Public health microbiology focuses on microorganisms and infectious agents that impact human health. Previously, many areas of public health microbiology used culture- or molecular-based methods to investigate microbial public health issues. However, with the increase in accuracy and decrease in sequencing cost over the last decade, there has been a transition to the use of next generation sequencing (NGS) in public health microbiology. Oftentimes, samples of public health relevance are complex, with low target DNA and high amounts of background community making them challenging to work with. As such, many of the available sequencing methods do not work well in complex sample types, require deep sequencing, or have inherent biases associated with them. Thus, these methods lack the ability to capture all the necessary information in an efficient and cost-effective manner. In this dissertation, I develop and validate novel NGS tools using hybridization bait capture to address microbial public health problems and use these tools to investigate complex samples with public health relevance. In the first chapter, I review previous gold standard methods for six key topic areas in public health microbiology and provide information on currently available hybridization bait capture sets. In the second chapter, I develop a hybridization bait capture set for the 16S rRNA for microbiome studies (i.e., 16S-cap), and validate this bait set in silico and in vitro using mock communities and host-associated samples. In the third chapter, I address the problem of developing baits for antimicrobial resistance genes (ARGs) due to continual novel ARG generation and discovery. I develop and validate a bait set for ARGs (i.e., AMR-cap) on environmental samples and estimate when the baits will need to be supplemented and eventually redesigned. In the fourth chapter, I develop a hybridization bait capture assay to capture the whole genome of six species of human infecting Cryptosporidium spp. that have regions of varying DNA sequence similarity (i.e., WGS Crypto-Cap). In addition, I use in silico simulations and in vitro tests to examine the ability of these baits to obtain Cryptosporidium genome sequences from host-associated clinical samples. Lastly, in the fifth chapter I summarize the key findings from each study and provide further information on how each of these techniques could be applied microbial public health issues.