Chronic disease prevalence in a population with structural hemoglobin disorders undergoing diabetes diagnosis: A bayesian approach.

Background: Structural disorders of hemoglobin are a group of rare and fatal genetic diseases that disrupt the transport and exchange of oxygen in the blood, causing tissue damage and ultimately leading to chronic conditions. The hemoglobin (Hb) S variant predominantly impacts individuals of Afro-descendant heritage. A significant concentration of the Afro-descendant population in Colombia, notably 12.5 %, is found in the city of Cali. Previous research has identified this city's structural hemoglobin disorders prevalence rate of 3.78 %. The aim of this study was to determine the prevalence of HbC, HbS, HbF, and HbA2 variants within a population who underwent HbA1c testing, as well as the prevalence of chronic diseases among patients with these hemoglobin alterations, at a high-complexity hospital in the city of Cali from 2015 to 2019. Methods: A descriptive observational study was conducted, involving a study population that comprised patients with both suspected and monitored diagnoses of diabetes. The cohort was selected from a high-complexity hospital in Cali. A total of 15,608 patients were included in the analysis, all of whom underwent HbA1C measurement through capillary electrophoresis, which also offers an indirect diagnosis of certain structural disorders of hemoglobin. Bayesian methods were employed for frequency analysis. Results: Among the 15,608 patients assessed, 63.6 % (n = 9920) were women. The overall prevalence of structural hemoglobin disorders was 1.98 % (n = 287, 95 % CI = 1.77 %-2.21 %). The co-occurrence of diabetes and kidney disease emerged as the most prevalent combination of pathologies observed in individuals with HbC, for both men and women across various age groups: 18-42 (58.3 % and 50.0 % respectively), 43-55 (50.0 % for both), 56-65 (50.0 % and 37.5 % respectively), and >65 years (66.7 % and 57.1 % respectively). Conclusions: The observed prevalence of the studied variants exceeded 1 %, a threshold underscored by the World Health Organization (WHO) as epidemiologically significant. Among HbC and HbS-positive patients, the elevated prevalence of diabetes and kidney disease is a guiding factor in developing proactive prevention strategies.

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)

Análisis espacio-temporal del SARS-COV-2 en Cali, Colombia / SARS-coV-2 spatio - temporal analysis in Cali, Colombia

RESUMEN Objetivo Describir la distribución espacio-temporal del COVID-19 en la ciudad de Cali durante el primer mes de epidemia. Métodos Se realizó un análisis exploratorio de datos espaciales, compuesto por un análisis de densidad de Kernel y se verificó la presencia de patrones espaciales por medio de la función K de Ripley. Resultados La distribución espacial de los casos tiende a concentrarse inicialmente en el norte y sur de la ciudad, con una dinámica cambiante hacia el oriente y occidente. Conclusiones El patrón espacial identificado puede estar influenciado por las medidas de aislamiento tomadas a nivel local y nivel nacional, además no se puede descartar el efecto del poco acceso que tiene la población general a las pruebas diagnósticas, los retrasos y represamientos para conocer los resultados de las mismas y aun los posibles sesgos por dificultades en la técnica de toma de la muestra o su conservación.(AU)

ABSTRACT Objective To describe the spatio-temporal distribution of the COVID-19 in the city of Cali during the first month of the epidemic. Methods An exploratory analysis of spatial data was carried out, consisting of a kernel density analysis and the presence of spatial patterns was verified by the K-Ripley function. Results The spatial distribution of the cases tends to initially concentrate in the north and south of the city, with a changing dynamic towards the east and west. Conclusions The identified spatial pattern may be influenced by the isolation measures taken at the local and national level, but the effect of the low access of the general population to diagnostic tests, delays and restraints to know the results cannot be ruled out and even possible biases due to difficulties in the technique of taking the sample or its conservation.(AU)

Objetivo: Descrever a distribuição espaço-temporal do COVID-19 na cidade de Cali durante o primeiro mês da epidemia. Métodos: Foi realizada uma análise exploratória de dados espaciais, consistindo em uma análise de densidade de kernel e a presença de padrões espaciais foi verificada pela função K-Ripley. Resultados: A distribuição espacial dos casos tende a se concentrar inicialmente no norte e no sul da cidade, com uma dinâmica mutante para o leste e oeste. Conclusões: O padrão espacial identificado pode ser influenciado pelas medidas de isolamento tomadas a nível local e nacional, mas não se pode descartar o efeito do baixo acesso da população em geral aos exames diagnósticos, atrasos e limitações para conhecer os resultados e mesmo possíveis vieses devido às dificuldades na técnica de coleta da amostra ou na sua conservação.(AU)

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

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.

[SARS-coV-2 spatio - temporal analysis in Cali, Colombia]. / Análisis espacio-temporal del SARS-COV-2 en Cali, Colombia.

OBJECTIVE: To describe the spatio-temporal distribution of the COVID-19 in the city of Cali during the first month of the epidemic. METHODS: An exploratory analysis of spatial data was carried out, consisting of a kernel density analysis and the presence of spatial patterns was verified by the K-Ripley function. RESULTS: The spatial distribution of the cases tends to initially concentrate in the north and south of the city, with a changing dynamic towards the east and west. CONCLUSIONS: The identified spatial pattern may be influenced by the isolation measures taken at the local and national level, but the effect of the low access of the general population to diagnostic tests, delays and restraints to know the results cannot be ruled out and even possible biases due to difficulties in the technique of taking the sample or its conservation.