Children are more vulnerable to environmental exposures determinant of respiratory diseases due to their dynamic developmental physiology. Whereas social determinants of health are also associated with a higher risk of these diseases in children exposed to environmental risk factors, most studies incorporate them as covariates in the statistical analysis rather than focusing on specific vulnerable populations. In this study a systematic review searched and selected studies of respiratory diseases in children with socioeconomic disadvantage to identify the environmental risk factors associated with these diseases. The review followed the PRISMA protocol to identify eleven eligible studies of children with socioeconomic conditions that included low income and low socioeconomic status, overcrowding, adults with low education level and Indigenous status. Infectious respiratory diseases, asthma, rhinitis and mortality due to respiratory diseases were associated with risk factors such as biomass fuel use, tobacco smoking, particulate matter, coal dust and other pollutants including ozone, nitrogen dioxide and sulphur dioxide. The most common associations were between respiratory infections and household air pollution and asthma with indoor and outdoor air pollution. The findings support previous reports on these associations and suggest that specific vulnerabilities such as indigenous children and living with adults with low socioeconomic status and education level increase the risk of respiratory diseases. These populations can be given special attention to prioritize public health interventions to lower the burden of disease of respiratory diseases in children.

El ciclo básico de los programas de medicina se compone de asignaturas caracterizadas por ser enseñadas de manera tradicionalista, presentar contenidos complejos y en constante actualización, generando dificultades y rechazo en los aprendices. Por este motivo, el presente trabajo tuvo como objetivo analizar la incidencia del conectivismo de George Siemens en el proceso de aprendizaje en red en los cursos de Bioquímica y Biología Molecular, pues esta teoría propone herramientas para mejorar el aprendizaje de los estudiantes, a través de su inmersión, navegación y construcción de redes de aprendizaje atractivas, autogestionadas y mediadas por tecnología. Se realizó una investigación de corte cualitativo, basado en la metodología de investigación acción, el aprendizaje basado en problemas y características propias del conectivismo, con estudiantes de pregrado de primer semestre de Medicina. La población considerada en esta investigación fueron estudiantes de las carreras del área de la salud que, dentro de sus cursos formativos, debían cursar asignaturas relacionadas con bioquímica y biología molecular. Se aplicaron cuestionarios de entrada y de salida, de y se aplicaron entrevistas a los participantes, como parte del diseño de una unidad didáctica, encaminada hacia la construcción de Blogs sobre la respiración celular, estudiada desde diversos procesos fisiológicos humanos. El conectivismo facilitó y motivó a los estudiantes a explorar las herramientas que tiene a su disposición y desconoce, los invitó a construir su propia red de aprendizaje y a gestionar su proceso formativo.

Morbidity statistics can be reported as grouped data for health services rather than for individual residence area, especially in low-middle income countries. Although such reports can support some evidence-based decisions, these are of limited use if the geographical distribution of morbidity cannot be identified. This study estimates the spatial rate of Acute respiratory infections (ARI) in census districts in Cúcuta -Colombia, using an analysis of the spatial distribution of health services providers. The spatial scope (geographical area of influence) of each health service was established from their spatial distribution and the population covered. Three levels of spatial aggregation were established considering the spatial scope of primary, intermediate and tertiary health services providers. The ARI cases per census district were then calculated and mapped using the distribution of cases per health services provider and the proportion of population per district in each level respectively. Hotspots of risk were identified using the Local Moran’s I statistic. There were 98 health services providers that attended 8994, 18,450 and 91,025 ARI cases in spatial levels 1, 2 and 3, respectively. Higher spatial rates of ARI were found in districts in central south; northwest and northeast; and southwest Cúcuta with hotspots of risk found in central and central south and west and northwest Cucuta. The method used allowed overcoming the limitations of health data lacking area of residence information to implementing epidemiological analyses to identify at risk communities. This methodology can be used in socioeconomic contexts where geographic identifiers are not attached to health statistics.

Background Acute respiratory infections (ARI) in Cúcuta -Colombia, have a comparatively high burden of disease associated with high public health costs. However, little is known about the epidemiology of these diseases in the city and its distribution within suburban areas. This study addresses this gap by estimating and mapping the risk of ARI in Cúcuta and identifying the most relevant risk factors. Methods A spatial epidemiological analysis was designed to investigate the association of sociodemographic and environmental risk factors with the rate of ambulatory consultations of ARI in urban sections of Cúcuta, 2018. The ARI rate was calculated using a method for spatial estimation of disease rates. A Bayesian spatial model was implemented using the Integrated Nested Laplace Approximation approach and the Besag-York-Mollié specification. The risk of ARI per urban section and the hotspots of higher risk were also estimated and mapped. Results A higher risk of IRA was found in central, south, north and west areas of Cúcuta after adjusting for sociodemographic and environmental factors, and taking into consideration the spatial distribution of the city’s urban sections. An increase of one unit in the percentage of population younger than 15 years; the Index of Multidimensional Poverty and the rate of ARI in the migrant population was associated with a 1.08 (1.06—1.1); 1.04 (1.01—1.08) and 1.25 (1.22—1.27) increase of the ARI rate, respectively. Twenty-four urban sections were identified as hotspots of risk in central, south, north and west areas in Cucuta. Conclusion Sociodemographic factors and their spatial patterns are determinants of acute respiratory infections in Cúcuta. Bayesian spatial hierarchical models can be used to estimate and map the risk of these infections in suburban areas of large cities in Colombia. The methods of this study can be used globally to identify suburban areas and or specific communities at risk to support the implementation of prevention strategies and decision-making in the public and private health sectors.

Effective analysis to support decision-making in public health requires adequate data that can be linked to the sociodemographic characteristics and distribution of communities that would be recipients of health programs. Although official statistics are an important source of data to support decisions on public health strategies, health statistics are of limited use if they do not include categorisations related to the spatial distribution of the population. This study introduces a method to use the frequency of disease reported by health care providers (HCP) to calculate disease rates in geographical areas in urban settings. Specifically, this study uses statistics on acute respiratory infections (ARI) to calculate the rate of these diseases at the census district level in Cucuta, a major city in Colombia. A Geographic Information System was used to establish the geographical area of influence (spatial scope) of each HCP, according to the distribution of the basic census geographical areas; the Urban Sections (USEC), in Cucuta. Three levels of increasing spatial aggregation were established considering the characteristics of the population receiving health care in primary, intermediate and tertiary public health services to establish the spatial scope of each HCP. The cases of ARI per USEC were calculated according to the proportion of the population of each USEC in each of the three levels. The spatial rate of ARI per USEC and the hotspots of higher risk of ARI were calculated using an Empirical Bayes method using a geostatistical software. There were 97 HCP, of which, 31 provided health services in USEC in level 1; 20 provided health services in USEC in level 2; and 47 provided health services in USEC in level 3. A higher spatial rate of ARI was found in USEC in central south; central west; north and northwest; northeast; central east; and central regions, compared to the whole of Cucuta. Hotspots of higher risk were identified in two clusters of USEC in central south and west Cucuta and three isolated USEC in central and northwest Cucuta. Health indicators at the census district geographical level could be calculated using basic statistics that do not include geographic identifiers by considering the characteristics of the HCP and the population receiving their services. The methodology of this study can be applied to other socioeconomic contexts where geographic identifiers are not attached to public health statistics to create better public health indicators and support potential health promotion and disease prevention strategies.

Research on urban biodiversity has primarily addressed the effects of urbanization and human activity synergistically as it has been virtually impossible to dissociate their impact on city wildlife. However, the anthropause resulting from COVID–19 lockdowns provided an unprecedented scenario to study the relative role of human activity on avian communities. Here we provide evidence of the relationships between human activity and bird species richness in urban areas of Colombia during its strict and subsequent relaxed lockdowns. Once the strict lockdown was lifted and human activity increased, avian species richness decreased by 32 % in 46 % of our sampling sites. Although the strict lockdown lasted only six weeks, local assemblages (mainly from low–intensity urbanization peri–urban sites) swiftly became more diverse. Our findings highlight the importance of taking human activity into account when planning cities, with important focus on greenspaces, if our aim is to conserve and enhance urban biodiversity. Such plans will require not only the cooperation of local governments but also greater awareness among the local population regarding the importance of creating livable, healthy, biodiverse, and resilient cities.