High altitude reduces infection rate of COVID-19 but not case-fatality rate.

Coronavirus disease 19 (COVID-19) is a pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). It is suggested that life at high altitude may reduce COVID-19 infections and case-fatality rates (cases/deaths). We study data from Peru COVID-19 pandemics, which first case was recorded on March 6th, 2020. By June 13, 2020 there were 6498 deaths, and 224,132 SARS-CoV-2 positives. Using data from 185 capitals of provinces with altitudes ranging from 3 to 4342 m, we confirm previous reports that infection with COVID-19 at high altitude is reduced. However, case-fatality rate is not dependent of altitude. We have also presented first evidence that female protection towards death by COVID-19 is reduced as altitude of residence increases.

[Suggestions for chikungunya control based on a sensitivity analysis of a mathematical model]. / Sugerencias a partir del análisis de sensibilidad de un modelo matemático de transmisión de chikungunya.

Chikungunya fever seriously affects peoples' health and causes chronic joint pain and even disability. Chikungunya is transmitted by the bite of Aedes aegypti and Aedes albopictus. Outbreaks have been reported in throughout the world, including Latin America. Mathematical modeling studies of these outbreaks have calculated the values of various​ epidemiological parameters. Based on them, a mathematical model was prepared to simulate a chikungunya outbreak in a local population, which was transmitted from an neighboring infected population. A sensitivity and uncertainty analysis revealed that the mosquito-to-human and human-to-mosquito transmission rates are the variables with the highest correlation with the number infected people, which were greatest at 60 days after the first case in the neighboring population. Therefore, it is recommended to take this into consideration when planning policies to control such variables as isolation of infected people, distribution of mosquito netting and repellents, fumigation, among others.

Sugerencias a partir del análisis de sensibilidad de un modelo matemático de transmisión de chikungunya / Suggestions for chikungunya control based on a sensitivity analysis of a mathematical model

La fiebre chikungunya afecta seriamente la salud de las personas, causando dolores articulares crónicos e incluso discapacidad. Es transmitida por picadura de los mosquitos Aedes aegypti y Aedes albopictus. Se han reportado brotes en diversas partes del mundo, incluyendo Latinoamérica. Estudios de modelamiento matemático de dichos brotes han calculado valores de parámetros epidemiológicos. En base a ellos, se elaboró un modelo matemático para simular un brote epidémico de chikungunya en una población local, transmitido desde una población vecina infectada. Mediante análisis de sensibilidad e incertidumbre se obtuvo que la tasa de transmisión mosquito-humano y humano-mosquito son las variables con mayor correlación con la cantidad de infectados, la cual se pierde significativamente a partir de los 60 días del primer caso en la población vecina. Se recomienda tomar esto en cuenta al planificar medidas de control sobre dichas variables como aislamiento de infectados, repartición de mosquiteros y repelentes, fumigación, entre otras...

Chikungunya fever seriously affects peoplesÆ health and causes chronic joint pain and even disability. Chikungunya is transmitted by the bite of Aedes aegypti and Aedes albopictus. Outbreaks have been reported in throughout the world, including Latin America. Mathematical modeling studies of these outbreaks have calculated the values of various epidemiological parameters. Based on them, a mathematical model was prepared to simulate a chikungunya outbreak in a local population, which was transmitted from an neighboring infected population. A sensitivity and uncertainty analysis revealed that the mosquito-to-human and human-to-mosquito transmission rates are the variables with the highest correlation with the number infected people, which were greatest at 60 days after the first case in the neighboring population. Therefore, it is recommended to take this into consideration when planning policies to control such variables as isolation of infected people, distribution of mosquito netting and repellents, fumigation, among others...

[Information system of the national network of public health laboratories in Peru (Netlab)]. / Sistema de información de la red nacional de laboratorios de salud pública en el Perú (Netlab).

Clinical laboratory information systems produce improvements in the quality of information, reduce service costs, and diminish wait times for results, among other things. In the construction process of this information system, the National Institute of Health (NIH) of Peru has developed and implemented a web-based application to communicate to health personnel (laboratory workers, epidemiologists, health strategy managers, physicians, etc.) the results of laboratory tests performed at the Peruvian NIH or in the laboratories of the National Network of Public Health Laboratories which is called NETLAB. This article presents the experience of implementing NETLAB, its current situation, perspectives of its use, and its contribution to the prevention and control of diseases in Peru.

Sistema de información de la red nacional de laboratorios de salud pública en el Perú (Netlab) / Information system of the national network of public health laboratories in Peru (Netlab)

Los sistemas de información de laboratorio clínico, producen mejoras en la calidad de la información, la reducción de los costos del servicio, disminución de la espera para obtener resultados, entre otros. En el proceso de construcción de este sistema de información, el Instituto Nacional de Salud (INS) del Perú ha desarrollado e implementado un aplicativo a través de Internet basado en la web, para comunicar, al personal de salud (laboratoristas, epidemiólogos, gestores de estrategias sanitarias, médicos tratantes, etc.), los resultados de las pruebas de laboratorio que se realizan en el INS o en los laboratorios de la Red Nacional de Laboratorios de Salud Pública el cual es llamado NETLAB. Este artículo presenta la experiencia de la implementación de NETLAB, su situación actual y las perspectivas de su empleo, así como su contribución en la prevención y control de enfermedades en el Perú.

Clinical laboratory information systems produce improvements in the quality of information, reduce service costs, and diminish wait times for results, among other things. In the construction process of this information system, the National Institute of Health (NIH) of Peru has developed and implemented a web-based application to communicate to health personnel (laboratory workers, epidemiologists, health strategy managers, physicians, etc.) the results of laboratory tests performed at the Peruvian NIH or in the laboratories of the National Network of Public Health Laboratories which is called NETLAB. This article presents the experience of implementing NETLAB, its current situation, perspectives of its use, and its contribution to the prevention and control of diseases in Perú.

Developing capacity in health informatics in a resource poor setting: lessons from Peru.

The public sectors of developing countries require strengthened capacity in health informatics. In Peru, where formal university graduate degrees in biomedical and health informatics were lacking until recently, the AMAUTA Global Informatics Research and Training Program has provided research and training for health professionals in the region since 1999. The Fogarty International Center supports the program as a collaborative partnership between Universidad Peruana Cayetano Heredia in Peru and the University of Washington in the United States of America. The program aims to train core professionals in health informatics and to strengthen the health information resource capabilities and accessibility in Peru. The program has achieved considerable success in the development and institutionalization of informatics research and training programs in Peru. Projects supported by this program are leading to the development of sustainable training opportunities for informatics and eight of ten Peruvian fellows trained at the University of Washington are now developing informatics programs and an information infrastructure in Peru. In 2007, Universidad Peruana Cayetano Heredia started offering the first graduate diploma program in biomedical informatics in Peru.

Identifying DNA splice sites using hypernetworks with artificial molecular evolution.

Identifying DNA splice sites is a main task of gene hunting. We introduce the hyper-network architecture as a novel method for finding DNA splice sites. The hypernetwork architecture is a biologically inspired information processing system composed of networks of molecules forming cells, and a number of cells forming a tissue or organism. Its learning is based on molecular evolution. DNA examples taken from GenBank were translated into binary strings and fed into a hypernetwork for training. We performed experiments to explore the generalization performance of hypernetwork learning in this data set by two-fold cross validation. The hypernetwork generalization performance was comparable to well known classification algorithms. With the best hypernetwork obtained, including local information and heuristic rules, we built a system (HyperExon) to obtain splice site candidates. The HyperExon system outperformed leading splice recognition systems in the list of sequences tested.

Training biomedical and health informatics professionals in Peru: towards the development of the first graduate diploma program in the country.

In Peru, there are no formal university graduate programs in biomedical and health informatics, and there is a lack of other health informatics programs. AMAUTA, a joint program between the Universidad Peruana Cayetano Heredia (UPCH) in Lima and the University of Washington (UW) in Seattle has been training Peruvian health professionals since 1999 regarding biomedical and health informatics. In 2007, UPCH is offering the first Graduate Diploma Program in Biomedical Informatics in the country.

Identifying control mechanisms of granuloma formation during M. tuberculosis infection using an agent-based model.

Infection with Mycobacterium tuberculosis is a major world health problem. An estimated 2 billion people are presently infected and the disease causes approximately 3 million deaths per year. After bacteria are inhaled into the lung, a complex immune response is triggered leading to the formation of multicellular structures termed granulomas. It is believed that the collection of host granulomas either contain bacteria resulting in a latent infection or are unable to do so, leading to active disease. Thus, understanding granuloma formation and function is essential for improving both diagnosis and treatment of tuberculosis. Granuloma formation is a complex spatio-temporal system involving interactions of bacteria, specific immune cells, including macrophages, CD4+ and CD8+ T cells, as well as immune effectors such as chemokine and cytokines. To study this complex dynamical system we have developed an agent-based model of granuloma formation in the lung. This model combines continuous representations of chemokines with discrete agent representations of macrophages and T cells in a cellular automata-like environment. Our results indicate that key host elements involved in granuloma formation are chemokine diffusion, prevention of macrophage overcrowding within the granuloma, arrival time, location and number of T cells within the granuloma, and an overall host ability to activate macrophages. Interestingly, a key bacterial factor is its intracellular growth rate, whereby slow growth actually facilitates survival.

The effect of molecular inhibition on evolutionary learning: studies in the hypernetwork architecture.

The hypernetwork architecture is a biologically inspired learning model based on abstract molecules and molecular interactions that exhibits functional and organizational correlation with biological systems. Hypernetwork organisms were trained, by molecular evolution, to solve N-input parity tasks. We found that learning improves when molecules exhibit inhibitory sites, allowing molecular inhibition and opening the possibility of forming negative feedback regulatory pathways. Optimal learning is achieved when at least 20% of the molecules in each cell have inhibitory sites. Intra-cellular as well as inter-cellular molecular inhibitions play an important role in the information processing of hypernetwork organisms, by maintaining a balance of the molecular cascade reactions. Similar mechanisms inside neurons are considered important for memory.