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1.
Rev Salud Publica (Bogota) ; 20(1): 117-125, 2018.
Artículo en Español | MEDLINE | ID: mdl-30183894

RESUMEN

HIV interaction with the immune response is modeled mathematically. Initially, a detailed model is proposed that consists of a system of differential equations including immune cells (antigen presenting cells, T latent infected cells, T actively infected cells, resting T cells, helper T cells, inactive cytotoxic cells and active cytotoxic cells) and viral particles. Then, stability conditions are given from the basic reproduction number and numerical simulations are performed. From this it is possible to conclude what are the most influential parameters to reduce infection. From the initial model, a control problem is formulated in order to determine the most appropriate type of intervention to ensure high levels of activated T cells and immune response. Five different control strategies based on antiretroviral are evaluated to conclude that a strategy of constant control, obtained as the average value of optimal control, provides satisfactory results.


Se modela matemáticamente la interacción del VIH con la respuesta inmune. Inicialmente se construye un modelo de manera detallada, que consiste en un sistema de ecuaciones diferenciales que incluye células del sistema inmune (células presentadoras de antígenos, células T infectadas en estado de latencia, células T infectadas activadas, células T en reposo, células T colaboradoras, células de respuesta citotóxica inactivas y células de respuesta citotóxica activas) y partículas virales. A continuación se dan condiciones de estabilidad a partir del número básico de reproducción y se hacen simulaciones numéricas que permiten concluir cuáles son los parámetros más influyentes si se desea reducir la infección. A partir del modelo inicial, se formula un Problema de Control con el objetivo de determinar el tipo de intervención más apropiado que asegure niveles altos de células T activas y de respuesta inmune. Se evalúan entonces cinco estrategias de control diferentes basadas en antirretrovirales y se concluye que una estrategia de control constante, obtenida como el valor promedio del control óptimo, brinda resultados satisfactorios.


Asunto(s)
Fármacos Anti-VIH/uso terapéutico , Infecciones por VIH/tratamiento farmacológico , Infecciones por VIH/inmunología , Modelos Inmunológicos , Esquema de Medicación , VIH/inmunología , Infecciones por VIH/virología , Humanos , Resultado del Tratamiento
2.
Rev Salud Publica (Bogota) ; 16(1): 114-27, 2014.
Artículo en Español | MEDLINE | ID: mdl-25184457

RESUMEN

Nonlinear differential equations were used for formulating a mathematical model describing the dynamics of HIV interaction with CD4 T-cells which are considered to be activated or not activated during recognition of viral particles; in either case they are susceptible to HIV infection. The system's equilibrium points were found and local stability was determined for trivial equilibrium or the absence of infection based on the basic reproduction number. The model was used for numerical simulation to show infected cell and viral load patterns regarding the variations of some parameters. The model was then reformulated, considering a cytotoxic cellular immune response and numerical simulation was run again.


Asunto(s)
Linfocitos T CD4-Positivos/inmunología , Citotoxicidad Inmunológica , Infecciones por VIH/inmunología , Modelos Teóricos , Humanos
3.
Rev Salud Publica (Bogota) ; 16(1): 139-52, 2014.
Artículo en Español | MEDLINE | ID: mdl-25184459

RESUMEN

Two models were constructed for sexually-transmitted HIV between healthy and infected patients in a mixed population, i.e. no discrimination was made between age, gender or sexual orientation. The first model had no control and considered three populations according to their infection status; the first concerned the average number of susceptible individuals, the second the average number of undiagnosed HIV infected people and the third was concerned with the average number of undiagnosed infected patients (assuming that susceptible people might acquire HIV from diagnosed and undiagnosed infected patients). The second model included control through diagnosis; it considered two additional populations: the average number of diagnosed healthy carriers and diagnosed HIV infected carriers. This was aimed at studying whether the disease can be controlled by diagnosis only. It was also assumed that, despite diagnosis, susceptible people may acquire HIV from both diagnosed and undiagnosed infected patients. It was noted that numerical simulation provided sufficient evidence for determining that the best diagnostic strategy (i.e. having 100 % effectiveness) was not effective enough to significantly reduce HIV transmission.


Asunto(s)
Infecciones por VIH/prevención & control , Infecciones por VIH/transmisión , Modelos Teóricos , Infecciones por VIH/diagnóstico , Humanos
4.
Rev Salud Publica (Bogota) ; 15(6): 943-56, 2013.
Artículo en Español | MEDLINE | ID: mdl-25124356

RESUMEN

A mathematical model was constructed for modelling transmission dynamics and the evolution of an infectious disease in a prison setting, considering asymptomatic infectious people, symptomatic infectious people and isolated infectious people. The model was proposed as a nonlinear differential equation system for describing disease epidemiology. The model's stability was analysed for including a preventative control strategy which would enable finding a suitable basic reproduction number-based control protocol. A cost function related to the system of differential equations was formulated to minimise infectious populations and intervention costs; such function was minimised by using the Pontryagin maximum principle which determines optimum preventative control strategies by minimising both infectious populations and associated costs. A numerical analysis of the model was made, considering preventative control effectiveness levels and different control weighting constants. Conclusions were drawn. The basic reproduction number characterises system stability and leads to determining clear control criteria; a preventative control threshold was defined, based on the controlled basic reproduction number which enabled deducing that disease control requires uniform preventative control involving high rates of effectiveness.


Asunto(s)
Control de Enfermedades Transmisibles/métodos , Enfermedades Transmisibles/epidemiología , Modelos Teóricos , Prisiones , Colombia/epidemiología , Control de Enfermedades Transmisibles/economía , Enfermedades Transmisibles/economía , Enfermedades Transmisibles/transmisión , Análisis Costo-Beneficio , Humanos , Prisiones/economía
5.
Rev. salud pública ; 20(1): 117-125, ene.-feb. 2018. tab, graf
Artículo en Español | LILACS | ID: biblio-962101

RESUMEN

RESUMEN Se modela matemáticamente la interacción del VIH con la respuesta inmune. Inicialmente se construye un modelo de manera detallada, que consiste en un sistema de ecuaciones diferenciales que incluye células del sistema inmune (células presentadoras de antígenos, células T infectadas en estado de latencia, células T infectadas activadas, células T en reposo, células T colaboradoras, células de respuesta citotóxica inactivas y células de respuesta citotóxica activas) y partículas virales. A continuación se dan condiciones de estabilidad a partir del número básico de reproducción y se hacen simulaciones numéricas que permiten concluir cuáles son los parámetros más influyentes si se desea reducir la infección. A partir del modelo inicial, se formula un Problema de Control con el objetivo de determinar el tipo de intervención más apropiado que asegure niveles altos de células T activas y de respuesta inmune. Se evalúan entonces cinco estrategias de control diferentes basadas en antirretrovirales y se concluye que una estrategia de control constante, obtenida como el valor promedio del control óptimo, brinda resultados satisfactorios.(AU)


ABSTRACT HIV interaction with the immune response is modeled mathematically. Initially, a detailed model is proposed that consists of a system of differential equations including immune cells (antigen presenting cells, T latent infected cells, T actively infected cells, resting T cells, helper T cells, inactive cytotoxic cells and active cytotoxic cells) and viral particles. Then, stability conditions are given from the basic reproduction number and numerical simulations are performed. From this it is possible to conclude what are the most influential parameters to reduce infection. From the initial model, a control problem is formulated in order to determine the most appropriate type of intervention to ensure high levels of activated T cells and immune response. Five different control strategies based on antiretroviral are evaluated to conclude that a strategy of constant control, obtained as the average value of optimal control, provides satisfactory results.(AU)


Asunto(s)
Humanos , Infecciones por VIH/tratamiento farmacológico , Modelos Estadísticos , Terapia Combinada , Antirretrovirales/uso terapéutico , Sistema Inmunológico
6.
Rev Salud Publica (Bogota) ; 12(6): 1033-41, 2010 Dec.
Artículo en Español | MEDLINE | ID: mdl-22030690

RESUMEN

Dengue fever is a common vector-borne disease in tropical and subtropical areas. It is transmitted to humans by the bite of an infected female Aedes mosquito. Since no vaccines are currently available which can protect against infection, disease control relies on controlling the mosquito population. This work was aimed at modelling such mosquito's population dynamics regarding chemical control of the adult population and its acquired resistance to chemicals. The model was analysed by using classical dynamic system theory techniques and mosquito growth threshold was determined as this establishes when a particular population may prosper in the environment or when it is likely to disappear. A suitable chemical control strategy was developed from such threshold. Simulations were made in control and non-control scenarios; this determined the degree of control application effectiveness against different levels of acquired resistance.


Asunto(s)
Aedes , Dengue/prevención & control , Insectos Vectores , Resistencia a los Insecticidas , Modelos Biológicos , Control de Mosquitos/métodos , Animales , Simulación por Computador , Dengue/transmisión , Femenino , Humanos , Dinámica Poblacional
7.
Rev Salud Publica (Bogota) ; 12(6): 1020-32, 2010 Dec.
Artículo en Español | MEDLINE | ID: mdl-22030689

RESUMEN

Dengue fever transmission dynamics were studied in an endemic region considering the use of preventative measures and mechanical control in reducing transmission of the disease. A system of ordinary differential equations was proposed, describing the dynamics and their evolution as determined by numerical simulation. Different mechanical control and prophylaxis strategies were compared to the situation without control. The basic reproduction number R0 was determined R0 to show that if R0 > 1 there would be a risk of an epidemic and otherwise the disease would have low impact levels. The basic reproduction number helps determine the dynamics' future pattern and contrast the results so obtained with those obtained numerically. It was concluded that although prophylaxis and mechanical control alone provide effective results in controlling the disease, if both controls are combined then infection levels become significantly reduced. Around 60 % mechanical control and prevention levels are needed to provide suitable results in controlling dengue outbreaks.


Asunto(s)
Control de Enfermedades Transmisibles/métodos , Dengue/transmisión , Enfermedades Endémicas , Modelos Biológicos , Aedes , Animales , Dengue/epidemiología , Dengue/prevención & control , Brotes de Enfermedades/prevención & control , Humanos , Insectos Vectores , Control de Mosquitos , Densidad de Población
8.
Rev. salud pública ; 16(1): 103-115, ene.-feb. 2014. ilus, tab
Artículo en Español | LILACS | ID: lil-717115

RESUMEN

Con base en ecuaciones diferenciales no lineales se formula un modelo matemático que describe la dinámica de interacción del VIH con células T CD4, que se considera que pueden ser activadas o no activadas en el reconocimiento de partículas virales; en cualquiera de los dos casos, son susceptibles a la infección con el virus. Se encuentran los puntos de equilibrio del sistema y en el caso particular del equilibrio trivial o de ausencia de infección, se determina su estabilidad local con base en el número básico de reproducción. Se efectúa además la simulación numérica del modelo para establecer el comportamiento que presentan las células infectadas y la carga viral, frente a variaciones de algunos de los parámetros. Finalmente, se reformula el modelo considerando respuesta inmune celular de tipo citotóxico y se realiza la simulación numérica.


Nonlinear differential equations were used for formulating a mathematical model describing the dynamics of HIV interaction with CD4 T-cells which are considered to be activated or not activated during recognition of viral particles; in either case they are susceptible to HIV infection. The system's equilibrium points were found and local stability was determined for trivial equilibrium or the absence of infection based on the basic reproduction number. The model was used for numerical simulation to show infected cell and viral load patterns regarding the variations of some parameters. The model was then reformulated, considering a cytotoxic cellular immune response and numerical simulation was run again.


Asunto(s)
Humanos , /inmunología , Citotoxicidad Inmunológica , Infecciones por VIH/inmunología , Modelos Teóricos
9.
Rev. salud pública ; 16(1): 126-138, ene.-feb. 2014. ilus, tab
Artículo en Español | LILACS | ID: lil-717117

RESUMEN

Se construyen dos modelos para la transmisión del VIH considerando exclusivamente transmisión sexual entre pacientes sanos e infectados en una población mezclada; es decir, que no se hace distinción de edad, género ni orientación sexual. El primer modelo es sin control y se consideran tres poblaciones según su estado de infección, la primera corresponde al número promedio de individuos sanos susceptibles de adquirir la infección, la segunda al número promedio de portadores del VIH sin diagnosticar y por último el número promedio de portadores enfermos sin diagnosticar, se asume que las personas susceptibles adquieren el virus por contacto sexual con portadores sanos y con portadores enfermos. En el segundo modelo se incluye control por diagnóstico, en éste se consideran dos poblaciones adicionales que son el número promedio de portadores sanos diagnosticados y el número promedio de portadores enfermos diagnosticados. Con esto se pretende estudiar si es posible el control de la enfermedad exclusivamente por diagnóstico, además se asume que a pesar del diagnóstico, aún es posible que las personas susceptibles adquieran el VIH por contacto con portadores sanos y enfermos, tanto diagnosticados como sin diagnosticar. Finalmente se observa que las simulaciones numéricas brindan evidencia suficiente para determinar que la mejor estrategia de diagnóstico, es decir, con una efectividad del 100 %, no es lo suficientemente efectiva como para reducir significativamente la transmisión del VIH.


Two models were constructed for sexually-transmitted HIV between healthy and infected patients in a mixed population, i.e. no discrimination was made between age, gender or sexual orientation. The first model had no control and considered three populations according to their infection status; the first concerned the average number of susceptible individuals, the second the average number of undiagnosed HIV infected people and the third was concerned with the average number of undiagnosed infected patients (assuming that susceptible people might acquire HIV from diagnosed and undiagnosed infected patients). The second model included control through diagnosis; it considered two additional populations: the average number of diagnosed healthy carriers and diagnosed HIV infected carriers. This was aimed at studying whether the disease can be controlled by diagnosis only. It was also assumed that, despite diagnosis, susceptible people may acquire HIV from both diagnosed and undiagnosed infected patients. It was noted that numerical simulation provided sufficient evidence for determining that the best diagnostic strategy (i.e. having 100 % effectiveness) was not effective enough to significantly reduce HIV transmission.


Asunto(s)
Humanos , Infecciones por VIH/prevención & control , Infecciones por VIH/transmisión , Modelos Teóricos , Infecciones por VIH/diagnóstico
10.
Rev. salud pública ; 12(6): 1020-1032, dic. 2010. ilus, tab
Artículo en Español | LILACS | ID: lil-602850

RESUMEN

Se modela la dinámica de transmisión del dengue clásico en una región endémica considerando el uso de medidas preventivas y de control mecánico en la reducción de la transmisión de la enfermedad. Se plantea un sistema de ecuaciones diferenciales ordinarias que describe la dinámica y mediante simulación numérica se determina su evolución en el tiempo. Se comparan diferentes estrategias de control mecánico y profilaxis con la situación sin control. Se determina el número básico de reproducción R0, mostrando que si R0 > 1 hay un alto riesgo de epidemia y que en caso contrario la enfermedad se mantiene en niveles de bajo impacto; estos resultados se contratan con los obtenidos numéricamente. Se concluye que si bien la profilaxis y el control mecánico por si solos brindan resultados efectivos en el control de la enfermedad, cuando se combinan ambos controles los niveles de infección se ven reducidos significativamente. Niveles de control mecánico y profilaxis cercanos al 60 por ciento son los que brindan resultados adecuados en el control del brote de dengue.


Dengue fever transmission dynamics were studied in an endemic region considering the use of preventative measures and mechanical control in reducing transmission of the disease. A system of ordinary differential equations was proposed, describing the dynamics and their evolution as determined by numerical simulation. Different mechanical control and prophylaxis strategies were compared to the situation without control. The basic reproduction number R0 was determined R0 to show that if R0 > 1 there would be a risk of an epidemic and otherwise the disease would have low impact levels. The basic reproduction number helps determine the dynamics' future pattern and contrast the results so obtained with those obtained numerically. It was concluded that although prophylaxis and mechanical control alone provide effective results in controlling the disease, if both controls are combined then infection levels become significantly reduced. Around 60 percent mechanical control and prevention levels are needed to provide suitable results in controlling dengue outbreaks.


Asunto(s)
Animales , Humanos , Control de Enfermedades Transmisibles/métodos , Dengue/transmisión , Enfermedades Endémicas , Modelos Biológicos , Aedes , Dengue/epidemiología , Dengue/prevención & control , Brotes de Enfermedades/prevención & control , Insectos Vectores , Control de Mosquitos , Densidad de Población
11.
Rev. salud pública ; 12(6): 1033-1041, dic. 2010. ilus, tab
Artículo en Español | LILACS | ID: lil-602851

RESUMEN

El dengue es una enfermedad viral común en zonas tropicales y subtropicales transmitida por mosquitos del género Aedes. El virus es transmitido a los humanos por la picadura de un mosquito hembra infectado. Ya que no existen vacunas que protejan contra la infección, el control de la enfermedad se hace controlando la población adulta o inmadura del mosquito. En este trabajo se modela la dinámica de crecimiento del mosquito sometido a control adulticida y con resistencia al químico. Se hace el análisis del modelo mediante análisis clásico de estabilidad local de sistemas dinámicos, lo que permite determinar el umbral de crecimiento del mosquito y a partir de éste establecer una estrategia adecuada de control químico. Se incluye la simulación numérica para diferentes escenarios con el fin de evaluar si hay diferencias en el comportamiento del sistema cuando la resistencia está presente y cuando no lo está.


Dengue fever is a common vector-borne disease in tropical and subtropical areas. It is transmitted to humans by the bite of an infected female Aedes mosquito. Since no vaccines are currently available which can protect against infection, disease control relies on controlling the mosquito population. This work was aimed at modelling such mosquito's population dynamics regarding chemical control of the adult population and its acquired resistance to chemicals. The model was analysed by using classical dynamic system theory techniques and mosquito growth threshold was determined as this establishes when a particular population may prosper in the environment or when it is likely to disappear. A suitable chemical control strategy was developed from such threshold. Simulations were made in control and non-control scenarios; this determined the degree of control application effectiveness against different levels of acquired resistance.


Asunto(s)
Animales , Femenino , Humanos , Aedes , Dengue/prevención & control , Insectos Vectores , Resistencia a los Insecticidas , Modelos Biológicos , Control de Mosquitos/métodos , Simulación por Computador , Dengue/transmisión , Dinámica Poblacional
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