Hybrid prediction of infections and deaths due to COVID-19 in two Colombian data series.

The prediction of the number of infected and dead due to COVID-19 has challenged scientists and government bodies, prompting them to formulate public policies to control the virus' spread and public health emergency worldwide. In this sense, we propose a hybrid method that combines the SIRD mathematical model, whose parameters are estimated via Bayesian inference with a seasonal ARIMA model. Our approach considers that notifications of both, infections and deaths are realizations of a time series process, so that components such as non-stationarity, trend, autocorrelation and/or stochastic seasonal patterns, among others, must be taken into account in the fitting of any mathematical model. The method is applied to data from two Colombian cities, and as hypothesized, the prediction outperforms the obtained with the fit of only the SIRD model. In addition, a simulation study is presented to assess the quality of the estimators of SIRD model in the inverse problem solution.

Follow-up of Kangaroo Mother Care programmes in the last 28 years: results from a cohort of 57 154 low-birth-weight infants in Colombia.

BACKGROUND: Kangaroo Mother Care (KMC) is an evidence-based intervention focused on premature and low-birth-weight (LBW) infants. In different healthcare systems, outpatient KMC programmes (KMCPs) have been pioneers in the follow-up of these high-risk newborns.Here, we describe an overview analysis performed in an unprecedented data set comprising Colombian infants and spanning 28 years. METHODS: Cohort study of 57 154 infants discharged home in kangaroo position (KP) for follow-up in four KMCPs between 1993 and 2021. RESULTS: At birth and at hospital discharge to a KMCP, median gestational age and weight were 34.5 and 36 weeks, 2000 g and 2200 g, respectively. Chronological age at admission was 8 days. Over time, anthropometric measures at birth and somatic growth during follow-up improved; on the other hand, percentages of mechanical ventilation, intraventricular haemorrhage and need for intensive care decreased as neuropsychomotor, sensory disorders and bronchopulmonary dysplasia incidence at 40 weeks. Risk of cerebral palsy and teenage mothers' frequency was higher in the poorest population. Early home discharge in KP in less than 72 hours was possible in 19% of the cohort. During the COVID-19 pandemic, we observed a more than twofold increase in exclusive breast feeding at 6 months and a reduction in readmission rates. CONCLUSION: This study provides a general overview of KMCPs follow-up during the last 28 years within the Colombian healthcare system. These descriptive analyses have allowed us to structure KMC as an evidence-based method. KMCPs allow close monitoring with regular feedback about preterm or LBW infants' perinatal care, quality of care over time and health status during their first year of life. Monitoring these outcomes is challenging but guarantees access to high-risk infants' care with equity.

Associated factors for mortality in a COVID-19 colombian cohort: is the third wave relevant when Mu variant was predominant epidemiologically?

OBJECTIVES: To evaluate the association between Colombia's third wave when the Mu variant was predominant epidemiologically (until 75%) in Colombia and COVID-19 all-cause in-hospital mortality. METHODS: In this retrospective cohort, we included hospitalized patients ≥18 years with SARS-CoV-2 infection between March 2020 to September 2021 in ten hospitals from three cities in Colombia. Description analysis, survival, and multivariate Cox regression analyses were performed to evaluate the association between the third epidemic wave and in-hospital mortality. RESULTS: A total of 25,371 patients were included. The age-stratified time-to-mortality curves showed differences according to epidemic waves in patients ≥75 years (log-rank test p = 0.012). In the multivariate Cox analysis, the third wave was not associated with increased mortality relative to the first wave (aHR 0.95; 95%CI 0.84-1.08), but there was an interaction between age ≥75 years and the third wave finding a lower HR for mortality (aHR 0.56, 95%CI 0.36-0.86). CONCLUSIONS: We did not find an increase in in-hospital mortality during the third epidemic wave in which the Mu variant was predominant in Colombia. The reduced hazard in mortality in patients ≥75 years hospitalized in the third wave could be explained by the high coverage of SARS-CoV-2 vaccination in this population and patients with underlying conditions.

The Principles of SARS-CoV-2 Intervariant Competition Are Exemplified in the Pre-Omicron Era of the Colombian Epidemic.

The first 18 months of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in Colombia were characterized by three epidemic waves. During the third wave, from March through August 2021, intervariant competition resulted in Mu replacing Alpha and Gamma. We employed Bayesian phylodynamic inference and epidemiological modeling to characterize the variants in the country during this period of competition. Phylogeographic analysis indicated that Mu did not emerge in Colombia but acquired increased fitness there through local transmission and diversification, contributing to its export to North America and Europe. Despite not having the highest transmissibility, Mu's genetic composition and ability to evade preexisting immunity facilitated its domination of the Colombian epidemic landscape. Our results support previous modeling studies demonstrating that both intrinsic factors (transmissibility and genetic diversity) and extrinsic factors (time of introduction and acquired immunity) influence the outcome of intervariant competition. This analysis will help set practical expectations about the inevitable emergences of new variants and their trajectories. IMPORTANCE Before the appearance of the Omicron variant in late 2021, numerous SARS-CoV-2 variants emerged, were established, and declined, often with different outcomes in different geographic areas. In this study, we considered the trajectory of the Mu variant, which only successfully dominated the epidemic landscape of a single country: Colombia. We demonstrate that Mu competed successfully there due to its early and opportune introduction time in late 2020, combined with its ability to evade immunity granted by prior infection or the first generation of vaccines. Mu likely did not effectively spread outside of Colombia because other immune-evading variants, such as Delta, had arrived in those locales and established themselves first. On the other hand, Mu's early spread within Colombia may have prevented the successful establishment of Delta there. Our analysis highlights the geographic heterogeneity of early SARS-CoV-2 variant spread and helps to reframe the expectations for the competition behaviors of future variants.

Socioeconomic disparities associated with mortality in patients hospitalized for COVID-19 in Colombia.

Socioeconomic disparities play an important role in the development of severe clinical outcomes including deaths from COVID-19. However, the current scientific evidence in regard the association between measures of poverty and COVID-19 mortality in hospitalized patients is scant. The objective of this study was to investigate whether there is an association between the Colombian Multidimensional Poverty Index (CMPI) and mortality from COVID-19 in hospitalized patients in Colombia from May 1, 2020 to August 15, 2021. This was an ecological study using individual data on hospitalized patients from the National Institute of Health of Colombia (INS), and municipal level data from the High-Cost Account and the National Administrative Department of Statistics. The main outcome variable was mortality due to COVID-19. The main exposure variable was the CMPI that ranges from 0 to 100% and was categorized into five levels: (i) level I (0%-20%), (ii) level II (20%-40%), (iii) level III (40%-60%), (iv) level IV (60%-80%); and (v) level V (80%-100%). The higher the level, the higher the level of multidimensional poverty. A Bayesian multilevel logistic regression model was applied to estimate Odds Ratio (OR) and their corresponding 95% credible intervals (CI). In addition, a subgroup analysis was performed according to the epidemiological COVID-19 waves using the same model. The odds for dying from COVID-19 was 1.46 (95% CI 1.4-1.53) for level II, 1.41 (95% CI 1.33-1.49) for level III and 1.70 (95% CI 1.54-1.89) for level IV hospitalized COVID-19 patients compared with the least poor patients (CMPI level I). In addition, age and male sex also increased mortality in COVID-19 hospitalized patients. Patients between 26 and 50 years-of-age had 4.17-fold increased odds (95% CI 4.07-4.3) of death compared with younger than 26-years-old patients. The corresponding for 51-75 years-old patients and those above the age of 75 years were 9.17 (95% CI 8.93-9.41) and 17.1 (95% CI 16.63-17.56), respectively. Finally, the odds of death from COVID-19 in hospitalized patients gradually decreased as the pandemic evolved. In conclusion, socioeconomic disparities were a major risk factor for mortality in patients hospitalized for COVID-19 in Colombia.

Quantification of impact of COVID-19 pandemic on cancer screening programmes - a case study from Argentina, Bangladesh, Colombia, Morocco, Sri Lanka, and Thailand.

It is quite well documented that the COVID-19 pandemic disrupted cancer screening services in all countries, irrespective of their resources and healthcare settings. While quantitative estimates on reduction in volume of screening tests or diagnostic evaluation are readily available from the high-income countries, very little data are available from the low- and middle-income countries (LMICs). From the CanScreen5 global cancer screening data repository we identified six LMICs through purposive sampling based on the availability of cancer screening data at least for the years 2019 and 2020. These countries represented those in high human development index (HDI) categories (Argentina, Colombia, Sri Lanka, and Thailand) and medium HDI categories (Bangladesh and Morocco). No data were available from low HDI countries to perform similar analysis. The reduction in the volume of tests in 2020 compared to the previous year ranged from 14.1% in Bangladesh to 72.9% in Argentina (regional programme) for cervical screening, from 14.2% in Bangladesh to 49.4% in Morocco for breast cancer screening and 30.7% in Thailand for colorectal cancer screening. Number of colposcopies was reduced in 2020 compared to previous year by 88.9% in Argentina, 38.2% in Colombia, 27.4% in Bangladesh, and 52.2% in Morocco. The reduction in detection rates of CIN 2 or worse lesions ranged from 20.7% in Morocco to 45.4% in Argentina. Reduction of breast cancer detection by 19.1% was reported from Morocco. No association of the impact of pandemic could be seen with HDI categories. Quantifying the impact of service disruptions in screening and diagnostic tests will allow the programmes to strategize how to ramp up services to clear the backlogs in screening and more crucially in further evaluation of screen positives. The data can be used to estimate the impact on stage distribution and avoidable mortality from these common cancers.

Epidemiology and healthcare resource utilization in atopic dermatitis in Colombia: A retrospective analysis of data from the National Health Registry from 2015 to 2020 / Epidemiología y uso de recursos de salud en dermatitis atópica en Colombia: análisis retrospectivo de datos del Registro Nacional de Salud de 2015 a 2020

Introduction: Atopic dermatitis, also known as eczema or atopic eczema, is a chronic inflammatory skin disorder characterized by the presence of pruritus accompanied by itching. In Colombia, epidemiological and healthcare resource utilization information regarding this pathology is limited. Objective: To describe atopic dermatitis epidemiological characteristics and healthcare resource utilization patterns in Colombia. Material and methods: A retrospective database study using real-world data obtained from the national claims database SISPRO (Sistema de Información para la Protección Social) for the 2015-2020 period was carried out. Sociodemographic (age, and health services delivery), epidemiological (incidence, prevalence, and comorbidities), and healthcare resource utilization data were extracted from the SISPRO database. Results: The epidemiological results showed increased incidence and prevalence of atopic dermatitis in Colombia in the 2018-2019 period compared to 2015-2017. Accordingly, the number of medical consultations (particularly with specialists), the number of procedures, and the number of hospitalizations of patients with atopic dermatitis increased. Topic and systemic corticoids were the most frequently prescribed drugs. Conclusions: Diagnoses of atopic dermatitis in Colombia increased with a concomitant increase in healthcare resource utilization during 2015-2020, which was possibly slowed down by the arrival of the Covid-19. This study may help physicians gaining a better understanding of the disease, improving atopic dermatitis patient management.

Introducción. La dermatitis atópica, también conocida como eczema o eczema atópico, es un trastorno inflamatorio crónico de la piel caracterizado por la presencia de prurito acompañado de picor. En Colombia, la información epidemiológica y de utilización de recursos sanitarios sobre esta enfermedad es limitada. Objetivo. Describir las características epidemiológicas y los patrones de utilización de recursos sanitarios para la dermatitis atópica en Colombia. Material y métodos. Se trata de un estudio retrospectivo en el cual se utilizan datos de la práctica clínica real obtenidos del registro nacional SISPRO (Sistema de Información para la Protección Social) en el período 2015-2020. Se extrajeron datos sociodemográficos (incluida la edad y la prestación de servicios de salud), epidemiológicos (incluidos la incidencia, la prevalencia y las comorbilidades) y los correspondientes a la utilización de los recursos sanitarios. Resultados. Los resultados epidemiológicos han demostrado un aumento de la incidencia y prevalencia de la dermatitis atópica en Colombia en el periodo 2018-2019, en comparación con el periodo 2015-2017. Aumentó el número de consultas médicas (particularmente, con especialistas) de pacientes con dermatitis atópica, el de procedimientos y el de hospitalizaciones. Los corticoides tópicos y sistémicos fueron los medicamentos más prescritos. Conclusiones. Los diagnósticos de dermatitis atópica en Colombia aumentaron con un incremento concomitante en la utilización de recursos sanitarios durante 2015-2020, que posiblemente se vio atenuado por la llegada del Covid-19. Este estudio puede ayudar a los médicos a tener un mejor conocimiento de la enfermedad y, por lo tanto, mejorar el tratamiento de los pacientes con dermatitis atópica.

Country and policy factors influencing the implementation of primary care-based alcohol screening: A comparison of Colombia, Mexico and Peru.

Researchers and practitioners recognise the importance of context when implementing healthcare interventions, but the influence of wider environment is rarely mapped. This paper identifies the country and policy-related factors potentially explaining the country differences in outcomes of an intervention focused on improving detection and management of heavy alcohol use in primary care in Colombia, Mexico and Peru. Qualitative data obtained through interviews, logbooks and document analysis are used to explain quantitative data on number of alcohol screenings and screening providers in each of the countries. Existing alcohol screening standards in Mexico, and policy prioritisation of primary care and consideration of alcohol as a public health issue in Colombia and Mexico positively contributed to the outcome, while the COVID-19 pandemic had a negative impact. In Peru, the context was unsupportive due to a combination of: political instability amongst regional health authorities; lack of focus on strengthening primary care due to the expansion of community mental health centres; alcohol considered as an addiction rather than a public health issue; and the impact of COVID-19 on healthcare. We found that wider environment-related factors interacted with the intervention implemented and can help explain country differences in outcomes.

Changes in birth outcomes and utilization of prenatal care during the COVID-19 pandemic in 2020: a secondary analysis of vital statistics in Colombia.

BACKGROUND: Birth outcomes could have been affected by the COVID-19 pandemic through changes in access to prenatal services and other pathways. The aim of this study was to examine the effects of the COVID-19 pandemic on fetal death, birth weight, gestational age, number of prenatal visits, and caesarean delivery in 2020 in Colombia. METHODS: We conducted a secondary analysis of data on 3,140,010 pregnancies and 2,993,534 live births from population-based birth certificate and fetal death certificate records in Colombia between 2016 and 2020. Outcomes were compared separately for each month during 2020 with the same month in 2019 and pre-pandemic trends were examined in regression models controlling for maternal age, educational level, marital status, type of health insurance, place of residence (urban/rural), municipality of birth, and the number of pregnancies the mother has had before last pregnancy. RESULTS: We found some evidence for a decline in miscarriage risk in some months after the pandemic start, while there was an apparent lagging increase in stillbirth risk, although not statistically significant after correction for multiple comparisons. Birth weight increased during the onset of the pandemic, a change that does not appear to be driven by pre-pandemic trends. Specifically, mean birth weight was higher in 2020 than 2019 for births in April through December by about 12 to 21 g (p < 0.01). There was also a lower risk of gestational age at/below 37 weeks in 2020 for two months following the pandemic (April, June), but a higher risk in October. Finally, there was a decline in prenatal visits in 2020 especially in June-October, but no evidence of a change in C-section delivery. CONCLUSIONS: The study findings suggest mixed early effects of the pandemic on perinatal outcomes and prenatal care utilization in Colombia. While there was a significant decline in prenatal visits, other factors may have had counter effects on perinatal health including an increase in birth weight on average.

Mapping Eastern (EEE) and Venezuelan Equine Encephalitides (VEE) among Equines Using Geographical Information Systems, Colombia, 2008-2019.

INTRODUCTION: Eastern equine encephalitis virus (EEEV) and Venezuelan equine encephalitis virus (VEEV) viruses are zoonotic pathogens affecting humans, particularly equines. These neuroarboviruses compromise the central nervous system and can be fatal in different hosts. Both have significantly influenced Colombia; however, few studies analyse its behaviour, and none develop maps using geographic information systems to characterise it. OBJECTIVE: To describe the temporal-spatial distribution of those viruses in Colombia between 2008 and 2019. METHODS: Retrospective cross-sectional descriptive study, based on weekly reports by municipalities of the ICA, of the surveillance of both arboviruses in equines, in Colombia, from 2008 to 2019. The data were converted into databases in Microsoft Access 365®, and multiple epidemiological maps were generated with the Kosmo RC1®3.0 software coupled to shape files of all municipalities in the country. RESULTS: In the study period, 96 cases of EEE and 70 of VEE were reported, with 58% of EEE cases occurring in 2016 and 20% of EEV cases in 2013. The most affected municipalities for EEE corresponded to the department of Casanare: Yopal (20), Aguazul (16), and Tauramena (10). In total, 40 municipalities in the country reported ≥1 case of EEE. CONCLUSIONS: The maps allow a quick appreciation of groups of neighbouring municipalities in different departments (1° political division) and regions of the country affected by those viruses, which helps consider the expansion of the disease associated with mobility and transport of equines between other municipalities, also including international borders, such as is the case with Venezuela. In that country, especially for EEV, municipalities in the department of Cesar are bordering and at risk for that arboviral infection. there is a high risk of equine encephalitis outbreaks, especially for VEE. This poses a risk also, for municipalities in the department of Cesar, bordering with Venezuela.

[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.

[Risk of transmission of SARS-CoV-2: multi-criteria spatial evaluation in a municipality of Colombia, 2020]. / Riesgo de transmisión de SARS-CoV-2: evaluación espacial multicriterio en un municipio de Colombia, 2020.

OBJECTIVE: To zoning the risk of SARS-CoV-2 transmission in Villavicencio, Colombia, through a multi-criteria spatial evaluation. MATERIALS AND METHODS: A multi-criteria evaluation model was implemented, through a hierarchical analysis process, integrated into a Geographic Information System. As criteria, descriptive attributes of the threats and vulnerabilities of viral transmission identified by means of an epidemiological model were included, on the same dimensionless numerical scale and proportional to the probability of contagion; the alternatives evaluated correspond to spatial entities represented by pixels. The criteria were weighted according to the expert judgment of the evaluators, with whom the calculation of a normalized matrix of relative priorities was performed, which allowed the estimation of a vector of weights, the degree of inconsistency of which was admissible. The magnitude of the risk was calculated with a weighted summation of the evaluation of the criteria, according to a map algebra geoprocessing. RESULTS: The spatial heterogeneity of the risk of SARS-CoV-2 transmission was described in Villavicencio, allowing the identification of the areas with the highest probability of transmission, located in neighborhoods characterized by high socioeconomic vulnerability. CONCLUSIONS: The cartographic representation derived from the implementation of a multicriteria model, integrated to a Geographical Information System, in the SARS-CoV-2 transmission risk analysis, constitutes a relevant methodological contribution for decision-making defining strategies of mitigation at the local level, facilitating the location and optimization of resources by the health authorities.

Colombian Ocular Diseases Epidemiology Study (CODES): incidence and sociodemographic characterisation of keratoconus between 2015 and 2020.

OBJECTIVE: To estimate the incidence and describe the demographic characteristics of keratoconus (KC) in Colombia using national health registry data between January 1st 2015 and December 31th 2020. METHODS AND ANALYSIS: We conducted a nationwide, population-based study using the Integrated Social Protection Information System from the Colombian Ministry of Health, the unique official database in the country. We used the International Classification of Diseases code for KC (H186) to identify the number of new cases of KC and estimate the incidence rates both overall and according to age and sex. We made a standard morbidity ratio map to graph Colombia's morbidity risk of KC onset. RESULTS: Of 50 372 424 subjects, 21 710 had KC between 2015 and 2020. However, due to the COVID-19 pandemic, all the incidence rates of this study were based on the 18 419 reported until 2019. The incidence rate in the general population was 10.36 (95% CI 10.08 to 10.64) per 100 000 inhabitants. The incidence peak among males was in their early 20s and females in their late 20s. The overall male to female incidence rate ratio was 1.60. Regarding the distribution of the disease, most cases were reported in Bogotá (48.64%), Antioquia (14.04%) and Cundinamarca (10.38%). CONCLUSION: We performed the first nationwide, population-based study of KC in Latin America, finding distribution patterns similar to those reported in the literature. This study provides valuable information on the epidemiology of KC in Colombia, which is helpful in the development of policies for the diagnosis, prevention and treatment of the disease.

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

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.

[Underlying conditions on the southern border between Colombia and Venezuela to face the COVID-19 pandemic]. / Condiciones en la frontera sur entre Colombia y Venezuela ante la pandemia de COVID-19.

OBJECTIVES: To size human migration on the southern border between Colombia and Venezuela (Guainía department), and characterize the social, access and health care conditions relevant to the COVID-19 pandemic. METHODS: Mixed epidemiological and ethnographic study. Rate of Venezuelan migrants was calculated according to Migration Colombia data until December 31st, 2019, also effective access to medical care, and provision of health posts were calculated, with information from each Guainía health post collected from June 2017 to June 2019, through semi-structured interviews, participant observations, Google Earth™ and Wikiloc™. Stata™ was used to calculate and graph median times of effective access. Cultural dynamics and health care conditions were described by the field work information and a permanent documentary review. RESULTS: Guainía is the 23rd department, according to the total number of Venezuelans, but the fourth in Venezuelans density (14,4%). In the Guainía river, the median times to the real reference health institution were 8,7 hours in winter and 12,3 in summer, and complex cases require air referrals. In the Inírida river, the median times to the real reference health institution were 11,9 hours in winter and 16,1 in summer. Only 57% of the health posts had supplies for acute respiratory infections. CONCLUSIONS: Facing COVID-19 in south border territories, it is necessary to immediately strengthen medical and public health services to avoid high fatality rates.

[Impact of the COVID-19 pandemic on the Colombian population according to mitigation measures. Preliminary data from epidemiological models for the period March 18 to April 18, 2020]. / Proyecciones de impacto de la pandemia COVID-19 en la población colombiana, según medidas de mitigación. Datos preliminares de modelos epidemiológicos para el periodo del 18 de marzo al 18 de abril de 2020.

INTRODUCTION: First case of COVID-19 in Colombia was diagnosed on March 6th. Two weeks later, cases have rapidly increased, leading the government to establish some mitigation measures. OBJECTIVES: The first objective is to estimate and model the number of cases, use of hospital resources and mortality by using different R0 scenarios in a 1-month scenario (from March 18 to April 18, 2020), based on the different isolation measures applied. This work also aims to model, without establishing a time horizon, the same outcomes given the assumption that eventually 70% of the population will be infected. MATERIALS AND METHODS: Data on the number of confirmed cases in the country as of March 18, 2020 (n=93) were taken as the basis for the achievement of the first objective. An initial transmission rate of R0= 2.5 and a factor of 27 for undetected infections per each confirmed case were taken as assumptions for the model. The proportion of patients who may need intensive care or other in-hospital care was based on data from the Imperial College of London. On the other hand, an age-specific mortality rate provided by the Instituto Superiore di Sanità in Italy was used for the second objective. RESULTS: Based on the 93 cases reported as of March 18, if no mitigation measures were applied, by April 18, the country would have 613 037 cases. Mitigation measures that reduce R0 by 10% generate a 50% reduction in the number of cases. However, despite halving the number of cases, there would still be a shortfall in the number of beds required and only one in two patients would have access to this resource. CONCLUSION: This model found that the mitigation measures implemented to date by the Colombian government and analyzed in this article are based on sufficient evidence and will help to slow the spread of SARS-CoV-2 in Colombia. Although a time horizon of one month was used for this model, it is plausible to believe that, if the current measures are sustained, the mitigation effect will also be sustained over time.

[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.

[Behavior by sex and gender of the COVID-19 pandemic in Colombia]. / Comportamiento por sexo y género de la pandemia de COVID-19 en Colombia.

OBJECTIVE: To determine the importance of mainstreaming from the perspective of sex-gender and age to recognize the differences and their inequality in the current situation of COVID-19. MATERIALS AND METHODS: Quantitative, exploratory, non-experimental, cross-sectional approach. Polynomial regressions were determined that better explain the current trends for sex-gender and age, the corresponding R2 was calculated. RESULTS: The trends of confirmed contagion cases are very similar between men and women. In deaths there is a greater relationship between men than women. Regarding age, there are differences in confirmed cases concentrated between 21 and 60 years and in those who died in those over 50 years of age. CONCLUSIONS: The COVID-19 pandemic affects both sexes. However, the number of death men is higher than that of women. Regarding age, contagion is concentrated between 21 and 60 years, mortality in over 50 years. The information provided by the National Institute of Health of Colombia is limited, but it has good characteristics in age groups, although improvements can be made based on sex-gender in terms of race, health personnel, the military, and the policemen infected by COVID-19.

OBJETIVO: Determinar la importancia de la transversalidad desde la prespectiva del sexo-género y edad para reconocer las diferencias y su desigualdad en la actual situación de COVID-19. MATERIALES Y MÉTODOS: Enfoque cuantitativo, exploratorio, no experimemental, de corte transversal. Se determinaron regresiones polinomiales que explican mejor las tendencias actuales para sexo-género y edad y se calculó el correspondiente R2. RESULTADOS: Las tendencias de casos de contagios confirmados son muy similares entre hombres y mujeres. En fallecimientos, existe una mayor relación entre hombres que en mujeres. En cuanto a la edad, existen diferencias en los casos confirmados concentrados entre 21 y 60 años y en los fallecidos en mayores de 50 años. CONCLUSIONES: La pandemia de COVID-19 afecta a ambos sexos. Sin embargo, es más alto el número de hombres fallecidos que de mujeres. En cuanto a la edad, se concentra el contagio entre los 21 y 60 años y la mortalidad en mayores de 50 años. La información suministrada por el Instituto Nacional de Salud de Colombia es limitada, pero cuenta con buenas características en grupos de edad pese a que se pueden realizar mejoras en función del sexo-género en cuanto a raza, el personal de salud, las fuerzas militares y la policía nacional infectados de COVID-19.

[SARS-C0V.2/COVID-I9 in Colombia: tendencies, predictions, and tensions about health system]. / SARS-COV.2/COVID-19 en Colombia: tendencias, predicciones y tensiones sobre el sistema sanitario.

OBJECTIVE: To analyze the temporal progress in the early stage of COVID-19 in Colombia using the SIRD model. METHODS: We analyzed the temporal progress of COVID-19 based on the number of infected persons between March 6th and April 15th, 2020. The SIRD model was implemented with variation in the rate of transmission (b) in three ways. A. Quarantine until July 11. 2. B. Flexible quarantine, [b=4%]. C. Flexible quarantine2 [b=8%]. Consecutively, we aimed to predict the number of total cases and 5% of infected persons in ICU to match them with the hospital beds and ICU staff. RESULTS: The results show that the number of COVID-19 cases will increase from 54 105 to 116 081 approximately, if the quarantine is lifted on May 11. If the infection rate increase, more hospital beds and a bigger ICU staff will be mandatory. The currently 2 650 beds won't be enough in the flexible quarantine2, and five intensive care specialist and four nurses per patient will be needed. CONCLUSION: Measures like mandatory social distancing help delay the saturation of the health care system. However, it's impracticable to maintain them due to a possible economic crisis. Therefore, it's necessary to take action to enhance the ability of the health care system to avoid a collapse.

[Mathematical models for COVID-19 infection estimation: essential considerations and projections in Colombia]. / Modelos matemáticos estimadores de la infección por COVID-19: consideraciones esenciales y proyecciones en Colombia.

OBJECTIVE: To estimate the COVID-19 infection behavior in Colombia using mathematical models. METHODS: Two mathematical models were constructed to estimate imported confirmed cases and related confirmed cases of COVID-19 infection in Colombia, respectively. The phenomenology of imported confirmed cases is modeled with sigmoidal function, while related confirmed cases are modeled using a combination of exponential functions and polynomial algebraic functions. The fitting algorithms based on least squares methods and direct search methods are used to determine the parameters of the models. RESULTS: The sigmodial model performs a highly convergent estimation of the reported confirmed cases of COVID-19 infection to May 28, 2020. This model achieved a prediction error of 0.5 % measured using the normalized root mean square error. The model of the confirmed cases reported as related shows a 3.5 % prediction error and a low bias of -0.01 associated with overestimation. CONCLUSIONS: This work shows that the mathematical models allow to predict the behavior of the infection efficiently and effectively by COVID 19 in Colombia when the imported cases and the related cases of infection are independently considered.

OBJETIVO: Estimar el comportamiento de la infección por COVID-19 en Colombia mediante modelos matemáticos. MÉTODOS: Se construyeron dos modelos matemáticos para estimar los casos confirmados importados y los casos confirmados relacionados de la infección por COVID-19 en Colombia, respectivamente. La fenomenología de los casos confirmados importados es modelada con una función sigmoidal, mientras que los casos confirmados relacionados son modelados mediante una combinación de funciones exponenciales y funciones algebraicas polinomiales. Se utilizan algoritmos de ajuste basados en métodos de mínimos cuadrados y métodos de búsqueda directa para la determinación de los parámetros de los modelos. RESULTADOS: El modelo sigmodial realiza una estimación altamente convergente de los datos reportados, al 28 de mayo de 2020, de los casos confirmados importados de infección por COVID-19. El modelo muestra un error de predicción de 0,5%, que se mide usando la raíz del error cuadrático medio normalizado. El modelo para los casos confirmados reportados como relacionados muestra un error en la predicción del 3,5 % y un sesgo bajo del -0,01 asociado a la sobrestimación. CONCLUSIONES: El presente trabajo evidencia que los modelos matemáticos permiten eficaz y efectivamente predecir el comportamiento de la infección por COVID-19 en Colombia cuando los casos importados y los casos relacionados de infección son consideradores de manera independiente.