Mapping Malaria Vector Habitats in West Africa: Drone Imagery and Deep Learning Analysis for Targeted Vector Surveillance.

Disease control programs are needed to identify the breeding sites of mosquitoes, which transmit malaria and other diseases, in order to target interventions and identify environmental risk factors. The increasing availability of very-high-resolution drone data provides new opportunities to find and characterize these vector breeding sites. Within this study, drone images from two malaria-endemic regions in Burkina Faso and Côte d'Ivoire were assembled and labeled using open-source tools. We developed and applied a workflow using region-of-interest-based and deep learning methods to identify land cover types associated with vector breeding sites from very-high-resolution natural color imagery. Analysis methods were assessed using cross-validation and achieved maximum Dice coefficients of 0.68 and 0.75 for vegetated and non-vegetated water bodies, respectively. This classifier consistently identified the presence of other land cover types associated with the breeding sites, obtaining Dice coefficients of 0.88 for tillage and crops, 0.87 for buildings and 0.71 for roads. This study establishes a framework for developing deep learning approaches to identify vector breeding sites and highlights the need to evaluate how results will be used by control programs.

Aedes aegypti in Southern Brazil: Spatiotemporal Distribution Dynamics and Association with Climate and Environmental Factors.

In Brazil, the mosquito Aedes (Stegomyia) aegypti is considered the main vector of the dengue, chikungunya, and Zika arbovirus transmission. Recent epidemiological studies in southern Brazil have shown an increase in the incidence of dengue, raising concerns over epidemiological control, monitoring, and surveys. Therefore, this study aimed at performing a historical spatiotemporal analysis of the Ae. aegypti house indices (HI) in southern Brazil over the last 19 years. As vector infestation was associated with climatic and environmental variables, HI data from the Brazilian Ministry of Health, climate data from the Giovanni web-based application, and environmental data from the Mapbiomas project were used in this study. Our results showed an expressive increase in the number of HI surveys in the municipalities confirming the vector presence, as compared to those in 2017. Environmental variables, such as urban infrastructure, precipitation, temperature, and humidity, were positively correlated with the Ae. aegypti HI. This was the first study to analyze Ae. aegypti HI surveys in municipalities of southern Brazil, and our findings could help in developing and planning disease control strategies to improve public health.

Estimation of potential epidemic risk in the landslide zone based on physical factors in the Sillapa district / Estimación de riesgo potencial epidémico en la zona de deslave basado en factores físicos en el distrito Sillapa

Almost 17% of causes of death due to natural hazards are the product of landslides. Most of them occur in the most deprived places of less developed countries, coexisting a lethal combination of factors that point to this type of tragedies: the natural and the human factor. On the other hand, after a disaster, health care needs and priorities may change; in this sense, the food security of refugees, the supply of drinking water, the disposal of excreta and solid waste, the need for shelters, attention to personal hygiene needs, vector control, attention to injuries after the cleanup activities and the conduct of public health surveillance becomes a priority. To mitigate the disruption, public health authorities must act promptly to avert the adverse effects of the disaster, prevent further damage, and restore public service delivery as soon as possible. In this sense, public health surveillance, epidemiology, can identify local problems and establish priorities for decision-making in the health area. In this article, mention is made of one of the most alarming events that occurred in Sillapata, Peru, where a level 4 landslide affected the infrastructure of the population. Considering an established statistical model, it is possible to predict the zoning of higher risks, and thus establish the most appropriate territorial planning and epidemiological surveillance when similar events reach this population or other populations of the Peruvian State(AU)

Casi el 17 % de causas de muerte por amenazas naturales es producto de los deslizamientos de masa. La mayoría de ellas ocurre en los sitios más deprimidos de los países menos desarrollados coexistiendo una combinación letal de factores que apuntan a este tipo de tragedias: el factor natural y el humano. Por otra parte, después de un desastre, las necesidades y prioridades de cuidado de salud pueden cambiar; en ese sentido, el aseguramiento alimenticio de los refugiados, el suministro de agua de potable, la disposición de excretas y desechos sólidos, la necesidad de albergues, la atención de las necesidades de higiene personal, el control de vectores, la atención de las lesiones después de las actividades de limpieza y la conducción de la vigilancia en salud pública se hace prioritarias. Para mitigar el trastorno, las autoridades de salud pública deben actuar con prontitud para evitar los efectos advesos del desastre, prevenir más daños y restaurar la prestación de servicios públicos lo más pronto posible. En ese sentido, la vigilancia en salud pública, la epidemiología, puede identificar los problemas del lugar y establecer prioridades para la toma de decisiones en el área de la salud. En este artículo, se hace mención a uno de los eventos más alarmante ocurrido en Sillapata, Perú, donde un deslizamiento nivel 4 afectó la infraestructura de la población. Tomando en cuenta, un modelo estadístico establecido es posible predecir la zonificación de mayores riesgos, y de esta manera establecer la planificación territorial y de vigilancia epidemiológica más adecuada cuando eventos similares alcance a esta población o a otras poblaciones del Estado Peruano(AU)

Medidas de control epidemiológico en el sector empresarial e impacto de la pandemia sobre la creación de empresas en el departamento del Magdalena Colombia / Epidemiological control measurements at the business sector and impact of pandemic on business creation in the department of Magdalena Colombia

Este trabajo se propone analizar el impacto de la pandemia por COVID-19 en los registros de creación de nuevas empresas en el departamento del Magdalena (Colombia) principalmente entre el 2019 y 2020, de la misma manera se desarrolla un análisis de las medidas de control epidemiológico a nivel nacional y a nivel departamental para comprender de mejor manera las iniciativas de contención de la COVID-19. Para el desarrollo de este trabajo, se tomaron como referencia los datos de creación de empresas de los últimos cinco años (2016 ­ 2020) en el Magdalena; así como se analizaron medidas para el control epidemiológico a nivel nacional (prevenir, mitigar, y suprimir), así como las adoptadas específicamente para el Magdalena. Entre los principales hallazgos, se encontró que, al contrastar los años 2019 y 2020, hubo una disminución del 2,6% en la creación de nuevas empresas en el departamento del Magdalena, porcentaje que representa 202 unidades productivas menos que en 2019; esta tendencia decreciente en materia de creación de empresas, venía desde 2019, año en el que hubo una caída del 0,8% en los nacimientos de nuevas empresas con respecto al 2018 -62 empresas menos-; la contundente caída en el año 2020 es un reflejo del nefasto efecto de la aparición de la COVID-19 en las dinámicas empresariales en el Magdalena; de otra parte, resaltan medidas de gestión intergremial al igual que las estrategias de apoyo financiero para dinamizar la economía en el Magdalena, así como una cronología prudente en materia de controles epidemiológicos en el Territorio(AU)

This study aims to analyze the impact of the COVID-19 pandemic on the records of the creation of new companies in the department of Magdalena (Colombia), mainly between 2019 and 2020. In the same way, an analysis of epidemiology control measures is developed at the national and departmental levels to better understand COVID-19 containment initiatives. For the development of this study, the data on business creation of the last five years (2016 - 2020) in Magdalena was taken as a reference; as well as measures for epidemiological control at the national level (prevent, mitigate, and suppress), along with those adopted specifically for Magdalena were analyzed. Among the main findings, it was found that, when comparing the years 2019 and 2020, there was a 2.6% decrease in the creation of new companies in Magdalena, a percentage that represents 202 production units less than in 2019; This downward trend in the creation of companies came from 2019, the year in which there was a 0.8% drop in the establishment of new companies compared to 2018 -62 fewer companies-; the overwhelming drop in 2020 is a reflection of the disastrous effect of the appearance of COVID-19 on business dynamics in Magdalena; On the other hand, the business associations management measures were a key important factor. Additionally, the financial support to boost the economy in Magdalena, as well as a prudent chronology - in terms of epidemiological controls in the Territory(AU)

Plan de vigilancia y control epidemiológico para prevenir. Casos de malaria en Beni-Bolivia / Surveillance and epidemiological control plan to prevent. Malaria cases in Beni-Bolivia / Plano de vigilância e controle epidemiológico para prevenir. Casos de malária em Beni-Bolívia

La malaria constituye una importante amenaza para la salud pública a nivel mundial. En Bolivia afecta a 7 departamentos, con particular afectación en la amazonia: Riberalta y Guayaramerín, lugar donde se concentra el 98% de los casos positivos. OBJETIVO: elaborar un programa de vigilancia y control epidemiológico, para prevenir casos de malaria en el departamento de Beni, gestión 2020. MATERIALES Y METODOS: investigación descriptiva, retrospectiva y cuasi experimental, se realizó revisión documental a una población de 399 personas. RESULTADOS: el 2018 existió 21,1% de malaria, 2019 se detectó 10.9% y el año 2020 14.0%, del total de casos positivos de este último año, el 90.4% corresponde a P. vivax y 9.6% a P. falciparum. El año 2020 es donde se observa mayor número de casos positivos. El grupo etario más afectado es entre 11 a 30 años, siendo el mayor porcentaje de casos positivos de la población Riberalta. CONCLUSIONES: el porcentaje de contagios por malaria es alto, por ello que se propone un plan de vigilancia y control de malaria regional, el mismo tenga las características de: métodos de diagnóstico, tratamiento y prevención de la enfermedad, eliminación de criaderos de vectores (mosquitos), vigilancia epidemiológica, intervención en las zonas inaccesibles de la Amazonía consideradas endémicas, con el fin de extender la capacidad de diagnóstico y finalmente la capacitación a la población para un diagnóstico oportuno, el mismo que permitirá lograr disminuir los casos de malaria positivos en la población de las zonas amazónicas: Riberalta y Guayaramerín.

Malaria constitutes a major threat to public health worldwide. In Bolivia, it affects 7 departments, with particular impact on the Amazon: Riberalta and Guayaramerín, where 98% of positive cases are concentrated. OBJECTIVE: to develop a surveillance and epidemiological control program to prevent cases of malaria in the department of Beni, management 2020. MATERIALS AND METHODS: descriptive, retrospective and quasi-experimental research, a documentary review was carried out on a population of 399 people. RESULTS: in 2018 there was 21.1% of malaria, in 2019 10.9% were detected and in 2020 14.0%, of the total positive cases of this last year, 90.4% correspond to P. vivax and 9.6% to P. falciparum. The year 2020 is where the highest number of positive cases is observed. The most affected age group is between 11 and 30 years, with the highest percentage of positive cases in the Riberalta population. CONCLUSIONS: the percentage of malaria infections is high, which is why a regional malaria surveillance and control plan is proposed, it has the characteristics of: methods of diagnosis, treatment and prevention of the disease, elimination of vector breeding sites ( mosquitoes), epidemiological surveillance, intervention in inaccessible areas of the Amazon considered endemic, in order to extend diagnostic capacity and finally train the population for timely diagnosis, the same that will allow to reduce positive malaria cases in the population of the Amazon areas: Riberalta and Guayaramerín.

A malária constitui uma grande ameaça à saúde pública em todo o mundo. Na Bolívia, afeta 7 departamentos, com especial incidência na Amazônia: Riberalta e Guayaramerín, onde se concentram 98% dos casos positivos. OBJETIVO: desenvolver um programa de vigilância e controle epidemiológico para prevenir casos de malária no departamento de Beni, gestão 2020. MATERIAIS E MÉTODOS: pesquisa descritiva, retrospectiva e quase experimental, foi realizada uma revisão documental em uma população de 399 pessoas. RESULTADOS: em 2018 houve 21,1% de malária, em 2019 foram detectados 10,9% e em 2020 14,0%, do total de casos positivos deste último año, 90,4% correspondem a P. vivax e 9,6% a P. falciparum. O ano de 2020 é onde se observa o maior número de casos positivos. A faixa etária mais acometida é entre 11 e 30 años, com maior percentual de casos positivos na população de Riberalta. CONCLUSÕES: o percentual de infecções por malária é alto, razão pela qual se propõe um plano regional de vigilância e controle da malária, que tem as características de: métodos de diagnóstico, tratamento e prevenção da doença, eliminação de criadouros de vetores (mosquitos), vigilância, intervenção em áreas inacessíveis da Amazônia consideradas endêmicas, a fim de ampliar a capacidade diagnóstica e finalmente capacitar a população para o diagnóstico oportuno, o mesmo que permitirá reduzir os casos positivos de malária na população das áreas amazônicas: Riberalta e Guayaramerín.