Dengue and COVID-19, overlapping epidemics? An analysis from Colombia.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly spread throughout Latin America, a region swept by multiple previous and ongoing epidemics. There are significant concerns that the arrival of COVID-19 is currently overlapping with other viruses, particularly dengue, in various endo-epidemic regions across South America. In this report, we analyzed trends for both viral infections in Colombia during the first 20 epidemiological weeks (EWs) of 2020. From 1st January to 16th May 2020 (EWs, 1-20), a total of 52 679 cases of dengue and 14 943 cases of COVID-19 have been confirmed in Colombia. As both conditions may potentially lead to fatal outcomes, especially in patients with chronic co-morbidities, overlapping infections, and co-occurrence may increase the number of patients requiring intensive care and mechanical ventilation. In regions, such as Valle del Cauca, intensified preparation for such scenarios should be pondered, and further studies should be performed to address this critical issue in a timely matter.

Predicción espacio-temporal probabilista de la epidemia de dengue total y grave en Colombia / Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia / Previsão probabilística espaço-temporal da epidemia de dengue total e grave na Colômbia

RESUMEN Objetivo Establecer una nueva metodología predictiva de la proporción de dengue grave respecto al total anual de infectados de dengue por departamento con base en la teoría de la probabilidad. Métodos Con base en los datos anuales de número de infectados por departamentos en el periodo 2005 -2010, se calculó la proporción entre casos de dengue grave respecto al total para cada año, y se construyeron espacios de probabilidad que evalúan estos eventos en rangos de 0,5 y 0,3. Se determinaron conjuntos de rangos y se calculó probabilidad, desviación media cuadrática y la diferencia entre ellas. Se realizó una predicción del rango de infectados para el 2011 con el promedio aritmético de los valores de los últimos dos años. Resultados Se predijo correctamente el rango en el que se encuentra incluida la proporción de número de infectados de dengue grave sobre el total en cada departamento con una efectividad del 93,3% para el rango de 0,5 y de 86,7% para el de 0,3. Conclusión Se evidenció una autoorganización matemática espacio temporal en la proporción de dengue grave respecto al total que permite establecer predicciones de utilidad para la toma de decisiones de salud pública.(AU)

ABSTRACT Objective To establish a new predictive methodology to determine the proportion of severe dengue with respect to the annual total of dengue infections per department based on the probability theory. Materials and Methods Based on annual data on the number of infected persons by department in the period 2005-2010, the proportion of cases of severe dengue was calculated with respect to the total for each year. Probability spaces were constructed to evaluate these events in the ranges 0.5 and 0.3. Sets of ranges were determined and probability, mean square deviation and the difference between them were estimated. A prediction of the range of infected people for 2011 was made using the arithmetic average of the values of the last two years. Results The range in which the proportion of the number of people infected with severe dengue is included with respect to the total amount in each department was correctly predicted, with an effectiveness of 93.3% for the 0.5 range and 86.7% for the 0.3 range. Conclusion A mathematical spatial-temporal self-organization was found in the proportion of severe dengue with respect to the total, which allows establishing useful predictions for decision-making in public health.(AU)

RESUMO Objetivo Estabelecer uma nova metodologia preditiva para a proporção de dengue grave em relação ao dengue total anual infectado por departamento com base na teoria da probabilidade. Métodos Com base nos dados anuais do número de infectados por departamentos no período 2005-2010, a proporção entre os casos de dengue grave em relação ao total foi calculada para cada ano, e foram construídos espaços de probabilidade que avaliam esses eventos em intervalos de 0, 5 e 0,3. Conjuntos de intervalos foram determinados e a probabilidade, o desvio médio quadrático e a diferença entre eles foram calculados. A previsão da faixa de infectados para 2011 foi feita com a média aritmética dos valores dos últimos dois anos. Resultados A faixa na qual a proporção do número de infectados por dengue grave sobre o total está incluída em cada departamento foi corretamente prevista com uma eficácia de 93,3% para a faixa de 0,5 e 86,7% para aquela de 0,3. Conclusão Evidenciou-se uma auto-organização matemática espaço-temporal na proporção de dengue grave em relação ao total, o que permite estabelecer previsões úteis para a tomada de decisões em saúde pública.(AU)

[Probabilistic spatial-temporal prediction of total and severe epidemic of dengue in Colombia]. / Predicción espacio-temporal probabilista de la epidemia de dengue total y grave en Colombia.

OBJECTIVE: To establish a new predictive methodology to determine the proportion of severe dengue with respect to the annual total of dengue infections per department based on the probability theory. MATERIALS AND METHODS: Based on annual data on the number of infected persons by department in the period 2005-2010, the proportion of cases of severe dengue was calculated with respect to the total for each year. Probability spaces were constructed to evaluate these events in the ranges 0.5 and 0.3. Sets of ranges were determined and probability, mean square deviation and the difference between them were estimated. A prediction of the range of infected people for 2011 was made using the arithmetic average of the values of the last two years. RESULTS: The range in which the proportion of the number of people infected with severe dengue is included with respect to the total amount in each department was correctly predicted, with an effectiveness of 93.3% for the 0.5 range and 86.7% for the 0.3 range. CONCLUSION: A mathematical spatial-temporal self-organization was found in the proportion of severe dengue with respect to the total, which allows establishing useful predictions for decision-making in public health.

OBJETIVO: Establecer una nueva metodología predictiva de la proporción de dengue grave respecto al total anual de infectados de dengue por departamento con base en la teoría de la probabilidad. MÉTODOS: Con base en los datos anuales de número de infectados por departamentos en el periodo 2005 -2010, se calculó la proporción entre casos de dengue grave respecto al total para cada año, y se construyeron espacios de probabilidad que evalúan estos eventos en rangos de 0,5 y 0,3. Se determinaron conjuntos de rangos y se calculó probabilidad, desviación media cuadrática y la diferencia entre ellas. Se realizó una predicción del rango de infectados para el 2011 con el promedio aritmético de los valores de los últimos dos años. RESULTADOS: Se predijo correctamente el rango en el que se encuentra incluida la proporción de número de infectados de dengue grave sobre el total en cada departamento con una efectividad del 93,3% para el rango de 0,5 y de 86,7% para el de 0,3. CONCLUSIÓN: Se evidenció una autoorganización matemática espacio temporal en la proporción de dengue grave respecto al total que permite establecer predicciones de utilidad para la toma de decisiones de salud pública.

Algunas consideraciones diagnósticas y terapéuticas del paciente con síndrome febril en Colombia / Some considerations regarding diagnosis and therapeutics of patients with febrile syndrome in Colombia

Sr. Editor, hemos leído con gran interés la revisión realizada por Cortés et al. respecto al enfoque clínico del síndrome febril agudo en Colombia, recientemente publicada en la revista INFECTIO. A manera de contribución, en primer lugar, quisiéramos resaltar la importancia de incluir y considerar la enfermedad de Chagas (en su fase aguda) como otro de los diagnósticos diferenciales a tener en cuenta y de suma importancia, en el contexto del síndrome febril agudo en Colombia, particularmente en los últimos años.

Mr. Editor, we have read with great interest the review by Cortés et al. on the clinical approach to acute febrile syndrome in Colombia, recently published in the journal INFECTIO. As a contribution, first of all, we would like to highlight the importance of including and considering Chagas disease (in its acute phase) as another of the differential diagnoses to be taken into account and of utmost importance in the context of acute febrile syndrome in Colombia, particularly in recent years.

Dinámica de la epidemia de malaria en Colombia: Predicción probabilística temporal / Dynamics of the malaria epidemic in Colombia: temporal probabilistic prediction

RESUMEN Objetivo Realizar una predicción de la dinámica de la epidemia de malaria para el 2007 en Colombia con base en el análisis de la dinámica geométrica de 1960-2006 como una caminata al azar probabilista. Materiales y Métodos Basados en la caminata al azar probabilística se estudió la dinámica geométrica del número de casos anuales de malaria registrados en Colombia durante los años 1960-2006, analizando el comportamiento probabilístico de aumentos y disminuciones consecutivos, y el comportamiento probabilístico de casos durante rangos de años consecutivos, para así realizar una predicción temporal de los casos. Resultados Se desarrolló una metodología sencilla y acausal que predice los valores extremos 81 003 y 104 098 para el número de infectados en el año 2007, predicción que fue refinada con el análisis de las variaciones anuales obteniendo un valor de 104 098 para el número de infectados en el año 2007. Esta predicción fue posteriormente corroborada con los datos del Instituto Nacional de Salud de Colombia, correspondiendo al 95,6 % respecto al número de casos reportados. Conclusión La comprensión del fenómeno acausal a partir de la caminata al azar probabilística permite realizar predicciones temporales, simples y prácticas, directamente comprobables y aplicables, economizando tiempo y recursos.(AU)

ABSTRACT Objective To predict the dynamics of the malaria epidemic of 2007 in Colombia. Materials and Methods Based on a random walk, the geometric dynamics of the number of annual cases of malaria registered in Colombia during the period 1960-2006 was studied by analyzing the probabilistic behavior of consecutive increases and decreases, as well as the probabilistic behavior of cases during consecutive year ranges, in order to make a temporary prediction of the cases. Results A simple and acausal methodology that predicts the extreme values for the number of infected people in 2007 was developed; the prediction was refined by the analysis of the annual variations, obtaining a value of 104098 corresponding to the number of infected population in 2007. This prediction was corroborated later against the information of Instituto Nacional de Salud de Colombia (National Institute of Health), finding a 95.6 % correspondence with the number of reported cases. Conclusion Understanding the acausal phenomenon based on a probabilistic random walk allows making temporal, simple and practical predictions that are directly verifiable and applicable, economizing time and sources.(AU)

[Dynamics of the malaria epidemic in Colombia: temporal probabilistic prediction]. / Dinámica de la epidemia de malaria en Colombia: Predicción probabilística temporal.

OBJECTIVE: To predict the dynamics of the malaria epidemic of 2007 in Colombia. MATERIALS AND METHODS: Based on a random walk, the geometric dynamics of the number of annual cases of malaria registered in Colombia during the period 1960-2006 was studied by analyzing the probabilistic behavior of consecutive increases and decreases, as well as the probabilistic behavior of cases during consecutive year ranges, in order to make a temporary prediction of the cases. RESULTS: A simple and acausal methodology that predicts the extreme values for the number of infected people in 2007 was developed; the prediction was refined by the analysis of the annual variations, obtaining a value of 104098 corresponding to the number of infected population in 2007. This prediction was corroborated later against the information of Instituto Nacional de Salud de Colombia (National Institute of Health), finding a 95.6 % correspondence with the number of reported cases. CONCLUSION: Understanding the acausal phenomenon based on a probabilistic random walk allows making temporal, simple and practical predictions that are directly verifiable and applicable, economizing time and sources.

OBJETIVO: Realizar una predicción de la dinámica de la epidemia de malaria para el 2007 en Colombia con base en el análisis de la dinámica geométrica de 1960-2006 como una caminata al azar probabilista. MATERIALES Y MÉTODOS: Basados en la caminata al azar probabilística se estudió la dinámica geométrica del número de casos anuales de malaria registrados en Colombia durante los años 1960-2006, analizando el comportamiento probabilístico de aumentos y disminuciones consecutivos, y el comportamiento probabilístico de casos durante rangos de años consecutivos, para así realizar una predicción temporal de los casos. RESULTADOS: Se desarrolló una metodología sencilla y acausal que predice los valores extremos 81 003 y 104 098 para el número de infectados en el año 2007, predicción que fue refinada con el análisis de las variaciones anuales obteniendo un valor de 104 098 para el número de infectados en el año 2007. Esta predicción fue posteriormente corroborada con los datos del Instituto Nacional de Salud de Colombia, correspondiendo al 95,6 % respecto al número de casos reportados. CONCLUSIÓN: La comprensión del fenómeno acausal a partir de la caminata al azar probabilística permite realizar predicciones temporales, simples y prácticas, directamente comprobables y aplicables, economizando tiempo y recursos.

Infections with biological therapy: strategies for risk minimization in tropical and developing countries.

In recent decades, biological therapy has enabled disease activity control and improved quality of life in patients with autoimmune diseases. These therapies that are involved in immune response modifications and change multiple immunological pathways induce an incremental risk for certain infectious diseases. Though there have been recent advances in risk assessment for biological therapy, there is a lack of data and recommendations for assessing risks in populations with high prevalence of infectious diseases, such as those located in tropical areas and developing countries. We performed a review on infections with biological therapy as well strategies for risk minimization in areas with a high prevalence of tropical diseases.

Giant Molluscum Contagiosum in an HIV positive patient.

Molluscum Contagiosum (MC) is a skin infection caused by a double-stranded DNA virus of the family Poxviridae that replicates in the human epidermis, affecting mainly children and young sexually active adults and causing flesh colored papular lesions with central umbilication with an average size of 3-5mm, although atypical lesions that reach great size (Giant Molluscum Contagiosum), 10-15mm, can be seen in almost any immunodeficiency condition. We report the case of a 35 year old male patient with C3 HIV disease with an abdominal pathology associated to skin lesions predominantly in the forehead and scalp that reached sizes over 5mm, diagnosed as Giant Molluscum Contagiosum by skin biopsies.