In the previous chapters we have considered the ‘nuts and bolts’ of epidemiology. In this and the next few chapters we look at how epidemiology is used in practice to improve public health. We start with ‘surveillance’ because without timely information on emerging and changing health problems, public health action can be paralysed or, at best, inefficient. In this chapter we discuss the design and use of surveillance systems that enable health officials to detect new risks and diseases such as mpox promptly, track known diseases and health problems, and generate data needed for effective health planning and resource allocation.

Once the theory is specified and an operationalization has been chosen for the nodes and links, the next step is to acquire the data. This chapter goes deep into issues that arise when designing surveys to collect data. Although this is not the only method of data collection, it is one that illuminates issues that pertain to all others. This chapter covers the practical question of how to use surveys to elicit network information. The advice leans heavily on a well-formulated theory.

This chapter describes lab verification and clinical validation of tests for the detection of SARS-CoV-2. As new SARS-CoV-2 tests were being developed early in the pandemic, extensive lab verification studies to “test the tests” were conducted at ACME POCT at Emory University. Initial testing was performed in a Biosafety Level 3 facility to determine if the assays could detect propagated SARS-CoV-2 in ideal conditions and evaluate the specificity of these tests. We then describe the establishment of a Biorepository to bank SARS-CoV-2 variant samples and use these samples to determine whether tests could detect new variants with equal sensitivity as the original wild-type virus. This chapter also describes the clinical validation of tests using samples collected from individuals at testing centers. The clinical validation core requires careful planning for staffing and personnel training, semi-permanent and mobile clinical sites, defining inclusion and exclusion parameters, and data collection and reporting. Our experience demonstrated the importance of developing strong relationships with academic and private partners to facilitate clinical site setup, marketing, and purchasing.

Chapter 3 shows why the contracts model doesn’t work: consent is absent in the information economy. Privacy harm can’t be seen as a risk that people accept in exchange for a service. Inferences, relational data, and de-identified data aren’t captured by consent provisions. Consent is unattainable in the information economy more broadly because the dynamic between corporations and users is plagued with uneven knowledge, inequality, and a lack of choices. Data harms are collective and unknowable, making individual choices to reduce them impossible. Worse, privacy has a moral hazard problem: corporations have incentives to behave against our best interests, creating profitable harms after obtaining agreements. Privacy’s moral hazard leads to informational exploitation. One manifestation of valid consent in the information economy are consent refusals. We can consider them by thinking of people’s data as part of them, as their bodies are.

This chapter describes the process of creating and annotating a corpus. This process involves, for instance, collecting data (speech and writing), transcribing recorded speech, and adding annotation, markup indicating in a conversation, for instance, when one person’s speech overlaps another speaker. While written texts are relatively easy to collect – most writing is readily available in digital formats – speech, especially spontaneous conversations, has to be transcribed, though voice recognition software has made progress in automating the transcription of certain kinds of speech, such as monologues. Other stages of building a corpus are also discussed, ranging from the administrative (keeping records of texts collected) to transcribing recordings of speech. The chapter concludes with a description of various kinds of textual markup and linguistic annotation that can be added to texts. Topics discussed include how to create a “header” for a particular text. Headers contain various kinds of information. For written texts, the header would include, for instance, the title of the text; the author(s); if published, where it was published. Other textual markup is internal to the text, and in a spoken text would include such information as speaker IDs, and the beginnings and ends of overlapping speech.

The chapter outlines social media and qualitative research. It describes social media for data collection and different qualitative research approaches to data collection. The chapter describes social media as a phenomenon for research and outlines different levels of social media utilization: individual, work-practice and supra-organizational levels. Vignettes for the different levels are provided and the need for qualitative research concluded.

A strong participant recruitment plan is a major determinant of the success of human subjects research. The plan adopted by researchers will determine the kinds of inferences that follow from the collected data and how much it will cost to collect. Research studies with weak or non-existent recruitment plans risk recruiting too few participants or the wrong kind of participants to be able to answer the question that motivated them. This chapter outlines key considerations for researchers who are developing recruitment plans and provides suggestions for how to make recruiting more efficient.

The chapter ’Going on Pawtrol’ describes how to conduct linguistic research using the cat examples from the original research done for this book. It looks at methodological issues, like research design, research methods, sampling methods, data collection, wordlists, and surveys. The chapter also discusses ethics in relation to the protection of research participants and the research, touching on the laws in place to protect people’s privacy and data and the ethical guidelines established for researchers.

In this chapter, we discuss and illustrate the tools of evaluating partnership work as part of a continuous improvement that you will need to make when building partnerships. As you engage with the chapter, you will learn what evaluation is and how to use evaluation to ensure that partnerships work for the benefit of children and their families. Throughout the chapter, we will explore different methods for collecting data and analysis, including various strategies that will inform the improvement and change necessary for good work in partnership-building.