Software Technology to Develop Large-Scale Self-Adaptive Systems: Accelerating Agent-Based Models and Fuzzy Cognitive Maps via CUDA

Agent-Based Models (ABMs) have long served to study self-adaptive systems and the emergence of population-wide patterns from simple rules applied to individuals. Recently, the rules for each agent have been expressed using a Fuzzy Cognitive Map (FCM), which is elicited from a subject-matter expert. This provides a transparent and participatory process to externalize the `mental model' of an expert and directly embed it into agents. However, software technology has been lacking to support such hybrid ABM/FCM models at scale, which has drastically limited the scope of applications and the ability of researchers to study emergent phenomena over large populations. In this paper, we designed and implemented the first open-source library that automatically accelerates ABM/FCM models by leveraging the CUDA cores available in a Graphical Processing Unit. We demonstrate the correctness and scaling of our library on a case study as well as across different networks representing agent interactions

Estimating public transport congestion in UK urban areas with open transport models

Operational urban transport models require to gather heterogeneous sets of data and often integrate different sub-models. Their systematic validation and reproducible application therefore remains problematic. We propose in this contribution to build transport models from the bottom-up using scientific workflow systems with open-source components and data. These open models are aimed in particular at estimating congestion of public transport in all UK urban areas. This allows us building health indicators related to public transport density in the context of the COVID-19 crisis, and testing related policies

A Lock Free Approach To Parallelize The Cellular Potts Model: Application To Ductal Carcinoma In Situ

In the field of computational biology, in order to simulate multiscale biological systems, the Cellular Potts Model (CPM) has been used, which determines the actions that simulated cells can perform by determining a hamiltonian of energy that takes into account the influence that neighboring cells exert, under a wide range of parameters. There are some proposals in the literature that parallelize the CPM; in all cases, either lockbased techniques or other techniques that require large amounts of information to be disseminated among parallel tasks are used to preserve data coherence. In both cases, computational performance is limited. This work proposes an alternative approach for the parallelization of the model that uses transactional memory to maintain the coherence of the information. A Java implementation has been applied to the simulation of the ductal adenocarcinoma of breast in situ (DCIS). Times and speedups of the simulated execution of the model on the cluster of our university are analyzed. The results show a good speedup

Projecting the demographic impact of AIDS

A simple model that simulates the spread of AIDS is used to generate estimates of deaths from AIDS, which are incorporated into population projections covering 20 years. Preliminary results for one country are shown - not firm estimates, as the model has several arbitrarily set parameters. The results suggest that the number of infectionsand deaths could be extremely large, even if transmission of the human immunodeficiency virus (HIV) is substantially reduced. In five years, deaths in a single country will be in the tens of thousands, and after 20 years could be hundreds of thousands and still rising. Nevertheless, the impact on population size appears small. The authors discuss why these results should not be entirely trusted, and what work remains to be done. Where HIV is relatively widespread, changes in sexual behavior, particulary increases in condom use, are essential to reduce the scale of the epidemic. Earlier changes are more effective than later changes. But across countries with different levels of prevalence and sexual activity, changes in sexual behavior produce similar effects.Health Indicators,,HIV AIDS,Adolescent Health,Health Monitoring&Evaluation

The impact of novel diagnostics on infectious disease epidemics

Diagnostic tests play a crucial role in the control and surveillance of infectious diseases, and to ensure effective clinical management. Novel diagnostic tests are traditionally evaluated in terms of their accuracy (sensitivity and specificity). Using mathematical models, I examine the impact of different novel diagnostic tests on the tuberculosis (“TB”) and severe acute respiratory syndrome coronavirus 2 (“SARS-CoV-2”) epidemics, and investigate how the context in which these tests are used may affect this impact. In chapter 3, I evaluate the use of a hypothetical biomarker test that can detect individuals at imminent risk of progressing to active TB disease (incipient TB) and subsequent TB preventive treatment (“TPT”) initiation in a high TB burden setting. I demonstrate that biomarker-led TPT can have a significant impact on TB incidence in a high TB burden setting; however, the cost of implementing such a strategy is likely to be prohibitive given the testing effort needed to identify those with incipient TB, even if testing is targeted to populations at high risk of TB. Next, in chapter 4, I evaluate the use of urine-based tests for active TB disease, in a high TB and HIV burden setting. Although current urine-based tests for TB suffer from poor sensitivity, these tests are continuously improving, and are essential for TB diagnosis amongst patient subgroups who struggle to produce quality sputum and who are therefore missed by traditional methods of TB diagnosis. I demonstrate that although urine-based diagnostic tests reduce mortality amongst people living with HIV, population-level epidemiological impact is not seen unless the tests are deployed outside of HIV care and into routine TB care. In chapter 5, I investigate the cost and epidemiological impact of expanding different TB publicprivate sector engagement services. My results reveal that services involving the use of Xpert, a highly accurate but costly test for diagnosing active TB disease are epidemiologically impactful, but costly, and thus have the highest cost per TB case or TB death averted than other services. Finally, in chapter 6, I explore the context under when cheap but less accurate rapid antigen diagnostic tests (“Ag-RDTs”) offer greater public health value than more accurate but costly nucleic acid amplification tests (“NAATs”) that often have high turnaround times. My results highlight that Ag-RDTs-led strategies, despite their imperfect sensitivity and specificity, are more impactful at a lower cost than NAATs under different use-cases. Overall, the context in which diagnostic tests are used is crucial in anticipating their impact. Factors, including but not limited to testing eligibility, levels of current testing and turnaround time, can affect 6 the potential epidemiological impact of a diagnostic test. Thus, future evaluation of diagnostic tests should move away from focussing exclusively on accuracy and move towards clearly defining different use-cases and investigating which factors other than accuracy, may affect the epidemiological impact of a diagnostic test.Open Acces