy was adopted to control the spread of the Ebola virus, vaccines would be given to reduce the transmission rate improving the tracing rate of the contact persons of an infected individual. CONCLUSION: The extended SEIHFR model predicted the total number of infected cases, number of deaths, number of recoveries, and duration of outbreaks among others with different levels of interventions such as vaccination rate. This model may be used to better understand the spread of Ebola and develop strategies that may achieve a disease-free state.

Modification of the Conventional Influenza Epidemic Models Using Environmental Parameters in Iran / 대한의료정보학회지

OBJECTIVES: The association between the spread of infectious diseases and climate parameters has been widely studied in recent decades. In this paper, we formulate, exploit, and compare three variations of the susceptible-infected-recovered (SIR) model incorporating climate data. The SIR model is a well-studied model to investigate the dynamics of influenza viruses; however, the improved versions of the classic model have been developed by introducing external factors into the model. METHODS: The modification models are derived by multiplying a linear combination of three complementary factors, namely, temperature (T), precipitation (P), and humidity (H) by the transmission rate. The performance of these proposed models is evaluated against the standard model for two outbreak seasons. RESULTS: The values of the root-mean-square error (RMSE) and the Akaike information criterion (AIC) improved as they declined from 8.76 to 7.05 and from 98.12 to 93.01 for season 2013/14, respectively. Similarly, for season 2014/15, the RMSE and AIC decreased from 8.10 to 6.45 and from 117.73 to 107.91, respectively. The estimated values of R(t) in the framework of the standard and modified SIR models are also compared. CONCLUSIONS: Through simulations, we determined that among the studied environmental factors, precipitation showed the strongest correlation with the transmission dynamics of influenza. Moreover, the SIR+P+T model is the most efficient for simulating the behavioral dynamics of influenza in the area of interest.

Introduction of Phylodynamics for Controlling the HIV/AIDS Epidemic in Korea / 예방의학회지

As over 1000 new cases of HIV/AIDS occur in Korea annually, preventive health programs against HIV/AIDS are urgently needed. Since phylodynamic studies have been suggested as a way to understand how infectious diseases are transmitted and evolve, phylodynamic inferences can be a useful tool for HIV/AIDS research. In particular, phylodynamic models are helpful for dating the origins of an epidemic and estimating its basic reproduction number. Thus, the introduction of phylodynamics would be a highly valuable step towards controlling the HIV/AIDS epidemic in Korea.

Effects of Timely Control Intervention on the Spread of Middle East Respiratory Syndrome Coronavirus Infection

OBJECTIVES: The 2015 Middle East Respiratory Syndrome Coronavirus (MERS-CoV) outbreak in Korea caused major economic and social problems. The control intervention was conducted during the MERS-CoV outbreak in Korea immediately after the confirmation of the index case. This study investigates whether the early risk communication with the general public and mass media is an effective preventive strategy. METHODS: The SEIR (Susceptible, Exposed, Infectious, Recovered) model with estimated parameters for the time series data of the daily MERS-CoV incidence in Korea was considered from May to December 2015. For 10,000 stochastic simulations, the SEIR model was computed using the Gillespie algorithm. Depending on the time of control intervention on the 20th, 40th, and 60th days after the identification of the index case, the box plots of MERS-CoV incidences in Korea were computed, and the results were analyzed via ANOVA. RESULTS: The box plots showed that there was a significant difference between the non-intervention and intervention groups (the 20th day, 40th day, and 60th day groups) and seemed to show no significant difference based on the time of intervention. However, the ANOVA revealed that early intervention was a good strategy to control the disease. CONCLUSION: Appropriate risk communication can secure the confidence of the general public in the public health authorities.

Potential occurrence of Zika from subtropical to temperate Argentina considering the basic reproduction number (R0) / Posible ocurrencia de zika en las zonas subtropical a templada de Argentina considerando el número de reproducción básico (R0) / Potencial de ocorrência de zika em Argentina subtropical e temperada considerando o número de reprodução básico (R0 )

ABSTRACT Objective To assess the potential occurrence of Zika transmission throughout Argentina by the mosquito Aedes aegypti considering the basic reproduction number (R0). Methods A model originally developed for dengue was adapted for Zika. R0 was estimated as a function of seven parameters, three of them were considered temperature-dependent. Seasonal Zika occurrence was evaluated in 9 locations representing different climatic suitability for the vector. Data of diary temperatures were extracted and included in the model. A threshold of R0 = 1 was fixed for Zika occurrence. Sensitivity analyses were performed to evaluate the uncertainty around the results. Results Zika transmission has the potential to occur in all studied locations at least in some moment of the year. In the northern region, transmission might be possible throughout the whole year or with an interruption in winter. The maximum R0 was estimated in 6.9, which means an average of 7 secondary cases from a primary case. The probabilistic sensitivity analysis showed that during winter the transmission can only be excluded in the southern fringe of geographic distribution of the vector and in part of central Argentina. Conclusion Zika virus has the potential to be transmitted in Argentina throughout the current geographic range of the mosquito vector. Although the transmission would be mainly seasonal, the possibility of winter transmission cannot be excluded in northern and central Argentina, meaning that there is a potential endemic maintenance of the disease.

RESUMEN Objetivo Evaluar la posibilidad de transmisión de zika en la Argentina por el mosquito Aedes aegypti considerando el número de reproducción básica (R0). Métodos Se adaptó para el zika un modelo desarrollado originalmente para el dengue. Se estimó R0 en función de siete parámetros, tres de los cuales se consideraron dependientes de la temperatura. Se evaluó la ocurrencia estacional de zika en nueve localidades que representan diferente aptitud climática para el vector. Se obtuvieron los datos de las temperaturas diarias y se incluyeron en el modelo. Se fijó un umbral de R0 = 1 para la ocurrencia de zika. Se realizaron análisis de sensibilidad para evaluar la incertidumbre de los resultados. Resultados En todos los lugares estudiados es posible la transmisión de zika al menos en algún momento del año. En la región norte, la transmisión podría ser posible durante todo el año o con una interrupción en invierno. Se estimó el R0 máximo en 6,9, lo que significa un promedio de siete casos secundarios a partir de un caso primario. El análisis de sensibilidad probabilística demostró que durante el invierno la transmisión sólo puede ser excluida en la franja sur de distribución geográfica del vector y en parte de la región central de Argentina. Conclusión El virus del Zika puede ser transmitido en Argentina en todo el rango geográfico actual del mosquito vector. Aunque la transmisión sería principalmente estacional, no es posible descartar la posibilidad de transmisión invernal en el norte y centro de la Argentina, lo que significa que la enfermedad puede mantenerse de manera endémica.

RESUMO Objetivo Avaliar a ocorrência potencial de transmissão de zika em Argentina pelo mosquito Aedes aegypti considerando o número de reprodução básico (R0). Métodos Foi adaptado para zika um modelo originalmente desenvolvido para dengue. R0 foi estimado como uma função de sete parâmetros, três deles considerados dependentes da temperatura. A ocorrência de zika sazonal foi avaliada em nove locais que representam diferentes adequações climáticas para o vetor. Os dados das temperaturas diárias foram extraídos e incluídos no modelo. Um limite de R0 = 1 foi fixado para a ocorrência de zika, e foram realizadas análises de sensibilidade para avaliar a incerteza em torno dos resultados. Resultados A transmissão de zika pode ocorrer em todos os locais estudados pelo menos em algum momento do ano. Na região norte, a transmissão pode ser possível durante todo o ano ou com uma interrupção no inverno. O R0 máximo foi estimado em 6.9, o que significa uma média de 7 casos secundários a partir de um caso primário. A análise de sensibilidade probabilística mostrou que durante o inverno a transmissão só pode ser excluída na franja sul da distribuição geográfica do vetor e em parte da Argentina central. Conclusão O vírus Zika tem o potencial de ser transmitido na Argentina ao longo da atual faixa geográfica do vetor. Embora a transmissão seja principalmente sazonal, a possibilidade de transmissão no inverno não pode ser excluída no norte e centro da Argentina, o que significa que existe uma potencial manutenção endêmica da doença.