This has been inspired by the current world fight with COVID-19, in an attempt to participate in it with patented and developed networking technology, also based on spreading powerful viruses in large physical and virtual spaces. The Spatial Grasp Technology (SGT) with basic Spatial Grasp Language (SGL) is using parallel self-spreading, self-replicating, and selfmatching semantic level code creating powerful distributed infrastructures for solving complex problems. This article shows how to find virus sources in distributed networks, first, by tracing them via infected predecessors if such were fixed, and then, more complexly, by moving through nodes with lower or close infection time, also taking into account possible failures in real networks. If to outline a number of infected nodes staying far away from each other and on different sides of the infected network, the probable source may also be on intersection of shortest path trees starting in them, as shown in SGL. But analyzing complexity, dynamics, and unpredictability of spread of COVID-19, we understood the insufficiency of discrete networks for simulating its world coverage. By using the SGT capability to directly operate in continuous physical spaces too, we showed how to describe the global malicious virus in a massive way, with the infection spreading via many and so far unclear channels. This article also shows how to model the planned distribution of the antivirus vaccine and its global impact on the virus, symbolically presented as spatial fight of benign (vaccine) with malicious (COVID) viruses. The latest version of SGT can be implemented and integrated with any existing networked systems in a global manner, with installment of communicating SGL interpreters in millions to billions copies and converting the world into a global simulation and control engine.