The Problem of Religious Evil: Does Belief in God Cause Evil?

Daniel Kodaj has recently developed a pro-atheistic argument that he calls "the problem of religious evil." This first premise of this argument is "belief in God causes evil." Although this idea that belief in God causes evil is widely accepted, certainly in the secular West, it is sufficiently problematic as to be unsuitable as a basis for an argument for atheism, as Kodaj seeks to use it. In this paper I shall highlight the problems inherent in it in three ways: by considering whether it is reasonable to say that "belief in God" causes evil; whether it is reasonable to say that belief in God "causes" evil; and whether it is reasonable to say that belief in God causes "evil." In each case I will argue that it is problematic to make such claims, and accordingly I will conclude that the premise "belief in God causes evil" is unacceptable as it stands, and consequently is unable to ground Kodaj's pro-atheistic argument

Predicting the potential for zoonotic transmission and host associations for novel viruses.

Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses

Predicting the potential for zoonotic transmission and host associations for novel viruses

Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses