Assessing The Impact of Medical Treatment and Fumigation on The Superinfection of Malaria: A Study of Sensitivity Analysis

Malaria is a disease caused by the parasite Plasmodium, transmitted by the bite of an infected female Anopheles. In general, five species of Plasmodium that can cause malaria. Of the five species, Plasmodium falciparum and Plasmodium vivax are two species of Plasmodium that can allow malaria superinfection in the human body. Typically, the popular intervention for malaria eradication is the use of fumigation to control the vector population and provide good medical services for malaria patients. Here in this article, we formulate a mathematical model based on a host-vector interaction. Our model considering two types of plasmodium in the infection process and the use of medical treatment and fumigation for the eradication program. Our analytical result succeeds in proving the existence of all equilibrium points and how their existence and local stability criteria depend not only on the control reproduction number but also in the invasive reproduction number. This invasive reproduction number represent how one plasmodium can dominate other plasmodium. Our sensitivity analysis shows that fumigation is the most influential parameter in determining all control reproduction numbers. Furthermore, we find that the order in which numerous intervention measures are taken will be very crucial to determine the level of success of our malaria eradication program

The impact of health system governance and policy processes on health services in Iraqi Kurdistan

BACKGROUND: Relative to the amount of global attention and media coverage since the first and second Gulf Wars, very little has been published in the health services research literature regarding the state of health services in Iraq, and particularly on the semi-autonomous region of Kurdistan. Building on findings from a field visit, this paper describes the state of health services in Kurdistan, analyzes their underlying governance structures and policy processes, and their overall impact on the quality, accessibility and cost of the health system, while stressing the importance of reinvesting in public health and community-based primary care. DISCUSSION: Very little validated, research-based data exists relating to the state of population health and health services in Kurdistan. What little evidence exists, points to a region experiencing an epidemiological polarization, with different segments of the population experiencing rapidly-diverging rates of morbidity and mortality related to different etiological patterns of communicable, non-communicable, acute and chronic illness and disease. Simply put, the rural poor suffer from malnutrition and cholera, while the urban middle and upper classes deal with issues of obesity and Type 2 diabetes. The inequity is exacerbated by a poorly governed, fragmented, unregulated, specialized and heavily privatized system, that not only leads to poor quality of care and catastrophic health expenditures, but also threatens the economic and political stability of the region. There is an urgent need to revisit and clearly define the core values and goals of a future health system, and to develop an inclusive governance and policy framework for change, towards a more equitable and effective primary care-based health system, with attention to broader social determinants of health and salutogenesis. SUMMARY: This paper not only frames the situation in Kurdistan in terms of a human rights or special political issue of a minority population, but provides important generalizable lessons for other constituencies, highlighting the need for political action before effective public health policies can be implemented - as embodied by Rudolf Virchow, the father of European public health and pathology, in his famous quote "politics is nothing but medicine at a larger scale"

Investigating the Impact of Social Awareness and Rapid Test on A COVID-19 Transmission Model

In this article, we propose and analyze a mathematical model of COVID-19 transmission among a closed population, with social awareness and rapid test intervention as the control variables. For this, we have constructed the model using a compartmental system of the ordinary differential equations. Dynamical analysis regarding the existence and local stability of equilibrium points is conducted rigorously. Our analysis shows that COVID-19 will disappear from the population if the basic reproduction number is less than one, and persist if the basic reproduction number is greater than one. In addition, we have shown a trans-critical bifurcation phenomenon based on our proposed model when the basic reproduction number equals one. From the elasticity analysis, we have observed that rapid testing is more promising in reducing the basic reproduction number as compared to a media campaign to improve social awareness on COVID-19. Using the Pontryagin Maximum Principle (PMP), the characterization of our optimal control problem is derived analytically and solved numerically using the forward-backward iterative algorithm. Our cost-effectiveness analysis shows that using rapid test and media campaigns partially are the best intervention strategy to reduce the number of infected humans with the minimum cost of intervention. If the intervention is to be implemented as a single intervention, then using solely the rapid test is a more promising and low-cost option in reducing the number of infected individuals vis-a-vis a media campaign to increase social awareness as a single intervention

Identification of differentially expressed microRNAs in human male breast cancer

<p>Abstract</p> <p>Background</p> <p>The discovery of small non-coding RNAs and the subsequent analysis of microRNA expression patterns in human cancer specimens have provided completely new insights into cancer biology. Genetic and epigenetic data indicate oncogenic or tumor suppressor function of these pleiotropic regulators. Therefore, many studies analyzed the expression and function of microRNA in human breast cancer, the most frequent malignancy in females. However, nothing is known so far about microRNA expression in male breast cancer, accounting for approximately 1% of all breast cancer cases.</p> <p>Methods</p> <p>The expression of 319 microRNAs was analyzed in 9 primary human male breast tumors and in epithelial cells from 15 male gynecomastia specimens using fluorescence-labeled bead technology. For identification of differentially expressed microRNAs data were analyzed by cluster analysis and selected statistical methods.</p> <p>Expression levels were validated for the most up- or down-regulated microRNAs in this training cohort using real-time PCR methodology as well as in an independent test cohort comprising 12 cases of human male breast cancer.</p> <p>Results</p> <p>Unsupervised cluster analysis separated very well male breast cancer samples and control specimens according to their microRNA expression pattern indicating cancer-specific alterations of microRNA expression in human male breast cancer. miR-21, miR519d, miR-183, miR-197, and miR-493-5p were identified as most prominently up-regulated, miR-145 and miR-497 as most prominently down-regulated in male breast cancer.</p> <p>Conclusions</p> <p>Male breast cancer displays several differentially expressed microRNAs. Not all of them are shared with breast cancer biopsies from female patients indicating male breast cancer specific alterations of microRNA expression.</p

Mathematical modelling for coronavirus disease (COVID-19) in predicting future behaviours and sensitivity analysis

Nowadays, there are a variety of descriptive studies of available clinical data for coronavirus disease (COVID-19). Mathematical modelling and computational simulations are effective tools that help global efforts to estimate key transmission parameters. The model equations often require computational tools and dynamical analysis that play an important role in controlling the disease. This work reviews some models for coronavirus first, that can address important questions about the global health care and suggest important notes. Then, we model the disease as a system of differential equations. We develop previous models for the coronavirus, some key computational simulations and sensitivity analysis are added. Accordingly, the local sensitivities for each model state with respect to the model parameters are computed using three different techniques: non-normalizations, half normalizations and full normalizations. Results based on sensitivity analysis show that almost all model parameters may have role on spreading this virus among susceptible, exposed and quarantined susceptible people. More specifically, communicate rate person–to–person, quarantined exposed rate and transition rate of exposed individuals have an effective role in spreading this disease. One possible solution suggests that healthcare programs should pay more attention to intervention strategies, and people need to self-quarantine that can effectively reduce the disease

Rapport annuel pour l´année 1941

Suomen virallinen tilasto (SVT