Purpose Rapid prototyping and three-dimensional (3D) printing allows the direct creation of objects from 3D computer-aided design files. To identify the effects 3D printing may have on student experiences and the learning of the design process, students were asked to create a design and create a prototype of that design. Design/methodology/approach This study follows an experimental design involving four total courses of interior design students. After conceptualizing a design, students were randomly selected to either create the prototype by hand or given access to 3D printing equipment. The models were graded by three subject experts using a rubric that focused on three key aspects of the model project, namely, craftsmanship, design quality and scale (proportion). Findings All three measures produced significant mean differences with a medium effect size when comparing the 3D printed models to the traditionally built models. Additional observations provided insights into the design processes approached by students using hand-constructed and 3D printed modeling. The most notable difference was the propensity for curved and rectilinear shapes by available design technologies. Research limitations/implications The experiment showed that the design technology (3D printing) did have an impact on the designs students conceptualized. This suggests that students do connect ideation to implementation, and the availability of enabling technology impacts the design process. This research was conducted in an interior design environment and consists of primarily female students. The experimental research may be limited to design programs with similar student populations and levels of exposure to various design technologies. Practical implications This research is designed to provide instructors and programs valuable information when looking at implementing new design technologies into the curriculum. Instructors are made aware that new design technologies do impact student design strategies. Additionally, although certain design technologies allow for revisions, it was apparent that students continued to be resistant to revise their initial models suggesting instructors prepare to address this issue in instruction. Social implications There is a strong body of research indicating inequality in education where students have differing access to technologies in schools. This research shows that 3D printing, similar to many technologies in education, can impact the cognitive processes of content being learned. Originality/value There is limited research on how design technologies impact design cognition and the experiences of design students. This paper looked specifically at one design technology (3D printing/rapid prototyping) and how it impacts the processes and quality of design, in addition to the quality of design products (prototypes or models). Research such as this provides instructors and faculty members an insight into how design technologies impact their curriculum.
For decades, mathematical models of disease transmission have provided researchers and public health officials with critical insights into the progression, control, and prevention of disease spread. Of these models, one of the most fundamental is the SIR differential equation model. However, this ubiquitous model has one significant and rarely acknowledged shortcoming: it is unable to account for a disease's true infectious period distribution. As the misspecification of such a biological characteristic is known to significantly affect model behavior, there is a need to develop new modeling approaches that capture such information. Therefore, we illustrate an innovative take on compartmental models, derived from their general formulation as systems of nonlinear Volterra integral equations, to capture a broader range of infectious period distributions, yet maintain the desirable formulation as systems of differential equations. Our work illustrates a compartmental model that captures any Erlang distributed duration of infection with only 3 differential equations, instead of the typical inflated model sizes required by traditional differential equation compartmental models, and a compartmental model that captures any mean, standard deviation, skewness, and kurtosis of an infectious period distribution with 4 differential equations. The significance of our work is that it opens up a new class of easy-to-use compartmental models to predict disease outbreaks that do not require a complete overhaul of existing theory, and thus provides a starting point for multiple research avenues of investigation under the contexts of mathematics, public health, and evolutionary biology.
Objective The objective of this study is to determine the epidemiological effectiveness of a first-line antiretroviral regimen with HIV protease inhibitor for preventing recurrent malaria in children under the range of HIV prevalence levels and malaria transmission intensities encountered in sub-Saharan Africa. Design A dynamic model of malaria transmission was developed using clinical data on the protease inhibitor extended posttreatment prophylactic effect of the antimalarial treatment, artemether-lumefantrine, in addition to parameter estimates from the literature. Methods To evaluate the benefits of HIV protease inhibitors on the health burden of recurrent malaria among children, we constructed a dynamic model of malaria transmission to both HIV-positive and HIV-negative children, parameterized by data from a recent clinical trial. The model was then evaluated under varying malaria transmission and HIV prevalence settings to determine the health benefits of HIV protease inhibitors in the context of artemether-lumefantrine treatment of malaria in children. Results Comparing scenarios of low, intermediate and high newborn HIV prevalence, in a range of malaria transmission settings, our dynamic model predicts that artemether-lumefantrine with HIV protease inhibitor based regimens prevents 0.03–0.10, 5.2–13.0 and 25.5–65.8 annual incidences of malaria per 1000 children, respectively. In addition, HIV protease inhibitors save 0.002–0.006, 0.22–0.8, 1.04–4.3 disability-adjusted life-years per 1000 children annually. Considering only HIV-infected children, HIV protease inhibitors avert between 278 and 1043 annual incidences of malaria per 1000 children. Conclusion The use of HIV protease inhibitor based regimens as first-line antiretroviral therapy for HIV is an effective measure for reducing recurrent malaria among HIV-infected children in areas where HIV and malaria are coendemic, and artemether-lumefantrine is a first-line antimalarial.
BackgroundSub-Saharan Africa harbors the majority of the global burden of malaria and schistosomiasis infections. The co-endemicity of these two tropical diseases has prompted investigation into the mechanisms of coinfection, particularly the competing immunological responses associated with each disease. Epidemiological studies have shown that infection with Schistosoma mansoni is associated with a greater malaria incidence among school-age children.MethodologyWe developed a co-epidemic model of malaria and S. mansoni transmission dynamics which takes into account key epidemiological interaction between the two diseases in terms of elevated malaria incidence among individuals with S. mansoni high egg output. The model was parameterized for S. mansoni high-risk endemic communities, using epidemiological and clinical data of the interaction between S. mansoni and malaria among children in sub-Saharan Africa. We evaluated the potential impact of the S. mansoni–malaria interaction and mass treatment of schistosomiasis on malaria prevalence in co-endemic communities.Principal FindingsOur results suggest that in the absence of mass drug administration of praziquantel, the interaction between S. mansoni and malaria may reduce the effectiveness of malaria treatment for curtailing malaria transmission, in S. mansoni high-risk endemic communities. However, when malaria treatment is used in combination with praziquantel, mass praziquantel administration may increase the effectiveness of malaria control intervention strategy for reducing malaria prevalence in malaria- S. mansoni co-endemic communities.Conclusions/SignificanceSchistosomiasis treatment and control programmes in regions where S. mansoni and malaria are highly prevalent may have indirect benefits on reducing malaria transmission as a result of disease interactions. In particular, mass praziquantel administration may not only have the direct benefit of reducing schistosomiasis infection, it may also reduce malaria transmission and disease burden.
Differential equation models of infectious disease have undergone many theoretical extensions that are invaluable for the evaluation of disease spread. For instance, while one traditionally uses a bilinear term to describe the incidence rate of infection, physically more realistic generalizations exist to account for effects such as the saturation of infection. However, such theoretical extensions of recovery rates in differential equation models have only started to be developed. This is despite the fact that a constant rate often does not provide a good description of the dynamics of recovery and that the recovery rate is arguably as important as the incidence rate in governing the dynamics of a system. We provide a first-principles derivation of state-dependent and time-varying recovery rates in differential equation models of infectious disease. Through this derivation, we demonstrate how to obtain time-varying and state-dependent recovery rates based on the family of Pearson distributions and a power-law distribution, respectively. For recovery rates based on the family of Pearson distributions, we show that uncertainty in skewness, in comparison to other statistical moments, is at least two times more impactful on the sensitivity of predicting an epidemic's peak. In addition, using recovery rates based on a power-law distribution, we provide a procedure to obtain state-dependent recovery rates. For such state-dependent rates, we derive a natural connection between recovery rate parameters with the mean and standard deviation of a power-law distribution, illustrating the impact that standard deviation has on the shape of an epidemic wave.
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