Epidesim: a FORTRAN 95 program for simulating the spread of infections on a 2D square population lattice.

The program epidesim (written in FORTRAN 95) was purpose-built for generating the simulations presented in the paper "The spread of infections from a physics perspective" which was accepted for publication in the Journal Biology Methods and Protocols as a part of the ongoing collection of Covid-19 related papers presented by the Journal. The program performs Monte-Carlo simulations of the evolution/spread of an epidemic on a 2D square lattice of 2001x2001 nodes. The lattice represents the entire population with each node representing an individual member. The spread of infection takes place in a SIR context. The file epidesim.txt contains the listing (as text file) of epidesim's FORTRAN 95 code. It can be used (in principle) via copying and pasting of the text of the listing into a suitable FORTRAN programming/development environment* and subsequent compilation (thus allowing for platform independent use of the program). The basic algorithm is outlined in the aforementioned paper, and the code has been intensively tested over and over again** and correctly does what it was designed for by the author. The file "code_description.pdf" contains a brief outline of what the program does, what user-input is required and how this should be provided to the program, and what output is generated by the program. However, as stated before, the program was purpose-built by the author for his own research. As such, it was never intended to be used by other users, and this may have a negative effect on the user-friendliness of the program. One should also be aware in this respect, that using the program for research purposes may (occasionally) require a fair (and sometimes detailed) knowledge of its inner workings in order to understand and judge the output. As such, the main motivation for making the code public is for reasons of scientific transparency. That is, to allow the readers of the aforementioned paper to take notice of the software specially developed and used for generating the results presented in the paper. Nevertheless, it is also presented here to be used freely by others under Creative Commons 4.0 International license. However, the author takes no liability of any kind and under any circumstances for damage (material or immaterial) arising from using the code (for instance (but not exclusively) as a result of improper/inexpert use of the code, or misinterpretation of the generated results). The author also strongly encourages those who wish to go deeper and actively into the subject of the paper to write their own code. After all, Monte-Carlo simulations are fun, and writing Monte-Carlo code all by yourself can be both instructive and rewarding (there is plenty of good literature available on the subject (for instance K. Binder and D.W. Heermann, Monte-Carlo Simulations in Statistical Physics (Springer Verlag))). * Compatible with FORTRAN 95 ** Not only by going over and over again through the algorithm and the code itself, but also by letting the program perform tasks of which the outcome is non-trivial but nevertheless known in advance via other means of analysis, and to check whether the results produced by the program agree with what they should be